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Bibliography on: Ecological Informatics

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ESP: PubMed Auto Bibliography 25 Sep 2022 at 01:50 Created: 

Ecological Informatics

Wikipedia: Ecological Informatics Ecoinformatics, or ecological informatics, is the science of information (Informatics) in Ecology and Environmental science. It integrates environmental and information sciences to define entities and natural processes with language common to both humans and computers. However, this is a rapidly developing area in ecology and there are alternative perspectives on what constitutes ecoinformatics. A few definitions have been circulating, mostly centered on the creation of tools to access and analyze natural system data. However, the scope and aims of ecoinformatics are certainly broader than the development of metadata standards to be used in documenting datasets. Ecoinformatics aims to facilitate environmental research and management by developing ways to access, integrate databases of environmental information, and develop new algorithms enabling different environmental datasets to be combined to test ecological hypotheses. Ecoinformatics characterize the semantics of natural system knowledge. For this reason, much of today's ecoinformatics research relates to the branch of computer science known as Knowledge representation, and active ecoinformatics projects are developing links to activities such as the Semantic Web. Current initiatives to effectively manage, share, and reuse ecological data are indicative of the increasing importance of fields like Ecoinformatics to develop the foundations for effectively managing ecological information. Examples of these initiatives are National Science Foundation Datanet projects, DataONE and Data Conservancy.

Created with PubMed® Query: "ecology OR ecological" and ("data management" or informatics) NOT "assays for monitoring autophagy" NOT pmcbook NOT ispreviousversion

Citations The Papers (from PubMed®)

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RevDate: 2022-09-23

Zhang L, Chen L, Yu XA, et al (2022)

MicrobiomeCensus estimates human population sizes from wastewater samples based on inter-individual variability in gut microbiomes.

PLoS computational biology, 18(9):e1010472 pii:PCOMPBIOL-D-22-00130 [Epub ahead of print].

The metagenome embedded in urban sewage is an attractive new data source to understand urban ecology and assess human health status at scales beyond a single host. Analyzing the viral fraction of wastewater in the ongoing COVID-19 pandemic has shown the potential of wastewater as aggregated samples for early detection, prevalence monitoring, and variant identification of human diseases in large populations. However, using census-based population size instead of real-time population estimates can mislead the interpretation of data acquired from sewage, hindering assessment of representativeness, inference of prevalence, or comparisons of taxa across sites. Here, we show that taxon abundance and sub-species diversisty in gut-associated microbiomes are new feature space to utilize for human population estimation. Using a population-scale human gut microbiome sample of over 1,100 people, we found that taxon-abundance distributions of gut-associated multi-person microbiomes exhibited generalizable relationships with respect to human population size. Here and throughout this paper, the human population size is essentially the sample size from the wastewater sample. We present a new algorithm, MicrobiomeCensus, for estimating human population size from sewage samples. MicrobiomeCensus harnesses the inter-individual variability in human gut microbiomes and performs maximum likelihood estimation based on simultaneous deviation of multiple taxa's relative abundances from their population means. MicrobiomeCensus outperformed generic algorithms in data-driven simulation benchmarks and detected population size differences in field data. New theorems are provided to justify our approach. This research provides a mathematical framework for inferring population sizes in real time from sewage samples, paving the way for more accurate ecological and public health studies utilizing the sewage metagenome.

RevDate: 2022-09-23

Botella C, Bonnet P, Hui C, et al (2022)

Dynamic Species Distribution Modeling Reveals the Pivotal Role of Human-Mediated Long-Distance Dispersal in Plant Invasion.

Biology, 11(9): pii:biology11091293.

Plant invasions generate massive ecological and economic costs worldwide. Predicting their spatial dynamics is crucial to the design of effective management strategies and the prevention of invasions. Earlier studies highlighted the crucial role of long-distance dispersal in explaining the speed of many invasions. In addition, invasion speed depends highly on the duration of its lag phase, which may depend on the scaling of fecundity with age, especially for woody plants, even though empirical proof is still rare. Bayesian dynamic species distribution models enable the fitting of process-based models to partial and heterogeneous observations using a state-space modeling approach, thus offering a tool to test such hypotheses on past invasions over large spatial scales. We use such a model to explore the roles of long-distance dispersal and age-structured fecundity in the transient invasion dynamics of Plectranthus barbatus, a woody plant invader in South Africa. Our lattice-based model accounts for both short and human-mediated long-distance dispersal, as well as age-structured fecundity. We fitted our model on opportunistic occurrences, accounting for the spatio-temporal variations of the sampling effort and the variable detection rates across datasets. The Bayesian framework enables us to integrate a priori knowledge on demographic parameters and control identifiability issues. The model revealed a massive wave of spatial spread driven by human-mediated long-distance dispersal during the first decade and a subsequent drastic population growth, leading to a global equilibrium in the mid-1990s. Without long-distance dispersal, the maximum population would have been equivalent to 30% of the current equilibrium population. We further identified the reproductive maturity at three years old, which contributed to the lag phase before the final wave of population growth. Our results highlighted the importance of the early eradication of weedy horticultural alien plants around urban areas to hamper and delay the invasive spread.

RevDate: 2022-09-17

Ma X, Zhu X, Xie Q, et al (2022)

Monitoring nature's calendar from space: emerging topics in land surface phenology and associated opportunities for science applications.

Global change biology [Epub ahead of print].

Vegetation phenology has been viewed as the nature's calendar and an integrative indicator of plant-climate interactions. The correct representation of vegetation phenology is important for models to accurately simulate the exchange of carbon, water, and energy between the vegetated land surface and the atmosphere. Remote sensing has advanced the monitoring of vegetation phenology by providing spatially and temporally continuous data that in together with conventional ground observations offering a unique contribution to our knowledge about environmental impact on ecosystems as well as the ecological adaptations and feedback to global climate change. Land surface phenology is defined as the use of satellites to monitor seasonal dynamics in vegetated land surfaces and to estimate phenological transition dates. Land surface phenology, as an interdisciplinary subject among remote sensing, ecology and biometeorology, has undergone rapid development over the past few decades. Recent advances in sensor technologies, as well as data fusion techniques, have enabled novel phenology retrieval algorithms that refine phenology details at even higher spatiotemporal resolutions, providing new insights into ecosystem dynamics. As such, here we summarize the recent advances in land surface phenology and the associated opportunities for science applications. We focus on the remaining challenges, promising techniques, and emerging topics that together we believe will truly form the very frontier of global land surface phenology research field.

RevDate: 2022-09-17
CmpDate: 2022-09-16

Nam S, Jeon S, Lee SJ, et al (2022)

Real-time racial discrimination, affective states, salivary cortisol and alpha-amylase in Black adults.

PloS one, 17(9):e0273081.

Perceived racial discrimination has been associated with the autonomic nervous system (ANS) and hypothalamic-pituitary-adrenal (HPA) axis activities-two major stress response systems. To date, most studies have used cross-sectional data that captured retrospective measures of the racial discrimination associated with current physiological stress responses. The purpose of this study was to examine the relationship between racial discrimination measured in real-time and physiological stress responses. Twelve healthy Black adults completed baseline surveys and self-collected saliva samples 4x/day for 4 days to measure cortisol and alpha amylase (AA) as a proxy of HPA and ANS systems, respectively. Real-time racial discrimination was measured using ecological momentary assessments (EMA) sent to participants 5x/day for 7 days. Multilevel models were conducted to examine the relationship between racial discrimination and stress responses. In multilevel models, the previous day's racial discrimination was significantly associated with the next day's cortisol level at wakening (β = 0.81, partial r = 0.74, p<0.01) and diurnal slope (β = -0.85, partial r = -0.73, p<0.01). Also, microaggressions were significantly associated with the diurnal cortisol slope in the same day, indicating that on the day when people reported more microaggressions than usual, a flatter diurnal slope of cortisol was observed (β = -0.50, partial r = -0.64, p<0.01). The concurrent use of salivary biomarkers and EMA was feasible methods to examine the temporal relationship between racial discrimination and physiological stress responses. The within-person approach may help us understand the concurrent or lagged effects of racial discrimination on the stress responses. Further studies are needed to confirm the observed findings with a large sample size and to improve stress related health outcomes in racial/ethnic minorities.

RevDate: 2022-09-12
CmpDate: 2022-09-12

Cao X, Chen W, Ge X, et al (2022)

Multidimensional soil salinity data mining and evaluation from different satellites.

The Science of the total environment, 846:157416.

Soil salinization, a common land degradation mode, restricts the ecological environment and is a global issue due to climate change. Accurately, quickly and effectively monitoring soil salinity is critical for governmental institutions that develop hazard prevention and mitigation strategies. Remote sensing (RS) technology provides a viable alternative to traditional field work due to its large area coverage, abundant spectral information and nearly constant observations. Key issues in RS-based soil salinity monitoring include the lack of both data-mining techniques for obtaining spectral band information and comprehensive considerations of synergies among different spectra. The main objective of this study was to provide in-depth explorations of data mining and integration algorithms from different satellites to multidimensionally evaluate soil salinity models. The Ebinur Lake Wetland Reserve (Xinjiang Province, China) was selected as a case study. First, ground-measured visible and near infrared (VIS-NIR) spectral data were combined with the RS band to simulate Landsat 8 (L8) and Sentinel 2 (S2) and 3 (S3) data. Second, one-dimensional RS bands and 15 soil salinity and vegetation indices were selected, and 15 spectral data transformations (reciprocal, differential, absorbance, etc.) were obtained. Two- and three-dimensional spectral indices were constructed, and the response relationships between different spectral indices and soil electrical conductivity (EC) were comprehensively explored. Finally, an integrated multidimensional algorithm was used to estimate soil salinity in high-performance models for the three satellites. The results showed that all data-mining-based model combinations performed well for all satellites (R2 > 0.80). However, with multidimensional model combinations, S3 presented the highest predictive capability (R2 = 0.89, RMSE = 2.57 mS·cm-1, RPD = 2.05), followed by S2 (R2 = 0.86, RMSE = 2.71 mS·cm-1, RPD = 1.90) and L8 (R2 = 0.85, RMSE = 2.84 mS·cm-1, RPD = 1.87). Therefore, data mining with integration algorithms in model combinations performs significantly better than previous models and could be considered a promising method for obtaining improved results from soil salinity susceptibility models in similar cases.

RevDate: 2022-08-25

Wang Y, Cai G, Yang L, et al (2022)

Monitoring of urban ecological environment including air quality using satellite imagery.

PloS one, 17(8):e0266759 pii:PONE-D-22-08585.

Rapid urbanisation has highlighted problems in the urban ecological environment and stimulated research on the evaluation of urban environments. In previous studies, key factors such as greenness, wetness, and temperature were extracted from satellite images to assess the urban ecological environment. Although air pollution has become increasingly serious as urbanisation proceeds, information on air pollution is not included in existing models. The Sentinel-5P satellite launched by the European Space Agency in 2017 is a reliable data source for monitoring air quality. By making full use of images from Landsat 8, Sentinel-2A, and Sentinel-5P, this work attempts to construct a new remote sensing monitoring index for urban ecology by adding air quality information to the existing remote sensing ecological index. The proposed index was tested in the Beijing metropolitan area using satellite data from 2020. The results obtained using the proposed index differ greatly in the central urban region and near large bodies of water from those obtained using the existing remote sensing monitoring model, indicating that air quality plays a significant role in evaluating the urban ecological environment. Because the model constructed in this study integrates information on vegetation, soil, humidity, heat, and air quality, it can comprehensively and objectively reflect the quality of the urban ecological environment. Consequently, the proposed remote sensing index provides a new approach to effectively monitoring the urban ecological environment.

RevDate: 2022-08-24

Waterhouse RM, Adam-Blondon AF, Agosti D, et al (2021)

Recommendations for connecting molecular sequence and biodiversity research infrastructures through ELIXIR.

F1000Research, 10:.

Threats to global biodiversity are increasingly recognised by scientists and the public as a critical challenge. Molecular sequencing technologies offer means to catalogue, explore, and monitor the richness and biogeography of life on Earth. However, exploiting their full potential requires tools that connect biodiversity infrastructures and resources. As a research infrastructure developing services and technical solutions that help integrate and coordinate life science resources across Europe, ELIXIR is a key player. To identify opportunities, highlight priorities, and aid strategic thinking, here we survey approaches by which molecular technologies help inform understanding of biodiversity. We detail example use cases to highlight how DNA sequencing is: resolving taxonomic issues; Increasing knowledge of marine biodiversity; helping understand how agriculture and biodiversity are critically linked; and playing an essential role in ecological studies. Together with examples of national biodiversity programmes, the use cases show where progress is being made but also highlight common challenges and opportunities for future enhancement of underlying technologies and services that connect molecular and wider biodiversity domains. Based on emerging themes, we propose key recommendations to guide future funding for biodiversity research: biodiversity and bioinformatic infrastructures need to collaborate closely and strategically; taxonomic efforts need to be aligned and harmonised across domains; metadata needs to be standardised and common data management approaches widely adopted; current approaches need to be scaled up dramatically to address the anticipated explosion of molecular data; bioinformatics support for biodiversity research needs to be enabled and sustained; training for end users of biodiversity research infrastructures needs to be prioritised; and community initiatives need to be proactive and focused on enabling solutions. For sequencing data to deliver their full potential they must be connected to knowledge: together, molecular sequence data collection initiatives and biodiversity research infrastructures can advance global efforts to prevent further decline of Earth's biodiversity.

RevDate: 2022-08-16

Ramírez-Castañeda V, Westeen EP, Frederick J, et al (2022)

A set of principles and practical suggestions for equitable fieldwork in biology.

Proceedings of the National Academy of Sciences of the United States of America, 119(34):e2122667119.

Field biology is an area of research that involves working directly with living organisms in situ through a practice known as "fieldwork." Conducting fieldwork often requires complex logistical planning within multiregional or multinational teams, interacting with local communities at field sites, and collaborative research led by one or a few of the core team members. However, existing power imbalances stemming from geopolitical history, discrimination, and professional position, among other factors, perpetuate inequities when conducting these research endeavors. After reflecting on our own research programs, we propose four general principles to guide equitable, inclusive, ethical, and safe practices in field biology: be collaborative, be respectful, be legal, and be safe. Although many biologists already structure their field programs around these principles or similar values, executing equitable research practices can prove challenging and requires careful consideration, especially by those in positions with relatively greater privilege. Based on experiences and input from a diverse group of global collaborators, we provide suggestions for action-oriented approaches to make field biology more equitable, with particular attention to how those with greater privilege can contribute. While we acknowledge that not all suggestions will be applicable to every institution or program, we hope that they will generate discussions and provide a baseline for training in proactive, equitable fieldwork practices.

RevDate: 2022-08-16
CmpDate: 2022-08-16

Hossain Bhuiyan MA, Chandra Karmaker S, BB Saha (2022)

Nexus between potentially toxic elements' accumulation and seasonal/anthropogenic influences on mangrove sediments and ecological risk in Sundarbans, Bangladesh: An approach from GIS, self-organizing map, conditional inference tree and random forest models.

Environmental pollution (Barking, Essex : 1987), 309:119765.

Mangroves play a vital role in protecting the coastal community from the climate change effect and in the restoration of the coastal ecosystem. This research has been designed to determine the spatial and seasonal changes of potentially toxic elements' (PTEs) concentration in sediments and their potential source contribution among the different human-driven processes in Sundarbans, Bangladesh. Different pollution evaluation indices, random forest (RF) model, conditional inference tree (CIT), self-organizing map (SOM), geographical information system (GIS), and principal component analysis (PCA) were used for the interpretation of sources and risk assessment of PTEs. The mean concentration of PTEs both in winter and monsoon seasons has fallen below the threshold effect level but exceeded the rare effect level of marine sediments quality standards. Results showed that the PTEs were significantly enriched (EF > 1.00 < 70.00) in sediments, whereas the Cd enrichment (7.00% samples) was very alarming (EF = 60-70). Except for Zn and Cd, other PTEs were enriched in 30-60% samples. The highest geoaccumulation and contamination factors for Cd were observed in 46-72% of samples. The ecological risk (ER) factors showed similar results where Cd showed strong to very strong factors (ER = 110-2218) in 80% of samples. The CIT explained the natural/geogenic and anthropogenic sources of pollution, where the higher CIT values for Cd indicated industrial, aquaculture, and coal-based thermal powerplant. The RF model provided that shrimp firms, power plants, industry, and seaport were recognized as the influential sources for Zn, Pb, Cr, Cd, and As in sediments. Though Pb and As were found as the most significant pollutants, Cd was identified as a severe threat to ecology and public health. Based on CIT, RF, SOM and PCA the order of PTEs in mangroves sediment were:industrial/urban > aquaculture/shrimpfirm > powerplant > seaportoperation > tourism > geogenic/natural. The present study will help the policymakers for effective and sustainable management of the mangrove ecosystem.

RevDate: 2022-07-31

Masarovič R, Zvaríková M, Zvarík M, et al (2022)

Changes in Diversity and Structure of Thrips (Thysanoptera) Assemblages in the Spruce Forest Stands of High Tatra Mts. after a Windthrow Calamity.

Insects, 13(8):.

Strong winds, fire, and subsequent forest management impact arthropod communities. We monitored the diversity and changes in the community structure of forest thrips assemblages in the context of secondary succession and anthropogenic impact. There were eight study plots that were affected to varying degrees by the mentioned disturbances that were selected in the Central European spruce (Picea abies (L.) Karst.) forests in Slovakia. The soil photoeclectors were used to obtain thrips in the study plots during two vegetation seasons. The thrips assemblages and their attributes were analyzed by non-metric multidimensional scaling (NMDS). The significant changes in community structure, composition, stratification, species richness, and diversity of thrips assemblages that were caused by natural- (wind) and human-induced disturbance (forestry and fire) were observed in our research. Our analyses revealed a clear relationship between different thrips assemblages and impacted environment. Moreover, our results indicate that silvicolous thrips species may be useful for indicating changes and disturbances in forest ecological systems.

RevDate: 2022-07-24
CmpDate: 2022-07-21

Bledsoe EK, Burant JB, Higino GT, et al (2022)

Data rescue: saving environmental data from extinction.

Proceedings. Biological sciences, 289(1979):20220938.

Historical and long-term environmental datasets are imperative to understanding how natural systems respond to our changing world. Although immensely valuable, these data are at risk of being lost unless actively curated and archived in data repositories. The practice of data rescue, which we define as identifying, preserving, and sharing valuable data and associated metadata at risk of loss, is an important means of ensuring the long-term viability and accessibility of such datasets. Improvements in policies and best practices around data management will hopefully limit future need for data rescue; these changes, however, do not apply retroactively. While rescuing data is not new, the term lacks formal definition, is often conflated with other terms (i.e. data reuse), and lacks general recommendations. Here, we outline seven key guidelines for effective rescue of historically collected and unmanaged datasets. We discuss prioritization of datasets to rescue, forming effective data rescue teams, preparing the data and associated metadata, and archiving and sharing the rescued materials. In an era of rapid environmental change, the best policy solutions will require evidence from both contemporary and historical sources. It is, therefore, imperative that we identify and preserve valuable, at-risk environmental data before they are lost to science.

