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.

Using epidemiological survey data to infer geographic distributions of leishmaniasis vector species

Abstract: An important aspect of tropical medicine is analysis of geographic aspects of risk of disease transmission, which for lack of detailed public health data must often be reduced to an understanding of the distributions of critical species such as vectors and reservoirs. We examine the applicability of a new technique, ecological niche modeling, to the challenge of understanding distributions of such species based on municipalities in the state of Sao Paulo in which a group of 5 Lutzomyia sandfly species have been recorded. The technique, when tested based on independent occurrence data, yielded highly significant predictions of species' distributions; minimum sample sizes for effective predictions were around 40 municipalities.

Do consensus models outperform individual models? Transferability evaluations of diverse modeling approaches for an invasive moth

Abstract: Transferability is key to many of the most novel and interesting applications of ecological niche models, such that maximizing predictive power of model transfers is crucial Here, we explored consensus methods as a means of reducing uncertainty and improving model transferability in anticipating the potential distribution of an invasive moth (Hyphantria cunea) Individual native-range niche models were calibrated using seven modelling algorithms and four environmental datasets, representing different degrees of dimensionality, spatial correlation, and ecological relevance, and showing different degrees of climate niche expansion Four consensus methods were used to combine individual niche models; we assessed transferability of consensus models and the individual models used to generate them The results suggested that ideal criteria for environmental variable selection vary among algorithms, as different algorithms showed different sensitivities to spatial dimensionality and correlation Consensus models reflected the central tendency of individual models, and reduced uncertainty by consolidating consistency across individual models, but did not outperform individual models The question of whether interpolation accuracy comes at the expense of transferability suggests caution in planning methodologies for processing niche models to predict invasive potential These explorations outline approaches by which to reduce uncertainty and improve niche model transferability with vital implications for ensemble forecasting

Fine-Scale Predictions of Distributions of Chagas Disease Vectors in the State of Guanajuato, Mexico

Abstract: One of the most daunting challenges for Chagas disease surveillance and control in Mexico is the lack of community level data on vector distributions. Although many states now have assembled representative domestic triatomine collections, only two triatomine specimens had been collected and reported previously from the state of Guanajuato. Field personnel from the state’s Secretaria de Salud conducted health promotion activities in 43 of the 46 counties in the state and received donations of a total of 2,522 triatomine specimens between 1998 and 2002. All specimens were identified, and live insects examined for Trypanosoma cruzi. In an effort to develop fine-scale distributional data for Guanajuato, collection localities were georeferenced and ecological niches were modeled for each species by using evolutionary-computing approaches. Five species were collected: Triatoma mexicana (Herrich-Schaeffer), Triatoma longipennis (Usinger), Triatoma pallidipennis (Stal), Triatoma barberi (Usinger), and Tr...

Assumption-versus data-based approaches to summarizing species’ ranges

Abstract: This is the peer reviewed version of the following article: Assumption- versus data-based approaches to summarizing species’ ranges, which will be published in final form in Conservation Biology at http://dx.doi.org/10.1111/cobi.12801. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving: http://olabout.wiley.com/WileyCDA/Section/id-828039.html#terms

The Theory of Island Biogeography

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

Bayesian Phylogenetics with BEAUti and the BEAST 1.7

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

Ecological and Evolutionary Responses 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