Species Distribution Modelling using Presence-only Data: Applications in Ecology, Evolution and Conservation
Species distribution models (SDMs) are used in many research areas. However, it is often the case that modellers only possess data on records of species occurrences, with little knowledge of species absences or the sampling scheme used for data collection. Sampling bias can significantly affect the predictive accuracy of SDMs. I am testing the effects of sampling bias on predictive accuracy of MaxEnt, a presence-only modelling approach, for tree ferns across New Zealand.
An overall research goal is to utilize SDMs to predict areas of high biological diversity at a global scale based on plant ecophysiology with an aim to have a direct application in conservation biology.
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Syfert M, Rudy J, Anderson L, Cleve C, Jenkins J, Skiles J, and Schmidt C. 2006. Forest Regeneration Assessment in Yosemite National Park. Proceedings of American Society for Photogrammetry and Remote Sensing. May 1- 5, 2006. Reno, NV.
Hall B, Motzkin G, Foster DR, Syfert M, and Burk J. 2002. Three Hundred Years of Forest and Land-use Change in Massachusetts, USA. Journal of Biogeography 29: 1319-1335.