RevDate: 2022-07-20

Sieben AJ, Mihaljevic JR, LG Shoemaker (2022)

Quantifying mechanisms of coexistence in disease ecology.

Ecology [Epub ahead of print].

Pathogen coexistence depends on ecological processes operating at both within and between-host scales, making it difficult to quantify which processes may promote or prevent coexistence. Here, we propose that adapting modern coexistence theory-traditionally applied in plant communities-to pathogen systems provides an exciting approach for examining mechanisms of coexistence operating across different spatial scales. We first overview modern coexistence theory and its mechanistic decomposition; we subsequently adapt the framework to quantify how spatial variation in pathogen density, host resources and immunity, and their interaction may promote pathogen coexistence. We apply this derivation to an example two pathogen, multi-scale model comparing two scenarios with generalist and strain-specific immunity: one with demographic equivalency among pathogens and one with demographic trade-offs among pathogens. We then show how host-pathogen feedbacks generate spatial heterogeneity that promote pathogen coexistence and decompose those mechanisms to quantify how each spatial heterogeneity contributes to that coexistence. Specifically, coexistence of demographically equivalent pathogens occurs due to spatial variation in host resources, immune responses, and pathogen aggregation. With a competition-colonization trade-off, the superior colonizer requires spatial heterogeneity to coexist, whereas the superior competitor does not. Finally, we suggest ways forward for linking theory and empirical tests of coexistence in disease systems.

RevDate: 2022-07-25

Beninde J, Toffelmier EM, Andreas A, et al (2022)

CaliPopGen: A genetic and life history database for the fauna and flora of California.

Scientific data, 9(1):380.

CaliPopGen is a database of population genetic data for native and naturalized eukaryotic species in California, USA. It summarizes the published literature (1985-2020) for 5,453 unique populations with genetic data from more than 187,394 individuals and 448 species (513 species plus subspecies) across molecular markers including allozymes, RFLPs, mtDNA, microsatellites, nDNA, and SNPs. Terrestrial habitats accounted for the majority (46.4%) of the genetic data. Taxonomic groups with the greatest representation were Magnoliophyta (20.31%), Insecta (13.4%), and Actinopterygii (12.85%). CaliPopGen also reports life-history data for most included species to enable analyses of the drivers of genetic diversity across the state. The large number of populations and wide taxonomic breadth will facilitate explorations of ecological patterns and processes across the varied geography of California. CaliPopGen covers all terrestrial and marine ecoregions of California and has a greater density of species and georeferenced populations than any previously published population genetic database. It is thus uniquely suited to inform conservation management at the regional and state levels across taxonomic groups.

RevDate: 2022-07-16
CmpDate: 2022-07-01

Tietje M, Antonelli A, Baker WJ, et al (2022)

Global variation in diversification rate and species richness are unlinked in plants.

Proceedings of the National Academy of Sciences of the United States of America, 119(27):e2120662119.

Species richness varies immensely around the world. Variation in the rate of diversification (speciation minus extinction) is often hypothesized to explain this pattern, while alternative explanations invoke time or ecological carrying capacities as drivers. Focusing on seed plants, the world's most important engineers of terrestrial ecosystems, we investigated the role of diversification rate as a link between the environment and global species richness patterns. Applying structural equation modeling to a comprehensive distribution dataset and phylogenetic tree covering all circa 332,000 seed plant species and 99.9% of the world's terrestrial surface (excluding Antarctica), we test five broad hypotheses postulating that diversification serves as a mechanistic link between species richness and climate, climatic stability, seasonality, environmental heterogeneity, or the distribution of biomes. Our results show that the global patterns of species richness and diversification rate are entirely independent. Diversification rates were not highest in warm and wet climates, running counter to the Metabolic Theory of Ecology, one of the dominant explanations for global gradients in species richness. Instead, diversification rates were highest in edaphically diverse, dry areas that have experienced climate change during the Neogene. Meanwhile, we confirmed climate and environmental heterogeneity as the main drivers of species richness, but these effects did not involve diversification rates as a mechanistic link, calling for alternative explanations. We conclude that high species richness is likely driven by the antiquity of wet tropical areas (supporting the "tropical conservatism hypothesis") or the high ecological carrying capacity of warm, wet, and/or environmentally heterogeneous environments.

RevDate: 2022-07-16
CmpDate: 2022-06-29

Abrahms B, Rafiq K, Jordan NR, et al (2022)

Long-term, climate-driven phenological shift in a tropical large carnivore.

Proceedings of the National Academy of Sciences of the United States of America, 119(27):e2121667119.

Understanding the degree to which animals are shifting their phenology to track optimal conditions as the climate changes is essential to predicting ecological responses to global change. Species at low latitudes or high trophic levels are theoretically expected to exhibit weaker phenological responses than other species, but limited research on tropical systems or on top predators impedes insight into the contexts in which these predictions are upheld. Moreover, a lack of phenological studies on top predators limits understanding of how climate change impacts propagate through entire ecosystems. Using a 30-y dataset on endangered African wild dogs (Lycaon pictus), we examined changes in reproductive phenology and temperatures during birthing and denning over time, as well as potential fitness consequences of these changes. We hypothesized that their phenology would shift to track a stable thermal range over time. Data from 60 packs and 141 unique pack-years revealed that wild dogs have delayed parturition by 7 days per decade on average in response to long-term warming. This shift has led to temperatures on birthing dates remaining relatively stable but, contrary to expectation, has led to increased temperatures during denning periods. Increased denning temperatures were associated with reduced reproductive success, suggesting that a continued phenological shift in the species may become maladaptive. Such results indicate that climate-driven shifts could be more widespread in upper trophic levels than previously appreciated, and they extend theoretical understanding of the species traits and environmental contexts in which large phenological shifts can be expected to occur as the climate changes.

RevDate: 2022-06-26

Balfour NJ, Castellanos MC, Goulson D, et al (2022)

DoPI: The Database of Pollinator Interactions.

Ecology [Epub ahead of print].

Despite the importance of pollinating insects to natural environments and agriculture, there have been few attempts to unite the existing plant-pollinator interaction datasets into a single depository using a common format. Accordingly, we have created one of the world's first online, open-access, and searchable pollinator-plant interaction databases. DoPI (The Database of Pollinator Interactions) was built from a systematic review of the scientific literature and unpublished datasets requested from researchers and organisations. We collated records of interactions between British plant and insect flower-visitor species (or genera), together with associated metadata (date, location, habitat, source publication) where available. The dataset currently (December 2021) contains 101,539 records, detailing over 320,000 interactions. The number of interactions (i.e. the number of times a pairwise species interaction was recorded per occasion) varies considerably among records, averaging 3.6. These include records from 1,888 pollinator species and 1,241 plant species, totalling >17,000 pairwise species interactions. By combining a large volume of information in a single repository, DoPI can be used to answer fundamental ecological questions on the dynamics of pollination interactions in space and time, as well as applied questions in conservation practice. We hope this dynamic database will be a useful tool not only for researchers, but also for conservationists, funding agencies, governmental departments, beekeepers, agronomists and gardeners. We request that this paper is cited when using the data in publications and individual studies where appropriate. Researchers and organisations are encouraged to add further data in the future. The database can be accessed at: https://www.dopi.org.uk/.

RevDate: 2022-06-16

Weinstein BG, Garner L, Saccomanno VR, et al (2022)

A general deep learning model for bird detection in high resolution airborne imagery.

Ecological applications : a publication of the Ecological Society of America [Epub ahead of print].

Advances in artificial intelligence for computer vision hold great promise for increasing the scales at which ecological systems can be studied. The distribution and behavior of individuals is central to ecology, and computer vision using deep neural networks can learn to detect individual objects in imagery. However, developing supervised models for ecological monitoring is challenging because it needs large amounts of human-labeled training data, requires advanced technical expertise and computational infrastructure, and is prone to overfitting. This limits application across space and time. One solution is developing generalized models that can be applied across species and ecosystems. Using over 250,000 annotations from 13 projects from around the world, we develop a general bird detection model that achieves over 65% recall and 50% precision on novel aerial data without any local training despite differences in species, habitat, and imaging methodology. Fine-tuning this model with only 1000 local annotations increase these values to an average of 84% recall and 69% precision by building on the general features learned from other data sources. Retraining from the general model improves local predictions even when moderately large annotation sets are available and makes model training faster and more stable. Our results demonstrate that general models for detecting broad classes of organisms using airborne imagery are achievable. These models can reduce the effort, expertise, and computational resources necessary for automating the detection of individual organisms across large scales, helping to transform the scale of data collection in ecology and the questions that can be addressed.

RevDate: 2022-07-16
CmpDate: 2022-06-17

Chen G, Tang P, H Wang (2022)

Boundary Determination of Lake-Type Wetland Park Based on GIS Multifactor Analysis.

Computational intelligence and neuroscience, 2022:6161491.

One key carrier for wetland resource protection is wetland park, the main form of which includes lake-type wetland park. To determine the management and control boundary of lake-type wetland parks scientifically and reasonably is of great significance to the sustainable protection and utilization of wetland resources. From the perspective of landscape architecture, and landscape ecology, this paper studies the boundary determination of Changdang Lake National Wetland Park (the Park) based on satellite remote sensing information technology and GIS technology and in virtue of Analytic Hierarchy Process (AHP). In this study, 12 subindicators were selected from three levels including visual control, human geography, and ecological control. The weight of each indicator was determined by AHP, and then the influencing factors were transformed into graphic data by using GIS technology. Finally, the Park's boundary was determined by factor superposition analysis based on the weight. The research shows that the newly defined management and control boundary are about 340 sq.km, which effectively integrates the human and natural ecological resources around the lake area, makes the development of the surrounding areas harmonious, ensures the integrity of the lake area ecosystem, and facilitates the sustainable development of wetland resources.

RevDate: 2022-07-25

McDonald PJ, Brown RM, Kraus F, et al (2022)

Cryptic extinction risk in a western Pacific lizard radiation.

Biodiversity and conservation, 31(8-9):2045-2062.

Cryptic ecologies, the Wallacean Shortfall of undocumented species' geographical ranges and the Linnaean Shortfall of undescribed diversity, are all major barriers to conservation assessment. When these factors overlap with drivers of extinction risk, such as insular distributions, the number of threatened species in a region or clade may be underestimated, a situation we term 'cryptic extinction risk'. The genus Lepidodactylus is a diverse radiation of insular and arboreal geckos that occurs across the western Pacific. Previous work on Lepidodactylus showed evidence of evolutionary displacement around continental fringes, suggesting an inherent vulnerability to extinction from factors such as competition and predation. We sought to (1) comprehensively review status and threats, (2) estimate the number of undescribed species, and (3) estimate extinction risk in data deficient and candidate species, in Lepidodactylus. From our updated IUCN Red List assessment, 60% of the 58 recognized species are threatened (n = 15) or Data Deficient (n = 21), which is higher than reported for most other lizard groups. Species from the smaller and isolated Pacific islands are of greatest conservation concern, with most either threatened or Data Deficient, and all particularly vulnerable to invasive species. We estimated 32 undescribed candidate species and linear modelling predicted that an additional 18 species, among these and the data deficient species, are threatened with extinction. Focusing efforts to resolve the taxonomy and conservation status of key taxa, especially on small islands in the Pacific, is a high priority for conserving this remarkably diverse, yet poorly understood, lizard fauna. Our data highlight how cryptic ecologies and cryptic diversity combine and lead to significant underestimation of extinction risk.

Supplementary Information: The online version contains supplementary material available at 10.1007/s10531-022-02412-x.

RevDate: 2022-07-16
CmpDate: 2022-05-30

Mammola S, Pavlek M, Huber BA, et al (2022)

A trait database and updated checklist for European subterranean spiders.

Scientific data, 9(1):236.

Species traits are an essential currency in ecology, evolution, biogeography, and conservation biology. However, trait databases are unavailable for most organisms, especially those living in difficult-to-access habitats such as caves and other subterranean ecosystems. We compiled an expert-curated trait database for subterranean spiders in Europe using both literature data (including grey literature published in many different languages) and direct morphological measurements whenever specimens were available to us. We started by updating the checklist of European subterranean spiders, now including 512 species across 20 families, of which at least 192 have been found uniquely in subterranean habitats. For each of these species, we compiled 64 traits. The trait database encompasses morphological measures, including several traits related to subterranean adaptation, and ecological traits referring to habitat preference, dispersal, and feeding strategies. By making these data freely available, we open up opportunities for exploring different research questions, from the quantification of functional dimensions of subterranean adaptation to the study of spatial patterns in functional diversity across European caves.

RevDate: 2022-07-18
CmpDate: 2022-07-14

Zhao F, Tian S, Wu Q, et al (2022)

Utility of Triti-Map for bulk-segregated mapping of causal genes and regulatory elements in Triticeae.

Plant communications, 3(4):100304.

Triticeae species, including wheat, barley, and rye, are critical for global food security. Mapping agronomically important genes is crucial for elucidating molecular mechanisms and improving crops. However, Triticeae includes many wild relatives with desirable agronomic traits, and frequent introgressions occurred during Triticeae evolution and domestication. Thus, Triticeae genomes are generally large and complex, making the localization of genes or functional elements that control agronomic traits challenging. Here, we developed Triti-Map, which contains a suite of user-friendly computational packages specifically designed and optimized to overcome the obstacles of gene mapping in Triticeae, as well as a web interface integrating multi-omics data from Triticeae for the efficient mining of genes or functional elements that control particular traits. The Triti-Map pipeline accepts both DNA and RNA bulk-segregated sequencing data as well as traditional QTL data as inputs for locating genes and elucidating their functions. We illustrate the usage of Triti-Map with a combination of bulk-segregated ChIP-seq data to detect a wheat disease-resistance gene with its promoter sequence that is absent from the reference genome and clarify its evolutionary process. We hope that Triti-Map will facilitate gene isolation and accelerate Triticeae breeding.

RevDate: 2022-07-16

Tadmor-Levi R, Borovski T, Marcos-Hadad E, et al (2022)

Establishing and using a genetic database for resolving identification of fish species in the Sea of Galilee, Israel.

PloS one, 17(5):e0267021.

Freshwaters are a very valuable resource in arid areas, such as Mediterranean countries. Freshwater systems are vulnerable ecological habitats, significantly disturbed globally and especially in arid areas. The Sea of Galilee is the largest surface freshwater body in the Middle East. It is an isolated habitat supporting unique fish populations, including endemic species and populations on the edge of their distribution range. Using the Sea of Galilee for water supply, fishing and recreation has been placing pressure on these fish populations. Therefore, efficient monitoring and effective actions can make a difference in the conservation of these unique fish populations. To set a baseline and develop molecular tools to do so, in this study, DNA barcoding was used to establish a database of molecular species identification based on sequences of Cytochrome C Oxidase subunit I gene. DNA barcodes for 22 species were obtained and deposited in Barcode of Life Database. Among these, 12 barcodes for 10 species were new to the database and different from those already there. Barcode sequences were queried against the database and similar barcodes from the same and closely related species were obtained. Disagreements between morphological and molecular species identification were identified for five species, which were further studied by phylogenetic and genetic distances analyses. These analyses suggested the Sea of Galilee contained hybrid fish of some species and other species for which the species definition should be reconsidered. Notably, the cyprinid fish defined as Garra rufa, should be considered as Garra jordanica. Taken together, along with data supporting reconsideration of species definition, this study sets the basis for further using molecular tools for monitoring fish populations, understanding their ecology, and effectively managing their conservation in this unique and important habitat and in the region.

RevDate: 2022-07-16

Record S, Jarzyna MA, Hardiman B, et al (2022)

Open data facilitate resilience in science during the COVID-19 pandemic.

Frontiers in ecology and the environment, 20(2):76-77.

RevDate: 2022-06-10
CmpDate: 2022-06-10

Xu N, Zhang Z, Shen Y, et al (2022)

Compare the performance of multiple binary classification models in microbial high-throughput sequencing datasets.

The Science of the total environment, 837:155807.

The development of machine learning and deep learning provided solutions for predicting microbiota response on environmental change based on microbial high-throughput sequencing. However, there were few studies specifically clarifying the performance and practical of two types of binary classification models to find a better algorithm for the microbiota data analysis. Here, for the first time, we evaluated the performance, accuracy and running time of the binary classification models built by three machine learning methods - random forest (RF), support vector machine (SVM), logistic regression (LR), and one deep learning method - back propagation neural network (BPNN). The built models were based on the microbiota datasets that removed low-quality variables and solved the class imbalance problem. Additionally, we optimized the models by tuning. Our study demonstrated that dataset pre-processing was a necessary process for model construction. Among these 4 binary classification models, BPNN and RF were the most suitable methods for constructing microbiota binary classification models. Using these 4 models to predict multiple microbial datasets, BPNN showed the highest accuracy and the most robust performance, while the RF method was ranked second. We also constructed the optimal models by adjusting the epochs of BPNN and the n_estimators of RF for six times. The evaluation related to performances of models provided a road map for the application of artificial intelligence to assess microbial ecology.

RevDate: 2022-05-24
CmpDate: 2022-05-24

Coolen JWP, Vanaverbeke J, Dannheim J, et al (2022)

Generalized changes of benthic communities after construction of wind farms in the southern North Sea.

Journal of environmental management, 315:115173.

Over the last years, the development of offshore renewable energy installations such as offshore wind farms led to an increasing number of man-made structures in marine environments. Since 2009, benthic impact monitoring programs were carried out in wind farms installed in the southern North Sea. We collated and analyzed data sets from three major monitoring programs. Our analysis considered a total of 2849 sampling points converted to a set of biodiversity response metrics. We analyzed biodiversity changes related to the implementation of offshore wind farms and generalized the correlation of these changes with spatial and temporal patterns. Our results demonstrate that depth, season and distance to structure (soft-bottom community) consistently determined diversity indicators and abundance parameters, whereas the age and the country affiliation were significantly related to some but not all indices. The water depth was the most important structuring factor for fouling communities while seasonal effects were driving most of the observed changes in soft-sediment communities. We demonstrate that a meta-analysis can provide an improved level of understanding of ecological patterns on large-scale effects of anthropogenic structures on marine biodiversity, which were not visible in single monitoring studies. We believe that meta-analyses should become an indispensable tool for management of offshore wind farm effects in the future, particularly in the view of the foreseen development of offshore renewable energies. This might lead to a better picture and more comprehensive view on potential alterations. However, this requires a modern open-source data policy and data management, across institutions and across national borders.

