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Bibliography on: Ecological Informatics

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ESP: PubMed Auto Bibliography 05 Jul 2020 at 01:32 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: 2020-07-02

Ferguson AW, Muloi D, Ngatia DK, et al (2020)

Volunteer based approach to dog vaccination campaigns to eliminate human rabies: Lessons from Laikipia County, Kenya.

PLoS neglected tropical diseases, 14(7):e0008260 pii:PNTD-D-19-01492.

BACKGROUND: An estimated 59,000 people die from rabies annually, with 99% of those deaths attributable to bites from domestic dogs (Canis lupus familiaris). This preventable Neglected Tropical Disease has a large impact across continental Africa, especially for rural populations living in close contact with livestock and wildlife. Mass vaccinations of domestic dogs are effective at eliminating rabies but require large amounts of resources, planning, and political will to implement. Grassroots campaigns provide an alternative method to successful implementation of rabies control but remain understudied in their effectiveness to eliminate the disease from larger regions.

We report on the development, implementation, and effectiveness of a grassroots mass dog rabies vaccination campaign in Kenya, the Laikipia Rabies Vaccination Campaign. During 2015-2017, a total of 13,155 domestic dogs were vaccinated against rabies in 17 communities covering approximately 1500 km2. Based on an estimated population size of 34,275 domestic dogs, percent coverages increased across years, from 2% in 2015 to 24% in 2017, with only 3 of 38 community-years of vaccination exceeding the 70% target. The average cost of vaccinating an animal was $3.44 USD with in-kind contributions and $7.44 USD without in-kind contributions.

CONCLUSIONS/SIGNIFICANCE: The evolution of the Laikipia Rabies Vaccination Campaign from a localized volunteer-effort to a large-scale program attempting to eliminate rabies at the landscape scale provides a unique opportunity to examine successes, failures, and challenges facing grassroots campaigns. Success, in the form of vaccinating more dogs across the study area, was relatively straightforward to achieve. However, lack of effective post-vaccination monitoring and education programs, limited funding, and working in diverse community types appeared to hinder achievement of 70% coverage levels. These results indicate that grassroots campaigns will inevitably be faced with a philosophical question regarding the value of local impacts versus their contributions to a larger effort to eliminate rabies at the regional, country, or global scale.

RevDate: 2020-07-01

Zhu LY, Chen YY, Liu J, et al (2020)

[Spatio-temporal Evolution and Relationship of Water Environment Quality and Phytoplankton Community in Wenyu River].

Huan jing ke xue= Huanjing kexue, 41(2):702-712.

The Wenyu River is an important ecological corridor of Beijing. In this study, the spatio-temporal dynamics of water quality and phytoplankton community in the Wenyu River in 2006, 2011, and 2018, as well as their relationship were thoroughly analyzed by historical data analysis and field surveys. Results show that the water quality in the Wenyu River improved significantly from serious pollution owing to pollution containment. The major water pollutant has shifted from ammonia nitrogen (NH4+-N) to total nitrogen (TN). Compared with 2011, the average multiple of NH4+-N and total nitrogen TN exceeding the national standard were reduced by factors of 0.29-0.33 and 2.77-2.39, respectively, in 2018. The average concentration of NH4+-N and TN decreased from 15.52-19.16 mg·L-1 and 20.21-19.58 mg·L-1 in 2011 to 1.93-2.66 mg·L-1 and 5.66-6.79 mg·L-1 in 2018. Moreover, dissolved oxygen (DO) and NH4+-N concentrations in the Wenyu River and its tributaries, the Qinghe River, almost met requirements of their water function zoning target. Corresponding with the water quality improvement, the phytoplankton and community species increased dramatically. Phytoplankton species increased from 6 to 8 phyla, as well as community species. The dominant species changed from Chlorophyta in 2006 to the Cyanophyta in 2011, then to Bacillariophyta in 2018. The Shannon-Wiener diversity index (H') and evenness Pielou index (J) had improved. However, the major dominant species such as Cyclotella and Melosira persisted, and the Wenyu River was still in the eutrophication state in 2018. Statistical analysis results indicated that Cyanophyta, Bacillariophyta, and other algae abundance were significantly correlated with DO, pH, NH4+-N, TN, and TP.

RevDate: 2020-06-26

Zhou Y, Rodriguez J, Fisher N, et al (2020)

Ecological Drivers and Sex-Based Variation in Body Size and Shape in the Queensland Fruit Fly, Bactrocera tryoni (Diptera: Tephritidae).

Insects, 11(6): pii:insects11060390.

The Queensland fruit fly (Bactrocera tryoni; Q-fly) is an Australian endemic horticultural pest species, which has caused enormous economic losses. It has the potential to expand its range to currently Q-fly-free areas and poses a serious threat to the Australian horticultural industry. A large number of studies have investigated the correlation between environmental factors and Q-fly development, reproduction, and expansion. However, it is still not clear how Q-fly morphological traits vary with the environment. Our study focused on three morphological traits (body size, wing shape, and fluctuating asymmetry) in Q-fly samples collected from 1955 to 1965. We assessed how these traits vary by sex, and in response to latitude, environmental variables, and geographic distance. First, we found sexual dimorphism in body size and wing shape, but not in fluctuating asymmetry. Females had a larger body size but shorter and wider wings than males, which may be due to reproductive and/or locomotion differences between females and males. Secondly, the body size of Q-flies varied with latitude, which conforms to Bergmann's rule. Finally, we found Q-fly wing shape was more closely related to temperature rather than aridity, and low temperature and high aridity may lead to high asymmetry in Q-fly populations.

RevDate: 2020-06-23

Cansler CA, Hood SM, Varner JM, et al (2020)

The Fire and Tree Mortality Database, for empirical modeling of individual tree mortality after fire.

Scientific data, 7(1):194 pii:10.1038/s41597-020-0522-7.

Wildland fires have a multitude of ecological effects in forests, woodlands, and savannas across the globe. A major focus of past research has been on tree mortality from fire, as trees provide a vast range of biological services. We assembled a database of individual-tree records from prescribed fires and wildfires in the United States. The Fire and Tree Mortality (FTM) database includes records from 164,293 individual trees with records of fire injury (crown scorch, bole char, etc.), tree diameter, and either mortality or top-kill up to ten years post-fire. Data span 142 species and 62 genera, from 409 fires occurring from 1981-2016. Additional variables such as insect attack are included when available. The FTM database can be used to evaluate individual fire-caused mortality models for pre-fire planning and post-fire decision support, to develop improved models, and to explore general patterns of individual fire-induced tree death. The database can also be used to identify knowledge gaps that could be addressed in future research.

RevDate: 2020-06-23
CmpDate: 2020-06-23

Liddell C, Morgan ER, Bull K, et al (2020)

Response to resources and parasites depends on health status in extensively grazed sheep.

Proceedings. Biological sciences, 287(1920):20192905.

A fundamental question in animal ecology is how an individual's internal state and the external environment together shape species distributions across habitats. The increasing availability of biologgers is driving a revolution in answering this question in a wide range of species. In this study, the position of sheep (Ovis aries) from Global Positioning System collars was integrated with remote sensing data, field sampling of parasite distributions, and parasite load and health measures for each tagged individual. This allowed inter-individual variation in habitat use to be examined. Once controlling for a positive relationship between vegetation productivity and tick abundance, healthier individuals spent more of their time at sites with higher vegetation productivity, while less healthy individuals showed a stronger (negative) response to tick abundance. These trends are likely to represent a trade-off in foraging decisions that vary between individuals based on their health status. Given the rarity of studies that explore how animal distributions are affected by health and external factors, we demonstrate the value of integrating biologging technology with remote sensing data, traditional ecological sampling and individual measures of animal health. Our study, using extensively grazed sheep as a model system, opens new possibilities to study free-living grazing systems.

RevDate: 2020-06-19

Piross IS, Siliwal M, Kumar RS, et al (2020)

Sex interacts with age-dependent change in the abundance of lice-infesting Amur Falcons (Falco amurensis).

Parasitology research pii:10.1007/s00436-020-06753-w [Epub ahead of print].

Sex-biassed and age-biassed parasite infections are common in nature, including ectoparasites-vertebrate host systems. We investigated the effect of Amur Falcons' sex, age and body size on the abundance of their lice at a migratory stopover site, where the falcons' habitat use and behaviour are more homogeneous across sex and age categories than during the breeding season. We sampled Amur Falcons in Nagaland, India at major roosting sites in 2016. We applied generalized linear models (with negative binomial distribution and log-link) to model the abundance of their two most numerous lice (Colpocephalum subzerafae and Degeeriella rufa) using the host age category (juvenile or adult) and wing length, both in interaction with sex, as explanatory variables. The abundance of C. subzerafae was only affected by host age, being nearly four times higher on juveniles than on adults. Juveniles were also more infested with D. rufa than the adults. Additionally, the abundance of the latter species was lower on adult male Falcons as compared to adult females. A juvenile bias in ectoparasite infestations is common in nature, probably due to juveniles being immunologically naïve, more resource-limited and may be inexperienced in body maintenance behaviours like preening and grooming. On the other hand, female-biassed infestations are much rarer than male-biassed infestations. We briefly discuss the possible causes of female-biassed infestations on Amur Falcons reported here, and in the closely related Red-footed Falcon and Lesser Kestrel as reported in the literature.

RevDate: 2020-06-19

Anderegg WRL, Trugman AT, Badgley G, et al (2020)

Climate-driven risks to the climate mitigation potential of forests.

Science (New York, N.Y.), 368(6497):.

Forests have considerable potential to help mitigate human-caused climate change and provide society with many cobenefits. However, climate-driven risks may fundamentally compromise forest carbon sinks in the 21st century. Here, we synthesize the current understanding of climate-driven risks to forest stability from fire, drought, biotic agents, and other disturbances. We review how efforts to use forests as natural climate solutions presently consider and could more fully embrace current scientific knowledge to account for these climate-driven risks. Recent advances in vegetation physiology, disturbance ecology, mechanistic vegetation modeling, large-scale ecological observation networks, and remote sensing are improving current estimates and forecasts of the risks to forest stability. A more holistic understanding and quantification of such risks will help policy-makers and other stakeholders effectively use forests as natural climate solutions.

RevDate: 2020-06-17

Duarte ME, Vigil-Hayes M, Littletree S, et al (2020)

"Of Course, Data Can Never Fully Represent Reality": Assessing the Relationship between "Indigenous Data" and "Indigenous Knowledge," "Traditional Ecological Knowledge," and "Traditional Knowledge".

Human biology, 91(3):163-178.

Multiple terms describe Indigenous peoples' creative expressions, including "Indigenous knowledge" (IK), "traditional ecological knowledge" (TEK), "traditional knowledge" (TK), and increasingly, "Indigenous data" (ID). Variation in terms contributes to disciplinary divides, challenges in organizing and finding prior studies about Indigenous peoples' creative expressions, and intellectually divergent chains of reference. The authors applied a decolonial, digital, feminist, ethics-of-care approach to citation analysis of records about Indigenous peoples knowledge and data, including network analyses of author-generated keywords and research areas, and content analysis of peer-reviewed studies about ID. Results reveal ambiguous uses of the term "Indigenous data"; the influence of ecology and environmental studies in research areas and topics associated with IK, TEK, and TK; and the influence of public administration and governance studies in research areas and topics associated with ID studies. Researchers of ID would benefit from applying a more nuanced and robust vocabulary, one informed by studies of IK, TEK, and TK. Researchers of TEK and TK would benefit from the more people-centered approaches of IK. Researchers and systems designers who work with data sets can practice relational accountability by centering the Indigenous peoples from whom observations are sourced, combining narrative methodologies with computational methods to sustain the holism favored by Indigenous science and the relationality of Indigenous peoples.

RevDate: 2020-06-16

Kaufman D, McKay N, Routson C, et al (2020)

Publisher Correction: A global database of Holocene paleotemperature records.

Scientific data, 7(1):183 pii:10.1038/s41597-020-0515-6.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

RevDate: 2020-06-16

Birk S, Chapman D, Carvalho L, et al (2020)

Impacts of multiple stressors on freshwater biota across spatial scales and ecosystems.

Nature ecology & evolution pii:10.1038/s41559-020-1216-4 [Epub ahead of print].

Climate and land-use change drive a suite of stressors that shape ecosystems and interact to yield complex ecological responses (that is, additive, antagonistic and synergistic effects). We know little about the spatial scales relevant for the outcomes of such interactions and little about effect sizes. These knowledge gaps need to be filled to underpin future land management decisions or climate mitigation interventions for protecting and restoring freshwater ecosystems. This study combines data across scales from 33 mesocosm experiments with those from 14 river basins and 22 cross-basin studies in Europe, producing 174 combinations of paired-stressor effects on a biological response variable. Generalized linear models showed that only one of the two stressors had a significant effect in 39% of the analysed cases, 28% of the paired-stressor combinations resulted in additive effects and 33% resulted in interactive (antagonistic, synergistic, opposing or reversal) effects. For lakes, the frequencies of additive and interactive effects were similar for all spatial scales addressed, while for rivers these frequencies increased with scale. Nutrient enrichment was the overriding stressor for lakes, with effects generally exceeding those of secondary stressors. For rivers, the effects of nutrient enrichment were dependent on the specific stressor combination and biological response variable. These results vindicate the traditional focus of lake restoration and management on nutrient stress, while highlighting that river management requires more bespoke management solutions.

RevDate: 2020-06-15
CmpDate: 2020-06-15

Goodman KR, Prost S, Bi K, et al (2019)

Host and geography together drive early adaptive radiation of Hawaiian planthoppers.

Molecular ecology, 28(19):4513-4528.

The interactions between insects and their plant host have been implicated in driving diversification of both players. Early arguments highlighted the role of ecological opportunity, with the idea that insects "escape and radiate" on new hosts, with subsequent hypotheses focusing on the interplay between host shifting and host tracking, coupled with isolation and fusion, in generating diversity. Because it is rarely possible to capture the initial stages of diversification, it is particularly difficult to ascertain the relative roles of geographic isolation versus host shifts in initiating the process. The current study examines genetic diversity between populations and hosts within a single species of endemic Hawaiian planthopper, Nesosydne umbratica (Hemiptera, Delphacidae). Given that the species was known as a host generalist occupying unrelated hosts, Clermontia (Campanulaceae) and Pipturus (Urticaceae), we set out to determine the relative importance of geography and host in structuring populations in the early stages of differentiation on the youngest islands of the Hawaiian chain. Results from extensive exon capture data showed that N. umbratica is highly structured, both by geography, with discrete populations on each volcano, and by host plant, with parallel radiations on Clermontia and Pipturus leading to extensive co-occurrence. The marked genetic structure suggests that populations can readily become established on novel hosts provided opportunity; subsequent adaptation allows monopolization of the new host. The results support the role of geographic isolation in structuring populations and with host shifts occurring as discrete events that facilitate subsequent parallel geographic range expansion.

RevDate: 2020-06-12
CmpDate: 2020-06-12

Wan Y, Jiang B, Wei D, et al (2020)

Ecological criteria for zinc in Chinese soil as affected by soil properties.

Ecotoxicology and environmental safety, 194:110418.

The increasing accumulation of zinc (Zn) in agricultural soils has led to the need to assess the potential risk of this element for terrestrial organisms. However, the soil ecological criteria in agricultural soil as a function of soil properties have been sparsely reported. In the present study, we derived the ecological criteria (expressed as predicted no effect concentration (PNEC)) for Zn in soils, based on ecotoxicity data for 19 terrestrial species in Chinese soils, the effect of soil properties on Zn ecotoxicity, differences in species sensitivity, and differences between laboratory and realistic field conditions. First, all ecotoxicity data of Zn for terrestrial organisms in Chinese soils were collected and filtered with given criteria to obtain reliable database. Second, the ecotoxicity data were normalized using Zn ecotoxicity predictive models to eliminate the effect of soil properties on Zn ecotoxicity, and corrected with leaching and aging factors to minimize the differences in Zn ecotoxicity under laboratory and field conditions. Then, species sensitivity distribution (SSD) curves were generated with a Burr Ⅲ function based on corrected ecotoxicity data. The concentration of Zn in soil that provides ecological safety for (100 - x)% of species (HCx), was calculated from the SSD curve and HC5 was used for estimation of PNEC. Finally, we developed the predictive models for HCx by quantifying the relationship between the Zn HCx and soil properties. Results showed that soil pH was the most crucial factor affecting Zn HCx values, with HC5 values varying from 38.3 mg/kg in an acidic soil to 263.3 mg/kg in an alkaline calcareous soil. Both the two-factor (soil pH and OC) and the three-factor (soil pH, OC and CEC) models predicted HCx values well, with determination coefficients (R2) of 0.941-0.959 and 0.978-0.982, respectively. This study provides a scientific and reliable basis for the improvement of ecological risk assessment and the establishment of soil environmental quality standards.

RevDate: 2020-06-10

Wang E, Zhang D, Braun MS, et al (2020)

Can Mitogenomes of the Northern Wheatear (Oenanthe oenanthe) Reconstruct Its Phylogeography and Reveal the Origin of Migrant Birds?.

Scientific reports, 10(1):9290 pii:10.1038/s41598-020-66287-0.

The Northern Wheatear (Oenanthe oenanthe, including the nominate and the two subspecies O. o. leucorhoa and O. o. libanotica) and the Seebohm's Wheatear (Oenanthe seebohmi) are today regarded as two distinct species. Before, all four taxa were regarded as four subspecies of the Northern Wheatear. Their classification has exclusively been based on ecological and morphological traits, while their molecular characterization is still missing. With this study, we used next-generation sequencing to assemble 117 complete mitochondrial genomes covering O. o. oenanthe, O. o. leucorhoa and O. seebohmi. We compared the resolution power of each individual mitochondrial marker and concatenated marker sets to reconstruct the phylogeny and estimate speciation times of three taxa. Moreover, we tried to identify the origin of migratory wheatears caught on Helgoland (Germany) and on Crete (Greece). Mitogenome analysis revealed two different ancient lineages that separated around 400,000 years ago. Both lineages consisted of a mix of subspecies and species. The phylogenetic trees, as well as haplotype networks are incongruent with the present morphology-based classification. Mitogenome could not distinguish these presumed species. The genetic panmixia among present populations and taxa might be the consequence of mitochondrial introgression between ancient wheatear populations.

