Wilson Lab

Department of Geography
Graduate Program in Evolution, Ecology and Behavior
University at Buffalo
Buffalo NY


Research in the lab focuses on the spatial patterns and processes of biodiversity and ecosystem function. We use remote sensing and field observations together with mechanistic and statistical modelling to understand how ecosystems change through space and time.


  1. Slingsby_TaylorPlots (2017) {}, {} 10.6084/m9.figshare.4737358
  2. Integrating occurrence data and expert maps for improved species range predictions (2017) {}, {} 10.1111/geb.12539 (10 citations) Altmetric6.8; Media Links:
  3. Intensifying postfire weather and biological invasion drive species loss in a Mediterranean-type biodiversity hotspot (2017) {}, {} 10.1073/pnas.1619014114 (8 citations) Altmetric53.6; Media Links: Zimbabwe Star, AllAfrica, Technology.org, Phys.org,
  4. An Introduction to R for Spatial Analysis and Mapping, by Chris Brunsdon and Lex Comber. 2015. London: Sage Publication Ltd. 343 + xii. ISBN: 9781446272954. $52.00. (2016) {}, {} 10.1111/jors.12271
  5. MODIS Cloud Climatology (2016) {}, {} 10.6084/m9.figshare.1531955
  6. Data from Estimating Uncertainty in Daily Weather Interpolations: a Bayesian Framework for Developing Climate Surfaces (2016) {}, {} 10.6084/m9.figshare.3997116
  7. Model-based integration of observed and expert-based information for assessing the geographic and environmental distribution of freshwater species (2016) {}, {} 10.1111/ecog.01925 (8 citations) Altmetric7.3; Media Links:
  8. Remotely Sensed High-Resolution Global Cloud Dynamics for Predicting Ecosystem and Biodiversity Distributions (2016) {}, {} 10.1371/journal.pbio.1002415 (50 citations) Altmetric349.6; Media Links: World Economic Forum, Washington Post, Washington Post, Washington Post, Grist, Scientific America - Spain, LiveScience, Climate Central, Vox.com, Quartz, ICI.Radio-Canada.ca, Space Daily, R&D Mag, Headlines & Global News, Science Daily, EurekAlert!, Environmental Monitor, La Repubblica, Environmental Research Web, Futurity, New York Times, New York Times, El País, Chennai Online , Phys.org, New Kerala, Big News Network, Yahoo! News India, Technology.org, Space Daily, Laboratory Equipment , Newswise, Science Daily, Discovery News, Yale News, Phys.org, EurekAlert!, EurekAlert!,
  9. Green-up of deciduous forest communities of northeastern North America in response to climate variation and climate change (2015) {}, {} 10.1007/s10980-014-0099-7 (15 citations)
  10. Post-fire recovery in the Cape Floristic Region of South Africa (2015) {}, {} 10.6084/m9.figshare.1420575
  11. Environmental Data for Biodiversity Analyses (2015) {}, {} 10.6084/m9.figshare.951960
  12. Using multi-timescale methods and satellite-derived land surface temperature for the interpolation of daily maximum air temperature in Oregon (2015) {}, {} 10.1002/joc.4251 (10 citations) Altmetric0.3; Media Links:
  13. ISEC2014: hSDM, an R package for hierarchical species distribution models taking into account imperfect detection and spatial correlation of the observations (2015) {}, {} 10.6084/m9.figshare.1577538 Altmetric1.9; Media Links:
  14. Climatic Influences on Survival of Migratory African Reed Warblers Acrocephalus baeticatus in South Africa (2015) {}, {} 10.5253/arde.v103i2.a5 (3 citations) Altmetric5.3; Media Links:
  15. Wikipedia Content Volatility (2015) {}, {} 10.6084/m9.figshare.1397533 Altmetric21.5; Media Links: Arstechnica,
  16. Climatic controls on ecosystem resilience: Postfire regeneration in the Cape Floristic Region of South Africa (2015) {}, {} 10.1073/pnas.1416710112 (14 citations) Altmetric37.9; Media Links: Nature World News, Technology.org, Phys.org,
  17. Content Volatility of Scientific Topics in Wikipedia: A Cautionary Tale (2015) {}, {} 10.1371/journal.pone.0134454 (9 citations) Altmetric300.5; Media Links: El Confidencial, Spektrum, Washington Post, Yahoo! News, Science News, forskning.no, Arstechnica, De Wereld Morgen, New Statesman, Tech Times, R&D, Washington Post, Wired.co.uk, Gizmodo, Real Clear Science,
  18. Estimating uncertainty in daily weather interpolations: A Bayesian framework for developing climate surfaces (2014) {}, {} 10.1002/joc.3859 (18 citations)
  19. Systematic land cover bias in Collection 5 MODIS cloud mask and derived products — A global overview (2014) {}, {} 10.1016/j.rse.2013.10.025 (31 citations)
