Perceived multiple stressor effects depend on sample size and stressor gradient length.

Multiple stressors are continuously deteriorating surface waters worldwide, posing many challenges for their conservation and restoration. Combined effect types of multiple stressors range from single-stressor dominance to complex interactions. Identifying prevalent combined effect types is critical for environmental management, as it helps to prioritise key stressors for mitigation. However, it remains unclear whether observed single and combined stressor effects reflect true ecological processes unbiased by sample size and length of stressor gradients. Therefore, we examined the role of sample size and stressor gradient lengths in 158 paired-stressor response cases with over 120,000 samples from rivers, lakes, transitional and marine ecosystems around the world. For each case, we split the overall stressor gradient into two partial gradients (lower and upper) and investigated associated changes in single and combined stressor effects. Sample size influenced the identified combined effect types, and stressor interactions were less likely for cases with fewer samples. After splitting gradients, 40 % of cases showed a change in combined effect type, 30 % no change, and 31 % showed a loss in stressor effects. These findings suggest that identified combined effect types may often be statistical artefacts rather than representing ecological processes. In 58 % of cases, we observed changes in stressor effect directions after the gradient split, suggesting unimodal stressor effects. In general, such non-linear responses were more pronounced for organisms at higher trophic levels. We conclude that observed multiple stressor effects are not solely determined by ecological processes, but also strongly depend on sampling design. Observed effects are likely to change when sample size and/or gradient length are modified. Our study highlights the need for improved monitoring programmes with sufficient sample size and stressor gradient coverage. Our findings emphasize the importance of adaptive management, as stress reduction measures or further ecosystem degradation may change multiple stressor-effect relationships, which will then require associated changes in management strategies.

Climate change induced range shifts in seaweeds distributions in Europe.

There are evidences of how climate change is affecting seaweeds distribution and the ecosystems services they provide. Therefore, it is necessary to consider these impacts when managing marine areas. One of the most applied tools in recent years to deal with this are species distribution models, however there are still some challenges to solve, such as the inclusion of hydrodynamic predictors and the application of effective, transferable and user-oriented methodologies. Five species (Saccorhiza polyschides, Gelidium spinosum, Sargassum muticum, Pelvetia canaliculata and Cystoseira baccata) in Europe and 15 variables were considered. Nine of them were projected to the RCPs 4.5 and 8.5 for the mid-term (2040-2069) and the long term (2070-2099). Algorithms for each species were applied to generate models that were assessed by comparison of probabilities and observations (area under the curve, true skill statistics, Boyce index, sensitivity, correct classification rate), niches overlap (Schoener's D, Hellinger's I), geographical similarity (interquartile range) and ecological realism. Models built demonstrated very good predictive accuracy and sensitivity, without overfitting risk. A medium overlap in the historical and RCPs environmental conditions were obtained, therefore the models can be considered transferable and results accurate because only some isolated points were detected as outliers, corresponding to low probabilities. The areas of S. polyschides and G. spinosum have been identified to be dramatically reduced, meanwhile S. muticum and C. baccata were predicted to expand their range. P. canaliculata was expected to keep its sites of presence but with a decrease in its probability of occurrence. For all species it was remarkable the importance of hydrodynamic variables and parameters representing extreme conditions. Spatially predictions of the potential species and areas at risk are decisive for defining management strategies and resource allocation. The performance and usefulness of the approach applied in this study have been demonstrated for algae with different ecological requirements (from upper littoral to subtidal) and distributional patterns (native and invasive), therefore results can be used by marine planners with different goals: marine protected areas designation, monitoring efforts guiding, invasions risk assessment or aquaculture facilities zonation.