RevDate: 2020-06-03
CmpDate: 2020-06-03

Fitak RR, Antonides JD, Baitchman EJ, et al (2019)

The Expectations and Challenges of Wildlife Disease Research in the Era of Genomics: Forecasting with a Horizon Scan-like Exercise.

The Journal of heredity, 110(3):261-274.

The outbreak and transmission of disease-causing pathogens are contributing to the unprecedented rate of biodiversity decline. Recent advances in genomics have coalesced into powerful tools to monitor, detect, and reconstruct the role of pathogens impacting wildlife populations. Wildlife researchers are thus uniquely positioned to merge ecological and evolutionary studies with genomic technologies to exploit unprecedented "Big Data" tools in disease research; however, many researchers lack the training and expertise required to use these computationally intensive methodologies. To address this disparity, the inaugural "Genomics of Disease in Wildlife" workshop assembled early to mid-career professionals with expertise across scientific disciplines (e.g., genomics, wildlife biology, veterinary sciences, and conservation management) for training in the application of genomic tools to wildlife disease research. A horizon scanning-like exercise, an activity to identify forthcoming trends and challenges, performed by the workshop participants identified and discussed 5 themes considered to be the most pressing to the application of genomics in wildlife disease research: 1) "Improving communication," 2) "Methodological and analytical advancements," 3) "Translation into practice," 4) "Integrating landscape ecology and genomics," and 5) "Emerging new questions." Wide-ranging solutions from the horizon scan were international in scope, itemized both deficiencies and strengths in wildlife genomic initiatives, promoted the use of genomic technologies to unite wildlife and human disease research, and advocated best practices for optimal use of genomic tools in wildlife disease projects. The results offer a glimpse of the potential revolution in human and wildlife disease research possible through multi-disciplinary collaborations at local, regional, and global scales.

RevDate: 2020-05-21
CmpDate: 2020-05-21

Bay RA, Taylor EB, D Schluter (2019)

Parallel introgression and selection on introduced alleles in a native species.

Molecular ecology, 28(11):2802-2813.

As humans cause the redistribution of species ranges, hybridization between previously allopatric species is on the rise. Such hybridization can have complex effects on overall fitness of native species as new allelic combinations are tested. Widespread species introductions provide a unique opportunity to study selection on introgressed alleles in independent, replicated populations. We examined selection on alleles that repeatedly introgressed from introduced rainbow trout (Oncorhynchus mykiss) into native westslope cutthroat trout (Oncorhynchus clarkii lewisi) populations in western Canada. We found that the degree of introgression of individual single nucleotide polymorphisms from the invasive species into the native is correlated between independent watersheds. A number of rainbow trout alleles have repeatedly swept to high frequency in native populations, suggesting parallel adaptive advantages. Using simulations, we estimated large selection coefficients up to 0.05 favoring several rainbow trout alleles in the native background. Although previous studies have found reduced hybrid fitness and genome-wide resistance to introgression in westslope cutthroat trout, our results suggest that some introduced genomic regions are strongly favored by selection. Our study demonstrates the utility of replicated introductions as case studies for understanding parallel adaptation and the interactions between selection and introgression across the genome. We suggest that understanding this variation, including consideration of beneficial alleles, can inform management strategies for hybridizing species.

RevDate: 2020-05-18
CmpDate: 2020-05-18

Tian D, Yan Z, Ma S, et al (2019)

Family-level leaf nitrogen and phosphorus stoichiometry of global terrestrial plants.

Science China. Life sciences, 62(8):1047-1057.

Leaf nitrogen (N) and phosphorus (P) concentrations are critical for photosynthesis, growth, reproduction and other ecological processes of plants. Previous studies on large-scale biogeographic patterns of leaf N and P stoichiometric relationships were mostly conducted using data pooled across taxa, while family/genus-level analyses are rarely reported. Here, we examined global patterns of family-specific leaf N and P stoichiometry using a global data set of 12,716 paired leaf N and P records which includes 204 families, 1,305 genera, and 3,420 species. After determining the minimum size of samples (i.e., 35 records), we analyzed leaf N and P concentrations, N:P ratios and N∼P scaling relationships of plants for 62 families with 11,440 records. The numeric values of leaf N and P stoichiometry varied significantly across families and showed diverse trends along gradients of mean annual temperature (MAT) and mean annual precipitation (MAP). The leaf N and P concentrations and N:P ratios of 62 families ranged from 6.11 to 30.30 mg g-1, 0.27 to 2.17 mg g-1, and 10.20 to 35.40, respectively. Approximately 1/3-1/2 of the families (22-35 of 62) showed a decrease in leaf N and P concentrations and N:P ratios with increasing MAT or MAP, while the remainder either did not show a significant trend or presented the opposite pattern. Family-specific leaf N∼P scaling exponents did not converge to a certain empirical value, with a range of 0.307-0.991 for 54 out of 62 families which indicated a significant N∼P scaling relationship. Our results for the first time revealed large variation in the family-level leaf N and P stoichiometry of global terrestrial plants and that the stoichiometric relationships for at least one-third of the families were not consistent with the global trends reported previously. The numeric values of the family-specific leaf N and P stoichiometry documented in the current study provide critical synthetic parameters for biogeographic modeling and for further studies on the physiological and ecological mechanisms underlying the nutrient use strategies of plants from different phylogenetic taxa.

RevDate: 2020-05-12

Herren CM (2020)

Disruption of cross-feeding interactions by invading taxa can cause invasional meltdown in microbial communities.

Proceedings. Biological sciences, 287(1927):20192945.

The strength of biotic interactions within an ecological community affects the susceptibility of the community to invasion by introduced taxa. In microbial communities, cross-feeding is a widespread type of biotic interaction that has the potential to affect community assembly and stability. Yet, there is little understanding of how the presence of cross-feeding within a community affects invasion risk. Here, I develop a metabolite-explicit model where native microbial taxa interact through both cross-feeding and competition for metabolites. I use this model to study how the strength of biotic interactions, especially cross-feeding, influence whether an introduced taxon can join the community. I found that stronger cross-feeding and competition led to much lower invasion risk, as both types of biotic interactions lead to greater metabolite scarcity for the invader. I also evaluated the impact of a successful invader on community composition and structure. The effect of invaders on the native community was greatest at intermediate levels of cross-feeding; at this 'critical' level of cross-feeding, successful invaders generally cause decreased diversity, decreased productivity, greater metabolite availability, and decreased quantities of metabolites exchanged among taxa. Furthermore, these changes resulting from a successful primary invader made communities further susceptible to future invaders. The increase in invasion risk was greatest when the network of metabolite exchange between taxa was minimally redundant. Thus, this model demonstrates a case of invasional meltdown that is mediated by initial invaders disrupting the metabolite exchange networks of the native community.

RevDate: 2020-05-05

Boyce HB, P Mallick (2019)

Geostatistical visualization of ecological interactions in tumors.

Proceedings. IEEE International Conference on Bioinformatics and Biomedicine, 2019:2741-2749.

Recent advances in our understanding of cancer progression have highlighted the roles played by molecular heterogeneity and by the tumor microenvironment in driving drug resistance and metastasis. The coupling of single-cell measurement technologies with algorithms, such as t-sne and SPADE, have enabled deep investigation of tumor heterogeneity. However, such techniques only capture molecular heterogeneity and do not enable the quantification nor visualization of intercellular interactions. They additionally do not allow the visualization of ecological niches that are critical to understanding tumor behavior. Novel computational tools to quantify and visualize spatial patterns in the tumor microenvironment are critically needed. Here, we take a tumor ecology perspective to examine how predation, mutualism, commensalism, and parasitism may impact tumor development and spatial patterning. We additionally quantify local spatial heterogeneity and the emergent global spatial behavior of the models using geostatistics. By visualizing emergent spatial patterns we demonstrate the potential utility of a geostatistical analysis in differentiating amongst cell-cell interactions in the tumor microenvironment. These studies introduce both an ecological framework for characterizing intercellular interactions in cancer and a novel way of quantifying and visualizing spatial patterns in cancer.

RevDate: 2020-05-04

Carson E, Feng DD, Pons MN, et al (2006)

Dealing with bio- and ecological complexity: Challenges and opportunities.

Annual reviews in control, 30(1):91-101.

The complexities of the dynamic processes and their control associated with biological and ecological systems offer many challenges for the control engineer. Over the past decades the application of dynamic modelling and control has aided understanding of their complexities. At the same time using such complex systems as test-beds for new control methods has highlighted their limitations (e.g. in relation to system identification) and has thus acted as a catalyst for methodological advance. This paper continues the theme of exploring opportunities and achievements in applying modelling and control in the bio- and ecological domains.

RevDate: 2020-04-30
CmpDate: 2020-04-30

Kienzler A, Connors KA, Bonnell M, et al (2019)

Mode of Action Classifications in the EnviroTox Database: Development and Implementation of a Consensus MOA Classification.

Environmental toxicology and chemistry, 38(10):2294-2304.

Multiple mode of action (MOA) frameworks have been developed in aquatic ecotoxicology, mainly based on fish toxicity. These frameworks provide information on a key determinant of chemical toxicity, but the MOA categories and level of specificity remain unique to each of the classification schemes. The present study aimed to develop a consensus MOA assignment within EnviroTox, a curated in vivo aquatic toxicity database, based on the following MOA classification schemes: Verhaar (modified) framework, Assessment Tool for Evaluating Risk, Toxicity Estimation Software Tool, and OASIS. The MOA classifications from each scheme were first collapsed into one of 3 categories: non-specifically acting (i.e., narcosis), specifically acting, or nonclassifiable. Consensus rules were developed based on the degree of concordance among the 4 individual MOA classifications to attribute a consensus MOA to each chemical. A confidence rank was also assigned to the consensus MOA classification based on the degree of consensus. Overall, 40% of the chemicals were classified as narcotics, 17% as specifically acting, and 43% as unclassified. Sixty percent of chemicals had a medium to high consensus MOA assignment. When compared to empirical acute toxicity data, the general trend of specifically acting chemicals being more toxic is clearly observed for both fish and invertebrates but not for algae. EnviroTox is the first approach to establishing a high-level consensus across 4 computationally and structurally distinct MOA classification schemes. This consensus MOA classification provides both a transparent understanding of the variation between MOA classification schemes and an added certainty of the MOA assignment. In terms of regulatory relevance, a reliable understanding of MOA can provide information that can be useful for the prioritization (ranking) and risk assessment of chemicals. Environ Toxicol Chem 2019;38:2294-2304. © 2019 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.

RevDate: 2020-04-30
CmpDate: 2020-04-30

Laudadio I, Fulci V, Stronati L, et al (2019)

Next-Generation Metagenomics: Methodological Challenges and Opportunities.

Omics : a journal of integrative biology, 23(7):327-333.

Metagenomics is not only one of the newest omics system science technologies but also one that has arguably the broadest set of applications and impacts globally. Metagenomics has found vast utility not only in environmental sciences, ecology, and public health but also in clinical medicine and looking into the future, in planetary health. In line with the One Health concept, metagenomics solicits collaboration between molecular biologists, geneticists, microbiologists, clinicians, computational biologists, plant biologists, veterinarians, and other health care professionals. Almost every ecological niche of our planet hosts an extremely diverse community of organisms that are still poorly characterized. Detailed characterization of the features of such communities is instrumental to our comprehension of ecological, biological, and clinical complexity. This expert review article evaluates how metagenomics is improving our knowledge of microbiota composition from environmental to human samples. Furthermore, we offer an analysis of the common technical and methodological challenges and potential pitfalls arising from metagenomics approaches, such as metagenomics study design, data processing, and interpretation. All in all, at this critical juncture of further growth of the metagenomics field, it is time to critically reflect on the lessons learned and the future prospects of next-generation metagenomics science, technology, and conceivable applications, particularly from the standpoint of a metagenomics methodology perspective.

RevDate: 2020-04-27
CmpDate: 2020-04-27

Le Provost G, Badenhausser I, Le Bagousse-Pinguet Y, et al (2020)

Land-use history impacts functional diversity across multiple trophic groups.

Proceedings of the National Academy of Sciences of the United States of America, 117(3):1573-1579.

Land-use change is a major driver of biodiversity loss worldwide. Although biodiversity often shows a delayed response to land-use change, previous studies have typically focused on a narrow range of current landscape factors and have largely ignored the role of land-use history in shaping plant and animal communities and their functional characteristics. Here, we used a unique database of 220,000 land-use records to investigate how 20-y of land-use changes have affected functional diversity across multiple trophic groups (primary producers, mutualists, herbivores, invertebrate predators, and vertebrate predators) in 75 grassland fields with a broad range of land-use histories. The effects of land-use history on multitrophic trait diversity were as strong as other drivers known to impact biodiversity, e.g., grassland management and current landscape composition. The diversity of animal mobility and resource-acquisition traits was lower in landscapes where much of the land had been historically converted from grassland to crop. In contrast, functional biodiversity was higher in landscapes containing old permanent grasslands, most likely because they offer a stable and high-quality habitat refuge for species with low mobility and specialized feeding niches. Our study shows that grassland-to-crop conversion has long-lasting impacts on the functional biodiversity of agricultural ecosystems. Accordingly, land-use legacy effects must be considered in conservation programs aiming to protect agricultural biodiversity. In particular, the retention of permanent grassland sanctuaries within intensive landscapes may offset ecological debts.

RevDate: 2020-04-22
CmpDate: 2020-04-22

Bjorbækmo MFM, Evenstad A, Røsæg LL, et al (2020)

The planktonic protist interactome: where do we stand after a century of research?.

The ISME journal, 14(2):544-559.

Microbial interactions are crucial for Earth ecosystem function, but our knowledge about them is limited and has so far mainly existed as scattered records. Here, we have surveyed the literature involving planktonic protist interactions and gathered the information in a manually curated Protist Interaction DAtabase (PIDA). In total, we have registered ~2500 ecological interactions from ~500 publications, spanning the last 150 years. All major protistan lineages were involved in interactions as hosts, symbionts (mutualists and commensalists), parasites, predators, and/or prey. Predation was the most common interaction (39% of all records), followed by symbiosis (29%), parasitism (18%), and 'unresolved interactions' (14%, where it is uncertain whether the interaction is beneficial or antagonistic). Using bipartite networks, we found that protist predators seem to be 'multivorous' while parasite-host and symbiont-host interactions appear to have moderate degrees of specialization. The SAR supergroup (i.e., Stramenopiles, Alveolata, and Rhizaria) heavily dominated PIDA, and comparisons against a global-ocean molecular survey (TARA Oceans) indicated that several SAR lineages, which are abundant and diverse in the marine realm, were underrepresented among the recorded interactions. Despite historical biases, our work not only unveils large-scale eco-evolutionary trends in the protist interactome, but it also constitutes an expandable resource to investigate protist interactions and to test hypotheses deriving from omics tools.

RevDate: 2020-04-20
CmpDate: 2020-04-20

Sarkar S, Singh P, Lingala MAL, et al (2019)

Malaria risk map for India based on climate, ecology and geographical modelling.

Geospatial health, 14(2):.

Mapping the malaria risk at various geographical levels is often undertaken considering climate suitability, infection rate and/or malaria vector distribution, while the ecological factors related to topography and vegetation cover are generally neglected. The present study abides a holistic approach to risk mapping by including topographic, climatic and vegetation components into the framework of malaria risk modelling. This work attempts to delineate the areas of Plasmodium falciparum and Plasmodium vivax malaria transmission risk in India using seven geo-ecological indicators: temperature, relative humidity, rainfall, forest cover, soil, slope, altitude and the normalized difference vegetation index using multi-criteria decision analysis based on geographical information system (GIS). The weight of the risk indicators was assigned by an analytical hierarchical process with the climate suitability (temperature and humidity) data generated using fuzzy logic. Model validation was done through both primary and secondary datasets. The spatio-ecological model was based on GIS to classify the country into five zones characterized by various levels of malaria transmission risk (very high; high; moderate; low; and very low. The study found that about 13% of the country is under very high malaria risk, which includes the malaria- endemic districts of the states of Chhattisgarh, Odisha, Jharkhand, Tripura, Assam, Meghalaya and Manipur. The study also showed that the transmission risk suitability for P. vivax is higher than that for P. falciparum in the Himalayan region. The field study corroborates the identified malaria risk zones and highlights that the low to moderate risk zones are outbreak-prone. It is expected that this information will help the National Vector Borne Disease Control Programme in India to undertake improved surveillance and conduct target based interventions.

RevDate: 2020-04-20
CmpDate: 2020-04-20

Vest JR, N Menachemi (2019)

A population ecology perspective on the functioning and future of health information organizations.

Health care management review, 44(4):344-355.

BACKGROUND: Increasingly, health care providers need to exchange information to meet policy expectations and business needs. A variety of health information organizations (HIOs) provide services to facilitate health information exchange (HIE). However, the future of these organizations is unclear.

PURPOSE: The aim of this study was to explore the environmental context, potential futures, and survivability of community HIOs, enterprise HIEs, and electronic health record vendor-mediated exchange using the population ecology theory.

APPROACH: Qualitative interviews with 33 key informants representing each type of HIE organization were analyzed using template analysis.

RESULTS: Community HIOs, enterprise HIEs, and electronic health record vendors exhibited a high degree of competition for resources, especially in the area of exchange infrastructure services. Competition resulted in closures in some areas. In response to environmental pressures, each organizational type was endeavoring to differentiate its services and unique use case, as well as pursing symbiotic relationships or attempting resource partitioning.

CONCLUSION: HIOs compete for similar resources and are reacting to environmental pressures to better position themselves for continued survival and success. Our ecological research perspective helps move the discourse away from situation of a single exchange organization type toward a view of the broader dynamics and relationships of all organizations involved in facilitating HIE activities.

PRACTICE IMPLICATIONS: HIOs are attempting to partition the environment and differentiate services. HIE options should not be construed as an "either/or" decision, but one where multiple and complementary participation may be required.

RevDate: 2020-04-17
CmpDate: 2020-04-17

Connors KA, Beasley A, Barron MG, et al (2019)

Creation of a Curated Aquatic Toxicology Database: EnviroTox.

Environmental toxicology and chemistry, 38(5):1062-1073.

