Predation and spatial connectivity interact to shape ecosystem resilience to an ongoing regime shift.

Ecosystem regime shifts can have severe ecological and economic consequences, making it a top priority to understand how to make systems more resilient. Theory predicts that spatial connectivity and the local environment interact to shape resilience, but empirical studies are scarce. Here, we use >7000 fish samplings from the Baltic Sea coast to test this prediction in an ongoing, spatially propagating shift in dominance from predatory fish to an opportunistic mesopredator, with cascading effects throughout the food web. After controlling for the influence of other drivers (including increasing mesopredator densities), we find that predatory fish habitat connectivity increases resilience to the shift, but only when densities of fish-eating top predators (seals, cormorants) are low. Resilience also increases with temperature, likely through boosted predatory fish growth and recruitment. These findings confirm theoretical predictions that spatial connectivity and the local environment can together shape resilience to regime shifts.

A spatial regime shift from predator to prey dominance in a large coastal ecosystem.

Regime shifts in ecosystem structure and processes are typically studied from a temporal perspective. Yet, theory predicts that in large ecosystems with environmental gradients, shifts should start locally and gradually spread through space. Here we empirically document a spatially propagating shift in the trophic structure of a large aquatic ecosystem, from dominance of large predatory fish (perch, pike) to the small prey fish, the three-spined stickleback. Fish surveys in 486 shallow bays along the 1200 km western Baltic Sea coast during 1979-2017 show that the shift started in wave-exposed archipelago areas near the open sea, but gradually spread towards the wave-sheltered mainland coast. Ecosystem surveys in 32 bays in 2014 show that stickleback predation on juvenile predators (predator-prey reversal) generates a feedback mechanism that appears to reinforce the shift. In summary, managers must account for spatial heterogeneity and dispersal to better predict, detect and confront regime shifts within large ecosystems.

Predicting the effects of eutrophication mitigation on predatory fish biomass and the value of recreational fisheries.

Improving water clarity is a core objective for eutrophication management in the Baltic Sea, but may influence fisheries via effects on fish habitat suitability. We apply an ensemble of species distribution models coupled with habitat productivity functions and willingness-to-pay estimates to assess these effects for two coastal predatory fish species, European perch (Perca fluviatilis) and pikeperch (Sander lucioperca). The models predicted a 37% increase in perch and 59% decrease in pikeperch biomass if reaching the reference level for water clarity in the Baltic Sea Action Plan. Reaching the target level was predicted to increase perch biomass by 13%. However, the associated economic gain for the recreational fisheries sector was countervailed by an 18% pikeperch reduction. Still, a net benefit was predicted since there are six times more fishing days for perch than pikeperch. We exemplify how ecological modelling can be combined with economic analyses to map and evaluate management alternatives.

Recreational boating degrades vegetation important for fish recruitment.

Recreational boating increases globally and associated moorings are often placed in vegetated habitats important for fish recruitment. Meanwhile, assessments of the effects of boating on vegetation, and potential effects on associated fish assemblages are rare. Here, we analysed (i) the effect of small-boat marinas on vegetation structure, and (ii) juvenile fish abundance in relation to vegetation cover in shallow wave-sheltered coastal inlets. We found marinas to have lower vegetation cover and height, and a different species composition, compared to control inlets. This effect became stronger with increasing berth density. Moreover, there was a clear positive relationship between vegetation cover and fish abundance. We conclude that recreational boating and related moorings are associated with reduced cover of aquatic vegetation constituting important habitats for juvenile fish. We therefore recommend that coastal constructions and associated boating should be allocated to more disturbance tolerant environments (e.g. naturally wave-exposed shores), thereby minimizing negative environmental impacts.

Outstanding Challenges in the Transferability of Ecological Models.

Predictive models are central to many scientific disciplines and vital for informing management in a rapidly changing world. However, limited understanding of the accuracy and precision of models transferred to novel conditions (their 'transferability') undermines confidence in their predictions. Here, 50 experts identified priority knowledge gaps which, if filled, will most improve model transfers. These are summarized into six technical and six fundamental challenges, which underlie the combined need to intensify research on the determinants of ecological predictability, including species traits and data quality, and develop best practices for transferring models. Of high importance is the identification of a widely applicable set of transferability metrics, with appropriate tools to quantify the sources and impacts of prediction uncertainty under novel conditions.

Size matters: relationships between body size and body mass of common coastal, aquatic invertebrates in the Baltic Sea.

