Access the full text.
Sign up today, get DeepDyve free for 14 days.
Jorge Soberón, A. Peterson (2005)
INTERPRETATION OF MODELS OF FUNDAMENTAL ECOLOGICAL NICHES AND SPECIES' DISTRIBUTIONAL AREASBiodiversity Informatics, 2
Steven Phillips, R. Anderson, R. Schapire (2006)
Maximum entropy modeling of species geographic distributionsEcological Modelling, 190
A. Guisan, W. Thuiller (2005)
Predicting species distribution: offering more than simple habitat models.Ecology letters, 8 9
A. Peterson, J. Shaw (2003)
Lutzomyia vectors for cutaneous leishmaniasis in Southern Brazil: ecological niche models, predicted geographic distributions, and climate change effects.International journal for parasitology, 33 9
J. Svenning, F. Skov (2004)
Limited filling of the potential range in European tree speciesEcology Letters, 7
M. Araújo, Paul Williams (2000)
Selecting areas for species persistence using occurrence dataBiological Conservation, 96
R. Anderson, E. Martínez‐Meyer (2004)
Modeling species’ geographic distributions for preliminary conservation assessments: an implementation with the spiny pocket mice (Heteromys) of EcuadorBiological Conservation, 116
E. Fleishman, R. Nally, J. Fay (2003)
Validation Tests of Predictive Models of Butterfly Occurrence Based on Environmental VariablesConservation Biology, 17
Peterson Peterson, Navarro‐Siguenza Navarro‐Siguenza, Benitez‐Diaz Benitez‐Diaz (1998)
The need for continued collecting: a geographic analysis of Mexican bird specimensIbis, 140
C. Graham, C. Graham, S. Ferrier, Falk Huettman, C. Moritz, A. Peterson (2004)
New developments in museum-based informatics and applications in biodiversity analysis.Trends in ecology & evolution, 19 9
E. Buffetaut, D. Martill, François Escuillié (2004)
Pterosaurs as part of a spinosaur dietNature, 430
Norman Bourg, W. McShea, D. Gill (2005)
PUTTING A CART BEFORE THE SEARCH: SUCCESSFUL HABITAT PREDICTION FOR A RARE FOREST HERBEcology, 86
G. Donque (1972)
The Climatology of Madagascar
C. Thomas, A. Cameron, R. Green, R. Green, M. Bakkenes, L. Beaumont, Yvonne Collingham, B. Erasmus, Marinez Siqueira, A. Grainger, L. Hannah, L. Hughes, B. Huntley, A. Jaarsveld, G. Midgley, L. Miles, L. Miles, M. Ortega-Huerta, A. Peterson, O. Phillips, S. Williams (2004)
Extinction risk from climate changeNature, 427
R. Pearson, T. Dawson, P. Berry, P. Harrison (2002)
SPECIES: A Spatial Evaluation of Climate Impact on the Envelope of SpeciesEcological Modelling, 154
N. Roura‐Pascual, A. Suarez, Crisanto Gómez, P. Pons, Y. Touyama, A. Wild, A. Peterson (2004)
Geographical potential of Argentine ants (Linepithema humile Mayr) in the face of global climate changeProceedings of the Royal Society of London. Series B: Biological Sciences, 271
A. Zaniewski, A. Lehmann, J. Overton (2002)
Predicting species spatial distributions using presence-only data: a case study of native New Zealand fernsEcological Modelling, 157
Jorge Soberón, Townsend Peterson (2004)
Biodiversity informatics: managing and applying primary biodiversity data.Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 359 1444
A. Peterson, Adolfo Navarro‐Sigüenza, Hesiquio Benítez-Díaz (2008)
The need for continued scientific collecting; a geographic analysis of Mexican bird specimensIbis, 140
W. Thuiller, S. Lavorel, M. Araújo, M. Sykes, I. Prentice (2005)
Climate change threats to plant diversity in Europe.Proceedings of the National Academy of Sciences of the United States of America, 102 23
Robin Engler, A. Guisan, Luca Rechsteiner (2004)
An improved approach for predicting the distribution of rare and endangered species from occurrence and pseudo-absence dataJournal of Applied Ecology, 41
Bette Loiselle, Christine Howell, C. Graham, Jaqueline Goerck, T. Brooks, Kimberly Smith, P. Williams (2003)
Avoiding Pitfalls of Using Species Distribution Models in Conservation PlanningConservation Biology, 17
