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Europe's freshwater biodiversity under climate change: distribution shifts and conservation needs
(2014)
Aim
To assess the future climatic suitability of European catchments for freshwater species and the future utility of the current network of protected areas.
Location
Europe.
Methods
Using recently updated catchment-scale species data and climate projections from multiple climate models, we assessed the climate change threat by the 2050s for 1648 European freshwater plants, fishes, molluscs, odonates, amphibians, crayfish and turtles for two dispersal scenarios and identified hotspots of change at three spatial scales: major river basins, countries and freshwater ecoregions. We considered both common species and the often overlooked rare species. To set our findings within the context of current and future conservation networks, we evaluated the coverage of freshwater biodiversity by Europe's protected area network.
Results
Six per cent of common and 77% of rare species are predicted to lose more than 90% of their current range. Eight fish species and nine mollusc species are predicted to experience 100% range loss under climate change. As the most species-rich group, molluscs are particularly vulnerable due to the high proportion of rare species and their relatively limited ability to disperse. Furthermore, around 50% of molluscs and fish species will have no protected area coverage given their projected distributions.
Main conclusions
We identified the species most at threat due to projected changes in both catchment suitability and representation within the European protected area network. Our findings suggest an urgent need for freshwater management plans to facilitate adaptation to climate change.
The conservation of freshwater ecosystems has lagged behind that of marine and terrestrial ecosystems and often requires the integration of large-scale approaches and transboundary considerations. This study aims to set the foundations of a spatial conservation strategy by identifying the most important catchments for the conservation of freshwater biodiversity in Europe.
Using data on 1296 species of fish, mollusc, odonate and aquatic plant, and the key biodiversity area criteria (species Red List status, range restriction and uniqueness of species assemblages), we identified a network of Critical Catchments for the conservation of freshwater biodiversity. Applying spatial prioritisation, we show how the prioritised network differs from the ideal case of protecting all Critical Catchments and how it changes when protected areas are included, and we also identify gaps between the prioritised network and existing protected areas.
Critical Catchments (n = 8423) covered 45% of the area of Europe, with 766 qualifying (‘trigger’) species located primarily in southern Europe. The prioritised network, limited to 17% of the area of Europe, comprised 3492 catchments mostly in southern and eastern Europe and species targets were met for at least 96% of the trigger species.
We found the majority of Critical Catchments to be inadequately covered by protected areas. However, our prioritised network presents a possible solution to augment protected areas to meet policy targets while also achieving good species coverage.
Policy implications. While Critical Catchments cover almost half of Europe, priority catchments are mostly in southern and eastern Europe where the current level of protection is not sufficient. This study presents a foundation for a Europe-wide systematic conservation plan to ensure the persistence of freshwater biodiversity. Our study provides a powerful new tool for optimising investment on the conservation of freshwater biodiversity and for meeting targets set forth in international biodiversity policies, conventions and strategies.
Climate change is expected to exacerbate the current threats to freshwater ecosystems, yet multifaceted studies on the
potential impacts of climate change on freshwater biodiversity at scales that inform management planning are lacking. The aim of this study was to fill this void through the development of a novel framework for assessing climate
change vulnerability tailored to freshwater ecosystems. The three dimensions of climate change vulnerability are as
follows: (i) exposure to climate change, (ii) sensitivity to altered environmental conditions and (iii) resilience potential.
Our vulnerability framework includes 1685 freshwater species of plants, fishes, molluscs, odonates, amphibians, crayfish and turtles alongside key features within and between catchments, such as topography and connectivity. Several
methodologies were used to combine these dimensions across a variety of future climate change models and scenarios. The resulting indices were overlaid to assess the vulnerability of European freshwater ecosystems at the catchment scale (18 783 catchments). The Balkan Lakes Ohrid and Prespa and Mediterranean islands emerge as most
vulnerable to climate change. For the 2030s, we showed a consensus among the applied methods whereby up to 573
lake and river catchments are highly vulnerable to climate change. The anthropogenic disruption of hydrological
habitat connectivity by dams is the major factor reducing climate change resilience. A gap analysis demonstrated that
the current European protected area network covers <25% of the most vulnerable catchments. Practical steps need to
be taken to ensure the persistence of freshwater biodiversity under climate change. Priority should be placed on
enhancing stakeholder cooperation at the major basin scale towards preventing further degradation of freshwater
ecosystems and maintaining connectivity among catchments. The catchments identified as most vulnerable to climate
change provide preliminary targets for development of climate change conservation management and mitigation
strategies.
