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Many ecological systems are now exposed to multiple stressors, and ecosystem management increasingly requires consideration of the joint effects of multiple stressors on focal populations, communities and ecosystems. In the absence of empirical data, ecosystem managers could use null models based on the combination of independently acting stressors to estimate the joint effects of multiple stressors. Here, we used a simulation study and a meta-analysis to explore the consequences of null model selection for the prediction of mortality resulting from exposure to two stressors. Comparing five existing null models, we show that some null models systematically predict lower mortality rates than others, with predicted mortality rates up to 67.5% higher or 50% lower than the commonly used Simple Addition model. However, the null model predicting the highest mortality rate differed across parameter sets, and therefore there is no general 'precautionary null model' for multiple stressors. Using a multi-model framework, we re-analysed data from two earlier meta-analyses and found that 54% of the observed joint effects fell within the range of predictions from the suite of null models. Furthermore, we found that most null models systematically underestimated the observed joint effects, with only the Stressor Addition model showing a bias for overestimation. Finally, we found that the intensity of individual stressors was the strongest predictor of the magnitude of the joint effect across all null models. As a result, studies characterizing the effects of individuals stressors are still required for accurate prediction of mortality resulting from multiple stressors. [ABSTRACT FROM AUTHOR]

Many ecological systems are now exposed to multiple stressors, and ecosystem management increasingly requires consideration of the joint effects of multiple stressors on focal populations, communities and ecosystems. In the absence of empirical data, ecosystem managers could use null models based on the combination of independently acting stressors to estimate the joint effects of multiple stressors. Here, we used a simulation study and a meta-analysis to explore the consequences of null model selection for the prediction of mortality resulting from exposure to two stressors. Comparing five existing null models, we show that some null models systematically predict lower mortality rates than others, with predicted mortality rates up to 67.5% higher or 50% lower than the commonly used Simple Addition model. However, the null model predicting the highest mortality rate differed across parameter sets, and therefore there is no general 'precautionary null model' for multiple stressors. Using a multi-model framework, we re-analysed data from two earlier meta-analyses and found that 54% of the observed joint effects fell within the range of predictions from the suite of null models. Furthermore, we found that most null models systematically underestimated the observed joint effects, with only the Stressor Addition model showing a bias for overestimation. Finally, we found that the intensity of individual stressors was the strongest predictor of the magnitude of the joint effect across all null models. As a result, studies characterizing the effects of individuals stressors are still required for accurate prediction of mortality resulting from multiple stressors. [ABSTRACT FROM AUTHOR]

Land‐use change via human development is a major driver of biodiversity loss. To reduce these impacts, billions of dollars are spent on biodiversity offsets. However, studies evaluating offset project effectiveness that examine components such as the overall compliance and function of projects remain rare. We reviewed 577 offsetting projects in freshwater ecosystems that included the metrics project size, type of aquatic system (e.g., wetland and creek), offsetting measure (e.g., enhancement, restoration, and creation), and an assessment of the projects' compliance and functional success. Project information was obtained from scientific and government databases and gray literature. Despite considerable investment in offsetting projects, crucial problems persisted. Although compliance and function were related to each other, a high level of compliance did not guarantee a high degree of function. However, large projects relative to area had better function than small projects. Function improved when projects targeted productivity or specific ecosystem features and when multiple complementary management targets were in place. Restorative measures were more likely to achieve targets than creating entirely new ecosystems. Altogether the relationships we found highlight specific ecological processes that may help improve offsetting outcomes. [ABSTRACT FROM AUTHOR]

While total phosphorus (TP) is a critical determinant of freshwater ecosystem productivity, multiple stressors can induce shifts in energy pathways, with profound implications for ecosystem and fishery restoration. The Bay of Quinte (Lake Ontario, Canada) is a Great Lakes nearshore ecosystem that has been historically subjected to a variety of environmental perturbations: cultural eutrophication, low dissolved oxygen, reduced fisheries, climatic extremes, phosphorus (P) abatement, and aquatic invasive species. We used the Bay of Quinte to study how trophic state alterations affect fish assemblages in Great Lakes nearshore environments by examining the response of fish biomass to TP concentration variability in the presence of multiple stressors.Our analysis is based on a 42‐year (1972–2013) dataset from the Bay of Quinte for water quality through the food web to fishes. We employed a series of statistical tools that can offer insights into the structural changes induced by the events examined. We first used dynamic linear modelling to detect temporal trends in fish biomass, while accounting for year‐to‐year TP variability over three spatial segments of the bay. We then developed piecewise regression models to assess the extent to which specific ecological events induced distinct shifts in the fish assemblage. Multiple regression modelling was used to quantify the relative importance of TP, zooplankton, and surface water temperature on fish biomass.Based on gillnets, there were consistent fish biomass changes across the bay with increased biomass before P control (1972–1977), declines after P control followed by the establishment of a steady state or modest increase (1978–1994), and a declining trajectory during the recent period (1995–2013). Even when accounting for the role of water temperature and zooplankton, TP still had a significant effect on fish biomass. However, the strength and nature of the relationship varied among fish groups, and overall, the effect of TP on fish biomass has weakened in recent years.Our models show that fish biomass in the Bay of Quinte is shaped by the year‐to‐year TP variability. However, the relationship between P and fish abundance has been modulated by various ecological events with the consequence that the Bay of Quinte fish assemblage has changed and the food web now produces less fish biomass per unit of TP. A projected reduction of mean ambient TP levels from 30 to 25 μg/L, is expected to induce a 24% decline in total fish biomass, and further shift the fish assemblage with the biomass of planktivores and walleye declining by >60% and 30%, respectively.Recreational fishing provides important economic benefits in the Bay of Quinte, through tourism and other local business operations. Recognising the economic importance of fishing, our analysis provides critical insights regarding the on‐going management efforts to reduce external nutrient loadings (point and non‐point sources, urban storm water) and further lower ambient TP levels and primary productivity. The potential implications of already low nutrient concentrations for fish productivity represent a major challenge in effectively balancing water quality with fisheries management in the area. [ABSTRACT FROM AUTHOR]

Anthropogenic pollution and the introduction of invasive species are two contributing factors to ecosystem degradation. Although Hamilton Harbour (Ontario, Canada), a highly impacted ecosystem, is well-studied, the diet, trophic position, and foraging behaviour of the invasive Round Goby (Neogobius melanostomus) in this area is not well understood. In this study, we compared digestive tract contents, foraging behaviour, and stable isotope values of Round Goby from sites of low and high sediment contamination in Hamilton Harbour. We also assessed prey availability by conducting sediment invertebrate abundance analyses at these sites. Regardless of site, Chironomids, Cladocerans, Copepods and Dreissenids were the most common food items found in Round Goby digestive tracts, and females always had heavier gut contents compared to males. Fish from the high contamination site consumed fewer prey items, had lower gut fullness scores, and fed at a lower trophic level based on lower δ13C and δ15N values. Our results suggest that Round Goby living in highly contaminated areas are feeding less than Round Goby from areas of lower contamination, but that these diet differences do not reflect differences in prey availability. Fish from the high contamination site also typically moved more slowly while foraging. Taken together, these results provide an analysis of the main prey items of Round Goby in Hamilton Harbour, and demonstrate how polluted environments can impact diet, trophic position, and foraging of an introduced fish species. [ABSTRACT FROM PUBLISHER]