Categorical structured additive regression for assessing habitat suitability in the spatial distribution of mussel seed abundance

Environmetrics - Tập 23 Số 1 - Trang 75-84 - 2012
María P. Pata1,2, Thomas Kneib3, Carmen Cadarso‐Suárez4, Vicente Lustres-Pérez1, Eugenio Fernández‐Pulpeiro1
1Department of Zoology and Physical Anthropology, School of Biology, Universidad de Santiago de Compostela, Santiago de Compostela, Spain
2Pyrenean Institute of Ecology, Consejo Superior de Investigaciones Científicas, Zaragoza, Spain
3Department of Mathematics, Carl von Ossietzky University of Oldenburg, Oldenburg, Germany
4Department of Statistics and Operations Research, School of Medicine, Universidad de Santiago de Compostela, Santiago de Compostela, Spain

Tóm tắt

Categorical regression models enable the investigation of regression relationships between a polytomous response and a set of regressor variables. Depending on whether the categories are ordered or nominal, special categorical models such as cumulative and multinomial models have been proposed in the statistical literature. In this paper, we compare various categorical structured additive regression (STAR) models for assessing habitat suitability in the spatial distribution of mussel seed abundance in the Galician coast (northwest Spain). STAR models allow us to include nonlinear effects of continuous covariates on the basis of penalized splines whereas spatial effects can be represented via a Markov random field. Inference is based on a mixed model representation that allows for the simultaneous estimation of regression coefficients and smoothing parameters. Although cumulative models may seem to be the most natural choice in our application because of the ordinal nature of the response, multinomial models provide more detailed information on covariate effects as all effects are allowed to depend on the different categories of mussel seed abundance. The statistical procedures based on STAR models proved very useful in revealing valuable information towards the application of adequate management of this marine resource. Copyright © 2011 John Wiley & Sons, Ltd.

Từ khóa


Tài liệu tham khảo

10.1111/j.1365-2664.2006.01164.x

10.1016/j.ecolmodel.2006.05.023

BelitzC BrezgerA KneibT LangS.2009.BAYESX‐Software for Bayesian inference in structured additive regression models Version 2.0.

BownesS.2005.Habitat segregation in competing species of intertidal mussels in South Africa PhD thesis Rhodes University.

10.1016/j.csda.2004.10.011

10.1177/1471082X0801000303

10.1017/S0025315400014909

10.1007/BF02365909

10.1007/BF02573952

10.1111/1467-9876.00229

10.1007/978-1-4757-3454-6

Fahrmeir L, 2004, Penalized structured additive regression for space–time data: a Bayesian perspective, Statistica Sinica, 14, 731

Fernández‐PulpeiroE Lustres PérezV Brea BermejoE Sestelo PérezM Souto DerungsJ PataMP.2007.Recartografiado y dinámica de poblaciones de especies de invertebrados marinos asociados a substratos rocosos de la Costa da Morte.:320.Informe final. Fundación Arao. Xunta de Galicia Santiago de Compostela.http://fundacionarao.xunta.es/P24_cas.pdf.

10.2307/3236568

10.1016/S0304-3800(00)00354-9

10.1023/A:1009841519580

10.1016/S0304-3800(02)00204-1

10.4319/lo.2003.48.4.1498

Hastie TJ, 1990, Generalized Additive Models

10.1111/j.1541-0420.2005.00392.x

10.1007/s10651-008-0092-x

10.1016/S0304-3800(02)00195-3

Lehmann A, 2002, Regression models for spatial prediction: their role for biodiversity and conservation, Biological Conservation, 11, 2085

10.1016/S0022-0981(00)00290-2

10.2307/1939924

10.1034/j.1600-0587.2002.250508.x

McFadden D, 1973, Frontiers in Econometrics

10.3354/meps206147

10.3354/meps301173

McCullagh P, 1997, Generalized Linear Models

10.1016/S0304-3800(02)00196-5

10.1086/284741

10.1016/j.ecolmodel.2006.05.015

Nicholls AO, 1989, How to make biological survey go further with generalized linear models, Biological Conservation, 50, 51, 10.1016/0006-3207(89)90005-0

Pata MP, 2010, Modelling spatial patterns of distribution and abundance of mussel seed using structured additive regression models, SORT, 34, 67

Pescadegalicia.2010.Plataforma tecnológica de Pesca. Consellería do Mar. Xunta de Galicia.http://www.pescadegalicia.com/default.htm(lastaccess 15‐11‐2010).

10.1111/j.1365-2109.2007.01757.x

10.1201/9780203492024

10.1007/BF00390380

10.1017/S0025315405012506

10.1016/0022-0981(78)90139-9

10.1016/S0022-0981(00)00181-7

10.1201/9781420010404

10.2307/3236170

10.2307/3237182