Estimating partial observability and nonlinear climate effects on stochastic community dynamics of migratory waterfowl

• Published in: Journal of Animal Ecology
• Main Authors: Almaraz, Pablo, Green, Andy J., Aguilera, Eduardo, Rendón, Miguel A., Bustamante, Javier
• Format: Article in Journal/Newspaper
• Language: English
• Published: Blackwell Publishing 2012
• Subjects: climate fluctuations; community dynamics; data augmentation; Doñana; Hierarchical Bayes; measurement error; missing data; multivariate state-space model; North Atlantic Oscillation; population dynamics; North Atlantic; North Atlantic oscillation
• Online Access: http://hdl.handle.net/10261/55360; https://doi.org/10.1111/j.1365-2656.2012.01972.x

1. Understanding the impact of environmental variability on migrating species requires the esti- mation of sequential abiotic effects in different geographic areas across the life cycle. For instance, waterfowl (ducks, geese and swans) usually breed widely dispersed throughout their breeding range and gather in large numbers in their wintering headquarters, but there is a lack of knowledge on the effects of the sequential environmental conditions experienced by migrating birds on the long-term community dynamics at their wintering sites. 2. Here, we analyse multidecadal time-series data of 10 waterfowl species wintering in the Guadal- quivir Marshes (SW Spain), the single most important wintering site for waterfowl breeding in Europe. We use a multivariate state-space approach to estimate the effects of biotic interactions, local environmental forcing during winter and large-scale climate during breeding and migration on wintering multispecies abundance fluctuations, while accounting for partial observability (observation error and missing data) in both population and environmental data. 3. The joint effect of local weather and large-scale climate explained 31Æ6% of variance at the com- munity level, while the variability explained by interspecific interactions was negligible (<5%). In general, abiotic conditions during winter prevailed over conditions experienced during breeding and migration. Across species, a pervasive and coherent nonlinear signal of environmental vari- ability on population dynamics suggests weaker forcing at extreme values of abiotic variables. 4. Modelling missing observations through data augmentation increased the estimated magnitude of environmental forcing by an average 30Æ1% and reduced the impact of stochasticity by 39Æ3% when accounting for observation error. Interestingly however, the impact of environmental forcing on community dynamics was underestimated by an average 15Æ3% and environmental stochastici- ty overestimated by 14Æ1% when ignoring both observation error and data ...