Access the full text.
Sign up today, get DeepDyve free for 14 days.
R. Degraaf, M. Yamasaki, W. Leak, John Lanier (1992)
New England wildlife: management forested habitats, 144
(1996)
Gap analysis: a landscape approach to biodiversity planning
A. Peterson, M. Ortega-Huerta, J. Bartley, V. Sánchez‐Cordero, Jorge Soberón, Robert Buddemeier, David Stockwell (2002)
Future projections for Mexican faunas under global climate change scenariosNature, 416
A. Peterson, V. Sánchez‐Cordero, Jorge Soberón, J. Bartley, R. Buddemeier, Adolfo Navarro‐Sigüenza (2001)
Effects of global climate change on geographic distributions of Mexican CracidaeEcological Modelling, 144
(2002)
Predicting distributions of tropical birds
(1996)
Mapping animal distribution areas for gap analysis
Share your story about how Open Access to this item benefits YOU at https://openaccess
J. Grinnell (1917)
Field Tests of Theories Concerning Distributional ControlThe American Naturalist, 51
Using intermodel variation in error components to select best subsets of ecological niche models
A. Peterson, D. Vieglais (2001)
Predicting species invasions using ecological niche modeling
J. Nichols, T. Boulinier, J. Hines, K. Pollock, J. Sauer (1998)
Inference Methods for Spatial Variation in Species Richness and Community Composition When Not All Species Are DetectedConservation Biology, 12
(2002)
Controlling bias in biodiversity data
(2002)
Distributional prediction based on ecological niche modelling of primary occurrence data. In Predicting species occurrences: issues of scale and accuracy
(1957)
Concluding remarks. Cold Spring Harbor Sym
T. P. Feria, A. T. Peterson (2002)
Using point occurrence data and inferential algorithms to predict local communities of birdsEcology, 8
T. A., A. Peterson (2002)
Prediction of bird community composition based on point‐occurrence data and inferential algorithms: a valuable tool in biodiversity assessmentsDiversity and Distributions, 8
(1996)
Gap analysis: a landscape approach to biodiversity planning. Bethesda, MD: American Society for Photogrammetry and Remote Sensing
N. Gotelli (2003)
Predicting Species Occurrences: Issues of Accuracy and Scale, 120
J. Grinnell (1924)
Geography and EvolutionEcology, 5
A. Peterson, Lisa Ball, Kevin Cohoon (2002)
Predicting distributions of Mexican birds using ecological niche modelling methodsIbis, 144
H. A. Nix (1986)
Atlas of elapid snakes of AustraliaStrix occidentalis. Conserv. Biol
(1998)
Maine Gap Analysis: a geographic analysis of biodiversity. Moscow, ID: US Biological Resources Division, Gap Analysis Program
Townsend Peterson, D. Vieglais, On (2001)
Predicting Species Invasions Using Ecological Niche Modeling: New Approaches from Bioinformatics Attack a Pressing Problem, 51
A. Fielding, J. Bell (1997)
A review of methods for the assessment of prediction errors in conservation presence/absence modelsEnvironmental Conservation, 24
A. T. Peterson, C. R. Robins
When endangered meets invasive: ecological niche modelling predicts double trouble for spotted owlsMaths. Comput. in Simul.
A. T. Peterson, V. Sanchez‐Cordero, C. B. Beard, J. M. Ramsey (2002c)
Ecologic niche modelling and potential reservoirs for Chagas disease, MexicoInt. J. of Geog. Inf. Syst., 8
(1998)
Maine Gap Analysis vertebrate data, Part II: Distribution, habitat relations, and status of breeding birds in Maine
(1986)
A biogeographic analysis of Australian elapid snakes
W. B. Krohn, R. B. Boone, S. A. Sader, J. A. Hepinstall, S. M. Schaefer, S. L. Painton (1998)
Maine Gap Analysis: a geographic analysis of biodiversityIbis
David Stockwell (1999)
The GARP modelling system: problems and solutions to automated spatial predictionInt. J. Geogr. Inf. Sci., 13
P. Walker, K. Cocks (1991)
HABITAT : a procedure for modelling a disjoint environmental envelope for a plant or animal species, 1
A. T. Peterson, A. G. Navarro‐Siguenza, H. Benitez‐Diaz (1998)
The need for continued scientific collecting: a geographic analysis of Mexican bird specimensBioScience, 140
A. Peterson, Jorge Soberón, V. Sánchez‐Cordero (1999)
Conservatism of ecological niches in evolutionary timeScience, 285 5431
J. Grinnell (1917)
Field tests of theories concerning distributional controlConserv. Biol., 51
David Stockwell, I. Noble (1992)
Induction of sets of rules from animal distribution data: a robust and informative method of data analysisMathematics and Computers in Simulation, 33
In press) When endangered meets invasive: ecological niche modelling predicts double trouble for spotted owls, Strix occidentalis
R. Anderson, Marcela Gómez‐Laverde, A. Peterson (2002)
Geographical distributions of spiny pocket mice in South America: insights from predictive modelsGlobal Ecology and Biogeography, 11
M. Austin, A. Nicholls, C. Margules (1990)
Measurement of the realized qualitative niche: environmental niches of five Eucalyptus speciesEcological Monographs, 60
(1996)
Predicted vertebrate distributions from gap analysis: considerations in the designs of statewide accuracy assessments
J. Scott, F. Davis, B. Csuti, R. Noss, C. Groves, H. Anderson, S. Caicco, T. Edwards, J. Ulliman, R. Wright (1993)
GAP ANALYSIS: A GEOGRAPHIC APPROACH TO PROTECTION OF BIOLOGICAL DIVERSITY
A., Townsend Peterson (2001)
PREDICTING SPECIES' GEOGRAPHIC DISTRIBUTIONS BASED ON ECOLOGICAL NICHE MODELING, 103
A. Peterson, Kevin Cohoon (1999)
Sensitivity of distributional prediction algorithms to geographic data completenessEcological Modelling, 117
R. Anderson, A. Peterson, Marcela Gómez‐Laverde, R. Anderson, A. Peterson, Gó Mez-Laverde (2002)
Using niche-based GIS modeling to test geographic predictions of competitive exclusion and competitive release in South American pocket miceOikos, 98
David Stockwell (1999)
Genetic Algorithms II
D. R. B. Stockwell, A. T. Peterson (2002a)
Predicting species occurrences: issues of scale and accuracy
David Stockwell, A. Peterson (2002)
Effects of sample size on accuracy of species distribution modelsEcological Modelling, 148
A. Peterson, V. Sánchez‐Cordero, C. Beard, J. Ramsey (2002)
Ecologic Niche Modeling and Potential Reservoirs for Chagas Disease, Mexico.Emerging Infectious Diseases, 8
D. R. B. Stockwell (1999)
Machine learning methods for ecological applications
(2002)
Using point occurrence data and inferential algorithms to predict local communities of birds. Divers. and Distrib
G. E. Hutchinson (1957)
Concluding remarksIbis, 22
A. H. Fielding, J. F. Bell (1997)
A review of methods for the assessment of prediction errors in conservation presence/absence modelsCold Spring Harbor Sym. Quant. Biol, 24
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
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.