RevDate: 2022-05-31
CmpDate: 2022-04-15

Tanalgo KC, Tabora JAG, de Oliveira HFM, et al (2022)

DarkCideS 1.0, a global database for bats in karsts and caves.

Scientific data, 9(1):155.

Understanding biodiversity patterns as well as drivers of population declines, and range losses provides crucial baselines for monitoring and conservation. However, the information needed to evaluate such trends remains unstandardised and sparsely available for many taxonomic groups and habitats, including the cave-dwelling bats and cave ecosystems. We developed the DarkCideS 1.0 (https://darkcides.org/), a global database of bat caves and species synthesised from publicly available information and datasets. The DarkCideS 1.0 is by far the largest database for cave-dwelling bats, which contains information for geographical location, ecological status, species traits, and parasites and hyperparasites for 679 bat species are known to occur in caves or use caves in part of their life histories. The database currently contains 6746 georeferenced occurrences for 402 cave-dwelling bat species from 2002 cave sites in 46 countries and 12 terrestrial biomes. The database has been developed to be collaborative and open-access, allowing continuous data-sharing among the community of bat researchers and conservation biologists to advance bat research and comparative monitoring and prioritisation for conservation.

RevDate: 2022-04-27
CmpDate: 2022-04-27

Pan SF, Ji XH, Xie YH, et al (2022)

Influence of soil properties on cadmium accumulation in vegetables: Thresholds, prediction and pathway models based on big data.

Environmental pollution (Barking, Essex : 1987), 304:119225.

Soil properties, such as soil pH, soil organic matter (SOM), cation exchange capacity (CEC), are the most important factors affecting cadmium (Cd) accumulation in vegetables. In this study, we conducted big data mining of 31,342 soil and vegetable samples to examine the influence of soil properties (soil pH, SOM, CEC, Zn and Mn content) on the accumulation of Cd in root, solanaceous, and leafy vegetables in Hunan Province, China. Specifically, the Cd accumulation capability was in the following order: leafy vegetables > root vegetables > solanaceous vegetables. The soil property thresholds for safety production in vegetables were determined by establishing nonlinear models between Cd bioaccumulation factor (BCF) and the individual soil property, and were 6.5 (pH), 30.0 g/kg (SOM), 13.0 cmol/kg (CEC), 100-140 mg/kg (Zn), and 300-400 mg/kg (Mn). When soil property values were higher than the thresholds, Cd accumulation in vegetables tended to be stable. Prediction models showed that pH and soil Zn were the leading factors influencing Cd accumulation in root vegetables, explaining 87% of the variance; pH, SOM, soil Zn and Mn explained 68% of the variance in solanaceous vegetables; pH and SOM were the main contributors in leafy vegetables, explaining 65% of the variance. Further, variance partitioning analysis (VPA) revealed that the interaction effect of the corresponding key soil properties contributed mostly to BCF. Meanwhile, partial least squares (PLS) path modeling was employed to analyze the path and the interactive effects of soil properties on Cd BCF. pH and SOM were found to be the biggest two players affecting BCF in PLS-models, and the most substantial interactive influence paths of soil properties on BCF were different among the three types of vegetables.

RevDate: 2022-05-31
CmpDate: 2022-04-14

Bolotov IN, Gofarov MY, Koshkin ES, et al (2022)

A nearly complete database on the records and ecology of the rarest boreal tiger moth from 1840s to 2020.

Scientific data, 9(1):107.

Global environmental changes may cause dramatic insect declines but over century-long time series of certain species' records are rarely available for scientific research. The Menetries' Tiger Moth (Arctia menetriesii) appears to be the most enigmatic example among boreal insects. Although it occurs throughout the entire Eurasian taiga biome, it is so rare that less than 100 specimens were recorded since its original description in 1846. Here, we present the database, which contains nearly all available information on the species' records collected from 1840s to 2020. The data on A. menetriesii records (N = 78) through geographic regions, environments, and different timeframes are compiled and unified. The database may serve as the basis for a wide array of future research such as the distribution modeling and predictions of range shifts under climate changes. It represents a unique example of a more than century-long dataset of distributional, ecological, and phenological data designed for an exceptionally rare but widespread boreal insect, which primarily occurs in hard-to-reach, uninhabited areas of Eurasia.

RevDate: 2022-07-16

Kollath DR, Mihaljevic JR, BM Barker (2022)

PM10 and Other Climatic Variables Are Important Predictors of Seasonal Variability of Coccidioidomycosis in Arizona.

Microbiology spectrum, 10(2):e0148321.

Coccidioidomycosis (Valley fever) is a disease caused by the fungal pathogens Coccidioides immitis and Coccidioides posadasii that are endemic to the southwestern United States and parts of Mexico and South America. Throughout the range where the pathogens are endemic, there are seasonal patterns of infection rates that are associated with certain climatic variables. Previous studies that looked at annual and monthly relationships of coccidioidomycosis and climate suggest that infection numbers are linked with precipitation and temperature fluctuations; however, these analytic methods may miss important nonlinear, nonmonotonic seasonal relationships between the response (Valley fever cases) and explanatory variables (climate) influencing disease outbreaks. To improve our current knowledge and to retest relationships, we used case data from three counties of high endemicity in southern Arizona paired with climate data to construct a generalized additive statistical model that explores which meteorological parameters are most useful in predicting Valley fever incidence throughout the year. We then use our model to forecast the pattern of Valley fever cases by month. Our model shows that maximum monthly temperature, average PM10, and total precipitation 1 month prior to reported cases (lagged model) were all significant in predicting Valley fever cases. Our model fits Valley fever case data in the region of endemicity of southern Arizona and captures the seasonal relationships that predict when the public is at higher risk of being infected. This study builds on and retests relationships described by previous studies regarding climate variables that are important for predicting risk of infection and understanding this fungal pathogen. IMPORTANCE The inhalation of environmental infectious propagules from the fungal pathogens Coccidioides immitis and Coccidioides posadasii by susceptible mammals can result in coccidioidomycosis (Valley fever). Arizona is known to be a region where the pathogen is hyperendemic, and reported cases are increasing throughout the western United States. Coccidioides spp. are naturally occurring fungi in arid soils. Little is known about ecological factors that influence the growth of these fungi, and a higher environmental burden may result in increases in human exposure and therefore case rates. By examining case and climate data from Arizona and using generalized additive statistical models, we were able to examine the relationship between disease outbreaks and climatic variables and predict seasonal time points of increased infection risk.

RevDate: 2022-05-25
CmpDate: 2022-05-25

Olker JH, Elonen CM, Pilli A, et al (2022)

The ECOTOXicology Knowledgebase: A Curated Database of Ecologically Relevant Toxicity Tests to Support Environmental Research and Risk Assessment.

Environmental toxicology and chemistry, 41(6):1520-1539.

The need for assembled existing and new toxicity data has accelerated as the amount of chemicals introduced into commerce continues to grow and regulatory mandates require safety assessments for a greater number of chemicals. To address this evolving need, the ECOTOXicology Knowledgebase (ECOTOX) was developed starting in the 1980s and is currently the world's largest compilation of curated ecotoxicity data, providing support for assessments of chemical safety and ecological research through systematic and transparent literature review procedures. The recently released version of ECOTOX (Ver 5, www.epa.gov/ecotox) provides single-chemical ecotoxicity data for over 12,000 chemicals and ecological species with over one million test results from over 50,000 references. Presented is an overview of ECOTOX, detailing the literature review and data curation processes within the context of current systematic review practices and discussing how recent updates improve the accessibility and reusability of data to support the assessment, management, and research of environmental chemicals. Relevant and acceptable toxicity results are identified from studies in the scientific literature, with pertinent methodological details and results extracted following well-established controlled vocabularies and newly extracted toxicity data added quarterly to the public website. Release of ECOTOX, Ver 5, included an entirely redesigned user interface with enhanced data queries and retrieval options, visualizations to aid in data exploration, customizable outputs for export and use in external applications, and interoperability with chemical and toxicity databases and tools. This is a reliable source of curated ecological toxicity data for chemical assessments and research and continues to evolve with accessible and transparent state-of-the-art practices in literature data curation and increased interoperability to other relevant resources. Environ Toxicol Chem 2022;41:1520-1539. © 2022 SETAC. This article has been contributed to by US Government employees and their work is in the public domain in the USA.

RevDate: 2022-05-02

Marqués L, Peltier DMP, Camarero JJ, et al (2022)

Disentangling the Legacies of Climate and Management on Tree Growth.

Ecosystems (New York, N.Y.), 25(1):215-235.

Legacies of past climate conditions and historical management govern forest productivity and tree growth. Understanding how these processes interact and the timescales over which they influence tree growth is critical to assess forest vulnerability to climate change. Yet, few studies address this issue, likely because integrated long-term records of both growth and forest management are uncommon. We applied the stochastic antecedent modelling (SAM) framework to annual tree-ring widths from mixed forests to recover the ecological memory of tree growth. We quantified the effects of antecedent temperature and precipitation up to 4 years preceding the year of ring formation and integrated management effects with records of harvesting intensity from historical forest management archives. The SAM approach uncovered important time periods most influential to growth, typically the warmer and drier months or seasons, but variation among species and sites emerged. Silver fir responded primarily to past climate conditions (25-50 months prior to the year of ring formation), while European beech and Scots pine responded mostly to climate conditions during the year of ring formation and the previous year, although these responses varied among sites. Past management and climate interacted in such a way that harvesting promoted growth in young silver fir under wet and warm conditions and in old European beech under drier and cooler conditions. Our study shows that the ecological memory associated with climate legacies and historical forest management is species-specific and context-dependent, suggesting that both aspects are needed to properly evaluate forest functioning under climate change.

SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10021-021-00650-8.

RevDate: 2022-05-09
CmpDate: 2022-04-14

Choo SW, Chong JL, Gaubert P, et al (2022)

A collective statement in support of saving pangolins.

The Science of the total environment, 824:153666.

RevDate: 2022-03-03
CmpDate: 2022-03-03

Nathan R, Monk CT, Arlinghaus R, et al (2022)

Big-data approaches lead to an increased understanding of the ecology of animal movement.

Science (New York, N.Y.), 375(6582):eabg1780.

Understanding animal movement is essential to elucidate how animals interact, survive, and thrive in a changing world. Recent technological advances in data collection and management have transformed our understanding of animal "movement ecology" (the integrated study of organismal movement), creating a big-data discipline that benefits from rapid, cost-effective generation of large amounts of data on movements of animals in the wild. These high-throughput wildlife tracking systems now allow more thorough investigation of variation among individuals and species across space and time, the nature of biological interactions, and behavioral responses to the environment. Movement ecology is rapidly expanding scientific frontiers through large interdisciplinary and collaborative frameworks, providing improved opportunities for conservation and insights into the movements of wild animals, and their causes and consequences.

RevDate: 2022-04-14
CmpDate: 2022-04-14

Wang W, Tian P, Zhang J, et al (2022)

Big data-based urban greenness in Chinese megalopolises and possible contribution to air quality control.

The Science of the total environment, 824:153834.

Urban greenness is essential for people's daily lives, while its contribution to air quality control is unclear. In this study, Streetview big data of urban greenness and air quality data (Air Quality Index, PM2.5, PM10, SO2, NO2, O3, CO) from 206 monitoring stations from 27 provincial capital cities in China were analyzed. The national averages for the sky, ground and middle-level (shrub and short trees) view greenness were 5.4%, 5.5%, and 15.4%, respectively, and the sky:ground:middle ratio was 2:2:6. Street-view/bird-view greenness ratio averaged at 1.1. Large inter-city variations were observed in all the greenness parameters, and the weak associations between all street-view parameters and bird-eye greenspace percentage (21%-73%) indicate their representatives of different aspects of green infrastructures. All air quality parameters were higher in winter than in summer, except O3. Over 90% of air quality variation could be explained by socioeconomics and geoclimates, suggesting that air quality control in China should first reduce efflux from social economics, while geoclimatic-oriented ventilation facilitation design is also critical. For different air quality components, greenness had most significant associations with NO2, O3 and CO, and street-view/bird-view ratio was the most powerful indicator of all greenness parameters. Pooled-data analysis at national level showed that street-view greenness was responsible for 2.3% of the air quality variations in the summer and 3.6% in the winter; however, when separated into different regions (North-South China; East-West China), the explaining power increased up to 16.2%. Increased NO2 was accompanied with decreased O3, indicating NO titration effect. The higher O3 aligned with the higher street-view greenness, showing the greenness-related precursor risk for O3 pollution. Our study manifested that big internet data could identify the association of greenness and air pollution from street view scale, which can favor urban greenness management and evaluation in other regions where street-view data are available.

RevDate: 2022-02-16
CmpDate: 2022-02-16

Xu Y, Wang X, Cui G, et al (2022)

Source apportionment and ecological and health risk mapping of soil heavy metals based on PMF, SOM, and GIS methods in Hulan River Watershed, Northeastern China.

Environmental monitoring and assessment, 194(3):181.

Heavy metals in agricultural soils not only affect the food security and soil security, but also endanger the human health through the food chain. Based on the incorporation of index analysis, positive matrix factorization (PMF), self-organizing map (SOM), and geostatistical methods, this research performed the assessment of source apportionment and ecological and health risks of soil heavy metals in Hulan River Watershed, Northeastern China. According to the Pollution Load Index (PLI), 83.08% of the soil samples were slightly or mildly polluted, and 1.54% of the soil samples were severely polluted. The ecological risk index (EI) showed that about 80.77% and 60.77% of the soil samples were beyond the low risk level for Hg and Cd, respectively. In this research, the non-carcinogenic and carcinogenic risk indices for children were higher than adult males and adult females. Four potential sources were revealed based on the PMF and SOM analysis including atmospheric deposition and industrial emission; transportation source; agricultural source; and a combination of agricultural, industrial, and natural sources. Considerable and high ecological risk from Hg existed in the area close to the coal steam-electric plant, and considerable and high ecological risk from Cd existed in the Hulan River estuary area. The eastern part of the study area experienced higher non-carcinogenic and carcinogenic risks for adults and children than the western part of the study area. The source apportionment and ecological and health risk mapping provide important role in reducing pollution sources. Zonal pollution control and soil restoration measures should be performed in the areas with high ecological and health risks.

RevDate: 2022-02-24
CmpDate: 2022-02-24

Engelstad P, Jarnevich CS, Hogan T, et al (2022)

INHABIT: A web-based decision support tool for invasive plant species habitat visualization and assessment across the contiguous United States.

PloS one, 17(2):e0263056.

Narrowing the communication and knowledge gap between producers and users of scientific data is a longstanding problem in ecological conservation and land management. Decision support tools (DSTs), including websites or interactive web applications, provide platforms that can help bridge this gap. DSTs can most effectively disseminate and translate research results when producers and users collaboratively and iteratively design content and features. One data resource seldom incorporated into DSTs are species distribution models (SDMs), which can produce spatial predictions of habitat suitability. Outputs from SDMs can inform management decisions, but their complexity and inaccessibility can limit their use by resource managers or policy makers. To overcome these limitations, we present the Invasive Species Habitat Tool (INHABIT), a novel, web-based DST built with R Shiny to display spatial predictions and tabular summaries of habitat suitability from SDMs for invasive plants across the contiguous United States. INHABIT provides actionable science to support the prevention and management of invasive species. Two case studies demonstrate the important role of end user feedback in confirming INHABIT's credibility, utility, and relevance.

RevDate: 2022-07-31
CmpDate: 2022-04-04

Shin YJ, Midgley GF, Archer ERM, et al (2022)

Actions to halt biodiversity loss generally benefit the climate.

Global change biology, 28(9):2846-2874.

The two most urgent and interlinked environmental challenges humanity faces are climate change and biodiversity loss. We are entering a pivotal decade for both the international biodiversity and climate change agendas with the sharpening of ambitious strategies and targets by the Convention on Biological Diversity and the United Nations Framework Convention on Climate Change. Within their respective Conventions, the biodiversity and climate interlinked challenges have largely been addressed separately. There is evidence that conservation actions that halt, slow or reverse biodiversity loss can simultaneously slow anthropogenic mediated climate change significantly. This review highlights conservation actions which have the largest potential for mitigation of climate change. We note that conservation actions have mainly synergistic benefits and few antagonistic trade-offs with climate change mitigation. Specifically, we identify direct co-benefits in 14 out of the 21 action targets of the draft post-2020 global biodiversity framework of the Convention on Biological Diversity, notwithstanding the many indirect links that can also support both biodiversity conservation and climate change mitigation. These relationships are context and scale-dependent; therefore, we showcase examples of local biodiversity conservation actions that can be incentivized, guided and prioritized by global objectives and targets. The close interlinkages between biodiversity, climate change mitigation, other nature's contributions to people and good quality of life are seldom as integrated as they should be in management and policy. This review aims to re-emphasize the vital relationships between biodiversity conservation actions and climate change mitigation in a timely manner, in support to major Conferences of Parties that are about to negotiate strategic frameworks and international goals for the decades to come.

RevDate: 2022-05-23
CmpDate: 2022-05-23

Yuan Q, Wu H, Zhao Y, et al (2022)

Ecosystem health of the Beiyun River basin (Beijing, China) as evaluated by the method of combination of AHP and PCA.

Environmental science and pollution research international, 29(26):39116-39130.

Ecosystem services provided by river ecosystems rely on healthy ecosystem structure and ecological processes. The Beijing-Tianjin-Hebei urban is a typical water-deficient area. As an important part of the urban-rural integration construction, evaluating the health status of the Beiyun River Basin and discovering the weak links in the water environment are the basis for improving the health of the basin. In this study, analytic hierarchy process (AHP) was used to establish an evaluation index system for the Beiyun River Basin from 5 aspects including water quality, biology, ecology, hydrology, and social functions, and the principal component analysis (PCA) was then used to assign weights to the index layer. The evaluation results showed that the health evaluation results of the Beiyun River Basin in 2019 are "sub-healthy," and the overall health status is getting worse from northwest to southeast. In the middle reaches of the region, the evaluation result is "healthy," followed by the upstream, and the downstream is the worst. The results showed that areas with less human interference or orderly intervention are in better health. High eutrophication level, low bio-diversity, and low vegetation coverage are the main indicators that leads to poor ecosystem health in the Beiyun River Basin. For the comprehensive management of the Beiyun River, the improvement of water quality and habitat ecological restoration are key actions to the health of the upstream ecosystem. The improvement of the health status of the downstream should focus on equal emphasis on water quality and quantity, restoration of biodiversity, and improvement of the quality of the riparian ecological environment.

RevDate: 2022-03-04
CmpDate: 2022-03-04

Bogdanowski A, Banitz T, Muhsal LK, et al (2022)

McComedy: A user-friendly tool for next-generation individual-based modeling of microbial consumer-resource systems.