BACKGROUND: Organism biomass is one of the most important variables in ecological studies, making biomass estimations one of the most common laboratory tasks. Biomass of small macroinvertebrates is usually estimated as dry mass or ash-free dry mass (hereafter 'DM' vs. 'AFDM') per sample; a laborious and time consuming process, that often can be speeded up using easily measured and reliable proxy variables like body size or wet (fresh) mass. Another common way of estimating AFDM (one of the most accurate but also time-consuming estimates of biologically active tissue mass) is the use of AFDM/DM ratios as conversion factors. So far, however, these ratios typically ignore the possibility that the relative mass of biologically active vs. non-active support tissue (e.g., protective exoskeleton or shell)-and therefore, also AFDM/DM ratios-may change with body size, as previously shown for taxa like spiders, vertebrates and trees. METHODS: We collected aquatic, epibenthic macroinvertebrates (>1 mm) in 32 shallow bays along a 360 km stretch of the Swedish coast along the Baltic Sea; one of the largest brackish water bodies on Earth. We then estimated statistical relationships between the body size (length or height in mm), body dry mass and ash-free dry mass for 14 of the most common taxa; five gastropods, three bivalves, three crustaceans and three insect larvae. Finally, we statistically estimated the potential influence of body size on the AFDM/DM ratio per taxon. RESULTS: For most taxa, non-linear regression models describing the power relationship between body size and (i) DM and (ii) AFDM fit the data well (as indicated by low SE and high R2). Moreover, for more than half of the taxa studied (including the vast majority of the shelled molluscs), body size had a negative influence on organism AFDM/DM ratios. DISCUSSION: The good fit of the modelled power relationships suggests that the constants reported here can be used to quickly estimate organism dry- and ash-free dry mass based on body size, thereby freeing up considerable work resources. However, the considerable differences in constants between taxa emphasize the need for taxon-specific relationships, and the potential dangers associated with ignoring body size. The negative influence of body size on the AFDM/DM ratio found in a majority of the molluscs could be caused by increasingly thicker shells with organism age, and/or spawning-induced loss of biologically active tissue in adults. Consequently, future studies utilizing AFDM/DM (and presumably also AFDM/wet mass) ratios should carefully assess the potential influence of body size to ensure more reliable estimates of organism body mass.

Shoreline development and degradation of coastal fish reproduction habitats.

Coastal development has severely affected habitats and biodiversity during the last century, but quantitative estimates of the impacts are usually lacking. We utilize predictive habitat modeling and mapping of human pressures to estimate the cumulative long-term effects of coastal development in relation to fish habitats. Based on aerial photographs since the 1960s, shoreline development rates were estimated in the Stockholm archipelago in the Baltic Sea. By combining shoreline development rates with spatial predictions of fish reproduction habitats, we estimated annual habitat degradation rates for three of the most common coastal fish species, northern pike (Esox lucius), Eurasian perch (Perca fluviatilis) and roach (Rutilus rutilus). The results showed that shoreline constructions were concentrated to the reproduction habitats of these species. The estimated degradation rates, where a degraded habitat was defined as having ≥3 constructions per 100 m shoreline, were on average 0.5 % of available habitats per year and about 1 % in areas close to larger population centers. Approximately 40 % of available habitats were already degraded in 2005. These results provide an example of how many small construction projects over time may have a vast impact on coastal fish populations.

Testing the potential for predictive modeling and mapping and extending its use as a tool for evaluating management scenarios and economic valuation in the Baltic Sea (PREHAB).

We evaluated performance of species distribution models for predictive mapping, and how models can be used to integrate human pressures into ecological and economic assessments. A selection of 77 biological variables (species, groups of species, and measures of biodiversity) across the Baltic Sea were modeled. Differences among methods, areas, predictor, and response variables were evaluated. Several methods successfully predicted abundance and occurrence of vegetation, invertebrates, fish, and functional aspects of biodiversity. Depth and substrate were among the most important predictors. Models incorporating water clarity were used to predict increasing cover of the brown alga bladderwrack Fucus vesiculosus and increasing reproduction area of perch Perca fluviatilis, but decreasing reproduction areas for pikeperch Sander lucioperca following successful implementation of the Baltic Sea Action Plan. Despite variability in estimated non-market benefits among countries, such changes were highly valued by citizens in the three Baltic countries investigated. We conclude that predictive models are powerful and useful tools for science-based management of the Baltic Sea.