Synthetic products based on biodiversity information such as gap analysis depend critically on accurate models of species' geographic distributions that simultaneously minimize error in both overprediction and omission. We compared current gap methodologies, as exemplified by the distributional models used in the Maine Gap Analysis project, with an alternative approach, the geographic projections of ecological niche models developed using the Genetic Algorithm for Rule‐Set Prediction (GARP). Point‐occurrence data were used to develop GARP models based on the same environmental data layers as were used in the gap project, and independent occurrence data used to test both methods. Gap models performed better in avoiding omission error, but GARP better avoided errors of overprediction. Advantages of the point‐based approach, and strategies for its incorporation into current gap efforts are discussed.
Animal Conservation – Wiley
Published: Feb 1, 2003
It’s your single place to instantly
discover and read the research
that matters to you.
Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.
All for just $49/month
Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly
Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.
Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.
Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.
All the latest content is available, no embargo periods.
“Hi guys, I cannot tell you how much I love this resource. Incredible. I really believe you've hit the nail on the head with this site in regards to solving the research-purchase issue.”Daniel C.
“Whoa! It’s like Spotify but for academic articles.”@Phil_Robichaud
“I must say, @deepdyve is a fabulous solution to the independent researcher's problem of #access to #information.”@deepthiw
“My last article couldn't be possible without the platform @deepdyve that makes journal papers cheaper.”@JoseServera