PLoS computational biology, 18(1):e1009777.

Individual-based modeling is widely applied to investigate the ecological mechanisms driving microbial community dynamics. In such models, the population or community dynamics emerge from the behavior and interplay of individual entities, which are simulated according to a predefined set of rules. If the rules that govern the behavior of individuals are based on generic and mechanistically sound principles, the models are referred to as next-generation individual-based models. These models perform particularly well in recapitulating actual ecological dynamics. However, implementation of such models is time-consuming and requires proficiency in programming or in using specific software, which likely hinders a broader application of this powerful method. Here we present McComedy, a modeling tool designed to facilitate the development of next-generation individual-based models of microbial consumer-resource systems. This tool allows flexibly combining pre-implemented building blocks that represent physical and biological processes. The ability of McComedy to capture the essential dynamics of microbial consumer-resource systems is demonstrated by reproducing and furthermore adding to the results of two distinct studies from the literature. With this article, we provide a versatile tool for developing next-generation individual-based models that can foster understanding of microbial ecology in both research and education.

RevDate: 2022-02-02
CmpDate: 2022-02-02

Chen Y, Xiong K, Ren X, et al (2022)

An overview of ecological vulnerability: a bibliometric analysis based on the Web of Science database.

Environmental science and pollution research international, 29(9):12984-12996.

Ecological vulnerability has become one of the hot issues of ecology and environmental science under global change and sustainable development scenarios. However, no study quantitatively analyzes the global scientific performance and hot research areas in this field by adopting the bibliometric method. Based on 935 pieces of literature retrieved from the Web of Science database, we comprehensively analyzed the research on ecological vulnerability in terms of growth trend, research content, publication journal and country, and co-occurrence network of keywords. The results showed that research on ecological vulnerability had experienced rapid growth since 2000, while ecological vulnerability research at the World Heritage sites was still embryonic. The top two productive countries in ecological vulnerability research were America and China, and the top two productive journals were Ecological Indicators and Regional Environmental Change. Study on ecological vulnerability was mainly classified as empirical evaluation and regional synthesis, whereas theoretical research is rare. Based on the summary of the main progress and achievements in ecological vulnerability research, we proposed five scientific issues that remain to be resolved in the field of ecological vulnerability. Overall, this study could shed light on a comprehensive and systematic understanding of ecological vulnerability and provide directions for future research on ecological vulnerability in a rapidly changing world.

RevDate: 2022-02-11
CmpDate: 2022-02-11

Tyrrell P, Amoke I, Betjes K, et al (2022)

Landscape Dynamics (landDX) an open-access spatial-temporal database for the Kenya-Tanzania borderlands.

Scientific data, 9(1):8.

The savannas of the Kenya-Tanzania borderland cover >100,000 km2 and is one of the most important regions globally for biodiversity conservation, particularly large mammals. The region also supports >1 million pastoralists and their livestock. In these systems, resources for both large mammals and pastoralists are highly variable in space and time and thus require connected landscapes. However, ongoing fragmentation of (semi-)natural vegetation by smallholder fencing and expansion of agriculture threatens this social-ecological system. Spatial data on fences and agricultural expansion are localized and dispersed among data owners and databases. Here, we synthesized data from several research groups and conservation NGOs and present the first release of the Landscape Dynamics (landDX) spatial-temporal database, covering ~30,000 km2 of southern Kenya. The data includes 31,000 livestock enclosures, nearly 40,000 kilometres of fencing, and 1,500 km2 of agricultural land. We provide caveats and interpretation of the different methodologies used. These data are useful to answer fundamental ecological questions, to quantify the rate of change of ecosystem function and wildlife populations, for conservation and livestock management, and for local and governmental spatial planning.

RevDate: 2022-04-29

La Manna G, Picciulin M, Crobu A, et al (2021)

Marine soundscape and fish biophony of a Mediterranean marine protected area.

PeerJ, 9:e12551.

BACKGROUND: Marine soundscape is the aggregation of sound sources known as geophony, biophony, and anthrophony. The soundscape analysis, in terms of collection and analysis of acoustic signals, has been proposed as a tool to evaluate the specific features of ecological assemblages and to estimate their acoustic variability over space and time. This study aimed to characterise the Capo Caccia-Isola Piana Marine Protected Area (Italy, Western Mediterranean Sea) soundscape over short temporal (few days) and spatial scales (few km) and to quantify the main anthropogenic and biological components, with a focus on fish biophonies.

METHODS: Within the MPA, three sites were chosen each in a different protection zone (A for the integral protection, B as the partial protection, and C as the general protection). In each site, two underwater autonomous acoustic recorders were deployed in July 2020 at a depth of about 10 m on rocky bottoms. To characterise the contribution of both biophonies and anthrophonies, sea ambient noise (SAN) levels were measured as sound pressure level (SPL dB re: 1 μ Pa-rms) at eight 1/3 octave bands, centred from 125 Hz to 16 kHz, and biological and anthropogenic sounds were noted. Fish sounds were classified and counted following a catalogue of known fish sounds from the Mediterranean Sea based on the acoustic characteristic of sound types. A contemporary fish visual census had been carried out at the test sites.

RESULTS: SPL were different by site, time (day vs. night), and hour. SPLs bands centred at 125, 250, and 500 Hz were significantly higher in the daytime, due to the high number of boats per minute whose noise dominated the soundscapes. The loudest man-made noise was found in the A zone, followed by the B and the C zone, confirming that MPA current regulations do not provide protection from acoustic pollution. The dominant biological components of the MPA soundscape were the impulsive sounds generated by some invertebrates, snapping shrimps and fish. The vast majority of fish sounds were recorded at the MPA site characterized by the highest sound richness, abundance, and Shannon-Wiener index, coherently with the results of a fish visual census. Moreover, the acoustic monitoring detected a sound associated with a cryptic species (Ophidion spp.) never reported in the study area before, further demonstrating the usefulness of passive acoustic monitoring as a complementary technique to species census. This study provides baseline data to detect future changes of the marine soundscapes and some suggestions to reduce the impact of noise on marine biodiversity.

RevDate: 2022-01-18
CmpDate: 2022-01-18

Ren W, Zhao J, Ma X, et al (2021)

Analysis of the spatial differentiation and scale effects of the three-dimensional architectural landscape in Xi'an, China.

PloS one, 16(12):e0261846.

Three-dimensional landscape patterns are an effective means to study the relationship between landscape pattern evolution and eco-environmental effects. This paper selects six districts in Xi'an as the study area to examine the spatial distribution characteristics of the three-dimensional architectural landscape in the city's main urban area using three-dimensional information on the buildings in 2020 with the support of GIS. In this study, two new architectural landscape indices-landscape height variable coefficient and building rugosity index-were employed in landscape pattern analysis, whilst a system of rigorous and comprehensive three-dimensional architectural landscape metrics was established using principal component analysis. A mathematical model of weighted change of landscape metrics based on the objective weighting method was applied to carry out scale analysis of the landscape patterns. Spatial statistical analysis and spatial autocorrelation analysis were conducted to comprehensively study the differentiation of three-dimensional architectural landscape spatial patterns. The results show that the characteristic scale of the three-dimensional landscape pattern in Xi'an's main urban area is around 8 km. Moreover, the three-dimensional landscape of the buildings in this area is spatially positively correlated, exhibiting a high degree of spatial autocorrelation whilst only showing small spatial differences. The layout of the architectural landscape pattern is disorderly and chaotic within the second ring, whilst the clustering of patch types occurs near the third ring. Moreover, the building density in the Beilin, Lianhu, and Xincheng districts is large, the building height types are rich, and the roughness of the underlying surface is high, such that these are key areas to be improved through urban renewal. The height, volume, density, morphological heterogeneity, and vertical roughness of the architectural landscape vary amongst functional areas within the study area. This paper is the first to apply the study of spatial heterogeneity of three-dimensional landscape patterns to Xi'an. It does so in order to provide a quantitative basis for urban landscape ecological design for urban renewal and the rational planning of built-up areas, which will promote the sustainable development of the city's urban environment.

RevDate: 2021-12-24

Latombe G, Richardson DM, McGeoch MA, et al (2021)

Mechanistic reconciliation of community and invasion ecology.

Ecosphere (Washington, D.C), 12(2):e03359.

Community and invasion ecology have mostly grown independently. There is substantial overlap in the processes captured by different models in the two fields, and various frameworks have been developed to reduce this redundancy and synthesize information content. Despite broad recognition that community and invasion ecology are interconnected, a process-based framework synthesizing models across these two fields is lacking. Here we review 65 representative community and invasion models and propose a common framework articulated around six processes (dispersal, drift, abiotic interactions, within-guild interactions, cross-guild interactions, and genetic changes). The framework is designed to synthesize the content of the two fields, provide a general perspective on their development, and enable their comparison. The application of this framework and of a novel method based on network theory reveals some lack of coherence between the two fields, despite some historical similarities. Community ecology models are characterized by combinations of multiple processes, likely reflecting the search for an overarching theory to explain community assembly and structure, drawing predominantly on interaction processes, but also accounting largely for the other processes. In contrast, most models in invasion ecology invoke fewer processes and focus more on interactions between introduced species and their novel biotic and abiotic environment. The historical dominance of interaction processes and their independent developments in the two fields is also reflected in the lower level of coherence for models involving interactions, compared to models involving dispersal, drift, and genetic changes. It appears that community ecology, with a longer history than invasion ecology, has transitioned from the search for single explanations for patterns observed in nature to investigate how processes may interact mechanistically, thereby generating and testing hypotheses. Our framework paves the way for a similar transition in invasion ecology, to better capture the dynamics of multiple alien species introduced in complex communities. Reciprocally, applying insights from invasion to community ecology will help us understand and predict the future of ecological communities in the Anthropocene, in which human activities are weakening species' natural boundaries. Ultimately, the successful integration of the two fields could advance a predictive ecology that is urgently required in a rapidly changing world.

RevDate: 2022-04-01
CmpDate: 2022-03-31

Allen-Perkins A, Magrach A, Dainese M, et al (2022)

CropPol: A dynamic, open and global database on crop pollination.

Ecology, 103(3):e3614.

Seventy five percent of the world's food crops benefit from insect pollination. Hence, there has been increased interest in how global change drivers impact this critical ecosystem service. Because standardized data on crop pollination are rarely available, we are limited in our capacity to understand the variation in pollination benefits to crop yield, as well as to anticipate changes in this service, develop predictions, and inform management actions. Here, we present CropPol, a dynamic, open, and global database on crop pollination. It contains measurements recorded from 202 crop studies, covering 3,394 field observations, 2,552 yield measurements (i.e., berry mass, number of fruits, and fruit density [kg/ha], among others), and 47,752 insect records from 48 commercial crops distributed around the globe. CropPol comprises 32 of the 87 leading global crops and commodities that are pollinator dependent. Malus domestica is the most represented crop (32 studies), followed by Brassica napus (22 studies), Vaccinium corymbosum (13 studies), and Citrullus lanatus (12 studies). The most abundant pollinator guilds recorded are honey bees (34.22% counts), bumblebees (19.19%), flies other than Syrphidae and Bombyliidae (13.18%), other wild bees (13.13%), beetles (10.97%), Syrphidae (4.87%), and Bombyliidae (0.05%). Locations comprise 34 countries distributed among Europe (76 studies), North America (60), Latin America and the Caribbean (29), Asia (20), Oceania (10), and Africa (7). Sampling spans three decades and is concentrated on 2001-2005 (21 studies), 2006-2010 (40), 2011-2015 (88), and 2016-2020 (50). This is the most comprehensive open global data set on measurements of crop flower visitors, crop pollinators and pollination to date, and we encourage researchers to add more datasets to this database in the future. This data set is released for non-commercial use only. Credits should be given to this paper (i.e., proper citation), and the products generated with this database should be shared under the same license terms (CC BY-NC-SA).

RevDate: 2022-07-16

Wang F, Harindintwali JD, Yuan Z, et al (2021)

Technologies and perspectives for achieving carbon neutrality.

Innovation (Cambridge (Mass.)), 2(4):100180.

Global development has been heavily reliant on the overexploitation of natural resources since the Industrial Revolution. With the extensive use of fossil fuels, deforestation, and other forms of land-use change, anthropogenic activities have contributed to the ever-increasing concentrations of greenhouse gases (GHGs) in the atmosphere, causing global climate change. In response to the worsening global climate change, achieving carbon neutrality by 2050 is the most pressing task on the planet. To this end, it is of utmost importance and a significant challenge to reform the current production systems to reduce GHG emissions and promote the capture of CO2 from the atmosphere. Herein, we review innovative technologies that offer solutions achieving carbon (C) neutrality and sustainable development, including those for renewable energy production, food system transformation, waste valorization, C sink conservation, and C-negative manufacturing. The wealth of knowledge disseminated in this review could inspire the global community and drive the further development of innovative technologies to mitigate climate change and sustainably support human activities.

RevDate: 2022-02-14
CmpDate: 2022-02-14

Civantos-Gómez I, García-Algarra J, García-Callejas D, et al (2021)

Fine scale prediction of ecological community composition using a two-step sequential Machine Learning ensemble.

PLoS computational biology, 17(12):e1008906.

Prediction is one of the last frontiers in ecology. Indeed, predicting fine-scale species composition in natural systems is a complex challenge as multiple abiotic and biotic processes operate simultaneously to determine local species abundances. On the one hand, species intrinsic performance and their tolerance limits to different abiotic pressures modulate species abundances. On the other hand, there is growing recognition that species interactions play an equally important role in limiting or promoting such abundances within ecological communities. Here, we present a joint effort between ecologists and data scientists to use data-driven models to predict species abundances using reasonably easy to obtain data. We propose a sequential data-driven modeling approach that in a first step predicts the potential species abundances based on abiotic variables, and in a second step uses these predictions to model the realized abundances once accounting for species competition. Using a curated data set over five years we predict fine-scale species abundances in a highly diverse annual plant community. Our models show a remarkable spatial predictive accuracy using only easy-to-measure variables in the field, yet such predictive power is lost when temporal dynamics are taken into account. This result suggests that predicting future abundances requires longer time series analysis to capture enough variability. In addition, we show that these data-driven models can also suggest how to improve mechanistic models by adding missing variables that affect species performance such as particular soil conditions (e.g. carbonate availability in our case). Robust models for predicting fine-scale species composition informed by the mechanistic understanding of the underlying abiotic and biotic processes can be a pivotal tool for conservation, especially given the human-induced rapid environmental changes we are experiencing. This objective can be achieved by promoting the knowledge gained with classic modelling approaches in ecology and recently developed data-driven models.

RevDate: 2022-01-04
CmpDate: 2022-01-04

Yang X, Baskin CC, Baskin JM, et al (2021)

Global patterns of potential future plant diversity hidden in soil seed banks.

Nature communications, 12(1):7023.

Soil seed banks represent a critical but hidden stock for potential future plant diversity on Earth. Here we compiled and analyzed a global dataset consisting of 15,698 records of species diversity and density for soil seed banks in natural plant communities worldwide to quantify their environmental determinants and global patterns. Random forest models showed that absolute latitude was an important predictor for diversity of soil seed banks. Further, climate and soil were the major determinants of seed bank diversity, while net primary productivity and soil characteristics were the main predictors of seed bank density. Moreover, global mapping revealed clear spatial patterns for soil seed banks worldwide; for instance, low densities may render currently species-rich low latitude biomes (such as tropical rain-forests) less resilient to major disturbances. Our assessment provides quantitative evidence of how environmental conditions shape the distribution of soil seed banks, which enables a more accurate prediction of the resilience and vulnerabilities of plant communities and biomes under global changes.

RevDate: 2021-12-24
CmpDate: 2021-12-24

Osone Y, Hashimoto S, T Kenzo (2021)

Verification of our empirical understanding of the physiology and ecology of two contrasting plantation species using a trait database.

PloS one, 16(11):e0254599.

The effects of climate change on forest ecosystems take on increasing importance more than ever. Information on plant traits is a powerful predictor of ecosystem dynamics and functioning. We reviewed the major ecological traits, such as foliar gas exchange and nutrients, xylem morphology and drought tolerance, of Cryptomeria japonica and Chamaecyparis obtusa, which are major timber species in East Asia, especially in Japan, by using a recently developed functional trait database for both species (SugiHinokiDB). Empirically, C. obtusa has been planted under drier conditions, whereas C. japonica, which grows faster but thought to be less drought tolerant, has been planted under wetter conditions. Our analysis generally support the empirical knowledge: The maximum photosynthetic rate, stomatal conductance, foliar nutrient content and soil-to-foliage hydraulic conductance were higher in C. japonica than in C. obtusa. In contrast, the foliar turgor loss point and xylem pressure corresponding to 50% conductivity, which indicate drought tolerance, were lower in C. obtusa and are consistent with the drier habitat of C. obtusa. Ontogenetic shifts were also observed; as the age and height of the trees increased, foliar nutrient concentrations, foliar minimum midday water potential and specific leaf area decreased in C. japonica, suggesting that nutrient and water limitation occurs with the growth. In C. obtusa, the ontogenetic shits of these foliar traits were less pronounced. Among the Cupressaceae worldwide, the drought tolerance of C. obtusa, as well as C. japonica, was not as high. This may be related to the fact that the Japanese archipelago has historically not been subjected to strong dryness. The maximum photosynthetic rate showed intermediate values within the family, indicating that C. japonica and C. obtusa exhibit relatively high growth rates in the Cupressaceae family, and this is thought to be the reason why they have been selected as economically suitable timber species in Japanese forestry. This study clearly demonstrated that the plant trait database provides us a promising opportunity to verify out empirical knowledge of plantation management and helps us to understand effect of climate change on plantation forests by using trait-based modelling.

RevDate: 2021-11-29

Love NLR, Bonnet P, Goëau H, et al (2021)

Machine Learning Undercounts Reproductive Organs on Herbarium Specimens but Accurately Derives Their Quantitative Phenological Status: A Case Study of Streptanthus tortuosus.

Plants (Basel, Switzerland), 10(11):.

Machine learning (ML) can accelerate the extraction of phenological data from herbarium specimens; however, no studies have assessed whether ML-derived phenological data can be used reliably to evaluate ecological patterns. In this study, 709 herbarium specimens representing a widespread annual herb, Streptanthus tortuosus, were scored both manually by human observers and by a mask R-CNN object detection model to (1) evaluate the concordance between ML and manually-derived phenological data and (2) determine whether ML-derived data can be used to reliably assess phenological patterns. The ML model generally underestimated the number of reproductive structures present on each specimen; however, when these counts were used to provide a quantitative estimate of the phenological stage of plants on a given sheet (i.e., the phenological index or PI), the ML and manually-derived PI's were highly concordant. Moreover, herbarium specimen age had no effect on the estimated PI of a given sheet. Finally, including ML-derived PIs as predictor variables in phenological models produced estimates of the phenological sensitivity of this species to climate, temporal shifts in flowering time, and the rate of phenological progression that are indistinguishable from those produced by models based on data provided by human observers. This study demonstrates that phenological data extracted using machine learning can be used reliably to estimate the phenological stage of herbarium specimens and to detect phenological patterns.