Flexible, rapid, and predictive approaches that do not require the use of large numbers of vertebrate test animals are needed because the chemical universe remains largely untested for potential hazards. Development of robust new approach methodologies and nontesting approaches requires the use of existing information via curated, integrated data sets. The ecological threshold of toxicological concern (ecoTTC) represents one such new approach methodology that can predict a conservative de minimis toxicity value for chemicals with little or no information available. For the creation of an ecoTTC tool, a large, diverse environmental data set was developed from multiple sources, with harmonization, characterization, and information quality assessment steps to ensure that the information could be effectively organized and mined. The resulting EnviroTox database contains 91 217 aquatic toxicity records representing 1563 species and 4016 unique Chemical Abstracts Service numbers and is a robust, curated database containing high-quality aquatic toxicity studies that are traceable to the original information source. Chemical-specific information is also linked to each record and includes physico-chemical information, chemical descriptors, and mode of action classifications. Toxicity data are associated with the physico-chemical data, mode of action classifications, and curated taxonomic information for the organisms tested. The EnviroTox platform also includes 3 analysis tools: a predicted-no-effect concentration calculator, an ecoTTC distribution tool, and a chemical toxicity distribution tool. Although the EnviroTox database and tools were originally developed to support ecoTTC analysis and development, they have broader applicability to the field of ecological risk assessment. Environ Toxicol Chem 2019;9999:1-12. © 2019 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.

RevDate: 2020-04-15
CmpDate: 2020-04-15

Buchner D, Beermann AJ, Laini A, et al (2019)

Analysis of 13,312 benthic invertebrate samples from German streams reveals minor deviations in ecological status class between abundance and presence/absence data.

PloS one, 14(12):e0226547.

Benthic invertebrates are the most commonly used organisms used to assess ecological status as required by the EU Water Framework Directive (WFD). For WFD-compliant assessments, benthic invertebrate communities are sampled, identified and counted. Taxa × abundance matrices are used to calculate indices and the resulting scores are compared to reference values to determine the ecological status class. DNA-based tools, such as DNA metabarcoding, provide a new and precise method for species identification but cannot deliver robust abundance data. To evaluate the applicability of DNA-based tools to ecological status assessment, we evaluated whether the results derived from presence/absence data are comparable to those derived from abundance data. We analysed benthic invertebrate community data obtained from 13,312 WFD assessments of German streams. Broken down to 30 official stream types, we compared assessment results based on abundance and presence/absence data for the assessment modules "organic pollution" (i.e., the saprobic index) and "general degradation" (a multimetric index) as well as their underlying metrics. In 76.6% of cases, the ecological status class did not change after transforming abundance data to presence/absence data. In 12% of cases, the status class was reduced by one (e.g., from good to moderate), and in 11.2% of cases, the class increased by one. In only 0.2% of cases, the status shifted by two classes. Systematic stream type-specific deviations were found and differences between abundance and presence/absence data were most prominent for stream types where abundance information contributed directly to one or several metrics of the general degradation module. For a single stream type, these deviations led to a systematic shift in status from 'good' to 'moderate' (n = 201; with only n = 3 increasing). The systematic decrease in scores was observed, even when considering simulated confidence intervals for abundance data. Our analysis suggests that presence/absence data can yield similar assessment results to those for abundance-based data, despite type-specific deviations. For most metrics, it should be possible to intercalibrate the two data types without substantial efforts. Thus, benthic invertebrate taxon lists generated by standardised DNA-based methods should be further considered as a complementary approach.

RevDate: 2020-04-15
CmpDate: 2020-04-15

Greenbaum G, Rubin A, Templeton AR, et al (2019)

Network-based hierarchical population structure analysis for large genomic data sets.

Genome research, 29(12):2020-2033.

Analysis of population structure in natural populations using genetic data is a common practice in ecological and evolutionary studies. With large genomic data sets of populations now appearing more frequently across the taxonomic spectrum, it is becoming increasingly possible to reveal many hierarchical levels of structure, including fine-scale genetic clusters. To analyze these data sets, methods need to be appropriately suited to the challenges of extracting multilevel structure from whole-genome data. Here, we present a network-based approach for constructing population structure representations from genetic data. The use of community-detection algorithms from network theory generates a natural hierarchical perspective on the representation that the method produces. The method is computationally efficient, and it requires relatively few assumptions regarding the biological processes that underlie the data. We show the approach by analyzing population structure in the model plant species Arabidopsis thaliana and in human populations. These examples illustrate how network-based approaches for population structure analysis are well-suited to extracting valuable ecological and evolutionary information in the era of large genomic data sets.

RevDate: 2020-04-14

Kaufman D, McKay N, Routson C, et al (2020)

A global database of Holocene paleotemperature records.

Scientific data, 7(1):115 pii:10.1038/s41597-020-0445-3.

A comprehensive database of paleoclimate records is needed to place recent warming into the longer-term context of natural climate variability. We present a global compilation of quality-controlled, published, temperature-sensitive proxy records extending back 12,000 years through the Holocene. Data were compiled from 679 sites where time series cover at least 4000 years, are resolved at sub-millennial scale (median spacing of 400 years or finer) and have at least one age control point every 3000 years, with cut-off values slackened in data-sparse regions. The data derive from lake sediment (51%), marine sediment (31%), peat (11%), glacier ice (3%), and other natural archives. The database contains 1319 records, including 157 from the Southern Hemisphere. The multi-proxy database comprises paleotemperature time series based on ecological assemblages, as well as biophysical and geochemical indicators that reflect mean annual or seasonal temperatures, as encoded in the database. This database can be used to reconstruct the spatiotemporal evolution of Holocene temperature at global to regional scales, and is publicly available in Linked Paleo Data (LiPD) format.

RevDate: 2020-04-13
CmpDate: 2020-04-13

Hoondert RPJ, Oldenkamp R, de Zwart D, et al (2019)

QSAR-Based Estimation of Species Sensitivity Distribution Parameters: An Exploratory Investigation.

Environmental toxicology and chemistry, 38(12):2764-2770.

Ecological risk assessments are hampered by limited availability of ecotoxicity data. The present study aimed to explore the possibility of deriving species sensitivity distribution (SSD) parameters for nontested compounds, based on simple physicochemical characteristics, known SSDs for data-rich compounds, and a quantitative structure-activity relationship (QSAR)-type approach. The median toxicity of a data-poor chemical for species assemblages significantly varies with values of the physicochemical descriptors, especially when based on high-quality SSD data (from either acute median effect concentrations or chronic no-observed-effect concentrations). Beyond exploratory uses, we discuss how the precision of QSAR-based SSDs can be improved to construct models that accurately predict the SSD parameters of data-poor chemicals. The current models show that the concept of QSAR-based SSDs supports screening-level evaluations of the potential ecotoxicity of compounds for which data are lacking. Environ Toxicol Chem 2019;38:2764-2770. © 2019 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.

RevDate: 2020-04-13
CmpDate: 2020-04-13

Eccles KM, Pauli BD, HM Chan (2019)

The Use of Geographic Information Systems for Spatial Ecological Risk Assessments: An Example from the Athabasca Oil Sands Area in Canada.

Environmental toxicology and chemistry, 38(12):2797-2810.

There is an acknowledged need in ecotoxicology for methods that integrate spatial analyses in risk assessment. This has resulted in the emergence of landscape ecotoxicology, a subdiscipline of ecotoxicology. However, landscape ecotoxicology has yet to become common practice in risk assessment due to the underdevelopment of techniques and a lack of standardized methods. In the present study, we demonstrate how geographic information systems (GISs) can serve as a standardized platform to integrate data, assess spatial patterns of ecotoxicological data for multiple species, and assess relationships between chemical mixture exposures and effects on biota for landscape ecotoxicological risks assessment. We use data collected under the Joint Oil Sands Monitoring Program in the Athabasca Oil Sands Region in Alberta, Canada. This dataset is composed of concentrations of contaminants including metals and polycyclic aromatic compounds, and health endpoints measured in 1100 biological samples, including tree swallows, amphibians, gull and tern eggs, plants, and mammals. We present 3 examples using a GIS as a platform and geospatial analysis to: 1) integrate data and assess spatial patterns of contaminant exposure in the region, 2) assess spatial patterns of exposures to complex mixtures, and 3) examine patterns of exposures and responses across the landscape. We summarize the methods used in the present study into a workflow for ease of use. The GIS methods allow researchers to identify hot spots of contamination, use georeferenced monitoring data to derive quantitative exposure-response relationships, and assess complex exposures with more realism. Environ Toxicol Chem 2019;38:2797-2810. © 2019 SETAC.

RevDate: 2020-04-13
CmpDate: 2020-04-13

Pitacco V, Reizopoulou S, Sfriso A, et al (2019)

The difficulty of disentangling natural from anthropogenic forcing factors makes the evaluation of ecological quality problematic: A case study from Adriatic lagoons.

Marine environmental research, 150:104756.

The complex and dynamic nature of transitional ecosystems pose problems for the assessment of the Ecological Quality Status required by the European Water Framework Directive (WFD; 2000/60/EC). In six Adriatic lagoons, Ecological Quality Status was studied by comparing a biotic index based on macrophytes (MaQI), and three indices based on invertebrates (M-AMBI, M-bAMBI, and ISD). Ecological Status evaluated though MaQI and ISD resulted in quite degraded ecosystems (moderate/poor/bad), with only opportunistic algae and macrobenthic communities dominated by small size classes. Those results were supported by physico-chemical parameters, indicating high nutrients inputs, and anthropogenic pressures related with agriculture and fishery activities. Ecological Status obtained with M-AMBI and M-bAMBI was higher, with some sites reaching even the "good" status. The best response to anthropogenic pressures, in terms of a pressure index, was obtained by M-AMBI and M-bAMBI. Nevertheless, the response of used metrics (such as AMBI and bAMBI) to environmental variables not related to anthropogenic impact, and the high heterogeneity of physical-chemical conditions within lagoons, represent potential problems for the correct evaluation of Ecological Status of transitional waters. When different metrics give different responses it becomes a problem for managers who cannot easily make a decision on the remedial measures. The disagreement among indices arose because of the different response of biological elements to different stressors, and because the different indices based on macroinvertebrates focused on different aspects of the community, providing complementary information. So urge the need to find alternative approaches for a correct assessment of Ecological Status, with the combination of different biological elements, and considering the development of new indices (e.g. M-bAMBI) or refinement of the existing ones.

RevDate: 2020-04-08
CmpDate: 2020-04-06

Douterelo I, Dutilh BE, Arkhipova K, et al (2020)

Microbial diversity, ecological networks and functional traits associated to materials used in drinking water distribution systems.

Water research, 173:115586.

Drinking water distribution systems host complex microbial communities as biofilms that interact continuously with delivered water. Understanding the diversity, behavioural and functional characteristics will be a requisite for developing future monitoring strategies and protection against water-borne health risks. To improve understanding, this study investigates mobilisation and accumulation behaviour, microbial community structure and functional variations of biofilms developing on different pipe materials from within an operational network. Samples were collected from four pipes during a repeated flushing operation three months after an initial visit that used hydraulic forces to mobilise regenerating biofilms yet without impacting the upstream network. To minimise confounding factors, test sections were chosen with comparable daily hydraulic regimes, physical dimensions, and all connected straight of a common trunk main and within close proximity, hence similar water chemistry, pressure and age. Taxonomical results showed differences in colonising communities between pipe materials, with several genera, including the bacteria Pseudomonas and the fungi Cladosporium, present in every sample. Diverse bacterial communities dominated compared to more homogeneous fungal, or mycobiome, community distribution. The analysis of bacterial/fungal networks based on relative abundance of operational taxonomic units (OTUs) indicated microbial communities from cast iron pipes were more stable than communities from the non-ferrous pipe materials. Novel analysis of functional traits between all samples were found to be mainly associated to mobile genetic elements that play roles in determining links between cells, including phages, prophages, transposable elements, and plasmids. The use of functional traits can be considered for development in future surveillance methods, capable of delivering network condition information beyond that of limited conventional faecal indicator tests, that will help protect water quality and public health.

RevDate: 2020-04-08
CmpDate: 2020-04-06

Bahlai CA, EF Zipkin (2020)

The Dynamic Shift Detector: An algorithm to identify changes in parameter values governing populations.

PLoS computational biology, 16(1):e1007542.

Environmental factors interact with internal rules of population regulation, sometimes perturbing systems to alternate dynamics though changes in parameter values. Yet, pinpointing when such changes occur in naturally fluctuating populations is difficult. An algorithmic approach that can identify the timing and magnitude of parameter shifts would facilitate understanding of abrupt ecological transitions with potential to inform conservation and management of species. The "Dynamic Shift Detector" is an algorithm to identify changes in parameter values governing temporal fluctuations in populations with nonlinear dynamics. The algorithm examines population time series data for the presence, location, and magnitude of parameter shifts. It uses an iterative approach to fitting subsets of time series data, then ranks the fit of break point combinations using model selection, assigning a relative weight to each break. We examined the performance of the Dynamic Shift Detector with simulations and two case studies. Under low environmental/sampling noise, the break point sets selected by the Dynamic Shift Detector contained the true simulated breaks with 70-100% accuracy. The weighting tool generally assigned breaks intentionally placed in simulated data (i.e., true breaks) with weights averaging >0.8 and those due to sampling error (i.e., erroneous breaks) with weights averaging <0.2. In our case study examining an invasion process, the algorithm identified shifts in population cycling associated with variations in resource availability. The shifts identified for the conservation case study highlight a decline process that generally coincided with changing management practices affecting the availability of hostplant resources. When interpreted in the context of species biology, the Dynamic Shift Detector algorithm can aid management decisions and identify critical time periods related to species' dynamics. In an era of rapid global change, such tools can provide key insights into the conditions under which population parameters, and their corresponding dynamics, can shift.

RevDate: 2020-04-08
CmpDate: 2020-04-06

Joshi J, Brännström Å, U Dieckmann (2020)

Emergence of social inequality in the spatial harvesting of renewable public goods.

PLoS computational biology, 16(1):e1007483.

Spatially extended ecological public goods, such as forests, grasslands, and fish stocks, are at risk of being overexploited by selfish consumers-a phenomenon widely recognized as the 'tragedy of the commons.' The interplay of spatial and ecological dimensions introduces new features absent in non-spatial ecological contexts, such as consumer mobility, local information availability, and strategy evolution through social learning in neighborhoods. It is unclear how these features interact to influence the harvesting and dispersal strategies of consumers. To answer these questions, we develop and analyze an individual-based, spatially structured, eco-evolutionary model with explicit resource dynamics. We report the following findings. (1) When harvesting efficiency is low, consumers evolve a sedentary consumption strategy, through which the resource is harvested sustainably, but with harvesting rates far below their maximum sustainable value. (2) As harvesting efficiency increases, consumers adopt a mobile 'consume-and-disperse' strategy, which is sustainable, equitable, and gives maximum sustainable yield. (3) A further increase in harvesting efficiency leads to large-scale overexploitation. (4) If costs of dispersal are significant, increased harvesting efficiency also leads to social inequality between frugal sedentary consumers and overexploitative mobile consumers. Whereas overexploitation can occur without social inequality, social inequality always leads to overexploitation. Thus, we identify four conditions that-while being characteristic of technological progress in modern societies-risk social inequality and overexploitation: high harvesting efficiency, moderately low costs of dispersal, high consumer density, and the tendency of consumers to adopt new strategies rapidly. We also show how access to global information-another feature widespread in modern societies-helps mitigate these risks.

RevDate: 2020-04-07

Purse BV, Darshan N, Kasabi GS, et al (2020)

Predicting disease risk areas through co-production of spatial models: The example of Kyasanur Forest Disease in India's forest landscapes.

PLoS neglected tropical diseases, 14(4):e0008179 pii:PNTD-D-19-01239 [Epub ahead of print].

Zoonotic diseases affect resource-poor tropical communities disproportionately, and are linked to human use and modification of ecosystems. Disentangling the socio-ecological mechanisms by which ecosystem change precipitates impacts of pathogens is critical for predicting disease risk and designing effective intervention strategies. Despite the global "One Health" initiative, predictive models for tropical zoonotic diseases often focus on narrow ranges of risk factors and are rarely scaled to intervention programs and ecosystem use. This study uses a participatory, co-production approach to address this disconnect between science, policy and implementation, by developing more informative disease models for a fatal tick-borne viral haemorrhagic disease, Kyasanur Forest Disease (KFD), that is spreading across degraded forest ecosystems in India. We integrated knowledge across disciplines to identify key risk factors and needs with actors and beneficiaries across the relevant policy sectors, to understand disease patterns and develop decision support tools. Human case locations (2014-2018) and spatial machine learning quantified the relative role of risk factors, including forest cover and loss, host densities and public health access, in driving landscape-scale disease patterns in a long-affected district (Shivamogga, Karnataka State). Models combining forest metrics, livestock densities and elevation accurately predicted spatial patterns in human KFD cases (2014-2018). Consistent with suggestions that KFD is an "ecotonal" disease, landscapes at higher risk for human KFD contained diverse forest-plantation mosaics with high coverage of moist evergreen forest and plantation, high indigenous cattle density, and low coverage of dry deciduous forest. Models predicted new hotspots of outbreaks in 2019, indicating their value for spatial targeting of intervention. Co-production was vital for: gathering outbreak data that reflected locations of exposure in the landscape; better understanding contextual socio-ecological risk factors; and tailoring the spatial grain and outputs to the scale of forest use, and public health interventions. We argue this inter-disciplinary approach to risk prediction is applicable across zoonotic diseases in tropical settings.

RevDate: 2020-04-02

Tournière O, Dolan D, Richards GS, et al (2020)

NvPOU4/Brain3 Functions as a Terminal Selector Gene in the Nervous System of the Cnidarian Nematostella vectensis.

Cell reports, 30(13):4473-4489.e5.

Terminal selectors are transcription factors that control the morphological, physiological, and molecular features that characterize distinct cell types. Here, we show that, in the sea anemone Nematostella vectensis, NvPOU4 is expressed in post-mitotic cells that give rise to a diverse set of neural cell types, including cnidocytes and NvElav1-expressing neurons. Morphological analyses of NvPOU4 mutants crossed to transgenic reporter lines show that the loss of NvPOU4 does not affect the initial specification of neural cells. Transcriptomes derived from the mutants and from different neural cell populations reveal that NvPOU4 is required for the execution of the terminal differentiation program of these neural cells. These findings suggest that POU4 genes have ancient functions as terminal selectors for morphologically and functionally disparate types of neurons and they provide experimental support for the relevance of terminal selectors for understanding the evolution of cell types.

