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A. Townsend Peterson

Bio: A. Townsend Peterson is an academic researcher from University of Kansas. The author has contributed to research in topics: Environmental niche modelling & Ecological niche. The author has an hindex of 91, co-authored 521 publications receiving 51524 citations. Previous affiliations of A. Townsend Peterson include California Academy of Sciences & University of Chicago.


Papers
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01 Jan 2010
TL;DR: This work outlines what biodiversity informatics should be, a link between diverse dimensions of organismal biology – genomics, phylogenetics, taxonomy, distributional biology, ecology, interactions, and conservation status – and describes the science progress that would result.
Abstract: Science is a sequence of generating new ideas, detailed explorations, incorporation of the results into a toolbox for understanding data, and turning them into useful knowledge. One recent development has been large-scale, computer-aided management of biodiversity information. This emerging field of biodiversity informatics has been growing quickly, but without overarching scientific questions to guide its development; the result has been developments that have no connection to genuine insight and forward progress. We outline what biodiversity informatics should be, a link between diverse dimensions of organismal biology – genomics, phylogenetics, taxonomy, distributional biology, ecology, interactions, and conservation status – and describe the science progress that would result. These steps will enable a transition from ‘gee-whiz’ to fundamental science infrastructure.

4 citations

Journal ArticleDOI
TL;DR: In this article, the authors evaluated digital accessible knowledge on occurrence of Indian bird species and found good coverage of the country by well-inventoried areas after 2000, but almost no coverage prior to 1980.
Abstract: This paper evaluates Digital Accessible Knowledge on occurrence of Indian bird species. More than 2 million primary occurrence records from across India were obtained from the Global Biodiversity Information Facility and eBird. These were processed into maps of inventory completeness across the country both prior to 1980 and after 2000, in an attempt to develop evaluations of faunal change resulting from global climate change. We found good coverage of the country by well-inventoried areas after 2000, but almost no coverage prior to 1980. As such, in before-and-after comparisons documenting effects of global change on Indian birds, the ‘after’ is well documented, but the ‘before’ is lacking. This significant information gap points to the need for digital capture and open sharing of historical information regarding Indian bird species’ occurrences; this information will derive in large part from natural history museum specimens, particularly in India and Great Britain, and potentially from older observational data sources and the literature.

4 citations

Journal ArticleDOI
TL;DR: In this article , the authors used ecological niche modeling to explore the role of ecology on the current and future distributions of genetic populations of Kersting's groundnut and found that M. geocarpum's distribution was correlated with both climatic and soil layers and identity and similarity tests revealed that the two genetic groups have identical and similar environmental niches.
Abstract: Orphan legume crops play an important role in smallholder farmers' food systems. Though less documented, they have the potential to contribute to adequate nutrition in vulnerable communities. Unfortunately, data are scarce about the potential of those crops to withstand current and future climate variations. Using Macrotyloma geocarpum as an example, we used ecological niche modeling to explore the role of ecology on the current and future distributions of genetic populations of Kersting's groundnut. Our findings showed that: (1) the models had good predictive power, indicating that M. geocarpum's distribution was correlated with both climatic and soil layers; (2) identity and similarity tests revealed that the two genetic groups have identical and similar environmental niches; (3) by integrating the genetic information in niche modeling, niches projections show divergence in the response of the species and genetic populations to ongoing climate change. This study highlights the importance of incorporating genetic data into Ecological Niche Modeling (ENM) approaches to obtain a finer information of species' future distribution, and explores the implications for agricultural adaptation, with a particular focus on identifying priority actions in orphan crops conservation and breeding.

