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Coefficient shifts in geographical ecology: an empirical evaluation of spatial and non-spatial regression

2009-04Journal article Open access
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dc.contributor.authorBini, L. Mauricio
dc.contributor.authorDiniz-Filho, J. Alexandre F.
dc.contributor.authorRangel, Thiago F. L. V. B.
dc.contributor.authorAkre, Thomas S. B.
dc.contributor.authorAlbaladejo, Rafael G.
dc.contributor.authorAlbuquerque, Fabio S.
dc.contributor.authorAparicio, Abelardo
dc.contributor.authorAraújo, Miguel B.
dc.contributor.authorBaselga, Andrés
dc.contributor.authorBeck, Jan
dc.contributor.authorBellocq, M. Isabel
dc.contributor.authorBöhning-Gaese, Katrin
dc.contributor.authorBorges, Paulo A. V.
dc.contributor.authorCastro-Parga, Isabel
dc.contributor.authorChey, Vun Khen
dc.contributor.authorChown, Steven L.
dc.contributor.authorMarco, Paulo de Jr
dc.contributor.authorDobkin, David S.
dc.contributor.authorFerrer-Castán, Dolores
dc.contributor.authorField, Richard
dc.contributor.authorFilloy, Julieta
dc.contributor.authorFleishman, Erica
dc.contributor.authorGómez, Jose F.
dc.contributor.authorHortal, Joaquín
dc.contributor.authorIverson, John B.
dc.contributor.authorKerr, Jeremy T.
dc.contributor.authorKissling, W. Daniel
dc.contributor.authorKitching, Ian J.
dc.contributor.authorLeón-Cortés, Jorge L.
dc.contributor.authorLobo, Jorge M.
dc.contributor.authorMontoya, Daniel
dc.contributor.authorMorales-Castilla, Ignacio
dc.contributor.authorMoreno, Juan C.
dc.contributor.authorOberdorff, Thierry
dc.contributor.authorOlalla-Tárraga, Miguel Á.
dc.contributor.authorPausas, Juli G.
dc.contributor.authorQian, Hong
dc.contributor.authorRahbek, Carsten
dc.contributor.authorRodríguez, Miguel Á.
dc.contributor.authorRueda, Marta
dc.contributor.authorRuggiero, Adriana
dc.contributor.authorSackmann, Paula
dc.contributor.authorSanders, Nathan J.
dc.contributor.authorTerribile, Levi Carina
dc.contributor.authorVetaas, Ole R.
dc.contributor.authorHawkins, Bradford A.
dc.date.accessioned2013-02-14T13:28:33Z
dc.date.available2013-02-14T13:28:33Z
dc.date.issued2009-04
dc.date.updated2012-07-08T20:12:52Z
dc.descriptionCopyright © 2009 The Authors. Copyright © ECOGRAPHY 2009.en
dc.description.abstractA major focus of geographical ecology and macro ecology is to understand the causes of spatially structured ecological patterns. However, achieving this understanding can be complicated when using multiple regressions, because the relative importance of explanatory variables, as measured by regression coefficients, can shift depending on whether spatially explicit or non-spatial modelling is used. However, the extent to which coefficients may shift and why shifts occur are unclear. Here, we analyze the relationship between environmental predictors and the geographical distribution of species richness, body size, range size and abundance in 97 multi-factorial data sets. Our goal was to compare standardized partial regression coefficients of non-spatial ordinary least squares regressions (i.e. models fitted using ordinary least squares without taking autocorrelation into account; “OLS models” hereafter) and eight spatial methods to evaluate the frequency of coefficient shifts and identify characteristics of data that might predict when shifts are likely. We generated three metrics of coefficient shifts and eight characteristics of the data sets as predictors of shifts. Typical of ecological data, spatial autocorrelation in the residuals of OLS models was found in most data sets. The spatial models varied in the extent to which they minimized residual spatial autocorrelation. Patterns of coefficient shifts also varied among methods and datasets, although the magnitudes of shifts tended to be small in all cases. We were unable to identify strong predictors of shifts, including the levels of autocorrelation in either explanatory variables or model residuals. Thus, changes in coefficients between spatial and non-spatial methods depend on the method used and are largely idiosyncratic, making it difficult to predict when or why shifts occur. We conclude that the ecological importance of regression coefficients cannot be evaluated with confidence irrespective of whether spatially explicit modelling is used or not. Researchers may have little choice but to be more explicit about the uncertainty of models and more cautious in their interpretation.en
dc.identifier.citationMauricio Bini, L.; Diniz-Filho, J. Alexandre F.; Rangel, Thiago F.L.V.B.; Akre, Thomas S.B.; Albaladejo, Rafael G.; Albuquerque, Fabio S.; Aparicio, Abelardo; Araújo, Miguel B.; Baselga, Andrés; Beck, Jan; Isabel Bellocq, M.; Böhning-Gaese, Katrin; Borges, Paulo A.V.; Castro-Parga, Isabel; Khen Chey, Vun; Chown, Steven L.; de Marco, Jr, Paulo; Dobkin, David S.; Ferrer-Castán, Dolores; Field, Richard; Filloy, Julieta; Fleishman, Erica; Gómez, Jose F.; Hortal, Joaquín; Iverson, John B.; Kerr, Jeremy T.; Daniel Kissling, W.; Kitching, Ian J.; León-Cortés, Jorge L.; Lobo, Jorge M.; Montoya, Daniel; Morales-Castilla, Ignacio; Moreno, Juan C.; Oberdorff, Thierry; Olalla-Tárraga, Miguel Á.; Pausas, Juli G.; Qian, Hong; Rahbek, Carsten; Rodríguez, Miguel Á.; Rueda, Marta; Ruggiero, Adriana; Sackmann, Paula; Sanders, Nathan J.; Carina Terribile, Levi; Vetaas, Ole R.; Hawkins, Bradford A. (2009). "Coefficient shifts in geographical ecology: an empirical evaluation of spatial and non-spatial regression". «Ecography», 32(2): 193-204. dx.doi.org/10.1111/j.1600-0587.2009.05717.xpor
dc.identifier.issn0906-7590 (Print)
dc.identifier.issn1600-0587 (Online)
dc.identifier.urihttp://hdl.handle.net/10400.3/1632
dc.language.isoengpor
dc.peerreviewedyespor
dc.publisherWiley-Blackwellen
dc.relation.publisherversionhttp://dx.doi.org/10.1111/j.1600-0587.2009.05717.xpor
dc.subjectPatterns of Diversityen
dc.titleCoefficient shifts in geographical ecology: an empirical evaluation of spatial and non-spatial regressionen
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage204por
oaire.citation.issue2por
oaire.citation.startPage193por
oaire.citation.titleEcographyen
oaire.citation.volume32por
rcaap.rightsopenAccesspor
rcaap.typearticlepor

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