RevDate: 2020-04-02
CmpDate: 2020-04-02

Franckowiak GA, Perdicas M, GA Smith (2019)

Spatial ecology of coyotes in the urbanizing landscape of the Cuyahoga Valley, Ohio.

PloS one, 14(12):e0227028.

Urban landscapes can present ecological challenges for wildlife species, yet many species survive, and even thrive, near dense human populations. Coyotes (Canis latrans), for example, have expanded their geographic range across North America and, as a result of their adaptability and behavioral flexibility, are now a common occupant of many urban areas in the United States. We investigated the spatial ecology of 27 coyotes fitted with Global Positioning System (GPS) telemetry collars radio-collared in the Cuyahoga Valley, Ohio. Our objectives were to quantify coyote space use, evaluate resource selection, and investigate coyote movement and activity patterns. To measure space use, we estimated home range (95%) and core area (50%) size of coyotes using the adaptive local convex hull (a-LoCoH) method. We found the mean (± SE) home range size of resident coyotes (4.7 ± 1.8 km2) was significantly smaller than ranges of transient coyotes (67.7 ± 89.6 km2). Similarly, mean (± SE) core area size of resident coyotes (0.9 ± 0.6 km2) was significantly smaller than core areas of transient coyotes (11.9 ± 16.7 km2). Home range and core area size of both resident and transient coyotes did not vary by sex, age, or season. For all coyotes, use of natural land cover was significantly greater than use of altered and developed land. When coyotes were using altered and developed land, GPS fixes were most common at night. Coyote movement patterns differed with respect to status, time period, and season; peaking during nighttime hours. A better understanding of coyote space use and movement within anthropogenic landscapes aids management of people, parks, and wildlife by providing the data necessary for research-based management decisions.

RevDate: 2020-03-27

Zhu C, Zhang Z, Wang H, et al (2020)

Assessing Soil Organic Matter Content in a Coal Mining Area through Spectral Variables of Different Numbers of Dimensions.

Sensors (Basel, Switzerland), 20(6): pii:s20061795.

Soil organic matter (SOM) is a crucial indicator for evaluating soil quality and an important component of soil carbon pools, which play a vital role in terrestrial ecosystems. Rapid, non-destructive and accurate monitoring of SOM content is of great significance for the environmental management and ecological restoration of mining areas. Visible-near-infrared (Vis-NIR) spectroscopy has proven its applicability in estimating SOM over the years. In this study, 168 soil samples were collected from the Zhundong coal field of Xinjiang Province, Northwest China. The SOM content (g kg-1) was determined by the potassium dichromate external heating method and the soil reflectance spectra were measured by the spectrometer. Two spectral feature extraction strategies, namely, principal component analysis (PCA) and the optimal band combination algorithm, were introduced to choose spectral variables. Linear models and random forests (RF) were used for predictive models. The coefficient of determination (R2), root mean square error (RMSE), and the ratio of the performance to the interquartile distance (RPIQ) were used to evaluate the predictive performance of the model. The results indicated that the variables (2DI and 3DI) derived from the optimal band combination algorithm outperformed the PCA variables (1DV) regardless of whether linear or RF models were used. An inherent gap exists between 2DI and 3DI, and the performance of 2DI is significantly poorer than that of 3DI. The accuracy of the prediction model increases with the increasing number of spectral variable dimensions (in the following order: 1DV < 2DI < 3DI). This study proves that the 3DI is the first choice for the optimal band combination algorithm to derive sensitive parameters related to SOM in the coal mining area. Furthermore, the optimal band combination algorithm can be applied to hyperspectral or multispectral images and to convert the spectral response into image pixels, which may be helpful for a soil property spatial distribution map.

RevDate: 2020-03-24

Ma J, Lu Y, Chen F, et al (2020)

Molecular Ecological Network Complexity Drives Stand Resilience of Soil Bacteria to Mining Disturbances among Typical Damaged Ecosystems in China.

Microorganisms, 8(3): pii:microorganisms8030433.

Understanding the interactions of soil microbial species and how they responded to disturbances are essential to ecological restoration and resilience in the semihumid and semiarid damaged mining areas. Information on this, however, remains unobvious and deficiently comprehended. In this study, based on the high throughput sequence and molecular ecology network analysis, we have investigated the bacterial distribution in disturbed mining areas across three provinces in China, and constructed molecular ecological networks to reveal the interactions of soil bacterial communities in diverse locations. Bacterial community diversity and composition were classified measurably between semihumid and semiarid damaged mining sites. Additionally, we distinguished key microbial populations across these mining areas, which belonged to Proteobacteria, Acidobacteria, Actinobacteria, and Chloroflexi. Moreover, the network modules were significantly associated with some environmental factors (e.g., annual average temperature, electrical conductivity value, and available phosphorus value). The study showed that network interactions were completely different across the different mining areas. The keystone species in different mining areas suggested that selected microbial communities, through natural successional processes, were able to resist the corresponding environment. Moreover, the results of trait-based module significances showed that several environmental factors were significantly correlated with some keystone species, such as OTU_8126 (Acidobacteria), OTU_8175 (Burkholderiales), and OTU_129 (Chloroflexi). Our study also implied that the complex network of microbial interaction might drive the stand resilience of soil bacteria in the semihumid and semiarid disturbed mining areas.

RevDate: 2020-03-20
CmpDate: 2020-03-20

Xu L, Stige LC, Leirs H, et al (2019)

Historical and genomic data reveal the influencing factors on global transmission velocity of plague during the Third Pandemic.

Proceedings of the National Academy of Sciences of the United States of America, 116(24):11833-11838.

Quantitative knowledge about which natural and anthropogenic factors influence the global spread of plague remains sparse. We estimated the worldwide spreading velocity of plague during the Third Pandemic, using more than 200 years of extensive human plague case records and genomic data, and analyzed the association of spatiotemporal environmental factors with spreading velocity. Here, we show that two lineages, 2.MED and 1.ORI3, spread significantly faster than others, possibly reflecting differences among strains in transmission mechanisms and virulence. Plague spread fastest in regions with low population density and high proportion of pasture- or forestland, findings that should be taken into account for effective plague monitoring and control. Temperature exhibited a nonlinear, U-shaped association with spread speed, with a minimum around 20 °C, while precipitation showed a positive association. Our results suggest that global warming may accelerate plague spread in warm, tropical regions and that the projected increased precipitation in the Northern Hemisphere may increase plague spread in relevant regions.

RevDate: 2020-03-19

Ropert-Coudert Y, Van de Putte AP, Reisinger RR, et al (2020)

The retrospective analysis of Antarctic tracking data project.

Scientific data, 7(1):94 pii:10.1038/s41597-020-0406-x.

The Retrospective Analysis of Antarctic Tracking Data (RAATD) is a Scientific Committee for Antarctic Research project led jointly by the Expert Groups on Birds and Marine Mammals and Antarctic Biodiversity Informatics, and endorsed by the Commission for the Conservation of Antarctic Marine Living Resources. RAATD consolidated tracking data for multiple species of Antarctic meso- and top-predators to identify Areas of Ecological Significance. These datasets and accompanying syntheses provide a greater understanding of fundamental ecosystem processes in the Southern Ocean, support modelling of predator distributions under future climate scenarios and create inputs that can be incorporated into decision making processes by management authorities. In this data paper, we present the compiled tracking data from research groups that have worked in the Antarctic since the 1990s. The data are publicly available through biodiversity.aq and the Ocean Biogeographic Information System. The archive includes tracking data from over 70 contributors across 12 national Antarctic programs, and includes data from 17 predator species, 4060 individual animals, and over 2.9 million observed locations.

RevDate: 2020-03-17

Piross IS, Solt S, Horváth É, et al (2020)

Sex-dependent changes in the louse abundance of red-footed falcons (Falco vespertinus).

Parasitology research pii:10.1007/s00436-020-06634-2 [Epub ahead of print].

Permanent ectoparasites live in stable environments; thus, their population dynamics are mostly adapted to changes in the host life cycle. We aimed to investigate how static and dynamic traits of red-footed falcons interplay with the dynamics of their louse subpopulations during breeding and how they affect the colonisation of new hosts by lice. We sampled red-footed falcon (Falco vespertinus) nestlings (two breeding seasons) and adults (one breeding season) in southern Hungary. The mean abundance of Colpocephalum subzerafae and Degeeriella rufa lice on the nestlings was modelled with generalized linear mixed models using clutch size and host sex in interaction with wing length. For adults, we used wing length and the number of days after laying the first egg, both in interaction with sex. D. rufa abundances increased with the nestlings' wing length. In one year, this trend was steeper on females. In adult birds, both louse species exhibited higher abundances on females at the beginning, but it decreased subsequently through the breeding season. Contrarily, abundances were constantly low on adult males. Apparently, D. rufa postpones transmission until nestlings develop juvenile plumage and choose the more feathered individual among siblings. The sexual difference in the observed abundance could either be caused by the different plumage, or by the females' preference for less parasitized males. Moreover, females likely have more time to preen during the incubation period, lowering their louse burdens. Thus, sex-biased infestation levels likely arise due to parasite preferences in the nestlings and host behavioural processes in the adult falcons.

RevDate: 2020-03-13

Thomas HJD, Bjorkman AD, Myers-Smith IH, et al (2020)

Global plant trait relationships extend to the climatic extremes of the tundra biome.

Nature communications, 11(1):1351 pii:10.1038/s41467-020-15014-4.

The majority of variation in six traits critical to the growth, survival and reproduction of plant species is thought to be organised along just two dimensions, corresponding to strategies of plant size and resource acquisition. However, it is unknown whether global plant trait relationships extend to climatic extremes, and if these interspecific relationships are confounded by trait variation within species. We test whether trait relationships extend to the cold extremes of life on Earth using the largest database of tundra plant traits yet compiled. We show that tundra plants demonstrate remarkably similar resource economic traits, but not size traits, compared to global distributions, and exhibit the same two dimensions of trait variation. Three quarters of trait variation occurs among species, mirroring global estimates of interspecific trait variation. Plant trait relationships are thus generalizable to the edge of global trait-space, informing prediction of plant community change in a warming world.

RevDate: 2020-03-13
CmpDate: 2020-03-13

Memarzadeh M, C Boettiger (2019)

Resolving the Measurement Uncertainty Paradox in Ecological Management.

The American naturalist, 193(5):645-660.

Ecological management and decision-making typically focus on uncertainty about the future, but surprisingly little is known about how to account for uncertainty of the present: that is, the realities of having only partial or imperfect measurements. Our primary paradigms for handling decisions under uncertainty-the precautionary principle and optimal control-have so far given contradictory results. This paradox is best illustrated in the example of fisheries management, where many ideas that guide thinking about ecological decision-making were first developed. We find that simplistic optimal control approaches have repeatedly concluded that a manager should increase catch quotas when faced with greater uncertainty about the fish biomass. Current best practices take a more precautionary approach, decreasing catch quotas by a fixed amount to account for uncertainty. Using comparisons to both simulated and historical catch data, we find that neither approach is sufficient to avoid stock collapses under moderate observational uncertainty. Using partially observed Markov decision process (POMDP) methods, we demonstrate how this paradox arises from flaws in the standard theory, which contributes to overexploitation of fisheries and increased probability of economic and ecological collapse. In contrast, we find that POMDP-based management avoids such overexploitation while also generating higher economic value. These results have significant implications for how we handle uncertainty in both fisheries and ecological management more generally.

RevDate: 2020-03-09
CmpDate: 2020-03-09

Mair C, Nickbakhsh S, Reeve R, et al (2019)

Estimation of temporal covariances in pathogen dynamics using Bayesian multivariate autoregressive models.

PLoS computational biology, 15(12):e1007492.

It is well recognised that animal and plant pathogens form complex ecological communities of interacting organisms within their hosts, and there is growing interest in the health implications of such pathogen interactions. Although community ecology approaches have been used to identify pathogen interactions at the within-host scale, methodologies enabling robust identification of interactions from population-scale data such as that available from health authorities are lacking. To address this gap, we developed a statistical framework that jointly identifies interactions between multiple viruses from contemporaneous non-stationary infection time series. Our conceptual approach is derived from a Bayesian multivariate disease mapping framework. Importantly, our approach captures within- and between-year dependencies in infection risk while controlling for confounding factors such as seasonality, demographics and infection frequencies, allowing genuine pathogen interactions to be distinguished from simple correlations. We validated our framework using a broad range of synthetic data. We then applied it to diagnostic data available for five respiratory viruses co-circulating in a major urban population between 2005 and 2013: adenovirus, human coronavirus, human metapneumovirus, influenza B virus and respiratory syncytial virus. We found positive and negative covariances indicative of epidemiological interactions among specific virus pairs. This statistical framework enables a community ecology perspective to be applied to infectious disease epidemiology with important utility for public health planning and preparedness.

RevDate: 2020-03-06

Cullen CM, Aneja KK, Beyhan S, et al (2020)

Emerging Priorities for Microbiome Research.

Frontiers in microbiology, 11:136.

Microbiome research has increased dramatically in recent years, driven by advances in technology and significant reductions in the cost of analysis. Such research has unlocked a wealth of data, which has yielded tremendous insight into the nature of the microbial communities, including their interactions and effects, both within a host and in an external environment as part of an ecological community. Understanding the role of microbiota, including their dynamic interactions with their hosts and other microbes, can enable the engineering of new diagnostic techniques and interventional strategies that can be used in a diverse spectrum of fields, spanning from ecology and agriculture to medicine and from forensics to exobiology. From June 19-23 in 2017, the NIH and NSF jointly held an Innovation Lab on Quantitative Approaches to Biomedical Data Science Challenges in our Understanding of the Microbiome. This review is inspired by some of the topics that arose as priority areas from this unique, interactive workshop. The goal of this review is to summarize the Innovation Lab's findings by introducing the reader to emerging challenges, exciting potential, and current directions in microbiome research. The review is broken into five key topic areas: (1) interactions between microbes and the human body, (2) evolution and ecology of microbes, including the role played by the environment and microbe-microbe interactions, (3) analytical and mathematical methods currently used in microbiome research, (4) leveraging knowledge of microbial composition and interactions to develop engineering solutions, and (5) interventional approaches and engineered microbiota that may be enabled by selectively altering microbial composition. As such, this review seeks to arm the reader with a broad understanding of the priorities and challenges in microbiome research today and provide inspiration for future investigation and multi-disciplinary collaboration.

RevDate: 2020-02-18

Gallagher RV, Falster DS, Maitner BS, et al (2020)

Open Science principles for accelerating trait-based science across the Tree of Life.

Nature ecology & evolution pii:10.1038/s41559-020-1109-6 [Epub ahead of print].

Synthesizing trait observations and knowledge across the Tree of Life remains a grand challenge for biodiversity science. Species traits are widely used in ecological and evolutionary science, and new data and methods have proliferated rapidly. Yet accessing and integrating disparate data sources remains a considerable challenge, slowing progress toward a global synthesis to integrate trait data across organisms. Trait science needs a vision for achieving global integration across all organisms. Here, we outline how the adoption of key Open Science principles-open data, open source and open methods-is transforming trait science, increasing transparency, democratizing access and accelerating global synthesis. To enhance widespread adoption of these principles, we introduce the Open Traits Network (OTN), a global, decentralized community welcoming all researchers and institutions pursuing the collaborative goal of standardizing and integrating trait data across organisms. We demonstrate how adherence to Open Science principles is key to the OTN community and outline five activities that can accelerate the synthesis of trait data across the Tree of Life, thereby facilitating rapid advances to address scientific inquiries and environmental issues. Lessons learned along the path to a global synthesis of trait data will provide a framework for addressing similarly complex data science and informatics challenges.

RevDate: 2020-02-19
CmpDate: 2020-02-19

Hua ZS, Wang YL, Evans PN, et al (2019)

Insights into the ecological roles and evolution of methyl-coenzyme M reductase-containing hot spring Archaea.

Nature communications, 10(1):4574.

Several recent studies have shown the presence of genes for the key enzyme associated with archaeal methane/alkane metabolism, methyl-coenzyme M reductase (Mcr), in metagenome-assembled genomes (MAGs) divergent to existing archaeal lineages. Here, we study the mcr-containing archaeal MAGs from several hot springs, which reveal further expansion in the diversity of archaeal organisms performing methane/alkane metabolism. Significantly, an MAG basal to organisms from the phylum Thaumarchaeota that contains mcr genes, but not those for ammonia oxidation or aerobic metabolism, is identified. Together, our phylogenetic analyses and ancestral state reconstructions suggest a mostly vertical evolution of mcrABG genes among methanogens and methanotrophs, along with frequent horizontal gene transfer of mcr genes between alkanotrophs. Analysis of all mcr-containing archaeal MAGs/genomes suggests a hydrothermal origin for these microorganisms based on optimal growth temperature predictions. These results also suggest methane/alkane oxidation or methanogenesis at high temperature likely existed in a common archaeal ancestor.

RevDate: 2020-02-14
CmpDate: 2020-02-14

Kaczensky P, Khaliun S, Payne J, et al (2019)

Through the eye of a Gobi khulan - Application of camera collars for ecological research of far-ranging species in remote and highly variable ecosystems.

PloS one, 14(6):e0217772 pii:PONE-D-18-35632.

The Mongolian Gobi-Eastern Steppe Ecosystem is one of the largest remaining natural drylands and home to a unique assemblage of migratory ungulates. Connectivity and integrity of this ecosystem are at risk if increasing human activities are not carefully planned and regulated. The Gobi part supports the largest remaining population of the Asiatic wild ass (Equus hemionus; locally called "khulan"). Individual khulan roam over areas of thousands of square kilometers and the scale of their movements is among the largest described for terrestrial mammals, making them particularly difficult to monitor. Although GPS satellite telemetry makes it possible to track animals in near-real time and remote sensing provides environmental data at the landscape scale, remotely collected data also harbors the risk of missing important abiotic or biotic environmental variables or life history events. We tested the potential of animal born camera systems ("camera collars") to improve our understanding of the drivers and limitations of khulan movements. Deployment of a camera collar on an adult khulan mare resulted in 7,881 images over a one-year period. Over half of the images showed other khulan and 1,630 images showed enough of the collared khulan to classify the behaviour of the animals seen into several main categories. These khulan images provided us with: i) new insights into important life history events and grouping dynamics, ii) allowed us to calculate time budgets for many more animals than the collared khulan alone, and iii) provided us with a training dataset for calibrating data from accelerometer and tilt sensors in the collar. The images also allowed to document khulan behaviour near infrastructure and to obtain a day-time encounter rate between a specific khulan with semi-nomadic herders and their livestock. Lastly, the images allowed us to ground truth the availability of water by: i) confirming waterpoints predicted from other analyses, ii) detecting new waterpoints, and iii) compare precipitation records for rain and snow from landscape scale climate products with those documented by the camera collar. We discuss the added value of deploying camera collars on a subset of animals in remote, highly variable ecosystems for research and conservation.