RevDate: 2022-03-14
CmpDate: 2022-03-14

Alberdi A, Martin Bideguren G, O Aizpurua (2021)

Diversity and compositional changes in the gut microbiota of wild and captive vertebrates: a meta-analysis.

Scientific reports, 11(1):22660.

The gut microbiota is recognised as an essential asset for the normal functioning of animal biology. When wild animals are moved into captivity, the modified environmental pressures are expected to rewire the gut microbiota, yet whether this transition follows similar patterns across vertebrates is still unresolved due to the absence of systematic multi-species analyses. We performed a meta-analysis of gut microbiota profiles of 322 captive and 322 wild specimens from 24 vertebrate species. Our analyses yielded no overall pattern of diversity and compositional variation between wild and captive vertebrates, but a heterogeneous landscape of responses, which differed depending on the components of diversity considered. Captive populations showed enrichment patterns of human-associated microorganisms, and the minimal host phylogenetic signal suggests that changes between wild and captive populations are mainly driven by case-specific captivity conditions. Finally, we show that microbiota differences between wild and captive populations can impact evolutionary and ecological inferences that rely on hierarchical clustering-based comparative analyses of gut microbial communities across species.

RevDate: 2022-04-28

Chamanara J, Gaikwad J, Gerlach R, et al (2021)

BEXIS2: A FAIR-aligned data management system for biodiversity, ecology and environmental data.

Biodiversity data journal, 9:e72901.

BACKGROUND: Obtaining fit-to-use data associated with diverse aspects of biodiversity, ecology and environment is challenging since often it is fragmented, sub-optimally managed and available in heterogeneous formats. Recently, with the universal acceptance of the FAIR data principles, the requirements and standards of data publications have changed substantially. Researchers are encouraged to manage the data as per the FAIR data principles and ensure that the raw data, metadata, processed data, software, codes and associated material are securely stored and the data be made available with the completion of the research.

NEW INFORMATION: We have developed BEXIS2 as an open-source community-driven web-based research data management system to support research data management needs of mid to large-scale research projects with multiple sub-projects and up to several hundred researchers. BEXIS2 is a modular and extensible system providing a range of functions to realise the complete data lifecycle from data structure design to data collection, data discovery, dissemination, integration, quality assurance and research planning. It is an extensible and customisable system that allows for the development of new functions and customisation of its various components from database schemas to the user interface layout, elements and look and feel.During the development of BEXIS2, we aimed to incorporate key aspects of what is encoded in FAIR data principles. To investigate the extent to which BEXIS2 conforms to these principles, we conducted the self-assessment using the FAIR indicators, definitions and criteria provided in the FAIR Data Maturity Model. Even though the FAIR data maturity model is developed initially to judge the conformance of datasets, the self-assessment results indicated that BEXIS2 remarkably conforms and supports FAIR indicators. BEXIS2 strongly conforms to the indicators Findability and Accessibility. The indicator Interoperability is moderately supported as of now; however, for many of the lesssupported facets, we have concrete plans for improvement. Reusability (as defined by the FAIR data principles) is partially achieved.This paper also illustrates community deployment examples of the BEXIS2 instances as success stories to exemplify its capacity to meet the biodiversity and ecological data management needs of differently sized projects and serve as an organisational research data management system.

RevDate: 2021-11-17

Ambarlı D, Simons NK, Wehner K, et al (2021)

Animal-Mediated Ecosystem Process Rates in Forests and Grasslands are Affected by Climatic Conditions and Land-Use Intensity.

Ecosystems (New York, N.Y.), 24(2):467-483.

Decomposition, vegetation regeneration, and biological control are essential ecosystem functions, and animals are involved in the underlying processes, such as dung removal, seed removal, herbivory, and predation. Despite evidence for declines of animal diversity and abundance due to climate change and land-use intensification, we poorly understand how animal-mediated processes respond to these global change drivers. We experimentally measured rates of four ecosystem processes in 134 grassland and 149 forest plots in Germany and tested their response to climatic conditions and land-use intensity, that is, grazing, mowing, and fertilization in grasslands and the proportion of harvested wood, non-natural trees, and deadwood origin in forests. For both climate and land use, we distinguished between short-term effects during the survey period and medium-term effects during the preceding years. Forests had significantly higher process rates than grasslands. In grasslands, the climatic effects on the process rates were similar or stronger than land-use effects, except for predation; land-use intensity negatively affected several process rates. In forests, the land-use effects were more pronounced than the climatic effects on all processes except for predation. The proportion of non-natural trees had the greatest impact on the process rates in forests. The proportion of harvested wood had negative effects, whereas the proportion of anthropogenic deadwood had positive effects on some processes. The effects of climatic conditions and land-use intensity on process rates mirror climatic and habitat effects on animal abundance, activity, and resource quality. Our study demonstrates that land-use changes and interventions affecting climatic conditions will have substantial impacts on animal-mediated ecosystem processes.

RevDate: 2022-07-31
CmpDate: 2022-01-28

G Ribeiro P, Torres Jiménez MF, Andermann T, et al (2021)

A bioinformatic platform to integrate target capture and whole genome sequences of various read depths for phylogenomics.

Molecular ecology, 30(23):6021-6035.

The increasing availability of short-read whole genome sequencing (WGS) provides unprecedented opportunities to study ecological and evolutionary processes. Although loci of interest can be extracted from WGS data and combined with target sequence data, this requires suitable bioinformatic workflows. Here, we test different assembly and locus extraction strategies and implement them into secapr, a pipeline that processes short-read data into multilocus alignments for phylogenetics and molecular ecology analyses. We integrate the processing of data from low-coverage WGS (<30×) and target sequence capture into a flexible framework, while optimizing de novo contig assembly and loci extraction. Specifically, we test different assembly strategies by contrasting their ability to recover loci from targeted butterfly protein-coding genes, using four data sets: a WGS data set across different average coverages (10×, 5× and 2×) and a data set for which these loci were enriched prior to sequencing via target sequence capture. Using the resulting de novo contigs, we account for potential errors within contigs and infer phylogenetic trees to evaluate the ability of each assembly strategy to recover species relationships. We demonstrate that choosing multiple sizes of kmer simultaneously for assembly results in the highest yield of extracted loci from de novo assembled contigs, while data sets derived from sequencing read depths as low as 5× recovers the expected species relationships in phylogenetic trees. By making the tested assembly approaches available in the secapr pipeline, we hope to inspire future studies to incorporate complementary data and make an informed choice on the optimal assembly strategy.

RevDate: 2022-01-27
CmpDate: 2022-01-27

Pekár S, Wolff JO, Černecká Ľ, et al (2021)

The World Spider Trait database: a centralized global open repository for curated data on spider traits.

Database : the journal of biological databases and curation, 2021:.

Spiders are a highly diversified group of arthropods and play an important role in terrestrial ecosystems as ubiquitous predators, which makes them a suitable group to test a variety of eco-evolutionary hypotheses. For this purpose, knowledge of a diverse range of species traits is required. Until now, data on spider traits have been scattered across thousands of publications produced for over two centuries and written in diverse languages. To facilitate access to such data, we developed an online database for archiving and accessing spider traits at a global scale. The database has been designed to accommodate a great variety of traits (e.g. ecological, behavioural and morphological) measured at individual, species or higher taxonomic levels. Records are accompanied by extensive metadata (e.g. location and method). The database is curated by an expert team, regularly updated and open to any user. A future goal of the growing database is to include all published and unpublished data on spider traits provided by experts worldwide and to facilitate broad cross-taxon assays in functional ecology and comparative biology. Database URL:https://spidertraits.sci.muni.cz/.

RevDate: 2022-06-03

Hoffmann MA, Nothias LF, Ludwig M, et al (2022)

High-confidence structural annotation of metabolites absent from spectral libraries.

Nature biotechnology, 40(3):411-421.

Untargeted metabolomics experiments rely on spectral libraries for structure annotation, but, typically, only a small fraction of spectra can be matched. Previous in silico methods search in structure databases but cannot distinguish between correct and incorrect annotations. Here we introduce the COSMIC workflow that combines in silico structure database generation and annotation with a confidence score consisting of kernel density P value estimation and a support vector machine with enforced directionality of features. On diverse datasets, COSMIC annotates a substantial number of hits at low false discovery rates and outperforms spectral library search. To demonstrate that COSMIC can annotate structures never reported before, we annotated 12 natural bile acids. The annotation of nine structures was confirmed by manual evaluation and two structures using synthetic standards. In human samples, we annotated and manually validated 315 molecular structures currently absent from the Human Metabolome Database. Application of COSMIC to data from 17,400 metabolomics experiments led to 1,715 high-confidence structural annotations that were absent from spectral libraries.

RevDate: 2021-12-14
CmpDate: 2021-12-14

Grundler MC, DL Rabosky (2021)

Rapid increase in snake dietary diversity and complexity following the end-Cretaceous mass extinction.

PLoS biology, 19(10):e3001414.

The Cenozoic marked a period of dramatic ecological opportunity in Earth history due to the extinction of non-avian dinosaurs as well as to long-term physiographic changes that created new biogeographic theaters and new habitats. Snakes underwent massive ecological diversification during this period, repeatedly evolving novel dietary adaptations and prey preferences. The evolutionary tempo and mode of these trophic ecological changes remain virtually unknown, especially compared with co-radiating lineages of birds and mammals that are simultaneously predators and prey of snakes. Here, we assemble a dataset on snake diets (34,060 observations on the diets of 882 species) to investigate the history and dynamics of the multidimensional trophic niche during the global radiation of snakes. Our results show that per-lineage dietary niche breadths remained remarkably constant even as snakes diversified to occupy disparate outposts of dietary ecospace. Rapid increases in dietary diversity and complexity occurred in the early Cenozoic, and the overall rate of ecospace expansion has slowed through time, suggesting a potential response to ecological opportunity in the wake of the end-Cretaceous mass extinction. Explosive bursts of trophic innovation followed colonization of the Nearctic and Neotropical realms by a group of snakes that today comprises a majority of living snake diversity. Our results indicate that repeated transformational shifts in dietary ecology are important drivers of adaptive radiation in snakes and provide a framework for analyzing and visualizing the evolution of complex ecological phenotypes on phylogenetic trees.

RevDate: 2021-10-28
CmpDate: 2021-10-28

Hafeez M, Li X, Ullah F, et al (2021)

Behavioral and Physiological Plasticity Provides Insights into Molecular Based Adaptation Mechanism to Strain Shift in Spodoptera frugiperda.

International journal of molecular sciences, 22(19):.

How herbivorous insects adapt to host plants is a key question in ecological and evolutionary biology. The fall armyworm, (FAW) Spodoptera frugiperda (J.E. Smith), although polyphagous and a major pest on various crops, has been reported to have a rice and corn (maize) feeding strain in its native range in the Americas. The species is highly invasive and has recently established in China. We compared behavioral changes in larvae and adults of a corn population (Corn) when selected on rice (Rice) and the molecular basis of these adaptational changes in midgut and antennae based on a comparative transcriptome analysis. Larvae of S. frugiperda reared on rice plants continuously for 20 generations exhibited strong feeding preference for with higher larval performance and pupal weight on rice than on maize plants. Similarly, females from the rice selected population laid significantly more eggs on rice as compared to females from maize population. The most highly expressed DEGs were shown in the midgut of Rice vs. Corn. A total of 6430 DEGs were identified between the populations mostly in genes related to digestion and detoxification. These results suggest that potential adaptations for feeding on rice crops, may contribute to the current rapid spread of fall armyworm on rice crops in China and potentially elsewhere. Consistently, highly expressed DEGs were also shown in antennae; a total of 5125 differentially expressed genes (DEGs) s were identified related to the expansions of major chemosensory genes family in Rice compared to the Corn feeding population. These results not only provide valuable insight into the molecular mechanisms in host plants adaptation of S. frugiperda but may provide new gene targets for the management of this pest.

RevDate: 2021-10-20
CmpDate: 2021-10-20

Wang X, Zhang C, Wang C, et al (2021)

GIS-based for prediction and prevention of environmental geological disaster susceptibility: From a perspective of sustainable development.

Ecotoxicology and environmental safety, 226:112881.

Geological disasters seriously threaten the safety of human life, property, ecological resources, and the environment. Effective control of geological disasters is the focus of achieving sustainable social development. The Helong City (Jilin Province, China) was selected as the case study. Combined with GIS technology, a new integrated prediction model of geological disaster susceptibility was developed to improve the accuracy of geological disaster assessment, reduce the cost of geological disaster treatment, and ensure the sustainable development of ecological environment. The research results showed that elevation and normalized difference vegetation index (NDVI) were the key factors affecting susceptibility. Compared with the conventional model, the accuracy of the developing integrated model FR-DT and FR-RF was improved by more than 6%, and the disaster points were more concentrated in the high susceptibility zone. Statistical results of disaster treatment cost estimation and gross domestic product (GDP) value showed that the integrated model can save about 10% of treatment cost, and the ratio of total GDP/disaster governance cost was higher. The performance of the integrated model FR-DT and FR-RF had obvious advantages over the conventional model in terms of prediction accuracy, prevention pertinence, and prevention cost. These research results promote the advancement of geological disaster prevention and control technology, ensure the safety of the geological environment, and are of great significance to the sustainable development of the regional economy.

RevDate: 2022-07-16
CmpDate: 2021-10-18

Freschet GT, Pagès L, Iversen CM, et al (2021)

A starting guide to root ecology: strengthening ecological concepts and standardising root classification, sampling, processing and trait measurements.

The New phytologist, 232(3):973-1122.

In the context of a recent massive increase in research on plant root functions and their impact on the environment, root ecologists currently face many important challenges to keep on generating cutting-edge, meaningful and integrated knowledge. Consideration of the below-ground components in plant and ecosystem studies has been consistently called for in recent decades, but methodology is disparate and sometimes inappropriate. This handbook, based on the collective effort of a large team of experts, will improve trait comparisons across studies and integration of information across databases by providing standardised methods and controlled vocabularies. It is meant to be used not only as starting point by students and scientists who desire working on below-ground ecosystems, but also by experts for consolidating and broadening their views on multiple aspects of root ecology. Beyond the classical compilation of measurement protocols, we have synthesised recommendations from the literature to provide key background knowledge useful for: (1) defining below-ground plant entities and giving keys for their meaningful dissection, classification and naming beyond the classical fine-root vs coarse-root approach; (2) considering the specificity of root research to produce sound laboratory and field data; (3) describing typical, but overlooked steps for studying roots (e.g. root handling, cleaning and storage); and (4) gathering metadata necessary for the interpretation of results and their reuse. Most importantly, all root traits have been introduced with some degree of ecological context that will be a foundation for understanding their ecological meaning, their typical use and uncertainties, and some methodological and conceptual perspectives for future research. Considering all of this, we urge readers not to solely extract protocol recommendations for trait measurements from this work, but to take a moment to read and reflect on the extensive information contained in this broader guide to root ecology, including sections I-VII and the many introductions to each section and root trait description. Finally, it is critical to understand that a major aim of this guide is to help break down barriers between the many subdisciplines of root ecology and ecophysiology, broaden researchers' views on the multiple aspects of root study and create favourable conditions for the inception of comprehensive experiments on the role of roots in plant and ecosystem functioning.

RevDate: 2022-04-01
CmpDate: 2022-03-31

Westfall AK, Telemeco RS, Grizante MB, et al (2021)

A chromosome-level genome assembly for the eastern fence lizard (Sceloporus undulatus), a reptile model for physiological and evolutionary ecology.

GigaScience, 10(10):.

BACKGROUND: High-quality genomic resources facilitate investigations into behavioral ecology, morphological and physiological adaptations, and the evolution of genomic architecture. Lizards in the genus Sceloporus have a long history as important ecological, evolutionary, and physiological models, making them a valuable target for the development of genomic resources.

FINDINGS: We present a high-quality chromosome-level reference genome assembly, SceUnd1.0 (using 10X Genomics Chromium, HiC, and Pacific Biosciences data), and tissue/developmental stage transcriptomes for the eastern fence lizard, Sceloporus undulatus. We performed synteny analysis with other snake and lizard assemblies to identify broad patterns of chromosome evolution including the fusion of micro- and macrochromosomes. We also used this new assembly to provide improved reference-based genome assemblies for 34 additional Sceloporus species. Finally, we used RNAseq and whole-genome resequencing data to compare 3 assemblies, each representing an increased level of cost and effort: Supernova Assembly with data from 10X Genomics Chromium, HiRise Assembly that added data from HiC, and PBJelly Assembly that added data from Pacific Biosciences sequencing. We found that the Supernova Assembly contained the full genome and was a suitable reference for RNAseq and single-nucleotide polymorphism calling, but the chromosome-level scaffolds provided by the addition of HiC data allowed synteny and whole-genome association mapping analyses. The subsequent addition of PacBio data doubled the contig N50 but provided negligible gains in scaffold length.

CONCLUSIONS: These new genomic resources provide valuable tools for advanced molecular analysis of an organism that has become a model in physiology and evolutionary ecology.

RevDate: 2021-12-14
CmpDate: 2021-12-13

Falster D, Gallagher R, Wenk EH, et al (2021)

AusTraits, a curated plant trait database for the Australian flora.

Scientific data, 8(1):254.

We introduce the AusTraits database - a compilation of values of plant traits for taxa in the Australian flora (hereafter AusTraits). AusTraits synthesises data on 448 traits across 28,640 taxa from field campaigns, published literature, taxonomic monographs, and individual taxon descriptions. Traits vary in scope from physiological measures of performance (e.g. photosynthetic gas exchange, water-use efficiency) to morphological attributes (e.g. leaf area, seed mass, plant height) which link to aspects of ecological variation. AusTraits contains curated and harmonised individual- and species-level measurements coupled to, where available, contextual information on site properties and experimental conditions. This article provides information on version 3.0.2 of AusTraits which contains data for 997,808 trait-by-taxon combinations. We envision AusTraits as an ongoing collaborative initiative for easily archiving and sharing trait data, which also provides a template for other national or regional initiatives globally to fill persistent gaps in trait knowledge.

RevDate: 2021-12-27
CmpDate: 2021-12-27

Fernandes-Martins MC, Keller LM, Munro-Ehrlich M, et al (2021)

Ecological Dichotomies Arise in Microbial Communities Due to Mixing of Deep Hydrothermal Waters and Atmospheric Gas in a Circumneutral Hot Spring.

