RESUMO
Wetland habitats are changing under multiple anthropogenic pressures. Nutrient leakage and pollution modify physico-chemical state of wetlands and affect the ecosystem through bottom-up processes, while alien predators affect the ecosystems in a top-down manner. Boreal wetlands are important breeding areas for several waterbird species, the abundances of which potentially reflect both bottom-up and top-down ecosystem processes. Here, we use long-term national monitoring data gathered from c. 130 waterbird breeding sites in Finland from the 1980s to the 2020s. We hypothesised that the physico-chemical state of the waters and increasing alien predator abundance both play a role in steering the waterbird population trends. We set out to test this hypothesis by relating population changes of 17 waterbird species to changes in water chemistry and to regional alien predator indices while allowing species-specific effects to vary with foraging niche (dabblers, invertivore divers, piscivorous divers, herbivores), nesting site, female mass and habitat (oligotrophic, eutrophic). We found niche and nesting site-specific, habitat-dependent changes in waterbird numbers. While the associations with higher phosphorus levels and browning water were in overall positive at the oligotrophic lakes, the numbers of invertivore and piscivore diving ducks were most strongly negatively associated with higher phosphorus levels and browning water at the eutrophic lakes. Furthermore, increased pH levels benefitted piscivores. Invertivore diving duck species nesting on the wetlands had declined most on sites with high alien predator indices. Large herbivorous species and species preferring oligotrophic lakes seem to be successful. We conclude that the large-scale breeding waterbird decline in Finland is closely connected to both bottom-up and top-down processes, where negative associations are emphasised especially at eutrophic lakes. Niche-, nest site- and habitat-specific management actions are required to conserve declining waterbird populations. Managing wetlands on catchments level together with alien predator control may provide important approaches to future wetland management.
RESUMO
The demography of many European waterbirds is not well understood because most countries have conducted little monitoring and assessment, and coordination among countries on waterbird management has little precedent. Yet intergovernmental treaties now mandate the use of sustainable, adaptive harvest strategies, whose development is challenged by a paucity of demographic information. In this study, we explore how a combination of allometric relationships, fragmentary monitoring and research information, and expert judgment can be used to estimate the parameters of a theta-logistic population model, which in turn can be used in a Markov decision process to derive optimal harvesting strategies. We show how to account for considerable parametric uncertainty, as well as for different management objectives. We illustrate our methodology with a poorly understood population of Taiga Bean Geese (Anser fabalis fabalis), which is a popular game bird in Fennoscandia. Our results for Taiga Bean Geese suggest that they may have demographic rates similar to other, well-studied species of geese, and our model-based predictions of population size are consistent with the limited monitoring information available. Importantly, we found that by using a Markov decision process, a simple scalar population model may be sufficient to guide harvest management of this species, even if its demography is age structured. Finally, we demonstrated how two different management objectives can lead to very different optimal harvesting strategies, and how conflicting objectives may be traded off with each other. This approach will have broad application for European waterbirds by providing preliminary estimates of key demographic parameters, by providing insights into the monitoring and research activities needed to corroborate those estimates, and by producing harvest management strategies that are optimal with respect to the managers' objectives, options, and available demographic information.