T. Ricketts, E. Dinerstein, T. Boucher, T. Brooks, S. Butchart, M. Hoffmann, John Lamoreux, J. Morrison, M. Parr, J. Pilgrim, A. Rodrigues, W. Sechrest, G. Wallace, Ken Berlin, J. Bielby, N. Burgess, D. Church, N. Cox, D. Knox, C. Loucks, G. Luck, L. Master, Robin Moore, R. Naidoo, R. Ridgely, G. Schatz, G. Shire, H. Strand, Wesley Wettengel, E. Wikramanayake (2005)
Pinpointing and preventing imminent extinctions.Proceedings of the National Academy of Sciences of the United States of America, 102 51
C. Raxworthy, E. Martínez‐Meyer, N. Horning, R. Nussbaum, G. Schneider, M. Ortega-Huerta, A. Peterson (2003)
Predicting distributions of known and unknown reptile species in MadagascarNature, 426
W. Thuiller, J. Vayreda, J. Pino, S. Sabaté, S. Lavorel, C. Gracia (2003)
Large-scale environmental correlates of forest tree distributions in Catalonia (NE Spain)Global Ecology and Biogeography, 12
Canran Liu, P. Berry, T. Dawson, R. Pearson (2005)
Selecting thresholds of occurrence in the prediction of species distributionsEcography, 28
A. Fielding, J. Bell (1997)
A review of methods for the assessment of prediction errors in conservation presence/absence modelsEnvironmental Conservation, 24
Rakotomalala Rakotomalala (2002)
Diversité des reptiles et amphibiens de la Réserve Spéciale de Manongarivo, MadagascarBoissiera, 59
M. Storey, J. Mahoney, A. Saunders, R. Duncan, S. Kelley, M. Coffin (1995)
Timing of Hot Spot—Related Volcanism and the Breakup of Madagascar and IndiaScience, 267
Sushma Reddy, L. Dávalos (2003)
Geographical sampling bias and its implications for conservation priorities in AfricaJournal of Biogeography, 30
A. Peterson (2003)
Predicting the Geography of Species’ Invasions via Ecological Niche ModelingThe Quarterly Review of Biology, 78
Raselimanana Raselimanana (1998)
Inventaire biologique, Forêt d'Andranomay, Anjozorobe: La diversité de la faune de reptiles et d'amphibiensRecherche pour le Développement, Série Sciences Biologiques, 13
David Stockwell (1999)
The GARP modelling system: problems and solutions to automated spatial predictionInt. J. Geogr. Inf. Sci., 13
A. Peterson, Jorge Soberón, V. Sánchez‐Cordero (1999)
Conservatism of ecological niches in evolutionary timeScience, 285 5431
W. Böhme, P. Ibisch (1990)
Studien an Uroplatus. I, Der Uroplatus-fimbriatus-KomplexSalamandra, 26
A. Hirzel, J. Hausser, D. Chessel, N. Perrin (2002)
ECOLOGICAL-NICHE FACTOR ANALYSIS: HOW TO COMPUTE HABITAT-SUITABILITY MAPS WITHOUT ABSENCE DATA?Ecology, 83
A. Bauer, A. Russell (1989)
A systematic review of the genus Uroplatus (Reptilia: Gekkonidae), with comments on its biologyJournal of Natural History, 23
S. Ferrier, M. Drielsma, G. Manion, G. Watson (2002)
Extended statistical approaches to modelling spatial pattern in biodiversity in northeast New South Wales. II. Community-level modellingBiodiversity & Conservation, 11
J. Pearce, S. Ferrier (2000)
Evaluating the predictive performance of habitat models developed using logistic regressionEcological Modelling, 133
A. Herman, V. Kumar, P. Arkin, J. Kousky (1997)
Objectively determined 10-day African rainfall estimates created for famine early warning systemsInternational Journal of Remote Sensing, 18
N. Myers, R. Mittermeier, C. Mittermeier, G. Fonseca, J. Kent (2000)
Biodiversity hotspots for conservation prioritiesNature, 403
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
L. Iverson, A. Prasad (1998)
PREDICTING ABUNDANCE OF 80 TREE SPECIES FOLLOWING CLIMATE CHANGE IN THE EASTERN UNITED STATESEcological Monographs, 68
M. Boyce, Pierre Vernier, S. Nielsen, F. Schmiegelow (2002)
Evaluating resource selection functionsEcological Modelling, 157
Böhme Böhme, Schönecker Schönecker (2003)
Eine neue art der gattung Uroplatus Duméril, 1805 aus ost‐Madagaskar (Reptilia: Squamata: Gekkonidae)Salamandra, 31
C. Raxworthy, M. Forstner, R. Nussbaum (2002)