Applied and environmental microbiology, 87(23):e0159821.

Little is known of how the confluence of subsurface and surface processes influences the assembly and habitability of hydrothermal ecosystems. To address this knowledge gap, the geochemical and microbial composition of a high-temperature, circumneutral hot spring in Yellowstone National Park was examined to identify the sources of solutes and their effect on the ecology of microbial inhabitants. Metagenomic analysis showed that populations comprising planktonic and sediment communities are archaeal dominated, are dependent on chemical energy (chemosynthetic), share little overlap in their taxonomic composition, and are differentiated by their inferred use of/tolerance to oxygen and mode of carbon metabolism. The planktonic community is dominated by putative aerobic/aerotolerant autotrophs, while the taxonomic composition of the sediment community is more evenly distributed and comprised of anaerobic heterotrophs. These observations are interpreted to reflect sourcing of the spring by anoxic, organic carbon-limited subsurface hydrothermal fluids and ingassing of atmospheric oxygen that selects for aerobic/aerotolerant organisms that have autotrophic capabilities in the water column. Autotrophy and consumption of oxygen by the planktonic community may influence the assembly of the anaerobic and heterotrophic sediment community. Support for this inference comes from higher estimated rates of genome replication in planktonic populations than sediment populations, indicating faster growth in planktonic populations. Collectively, these observations provide new insight into how mixing of subsurface waters and atmospheric oxygen create dichotomy in the ecology of hot spring communities and suggest that planktonic and sediment communities may have been less differentiated taxonomically and functionally prior to the rise of oxygen at ∼2.4 billion years ago (Gya). IMPORTANCE Understanding the source and availability of energy capable of supporting life in hydrothermal environments is central to predicting the ecology of microbial life on early Earth when volcanic activity was more widespread. Little is known of the substrates supporting microbial life in circumneutral to alkaline springs, despite their relevance to early Earth habitats. Using metagenomic and informatics approaches, water column and sediment habitats in a representative circumneutral hot spring in Yellowstone were shown to be dichotomous, with the former largely hosting aerobic/aerotolerant autotrophs and the latter primarily hosting anaerobic heterotrophs. This dichotomy is attributed to influx of atmospheric oxygen into anoxic deep hydrothermal spring waters. These results indicate that the ecology of microorganisms in circumneutral alkaline springs sourced by deep hydrothermal fluids was different prior to the rise of atmospheric oxygen ∼2.4 Gya, with planktonic and sediment communities likely to be less differentiated than contemporary circumneutral hot springs.

RevDate: 2021-10-14
CmpDate: 2021-10-14

Upham NS, Poelen JH, Paul D, et al (2021)

Liberating host-virus knowledge from biological dark data.

The Lancet. Planetary health, 5(10):e746-e750.

Connecting basic data about bats and other potential hosts of SARS-CoV-2 with their ecological context is crucial to the understanding of the emergence and spread of the virus. However, when lockdowns in many countries started in March, 2020, the world's bat experts were locked out of their research laboratories, which in turn impeded access to large volumes of offline ecological and taxonomic data. Pandemic lockdowns have brought to attention the long-standing problem of so-called biological dark data: data that are published, but disconnected from digital knowledge resources and thus unavailable for high-throughput analysis. Knowledge of host-to-virus ecological interactions will be biased until this challenge is addressed. In this Viewpoint, we outline two viable solutions: first, in the short term, to interconnect published data about host organisms, viruses, and other pathogens; and second, to shift the publishing framework beyond unstructured text (the so-called PDF prison) to labelled networks of digital knowledge. As the indexing system for biodiversity data, biological taxonomy is foundational to both solutions. Building digitally connected knowledge graphs of host-pathogen interactions will establish the agility needed to quickly identify reservoir hosts of novel zoonoses, allow for more robust predictions of emergence, and thereby strengthen human and planetary health systems.

RevDate: 2021-12-27
CmpDate: 2021-12-27

Kouba M, Bartoš L, Bartošová J, et al (2021)

Long-term trends in the body condition of parents and offspring of Tengmalm's owls under fluctuating food conditions and climate change.

Scientific reports, 11(1):18893.

Physical condition is important for the ability to resist various parasites and diseases as well as in escaping predators thus contributing to reproductive success, over-winter survival and possible declines in wildlife populations. However, in-depth research on trends in body condition is rare because decades-long datasets are not available for a majority of species. We analysed the long-term dataset of offspring covering 34 years, male parents (40 years) and female parents (42 years) to find out whether the decline of Tengmalm's owl population in western Finland is attributable to either decreased adult and/or juvenile body condition in interaction with changing weather conditions and density estimates of main foods. We found that body condition of parent owl males and females declined throughout the 40-year study period whereas the body condition of owlets at the fledging stage very slightly increased. The body condition of parent owls increased with augmenting depth of snow cover in late winter (January to March), and that of offspring improved with increasing precipitation in late spring (May to June). We conclude that the decreasing trend of body condition of parent owl males and females is important factor probably inducing reduced adult survival and reduced reproduction success thus contributing to the long-term decline of the Tengmalm's owl study population. The very slightly increasing trend of body condition of offspring is obviously not able to compensate the overall decline of Tengmalm's owl population, because the number of offspring in turn simultaneously decreased considerably in the long-term. The ongoing climate change appeared to work in opposite ways in this case because declining depth of snow cover will make the situation worse but increased precipitation will improve. We suggest that the main reasons for long-term decline of body condition of parent owls are interactive or additive effects of reduced food resources and increased overall predation risk due to habitat degradation (loss and fragmentation of mature and old-growth forests due to clear-felling) subsequently leading to decline of Tengmalm's owl study population.

RevDate: 2022-01-06
CmpDate: 2022-01-06

Migliavacca M, Musavi T, Mahecha MD, et al (2021)

The three major axes of terrestrial ecosystem function.

Nature, 598(7881):468-472.

The leaf economics spectrum1,2 and the global spectrum of plant forms and functions3 revealed fundamental axes of variation in plant traits, which represent different ecological strategies that are shaped by the evolutionary development of plant species2. Ecosystem functions depend on environmental conditions and the traits of species that comprise the ecological communities4. However, the axes of variation of ecosystem functions are largely unknown, which limits our understanding of how ecosystems respond as a whole to anthropogenic drivers, climate and environmental variability4,5. Here we derive a set of ecosystem functions6 from a dataset of surface gas exchange measurements across major terrestrial biomes. We find that most of the variability within ecosystem functions (71.8%) is captured by three key axes. The first axis reflects maximum ecosystem productivity and is mostly explained by vegetation structure. The second axis reflects ecosystem water-use strategies and is jointly explained by variation in vegetation height and climate. The third axis, which represents ecosystem carbon-use efficiency, features a gradient related to aridity, and is explained primarily by variation in vegetation structure. We show that two state-of-the-art land surface models reproduce the first and most important axis of ecosystem functions. However, the models tend to simulate more strongly correlated functions than those observed, which limits their ability to accurately predict the full range of responses to environmental changes in carbon, water and energy cycling in terrestrial ecosystems7,8.

RevDate: 2021-09-16

Remeš V, Remešová E, Friedman NR, et al (2021)

Functional diversity of avian communities increases with canopy height: From individual behavior to continental-scale patterns.

Ecology and evolution, 11(17):11839-11851.

Vegetation complexity is an important predictor of animal species diversity. Specifically, taller vegetation should provide more potential ecological niches and thus harbor communities with higher species richness and functional diversity (FD). Resource use behavior is an especially important functional trait because it links species to their resource base with direct relevance to niche partitioning. However, it is unclear how exactly the diversity of resource use behavior changes with vegetation complexity. To address this question, we studied avian FD in relation to vegetation complexity along a continental-scale vegetation gradient. We quantified foraging behavior of passerine birds in terms of foraging method and substrate use at 21 sites (63 transects) spanning 3,000 km of woodlands and forests in Australia. We also quantified vegetation structure on 630 sampling points at the same sites. Additionally, we measured morphological traits for all 111 observed species in museum collections. We calculated individual-based, abundance-weighted FD in morphology and foraging behavior and related it to species richness and vegetation complexity (indexed by canopy height) using structural equation modeling, rarefaction analyses, and distance-based metrics. FD of morphology and foraging methods was best predicted by species richness. However, FD of substrate use was best predicted by canopy height (ranging 10-30 m), but only when substrates were categorized with fine resolution (17 categories), not when categorized coarsely (8 categories). These results suggest that, first, FD might increase with vegetation complexity independently of species richness, but whether it does so depends on the studied functional trait. Second, patterns found might be shaped by how finely we categorize functional traits. More complex vegetation provided larger "ecological space" with more resources, allowing the coexistence of more species with disproportionately more diverse foraging substrate use. We suggest that the latter pattern was driven by nonrandom accumulation of functionally distinct species with increasing canopy height.

RevDate: 2021-08-31
CmpDate: 2021-08-31

Guo J, Zhang M, Shang Q, et al (2021)

River Basin Cyberinfrastructure in the Big Data Era: An Integrated Observational Data Control System in the Heihe River Basin.

Sensors (Basel, Switzerland), 21(16):.

River basin cyberinfrastructure with the Internet of Things (IoT) as the core has brought watershed data science into the big data era, greatly improving data acquisition and sharing efficiency. However, challenges in analyzing, processing, and applying very large quantities of observational data remain. Given the observational needs in watershed research, we studied the construction of river basin cyberinfrastructure and developed an integrated observational data control system (IODCS). The IODCS is an important platform for processing large quantities of observational data, including automated collection, storage, analysis, processing, and release. This paper presents various aspects of the IODCS in detail, including the system's overall design, function realization, big data analysis methods, and integrated models. We took the middle reaches of the Heihe River Basin (HRB) as the application research area to show the performance of the developed system. Since the system began operation, it has automatically received, analyzed, and stored more than 1.4 billion observational data records, with an average of more than 14 million observational data records processed per month and up to 21,011 active users. The demonstrated results show that the IODCS can effectively leverage the processing capability of massive observational data and provide a new perspective for facilitating ecological and hydrological scientific research on the HRB.

RevDate: 2021-08-26

Abdullah MM, Al-Ali ZM, S Srinivasan (2021)

The use of UAV-based remote sensing to estimate biomass and carbon stock for native desert shrubs.

MethodsX, 8:101399.

Unmanned Aerial Vehicles (UAVs) have started to receive more attention in the ecological field in the past 15 years, as they provide very high-resolution imagery that ranges from meters to millimeters. Very high-resolution multispectral imagery obtained from UAVs can help in assessing and monitoring native desert vegetation. Thus, this study use UAVs to develop a method to estimate the biomass and carbon stock of native desert shrubs. The method integrates different techniques and software to monitor native plants' coverage, biomass, and carbon stock. The techniques used in this work are also applicable for other native desert shrubs in the region and could support ecosystem managers in assessing and monitoring arid ecosystems and restoration and revegetation programs. A three-stage image and data management are discussed, including: (1) fieldwork and image acquisition using UAVs, (2) image pre-processing, and (3) image processing using different techniques and software.•Determining shrub biomass is not restricted to multispectral data only but could be applicable for RGB data since it mainly depends on the DSM and DTM.•Allometric parameters could help in estimating desert shrub biomass which could be measured easily and rapidly using UAV imagery.•SVM Supervised classification could help in distinguishing between native shrubs and grasses.

RevDate: 2021-09-30
CmpDate: 2021-09-30

Sabatini FM, Bluhm H, Kun Z, et al (2021)

European primary forest database v2.0.

Scientific data, 8(1):220.

Primary forests, defined here as forests where the signs of human impacts, if any, are strongly blurred due to decades without forest management, are scarce in Europe and continue to disappear. Despite these losses, we know little about where these forests occur. Here, we present a comprehensive geodatabase and map of Europe's known primary forests. Our geodatabase harmonizes 48 different, mostly field-based datasets of primary forests, and contains 18,411 individual patches (41.1 Mha) spread across 33 countries. When available, we provide information on each patch (name, location, naturalness, extent and dominant tree species) and the surrounding landscape (biogeographical regions, protection status, potential natural vegetation, current forest extent). Using Landsat satellite-image time series (1985-2018) we checked each patch for possible disturbance events since primary forests were identified, resulting in 94% of patches free of significant disturbances in the last 30 years. Although knowledge gaps remain, ours is the most comprehensive dataset on primary forests in Europe, and will be useful for ecological studies, and conservation planning to safeguard these unique forests.

RevDate: 2022-01-11
CmpDate: 2022-01-11

Karabulut Aİ, Yazici-Karabulut B, Derin P, et al (2022)

Landfill siting for municipal solid waste using remote sensing and geographic information system integrated analytic hierarchy process and simple additive weighting methods from the point of view of a fast-growing metropolitan area in GAP area of Turkey.

Environmental science and pollution research international, 29(3):4044-4061.

The site selection process for municipal solid wastes (MSW) plays an important role in environmental impact studies by allowing the use of environmental design criteria in city and country planning. This process also includes the subject of urban planning due to its impact on the economy, ecology, and environmental health of the region. Urban growth is a phenomenon that is difficult to stop or limit in line with environmental, social, and economic changes and development. Therefore, the selection of solid waste landfill is of great importance in terms of ensuring a sustainable urban future. In the study, Landsat 5 and Landsat 8 satellite images, base map, soil, and geology maps were used for the integration of geospatial data. Each layer specified in the map has been formed using the spatial analysis potential of the ArcGIS10.5 software. In these digitized layers, weight scoring was made using the comparison matrix and the final suitability map was produced. All digital layers established in the generated maps were arranged according to the analytical hierarchy method (AHP) and subjected to the simple additive weighting (SAW) method. The results indicated that 13.51% of the total area was suitable for a sanitary landfill. As a result of this study, urban growth, population projection, and domestic solid waste volume of Sanliurfa province were determined. According to the 25-year population projection, the population in 2045 was approximately 4,471,938 people, and the cumulative waste volume was 27,415,627 m3. In addition, as a result of accepting the wastes of three metropolitan districts and seven district municipalities to the sanitary landfill, only "first candidate area" is the most and has been deemed appropriate. Given the ecological and environmental challenges (proximity to the city center, etc.) associated with the existing MSW sanitary landfill facility in Sanliurfa, the results of this study show that the geographic information system (GIS) integrated AHP and SAW method is an effective tool to assist decision makers to properly plan towards achieving a sustainable environment.

RevDate: 2021-09-21
CmpDate: 2021-09-21

Li J, Chen X, Kurban A, et al (2021)

Identification of conservation priorities in the major basins of Central Asia: Using an integrated GIS-based ordered weighted averaging approach.

Journal of environmental management, 298:113442.

Ecosystem services (ESs) provided by the major basins of Central Asia are critical to human well-being and have attracted the attention of the international community. The identification of conservation priorities is of great significance for the maintenance and protection of key ESs. In this study, we quantified the spatiotemporal changes of net primary productivity (NPP), soil conservation (SC), water yield (WY) and habitat quality (HQ) in the major basins of Central Asia from 1995 to 2015. In addition, a GIS-based ordered weighted averaging (OWA) multi-criterion valuation method was adopted to identify potential conservation areas under 11 scenarios. Conservation priorities were determined by comparing the conservation efficiency under each scenario. Then, a broad range of indicators were considered to distinguish the driving factors affecting ESs in conservation priorities. The results show that the average conservation efficiency in the Issyk-Kul Basin was the highest, followed by the Am Darya Basin, Ili-Balkhash Basin and Syr Darya Basin. We observed that the conservation efficiency of the four ESs declined continuously in the Ili-Balkhash Basin from 1995 to 2015, while it changed steadily in the other three basins. Correlation analysis indicated that natural factors (e.g., precipitation and topography) were the main driving factors of WY, SR and NPP in conservation priorities, while HQ was more affected by socio-economic factors (e.g., population density and both cropland and urban percentages). The identification of conservation priorities and their driving factors plays an important role in ensuring the ecological security of the lower reaches, regulating the regional water balance and stabilizing the climate pattern.

RevDate: 2021-08-06

Jones B, Goodall T, George PBL, et al (2021)

Beyond Taxonomic Identification: Integration of Ecological Responses to a Soil Bacterial 16S rRNA Gene Database.

Frontiers in microbiology, 12:682886.

High-throughput sequencing 16S rRNA gene surveys have enabled new insights into the diversity of soil bacteria, and furthered understanding of the ecological drivers of abundances across landscapes. However, current analytical approaches are of limited use in formalizing syntheses of the ecological attributes of taxa discovered, because derived taxonomic units are typically unique to individual studies and sequence identification databases only characterize taxonomy. To address this, we used sequences obtained from a large nationwide soil survey (GB Countryside Survey, henceforth CS) to create a comprehensive soil specific 16S reference database, with coupled ecological information derived from survey metadata. Specifically, we modeled taxon responses to soil pH at the OTU level using hierarchical logistic regression (HOF) models, to provide information on both the shape of landscape scale pH-abundance responses, and pH optima (pH at which OTU abundance is maximal). We identify that most of the soil OTUs examined exhibited a non-flat relationship with soil pH. Further, the pH optima could not be generalized by broad taxonomy, highlighting the need for tools and databases synthesizing ecological traits at finer taxonomic resolution. We further demonstrate the utility of the database by testing against geographically dispersed query 16S datasets; evaluating efficacy by quantifying matches, and accuracy in predicting pH responses of query sequences from a separate large soil survey. We found that the CS database provided good coverage of dominant taxa; and that the taxa indicating soil pH in a query dataset corresponded with the pH classifications of top matches in the CS database. Furthermore we were able to predict query dataset community structure, using predicted abundances of dominant taxa based on query soil pH data and the HOF models of matched CS database taxa. The database with associated HOF model outputs is released as an online portal for querying single sequences of interest (https://shiny-apps.ceh.ac.uk/ID-TaxER/), and flat files are made available for use in bioinformatic pipelines. The further development of advanced informatics infrastructures incorporating modeled ecological attributes along with new functional genomic information will likely facilitate large scale exploration and prediction of soil microbial functional biodiversity under current and future environmental change scenarios.

RevDate: 2022-07-31
CmpDate: 2022-03-11

Hagmann RK, Hessburg PF, Prichard SJ, et al (2021)

Evidence for widespread changes in the structure, composition, and fire regimes of western North American forests.

Ecological applications : a publication of the Ecological Society of America, 31(8):e02431.

