Salinity is one of the main factors that explain the distribution of species in the Baltic Sea. Increased precipitation and consequent increase in freshwater inflow is predicted to decrease salinity in some areas of the Baltic Sea. Clearly such changes may have profound effects on the organisms living there. Here we investigate the response of the commonly occurring cyanobacterium Dolichospermum spp. to three salinities, 0, 3 and 6. For the three strains tested we recorded growth, intracellular toxicity (microcystin) and allelopathic properties. We show that Dolichospermum can grow in all the three salinities tested with highest growth rates in the lowest salinity. All strains showed allelopathic potential and it differed significantly between strains and salinities, but was highest in the intermediate salinity and lowest in freshwater. Intracellular toxin concentration was highest in salinity 6. In addition, based on monitoring data from the northern Baltic Proper and the Gulf of Finland, we show that salinity has decreased, while Dolichospermum spp. biomass has increased between 1979 and 2013. Thus, based on our experimental findings it is evident that salinity plays a large role in Dolichospermum growth, allelopathic properties and toxicity. In combination with our long-term data analyses, we conclude that decreasing salinity is likely to result in a more favourable environment for Dolichospermum spp. in some areas of the Baltic Sea.

Species distribution models (SDM) are a key tool in ecology, conservation and management of natural resources. Two key components of the state-of-the-art SDMs are the description for species distribution response along environmental covariates and the spatial random effect that captures deviations from the distribution patterns explained by environmental covariates. Joint species distribution models (JSDMs) additionally include interspecific correlations which have been shown to improve their descriptive and predictive performance compared to single species models. However, current JSDMs are restricted to hierarchical generalized linear modeling framework. Their limitation is that parametric models have trouble in explaining changes in abundance due, for example, highly non-linear physical tolerance limits which is particularly important when predicting species distribution in new areas or under scenarios of environmental change. On the other hand, semi-parametric response functions have been shown to improve the predictive performance of SDMs in these tasks in single species models. Here, we propose JSDMs where the responses to environmental covariates are modeled with additive multivariate Gaussian processes coded as linear models of coregionalization. These allow inference for wide range of functional forms and interspecific correlations between the responses. We propose also an efficient approach for inference with Laplace approximation and parameterization of the interspecific covariance matrices on the euclidean space. We demonstrate the benefits of our model with two small scale examples and one real world case study. We use cross-validation to compare the proposed model to analogous semi-parametric single species models and parametric single and joint species models in interpolation and extrapolation tasks. The proposed model outperforms the alternative models in all cases. We also show that the proposed model can be seen as an extension of the current state-of-the-art JSDMs to semi-parametric models.

Climate-induced warming and increased river inflows are forcing the Baltic Sea to radical changes in the near future; organisms living in this brackish-water ecosystem are already experiencing osmotic stress, which, together with thermal stress, may have severe consequences on the ecosystem. The aim of this work was to study the combined effect of decreasing salinity and increasing temperature on reproductive success and oxidative stress in zooplankton by using a calanoid copepod Acartia sp. as a model organism. The field study was conducted during summer 2020 in the western Gulf of Finland, using three sampling sites with naturally differing salinity levels. Additionally, the copepods from these sites were experimentally exposed to ambient or 3 degrees C elevated temperature for 72 h. The copepods derived from the deepest and the most saline sampling site suffered less oxidative damage and exhibited relatively high reproduction, while the temperature treatment itself had little effect. On the other hand, the field-based monitoring data showed otherwise; temperature increased lipid peroxidation, glutathione-s-transferase activity, or both in all three sampling sites. Meanwhile, egg production rate was negatively associated with temperature in the area with the lowest salinity. Moreover, egg production rate decreased from June to September along with increasing temperatures in the mid-salinity sampling site, while similar change occurred also in the highest-salinity site between August and September. The combined effect of salinity and sampling date on reproduction indicates the importance of even subtle salinity changes on copepods. Moreover, the data suggest that the unusually strong heatwave was responsible for increased oxidative stress during the sampling season and possibly forced a trade-off between antioxidant activity and reproductive effort.