RevDate: 2020-02-11
CmpDate: 2020-02-11

Jensen EL, Clement R, Kosta A, et al (2019)

A new widespread subclass of carbonic anhydrase in marine phytoplankton.

The ISME journal, 13(8):2094-2106.

Most aquatic photoautotrophs depend on CO2-concentrating mechanisms (CCMs) to maintain productivity at ambient concentrations of CO2, and carbonic anhydrase (CA) plays a key role in these processes. Here we present different lines of evidence showing that the protein LCIP63, identified in the marine diatom Thalassiosira pseudonana, is a CA. However, sequence analysis showed that it has a low identity with any known CA and therefore belongs to a new subclass that we designate as iota-CA. Moreover, LCIP63 unusually prefers Mn2+ to Zn2+ as a cofactor, which is potentially of ecological relevance since Mn2+ is more abundant than Zn2+ in the ocean. LCIP63 is located in the chloroplast and only expressed at low concentrations of CO2. When overexpressed using biolistic transformation, the rate of photosynthesis at limiting concentrations of dissolved inorganic carbon increased, confirming its role in the CCM. LCIP63 homologs are present in the five other sequenced diatoms and in other algae, bacteria, and archaea. Thus LCIP63 is phylogenetically widespread but overlooked. Analysis of the Tara Oceans database confirmed this and showed that LCIP63 is widely distributed in marine environments and is therefore likely to play an important role in global biogeochemical carbon cycling.

RevDate: 2020-02-06

Mascarenhas R, Ruziska FM, Moreira EF, et al (2019)

Integrating Computational Methods to Investigate the Macroecology of Microbiomes.

Frontiers in genetics, 10:1344.

Studies in microbiology have long been mostly restricted to small spatial scales. However, recent technological advances, such as new sequencing methodologies, have ushered an era of large-scale sequencing of environmental DNA data from multiple biomes worldwide. These global datasets can now be used to explore long standing questions of microbial ecology. New methodological approaches and concepts are being developed to study such large-scale patterns in microbial communities, resulting in new perspectives that represent a significant advances for both microbiology and macroecology. Here, we identify and review important conceptual, computational, and methodological challenges and opportunities in microbial macroecology. Specifically, we discuss the challenges of handling and analyzing large amounts of microbiome data to understand taxa distribution and co-occurrence patterns. We also discuss approaches for modeling microbial communities based on environmental data, including information on biological interactions to make full use of available Big Data. Finally, we summarize the methods presented in a general approach aimed to aid microbiologists in addressing fundamental questions in microbial macroecology, including classical propositions (such as "everything is everywhere, but the environment selects") as well as applied ecological problems, such as those posed by human induced global environmental changes.

RevDate: 2020-01-17

Llanos-Garrido A, Pérez-Tris J, JA Díaz (2019)

The combined use of raw and phylogenetically independent methods of outlier detection uncovers genome-wide dynamics of local adaptation in a lizard.

Ecology and evolution, 9(24):14356-14367.

Local adaptation is a dynamic process by which different allele combinations are selected in different populations at different times, and whose genetic signature can be inferred by genome-wide outlier analyses. We combined gene flow estimates with two methods of outlier detection, one of them independent of population coancestry (CIOA) and the other one not (ROA), to identify genetic variants favored when ecology promotes phenotypic convergence. We analyzed genotyping-by-sequencing data from five populations of a lizard distributed over an environmentally heterogeneous range that has been changing since the split of eastern and western lineages ca. 3 mya. Overall, western lizards inhabit forest habitat and are unstriped, whereas eastern ones inhabit shrublands and are striped. However, one population (Lerma) has unstriped phenotype despite its eastern ancestry. The analysis of 73,291 SNPs confirmed the east-west division and identified nonoverlapping sets of outliers (12 identified by ROA and 9 by CIOA). ROA revealed ancestral adaptive variation in the uncovered outliers that were subject to divergent selection and differently fixed for eastern and western populations at the extremes of the environmental gradient. Interestingly, such variation was maintained in Lerma, where we found high levels of heterozygosity for ROA outliers, whereas CIOA uncovered innovative variants that were selected only there. Overall, it seems that both the maintenance of ancestral variation and asymmetric migration have counterbalanced adaptive lineage splitting in our model species. This scenario, which is likely promoted by a changing and heterogeneous environment, could hamper ecological speciation of locally adapted populations despite strong genetic structure between lineages.

RevDate: 2020-01-23

vonHoldt BM, DeCandia AL, Heppenheimer E, et al (2020)

Heritability of interpack aggression in a wild pedigreed population of North American grey wolves.

Molecular ecology [Epub ahead of print].

Aggression is a quantitative trait deeply entwined with individual fitness. Mapping the genomic architecture underlying such traits is complicated by complex inheritance patterns, social structure, pedigree information and gene pleiotropy. Here, we leveraged the pedigree of a reintroduced population of grey wolves (Canis lupus) in Yellowstone National Park, Wyoming, USA, to examine the heritability of and the genetic variation associated with aggression. Since their reintroduction, many ecological and behavioural aspects have been documented, providing unmatched records of aggressive behaviour across multiple generations of a wild population of wolves. Using a linear mixed model, a robust genetic relationship matrix, 12,288 single nucleotide polymorphisms (SNPs) and 111 wolves, we estimated the SNP-based heritability of aggression to be 37% and an additional 14% of the phenotypic variation explained by shared environmental exposures. We identified 598 SNP genotypes from 425 grey wolves to resolve a consensus pedigree that was included in a heritability analysis of 141 individuals with SNP genotype, metadata and aggression data. The pedigree-based heritability estimate for aggression is 14%, and an additional 16% of the phenotypic variation was explained by shared environmental exposures. We find strong effects of breeding status and relative pack size on aggression. Through an integrative approach, these results provide a framework for understanding the genetic architecture of a complex trait that influences individual fitness, with linkages to reproduction, in a social carnivore. Along with a few other studies, we show here the incredible utility of a pedigreed natural population for dissecting a complex, fitness-related behavioural trait.

RevDate: 2020-01-15
CmpDate: 2020-01-08

Kattge J, Bönisch G, Díaz S, et al (2020)

TRY plant trait database - enhanced coverage and open access.

Global change biology, 26(1):119-188.

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.

RevDate: 2020-01-17

Tomazatos A, Jansen S, Pfister S, et al (2019)

Ecology of West Nile Virus in the Danube Delta, Romania: Phylogeography, Xenosurveillance and Mosquito Host-Feeding Patterns.

Viruses, 11(12):.

The ecology of West Nile virus (WNV) in the Danube Delta Biosphere Reserve (Romania) was investigated by combining studies on the virus genetics, phylogeography, xenosurveillance and host-feeding patterns of mosquitoes. Between 2014 and 2016, 655,667 unfed and 3842 engorged mosquito females were collected from four sampling sites. Blood-fed mosquitoes were negative for WNV-RNA, but two pools of unfed Culex pipiens s.l./torrentium collected in 2014 were tested positive. Our results suggest that Romania experienced at least two separate WNV lineage 2 introductions: from Africa into Danube Delta and from Greece into south-eastern Romania in the 1990s and early 2000s, respectively. The genetic diversity of WNV in Romania is primarily shaped by in situ evolution. WNV-specific antibodies were detected for 19 blood-meals from dogs and horses, but not from birds or humans. The hosts of mosquitoes were dominated by non-human mammals (19 species), followed by human and birds (23 species). Thereby, the catholic host-feeding pattern of Culex pipiens s.l./torrentium with a relatively high proportion of birds indicates the species' importance as a potential bridge vector. The low virus prevalence in combination with WNV-specific antibodies indicate continuous, but low activity of WNV in the Danube Delta during the study period.

RevDate: 2020-01-08

Romanuk TN, Binzer A, Loeuille N, et al (2019)

Simulated evolution assembles more realistic food webs with more functionally similar species than invasion.

Scientific reports, 9(1):18242 pii:10.1038/s41598-019-54443-0.

While natural communities are assembled by both ecological and evolutionary processes, ecological assembly processes have been studied much more and are rarely compared with evolutionary assembly processes. We address these disparities here by comparing community food webs assembled by simulating introductions of species from regional pools of species and from speciation events. Compared to introductions of trophically dissimilar species assumed to be more typical of invasions, introducing species trophically similar to native species assumed to be more typical of sympatric or parapatric speciation events caused fewer extinctions and assembled more empirically realistic networks by introducing more persistent species with higher trophic generality, vulnerability, and enduring similarity to native species. Such events also increased niche overlap and the persistence of both native and introduced species. Contrary to much competition theory, these findings suggest that evolutionary and other processes that more tightly pack ecological niches contribute more to ecosystem structure and function than previously thought.

RevDate: 2019-11-21

Podar D, Macalik K, Réti KO, et al (2019)

Morphological, physiological and biochemical aspects of salt tolerance of halophyte Petrosimonia triandra grown in natural habitat.

Physiology and molecular biology of plants : an international journal of functional plant biology, 25(6):1335-1347.

Salt tolerance mechanisms of halophyte Petrosimonia triandra, growing in its natural habitat in Cluj County, Romania, were investigated via biomass, growth parameters, water status, ion content, photosynthetic and antioxidative system efficiency, proline accumulation and lipid degradation. Two sampling sites with different soil electrical conductivities were selected: site 1: 3.14 dS m-1 and site 2: 4.45 dS m-1. Higher salinity proved to have a positive effect on growth. The relative water content did not decline severely, Na+ and K+ content of the roots, stem and leaves was more, and the functions of the photosynthetic apparatus and photosynthetic pigment contents were not altered. The efficiency of the antioxidative defence system was found to be assured by coordination of several reactive oxygen species scavengers. The presence of higher salinity led to accumulation of the osmolyte proline, while degradation of membrane lipids was reduced. As a whole, P. triandra evolved different adaptational strategies to counteract soil salinity, including morphological and physiological adaptations, preservation of photosynthetic activity, development of an efficient antioxidative system and accumulation of the osmotic compound, proline.

RevDate: 2019-12-25

Wang Y, Qiao M, Baikeli Y, et al (2020)

Soft-templated mesoporous carbon-modified glassy carbon electrode for sensitive and selective detection of aristolochic acids.

Journal of hazardous materials, 385:121550.

In this study, ordered mesoporous carbon (OMC) was synthesized by applying a soft template method, and its mesoporous structure was characterized by scanning electron microscopy, transmission electron microscopy, and nitrogen adsorption-desorption techniques. X-ray diffraction and Raman spectroscopic analyses were conducted to demonstrate the high graphitization and topological defects at the sample surface. An electrochemical sensor based on an OMC-modified glassy carbon electrode (OMC/GCE) was constructed to detect aristolochic acids (AAs) using cyclic voltammetry and linear sweep voltammetry. The dependence of the experimental parameters including solution pH, scan rate, and accumulation time were examined and optimized. Under the optimal conditions, the response of OMC/GCE was linear over wide concentration ranges of AAs (0.6-10 μM and 10-50 μM), with sensitivities of -1.77 and -0.31 μA/μM, respectively. The limit of detection was calculated to be 0.186 μM (at S/N = 3). Furthermore, the proposed OMC/GCE was applied to detect AAs in Asarum sieboldini and the content of AAs was calculated to be 8.9 μg/g with high accuracy and precision. In addition, the modified electrode also exhibited good selectivity, reproducibility, and stability. Therefore, the OMC/GCE can be used as a platform for the determination of AAs.

RevDate: 2019-11-15

Näpflin K, O'Connor EA, Becks L, et al (2019)

Genomics of host-pathogen interactions: challenges and opportunities across ecological and spatiotemporal scales.

PeerJ, 7:e8013.

Evolutionary genomics has recently entered a new era in the study of host-pathogen interactions. A variety of novel genomic techniques has transformed the identification, detection and classification of both hosts and pathogens, allowing a greater resolution that helps decipher their underlying dynamics and provides novel insights into their environmental context. Nevertheless, many challenges to a general understanding of host-pathogen interactions remain, in particular in the synthesis and integration of concepts and findings across a variety of systems and different spatiotemporal and ecological scales. In this perspective we aim to highlight some of the commonalities and complexities across diverse studies of host-pathogen interactions, with a focus on ecological, spatiotemporal variation, and the choice of genomic methods used. We performed a quantitative review of recent literature to investigate links, patterns and potential tradeoffs between the complexity of genomic, ecological and spatiotemporal scales undertaken in individual host-pathogen studies. We found that the majority of studies used whole genome resolution to address their research objectives across a broad range of ecological scales, especially when focusing on the pathogen side of the interaction. Nevertheless, genomic studies conducted in a complex spatiotemporal context are currently rare in the literature. Because processes of host-pathogen interactions can be understood at multiple scales, from molecular-, cellular-, and physiological-scales to the levels of populations and ecosystems, we conclude that a major obstacle for synthesis across diverse host-pathogen systems is that data are collected on widely diverging scales with different degrees of resolution. This disparity not only hampers effective infrastructural organization of the data but also data granularity and accessibility. Comprehensive metadata deposited in association with genomic data in easily accessible databases will allow greater inference across systems in the future, especially when combined with open data standards and practices. The standardization and comparability of such data will facilitate early detection of emerging infectious diseases as well as studies of the impact of anthropogenic stressors, such as climate change, on disease dynamics in humans and wildlife.

RevDate: 2019-11-04

Tamburello L, Papa L, Guarnieri G, et al (2019)

Are we ready for scaling up restoration actions? An insight from Mediterranean macroalgal canopies.

PloS one, 14(10):e0224477.

Extensive loss of macroalgal forests advocates for large-scale restoration interventions, to compensate habitat degradation and recover the associated ecological functions and services. Yet, restoration attempts have generally been limited to small spatial extensions, with the principal aim of developing efficient restoration techniques. Here, the success of outplanting Cystoseira amentacea v. stricta germlings cultured in aquaria was experimentally explored at a scale of tens of kms, by means of a multifactorial experimental design. In the intertidal rocky shores of SE Italy, locations with a continuous distribution for hundreds of meters or with few thalli forming patches of few centimeters of C. amentacea canopy were selected. In each location, the effects of adult conspecifics and the exclusion of macrograzers (salema fish and sea urchins) on the survival of germlings were tested. We evaluated the most critical determinants of mortality for germlings, including the overlooked pressure of mesograzers (e.g. amphipods, small mollusks, polychaetes). Despite the high mortality observed during outplanting and early settlement stages, survival of C. amentacea germlings was consistently favored by the exclusion of macrograzers, while the presence of adult conspecifics had no effects. In addition, the cost analysis of the interventions showed the feasibility of the ex-situ method, representing an essential tool for preserving Cystoseira forests. Large scale restoration is possible but requires baseline information with an in-depth knowledge of the species ecology and of the areas to be restored, together with the development of specific cultivation protocols to make consistently efficient restoration interventions.

RevDate: 2019-11-17

Palomo I, Dujardin Y, Midler E, et al (2019)

Modeling trade-offs across carbon sequestration, biodiversity conservation, and equity in the distribution of global REDD+ funds.

Proceedings of the National Academy of Sciences of the United States of America, 116(45):22645-22650.

The program on Reducing Emissions from Deforestation and Forest Degradation (REDD+) is one of the major attempts to tackle climate change mitigation in developing countries. REDD+ seeks to provide result-based incentives to promote emission reductions and increase carbon sinks in forest land while promoting other cobenefits, such as the conservation of biodiversity. We model different scenarios of international REDD+ funds distribution toward potential recipient countries using 2 carbon emission reduction targets (20% and 50% compared to the baseline scenario, i.e., deforestation and forest degradation without REDD+) by 2030. The model combines the prioritization of environmental outcomes in terms of carbon sequestration and biodiversity conservation and social equity, accounting for the equitable distribution of international REDD+ funds. Results highlight the synergy between carbon sequestration and biodiversity conservation under alternative fund allocation criteria, especially for scenarios of low carbon emission reduction. Trade-offs increase when distributional equity is considered as an additional criterion, especially under higher equity requirements. The analysis helps to better understand the inherent trade-offs between enhancing distributional equity and meeting environmental targets under alternative REDD+ fund allocation options.

RevDate: 2020-02-04
CmpDate: 2020-02-04

Shen L, Li XW, Meng XX, et al (2019)

Prediction of the globally ecological suitability of Panax quinquefolius by the geographic information system for global medicinal plants (GMPGIS).

Chinese journal of natural medicines, 17(7):481-489.

American ginseng (Panax quinquefolius L.) is a well-known Asian traditional herbal medicine with a large market demand. The plant is native to eastern North America, and its main producing areas worldwide are decreasing due to continuous cropping obstacles and environmental changes. Therefore, the identification of maximum similarities of new ecological distribution of P. quinquefolius, and prediction of its response to climate change in the future are necessary for plant introduction and cultivation. In this study, the areas with potential ecological suitability for P. quinquefolius were predicted using the geographic information system for global medicinal plants (GMPGIS) based on 476 occurrence points and 19 bioclimatic variables. The results indicate that the new ecologically suitable areas for P. quinquefolius are East Asia and the mid-eastern Europe, which are mainly distributed in China, Russia, Japan, Ukraine, Belarus, North Korean, South Korea, andRomania. Under global climate change scenarios, the suitable planting areas for P. quinquefolius would be increased by 9.16%-30.97%, and expandingnorth and west over the current ecologically suitable areas by 2070. The potential increased areas that are ecologically suitable include northern Canada, Eastern Europe, and the Lesser Khingan Mountains of China, and reduced regions are mainly in central China, the southern U.S., and southern Europe. Jackknife tests indicate that the precipitation of the warmest quarter was the important climatic factor controlling the distribution of P. quinquefolius. Our findings can be used as auseful guide for P. quinquefolius introduction and cultivation in ecologically suitable areas.

