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|Temporal variability of ecological niches: a study on intertidal macrobenthic fauna|Kraan, C.; Aarts, G.; Dormann, C.F.; Piersma, T. (2013). Temporal variability of ecological niches: a study on intertidal macrobenthic fauna. Oikos (Kbh.) 122(5): 754-760. dx.doi.org/10.1111/j.1600-0706.2012.20418.x
In: Oikos (København). Munksgaard: Copenhagen. ISSN 0030-1299; e-ISSN 1600-0706, meer
|Auteurs|| || Top |
- Kraan, C.
- Aarts, G.
- Dormann, C.F.
- Piersma, T., meer
The determination of temporal niche dynamics under field conditions is an important component of a species' ecology. Recent developments in niche mapping, and the possibility to account for spatial autocorrelation in species distributions, hold promise for the statistical approach explored here. Using species counts from a landscape-scale benthic monitoring programme in the western Dutch Wadden Sea during 19972005 in combination with sediment characteristics and tidal height as explanatory variables, we statistically derive realised niches for two bivalves, two crustaceans and three polychaetes, encompassing predators, suspension and bottom feeding functional groups. Unsurprisingly, realized niches varied considerably between species. Intraspecific temporal variation was assessed as overlap between the year-specific niche and the overall mean niche, and this analysis revealed considerable variation between years. The main functional groups represented by these species showed idiosyncratic and wide variability through the study period. There were no strong associations between niche characteristics and mean abundance or body size. Our assessment of intraspecific niche variability has ramifications for species distribution models in general and offers advances from previous methods. 1) By assessing species' realized niches in the multivariate environmental space, analyses are independent from the relative availability of particular environments. Predicted realized niches present differences between years, rather than annual differences in environmental conditions. 2) Using spatially explicit models to predict species habitat preferences provide more precise and unbiased estimates of speciesenvironment relationships. 3) Current niche models assume constant niches, whereas we illustrate how much these can vary over only a few generations. This emphasizes the potentially limited scope of global change studies with forecasts based on single-time species distribution snapshots.