Modelling habitat selection at multiple scales with multivariate geostatistics: an application to seabirds in open sea

• Published in: Oikos
• Main Authors: Bellier, Edwige, Certain, Grégoire, Planque, Benjamin, Monestiez, Pascal, Bretagnolle, Vincent
• Other Authors: Centre d'Études Biologiques de Chizé (CEBC), Centre National de la Recherche Scientifique (CNRS)
• Format: Article in Journal/Newspaper
• Language: English
• Published: HAL CCSD 2010
• Subjects: URIA AALGE; ALCIDAE; SPATIAL DISTRIBUTION; SALINITY; CHLOROPHYLL; MIXED LAYER DEPTH; ECOSYSTEME MARIN; OISEAU MARIN; [SDE]Environmental Sciences; Uria aalge; uria
• Online Access: https://hal.science/hal-00527409; https://doi.org/10.1111/j.1600-0706.2009.17808.x

International audience Modelling habitat of species necessitates robust identification of relevant environmental variables linked to species distribution. To achieve this, we connect hierarchical patch theory and habitat modelling at multiple scales. We suggest discriminating between ‘circumstancial variables' and ‘process variables' on the basis of temporal evolution of the spatial links between species distribution and their environment at different scales. ‘Process variables' are informative of the ecological processes driving the distribution of organisms at multiple scales. By opposition, ‘circumstantial variable' provide little insight because their relationship with animal spatial distribution is subject to great variations through time. As a real case study, we investigate the relationships between auk distribution (mainly Uria aalge) and oceanographic landscapes over two scales (i.e. large ~ 200 km and medium ~ 50 km) during the wintering season in the Bay of Biscay. Surface salinity, mixed layer depth and chlorophyll a are identified as ‘process variables' as they are invariably correlated with the spatial distribution of auks, whereas bottom temperature can be viewed as a ‘circumstantial variable' since the correlation is non-constant through time at large scale. The process variables at large scale are used to model the potential habitat of auks in the Bay of Biscay during the wintering season. At medium scale, only the chlorophyll a is identified as ‘process variable' and used to model preferential habitat of wintering auks in the Bay of Biscay. The analytical approach proposed here (i.e. multivariate factorial kriging in a temporal context) is an effective framework to model the potential and preferential habitat of a species and can be related to the ecological niche concept and by focusing explicitly on scale dependence, the distinction between the variables that can be used as niche descriptors into species distribution models. Then our method lead to the identification of variables that ...