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

A major focus of geographical ecology and macroecology is to understand the causes of spatially structured ecological patterns. However, achieving this understanding can be complicated when using multiple regression, because the relative importance of explanatory variables, as measured by regression...

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Published in:Ecography (Copenhagen) 2009-04, Vol.32 (2), p.193-204
Main Authors: Mauricio 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
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cited_by cdi_FETCH-LOGICAL-c5757-82dd68d79191a98059e77d83e192018738caed81663f03d23b27764ca206c1983
cites cdi_FETCH-LOGICAL-c5757-82dd68d79191a98059e77d83e192018738caed81663f03d23b27764ca206c1983
container_end_page 204
container_issue 2
container_start_page 193
container_title Ecography (Copenhagen)
container_volume 32
creator Mauricio 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
description A major focus of geographical ecology and macroecology is to understand the causes of spatially structured ecological patterns. However, achieving this understanding can be complicated when using multiple regression, because the relative importance of explanatory variables, as measured by regression coefficients, can shift depending on whether spatially explicit or non-spatial modeling 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.
doi_str_mv 10.1111/j.1600-0587.2009.05717.x
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Psychology</topic><topic>General aspects</topic><topic>General aspects. Techniques</topic><topic>Methods and techniques (sampling, tagging, trapping, modelling...)</topic><topic>Modeling</topic><topic>Regression coefficients</topic><topic>Review &amp; Synthesis</topic><topic>Spatial models</topic><topic>Variable coefficients</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Mauricio Bini, L</creatorcontrib><creatorcontrib>Diniz-Filho, J. Alexandre F</creatorcontrib><creatorcontrib>Rangel, Thiago F.L.V.B</creatorcontrib><creatorcontrib>Akre, Thomas S.B</creatorcontrib><creatorcontrib>Albaladejo, Rafael G</creatorcontrib><creatorcontrib>Albuquerque, Fabio S</creatorcontrib><creatorcontrib>Aparicio, Abelardo</creatorcontrib><creatorcontrib>Araújo, Miguel B</creatorcontrib><creatorcontrib>Baselga, Andrés</creatorcontrib><creatorcontrib>Beck, Jan</creatorcontrib><creatorcontrib>Isabel Bellocq, M</creatorcontrib><creatorcontrib>Böhning-Gaese, Katrin</creatorcontrib><creatorcontrib>Borges, Paulo A.V</creatorcontrib><creatorcontrib>Castro-Parga, Isabel</creatorcontrib><creatorcontrib>Khen Chey, Vun</creatorcontrib><creatorcontrib>Chown, Steven L</creatorcontrib><creatorcontrib>de Marco, Jr, Paulo</creatorcontrib><creatorcontrib>Dobkin, David S</creatorcontrib><creatorcontrib>Ferrer-Castán, Dolores</creatorcontrib><creatorcontrib>Field, Richard</creatorcontrib><creatorcontrib>Filloy, Julieta</creatorcontrib><creatorcontrib>Fleishman, Erica</creatorcontrib><creatorcontrib>Gómez, Jose F</creatorcontrib><creatorcontrib>Hortal, Joaquín</creatorcontrib><creatorcontrib>Iverson, John B</creatorcontrib><creatorcontrib>Kerr, Jeremy T</creatorcontrib><creatorcontrib>Daniel Kissling, W</creatorcontrib><creatorcontrib>Kitching, Ian J</creatorcontrib><creatorcontrib>León-Cortés, Jorge L</creatorcontrib><creatorcontrib>Lobo, Jorge M</creatorcontrib><creatorcontrib>Montoya, Daniel</creatorcontrib><creatorcontrib>Morales-Castilla, Ignacio</creatorcontrib><creatorcontrib>Moreno, Juan C</creatorcontrib><creatorcontrib>Oberdorff, Thierry</creatorcontrib><creatorcontrib>Olalla-Tárraga, Miguel Á</creatorcontrib><creatorcontrib>Pausas, Juli G</creatorcontrib><creatorcontrib>Qian, Hong</creatorcontrib><creatorcontrib>Rahbek, Carsten</creatorcontrib><creatorcontrib>Rodríguez, Miguel