Implementation of wildfire- and climate-adaptation strategies in seasonally dry forests of western North America is impeded by numerous constraints and uncertainties. After more than a century of resource and land use change, some question the need for proactive management, particularly given novel social, ecological, and climatic conditions. To address this question, we first provide a framework for assessing changes in landscape conditions and fire regimes. Using this framework, we then evaluate evidence of change in contemporary conditions relative to those maintained by active fire regimes, i.e., those uninterrupted by a century or more of human-induced fire exclusion. The cumulative results of more than a century of research document a persistent and substantial fire deficit and widespread alterations to ecological structures and functions. These changes are not necessarily apparent at all spatial scales or in all dimensions of fire regimes and forest and nonforest conditions. Nonetheless, loss of the once abundant influence of low- and moderate-severity fires suggests that even the least fire-prone ecosystems may be affected by alteration of the surrounding landscape and, consequently, ecosystem functions. Vegetation spatial patterns in fire-excluded forested landscapes no longer reflect the heterogeneity maintained by interacting fires of active fire regimes. Live and dead vegetation (surface and canopy fuels) is generally more abundant and continuous than before European colonization. As a result, current conditions are more vulnerable to the direct and indirect effects of seasonal and episodic increases in drought and fire, especially under a rapidly warming climate. Long-term fire exclusion and contemporaneous social-ecological influences continue to extensively modify seasonally dry forested landscapes. Management that realigns or adapts fire-excluded conditions to seasonal and episodic increases in drought and fire can moderate ecosystem transitions as forests and human communities adapt to changing climatic and disturbance regimes. As adaptation strategies are developed, evaluated, and implemented, objective scientific evaluation of ongoing research and monitoring can aid differentiation of warranted and unwarranted uncertainties.

RevDate: 2021-11-01
CmpDate: 2021-11-01

Rubin IN, Ispolatov I, M Doebeli (2021)

Evolution to alternative levels of stable diversity leaves areas of niche space unexplored.

PLoS computational biology, 17(7):e1008650.

One of the oldest and most persistent questions in ecology and evolution is whether natural communities tend to evolve toward saturation and maximal diversity. Robert MacArthur's classical theory of niche packing and the theory of adaptive radiations both imply that populations will diversify and fully partition any available niche space. However, the saturation of natural populations is still very much an open area of debate and investigation. Additionally, recent evolutionary theory suggests the existence of alternative evolutionary stable states (ESSs), which implies that some stable communities may not be fully saturated. Using models with classical Lotka-Volterra ecological dynamics and three formulations of evolutionary dynamics (a model using adaptive dynamics, an individual-based model, and a partial differential equation model), we show that following an adaptive radiation, communities can often get stuck in low diversity states when limited by mutations of small phenotypic effect. These low diversity metastable states can also be maintained by limited resources and finite population sizes. When small mutations and finite populations are considered together, it is clear that despite the presence of higher-diversity stable states, natural populations are likely not fully saturating their environment and leaving potential niche space unfilled. Additionally, within-species variation can further reduce community diversity from levels predicted by models that assume species-level homogeneity.

RevDate: 2021-12-15

Li YX, Rao YZ, Qi YL, et al (2021)

Deciphering Symbiotic Interactions of "Candidatus Aenigmarchaeota" with Inferred Horizontal Gene Transfers and Co-occurrence Networks.

mSystems, 6(4):e0060621.

"Candidatus Aenigmarchaeota" ("Ca. Aenigmarchaeota") represents one of the earliest proposed evolutionary branches within the Diapherotrites, Parvarchaeota, Aenigmarchaeota, Nanoarchaeota, and Nanohaloarchaeota (DPANN) superphylum. However, their ecological roles and potential host-symbiont interactions are still poorly understood. Here, eight metagenome-assembled genomes (MAGs) were reconstructed from hot spring ecosystems, and further in-depth comparative and evolutionary genomic analyses were conducted on these MAGs and other genomes downloaded from public databases. Although with limited metabolic capacities, we reported that "Ca. Aenigmarchaeota" in thermal environments harbor more genes related to carbohydrate metabolism than "Ca. Aenigmarchaeota" in nonthermal environments. Evolutionary analyses suggested that members from the Thaumarchaeota, Aigarchaeota, Crenarchaeota, and Korarchaeota (TACK) superphylum and Euryarchaeota contribute substantially to the niche expansion of "Ca. Aenigmarchaeota" via horizontal gene transfer (HGT), especially genes related to virus defense and stress responses. Based on co-occurrence network results and recent genetic exchanges among community members, we conjectured that "Ca. Aenigmarchaeota" may be symbionts associated with one MAG affiliated with the genus Pyrobaculum, though host specificity might be wide and variable across different "Ca. Aenigmarchaeota" organisms. This study provides significant insight into possible DPANN-host interactions and ecological roles of "Ca. Aenigmarchaeota." IMPORTANCE Recent advances in sequencing technology promoted the blowout discovery of super tiny microbes in the Diapherotrites, Parvarchaeota, Aenigmarchaeota, Nanoarchaeota, and Nanohaloarchaeota (DPANN) superphylum. However, the unculturable properties of the majority of microbes impeded our investigation of their behavior and symbiotic lifestyle in the corresponding community. By integrating horizontal gene transfer (HGT) detection and co-occurrence network analysis on "Candidatus Aenigmarchaeota" ("Ca. Aenigmarchaeota"), we made one of the first attempts to infer their putative interaction partners and further decipher the potential functional and genetic interactions between the symbionts. We revealed that HGTs contributed by members from the Thaumarchaeota, Aigarchaeota, Crenarchaeota, and Korarchaeota (TACK) superphylum and Euryarchaeota conferred "Ca. Aenigmarchaeota" with the ability to survive under different environmental stresses, such as virus infection, high temperature, and oxidative stress. This study demonstrates that the interaction partners might be inferable by applying informatics analyses on metagenomic sequencing data.

RevDate: 2021-09-28
CmpDate: 2021-09-28

Liu C, Yang M, Hou Y, et al (2021)

Ecosystem service multifunctionality assessment and coupling coordination analysis with land use and land cover change in China's coastal zones.

The Science of the total environment, 797:149033.

Ecosystem services (ESs) have received widespread attention worldwide for their potential to solve sustainability issues. However, extensive land use and land cover change (LUCC) driven by human activities has raised concerns regarding its impacts on ESs, especially in coastal zones. More importantly, spatial-temporal changes, their coupling relationships with LUCC, and their underlying drivers have not been thoroughly analyzed. This study focuses on China's coastal zones to investigate the spatial-temporal changes of ecosystem service multifunctionality (ESM) from 2000 to 2018. Coupling coordination degree (CCD) analysis of the relationship between ESM and comprehensive intensity of land use was applied to identify coastal cities with low-level coordination and their main drivers in 2018. The results show that: (1) the proportion with high levels of ESM decreased by 1.01% from 2000 to 2010 and then increased by 3.29% from 2010 to 2018; (2) the ESM of China's coastal zones present significant spatial heterogeneity, and the low levels of ESM are mainly distributed in the north and urban areas, while most areas in the southern coastal zones have high levels of ESM; (3) forest land is the leading land cover type for ESM, and China's forest conservation policies significantly contribute to the increase in ESM; (4) the CCD of most cities in the southern coastal zones, apart from Shanghai and the Pearl River Delta, is at a relatively high level and experiences no significant changes, while most cities in the northern coastal zones display an improving trend; (5) the land use type, landform type, and leaf area index are the determinants of ESM, and the annual average temperature, population density, and surface elevation are the greatest influences on the CCD. The findings of this study can inform ecological conservation and landscape planning and are beneficial to the sustainable development of coastal zones in China.

RevDate: 2021-08-11
CmpDate: 2021-08-11

Ali EOM, Babalghith AO, Bahathig AOS, et al (2021)

Prevalence of Larval Breeding Sites and Seasonal Variations of Aedes aegypti Mosquitoes (Diptera: Culicidae) in Makkah Al-Mokarramah, Saudi Arabia.

International journal of environmental research and public health, 18(14):.

Since 1994, dengue fever (DF) transmission rates have increased significantly in Saudi Arabia (KSA). Climatic, geographic, and demographic conditions make KSA especially suitable for DF's spread. Still, there are insufficient strategies for controlling the Aedes species that transmit DF virus (DENV). To develop effective management strategies, it is necessary to identify Aedes species and the ecological habitat of larvae in Makkah Al-Mokarramah, KSA. We conducted a longitudinal survey of Aedes mosquitoes in 14 localities from January 2015 to December 2015. World Health Organization (WHO) inspection kits for larvae were used to detect and sample larvae, along with pictorial keys. A total of 42,981 potential Aedes larval breeding sites were surveyed. A total of 5403 (12.6%) sites had at least one water source positive for Aedes aegypti (Linnaeus) mosquitoes. Among the total of 15,133 water sources surveyed within the sampled sites, 1815 (12.0%) were positive for Aedes aegypti. Aedes aegypti was the only Aedes species identified in the course of the survey. The presence of such a large immature population may indicate an imminent outbreak of DF in the near future unless proper implementation of control and elimination of Aedes&nbsp;aegypti are undertaken. Additionally, the adaptation of Aedes&nbsp;aegypti to the arid climate of Makkah needs further investigation.

RevDate: 2022-05-17

Coutinho FH, Zaragoza-Solas A, López-Pérez M, et al (2021)

RaFAH: Host prediction for viruses of Bacteria and Archaea based on protein content.

Patterns (New York, N.Y.), 2(7):100274.

Culture-independent approaches have recently shed light on the genomic diversity of viruses of prokaryotes. One fundamental question when trying to understand their ecological roles is: which host do they infect? To tackle this issue we developed a machine-learning approach named Random Forest Assignment of Hosts (RaFAH), that uses scores to 43,644 protein clusters to assign hosts to complete or fragmented genomes of viruses of Archaea and Bacteria. RaFAH displayed performance comparable with that of other methods for virus-host prediction in three different benchmarks encompassing viruses from RefSeq, single amplified genomes, and metagenomes. RaFAH was applied to assembled metagenomic datasets of uncultured viruses from eight different biomes of medical, biotechnological, and environmental relevance. Our analyses led to the identification of 537 sequences of archaeal viruses representing unknown lineages, whose genomes encode novel auxiliary metabolic genes, shedding light on how these viruses interfere with the host molecular machinery. RaFAH is available at https://sourceforge.net/projects/rafah/.

RevDate: 2021-07-16

Rocchini D, Thouverai E, Marcantonio M, et al (2021)

rasterdiv-An Information Theory tailored R package for measuring ecosystem heterogeneity from space: To the origin and back.

Methods in ecology and evolution, 12(6):1093-1102.

Ecosystem heterogeneity has been widely recognized as a key ecological indicator of several ecological functions, diversity patterns and change, metapopulation dynamics, population connectivity or gene flow.In this paper, we present a new R package-rasterdiv-to calculate heterogeneity indices based on remotely sensed data. We also provide an ecological application at the landscape scale and demonstrate its power in revealing potentially hidden heterogeneity patterns.The rasterdiv package allows calculating multiple indices, robustly rooted in Information Theory, and based on reproducible open-source algorithms.

RevDate: 2022-05-31
CmpDate: 2021-11-11

Levi A, Z Barnett-Itzhaki (2021)

Effects of chronic exposure to ambient air pollutants, demographic, and socioeconomic factors on COVID-19 morbidity: The Israeli case study.

Environmental research, 202:111673.

BACKGROUND: Recent studies conducted in several OECD countries have shown that chronic exposure to elevated levels of air pollutants (especially PM2.5, PM10 and NOx), might negatively impact COVID-19 morbidity and mortality rates. The aim of this study was to examine the association between chronic exposure to air pollution in Israeli cities and towns, their demographic and socioeconomic status, and COVID-19 morbidity, during the three local morbidity waves.

METHODS: We examined the associations between: (a) annual average concentrations of NOx, CO, PM10, PM2.5 and SO2 in 2016-2019, and demographic and socioeconomic parameters, and (b) COVID-19 positive cases in 279 Israeli cities and towns, in the four state-wide morbidity peaks: 1st wave peak: March 31st, 2020; 2nd wave peaks: July 24th and September 27th, 2020, and the 3rd wave peak: January 17th, 2021, which occurred after the beginning of the nationwide vaccination campaign. These associations were calculated using both Spearman correlations and multivariate linear regressions.

RESULTS: We found statistically significant positive correlations between the concentrations of most pollutants in 2016-19 and COVID-19 morbidity rate at the first three timepoints but not the 4th (January 17th, 2021). Population density and city/town total population were also positively associated with the COVID-19 morbidity rates at these three timepoints, but not the 4th, in which socioeconomic parameters were more dominant - we found a statistically significant negative correlation between socioeconomic cluster and COVID-19 morbidity. In addition, all multivariate models including PM2.5 concentrations were statistically significant, and PM2.5 concentrations were positively associated with the COVID-19 morbidity rates in all models.

CONCLUSIONS: We found a nationwide association between population chronic exposure to five main air pollutants in Israeli cities and towns, and COVID-19 morbidity rates during two of the three morbidity waves experienced in Israel. The widespread morbidity that was related to socioeconomic factors during the 3rd wave, emphasizes the need for special attention to morbidity prevention in socioeconomically vulnerable populations and especially in large household communities. Nevertheless, this ecological study has several limitations, such as the inability to draw conclusions about causality or mechanisms of action. The growing body of evidence, regarding association between exacerbated COVID-19 morbidity and mortality rates and long-term chronic exposure to elevated concentrations of air pollutants should serve as a wake-up call to policy makers regarding the urgent need to reduce air pollution and its harmful effects.

RevDate: 2021-07-21
CmpDate: 2021-07-21

Mehrshad M, Lopez-Fernandez M, Sundh J, et al (2021)

Energy efficiency and biological interactions define the core microbiome of deep oligotrophic groundwater.

Nature communications, 12(1):4253.

While oligotrophic deep groundwaters host active microbes attuned to the low-end of the bioenergetics spectrum, the ecological constraints on microbial niches in these ecosystems and their consequences for microbiome convergence are unknown. Here, we provide a genome-resolved, integrated omics analysis comparing archaeal and bacterial communities in disconnected fracture fluids of the Fennoscandian Shield in Europe. Leveraging a dataset that combines metagenomes, single cell genomes, and metatranscriptomes, we show that groundwaters flowing in similar lithologies offer fixed niches that are occupied by a common core microbiome. Functional expression analysis highlights that these deep groundwater ecosystems foster diverse, yet cooperative communities adapted to this setting. We suggest that these communities stimulate cooperation by expression of functions related to ecological traits, such as aggregate or biofilm formation, while alleviating the burden on microorganisms producing compounds or functions that provide a collective benefit by facilitating reciprocal promiscuous metabolic partnerships with other members of the community. We hypothesize that an episodic lifestyle enabled by reversible bacteriostatic functions ensures the subsistence of the oligotrophic deep groundwater microbiome.

RevDate: 2022-04-18
CmpDate: 2022-01-06

Queiroz N, Humphries NE, Couto A, et al (2021)

Reply to: Caution over the use of ecological big data for conservation.

Nature, 595(7866):E20-E28.

RevDate: 2022-04-18
CmpDate: 2022-01-06

Harry AV, JM Braccini (2021)

Caution over the use of ecological big data for conservation.

Nature, 595(7866):E17-E19.

RevDate: 2021-12-14
CmpDate: 2021-12-03

Pauling CD, Finke DL, DM Anderson (2021)

Interrelationship of soil moisture and temperature to sylvatic plague cycle among prairie dogs in the Western United States.

Integrative zoology, 16(6):852-867.

Plague, caused by Yersinia pestis, is a flea-borne disease that is endemic in areas throughout the world due to its successful maintenance in a sylvatic cycle, mainly in areas with temperate climates. Burrowing rodents are thought to play a key role in the enzootic maintenance as well as epizootic outbreaks of plague. In the United States, prairie dogs (Cynomys), rodents (Muridae), and ground squirrels (Spermophilus) are susceptible to infection and are parasitized by fleas that transmit plague. In particular, prairie dogs can experience outbreaks that rapidly spread, which can lead to extirpation of colonies. A number of ecological parameters, including climate, are associated with these epizootics. In this study, we asked whether soil parameters, primarily moisture and temperature, are associated with outbreaks of plague in black-tailed prairie dogs and Gunnison's prairie dogs in the Western United States, and at what depth these associations were apparent. We collected publicly available county-level information on the occurrence of population declines or colony extirpation, while historical soil data was collected from SCAN and USCRN stations in counties and states where prairie dogs have been located. The analysis suggests that soil moisture at lower depths correlates with colony die-offs, in addition to temperature near the surface, with key differences within the landscape ecology that impact the occurrence of plague. Overall, the model suggests that the burrow environment may play a significant role in the epizootic spread of disease amongst black-tailed and Gunnison's prairie dogs.

RevDate: 2022-04-05
CmpDate: 2022-04-04

Justus J, S Wakil (2021)

The algorithmic turn in conservation biology: Characterizing progress in ethically-driven sciences.

Studies in history and philosophy of science, 88:181-192.

As a discipline distinct from ecology, conservation biology emerged in the 1980s as a rigorous science focused on protecting biodiversity. Two algorithmic breakthroughs in information processing made this possible: place-prioritization algorithms and geographical information systems. They provided defensible, data-driven methods for designing reserves to conserve biodiversity that obviated the need for largely intuitive and highly problematic appeals to ecological theory at the time. But the scientific basis of these achievements and whether they constitute genuine scientific progress has been criticized. We counter by pointing out important inaccuracies about the science and rejecting the apparent theory-first focus. More broadly, the case study reveals significant limitations of the predominant epistemic-semantic conceptions of scientific progress and the considerable merits of pragmatic, practically-oriented accounts.

RevDate: 2021-11-01
CmpDate: 2021-11-01

Weinstein BG, Graves SJ, Marconi S, et al (2021)

A benchmark dataset for canopy crown detection and delineation in co-registered airborne RGB, LiDAR and hyperspectral imagery from the National Ecological Observation Network.

PLoS computational biology, 17(7):e1009180.

Broad scale remote sensing promises to build forest inventories at unprecedented scales. A crucial step in this process is to associate sensor data into individual crowns. While dozens of crown detection algorithms have been proposed, their performance is typically not compared based on standard data or evaluation metrics. There is a need for a benchmark dataset to minimize differences in reported results as well as support evaluation of algorithms across a broad range of forest types. Combining RGB, LiDAR and hyperspectral sensor data from the USA National Ecological Observatory Network's Airborne Observation Platform with multiple types of evaluation data, we created a benchmark dataset to assess crown detection and delineation methods for canopy trees covering dominant forest types in the United States. This benchmark dataset includes an R package to standardize evaluation metrics and simplify comparisons between methods. The benchmark dataset contains over 6,000 image-annotated crowns, 400 field-annotated crowns, and 3,000 canopy stem points from a wide range of forest types. In addition, we include over 10,000 training crowns for optional use. We discuss the different evaluation data sources and assess the accuracy of the image-annotated crowns by comparing annotations among multiple annotators as well as overlapping field-annotated crowns. We provide an example submission and score for an open-source algorithm that can serve as a baseline for future methods.

