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.

Phylogenetic perspective on ecological niche evolution in american blackbirds (Family Icteridae)

Abstract: Analysis of ecological characters on phylogenetic frameworks has only recently appeared in the literature, with several studies addressing patterns of niche evolution, generally over relatively recent time frames. In the present study, we examined patterns of niche evolution for a broad radiation of American blackbird species (Family Icteridae), exploring more deeply into phylogenetic history. Within each of three major blackbird lineages, overlap of ecological niches in principal components analysis transformed environmental space varied from high to none. Comparative phylogenetic analyses of ecological niche characteristics showed a general pattern of niche conservatism over evolutionary time, with differing degrees of innovation among lineages. Although blackbird niches were evolutionarily plastic over differing periods of time, they diverged within a limited set of ecological possibilities, resulting in examples of niche convergence among extant blackbird species. Hence, an understanding of the patterns of ecological niche evolution on broad phylogenetic scales sets the stage for framing questions of evolutionary causation, historical biogeography, and ancestral ecological characteristics more appropriately. © 2008 The Linnean Society of London, Biological Journal of the Linnean Society, 2008, 94, 869–878.

Priority Contribution West Nile virus in the New World: potential impacts on bird species

Abstract: Summary The past five years have seen the arrival and extremely rapid expansion of West Nile virus (WNV) in the Western Hemisphere. The rapid sweep across North America has permitted little time for developing knowledge of the virus’s potential impacts on wildlife in the New World. Given this information gap, we here summarize for the ornithological community what is known or can be anticipated for WNV’s effect on bird communities in coming years. Our particular focus is on impacts of WNV on the conservation status of birds, the principal vertebrate reservoir for the virus. Origins West Nile virus (WNV) was first isolated in Uganda in 1937, and was subsequently documented as a relatively benign arbovirus across much of Africa, the Middle East and southern Europe (Hubalek and Halouzka 1999). It was viewed as a cause of mild febrile illness in humans, with no apparent negative effect on birds. WNV nevertheless caused several major human disease outbreaks, for example in South Africa in 1974 and Algeria in 1994. WNV was not fully appreciated as a serious human health concern, however, until the encephalitis outbreaks in Romania in 1996–1997, which involved hundreds of human clinical cases and a 9% case-fatality rate. Other recent outbreaks have seemed to come at shorter intervals, and with more severe effects, both on humans and on birds, suggesting to some the possible evolution of a new, more virulent strain (Petersen and Roehrig 2001).

Mapping monkeypox transmission risk through time and space in the Congo Basin.

Abstract: Monkeypox is a major public health concern in the Congo Basin area, with changing patterns of human case occurrences reported in recent years. Whether this trend results from better surveillance and detection methods, reduced proportions of vaccinated vs. non-vaccinated human populations, or changing environmental conditions remains unclear. Our objective is to examine potential correlations between environment and transmission of monkeypox events in the Congo Basin. We created ecological niche models based on human cases reported in the Congo Basin by the World Health Organization at the end of the smallpox eradication campaign, in relation to remotely-sensed Normalized Difference Vegetation Index datasets from the same time period. These models predicted independent spatial subsets of monkeypox occurrences with high confidence; models were then projected onto parallel environmental datasets for the 2000s to create present-day monkeypox suitability maps. Recent trends in human monkeypox infection are associated with broad environmental changes across the Congo Basin. Our results demonstrate that ecological niche models provide useful tools for identification of areas suitable for transmission, even for poorly-known diseases like monkeypox.

Effects of georeferencing effort on mapping monkeypox case distributions and transmission risk

Abstract: Background: Maps of disease occurrences and GIS-based models of disease transmission risk are increasingly common, and both rely on georeferenced diseases data. Automated methods for georeferencing disease data have been widely studied for developed countries with rich sources of geographic referenced data. However, the transferability of these methods to countries without comparable geographic reference data, particularly when working with historical disease data, has not been as widely studied. Historically, precise geographic information about where individual cases occur has been collected and stored verbally, identifying specific locations using place names. Georeferencing historic data is challenging however, because it is difficult to find appropriate geographic reference data to match the place names to. Here, we assess the degree of care and research invested in converting textual descriptions of disease occurrence locations to numerical grid coordinates (latitude and longitude). Specifically, we develop three datasets from the same, original monkeypox disease occurrence data, with varying levels of care and effort: the first based on an automated web-service, the second improving on the first by reference to additional maps and digital gazetteers, and the third improving still more based on extensive consultation of legacy surveillance records that provided considerable additional information about each case. To illustrate the implications of these seemingly subtle improvements in data quality, we develop ecological niche models and predictive maps of monkeypox transmission risk based on each of the three occurrence data sets. Results: We found macrogeographic variations in ecological niche models depending on the type of georeferencing method used. Less-careful georeferencing identified much smaller areas as having potential for monkeypox transmission in the Sahel region, as well as around the rim of the Congo Basin. These results have implications for mapping efforts, as each higher level of georeferencing precision required considerably greater time investment. Conclusions: The importance of careful georeferencing cannot be overlooked, despite it being a time- and labor-intensive process. Investment in archival storage of primary disease-occurrence data is merited, and improved digital gazetteers are needed to support public health mapping activities, particularly in developing countries, where maps and geographic information may be sparse.

Deep Learning Algorithms Improve Automated Identification of Chagas Disease Vectors.

Abstract: Vector-borne Chagas disease is endemic to the Americas and imposes significant economic and social burdens on public health. In a previous contribution, we presented an automated identification system that was able to discriminate among 12 Mexican and 39 Brazilian triatomine (Hemiptera: Reduviidae) species from digital images. To explore the same data more deeply using machine-learning approaches, hoping for improvements in classification, we employed TensorFlow, an open-source software platform for a deep learning algorithm. We trained the algorithm based on 405 images for Mexican triatomine species and 1,584 images for Brazilian triatomine species. Our system achieved 83.0 and 86.7% correct identification rates across all Mexican and Brazilian species, respectively, an improvement over comparable rates from statistical classifiers (80.3 and 83.9%, respectively). Incorporating distributional information to reduce numbers of species in analyses improved identification rates to 95.8% for Mexican species and 98.9% for Brazilian species. Given the 'taxonomic impediment' and difficulties in providing entomological expertise necessary to control such diseases, automating the identification process offers a potential partial solution to crucial challenges.

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