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.

Biodiversity Consequences of Sea Level Rise in New Guinea

Abstract: Climate change poses a growing threat to biodiversity globally. Under changing conditions, affected species must either shift spatially to track changing conditions, adapt in terms of ecological tolerances, or become extinct. Currently, most climate change studies focus on direct climate effects on biodiversity and little attention is paid to the effects of sea level rise. We explore two scenarios of sea level rise (1 m and 6 m) and their implications for biodiversity across a major biodiversity hotspot, New Guinea. Marine intrusion at just 1 m of sea level rise is widespread, affecting large sectors of New Guinea. Protected areas (0?58.3% loss), ecoregions (0?90.0% loss) and endemic species (e.g., Pitohui incertus, 41?50% loss) across New Guinea would be affected by sea level rise within the projected range of likely occurrence.

Kansas gap analysis: the importance of validating distributional models before using them

Abstract: Maps of vertebrate distributions resulting from the Kansas Gap Analysis were com- pared with maps based on ecological-niche modeling of primary point-occurrence information. The latter maps were considerably more predictive of independent sets of test data than were the Gap maps, further supporting the idea that the method of Gap wildlife-habitat modeling has little analytical power. In general, the Kansas Gap maps were untested and unchecked, thus being heterogeneous, unreliable, and of little use for further analyses. R ESUMEN Se compararon los mapas de distribuciones de vertebrados que resultaron del pro- grama de analisis de ''Gap'' del estado de Kansas con mapas que se derivaron de modelaje de nichos ecologicos de datos de informacion primaria de puntos de ocurrencia. Estos ultimos re- sultaron con bastante mas poder predictivo de juegos de datos de pruebas independientes que los mapas de Gap, apoyando aun ma a la idea de que el metodo de modelaje de habitat silvestre de Gap tiene poco poder analitico. En general los mapas que se produjeron en el proyecto de Gap en Kansas no fueron probados ni revisados, y finalmente fueron heterogeneos, no confiables, y de poco valor para analisis posteriores. Gap analysis consists of the integration of in- formation on geographic distributions of spe- cies with information on land use, land cover, and land tenure, with the aim of improving

Automated identification of insect vectors of Chagas disease in Brazil and Mexico: the Virtual Vector Lab.

Abstract: Identification of arthropods important in disease transmission is a crucial, yet difficult, task that can demand considerable training and experience. An important case in point is that of the 150+ species of Triatominae, vectors of Trypanosoma cruzi, causative agent of Chagas disease across the Americas. We present a fully automated system that is able to identify triatomine bugs from Mexico and Brazil with an accuracy consistently above 80%, and with considerable potential for further improvement. The system processes digital photographs from a photo apparatus into landmarks, and uses ratios of measurements among those landmarks, as well as (in a preliminary exploration) two measurements that approximate aspects of coloration, as the basis for classification. This project has thus produced a working prototype that achieves reasonably robust correct identification rates, although many more developments can and will be added, and-more broadly-the project illustrates the value of multidisciplinary collaborations in resolving difficult and complex challenges.

Hundred-year changes in the avifauna of the Valley of Mexico, Distrito Federal, Mexico

Abstract: Resumen en: Species lists were compiled for the Valley of Mexico from the nineteenth century and from 1950-present. Of a total of 401 species, 228 were documented t...

Vegetation-index models predict areas vulnerable to purple loosestrife (lythrum salicaria) invasion in kansas

Abstract: Purple loosestrife (Lythrum salicaria) constitutes an invasive species detrimental to wetland habitats in North America. To estimate areas vulnerable to it in Kansas, we modeled the potential geographic distribution of the species by using current records in the state, remotely sensed vegetation- index data from the Moderate Resolution Imaging Spectrometer (MODIS), and the Genetic Algorithm for Rule-Set Prediction (GARP). Models built using only localities from northeastern Kansas (the origin of invasion within the state) consistently predicted test localities in other parts of the state with negligible omission. An additional analysis using records from all counties where the species is known showed a similar prediction. All models indicated suitable conditions for purple loosestrife in much of eastern and central Kansas, as well as in riverine and irrigated areas in the western part of the state. The approach presented here might prove useful for assessing the regional colonization potential of other newly detected invasive species before other studies can be undertaken.

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