Salinity is an important biodiversity regulating factor in the Baltic Sea, forming a physiological dispersal barrier for species. The salinity in the Baltic Sea has been predicted to decline due to increased precipitation and fewer saline water inflows from the ocean. This causes stress to species already living on the edge of their tolerances and can alter species compositions and interactions in ecosystems. Calanoid copepod resting eggs, originating from a known egg bank on the seabed in the western Gulf of Finland, were incubated in the laboratory. We monitored the hatching of the calanoid copepods Acartia sp. and Eurytemora affinis, as well as the survival to maturity of hatched Eurytemora affinis nauplii in salinities ranging from 0 to 25. Further, we also investigated salinity-related effects on body size and egg production. Based on the results of our generalized linear mixed model, peak hatching occurred within the salinity range 5-20 (6.3 at the study site). Body size was not affected by salinity and most eggs were produced in salinities of 5, 7.5 and 15. The results suggest that E. affinis lives on the edge of an optimal salinity and that a decline of salinity could affect the fitness of the local populations of the species.

Marine ecosystems and communities are influenced by climate change through precipitation-driven salinity decrease in mar-

Coastal areas are at the centre of human–nature relationship, shaped by recreation, tourism and aesthetic values. However, socioeconomic drivers of biodiversity change in coastal areas have received less attention. Soft sediment seafloors support diverse species communities and contribute to ecosystem functionality. One of the main threats is dredging, which sweeps resident organisms. Dredgings are commonly done to deepen waterways, but also for the purposes of private housing. The ecological impacts of these small‐sized dredgings are not well known over broad environmental and geographical gradients. We developed a simple approach for spatial integration of ecological and socioeconomic system, to describe how recreational land use change contributes to the loss of marine biodiversity. It shows how human behaviour, such as preference for a location of second home, can be derived from spatial data and coupled with ecological change. We characterize typical locations of second homes based on accessibility, aesthetics and environment, and with the information identified suitable areas for new second homes. We also quantified typical areas of dredging, based on the depth and substrate of the sea floor, and the extent of the reed beds, influencing the access to properties. We then simulate an annual increase of new second homes and expected land‐use change, namely dredging of shores. Finally, we quantified the realized and projected loss of marine biodiversity from dredged sites, based on species distribution models, relying on extensive ecological data collected from over 170,000 underwater sites. We found that small‐sized dredging can be detrimental to coastal biodiversity, as dredging targets shallow, photic bays and lagoons, with diverse algal and aquatic plant communities, with limited recovery potential. Dredgings also had broad impacts on benthic faunal habitats, which maintain ecosystem processes and functions. Our results reveal a significant ecological change driven by recreational land use. Reversing the trend of biodiversity loss requires a holistic understanding of socioecological systems. Our results highlight the need for integrating land–sea interactions into conservation policies and reforming current land‐use regulation for the benefit of marine biodiversity. Read the free Plain Language Summary for this article on the Journal blog.

Studying aquatic population dynamics using spatio-temporal monitoring data is associated with a number of challenges and choices. One can let several samples represent the same population over larger areas, or alternatively model the dynamics of each sampling location in continuous space. We analysed the spatio-temporal population dynamics of six phytoplankton taxa in the Baltic Sea applying multivariate state-space models with first-order density dependence. We compared three spatial scales and three models for spatial correlation between predefined subpopulations using information theoretic model selection. We hypothesised that populations close to each other display similar dynamic properties and spatial synchrony decreasing with the distance. We further hypothesize that intermediate-scale grouping of data into subpopulations may parsimoniously represent such dynamics. All taxa showed constant density dependence across space and strong spatial synchrony, consistently requiring a parameter for spatial correlation whenever models included several population states. The most parsimonious spatial structure varied between taxa, most often being one panmictic population or ten intercorrelated population states. Evidently, longer time-series, containing more information, provide more options for modelling detailed spatio-temporal patterns. With a few decade-long plankton time-series data, we encourage determining the appropriate spatial scale on biological grounds rather than model fit.