  20. Morocco Natural Resources Management and Community Development (2014) {}, {} 10.6084/m9.figshare.1144538
  21. Ecosystem dynamics: disturbance and recovery in the Cape Floristic Region of South Africa (2014) {}, {} 10.6084/m9.figshare.1025883
  22. Climatic controls on ecosystem resilience: combining hierarchical modelling with space borne monitoring of past fire plant biomass accumulation (2014) {}, {} 10.6084/m9.figshare.1142275
  23. Incorporating satellite derived cloud climatologies to improve high resolution interpolation of daily precipitation (2014) {}, {} 10.6084/m9.figshare.951959
  24. An Assessment of Methods and Remote-Sensing Derived Covariates for Regional Predictions of 1 km Daily Maximum Air Temperature (2014) {}, {} 10.3390/rs6098639 (11 citations)
  25. From imperfection to inference: issues of scale and uncertainty in global change biology (2014) {}, {} 10.6084/m9.figshare.947682
  26. Uncertainty, priors, autocorrelation and disparate data in downscaling of species distributions (2014) {}, {} 10.1111/ddi.12199 (12 citations) Altmetric4.6; Media Links:
  27. On using integral projection models to generate demographically driven predictions of species' distributions: development and validation using sparse data (2014) {}, {} 10.1111/ecog.00839 (58 citations) Altmetric6.1; Media Links:
  28. Modeling daily flowering probabilities: expected impact of climate change on Japanese cherry phenology (2014) {}, {} 10.1111/gcb.12364 (15 citations) Altmetric14.6; Media Links:
  29. Global 2009 1km MODIS (MOD35/MOD09) cloud frequency and MOD35 processing path, supplement to: Wilson, Adam M; Parmentier, Benoit; Walter, Jetz (2013): Systematic landcover bias in collection 5 MODIS cloud mask and derived products - a global overview. Remote Sensing of Environment, conditionally accept (2013) {}, {} 10.1594/pangaea.820938
  30. Bias correction and downscaling of climate model outputs for climate change impact assessments in the U.S. Northeast (2013) {}, {} 10.1016/j.gloplacha.2012.11.003
  31. Downscaling of species distribution models: A hierarchical approach (2013) {}, {} 10.1111/j.2041-210x.2012.00264.x (46 citations) Altmetric2.8; Media Links:
  32. A new class of flexible link functions with application to species co-occurrence in Cape Floristic Region (2013) {}, {} 10.1214/13-aoas663 (18 citations) Altmetric5.3; Media Links:
  33. Evaluation of satellite-derived burned area products for the fynbos, a Mediterranean shrubland (2012) {}, {} 10.1071/wf11002 (16 citations)
  34. Developing Dynamic Mechanistic Species Distribution Models: Predicting Bird-Mediated Spread of Invasive Plants across Northeastern North America (2011) {}, {} 10.1086/660295 (49 citations)
  35. Scaling up: Linking field data and remote sensing with a hierarchical model (2011) {}, {} 10.1080/13658816.2010.522779 (18 citations)
  36. Point pattern modelling for degraded presence-only data over large regions (2011) {}, {} 10.1111/j.1467-9876.2011.01023.x (68 citations)
  38. A Hierarchical Bayesian model of wildfire in a Mediterranean biodiversity hotspot: Implications of weather variability and global circulation (2010) {}, {} 10.1016/j.ecolmodel.2009.09.016 (51 citations) Altmetric1; Media Links:
  39. Identifying hotspots for plant invasions and forecasting focal points of further spread (2009) {}, {} 10.1111/j.1365-2664.2009.01736.x (58 citations)
  40. Spatial and interspecific variability in phenological responses to warming temperatures (2009) {}, {} 10.1016/j.biocon.2009.06.003 (169 citations) Altmetric1; Media Links:
  41. Multivariate forecasts of potential distributions of invasive plant species (2009) {}, {} 10.1890/07-2095.1 (92 citations) Altmetric3; Media Links:
  42. Are there spurious precipitation trends in the United States Climate Division database? (2005) {}, {} 10.1029/2004gl021985 (48 citations)
  43. Air pollution, weather, and respiratory emergency room visits in two northern New England cities: An ecological time-series study (2005) {}, {} 10.1016/j.envres.2004.07.010 (109 citations) Altmetric3.3; Media Links:
  44. Air pollution and the demand for hospital services: A review (2004) {}, {} 10.1016/j.envint.2004.01.004 (78 citations) Altmetric3; Media Links:
  45. Are there spurious temperature trends in the United States Climate Division database? (2003) {}, {} 10.1029/2002gl016295 (69 citations)