Marenzelleria spp. are among the most successful non-native benthic species in the Baltic Sea. These burrowing polychaetes dig deeper than most native Baltic species, performing previously lacking ecosystem functions. We examine evidence from experiments, field sampling and modelling that the introduction of Marenzelleria spp. affects nutrient cycling and biogeochemical processes at the sediment water interface. Over longer time scales, bioirrigation by Marenzelleria spp. has the potential to increase phosphorus retention in bottom deposits because of deeper oxygen penetration into sediments and formation of a deeper oxidized layer. In contrast, nitrogen fluxes from the sediment increase. As a consequence of a decline of the phosphate concentration and/or rising nitrogen/phosphorus ratio, some Northern Baltic ecosystems may experience improvement of the environment because of mitigation of eutrophication and harmful cyanobacteria blooms. Although it is difficult to unambiguously estimate the ecosystem-level consequences of invasion, in many cases it could be considered as positive due to increased structural and functional diversity. The long-term interactions with the native fauna still remain unknown, however, and in this paper we highlight the major knowledge gaps. (C) 2015 Institute of Oceanology of the Polish Academy of Sciences., Production and hosting by Elsevier Sp. z o.o.

Many studies underscore the importance of incorporating the effect of environmental data within a life-history-stage-specific framework for determining the recruitment and survival of small pelagic fish. The recruitment of anchovy (Engraulis encrasicolus) in the Gulf of Cadiz (NE Atlantic) is sensitive to the effect of intense easterlies, stratification of the water column, and discharges from the Guadalquivir River on early life stages. As a proof of concept, we have developed the basis for a new Bayesian model with a dual time step resolution: monthly for juveniles and adults, and weekly for earlier life stages. This dual time step resolution resolves environmental effects on prerecruits while simulating the effect of fishing on recruits. Our estimates for juvenile abundances are validated with field data. The Bayesian framework accounts for the uncertainty, thus providing consistent length-frequency estimates and a plausible environmentally driven stock-recruitment relationship.

Functional traits are becoming more common in the analysis of marine zooplankton community dynamics associated with environmental change. We used zooplankton groups with common functional properties to assess long-term trends in the zooplankton caused by certain environmental conditions in a highly eutrophicated gulf. Time series of zooplankton traits have been collected since the 1960s in the Gulf of Riga, Baltic Sea, and were analyzed using a combination of multivariate methods (principal coordinate analysis) and generalized additive models. One of the most significant changes was the considerable increase in the amount of the zooplankton functional groups (FGR) in coastal springtime communities, and dominance shifts from more complex to simpler organism groups-cladocerans and rotifers. The results also show that functional trait organism complexity (body size) decreased considerably due to cladoceran and rotifer increase following elevated water temperature. Salinity and oxygen had negligible effects on the zooplankton community.

The risk of a large-scale oil spill remains significant in marine environments as international maritime transport continues to grow. The environmental as well as the socio-economic impacts of a large-scale oil spill could be substantial. Oil spill models and modeling tools for Pollution Preparedness and Response (PPR) can support effective risk management. However, there is a lack of integrated approaches that consider oil spill risks comprehensively, learn from all information sources, and treat the system uncertainties in an explicit manner. Recently, the use of the international ISO 31000:2018 risk management framework has been suggested as a suitable basis for supporting oil spill PPR risk management. Bayesian networks (BNs) are graphical models that express uncertainty in a probabilistic form and can thus support decision-making processes when risks are complex and data are scarce. While BNs have increasingly been used for oil spill risk assessment (OSRA) for PPR, no link between the BNs literature and the ISO 31000:2018 framework has previously been made. This study explores how Bayesian risk models can be aligned with the ISO 31000:2018 framework by offering a flexible approach to integrate various sources of probabilistic knowledge. In order to gain insight in the current utilization of BNs for oil spill risk assessment and management (OSRA-BNs) for maritime oil spill preparedness and response, a literature review was performed. The review focused on articles presenting BN models that analyze the occurrence of oil spills, consequence mitigation in terms of offshore and shoreline oil spill response, and impacts of spills on the variables of interest. Based on the results, the study discusses the benefits of applying BNs to the ISO 31000:2018 framework as well as the challenges and further research needs.

