Delimiting the geographical background in species distribution modelling

Aim  The extent of the study area (geographical background, GB) can strongly affect the results of species distribution models (SDMs), but as yet we lack objective and practicable criteria for delimiting the appropriate GB. We propose an approach to this problem using trend surface analysis (TSA) and provide an assessment of the effects of varying GB extent on the performance of SDMs for four species.

[1]  A. Peterson,et al.  The crucial role of the accessible area in ecological niche modeling and species distribution modeling , 2011 .

[2]  A. Jiménez‐Valverde,et al.  Environmental suitability of new reported localities of the funnelweb spider Macrothele calpeiana: an assessment using potential distribution modelling with presence‐only techniques , 2011 .

[3]  A. Peterson,et al.  Use of niche models in invasive species risk assessments , 2011, Biological Invasions.

[4]  R. Real,et al.  Biogeographical differences between the two Capra pyrenaica subspecies, C. p. victoriae and C. p. hispanica, inhabiting the Iberian Peninsula: Implications for conservation , 2011 .

[5]  A. Peterson,et al.  Dominant climate influences on North American bird distributions , 2011 .

[6]  J. Lobo,et al.  Species distribution models that do not incorporate global data misrepresent potential distributions: a case study using Iberian diving beetles , 2011 .

[7]  Steven J. Phillips,et al.  The art of modelling range‐shifting species , 2010 .

[8]  Robert P. Anderson,et al.  The effect of the extent of the study region on GIS models of species geographic distributions and estimates of niche evolution: preliminary tests with montane rodents (genus Nephelomys) in Venezuela , 2010 .

[9]  Alberto Jiménez-Valverde,et al.  The uncertain nature of absences and their importance in species distribution modelling , 2010 .

[10]  Jorge Soberón.  Niche and area of distribution modeling: a population ecology perspective , 2010 .

[11]  A. Zuur,et al.  Mixed Effects Models and Extensions in Ecology with R , 2009 .

[12]  C. Graham,et al.  Selecting pseudo-absence data for presence-only distribution modeling: How far should you stray from what you know? , 2009 .

[13]  P. Acevedo,et al.  Biology, ecology and status of Iberian ibex Capra pyrenaica: a critical review and research prospectus , 2009 .

[14]  Alberto Jiménez-Valverde,et al.  Not as good as they seem: the importance of concepts in species distribution modelling , 2008 .

[15]  R. Real,et al.  AUC: a misleading measure of the performance of predictive distribution models , 2008 .

[16]  Wilfried Thuiller,et al.  Accuracy of resource selection functions across spatial scales , 2006 .

[17]  A. Márcia Barbosa,et al.  Obtaining Environmental Favourability Functions from Logistic Regression , 2006, Environmental and Ecological Statistics.

[18]  Jane Elith,et al.  Fauna habitat modelling and mapping: A review and case study in the Lower Hunter Central Coast region of NSW , 2005 .

[19]  J. Svenning,et al.  The relative roles of environment and history as controls of tree species composition and richness in Europe , 2005 .

[20]  A. Peterson,et al.  INTERPRETATION OF MODELS OF FUNDAMENTAL ECOLOGICAL NICHES AND SPECIES' DISTRIBUTIONAL AREAS , 2005 .

[21]  I. Hevia.  Geología de España: una historia de seiscientos millones de años , 2004 .

[22]  A. Márcia Barbosa,et al.  Otter (Lutra lutra) distribution modeling at two resolution scales suited to conservation planning in the Iberian Peninsula , 2003 .

[23]  A. Márcia Barbosa,et al.  Relative importance of environment, human activity and spatial situation in determining the distribution of terrestrial mammal diversity in Argentina , 2003 .

[24]  S. Ferrier,et al.  An evaluation of alternative algorithms for fitting species distribution models using logistic regression , 2000 .

[25]  M. McGlone,et al.  When History Matters: Scale, Time, Climate and Tree Diversity , 1996 .

[26]  S L Hui,et al.  Validation techniques for logistic regression models. , 1991, Statistics in medicine.

[27]  Louis Legendre,et al.  The Importance of Being Digital , 1963 .

[28]  Inocencio Font Tullot.  Climatología de España y Portugal , 1983 .