Spatial Data Science (GEO 503)

'Big Data' in ecology and environmental science now allow us to address important questions (both old and new) with unprecedented rigor and generality. Leveraging these new data streams requires new tools and increasingly sophisticated workflows. The free and open-source R programming language has become a lingua franca for ecological, epidemiological, and statistical research. The course will use a combination of lecture and hands-on exercises to provide a gentle introduction to programming in R with a focus on spatial data processing.

Environmental Science (GEO104)

Environmental science is the interdisciplinary study of the physical, chemical, and biological systems that sustain life on our planet. In this course we will explore current environmental challenges such as the conservation of biodiversity, the sustainable production of energy, and the implications of human population growth. The processes of scientific inquiry and discovery will be emphasized through investigation of specific case studies and the critical evaluation of the underlying scientific evidence.

Global Change Ecology (GEO 446/546)

Global environmental change has significant impacts on social and ecological systems around the world. Global Change Ecology is an emerging field that aims to understand the ecological implications of environmental change (especially anthropogenic climate change) and to assess risks under future global change. The course will include lectures, discussions of important scientific articles, hands-on exercises in conducting scientific research, and a group project to investigate novel scientific questions. In this course, students will review the basics of the earth system and climate change before investigating how organisms in terrestrial and aquatic ecosystems respond to climate change. Finally, we will consider the impacts of future climate change and the implications for conservation policy and adaptation management.

Lab Members

Adam M. Wilson

Assistant Professor

Global change biology, Biodiversity, remote sensing, hierarchical statistical modeling

Martin van Leeuwen

Postdoctoral Associate

Ecology, plant physiology, remote sensing

Yingying Xie

Postdoctoral Associate

Plant phenology mechanisms, spatio-temporal analysis, climate change

Chenyang Wei

Geography PhD Student

Ecology, remote sensing, geographic information science

Yating Chen

Geography MSc. Student

Climate change and geography

Gillian Schwert

Geography MSc. Student

GIS and remote sensing to address contemporary environmental problems

Former Lab Members

Larry Kaminski

Former Evolution, Ecology, and Behavior MSc. Student

Remote sensing and ecological modeling

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Our location:

120 Wilkeson Quad, Department of Geography, University at Buffalo, Buffalo, NY 14214

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