Improving multiple stressor-response models through the inclusion of nonlinearity and interactions among stressor gradients.

Stressor-response models are used to detect and predict changes within ecosystems in response to anthropogenic and naturally occurring stressors. While nonlinear stressor-response relationships and interactions between stressors are common in nature, predictive models often do not account for them due to perceived difficulties in the interpretation of results. We used Irish river monitoring data from 177 river sites to investigate if multiple stressor-response models can be improved by accounting for nonlinearity, interactions in stressor-response relationships and environmental context dependencies. Out of the six models of distinct biological responses, five models benefited from the inclusion of nonlinearity while all six benefited from the inclusion of interactions. The addition of nonlinearity means that we can better see the exponential increase in Trophic Diatom Index (TDI3) as phosphorus increases, inferring ecological conditions deteriorating at a faster rate with increasing phosphorus. Furthermore, our results show that the relationship between stressor and response has the potential to be dependent on other variables, as seen in the interaction of elevation with both siltation and nutrients in relation to Ephemeroptera, Plecoptera and Trichoptera (EPT) richness. Both relationships weakened at higher elevations, perhaps demonstrating that there is a decreased capacity for resilience to stressors at lower elevations due to greater cumulative effects. Understanding interactions such as this is vital to managing ecosystems. Our findings provide empirical support for the need to further develop and employ more complex modelling techniques in environmental assessment and management.

Studying interactions among anthropogenic stressors in freshwater ecosystems: A systematic review of 2396 multiple-stressor experiments.

Understanding the interactions among anthropogenic stressors is critical for effective conservation and management of ecosystems. Freshwater scientists have invested considerable resources in conducting factorial experiments to disentangle stressor interactions by testing their individual and combined effects. However, the diversity of stressors and systems studied has hindered previous syntheses of this body of research. To overcome this challenge, we used a novel machine learning framework to identify relevant studies from over 235,000 publications. Our synthesis resulted in a new dataset of 2396 multiple-stressor experiments in freshwater systems. By summarizing the methods used in these studies, quantifying trends in the popularity of the investigated stressors, and performing co-occurrence analysis, we produce the most comprehensive overview of this diverse field of research to date. We provide both a taxonomy grouping the 909 investigated stressors into 31 classes and an open-source and interactive version of the dataset (https://jamesaorr.shinyapps.io/freshwater-multiple-stressors/). Inspired by our results, we provide a framework to help clarify whether statistical interactions detected by factorial experiments align with stressor interactions of interest, and we outline general guidelines for the design of multiple-stressor experiments relevant to any system. We conclude by highlighting the research directions required to better understand freshwater ecosystems facing multiple stressors.

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.

Using weighted expert judgement and nonlinear data analysis to improve Bayesian belief network models for riverine ecosystem services.

Rivers are a key part of the hydrological cycle and a vital conduit of water resources, but are under increasing threat from anthropogenic pressures. Linking pressures with ecosystem services is challenging because the processes interconnecting the physico-chemical, biological and socio-economic elements are usually captured using heterogenous methods. Our objectives were, firstly, to advance an existing proof-of-principle Bayesian belief network (BBN) model for integration of ecosystem services considerations into river management. We causally linked catchment stressors with ecosystem services using weighted evidence from an expert workshop (capturing confidence among expert groups), legislation and published literature. The BBN was calibrated with analyses of national monitoring data (including non-linear relationships and ecologically meaningful breakpoints) and expert judgement. We used a novel expected index of desirability to quantify the model outputs. Secondly, we applied the BBN to three case study catchments in Ireland to demonstrate the implications of changes in stressor levels for ecosystem services in different settings. Four out of the seven significant relationships in data analyses were non-linear, highlighting that non-linearity is common in ecosystems, but rarely considered in environmental modelling. Deficiency of riparian shading was identified as a prevalent and strong influence, which should be addressed to improve a broad range of societal benefits, particularly in the catchments where riparian shading is scarce. Sediment load had a lower influence on river biology in flashy rivers where it has less potential to settle out. Sediment interacted synergistically with organic matter and phosphate where these stressors were active; tackling these stressor pairs simultaneously can yield additional societal benefits compared to the sum of their individual influences, which highlights the value of integrated management. Our BBN model can be parametrised for other Irish catchments whereas elements of our approach, including the expected index of desirability, can be adapted globally.

Towards a unified study of multiple stressors: divisions and common goals across research disciplines.