RevDate: 2020-01-20
CmpDate: 2020-01-20

Becker AD, Wesolowski A, Bjørnstad ON, et al (2019)

Long-term dynamics of measles in London: Titrating the impact of wars, the 1918 pandemic, and vaccination.

PLoS computational biology, 15(9):e1007305 pii:PCOMPBIOL-D-19-00008.

A key question in ecology is the relative impact of internal nonlinear dynamics and external perturbations on the long-term trajectories of natural systems. Measles has been analyzed extensively as a paradigm for consumer-resource dynamics due to the oscillatory nature of the host-pathogen life cycle, the abundance of rich data to test theory, and public health relevance. The dynamics of measles in London, in particular, has acted as a prototypical test bed for such analysis using incidence data from the pre-vaccination era (1944-1967). However, during this timeframe there were few external large-scale perturbations, limiting an assessment of the relative impact of internal and extra demographic perturbations to the host population. Here, we extended the previous London analyses to include nearly a century of data that also contains four major demographic changes: the First and Second World Wars, the 1918 influenza pandemic, and the start of a measles mass vaccination program. By combining mortality and incidence data using particle filtering methods, we show that a simple stochastic epidemic model, with minimal historical specifications, can capture the nearly 100 years of dynamics including changes caused by each of the major perturbations. We show that the majority of dynamic changes are explainable by the internal nonlinear dynamics of the system, tuned by demographic changes. In addition, the 1918 influenza pandemic and World War II acted as extra perturbations to this basic epidemic oscillator. Our analysis underlines that long-term ecological and epidemiological dynamics can follow very simple rules, even in a non-stationary population subject to significant perturbations and major secular changes.

RevDate: 2020-02-05

Pranovi F, Libralato S, Zucchetta M, et al (2020)

Cumulative biomass curves describe past and present conditions of Large Marine Ecosystems.

Global change biology, 26(2):786-797.

Implementing the Ecosystem Approach in marine ecosystems is moving from preliminary steps-dedicated to defining the optimal features for indicators and developing efficient indicator frameworks-towards an operational phase where multisector marine management decisions are executed using this information. Within this operational context, emergent ecosystem properties are becoming quite promising as they have been demonstrated to be globally widespread and repeatable, and to be quite effective in detecting significant state variations of complex systems. Biomass accumulation across TLs (CumB-TL) combines two important emergent properties of an ecosystem (energy flow, in terms of transfer efficiency, and storage, expressed as biomass), both amenable to detecting rapid ecosystem change. However, for further application, it is crucial to understand which types of drivers an indicator is sensitive to and how robust it is in relation to modifications of the external conditions and/or the system state. Here we address some outstanding questions of these CumB-TL curves related to their sensitivity to various drivers by carrying out a global scale assessment (using data from 62 LMEs) over six decades (1950-2010). We confirm the consistency of the S-pattern across all the LMEs, independent from latitude, ecosystem, environmental conditions, and stress level. The dynamics of the curve shape showed a tendency to stretch (i.e. decrease of steepness), in the presence of external disturbance and conversely to increase in steepness and shift towards higher TL in the case of recovery from stressed conditions. Our results suggest the presence of three main types of ecosystem dynamics, those showing an almost continuous increase in ecological state over time, those showing a continuous decrease in ecological state over time, and finally those showing a mixed behaviour flipping between recovering and degrading phases. These robust patterns suggest that the CumB-TL curve approach has some useful properties for use in further advancing the implementation of the Ecosystem Approach, allowing us to detect the state of a given marine ecosystem based on the dynamics of its curve shape, by using readily available time series data. The value of being able to identify conditions that might require management actions is quite high and, in many respects, represents the main objective in the context of an Ecosystem Approach, with large applications for detecting and responding to global changes in marine ecosystems.

RevDate: 2019-11-08
CmpDate: 2019-11-08

Reaney SM, Mackay EB, Haygarth PM, et al (2019)

Identifying critical source areas using multiple methods for effective diffuse pollution mitigation.

Journal of environmental management, 250:109366.

Diffuse pollution from agriculture constitutes a key pressure on the water quality of freshwaters and is frequently the cause of ecological degradation. The problem of diffuse pollution can be conceptualised with a source-mobilisation-pathway (or delivery)-impact model, whereby the combination of high source risk and strong connected pathways leads to 'critical source areas' (CSAs). These areas are where most diffuse pollution will originate, and hence are the optimal places to implement mitigation measures. However, identifying the locations of these areas is a key problem across different spatial scales within catchments. A number of approaches are frequently used for this assessment, although comparisons of these assessments are rarely carried out. We evaluate the CSAs identified via traditional walkover surveys supported by three different approaches, highlighting their benefits and disadvantages. These include a custom designed smartphone app; a desktop geographic information system (GIS) and terrain analysis-based SCIMAP (Sensitive Catchment Integrated Modelling and Analysis Platform) approach; and the use of a high spatial resolution drone dataset as an improved input data for SCIMAP modelling. Each of these methods captures the locations of the CSAs, revealing similarities and differences in the prioritisation of CSA features. The differences are due to the temporal and spatial resolution of the three methods such as the use of static land cover information, the ability to capture small scale features, such as gateways and the incomplete catchment coverage of the walkover survey. The relative costs and output resolutions of the three methods indicate that they are suitable for application at different catchment scales in conjunction with other methods. Based on the results in this paper, it is recommended that a multi-evidence-based approach to diffuse pollution management is taken across catchment spatial scales, incorporating local knowledge from the walkover with the different data resolutions of the SCIMAP approach.

RevDate: 2019-11-08
CmpDate: 2019-11-08

Pereira-Flores E, Glöckner FO, A Fernandez-Guerra (2019)

Fast and accurate average genome size and 16S rRNA gene average copy number computation in metagenomic data.

BMC bioinformatics, 20(1):453 pii:10.1186/s12859-019-3031-y.

BACKGROUND: Metagenomics caused a quantum leap in microbial ecology. However, the inherent size and complexity of metagenomic data limit its interpretation. The quantification of metagenomic traits in metagenomic analysis workflows has the potential to improve the exploitation of metagenomic data. Metagenomic traits are organisms' characteristics linked to their performance. They are measured at the genomic level taking a random sample of individuals in a community. As such, these traits provide valuable information to uncover microorganisms' ecological patterns. The Average Genome Size (AGS) and the 16S rRNA gene Average Copy Number (ACN) are two highly informative metagenomic traits that reflect microorganisms' ecological strategies as well as the environmental conditions they inhabit.

RESULTS: Here, we present the ags.sh and acn.sh tools, which analytically derive the AGS and ACN metagenomic traits. These tools represent an advance on previous approaches to compute the AGS and ACN traits. Benchmarking shows that ags.sh is up to 11 times faster than state-of-the-art tools dedicated to the estimation AGS. Both ags.sh and acn.sh show comparable or higher accuracy than existing tools used to estimate these traits. To exemplify the applicability of both tools, we analyzed the 139 prokaryotic metagenomes of TARA Oceans and revealed the ecological strategies associated with different water layers.

CONCLUSION: We took advantage of recent advances in gene annotation to develop the ags.sh and acn.sh tools to combine easy tool usage with fast and accurate performance. Our tools compute the AGS and ACN metagenomic traits on unassembled metagenomes and allow researchers to improve their metagenomic data analysis to gain deeper insights into microorganisms' ecology. The ags.sh and acn.sh tools are publicly available using Docker container technology at https://github.com/pereiramemo/AGS-and-ACN-tools .

RevDate: 2019-12-03
CmpDate: 2019-12-03

Giri S, Zhang Z, Krasnuk D, et al (2019)

Evaluating the impact of land uses on stream integrity using machine learning algorithms.

The Science of the total environment, 696:133858.

A general pattern of declining aquatic ecological integrity with increasing urban land use has been well established for a number of watersheds worldwide. A more nuanced characterization of the influence of different urban land uses and the determination of cumulative thresholds will further inform watershed planning and management. To this end, we investigated the utility of two machine learning algorithms (Random Forests (RF) and Boosted Regression Trees (BRT)) to model stream impairment through multimetric macroinvertebrate index known as High Gradient Macroinvertebrate Index (HGMI) in an urbanizing watershed located in north-central New Jersey, United States. These machine learning algorithms were able to explain at least 50% of the variability of stream integrity based on watershed land use/land cover. While comparable in results, RF was found to be easier to train and was somewhat more robust to model overfitting compared to BRT. Our results document the influence of increasing high-medium density (> 30% Impervious Surface cover (ISC)), low density (15-30% ISC) urban and transitional/barren land had in negatively affecting stream biological integrity. The thresholds generated by partial plots suggest that the stream integrity decreased abruptly when the percentage of high-medium and low density urban, and transitional/barren land went above 10%, 8%, and 2% of the watershed, respectively. Additionally, when rural residential surpassed 30% threshold, it behaved similar to low density urban towards stream integrity. Identification of such cumulative thresholds can help watershed managers and policymakers to craft land use zoning regulations and design restoration programs that are grounded by objective scientific criteria.

RevDate: 2020-01-20
CmpDate: 2020-01-20

Miele V, Guill C, Ramos-Jiliberto R, et al (2019)

Non-trophic interactions strengthen the diversity-functioning relationship in an ecological bioenergetic network model.

PLoS computational biology, 15(8):e1007269 pii:PCOMPBIOL-D-18-02071.

Ecological communities are undeniably diverse, both in terms of the species that compose them as well as the type of interactions that link species to each other. Despite this long recognition of the coexistence of multiple interaction types in nature, little is known about the consequences of this diversity for community functioning. In the ongoing context of global change and increasing species extinction rates, it seems crucial to improve our understanding of the drivers of the relationship between species diversity and ecosystem functioning. Here, using a multispecies dynamical model of ecological communities including various interaction types (e.g. competition for space, predator interference, recruitment facilitation in addition to feeding), we studied the role of the presence and the intensity of these interactions for species diversity, community functioning (biomass and production) and the relationship between diversity and functioning.Taken jointly, the diverse interactions have significant effects on species diversity, whose amplitude and sign depend on the type of interactions involved and their relative abundance. They however consistently increase the slope of the relationship between diversity and functioning, suggesting that species losses might have stronger effects on community functioning than expected when ignoring the diversity of interaction types and focusing on feeding interactions only.

RevDate: 2020-01-19

Lemos LN, Medeiros JD, Dini-Andreote F, et al (2019)

Genomic signatures and co-occurrence patterns of the ultra-small Saccharimonadia (phylum CPR/Patescibacteria) suggest a symbiotic lifestyle.

Molecular ecology, 28(18):4259-4271.

The size of bacterial genomes is often associated with organismal metabolic capabilities determining ecological breadth and lifestyle. The recently proposed Candidate Phyla Radiation (CPR)/Patescibacteria encompasses mostly unculturable bacterial taxa with relatively small genome sizes with potential for co-metabolism interdependencies. As yet, little is known about the ecology and evolution of CPR, particularly with respect to how they might interact with other taxa. Here, we reconstructed two novel genomes (namely, Candidatus Saccharibacter sossegus and Candidatus Chaer renensis) of taxa belonging to the class Saccharimonadia within the CPR/Patescibacteria using metagenomes obtained from acid mine drainage (AMD). By testing the hypothesis of genome streamlining or symbiotic lifestyle, our results revealed clear signatures of gene losses in these genomes, such as those associated with de novo biosynthesis of essential amino acids, nucleotides, fatty acids and cofactors. In addition, co-occurrence analysis provided evidence supporting potential symbioses of these organisms with Hydrotalea sp. in the AMD system. Together, our findings provide a better understanding of the ecology and evolution of CPR/Patescibacteria and highlight the importance of genome reconstruction for studying metabolic interdependencies between unculturable Saccharimonadia representatives.

RevDate: 2019-09-03
CmpDate: 2019-09-03

Wang QL, Han YJ, Zhang LP, et al (2019)

[GIS-based ecological climate suitability regionalization for Cordyceps sinensis in Shiqu County, Sichuan Province, China.].

Ying yong sheng tai xue bao = The journal of applied ecology, 30(7):2137-2144.

Based on the biological characteristics of Cordyceps sinensis, combined with the spatial and temporal distribution characteristics of local agro-climatic resources and the investigation data of C. sinensis resources, we investigated the ecological climate suitability regionalization and the spatial distribution of C. sinensis in Shiqu County using mathematical statistics analysis, optimization method and GIS spatial analysis. We used altitude, mean annual temperature, mean annual precipitation, vegetation, and soil as the leading indicators and topographic gradient as the auxiliary indicators, as the main basis for the suitability zoning of C. sinensis resources. The results showed that C. sinensis grew in most of the townships in Shiqu County, with their distribution areas being fragmented and scattered, showing sporadic patches and blocks. They were mainly distributed in east and west parts of the county and in the Zhaqu River basin in the central part. The suitable distribution area for C. sinensis in Shiqu was 4000-4700 m above sea level, with mean annual temperature of -2.5-3 ℃ and mean annual precipitation of 550-850 mm. The growth environment was generally alpine mea-dow and subalpine meadow with good hydrophobicity and slope of 15°-50°. The suitable growth environment and meteorological conditions were beneficial to the growth and development of feeding plants and bat moths. The unsuitable area was in the high mountain area above the river wide valley area, pastoral area, wetland, or snowline.

RevDate: 2020-01-08
CmpDate: 2019-10-17

Liu Y, Schwalm CR, Samuels-Crow KE, et al (2019)

Ecological memory of daily carbon exchange across the globe and its importance in drylands.

Ecology letters, 22(11):1806-1816.

How do antecedent (past) conditions influence land-carbon dynamics after those conditions no longer persist? In particular, quantifying such memory effects associated with the influence of past environmental (exogenous) and biological (endogenous) conditions is crucial for understanding and predicting the carbon cycle. Here we show, using data from 42 eddy covariance sites across six major biomes, that ecological memory-decomposed into environmental and biological memory components-of daily net carbon exchange (NEE) is critical for understanding the land-carbon metabolism, especially in drylands for which memory explains ~ 32% of the variation in NEE. The strong environmental memory in drylands was primarily driven by short- and long-term moisture status. Moreover, the strength of environmental memory scales with increasing water stress. This universal scaling relationship, emerging within and among major biomes, suggests a potential adaptive response to water limitation. Our findings underscore the necessity of considering ecological memory in experiments, observations and modelling.

RevDate: 2019-11-08
CmpDate: 2019-11-08

Saedpanah S, J Amanollahi (2019)

Environmental pollution and geo-ecological risk assessment of the Qhorveh mining area in western Iran.

Environmental pollution (Barking, Essex : 1987), 253:811-820.

In order to evaluate the effect of mining activity on the environment of the Qhorveh mining area in the west of Iran, the geological, ecological and environmental data, related to social development and regional economic status, were used. The geological data included seven sub-indices, such as vegetation coverage, land utilization type, and fault activity; ecological data, with two sub-indices, such as degree of ecological environment recovery; and finally, environmental data, with three sub-indices, such as soil and dust pollutions. These were selected based on the literature and expert opinion which were utilized for environmental pollution and geo-ecological (EPGE) risk assessment of the study site. Remote sensing (RS) image, field sampling, digital elevation map, and data retrieved from different government agencies were used to generate layers for the sub-indices in the geographic information system (GIS) environment. In addition, the analytical hierarchy process (AHP) method was used to determine the weight of sub-indices. Five levels consisting of best, good, middle, poor and worst were used to describe the EPGE risk assessment of the Qhorveh mining area. Results showed that worst and poor levels of EPGE risk are in the east and northeast of the study area where the gold and pumice mines are located while best and good levels of EPGE risk are in its center where the stone mines are located. According to the results of this research, the EPGE risk assessment of the Qhorveh mining area is affected by the environmental pollution index with its highest weight (0.3908). It can be concluded that the integration of the RS, GIS and AHP methods proposed in this study improved the evaluation quality of EPGE risk assessment.

RevDate: 2020-01-08
CmpDate: 2019-12-11

Fountain-Jones NM, Machado G, Carver S, et al (2019)

How to make more from exposure data? An integrated machine learning pipeline to predict pathogen exposure.

The Journal of animal ecology, 88(10):1447-1461.

Predicting infectious disease dynamics is a central challenge in disease ecology. Models that can assess which individuals are most at risk of being exposed to a pathogen not only provide valuable insights into disease transmission and dynamics but can also guide management interventions. Constructing such models for wild animal populations, however, is particularly challenging; often only serological data are available on a subset of individuals and nonlinear relationships between variables are common. Here we provide a guide to the latest advances in statistical machine learning to construct pathogen-risk models that automatically incorporate complex nonlinear relationships with minimal statistical assumptions from ecological data with missing data. Our approach compares multiple machine learning algorithms in a unified environment to find the model with the best predictive performance and uses game theory to better interpret results. We apply this framework on two major pathogens that infect African lions: canine distemper virus (CDV) and feline parvovirus. Our modelling approach provided enhanced predictive performance compared to more traditional approaches, as well as new insights into disease risks in a wild population. We were able to efficiently capture and visualize strong nonlinear patterns, as well as model complex interactions between variables in shaping exposure risk from CDV and feline parvovirus. For example, we found that lions were more likely to be exposed to CDV at a young age but only in low rainfall years. When combined with our data calibration approach, our framework helped us to answer questions about risk of pathogen exposure that are difficult to address with previous methods. Our framework not only has the potential to aid in predicting disease risk in animal populations, but also can be used to build robust predictive models suitable for other ecological applications such as modelling species distribution or diversity patterns.

RevDate: 2019-07-26

Flórián N, Ladányi M, Ittzés A, et al (2019)

Effects of single and repeated drought on soil microarthropods in a semi-arid ecosystem depend more on timing and duration than drought severity.

PloS one, 14(7):e0219975 pii:PONE-D-18-35187.