Á</creatorcontrib><creatorcontrib>Rueda, Marta</creatorcontrib><creatorcontrib>Ruggiero, Adriana</creatorcontrib><creatorcontrib>Sackmann, Paula</creatorcontrib><creatorcontrib>Sanders, Nathan J</creatorcontrib><creatorcontrib>Carina Terribile, Levi</creatorcontrib><creatorcontrib>Vetaas, Ole R</creatorcontrib><creatorcontrib>Hawkins, Bradford A</creatorcontrib><collection>AGRIS</collection><collection>Istex</collection><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Ecology Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><jtitle>Ecography (Copenhagen)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Mauricio Bini, L</au><au>Diniz-Filho, J. Alexandre F</au><au>Rangel, Thiago F.L.V.B</au><au>Akre, Thomas S.B</au><au>Albaladejo, Rafael G</au><au>Albuquerque, Fabio S</au><au>Aparicio, Abelardo</au><au>Araújo, Miguel B</au><au>Baselga, Andrés</au><au>Beck, Jan</au><au>Isabel Bellocq, M</au><au>Böhning-Gaese, Katrin</au><au>Borges, Paulo A.V</au><au>Castro-Parga, Isabel</au><au>Khen Chey, Vun</au><au>Chown, Steven L</au><au>de Marco, Jr, Paulo</au><au>Dobkin, David S</au><au>Ferrer-Castán, Dolores</au><au>Field, Richard</au><au>Filloy, Julieta</au><au>Fleishman, Erica</au><au>Gómez, Jose F</au><au>Hortal, Joaquín</au><au>Iverson, John B</au><au>Kerr, Jeremy T</au><au>Daniel Kissling, W</au><au>Kitching, Ian J</au><au>León-Cortés, Jorge L</au><au>Lobo, Jorge M</au><au>Montoya, Daniel</au><au>Morales-Castilla, Ignacio</au><au>Moreno, Juan C</au><au>Oberdorff, Thierry</au><au>Olalla-Tárraga, Miguel Á</au><au>Pausas, Juli G</au><au>Qian, Hong</au><au>Rahbek, Carsten</au><au>Rodríguez, Miguel Á</au><au>Rueda, Marta</au><au>Ruggiero, Adriana</au><au>Sackmann, Paula</au><au>Sanders, Nathan J</au><au>Carina Terribile, Levi</au><au>Vetaas, Ole R</au><au>Hawkins, Bradford A</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Coefficient shifts in geographical ecology: an empirical evaluation of spatial and non-spatial regression</atitle><jtitle>Ecography (Copenhagen)</jtitle><addtitle>Ecography</addtitle><date>2009-04</date><risdate>2009</risdate><volume>32</volume><issue>2</issue><spage>193</spage><epage>204</epage><pages>193-204</pages><issn>0906-7590</issn><eissn>1600-0587</eissn><abstract>A major focus of geographical ecology and macroecology is to understand the causes of spatially structured ecological patterns. However, achieving this understanding can be complicated when using multiple regression, because the relative importance of explanatory variables, as measured by regression coefficients, can shift depending on whether spatially explicit or non-spatial modeling 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.</abstract><cop>Oxford, UK</cop><pub>Oxford, UK : Blackwell Publishing Ltd</pub><doi>10.1111/j.1600-0587.2009.05717.x</doi><tpages>12</tpages><oa>free_for_read</oa></addata></record>
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identifier ISSN: 0906-7590
ispartof Ecography (Copenhagen), 2009-04, Vol.32 (2), p.193-204
issn 0906-7590
1600-0587
language eng
recordid cdi_proquest_miscellaneous_20591626
source JSTOR Archival Journals
subjects Animal and plant ecology
Animal, plant and microbial ecology
Autocorrelation
Biological and medical sciences
Coefficients
Correlation coefficients
Correlations
Datasets
Ecological modeling
Fundamental and applied biological sciences. Psychology
General aspects
General aspects. Techniques
Methods and techniques (sampling, tagging, trapping, modelling...)
Modeling
Regression coefficients
Review & Synthesis
Spatial models
Variable coefficients
title Coefficient shifts in geographical ecology: an empirical evaluation of spatial and non-spatial regression
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