Anthropogenic environmental changes, or 'stressors', increasingly threaten biodiversity and ecosystem functioning worldwide. Multiple-stressor research is a rapidly expanding field of science that seeks to understand and ultimately predict the interactions between stressors. Reviews and meta-analyses of the primary scientific literature have largely been specific to either freshwater, marine or terrestrial ecology, or ecotoxicology. In this cross-disciplinary study, we review the state of knowledge within and among these disciplines to highlight commonality and division in multiple-stressor research. Our review goes beyond a description of previous research by using quantitative bibliometric analysis to identify the division between disciplines and link previously disconnected research communities. Towards a unified research framework, we discuss the shared goal of increased realism through both ecological and temporal complexity, with the overarching aim of improving predictive power. In a rapidly changing world, advancing our understanding of the cumulative ecological impacts of multiple stressors is critical for biodiversity conservation and ecosystem management. Identifying and overcoming the barriers to interdisciplinary knowledge exchange is necessary in rising to this challenge. Division between ecosystem types and disciplines is largely a human creation. Species and stressors cross these borders and so should the scientists who study them.

Thermal effluents from power plants boost performance of the invasive clam Corbicula fluminea in Ireland's largest river.

Elevated temperatures due to anthropogenic activities can improve the performance of non-native species that are adapted to higher temperatures than resident species. Ecosystems may experience higher temperature due to global stressors, such as climate change, or local stressors, including thermal effluents and urban heat islands. Using field surveys of population density and body size of the highly invasive and hot-adapted clam Corbicula fluminea in and out of two thermal effluents from power plants along the River Shannon, Ireland, we tested the hypothesis that C. fluminea performs better in thermal plumes. Shell length and body mass of C. fluminea in thermal effluents were 1.8 and 4.4 times higher, respectively, compared with adjacent unheated river sections. Density of C. fluminea was 13.7 times higher in heated, compared with unheated river reaches, leading to an increase in combined biomass per unit area of >50-fold. Our temperature data suggest an up to 2.5-fold increase of degree-days for growth and up to 5.2-fold increase of degree-days for larval incubation in the thermal plumes in River Shannon, compared with unheated conditions. Through enlarged body size, the elevated temperatures likely increase fecundity within the plumes. These findings illustrate that, in temperate climates, thermal plumes can form sanctuaries, where C. fluminea likely alters habitat, outpaces competitors and potentially dominates the energy flow through food webs. Furthermore, thermal plumes can act as stepping-stones and propagule banks for further proliferation of C. fluminea and other warm-adapted invaders.

Warming can enhance invasion success through asymmetries in energetic performance.

Both climate warming and biological invasions are prominent drivers of global environmental change and it is important to determine how they interact. However, beyond tolerance and reproductive thresholds, little is known about temperature dependence of invaders' performance, particularly in the light of competitive attributes of functionally similar native species. We used experimentally derived energy budgets and field temperature data to determine whether anticipated warming will asymmetrically affect the energy budgets of the globally invasive Ponto-Caspian mysid crustacean Hemimysis anomala and a functionally similar native competitor (Mysis salemaai) whose range is currently being invaded. In contrast to M. salemaai, which maintains a constant feeding rate with temperature leading to diminishing energy assimilation, we found that H. anomala increases its feeding rate with temperature in parallel with growing metabolic demand. This enabled the invader to maintain high energy assimilation rates, conferring substantially higher scope for growth compared to the native analogue at spring-to-autumn temperatures. Anticipated warming will likely exacerbate this energetic asymmetry and remove the winter overlap, which, given the seasonal limitation of mutually preferred prey, appears to underpin coexistence of the two species. These results indicate that temperature-dependent asymmetries in scope for growth between invaders and native analogues comprise an important mechanism determining invasion success under warming climates. They also highlight the importance of considering relevant spectra of ecological contexts in predicting successful invaders and their impacts under warming scenarios.

Ecosystem-level effects of a globally spreading invertebrate invader are not moderated by a functionally similar native.

Biological invasions are a key element of human-induced global environmental change. However, lack of knowledge of the indirect consequences of invasions, combined with poor understanding of how their ecological effects depend upon competitive attributes of the receiving community, hinders our ability to manage and predict the effects of invasive species on ecosystems. We established an experiment using a combination of both additive and substitutive experimental designs to explore the effects of the globally spreading mysid shrimp Hemimysis anomala on the biological structure of outdoor pond mesocosms in the absence and presence of a functionally similar native competitor, Mysis salemaai. The naturally smaller H. anomala had considerably stronger effects on primary producers, multiple aspects of consumer assemblages and overall biological structure of the ponds in comparison with the functionally similar native. Moreover, the magnitude of these effects was generally independent of the presence of M. salemaai and even total mysid density. Hemimysis anomala reduced both the abundance and diversity of zooplankton assemblages significantly, triggering a strong trophic cascade on phytoplankton and a simultaneous increase of benthic invertebrate biomass. These findings indicate that invasion by H. anomala may exacerbate the effects of nutrient enrichment on lakes. Our results demonstrate that introduced species can, irrespective of the presence of functionally similar natives, induce complex changes to ecosystems that reach beyond direct consumptive effects. Moreover, the cascading indirect effects of invasion can exacerbate the impacts of other stressors. Disregarding the complexity of indirect effects therefore risks underestimating significantly the global ecological footprint of biological invasions.