Integrating occurrence data and expert maps for improved species range predictions-Reference-Cited by-同舟云学术

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Integrating occurrence data and expert maps for improved species range predictions

Published:2016-11-23 Issue:2 Volume:26 Page:243-258
ISSN:1466-822X
Container-title:Global Ecology and Biogeography
language:en
Short-container-title:Global Ecol. Biogeogr.

Author:

Merow Cory¹²^ORCID,Wilson Adam M.¹³,Jetz Walter¹⁴

Affiliation:

1. Ecology and Evolutionary Biology; Yale University; 165 Prospect Street New Haven CT USA

2. Ecology and Evolutionary Biology; University of Connecticut; Storrs CT USA

3. Department of Geography; University at Buffalo, Wilkeson Quad; Buffalo NY USA

4. Department of Life Sciences; Imperial College London Silwood Park Campus Ascot; Berkshire SL5 7PY UK

Funder

NSF Grants

National Aeronautics and Space Administration

Publisher

Wiley

Subject

Ecology,Ecology, Evolution, Behavior and Systematics,Global and Planetary Change

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1111/geb.12539/fullpdf

Reference44 articles.

1. Comparative interpretation of count, presence-absence and point methods for species distribution models;Aarts;Methods in Ecology and Evolution,2012

2. Harnessing the world's biodiversity data: promise and peril in ecological niche modeling of species distributions;Anderson;Annals of the New York Academy of Sciences,2012

3. Distorted views of biodiversity: spatial and temporal bias in species occurrence data;Boakes;PLoS Biology,2010

4. Point pattern modelling for degraded presence only data over large regions;Chakraborty;Journal of the Royal Statistical Society: Series C (Applied Statistics),2011

5. Beyond predictions: biodiversity conservation in a changing climate;Dawson;Science,2011

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1. The Best of Two Worlds: Using Stacked Generalisation for Integrating Expert Range Maps in Species Distribution Models;Global Ecology and Biogeography;2024-09-10

2. Regional uniqueness of tree species composition and response to forest loss and climate change;Nature Communications;2024-05-31

3. Evaluating spatial resolution and imperfect detection effects on the predictive performance of inhomogeneous spatial point process models trained with simulated presence-only data;Modeling Earth Systems and Environment;2024-05-17

4. Expert‐based range maps cannot be replicated using data‐driven methods but macroecological conclusions arising from them can;Journal of Biogeography;2024-04-12

5. Selecting umbrella species as mammal biodiversity indicators in tropical forest;Biological Conservation;2024-04

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