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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Autores principales: Bini, L.M., Diniz-Filho, J.A.F., Rangel, T.F.L.V.B., Akre, T.S.B., Albaladejo, R.G., Albuquerque, F.S., Aparicio, A., Araújo, M.B., Baselga, A., Beck, J., Bellocq, M.I., Böhning-Gaese, K., Borges, P.A.V., Castro-Parga, I., Chey, V.K., Chown, S.L., De Marco Jr., P., Dobkin, D.S., Ferrer-Castán, D., Field, R., Filloy, J., Fleishman, E., Gómez, J.F., Hortal, J., Iverson, J.B., Kerr, J.T., Kissling, W.D., Kitching, I.J., León-Cortés, J.L., Lobo, J.M., Montoya, D., Morales-Castilla, I., Moreno, J.C., Oberdorff, T., Olalla-Tárraga, M.A., Pausas, J.G., Qian, H., Rahbek, C., Rodríguez, M.A., Rueda, M., Ruggiero, A., Sackmann, P., Sanders, N.J., Terribile, L.C., Vetaas, O.R., Hawkins, B.A.
Formato: JOUR
Materias:
abundance
body size
data set
least squares method
macroecology
range size
regression analysis
species richness
Acceso en línea:http://hdl.handle.net/20.500.12110/paper_09067590_v32_n2_p193_Bini
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Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires
id todo:paper_09067590_v32_n2_p193_Bini
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spelling todo:paper_09067590_v32_n2_p193_Bini2023-10-03T15:44:33Z Coefficient shifts in geographical ecology: An empirical evaluation of spatial and non-spatial regression Bini, L.M. Diniz-Filho, J.A.F. Rangel, T.F.L.V.B. Akre, T.S.B. Albaladejo, R.G. Albuquerque, F.S. Aparicio, A. Araújo, M.B. Baselga, A. Beck, J. Bellocq, M.I. Böhning-Gaese, K. Borges, P.A.V. Castro-Parga, I. Chey, V.K. Chown, S.L. De Marco Jr., P. Dobkin, D.S. Ferrer-Castán, D. Field, R. Filloy, J. Fleishman, E. Gómez, J.F. Hortal, J. Iverson, J.B. Kerr, J.T. Kissling, W.D. Kitching, I.J. León-Cortés, J.L. Lobo, J.M. Montoya, D. Morales-Castilla, I. Moreno, J.C. Oberdorff, T. Olalla-Tárraga, M.A. Pausas, J.G. Qian, H. Rahbek, C. Rodríguez, M.A. Rueda, M. Ruggiero, A. Sackmann, P. Sanders, N.J. Terribile, L.C. Vetaas, O.R. Hawkins, B.A. abundance body size data set least squares method macroecology range size regression analysis species richness 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. © 2009 Ecography. Fil:Bellocq, M.I. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Filloy, J. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Sackmann, P. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. JOUR info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_09067590_v32_n2_p193_Bini
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-134
collection Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic abundance
body size
data set
least squares method
macroecology
range size
regression analysis
species richness
spellingShingle abundance
body size
data set
least squares method
macroecology
range size
regression analysis
species richness
Bini, L.M.
Diniz-Filho, J.A.F.
Rangel, T.F.L.V.B.
Akre, T.S.B.
Albaladejo, R.G.
Albuquerque, F.S.
Aparicio, A.
Araújo, M.B.
Baselga, A.
Beck, J.
Bellocq, M.I.
Böhning-Gaese, K.
Borges, P.A.V.
Castro-Parga, I.
Chey, V.K.
Chown, S.L.
De Marco Jr., P.
Dobkin, D.S.
Ferrer-Castán, D.
Field, R.
Filloy, J.
Fleishman, E.
Gómez, J.F.
Hortal, J.
Iverson, J.B.
Kerr, J.T.
Kissling, W.D.
Kitching, I.J.
León-Cortés, J.L.
Lobo, J.M.
Montoya, D.
Morales-Castilla, I.
Moreno, J.C.
Oberdorff, T.
Olalla-Tárraga, M.A.
Pausas, J.G.
Qian, H.
Rahbek, C.
Rodríguez, M.A.
Rueda, M.
Ruggiero, A.
Sackmann, P.
Sanders, N.J.
Terribile, L.C.
Vetaas, O.R.
Hawkins, B.A.
Coefficient shifts in geographical ecology: An empirical evaluation of spatial and non-spatial regression
topic_facet abundance
body size
data set
least squares method
macroecology
range size
regression analysis
species richness
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. © 2009 Ecography.
format JOUR
author Bini, L.M.
Diniz-Filho, J.A.F.
Rangel, T.F.L.V.B.
Akre, T.S.B.
Albaladejo, R.G.
Albuquerque, F.S.
Aparicio, A.
Araújo, M.B.
Baselga, A.
Beck, J.
Bellocq, M.I.
Böhning-Gaese, K.
Borges, P.A.V.
Castro-Parga, I.
Chey, V.K.
Chown, S.L.
De Marco Jr., P.
Dobkin, D.S.
Ferrer-Castán, D.
Field, R.
Filloy, J.
Fleishman, E.
Gómez, J.F.
Hortal, J.
Iverson, J.B.
Kerr, J.T.
Kissling, W.D.
Kitching, I.J.
León-Cortés, J.L.
Lobo, J.M.
Montoya, D.
Morales-Castilla, I.
Moreno, J.C.
Oberdorff, T.
Olalla-Tárraga, M.A.
Pausas, J.G.
Qian, H.
Rahbek, C.
Rodríguez, M.A.
Rueda, M.
Ruggiero, A.
Sackmann, P.
Sanders, N.J.
Terribile, L.C.
Vetaas, O.R.
Hawkins, B.A.
author_facet Bini, L.M.
Diniz-Filho, J.A.F.
Rangel, T.F.L.V.B.
Akre, T.S.B.
Albaladejo, R.G.
Albuquerque, F.S.
Aparicio, A.
Araújo, M.B.
Baselga, A.
Beck, J.
Bellocq, M.I.
Böhning-Gaese, K.
Borges, P.A.V.
Castro-Parga, I.
Chey, V.K.
Chown, S.L.
De Marco Jr., P.
Dobkin, D.S.
Ferrer-Castán, D.
Field, R.
Filloy, J.
Fleishman, E.
Gómez, J.F.
Hortal, J.
Iverson, J.B.
Kerr, J.T.
Kissling, W.D.
Kitching, I.J.
León-Cortés, J.L.
Lobo, J.M.
Montoya, D.
Morales-Castilla, I.
Moreno, J.C.
Oberdorff, T.
Olalla-Tárraga, M.A.
Pausas, J.G.
Qian, H.
Rahbek, C.
Rodríguez, M.A.
Rueda, M.
Ruggiero, A.
Sackmann, P.
Sanders, N.J.
Terribile, L.C.
Vetaas, O.R.
Hawkins, B.A.
author_sort Bini, L.M.
title Coefficient shifts in geographical ecology: An empirical evaluation of spatial and non-spatial regression
title_short Coefficient shifts in geographical ecology: An empirical evaluation of spatial and non-spatial regression
title_full Coefficient shifts in geographical ecology: An empirical evaluation of spatial and non-spatial regression
title_fullStr Coefficient shifts in geographical ecology: An empirical evaluation of spatial and non-spatial regression
title_full_unstemmed Coefficient shifts in geographical ecology: An empirical evaluation of spatial and non-spatial regression
title_sort coefficient shifts in geographical ecology: an empirical evaluation of spatial and non-spatial regression
url http://hdl.handle.net/20.500.12110/paper_09067590_v32_n2_p193_Bini
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