Please use this identifier to cite or link to this item: http://hdl.handle.net/10174/34389

Title: Predicting climatic threats to an endangered freshwater mussel in Europe: The need to account for fish hosts
Authors: da Silva, J.P.
Gonçalves, D.V.
Lopes-Lima, M.
Gama, M.
Miranda, R.
Reis, J.
Filipe, A.F.
Banha, F.
Sousa, R.
Keywords: Spedies Distribution Models
Freshwater mussels
Issue Date: 2022
Citation: da Silva, J. P., Gonçalves, D. V., Lopes-Lima, M., Anastácio, P. M., Banha, F., Frimpong, E., Gama, M., Miranda, R., Reis, J., Filipe, A. F., & Sousa, R. (2022). Predicting climatic threats to an endangered freshwater mussel in Europe: The need to account for fish hosts. Freshwater Biology, 67, 842-856.
Abstract: The freshwater pearl mussel Margaritifera margaritifera has been suffering major population declines in Europe. This endangered species is a host specialist and exclusively requires salmonid species (Salmo trutta and Salmo salar) to complete its life cycle. In theory, obligatory biotic interactions should deserve special conservation attention, because the loss or massive decline of fish hosts may elicit the extirpation of their affiliated species. While many threats disturbing M. margaritifera are similarly affecting salmonids, climate change is particularly alarming, with the potential to significantly change the fish-mussel dynamics. To evaluate the importance of including the occurrence of fish hosts for predicting the distribution of M. margaritifera in Europe, three datasets were used to build species distribution models (SDMs) with a maximum entropy (MaxEnt) approach: (1) environmental variables (ENV); (2) probability of fish hosts occurrence (FH); and (3) environmental variables and probability of fish hosts occurrence (ENV + FH). We identified the environmental variables that better explain M. margaritifera distribution and modelled its current and future distribution under a suite of climate change scenarios. Furthermore, projections were used to evaluate the adequacy of current networks of European protected areas in covering the suitable habitats for M. margaritifera. Results showed that incorporating data about fish hosts into M. margaritifera SDMs avoided the overprediction of geographical projections and, to a minor extent, improved model performance (area under the curve: ENV = 0.851; FH = 0.848; ENV + FH = 0.867). The distribution range of M. margaritifera in Europe is expected to contract in all future timeframes and emission scenarios considered. Forecasts point to large contractions particularly in central and southern Europe and lowland regions. The European network of protected areas fails to protect 69% of the current and 66%–67% of the future predicted M. margaritifera distribution. This study clearly illustrates the importance of including mussel–fish hosts interactions for accurately predicting M. margaritifera's distribution. The response of M. margaritifera to environmental variables highlights its vulnerability to the higher temperatures, particularly in southern Europe. While predictions indicate large contractions in M. margaritifera's distribution as a result of future climate change, the current European network of protected areas fails to safeguard M. margaritifera. This work provides strong evidence for proposing the generalised use of biotic information about hosts in addition to purely environmental variables to model the distribution of freshwater mussels, as well as for other species with obligatory biotic interactions. Building SDMs such as those discussed here can inform political decision-making about the likely scenarios for species occurrence in future decades, the requirements needed for an effective conservation strategy, and the regions where conservation should be a priority.
URI: https://onlinelibrary.wiley.com/doi/10.1111/fwb.13885
http://hdl.handle.net/10174/34389
Type: article
Appears in Collections:MARE-UE - Publicações - Artigos em Revistas Internacionais Com Arbitragem Científica
PAO - Publicações - Artigos em Revistas Internacionais Com Arbitragem Científica

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