Soil moisture is one of the most important factors affecting soil biota. In arid and semi-arid ecosystems, soil mesofauna is adapted to temporary drought events, but, until now, we have had a limited understanding of the impacts of the different magnitudes and frequencies of drought predicted to occur according to future climate change scenarios. The present study focuses on how springtails and mites respond to simulated repeated drought events of different magnitudes in a field experiment in a Hungarian semi-arid sand steppe. Changes in soil arthropod activities were monitored with soil trapping over two years in a sandy soil. In the first year (2014), we applied an extreme drought pretreatment, and in the consecutive year, we applied less devastating treatments (severe drought, moderate drought, water addition) to these sites. In the first year, the extreme drought pretreatment tended to have a negative effect (either significantly or not significantly) on the capture of all Collembola groups, whereas all mite groups increased in activity density. However, in the consecutive year, between the extreme drought and control treatments, we only detected differences in soil microbial biomass. In the cases of severe drought, moderate drought and water addition, we did not find considerable changes across the microarthropods, except in the case of epedaphic Collembola. In the cases of the water addition and drought treatments, the duration and timing of the manipulation seemed to be more important for soil mesofauna than their severity (i.e., the level of soil moisture decrease). We suggest that in these extreme habitats, soil mesofauna are able to survive extreme conditions, and their populations recover rapidly, but they may not be able to cope with very long drought periods.

RevDate: 2019-11-22
CmpDate: 2019-11-21

di Porcia E Brugnera M, Meunier F, Longo M, et al (2019)

Modeling the impact of liana infestation on the demography and carbon cycle of tropical forests.

Global change biology, 25(11):3767-3780.

There is mounting empirical evidence that lianas affect the carbon cycle of tropical forests. However, no single vegetation model takes into account this growth form, although such efforts could greatly improve the predictions of carbon dynamics in tropical forests. In this study, we incorporated a novel mechanistic representation of lianas in a dynamic global vegetation model (the Ecosystem Demography Model). We developed a liana-specific plant functional type and mechanisms representing liana-tree interactions (such as light competition, liana-specific allometries, and attachment to host trees) and parameterized them according to a comprehensive literature meta-analysis. We tested the model for an old-growth forest (Paracou, French Guiana) and a secondary forest (Gigante Peninsula, Panama). The resulting model simulations captured many features of the two forests characterized by different levels of liana infestation as revealed by a systematic comparison of the model outputs with empirical data, including local census data from forest inventories, eddy flux tower data, and terrestrial laser scanner-derived forest vertical structure. The inclusion of lianas in the simulations reduced the secondary forest net productivity by up to 0.46 tC ha-1 year-1 , which corresponds to a limited relative reduction of 2.6% in comparison with a reference simulation without lianas. However, this resulted in significantly reduced accumulated above-ground biomass after 70 years of regrowth by up to 20 tC /ha (19% of the reference simulation). Ultimately, the simulated negative impact of lianas on the total biomass was almost completely cancelled out when the forest reached an old-growth successional stage. Our findings suggest that lianas negatively influence the forest potential carbon sink strength, especially for young, disturbed, liana-rich sites. In light of the critical role that lianas play in the profound changes currently experienced by tropical forests, this new model provides a robust numerical tool to forecast the impact of lianas on tropical forest carbon sinks.

RevDate: 2019-12-17
CmpDate: 2019-12-09

Meola M, Rifa E, Shani N, et al (2019)

DAIRYdb: a manually curated reference database for improved taxonomy annotation of 16S rRNA gene sequences from dairy products.

BMC genomics, 20(1):560 pii:10.1186/s12864-019-5914-8.

BACKGROUND: Reads assignment to taxonomic units is a key step in microbiome analysis pipelines. To date, accurate taxonomy annotation of 16S reads, particularly at species rank, is still challenging due to the short size of read sequences and differently curated classification databases. The close phylogenetic relationship between species encountered in dairy products, however, makes it crucial to annotate species accurately to achieve sufficient phylogenetic resolution for further downstream ecological studies or for food diagnostics. Curated databases dedicated to the environment of interest are expected to improve the accuracy and resolution of taxonomy annotation.

RESULTS: We provide a manually curated database composed of 10'290 full-length 16S rRNA gene sequences from prokaryotes tailored for dairy products analysis (https://github.com/marcomeola/DAIRYdb). The performance of the DAIRYdb was compared with the universal databases Silva, LTP, RDP and Greengenes. The DAIRYdb significantly outperformed all other databases independently of the classification algorithm by enabling higher accurate taxonomy annotation down to the species rank. The DAIRYdb accurately annotates over 90% of the sequences of either single or paired hypervariable regions automatically. The manually curated DAIRYdb strongly improves taxonomic annotation accuracy for microbiome studies in dairy environments. The DAIRYdb is a practical solution that enables automatization of this key step, thus facilitating the routine application of NGS microbiome analyses for microbial ecology studies and diagnostics in dairy products.

RevDate: 2020-01-20
CmpDate: 2020-01-20

Edwards RA, Vega AA, Norman HM, et al (2019)

Global phylogeography and ancient evolution of the widespread human gut virus crAssphage.

Nature microbiology, 4(10):1727-1736.

Microbiomes are vast communities of microorganisms and viruses that populate all natural ecosystems. Viruses have been considered to be the most variable component of microbiomes, as supported by virome surveys and examples of high genomic mosaicism. However, recent evidence suggests that the human gut virome is remarkably stable compared with that of other environments. Here, we investigate the origin, evolution and epidemiology of crAssphage, a widespread human gut virus. Through a global collaboration, we obtained DNA sequences of crAssphage from more than one-third of the world's countries and showed that the phylogeography of crAssphage is locally clustered within countries, cities and individuals. We also found fully colinear crAssphage-like genomes in both Old-World and New-World primates, suggesting that the association of crAssphage with primates may be millions of years old. Finally, by exploiting a large cohort of more than 1,000 individuals, we tested whether crAssphage is associated with bacterial taxonomic groups of the gut microbiome, diverse human health parameters and a wide range of dietary factors. We identified strong correlations with different clades of bacteria that are related to Bacteroidetes and weak associations with several diet categories, but no significant association with health or disease. We conclude that crAssphage is a benign cosmopolitan virus that may have coevolved with the human lineage and is an integral part of the normal human gut virome.

RevDate: 2020-01-08
CmpDate: 2020-01-08

Watson AK, Lannes R, Pathmanathan JS, et al (2019)

The Methodology Behind Network Thinking: Graphs to Analyze Microbial Complexity and Evolution.

Methods in molecular biology (Clifton, N.J.), 1910:271-308.

In the post genomic era, large and complex molecular datasets from genome and metagenome sequencing projects expand the limits of what is possible for bioinformatic analyses. Network-based methods are increasingly used to complement phylogenetic analysis in studies in molecular evolution, including comparative genomics, classification, and ecological studies. Using network methods, the vertical and horizontal relationships between all genes or genomes, whether they are from cellular chromosomes or mobile genetic elements, can be explored in a single expandable graph. In recent years, development of new methods for the construction and analysis of networks has helped to broaden the availability of these approaches from programmers to a diversity of users. This chapter introduces the different kinds of networks based on sequence similarity that are already available to tackle a wide range of biological questions, including sequence similarity networks, gene-sharing networks and bipartite graphs, and a guide for their construction and analyses.

RevDate: 2019-10-24
CmpDate: 2019-08-30

Ha S, Z Yang (2019)

Evaluation for landscape aesthetic value of the Natural World Heritage Site.

Environmental monitoring and assessment, 191(8):483.

The landscape aesthetic value (LAV) is one essential component of outstanding universal value (OUV) for a Natural World Heritage Site (NWHS). In the identification of LAV, there is the subjectivity of methodology suggested by IUCN in the operation manual, and the expert-led evaluation is insufficient for reflecting all observers' opinions. This study focuses on establishing a universal system combining the subjectivity and objectivity, the experts' and the public's opinions to evaluate the LAV of an NWHS. We used the NWHS criteria, the ecological environment, and the viewing experience as established indicators; nine metrics were applied as corresponding layers respectively to map and give a final spatial evaluation based on the ArcGIS overlay analysis with their comprehensive weights from 3 groups of decision makers. In order to verify the rationality of our model, the LAV of a case study in Bayanbulak of NWHS Xinjiang Tianshan has been evaluated. It is demonstrated that central region of Bayanbulak with unique landscape that taking rivers, lakes, and swamps as base interlacing with wetland meadows has particularly high LAV; it basically shows a concentric circle-like distribution feature that LAV decreases from inside to outside and is consistent with practical protection status. This study responds to the UNESCO's request to monitor and evaluate the OUV of the NWHS; we believe results can provide a useful reference for the planning and decision-making of relevant scenic spots.

RevDate: 2019-12-19
CmpDate: 2019-12-19

Ruess J, Pleška M, Guet CC, et al (2019)

Molecular noise of innate immunity shapes bacteria-phage ecologies.

PLoS computational biology, 15(7):e1007168 pii:PCOMPBIOL-D-19-00148.

Mathematical models have been used successfully at diverse scales of biological organization, ranging from ecology and population dynamics to stochastic reaction events occurring between individual molecules in single cells. Generally, many biological processes unfold across multiple scales, with mutations being the best studied example of how stochasticity at the molecular scale can influence outcomes at the population scale. In many other contexts, however, an analogous link between micro- and macro-scale remains elusive, primarily due to the challenges involved in setting up and analyzing multi-scale models. Here, we employ such a model to investigate how stochasticity propagates from individual biochemical reaction events in the bacterial innate immune system to the ecology of bacteria and bacterial viruses. We show analytically how the dynamics of bacterial populations are shaped by the activities of immunity-conferring enzymes in single cells and how the ecological consequences imply optimal bacterial defense strategies against viruses. Our results suggest that bacterial populations in the presence of viruses can either optimize their initial growth rate or their population size, with the first strategy favoring simple immunity featuring a single restriction modification system and the second strategy favoring complex bacterial innate immunity featuring several simultaneously active restriction modification systems.

RevDate: 2020-01-08

Pepin KM, Pedersen K, Wan XF, et al (2019)

Individual-Level Antibody Dynamics Reveal Potential Drivers of Influenza A Seasonality in Wild Pig Populations.

Integrative and comparative biology, 59(5):1231-1242.

Swine are important in the ecology of influenza A virus (IAV) globally. Understanding the ecological role of wild pigs in IAV ecology has been limited because surveillance in wild pigs is often for antibodies (serosurveillance) rather than IAVs, as in humans and domestic swine. As IAV antibodies can persist long after an infection, serosurveillance data are not necessarily indicative of current infection risk. However, antibody responses to IAV infections cause a predictable antibody response, thus time of infection can be inferred from antibody levels in serological samples, enabling identification of risk factors of infection at estimated times of infection. Recent work demonstrates that these quantitative antibody methods (QAMs) can accurately recover infection dates, even when individual-level variation in antibody curves is moderately high. Also, the methodology can be implemented in a survival analysis (SA) framework to reduce bias from opportunistic sampling. Here we integrated QAMs and SA and applied this novel QAM-SA framework to understand the dynamics of IAV infection risk in wild pigs seasonally and spatially, and identify risk factors. We used national-scale IAV serosurveillance data from 15 US states. We found that infection risk was highest during January-March (54% of 61 estimated peaks), with 24% of estimated peaks occurring from May to July, and some low-level of infection risk occurring year-round. Time-varying IAV infection risk in wild pigs was positively correlated with humidity and IAV infection trends in domestic swine and humans, and did not show wave-like spatial spread of infection among states, nor more similar levels of infection risk among states with more similar meteorological conditions. Effects of host sex on IAV infection risk in wild pigs were generally not significant. Because most of the variation in infection risk was explained by state-level factors or infection risk at long-distances, our results suggested that predicting IAV infection risk in wild pigs is complicated by local ecological factors and potentially long-distance translocation of infection. In addition to revealing factors of IAV infection risk in wild pigs, our framework is broadly applicable for quantifying risk factors of disease transmission using opportunistic serosurveillance sampling, a common methodology in wildlife disease surveillance. Future research on the factors that determine individual-level antibody kinetics will facilitate the design of serosurveillance systems that can extract more accurate estimates of time-varying disease risk from quantitative antibody data.

RevDate: 2019-12-02
CmpDate: 2019-12-02

Michalska-Smith MJ, S Allesina (2019)

Telling ecological networks apart by their structure: A computational challenge.

PLoS computational biology, 15(6):e1007076 pii:PCOMPBIOL-D-18-01703.

Ecologists have been compiling ecological networks for over a century, detailing the interactions between species in a variety of ecosystems. To this end, they have built networks for mutualistic (e.g., pollination, seed dispersal) as well as antagonistic (e.g., herbivory, parasitism) interactions. The type of interaction being represented is believed to be reflected in the structure of the network, which would differ substantially between mutualistic and antagonistic networks. Here, we put this notion to the test by attempting to determine the type of interaction represented in a network based solely on its structure. We find that, although it is easy to separate different kinds of nonecological networks, ecological networks display much structural variation, making it difficult to distinguish between mutualistic and antagonistic interactions. We therefore frame the problem as a challenge for the community of scientists interested in computational biology and machine learning. We discuss the features a good solution to this problem should possess and the obstacles that need to be overcome to achieve this goal.

RevDate: 2019-10-07
CmpDate: 2019-10-04

Bastille-Rousseau G, G Wittemyer (2019)

Leveraging multidimensional heterogeneity in resource selection to define movement tactics of animals.

Ecology letters, 22(9):1417-1427.

Increasing interest in the complexity, variation and drivers of movement-related behaviours promise new insight into fundamental components of ecology. Resolving the multidimensionality of spatially explicit behaviour remains a challenge for investigating tactics and their relation to niche construction, but high-resolution movement data are providing unprecedented understanding of the diversity of spatially explicit behaviours. We introduce a framework for investigating individual variation in movement-defined resource selection that integrates the behavioural and ecological niche concepts. We apply it to long-term tracking data of 115 African elephants (Loxodonta africana), illustrating how a behavioural hypervolume can be defined based on differences between individuals and their ecological settings, and applied to explore population heterogeneity. While normative movement behaviour is frequently used to characterise population behaviour, we demonstrate the value of leveraging heterogeneity in the behaviour to gain greater insight into population structure and the mechanisms driving space-use tactics.

RevDate: 2019-11-19
CmpDate: 2019-10-11

Norton BA, Bending GD, Clark R, et al (2019)

Urban meadows as an alternative to short mown grassland: effects of composition and height on biodiversity.

Ecological applications : a publication of the Ecological Society of America, 29(6):e01946.

There are increasing calls to provide greenspace in urban areas, yet the ecological quality, as well as quantity, of greenspace is important. Short mown grassland designed for recreational use is the dominant form of urban greenspace in temperate regions but requires considerable maintenance and typically provides limited habitat value for most taxa. Alternatives are increasingly proposed, but the biodiversity potential of these is not well understood. In a replicated experiment across six public urban greenspaces, we used nine different perennial meadow plantings to quantify the relative roles of floristic diversity and height of sown meadows on the richness and composition of three taxonomic groups: plants, invertebrates, and soil microbes. We found that all meadow treatments were colonized by plant species not sown in the plots, suggesting that establishing sown meadows does not preclude further locally determined grassland development if management is appropriate. Colonizing species were rarer in taller and more diverse plots, indicating competition may limit invasion rates. Urban meadow treatments contained invertebrate and microbial communities that differed from mown grassland. Invertebrate taxa responded to changes in both height and richness of meadow vegetation, but most orders were more abundant where vegetation height was longer than mown grassland. Order richness also increased in longer vegetation and Coleoptera family richness increased with plant diversity in summer. Microbial community composition seems sensitive to plant species composition at the soil surface (0-10 cm), but in deeper soils (11-20 cm) community variation was most responsive to plant height, with bacteria and fungi responding differently. In addition to improving local residents' site satisfaction, native perennial meadow plantings can produce biologically diverse grasslands that support richer and more abundant invertebrate communities, and restructured plant, invertebrate, and soil microbial communities compared with short mown grassland. Our results suggest that diversification of urban greenspace by planting urban meadows in place of some mown amenity grassland is likely to generate substantial biodiversity benefits, with a mosaic of meadow types likely to maximize such benefits.

RevDate: 2019-11-08
CmpDate: 2019-11-08

Boza G, Worsley SF, Yu DW, et al (2019)

Efficient assembly and long-term stability of defensive microbiomes via private resources and community bistability.

PLoS computational biology, 15(5):e1007109 pii:PCOMPBIOL-D-19-00034.

Understanding the mechanisms that promote the assembly and maintenance of host-beneficial microbiomes is an open problem. Empirical evidence supports the idea that animal and plant hosts can combine 'private resources' with the ecological phenomenon known as 'community bistability' to favour some microbial strains over others. We briefly review evidence showing that hosts can: (i) protect the growth of beneficial strains in an isolated habitat, (ii) use antibiotics to suppress non-beneficial, competitor strains, and (iii) provide resources that only beneficial strains are able to translate into an increased rate of growth, reproduction, or antibiotic production. We then demonstrate in a spatially explicit, individual-based model that these three mechanisms act similarly by selectively promoting the initial proliferation of preferred strains, that is, by acting as a private resource. The faster early growth of preferred strains, combined with the phenomenon of 'community bistability,' allows those strains to continue to dominate the microbiome even after the private resource is withdrawn or made public. This is because after a beneficial colony reaches a sufficiently large size, it can resist invasion by parasites without further private support from the host. We further explicitly model localized microbial interactions and diffusion dynamics, and we show that an intermediate level of antibiotic diffusion is the most efficient mechanism in promoting preferred strains and that there is a wide range of parameters under which hosts can promote the assembly of a self-sustaining defensive microbiome. This in turn supports the idea that hosts readily evolve to promote host-beneficial defensive microbiomes.

RevDate: 2019-11-20

Piross IS, Harnos A, L Rózsa (2019)

Rensch's rule in avian lice: contradictory allometric trends for sexual size dimorphism.

Scientific reports, 9(1):7908 pii:10.1038/s41598-019-44370-5.

Rensch's rule (RR) postulates that in comparisons across closely related species, male body size relative to female size increases with the average size of the species. This holds true in several vertebrate and also in certain free-living invertebrate taxa. Here, we document the validity of RR in avian lice using three families (Philopteridae, Menoponidae, and Ricinidae). Using published data on the body length of 989 louse species, subspecies, or distinct intraspecific lineages, we applied phylogenetic reduced major axis regression to analyse the body size of females vs. males while accounting for phylogenetic non-independence. Our results indicate that philopterid and menoponid lice follow RR, while ricinids exhibit the opposite pattern. In the case of philopterids and menoponids, we argue that larger-bodied bird species tend to host lice that are both larger in size and more abundant. Thus, sexual selection acting on males makes them relatively larger, and this is stronger than fecundity selection acting on females. Ricinids exhibit converse RR, likely because fecundity selection is stronger in their case.