RevDate: 2021-11-18
CmpDate: 2021-11-18

Murareanu BM, Sukhdeo R, Qu R, et al (2021)

Generation of a Microsporidia Species Attribute Database and Analysis of the Extensive Ecological and Phenotypic Diversity of Microsporidia.

mBio, 12(3):e0149021.

Microsporidia are a large group of fungus-related obligate intracellular parasites. Though many microsporidia species have been identified over the past 160 years, depiction of the full diversity of this phylum is lacking. To systematically describe the characteristics of these parasites, we created a database of 1,440 species and their attributes, including the hosts they infect and spore characteristics. We find that microsporidia have been reported to infect 16 metazoan and 4 protozoan phyla, with smaller phyla being underrepresented. Most species are reported to infect only a single host, but those that are generalists are also more likely to infect a broader set of host tissues. Strikingly, polar tubes are threefold longer in species that infect tissues besides the intestine, suggesting that polar tube length is a determinant of tissue specificity. Phylogenetic analysis revealed four clades which each contain microsporidia that infect hosts from all major habitats. Although related species are more likely to infect similar hosts, we observe examples of changes in host specificity and convergent evolution. Taken together, our results show that microsporidia display vast diversity in their morphology and the hosts they infect, illustrating the flexibility of these parasites to evolve new traits. IMPORTANCE Microsporidia are a large group of parasites that cause death and disease in humans and many agriculturally important animal species. To fully understand the diverse properties of these parasites, we curated species reports from the last 160 years. Using these data, we describe when and where microsporidia were identified and what types of animals and host tissues these parasites infect. Microsporidia infect hosts using a conserved apparatus known as the polar tube. We observe that the length of this tube is correlated with the tissues that are being infected, suggesting that the polar tube controls where within the animals that the parasite infects. Finally, we show that microsporidia species often exist in multiple environments and are flexible in their ability to evolve new traits. Our study provides insight into the ecology and evolution of microsporidia and provides a useful resource to further understand these fascinating parasites.

RevDate: 2022-03-21
CmpDate: 2022-03-21

Mairal M, Chown SL, Shaw J, et al (2022)

Human activity strongly influences genetic dynamics of the most widespread invasive plant in the sub-Antarctic.

Molecular ecology, 31(6):1649-1665.

The link between the successful establishment of alien species and propagule pressure is well-documented. Less known is how humans influence the post-introduction dynamics of invasive alien populations. The latter requires studying parallel invasions by the same species in habitats that are differently impacted by humans. We analysed microsatellite and genome size variation, and then compared the genetic diversity and structure of invasive Poa annua L. on two sub-Antarctic islands: human-occupied Marion Island and unoccupied Prince Edward Island. We also carried out niche modelling to map the potential distribution of the species on both islands. We found high levels of genetic diversity and evidence for extensive admixture between genetically distinct lineages of P. annua on Marion Island. By contrast, the Prince Edward Island populations showed low genetic diversity, no apparent admixture, and had smaller genomes. On both islands, high genetic diversity was apparent at human landing sites, and on Marion Island, also around human settlements, suggesting that these areas received multiple introductions and/or acted as initial introduction sites and secondary sources (bridgeheads) for invasive populations. More than 70 years of continuous human activity associated with a meteorological station on Marion Island led to a distribution of this species around human settlements and along footpaths, which facilitates ongoing gene flow among geographically separated populations. By contrast, this was not the case for Prince Edward Island, where P. annua populations showed high genetic structure. The high levels of genetic variation and admixture in P. annua facilitated by human activity, coupled with high habitat suitability on both islands, suggest that P. annua is likely to increase its distribution and abundance in the future.

RevDate: 2022-04-05
CmpDate: 2022-04-04

Tanner RL, Grover N, Anderson ML, et al (2022)

Examining Cultural Structures and Functions in Biology.

Integrative and comparative biology, 61(6):2282-2293.

Scientific culture and structure organize biological sciences in many ways. We make choices concerning the systems and questions we study. Our research then amplifies these choices into factors that influence the directions of future research by shaping our hypotheses, data analyses, interpretation, publication venues, and dissemination via other methods. But our choices are shaped by more than objective curiosity-we are influenced by cultural paradigms reinforced by societal upbringing and scientific indoctrination during training. This extends to the systems and data that we consider to be ethically obtainable or available for study, and who is considered qualified to do research, ask questions, and communicate about research. It is also influenced by the profitability of concepts like open-access-a system designed to improve equity, but which enacts gatekeeping in unintended but foreseeable ways. Creating truly integrative biology programs will require more than intentionally developing departments or institutes that allow overlapping expertise in two or more subfields of biology. Interdisciplinary work requires the expertise of large and diverse teams of scientists working together-this is impossible without an authentic commitment to addressing, not denying, racism when practiced by individuals, institutions, and cultural aspects of academic science. We have identified starting points for remedying how our field has discouraged and caused harm, but we acknowledge there is a long path forward. This path must be paved with field-wide solutions and institutional buy-in: our solutions must match the scale of the problem. Together, we can integrate-not reintegrate-the nuances of biology into our field.

RevDate: 2022-07-16
CmpDate: 2021-07-07

Borko Š, Trontelj P, Seehausen O, et al (2021)

A subterranean adaptive radiation of amphipods in Europe.

Nature communications, 12(1):3688.

Adaptive radiations are bursts of evolutionary species diversification that have contributed to much of the species diversity on Earth. An exception is modern Europe, where descendants of ancient adaptive radiations went extinct, and extant adaptive radiations are small, recent and narrowly confined. However, not all legacy of old radiations has been lost. Subterranean environments, which are dark and food-deprived, yet buffered from climate change, have preserved ancient lineages. Here we provide evidence of an entirely subterranean adaptive radiation of the amphipod genus Niphargus, counting hundreds of species. Our modelling of lineage diversification and evolution of morphological and ecological traits using a time-calibrated multilocus phylogeny suggests a major adaptive radiation, comprised of multiple subordinate adaptive radiations. Their spatio-temporal origin coincides with the uplift of carbonate massifs in South-Eastern Europe 15 million years ago. Emerging subterranean environments likely provided unoccupied, predator-free space, constituting ecological opportunity, a key trigger of adaptive radiation. This discovery sheds new light on the biodiversity of Europe.

RevDate: 2021-06-15
CmpDate: 2021-06-09

Colella JP, Bates J, Burneo SF, et al (2021)

Leveraging natural history biorepositories as a global, decentralized, pathogen surveillance network.

PLoS pathogens, 17(6):e1009583.

The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic reveals a major gap in global biosecurity infrastructure: a lack of publicly available biological samples representative across space, time, and taxonomic diversity. The shortfall, in this case for vertebrates, prevents accurate and rapid identification and monitoring of emerging pathogens and their reservoir host(s) and precludes extended investigation of ecological, evolutionary, and environmental associations that lead to human infection or spillover. Natural history museum biorepositories form the backbone of a critically needed, decentralized, global network for zoonotic pathogen surveillance, yet this infrastructure remains marginally developed, underutilized, underfunded, and disconnected from public health initiatives. Proactive detection and mitigation for emerging infectious diseases (EIDs) requires expanded biodiversity infrastructure and training (particularly in biodiverse and lower income countries) and new communication pipelines that connect biorepositories and biomedical communities. To this end, we highlight a novel adaptation of Project ECHO's virtual community of practice model: Museums and Emerging Pathogens in the Americas (MEPA). MEPA is a virtual network aimed at fostering communication, coordination, and collaborative problem-solving among pathogen researchers, public health officials, and biorepositories in the Americas. MEPA now acts as a model of effective international, interdisciplinary collaboration that can and should be replicated in other biodiversity hotspots. We encourage deposition of wildlife specimens and associated data with public biorepositories, regardless of original collection purpose, and urge biorepositories to embrace new specimen sources, types, and uses to maximize strategic growth and utility for EID research. Taxonomically, geographically, and temporally deep biorepository archives serve as the foundation of a proactive and increasingly predictive approach to zoonotic spillover, risk assessment, and threat mitigation.

RevDate: 2021-07-14

Cadar D, Schmidt-Chanasit J, D Tappe (2021)

Genomic and Micro-Evolutionary Features of Mammalian 2 orthobornavirus (Variegated Squirrel Bornavirus 1, VSBV-1).

Microorganisms, 9(6):.

Mammalian 2 orthobornavirus (VSBV-1) is an emerging zoonotic pathogen discovered in several exotic squirrel species and associated with fatal human encephalitis. The dynamics of VSBV-1 spread and evolution in its presumed natural hosts are unknown. Here, we present the phylogeny, micro-evolution, cross-species transmission and spread of VSBV-1 at a temporal and spatial resolution within the limits of animal husbandry. The results showed that VSBV-1 can be classified into six distinct groups and that the most recent common ancestor of the known German strains emerged at least 20 years ago. We here demonstrate that the genetic diversity of the VSBV-1 groups is shaped primarily by in situ evolution and most of the amino acid changes are deleterious polymorphisms removed by purifying selection. Evidence of adaptive evolution has been found in the G and L genes which might have an influence on transmission fitness. Furthermore, there was also evidence for some form of adaptive changes in the glycoprotein which suggests that many sites might be subjected to positive pressure evolving under episodic directional selection, indicating past occurrence of positive selection. Host switching events were detected as dominant evolutionary mechanisms driving the virus-host associations. Virus spread by animal trade followed by subsequent local micro-evolution in zoos and holdings is responsible for diversifying strains. Time-resolved phylogeny indicated that Prevost's squirrels might be the original squirrel species carrying and seeding the virus in Germany. This study provides the first insight into the ecology and micro-evolutionary dynamics of this novel viral pathogen in the captive exotic squirrel population under artificial ecological conditions (zoos and animal husbandry) and co-housing of different squirrel species.

RevDate: 2021-10-01
CmpDate: 2021-10-01

Miller KE, Polaszek A, DM Evans (2021)

A dearth of data: fitting parasitoids into ecological networks.

Trends in parasitology, 37(10):863-874.

Studying parasitoids can provide insights into global diversity estimates, climate change impacts, and agroecosystem service provision. However, this potential remains largely untapped due to a lack of data on how parasitoids interact with other organisms. Ecological networks are a useful tool for studying and exploiting the impacts of parasitoids, but their construction is hindered by the magnitude of undescribed parasitoid species, a sparse knowledge of host ranges, and an under-representation of parasitoids within DNA-barcode databases (we estimate <5% have a barcode). Here, we advocate the use of DNA metabarcoding to construct the host-parasitoid component of multilayer networks. While the incorporation of parasitoids into network-based analyses has far ranging applications, we focus on its potential for assessing ecosystem service provision within agroecosystems.

RevDate: 2021-07-08
CmpDate: 2021-07-08

Wright ES, Gupta R, KH Vetsigian (2021)

Multi-stable bacterial communities exhibit extreme sensitivity to initial conditions.

FEMS microbiology ecology, 97(6):.

Microbial communities can have dramatically different compositions even among similar environments. This might be due to the existence of multiple alternative stable states, yet there exists little experimental evidence supporting this possibility. Here, we gathered a large collection of absolute population abundances capturing population dynamics in one- to four-strain communities of soil bacteria with a complex life cycle in a feast-or-famine environment. This dataset led to several observations: (i) some pairwise competitions resulted in bistability with a separatrix near a 1:1 initial ratio across a range of population densities; (ii) bistability propagated to multi-stability in multispecies communities; and (iii) replicate microbial communities reached different stable states when starting close to initial conditions separating basins of attraction, indicating finite-sized regions where the dynamics are unpredictable. The generalized Lotka-Volterra equations qualitatively captured most competition outcomes but were unable to quantitatively recapitulate the observed dynamics. This was partly due to complex and diverse growth dynamics in monocultures that ranged from Allee effects to nonmonotonic behaviors. Overall, our results highlight that multi-stability might be generic in multispecies communities and, combined with ecological noise, can lead to unpredictable community assembly, even in simple environments.

RevDate: 2021-05-31
CmpDate: 2021-05-31

Rabosky DL, RBJ Benson (2021)

Ecological and biogeographic drivers of biodiversity cannot be resolved using clade age-richness data.

Nature communications, 12(1):2945.

Estimates of evolutionary diversification rates - speciation and extinction - have been used extensively to explain global biodiversity patterns. Many studies have analyzed diversification rates derived from just two pieces of information: a clade's age and its extant species richness. This "age-richness rate" (ARR) estimator provides a convenient shortcut for comparative studies, but makes strong assumptions about the dynamics of species richness through time. Here we demonstrate that use of the ARR estimator in comparative studies is problematic on both theoretical and empirical grounds. We prove mathematically that ARR estimates are non-identifiable: there is no information in the data for a single clade that can distinguish a process with positive net diversification from one where net diversification is zero. Using paleontological time series, we demonstrate that the ARR estimator has no predictive ability for real datasets. These pathologies arise because the ARR inference procedure yields "point estimates" that have been computed under a saturated statistical model with zero degrees of freedom. Although ARR estimates remain useful in some contexts, they should be avoided for comparative studies of diversification and species richness.

RevDate: 2021-05-25
CmpDate: 2021-05-24

Karatayev VA, Vasconcelos VV, Lafuite AS, et al (2021)

A well-timed shift from local to global agreements accelerates climate change mitigation.

Nature communications, 12(1):2908.

Recent attempts at cooperating on climate change mitigation highlight the limited efficacy of large-scale negotiations, when commitment to mitigation is costly and initially rare. Deepening existing voluntary mitigation pledges could require more stringent, legally-binding agreements that currently remain untenable at the global scale. Building-blocks approaches promise greater success by localizing agreements to regions or few-nation summits, but risk slowing mitigation adoption globally. Here, we show that a well-timed policy shift from local to global legally-binding agreements can dramatically accelerate mitigation compared to using only local, only global, or both agreement types simultaneously. This highlights the scale-specific roles of mitigation incentives: local agreements promote and sustain mitigation commitments in early-adopting groups, after which global agreements rapidly draw in late-adopting groups. We conclude that focusing negotiations on local legally-binding agreements and, as these become common, a renewed pursuit of stringent, legally-binding world-wide agreements could best overcome many current challenges facing climate mitigation.

RevDate: 2022-07-16
CmpDate: 2021-07-23

Baptiste YM (2021)

Digital Feast and Physical Famine: The Altered Ecosystem of Anatomy Education due to the Covid-19 Pandemic.

Anatomical sciences education, 14(4):399-407.

This article explores the effects of the coronavirus disease 2019 (Covid-19) pandemic on the evolution of both physical and digital cadavers within the unique ecosystem of the anatomy laboratory. A physical cadaver is a traditional and established learning tool in anatomy education, whereas a digital cadaver is a relatively recent phenomenon. The Covid-19 pandemic presented a major disturbance and disruption to all levels and types of education, including anatomy education. This article constructs a conceptual metaphor between a typical anatomy laboratory and an ecosystem, and considers the affordances, constraints, and changing roles of physical and digital cadavers within anatomy education through an ecological lens. Adaptation of physical and digital cadavers during the disturbance is analyzed, and the resiliency of digital cadaver technology is recognized. The evolving role of the digital cadaver is considered in terms of increasing accessibility and inclusivity within the anatomy laboratory ecosystem of the future.

RevDate: 2021-09-29
CmpDate: 2021-09-23

Huettmann F, K Hueffer (2021)

The ecological niche of reported rabies cases in Canada is similar to Alaska.

Zoonoses and public health, 68(6):677-683.

The ecology of rabies in the circumpolar North is still not well understood. We use machine learning, a geographic information system and data explicit in time and space obtained for reported rabies cases and predictors in Canada to develop an ecological niche model for the distribution of reported rabies cases in the American north (Alaska and Canada). The ecological niche model based on reported rabies cases in Canada predicted reported rabies cases in Alaska, suggesting a rather robust inference and even similar drivers on a continental scale. As found in Alaska, proximity to human infrastructure-specifically along the coast-was a strong predictor in the detection of rabies cases in Canada. Also, this finding highlights the need for a more systematic landscape sampling for rabies infection model predictions to better understand and tackle the ecology of this important zoonotic disease on a landscape scale at some distance from human infrastructure in wilderness areas.

RevDate: 2021-05-07

Santos FP, Levin SA, VV Vasconcelos (2021)

Biased perceptions explain collective action deadlocks and suggest new mechanisms to prompt cooperation.

iScience, 24(4):102375.

When individuals face collective action problems, their expectations about others' willingness to contribute affect their motivation to cooperate. Individuals, however, often misperceive the cooperation levels in a population. In the context of climate action, people underestimate the pro-climate positions of others. Designing incentives to enable cooperation and a sustainable future must thereby consider how social perception biases affect collective action. We propose a theoretical model and investigate the effect of social perception bias in non-linear public goods games. We show that different types of bias play a distinct role in cooperation dynamics. False uniqueness (underestimating own views) and false consensus (overestimating own views) both explain why communities get locked in suboptimal states. Such dynamics also impact the effectiveness of typical monetary incentives, such as fees. Our work contributes to understanding how targeting biases, e.g., by changing the information available to individuals, can comprise a fundamental mechanism to prompt collective action.

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In the early 1990's, Robert Robbins was a faculty member at Johns Hopkins, where he directed the informatics core of GDB — the human gene-mapping database of the international human genome project. To share papers with colleagues around the world, he set up a small paper-sharing section on his personal web page. This small project evolved into The Electronic Scholarly Publishing Project.

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In 1995, Robbins became the VP/IT of the Fred Hutchinson Cancer Research Center in Seattle, WA. Soon after arriving in Seattle, Robbins secured funding, through the ELSI component of the US Human Genome Project, to create the original ESP.ORG web site, with the formal goal of providing free, world-wide access to the literature of classical genetics.

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This is a must read book for anyone with an interest in invasion biology. The full title of the book lays out the author's premise — The New Wild: Why Invasive Species Will Be Nature's Salvation. Not only is species movement not bad for ecosystems, it is the way that ecosystems respond to perturbation — it is the way ecosystems heal. Even if you are one of those who is absolutely convinced that invasive species are actually "a blight, pollution, an epidemic, or a cancer on nature", you should read this book to clarify your own thinking. True scientific understanding never comes from just interacting with those with whom you already agree. R. Robbins

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Papers in Classical Genetics

The ESP began as an effort to share a handful of key papers from the early days of classical genetics. Now the collection has grown to include hundreds of papers, in full-text format.

Digital Books

Along with papers on classical genetics, ESP offers a collection of full-text digital books, including many works by Darwin (and even a collection of poetry — Chicago Poems by Carl Sandburg).

Timelines

ESP now offers a much improved and expanded collection of timelines, designed to give the user choice over subject matter and dates.

Biographies

Biographical information about many key scientists.

Selected Bibliographies

Bibliographies on several topics of potential interest to the ESP community are now being automatically maintained and generated on the ESP site.

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