The distribution of a species along a thermal gradient is commonly approximated by a unimodal response curve, with a characteristic single optimum near the tempera‐ture where a species is most likely to be found, and a decreasing probability of occur‐rence away from the optimum. We aimed at identifying thermal response curves (TRCs) of European freshwater species and evaluating the potential impact of climate warming across species, taxonomic groups, and latitude. We first applied generalized additive models using catchment‐scale global data on distribution ranges of 577 freshwater species native to Europe and four different temperature variables (the current annual mean air/water temperature and the maximum air/water temperature of the warmest month) to describe species TRCs. We then classified TRCs into one of eight curve types and identified spatial patterns in thermal responses. Finally, we in‐tegrated empirical TRCs and the projected geographic distribution of climate warm‐ing to evaluate the effect of rising temperatures on species’ distributions. For the different temperature variables, 390–463 of 577 species (67.6%–80.2%) were char‐acterized by a unimodal TRC. The number of species with a unimodal TRC decreased from central toward northern and southern Europe. Warming tolerance (WT = maxi‐mum temperature of occurrence—preferred temperature) was higher at higher lati‐tudes. Preferred temperature of many species is already exceeded. Rising temperatures will affect most Mediterranean species. We demonstrated that fresh‐water species’ occurrence probabilities are most frequently unimodal. The impact of the global climate warming on species distributions is species and latitude depend‐ent. Among the studied taxonomic groups, rising temperatures will be most detri‐mental to fish. Our findings support the efforts of catchment‐based freshwater management and conservation in the face of global warming.
Niche-based species distribution models (SDMs) have become an essential tool in conservation and restoration planning. Given the current threats to freshwater biodiversity, it is of fundamental importance to address scale effects on the performance of niche-based SDMs of freshwater species’ distributions. The scale effects are addressed here in the context of hierarchical catchment ordering, considered as counterpart to coarsening grain-size by increasing grid-cell size. We combine fish occurrence data from the Danube River Basin, the hierarchical catchment ordering and multiple environmental factors representing topographic, climatic and anthropogenic effects to model fish occurrence probability across multiple scales. We focus on 1st to 5th order catchments. The spatial scale (hierarchical catchment order) only marginally influences the mean performance of SDMs, however the uncertainty of the estimates increases with scale. Key predictors and their relative importance are scale and species dependent. Our findings have useful implications for choosing proper species dependent spatial scales for river rehabilitation measures, and for conservation planning in areas where fine grain species data are unavailable.
Model-derived relationships between chlorophyll a (Chl-a) and nutrients and temperature have fundamental implications for understanding complex interactions among water quality measures used for lake classification, yet accuracy comparisons of different approaches are scarce. Here, we (1) compared Chl-a model performances across linear and nonlinear statistical approaches; (2) evaluated single and combined effects of nutrients, depth, and temperature as lake surface water temperature (LSWT) or altitude on Chl-a; and (3) investigated the reliability of the best water quality model across 13 lakes from perialpine and central Balkan mountain regions. Chl-a was modelled using in situ water quality data from 157 European lakes; elevation data and LSWT in situ data were complemented by remote sensing measurements. Nonlinear approaches performed better, implying complex relationships between Chl-a and the explanatory variables. Boosted regression trees, as the best performing approach, accommodated interactions among predictor variables. Chl-a–nutrient relationships were characterized by sigmoidal curves, with total phosphorus having the largest explanatory power for our study region. In comparison with LSWT, utilization of altitude, the often-used temperature surrogate, led to different influence directions but similar predictive performances. These results support utilizing altitude in models for Chl-a predictions. Compared to Chl-a observations, Chl-a predictions of the best performing approach for mountain lakes (oligotrophic–eutrophic) led to minor differences in trophic state categorizations. Our findings suggest that both models with LSWT and altitude are appropriate for water quality predictions of lakes in mountain regions and emphasize the importance of incorporating interactions among variables when facing lake management challenges.