Although studies of biogeochemical processes in polar sea ice have been increasing, similar research on relatively warm low-salinity sea ice remains sparse. In this study, we investigated biogeochemical properties of the landfast sea ice cover in the brackish Bothnian Bay (Northern Baltic Sea) and the possible role of this sea ice in mediating the exchange of greenhouse gases, including carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) across the water column-sea ice-atmosphere interface. Observations of total alkalinity and dissolved inorganic carbon in both landfast sea ice and the water column suggest that the carbonate system is mainly driven by salinity. While high CH4 and N2O concentrations were observed in both the water column (up to 14.3 and 17.5 nmol L-1, respectively) and the sea ice (up to 143.6 and 22.4 nmol L-1, respectively), these gases appear to be enriched in sea ice compared to the water column. This enrichment may be attributable to the sea ice formation process, which concentrates impurities within brine. As sea ice temperature and brine volume decrease, gas solubility decreases as well, promoting the formation of bubbles. Gas bubbles originating from underlying sediments may also be incorporated within the ice cover and contribute to the enrichment in sea ice. The fate of these greenhouse gases within the ice merits further research, as storage in this low-salinity seasonal sea ice is temporary.

Even though the effects of benthic fauna on aquatic biogeochemistry have been long recognized, few studies have addressed the combined effects of animal bioturbation and metabolism on ecosystem-level carbon and nutrient dynamics. Here we merge a model of benthic fauna (BMM) into a physical-biogeochemical ecosystem model (BALTSEM) to study the long-term and large-scale effects of benthic fauna on nutrient and carbon cycling in the Baltic Sea. We include both the direct effects of faunal growth and metabolism and the indirect effects of its bioturbating activities on biogeochemical fluxes of and transformations between organic and inorganic forms of carbon (C), nitrogen (N), phosphorus (P) and oxygen (0). Analyses of simulation results from the Baltic Proper and Gulf of Riga indicate that benthic fauna makes up a small portion of seafloor active organic stocks (on average 1%-4 % in 2000-2020) but contributes considerably to benthic-pelagic fluxes of inorganic C (23%-31%), N (42%-51%) and P (25 %-34 %) through its metabolism. Results also suggest that the relative contribution of fauna to the mineralization of sediment organic matter increases with increasing nutrient loads. Further, through enhanced sediment oxygenation, bioturbation decreases benthic denitrification and increases P retention, the latter having far-reaching consequences throughout the ecosystem. Reduced benthic-pelagic P fluxes lead to a reduction in N fixation and primary production, lower organic matter sedimentation fluxes, and thereby generally lower benthic stocks and fluxes of C, N and P. This chain of effects through the ecosystem overrides the local effects of faunal respiration, excretion and bioturbation. Due to large uncertainties related to the parameterization of benthic processes, we consider this modelling study a first step towards disentangling the complex ecosystem-scale effects of benthic fauna on biogeochemical cycling.

On a daily basis, planktonic organisms migrate vertically and thus experience widely varying conditions in their physico-chemical environment. In the Gulf of Finland, these changes are larger than values predicted by climate change scenarios predicted for the next century (up to 0.5 units in pH and 5 degrees C in temperature). In this work, we are interested in how temporal variations in physico-chemical characteristics of the water column on a daily and weekly scale influence oxidative stress level and antioxidant responses in the planktonic copepod of the genus Acartia. Responses were determined from samples collected during a two-week field survey in the western Gulf of Finland, Baltic Sea. Our results showed that GST (Glutathione-S-transferase) enzyme activity increased in the surface waters between Weeks I and II, indicating antioxidant defense mechanism activation. This is most likely due to elevating temperature, pH, and dissolved oxygen observed between these two weeks. During Week II also GSSG (oxidized glutathione) was detected, indicating that copepods responded to stressor(s) in the environment. Our results suggest that Acartia copepods seem fairly tolerant to weekly fluctuations in environmental conditions in coastal and estuarine areas, in terms of antioxidant defense and oxidative stress. This could be directly connected to a very efficient glutathione cycling system acting as antioxidant defense system for neutralizing ROS and avoiding elevated levels of LPX.