Chameleon radiation by oceanic dispersalNature, 415
Raselimanana Raselimanana (1999)
Inventaire biologique de la Réserve Spéciale de Pic d'Ivohibe et du couloire forestier qui la relie au Parc National d'Andringitra: L'herpetofaunaRecherche pour le Développement, Série Sciences Biologiques, 15
J. Elith, Catherine Graham, Robert Anderson, Miroslav Dudı́k, Simon Ferrier, A. Guisan, R. Hijmans, F. Huettmann, J. Leathwick, Anthony Lehmann, Jin Li, Lúcia Lohmann, Bette Loiselle, G. Manion, Craig Moritz, Miguel Nakamura, Yoshinori Nakazawa, J. Overton, A. Peterson, Steven Phillips, Karen Richardson, R. Scachetti-Pereira, R. Schapire, Jorge Soberón, Stephen Williams, M. Wisz, N. Zimmermann (2006)
Novel methods improve prediction of species' distributions from occurrence dataEcography, 29
M. Araújo, R. Pearson, W. Thuiller, M. Erhard (2005)
Validation of species–climate impact models under climate changeGlobal Change Biology, 11
W. Thuiller, D. Richardson, P. Pyšek, G. Midgley, G. Hughes, M. Rouget (2005)
Niche‐based modelling as a tool for predicting the risk of alien plant invasions at a global scaleGlobal Change Biology, 11
P. Segurado, M. Araújo (2004)
An evaluation of methods for modelling species distributionsJournal of Biogeography, 31
C. Graham, S. Ron, Juan Santos, C. Schneider, C. Moritz (2004)
INTEGRATING PHYLOGENETICS AND ENVIRONMENTAL NICHE MODELS TO EXPLORE SPECIATION MECHANISMS IN DENDROBATID FROGS, 58
R. Anderson, D. Lew, A. Peterson (2003)
Evaluating predictive models of species’ distributions: criteria for selecting optimal modelsEcological Modelling, 162
J. Karl, P. Heglund, E. Garton, J. Scott, N. Wright, R. Hutto (2000)
SENSITIVITY OF SPECIES HABITAT-RELATIONSHIP MODEL PERFORMANCE TO FACTORS OF SCALEEcological Applications, 10
E. Martínez‐Meyer, A. Peterson, Adolfo Navarro‐Sigüenza (2004)
Evolution of seasonal ecological niches in the Passerina buntings (Aves: Cardinalidae)Proceedings of the Royal Society of London. Series B: Biological Sciences, 271
P. Xie, P. Arkin (1996)
Analyses of Global Monthly Precipitation Using Gauge Observations, Satellite Estimates, and Numerical Model PredictionsJournal of Climate, 9
R. Hijmans, S. Cameron, J. Parra, Peter Jones, A. Jarvis (2005)
Very high resolution interpolated climate surfaces for global land areasInternational Journal of Climatology, 25
N. Rice, E. Martínez‐Meyer, A. Peterson (2003)
Ecological niche differentiation in the Aphelocoma jays: a phylogenetic perspectiveBiological Journal of The Linnean Society, 80
M. Luoto, J. Pöyry, R. Heikkinen, K. Saarinen (2005)
Uncertainty of bioclimate envelope models based on the geographical distribution of speciesGlobal Ecology and Biogeography, 14
Hampe Hampe (2004)
Bioclimatic models: what they detect and what they hideGlobal Ecology and Biogeography, 11
Hutchinson Hutchinson (1957)
Concluding remarksCold Spring Harbor Symposium on Quantitative Biology, 22
A. Hampe (2004)
Bioclimate envelope models: what they detect and what they hideGlobal Ecology and Biogeography, 13
David Stockwell, A. Peterson (2002)
Effects of sample size on accuracy of species distribution modelsEcological Modelling, 148
M. Araújo, R. Pearson (2005)
Equilibrium of species’ distributions with climateEcography, 28
Richard Pearson, Terence Dawson (2003)
Predicting the impacts of climate change on the distribution of species: are bioclimate envelope models useful?Global Ecology and Biogeography, 12
Stockwell Stockwell, Peters Peters (1999)
The GARP modelling system: problems and solutions to automated spatial predictionInternational Journal of Geographical Information Systems, 13
M. Ortega-Huerta, A. Peterson (2004)
Modelling spatial patterns of biodiversity for conservation prioritization in North‐eastern MexicoDiversity and Distributions, 10
G. Carpenter, A. Gillison, J. Winter (1993)