3 citations

Journal ArticleDOI
17 Dec 2019-PLOS ONE
TL;DR: A zero-inflated negative binomial regression and multimodel averaging approach with georeferenced Ae.
Abstract: Rift Valley fever virus (RVFV) is a mosquito-borne zoonotic arbovirus with important livestock and human health, and economic consequences across Africa and the Arabian Peninsula. Climate and vegetation monitoring guide RVFV forecasting models and early warning systems; however, these approaches make monthly predictions and a need exists to predict primary vector abundances at finer temporal scales. In Kenya, an important primary RVFV vector is the mosquito Aedes mcintoshi. We used a zero-inflated negative binomial regression and multimodel averaging approach with georeferenced Ae. mcintoshi mosquito counts and remotely sensed climate and topographic variables to predict where and when abundances would be high in Kenya and western Somalia. The data supported a positive effect on abundance of minimum wetness index values within 500 m of a sampling site, cumulative precipitation values 0 to 14 days prior to sampling, and elevated land surface temperature values ~3 weeks prior to sampling. The probability of structural zero counts of mosquitoes increased as percentage clay in the soil decreased. Weekly retrospective predictions for unsampled locations across the study area between 1 September and 25 January from 2002 to 2016 predicted high abundances prior to RVFV outbreaks in multiple foci during the 2006-2007 epizootic, except for two districts in Kenya. Additionally, model predictions supported the possibility of high Ae. mcintoshi abundances in Somalia, independent of Kenya. Model-predicted abundances were low during the 2015-2016 period when documented outbreaks did not occur, although several surveillance systems issued warnings. Model predictions prior to the 2018 RVFV outbreak indicated elevated abundances in Wajir County, Kenya, along the border with Somalia, but RVFV activity occurred west of the focus of predicted high Ae. mcintoshi abundances.

3 citations


Cited by
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Journal ArticleDOI
TL;DR: Preface to the Princeton Landmarks in Biology Edition vii Preface xi Symbols used xiii 1.
Abstract: Preface to the Princeton Landmarks in Biology Edition vii Preface xi Symbols Used xiii 1. The Importance of Islands 3 2. Area and Number of Speicies 8 3. Further Explanations of the Area-Diversity Pattern 19 4. The Strategy of Colonization 68 5. Invasibility and the Variable Niche 94 6. Stepping Stones and Biotic Exchange 123 7. Evolutionary Changes Following Colonization 145 8. Prospect 181 Glossary 185 References 193 Index 201

14,171 citations

Journal ArticleDOI
TL;DR: In this paper, the use of the maximum entropy method (Maxent) for modeling species geographic distributions with presence-only data was introduced, which is a general-purpose machine learning method with a simple and precise mathematical formulation.

13,120 citations

Journal Article
Fumio Tajima1
30 Oct 1989-Genomics
TL;DR: It is suggested that the natural selection against large insertion/deletion is so weak that a large amount of variation is maintained in a population.

11,521 citations

Journal ArticleDOI
TL;DR: The Bayesian Evolutionary Analysis by Sampling Trees (BEAST) software package version 1.7 is presented, which implements a family of Markov chain Monte Carlo algorithms for Bayesian phylogenetic inference, divergence time dating, coalescent analysis, phylogeography and related molecular evolutionary analyses.
Abstract: Computational evolutionary biology, statistical phylogenetics and coalescent-based population genetics are becoming increasingly central to the analysis and understanding of molecular sequence data. We present the Bayesian Evolutionary Analysis by Sampling Trees (BEAST) software package version 1.7, which implements a family of Markov chain Monte Carlo (MCMC) algorithms for Bayesian phylogenetic inference, divergence time dating, coalescent analysis, phylogeography and related molecular evolutionary analyses. This package includes an enhanced graphical user interface program called Bayesian Evolutionary Analysis Utility (BEAUti) that enables access to advanced models for molecular sequence and phenotypic trait evolution that were previously available to developers only. The package also provides new tools for visualizing and summarizing multispecies coalescent and phylogeographic analyses. BEAUti and BEAST 1.7 are open source under the GNU lesser general public license and available at http://beast-mcmc.googlecode.com and http://beast.bio.ed.ac.uk

9,055 citations

Journal ArticleDOI
TL;DR: Range-restricted species, particularly polar and mountaintop species, show severe range contractions and have been the first groups in which entire species have gone extinct due to recent climate change.
Abstract: Ecological changes in the phenology and distribution of plants and animals are occurring in all well-studied marine, freshwater, and terrestrial groups These observed changes are heavily biased in the directions predicted from global warming and have been linked to local or regional climate change through correlations between climate and biological variation, field and laboratory experiments, and physiological research Range-restricted species, particularly polar and mountaintop species, show severe range contractions and have been the first groups in which entire species have gone extinct due to recent climate change Tropical coral reefs and amphibians have been most negatively affected Predator-prey and plant-insect interactions have been disrupted when interacting species have responded differently to warming Evolutionary adaptations to warmer conditions have occurred in the interiors of species’ ranges, and resource use and dispersal have evolved rapidly at expanding range margins Observed genetic shifts modulate local effects of climate change, but there is little evidence that they will mitigate negative effects at the species level

7,657 citations