RevDate: 2019-11-14
CmpDate: 2019-11-14

Blažek J, Zukal J, Bandouchova H, et al (2019)

Numerous cold arousals and rare arousal cascades as a hibernation strategy in European Myotis bats.

Journal of thermal biology, 82:150-156.

Hibernating bats optimise the duration of torpor bouts and arousals in relation to hibernaculum microclimatic conditions and fat reserves. Clustering has significant physiological and ecological benefits, promoting successful hibernation of individuals. Such aggregations may help maintain optimal temperatures, allowing better energy utilisation than in solitarily bats. However, aroused bats in a cluster could conceivably disturb those still hibernating, starting an energy-demanding arousal process. Our study was conducted over two winters in two different hibernacula (cave and mine) in the Czech Republic, where Greater mouse-eared bats (Myotis myotis) have previously been diagnosed with white-nose syndrome. In 118 arousal episodes we recorded 193 individual arousals in which a warming phase was observed, 135 (69.9%) being cold arousals, where bats ceased increasing their body temperatures at ≤ 10 °C. The remaining arousals were standard normothermic arousals, where body (fur) surface temperatures reached > 20 °C. Cold arousals occurred during the mid- and late hibernation periods, suggesting they were a response to disturbance by a neighbour in the same cluster. Arousal cascades, where bats aroused in series, were rare (12.7%) and reached a maximum in mid-January. Our data suggest that Myotis bats prolong their torpor bouts using numerous cold arousals but few arousal cascades. Upon arrival of a bat, the clustered bats show tolerance to disturbing by conspecifics.

RevDate: 2019-11-29
CmpDate: 2019-11-29

Liu YY, Jin WT, Wei XX, et al (2019)

Cryptic speciation in the Chinese white pine (Pinus armandii): Implications for the high species diversity of conifers in the Hengduan Mountains, a global biodiversity hotspot.

Molecular phylogenetics and evolution, 138:114-125.

Conifers are the largest and ecologically and economically most important component group of the gymnosperms. Despite their slow rate of molecular evolution, rapid and recent diversification was unexpectedly prevalent in this ancient group in the Hengduan Mountains, a world's biodiversity hotspot and gymnosperm diversity center in Southwest China. In this study, we investigated the underlying mechanisms and disentangled the interactions of geography and ecology in speciation and evolution in Pinus armandii, an important forest tree species endemic to China, by integrating analyses of population transcriptomics, population genetics and ecological niche modeling. Many lines of evidence suggest that cryptic speciation has occurred in P. armandii. During the process, geologically induced formation of Mount Gongga and other massive peaks might trigger the initial vicariance isolation of the northern and southern subdivisions, and ecologically based selection then reinforced their differentiation and local adaptation. Our ecological niche analysis and earlier reciprocal transplant experiments in P. armandii provided convincing evidences for the critical role of ecology in the process of speciation. These findings suggest that both geography and ecology contributed significantly to the abundance of very recent and rapid species divergences, which promoted the rising of the extremely high conifer diversity in the Hengduan Mountains.

RevDate: 2019-11-20

Warwick-Dugdale J, Solonenko N, Moore K, et al (2019)

Long-read viral metagenomics captures abundant and microdiverse viral populations and their niche-defining genomic islands.

PeerJ, 7:e6800 pii:6800.

Marine viruses impact global biogeochemical cycles via their influence on host community structure and function, yet our understanding of viral ecology is constrained by limitations in host culturing and a lack of reference genomes and 'universal' gene markers to facilitate community surveys. Short-read viral metagenomic studies have provided clues to viral function and first estimates of global viral gene abundance and distribution, but their assemblies are confounded by populations with high levels of strain evenness and nucleotide diversity (microdiversity), limiting assembly of some of the most abundant viruses on Earth. Such features also challenge assembly across genomic islands containing niche-defining genes that drive ecological speciation. These populations and features may be successfully captured by single-virus genomics and fosmid-based approaches, at least in abundant taxa, but at considerable cost and technical expertise. Here we established a low-cost, low-input, high throughput alternative sequencing and informatics workflow to improve viral metagenomic assemblies using short-read and long-read technology. The 'VirION' (Viral, long-read metagenomics via MinION sequencing) approach was first validated using mock communities where it was found to be as relatively quantitative as short-read methods and provided significant improvements in recovery of viral genomes. We then then applied VirION to the first metagenome from a natural viral community from the Western English Channel. In comparison to a short-read only approach, VirION: (i) increased number and completeness of assembled viral genomes; (ii) captured abundant, highly microdiverse virus populations, and (iii) captured more and longer genomic islands. Together, these findings suggest that VirION provides a high throughput and cost-effective alternative to fosmid and single-virus genomic approaches to more comprehensively explore viral communities in nature.

RevDate: 2019-11-20

Bátori Z, Vojtkó A, Maák IE, et al (2019)

Karst dolines provide diverse microhabitats for different functional groups in multiple phyla.

Scientific reports, 9(1):7176 pii:10.1038/s41598-019-43603-x.

Fine-scale topographic complexity creates important microclimates that can facilitate species to grow outside their main distributional range and increase biodiversity locally. Enclosed depressions in karst landscapes ('dolines') are topographically complex environments which produce microclimates that are drier and warmer (equator-facing slopes) and cooler and moister (pole-facing slopes and depression bottoms) than the surrounding climate. We show that the distribution patterns of functional groups for organisms in two different phyla, Arthropoda (ants) and Tracheophyta (vascular plants), mirror this variation of microclimate. We found that north-facing slopes and bottoms of solution dolines in northern Hungary provided key habitats for ant and plant species associated with cooler and/or moister conditions. Contrarily, south-facing slopes of dolines provided key habitats for species associated with warmer and/or drier conditions. Species occurring on the surrounding plateau were associated with intermediate conditions. We conclude that karst dolines provide a diversity of microclimatic habitats that may facilitate the persistence of taxa with diverse environmental preferences, indicating these dolines to be potential safe havens for multiple phyla under local and global climate oscillations.

RevDate: 2020-01-14
CmpDate: 2020-01-14

Hofman MPG, Hayward MW, Heim M, et al (2019)

Right on track? Performance of satellite telemetry in terrestrial wildlife research.

PloS one, 14(5):e0216223 pii:PONE-D-18-33139.

Satellite telemetry is an increasingly utilized technology in wildlife research, and current devices can track individual animal movements at unprecedented spatial and temporal resolutions. However, as we enter the golden age of satellite telemetry, we need an in-depth understanding of the main technological, species-specific and environmental factors that determine the success and failure of satellite tracking devices across species and habitats. Here, we assess the relative influence of such factors on the ability of satellite telemetry units to provide the expected amount and quality of data by analyzing data from over 3,000 devices deployed on 62 terrestrial species in 167 projects worldwide. We evaluate the success rate in obtaining GPS fixes as well as in transferring these fixes to the user and we evaluate failure rates. Average fix success and data transfer rates were high and were generally better predicted by species and unit characteristics, while environmental characteristics influenced the variability of performance. However, 48% of the unit deployments ended prematurely, half of them due to technical failure. Nonetheless, this study shows that the performance of satellite telemetry applications has shown improvements over time, and based on our findings, we provide further recommendations for both users and manufacturers.

RevDate: 2019-12-10
CmpDate: 2019-08-15

Švec P, Hönig V, Zubriková D, et al (2019)

The use of multi-criteria evaluation for the selection of study plots for monitoring of I. ricinus ticks - Example from Central Europe.

Ticks and tick-borne diseases, 10(4):905-910.

Research projects in the field of eco-epidemiology of tick-borne diseases often require extensive sampling of arthropod vectors in the field. The aim of our study was to use geographical information systems (GIS) to select appropriate sampling sites of Ixodes ricinus ticks in central European habitat for further ecological studies of vector-borne pathogens (tick-borne encephalitis virus and Borrelia burgdorferi sensu lato). The model area was the Czech-German borderland (the region of South Bohemia and two regions in Germany: the Upper Palatinate and Lower Bavaria) where numerous human tick-borne encephalitis cases are reported annually. We prepared the sampling site design as a multi-criteria evaluation (MCE) task. In the GIS environment, we conducted MCE with a set of environmental, socio-economic and epidemiological data (altitude, vegetation cover, number of tick-borne encephalitis cases recorded in the past, tourist activity). The MCE classified the surveyed area into two classes: suitable for tick collection and unsuitable for tick collection. Subsequently, 50 tick sampling sites were randomly selected in the suitable area: 30 in South Bohemia (Czech Republic) and 20 in the Upper Palatinate and Lower Bavaria regions (Bavaria, Germany). The sampling sites were identified and surveyed in the field. The presence of ticks was confirmed by flagging at each of the selected plots. The described MCE system represents a versatile tool for semi-randomized design of tick sampling sites for research projects in the field of tick-borne pathogen ecology as well as for tick-borne pathogen surveillance programs run by local health authorities.

RevDate: 2020-01-09
CmpDate: 2020-01-09

Niku J, Brooks W, Herliansyah R, et al (2019)

Efficient estimation of generalized linear latent variable models.

PloS one, 14(5):e0216129 pii:PONE-D-18-34077.

Generalized linear latent variable models (GLLVM) are popular tools for modeling multivariate, correlated responses. Such data are often encountered, for instance, in ecological studies, where presence-absences, counts, or biomass of interacting species are collected from a set of sites. Until very recently, the main challenge in fitting GLLVMs has been the lack of computationally efficient estimation methods. For likelihood based estimation, several closed form approximations for the marginal likelihood of GLLVMs have been proposed, but their efficient implementations have been lacking in the literature. To fill this gap, we show in this paper how to obtain computationally convenient estimation algorithms based on a combination of either the Laplace approximation method or variational approximation method, and automatic optimization techniques implemented in R software. An extensive set of simulation studies is used to assess the performances of different methods, from which it is shown that the variational approximation method used in conjunction with automatic optimization offers a powerful tool for estimation.

RevDate: 2020-01-31

Gregory AC, Zayed AA, Conceição-Neto N, et al (2019)

Marine DNA Viral Macro- and Microdiversity from Pole to Pole.

Cell, 177(5):1109-1123.e14.

Microbes drive most ecosystems and are modulated by viruses that impact their lifespan, gene flow, and metabolic outputs. However, ecosystem-level impacts of viral community diversity remain difficult to assess due to classification issues and few reference genomes. Here, we establish an ∼12-fold expanded global ocean DNA virome dataset of 195,728 viral populations, now including the Arctic Ocean, and validate that these populations form discrete genotypic clusters. Meta-community analyses revealed five ecological zones throughout the global ocean, including two distinct Arctic regions. Across the zones, local and global patterns and drivers in viral community diversity were established for both macrodiversity (inter-population diversity) and microdiversity (intra-population genetic variation). These patterns sometimes, but not always, paralleled those from macro-organisms and revealed temperate and tropical surface waters and the Arctic as biodiversity hotspots and mechanistic hypotheses to explain them. Such further understanding of ocean viruses is critical for broader inclusion in ecosystem models.

RevDate: 2019-11-12
CmpDate: 2019-11-12

Park DS, Akuffo AA, Muench DE, et al (2019)

Clonal hematopoiesis of indeterminate potential and its impact on patient trajectories after stem cell transplantation.

PLoS computational biology, 15(4):e1006913 pii:PCOMPBIOL-D-18-00635.

Clonal hematopoiesis of indeterminate potential (CHIP) is a recently identified process where older patients accumulate distinct subclones defined by recurring somatic mutations in hematopoietic stem cells. CHIP's implications for stem cell transplantation have been harder to identify due to the high degree of mutational heterogeneity that is present within the genetically distinct subclones. In order to gain a better understanding of CHIP and the impact of clonal dynamics on transplantation outcomes, we created a mathematical model of clonal competition dynamics. Our analyses highlight the importance of understanding competition intensity between healthy and mutant clones. Importantly, we highlight the risk that CHIP poses in leading to dominance of precancerous mutant clones and the risk of donor derived leukemia. Furthermore, we estimate the degree of competition intensity and bone marrow niche decline in mice during aging by using our modeling framework. Together, our work highlights the importance of better characterizing the ecological and clonal composition in hematopoietic donor populations at the time of stem cell transplantation.

RevDate: 2019-05-14
CmpDate: 2019-05-14

Rund SSC, Braak K, Cator L, et al (2019)

MIReAD, a minimum information standard for reporting arthropod abundance data.

Scientific data, 6(1):40 pii:10.1038/s41597-019-0042-5.

Arthropods play a dominant role in natural and human-modified terrestrial ecosystem dynamics. Spatially-explicit arthropod population time-series data are crucial for statistical or mathematical models of these dynamics and assessment of their veterinary, medical, agricultural, and ecological impacts. Such data have been collected world-wide for over a century, but remain scattered and largely inaccessible. In particular, with the ever-present and growing threat of arthropod pests and vectors of infectious diseases, there are numerous historical and ongoing surveillance efforts, but the data are not reported in consistent formats and typically lack sufficient metadata to make reuse and re-analysis possible. Here, we present the first-ever minimum information standard for arthropod abundance, Minimum Information for Reusable Arthropod Abundance Data (MIReAD). Developed with broad stakeholder collaboration, it balances sufficiency for reuse with the practicality of preparing the data for submission. It is designed to optimize data (re)usability from the "FAIR," (Findable, Accessible, Interoperable, and Reusable) principles of public data archiving (PDA). This standard will facilitate data unification across research initiatives and communities dedicated to surveillance for detection and control of vector-borne diseases and pests.

RevDate: 2019-11-20

Thomas HJD, Myers-Smith IH, Bjorkman AD, et al (2019)

Traditional plant functional groups explain variation in economic but not size-related traits across the tundra biome.

Global ecology and biogeography : a journal of macroecology, 28(2):78-95.

Aim: Plant functional groups are widely used in community ecology and earth system modelling to describe trait variation within and across plant communities. However, this approach rests on the assumption that functional groups explain a large proportion of trait variation among species. We test whether four commonly used plant functional groups represent variation in six ecologically important plant traits.

Location: Tundra biome.

Time period: Data collected between 1964 and 2016.

Major taxa studied: 295 tundra vascular plant species.

Methods: We compiled a database of six plant traits (plant height, leaf area, specific leaf area, leaf dry matter content, leaf nitrogen, seed mass) for tundra species. We examined the variation in species-level trait expression explained by four traditional functional groups (evergreen shrubs, deciduous shrubs, graminoids, forbs), and whether variation explained was dependent upon the traits included in analysis. We further compared the explanatory power and species composition of functional groups to alternative classifications generated using post hoc clustering of species-level traits.

Results: Traditional functional groups explained significant differences in trait expression, particularly amongst traits associated with resource economics, which were consistent across sites and at the biome scale. However, functional groups explained 19% of overall trait variation and poorly represented differences in traits associated with plant size. Post hoc classification of species did not correspond well with traditional functional groups, and explained twice as much variation in species-level trait expression.

Main conclusions: Traditional functional groups only coarsely represent variation in well-measured traits within tundra plant communities, and better explain resource economic traits than size-related traits. We recommend caution when using functional group approaches to predict tundra vegetation change, or ecosystem functions relating to plant size, such as albedo or carbon storage. We argue that alternative classifications or direct use of specific plant traits could provide new insights for ecological prediction and modelling.

RevDate: 2019-12-10
CmpDate: 2019-05-28

Stone L, Simberloff D, Y Artzy-Randrup (2019)

Network motifs and their origins.

PLoS computational biology, 15(4):e1006749 pii:PCOMPBIOL-D-18-01805.

Modern network science is a new and exciting research field that has transformed the study of complex systems over the last 2 decades. Of particular interest is the identification of small "network motifs" that might be embedded in a larger network and that indicate the presence of evolutionary design principles or have an overly influential role on system-wide dynamics. Motifs are patterns of interconnections, or subgraphs, that appear in an observed network significantly more often than in compatible randomized networks. The concept of network motifs was introduced into Systems Biology by Milo, Alon and colleagues in 2002, quickly revolutionized the field, and it has had a huge impact in wider scientific domains ever since. Here, we argue that the same concept and tools for the detection of motifs were well known in the ecological literature decades into the last century, a fact that is generally not recognized. We review the early history of network motifs, their evolution in the mathematics literature, and their recent rediscoveries.

RevDate: 2019-08-01
CmpDate: 2019-08-01

Louro R, Santos-Silva C, T Nobre (2019)

What is in a name? Terfezia classification revisited.

Fungal biology, 123(4):267-273.

Desert truffles (mycorrhizal hypogeous Ascomycota) are found in arid and semi-arid areas of the globe and have great ecological and economic importance. Terfezia is undoubtedly the most diversified of all desert truffle genera, but its taxonomy is far from resolved. Specifically, the large number of newly described species plus the high intraspecific morphological variability observed within some Terfezia lineages as rendered the use of molecular techniques mandatory for specimen's discrimination. But the subsequent increasing amount of sequence data produced also a huge number of undescribed taxa that required determination. We compiled and used the public available ITS data on Terfezia spp. on the custom-curated UNITE database to reconstruct the genus phylogeny. We found at least 17 distinct lineages within the genus and successfully resolved some of the more pressing taxonomic issues, namely the T. leptoderma/olbiensis complex and some misapplied synonymy. Based on this resolved phylogeny, and motivated by the recent new described species, we proposed an identification key to Terfezia genus highlighting the importance of morphological and ecological characterization.

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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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Although the methods of molecular biology can seem almost magical to the uninitiated, the original techniques of classical genetics are readily appreciated by one and all: cross individuals that differ in some inherited trait, collect all of the progeny, score their attributes, and propose mechanisms to explain the patterns of inheritance observed.

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In reading the early works of classical genetics, one is drawn, almost inexorably, into ever more complex models, until molecular explanations begin to seem both necessary and natural. At that point, the tools for understanding genome research are at hand. Assisting readers reach this point was the original goal of The Electronic Scholarly Publishing Project.

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Usage of the site grew rapidly and has remained high. Faculty began to use the site for their assigned readings. Other on-line publishers, ranging from The New York Times to Nature referenced ESP materials in their own publications. Nobel laureates (e.g., Joshua Lederberg) regularly used the site and even wrote to suggest changes and improvements.

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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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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.

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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).

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