DOMAIN: a flexible modelling procedure for mapping potential distributions of plants and animalsBiodiversity & Conservation, 2
W. Thuiller, M. Araújo, R. Pearson, R. Whittaker, L. Brotóns, S. Lavorel (2004)
Biodiversity conservation: Uncertainty in predictions of extinction riskNature, 430
F. Andreone, M. Vences, J. Randrianirina (2001)
Patterns of amphibian and reptile diversity at Berara Forest (Sahamalaza Peninsula), NW MadagascarItalian Journal of Zoology, 68
R. Pearson, W. Thuiller, M. Araújo, E. Martínez‐Meyer, L. Brotóns, C. McClean, L. Miles, P. Segurado, T. Dawson, D. Lees (2006)
Model‐based uncertainty in species range predictionJournal of Biogeography, 33
Araújo Araújo, Pearson Pearson, Thuiller Thuiller, Erhard Erhard (2005)
Validation of species‐climate envelope models under climate changeGlobal Change Biology, 11
Rakotomalala Rakotomalala, Raholimavo Raholimavo, Talata Talata, Rajeriarison Rajeriarison (2001)
Les amphibiens et reptiles du Parc National de Ranomafana et de la zone forestiere le reliant au Parc National d'AndringitraRecherche pour le Développement, Série Sciences Biologiques, 17
G. Reese, K. Wilson, J. Hoeting, C. Flather (2005)
FACTORS AFFECTING SPECIES DISTRIBUTION PREDICTIONS: A SIMULATION MODELING EXPERIMENTEcological Applications, 15
R. Pearson, T. Dawson, Canran Liu (2004)
Modelling species distributions in Britain: a hierarchical integration of climate and land-cover dataEcography, 27
Aim Techniques that predict species potential distributions by combining observed occurrence records with environmental variables show much potential for application across a range of biogeographical analyses. Some of the most promising applications relate to species for which occurrence records are scarce, due to cryptic habits, locally restricted distributions or low sampling effort. However, the minimum sample sizes required to yield useful predictions remain difficult to determine. Here we developed and tested a novel jackknife validation approach to assess the ability to predict species occurrence when fewer than 25 occurrence records are available. Location Madagascar. Methods Models were developed and evaluated for 13 species of secretive leaf‐tailed geckos (Uroplatus spp.) that are endemic to Madagascar, for which available sample sizes range from 4 to 23 occurrence localities (at 1 km2 grid resolution). Predictions were based on 20 environmental data layers and were generated using two modelling approaches: a method based on the principle of maximum entropy (Maxent) and a genetic algorithm (GARP). Results We found high success rates and statistical significance in jackknife tests with sample sizes as low as five when the Maxent model was applied. Results for GARP at very low sample sizes (less than c. 10) were less good. When sample sizes were experimentally reduced for those species with the most records, variability among predictions using different combinations of localities demonstrated that models were greatly influenced by exactly which observations were included. Main conclusions We emphasize that models developed using this approach with small sample sizes should be interpreted as identifying regions that have similar environmental conditions to where the species is known to occur, and not as predicting actual limits to the range of a species. The jackknife validation approach proposed here enables assessment of the predictive ability of models built using very small sample sizes, although use of this test with larger sample sizes may lead to overoptimistic estimates of predictive power. Our analyses demonstrate that geographical predictions developed from small numbers of occurrence records may be of great value, for example in targeting field surveys to accelerate the discovery of unknown populations and species.
Journal of Biogeography – Wiley
Published: Jan 1, 2007
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.