How do waterbirds respond to climate change? A study at a key wintering site in Europe
- Published
- Accepted
- Subject Areas
- Climate Change Biology, Ecology, Ecosystem Science, Freshwater Biology, Zoology
- Keywords
- winter range shift, ice coverage sensitivity, Greater Scaup, Common Pochard, Tufted Duck, Eurasian Coot, Smew, important bird areas, behavior, Baltic Sea
- Copyright
- © 2017 Marchowski et al.
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
- Cite this article
- 2017. How do waterbirds respond to climate change? A study at a key wintering site in Europe. PeerJ Preprints 5:e2652v3 https://doi.org/10.7287/peerj.preprints.2652v3
Abstract
Many species of birds react to climate change, for example, by wintering in areas closer to their breeding areas. We investigated the responses of two different functional groups of waterbirds to factors associated with climate change. The Odra River Estuary (SW Baltic Sea) is of key importance to wintering waterfowl. The most numerous birds here belong to two ecological groups: benthic feeders and fish feeders. We showed that numbers of all benthivorous waterbirds were negatively correlated with the presence of ice, but failed to find such a relationship for piscivores. We anticipated that, with ongoing global warming, the significance of this area would increase for benthic feeders but decrease for fish feeders: our results bore this out. The maximum range of ice cover in the Baltic Sea has a weak and negative effect on both groups of birds. Five of the seven target species are benthivores (Greater Scaup Aythya marila, Tufted Duck A. fuligula, Common Pochard A. ferina, Common Goldeneye Bucephala clangula and Eurasian Coot Fulica atra), while the other two are piscivores (Smew Mergellus albellus and Goosander Mergus merganser). Local changes at the level of particular species vary for different reasons. The local decline of Common Pochard may be a reflection of the species’ global decline. Climate change may be responsible for some of the local changes in the study area, namely, the significance of the area has increased for Greater Scaup and Tufted Duck but declined for Smew.
Author Comment
This is a preprint submission to PeerJ Preprints.
Supplemental Information
Raw data
A - date of count. B - season of count. C - species. D - month of count. E - number of days with 100% ice cover 15 days prior to count. F - mean daily temp. 15 days prior to count. G - mean max. temp. 15 days prior to count. H - mean min.temp.15 days prior to count. I - feeding group: B-benthivorous, P-piscivorous. J - count method: A - aerial, L - terrrestrial. K - maximum ice cover in the Baltic in thousand km². L - [=(Mx/Nx)*100]. M - Count results. N - Size of population in a given season.
Ranking of generalized linear mixed models showing the influence of ice cover, maximum ice extent [km2] in the Baltic Sea (max ice) and season on the percentages of the population of the target species in the Odra River Estuary
The models were ranked using the Akaike information criterion (AIC). ΔAIC represents the difference between each model and the best-fit model. wi – Akaike weight (indicating model probabilities); df, – degrees of freedom. The terms in the models are represented by numbers: 1 –feed, 2 – ice cover, 3 – max ice, 4 – season, 5 – ice cover*feed, 6 – max ice*feed, 7 – season*feed.
Results of generalized linear mixed models showing the influence of ice cover, maximum ice extent [km2] in the Baltic Sea (max ice) and season on the percentages of the population of the target species in the Odra River Estuary
The parameters show the interaction between season and species, ice cover and species, max ice and species. The interaction parameters species*season, species*ice cover, species*max ice were used to predict the values presented in Figures 1-3.
Trend of biogeographic population (2) and impact of covariates (3-5) on the dependent variable – the ratio of the percentage of the numbers of a given species in the study area to the estimated total biogeographic population in a given year
(1) Target species, (2) trend of biogeographic population after Nagy et al. 2014; (3) direction of population index change in the ORE; (4) impact of ice cover in the ORE on the dependent variable; (5) impact of ice cover in the whole Baltic on the dependent variable.