Interactive effects of warming, eutrophication and size structure: impacts on biodiversity and food-web structure

The environment to the rescue: can physics help predict predator-prey interactions?

Understanding the factors that determine the occurrence and strength of ecological interactions under specific abiotic and biotic conditions is fundamental since many aspects of ecological community stability and ecosystem functioning depend on patterns of interactions among species. Current approaches to mapping food webs are mostly based on traits, expert knowledge, experiments, and/or statistical inference. However, they do not offer clear mechanisms explaining how trophic interactions are affected by the interplay between organism characteristics and aspects of the physical environment, such as temperature, light intensity or viscosity. Hence, they cannot yet predict accurately how local food webs will respond to anthropogenic pressures, notably to climate change and species invasions. Herein, we propose a framework that synthesises recent developments in food-web theory, integrating body size and metabolism with the physical properties of ecosystems. We advocate for combination of the movement paradigm with a modular definition of the predation sequence, because movement is central to predator-prey interactions, and a generic, modular model is needed to describe all the possible variation in predator-prey interactions. Pending sufficient empirical and theoretical knowledge, our framework will help predict the food-web impacts of well-studied physical factors, such as temperature and oxygen availability, as well as less commonly considered variables such as wind, turbidity or electrical conductivity. An improved predictive capability will facilitate a better understanding of ecosystem responses to a changing world.

Flexible foraging behaviour increases predator vulnerability to climate change

Higher temperatures are expected to reduce species coexistence by increasing energetic demands. However, flexible foraging behaviour could balance this effect by allowing predators to target specific prey species to maximize their energy intake, according to principles of optimal foraging theory. Here we test these assumptions using a large dataset comprising 2,487 stomach contents from six fish species with different feeding strategies, sampled across environments with varying prey availability over 12 years in Kiel Bay (Baltic Sea). Our results show that foraging shifts from trait- to density-dependent prey selectivity in warmer and more productive environments. This behavioural change leads to lower consumption efficiency at higher temperature as fish select more abundant but less energetically rewarding prey, thereby undermining species persistence and biodiversity. By integrating this behaviour into dynamic food web models, our study reveals that flexible foraging leads to lower species coexistence and biodiversity in communities under global warming.

Quantitative description of six fish species' gut contents and prey abundances in the Baltic Sea (1968-1978)

The dataset presents a compilation of stomach contents from six demersal fish species from two functional groups inhabiting the Baltic Sea. It includes detailed information on prey identities, body masses, and biomasses recovered from both the fish's digestive systems and their surrounding environment. Environmental parameters, such as salinity and temperature levels, have been integrated to enrich this dataset. The juxtaposition of information on prey found in stomachs and in the environment provides an opportunity to quantify trophic interactions across different environmental contexts and investigate how fish foraging behaviour adapts to changes in their environment, such as an increase in temperature. The compilation of body mass and taxonomic information for all species allows approaching these new questions using either a taxonomic (based on species identity) or functional trait (based on body mass) approach.

Body size and trophic position determine the outcomes of species invasions along temperature and productivity gradients

Species invasions are predicted to increase in frequency with global change, but quantitative predictions of how environmental filters and species traits influence the success and consequences of invasions for local communities are lacking. Here we investigate how invaders alter the structure, diversity and stability regime of simple communities across environmental gradients (habitat productivity, temperature) and community size structure. We simulate all three-species trophic modules (apparent and exploitative competition, trophic chain and intraguild predation). We predict that invasions most often succeed in warm and productive habitats and that successful invaders include smaller competitors, intraguild predators and comparatively small top predators. This suggests that species invasions and global change may facilitate the downsizing of food webs. Furthermore, we show that successful invasions leading to species substitutions rarely alter system stability, while invasions leading to increased diversity can destabilize or stabilize community dynamics depending on the environmental conditions and invader's trophic position.

Climate change affects the distribution of diversity across marine food webs

Many studies predict shifts in species distributions and community size composition in response to climate change, yet few have demonstrated how these changes will be distributed across marine food webs. We use Bayesian Additive Regression Trees to model how climate change will affect the habitat suitability of marine fish species across a range of body sizes and belonging to different feeding guilds, each with different habitat and feeding requirements in the northeast Atlantic shelf seas. Contrasting effects of climate change are predicted for feeding guilds, with spatially extensive decreases in the species richness of consumers lower in the food web (planktivores) but increases for those higher up (piscivores). Changing spatial patterns in predator-prey mass ratios and fish species size composition are also predicted for feeding guilds and across the fish assemblage. In combination, these changes could influence nutrient uptake and transformation, transfer efficiency and food web stability, and thus profoundly alter ecosystem structure and functioning.

Thermal mismatches explain consumer-resource dynamics in response to environmental warming

Changing temperatures will impact food webs in ways we yet to fully understand. The thermal sensitivities of various physiological and ecological processes differ across organisms and study systems, hindering the generation of accurate predictions. One step towards improving this picture is to acquire a mechanistic understanding of how temperature change impacts trophic interactions before we can scale these insights up to food webs and ecosystems. Here, we implement a mechanistic approach centered on the thermal sensitivity of energetic balances in pairwise consumer-resource interactions, measuring the thermal dependence of energetic gain and loss for two resource and one consumer freshwater species. Quantifying the balance between energy gain and loss, we determined the temperature ranges where the balance decreased for each species in isolation (intraspecific thermal mismatch) and where a mismatch in the balance between consumer and resource species emerged (interspecific thermal mismatch). The latter reveals the temperatures for which consumer and resource energetic balances respond either differently or in the same way, which in turn informs us of the strength of top-down control. We found that warming improved the energetic balance for both resources, but reduces it for the consumer, due to the stronger thermal sensitivity of respiration compared to ingestion. The interspecific thermal mismatch yielded different patterns between the two consumer-resource pairs. In one case, the consumer-resource energetic balance became weaker throughout the temperature gradient, and in the other case it produced a U-shaped response. By also measuring interaction strength for these interaction pairs, we demonstrated the correspondence of interspecific thermal mismatches and interaction strength. Our approach accounts for the energetic traits of both consumer and resource species, which combined produce a good indication of the thermal sensitivity of interaction strength. Thus, this novel approach links thermal ecology with parameters typically explored in food-web studies.

Temperature, productivity, and habitat characteristics collectively drive lake food web structure

While many efforts have been devoted to understand variations in food web structure among terrestrial and aquatic ecosystems, the environmental factors influencing food web structure at large spatial scales remain hardly explored. Here, we compiled biodiversity inventories to infer food web structure of 67 French lakes using an allometric niche-based model and tested how environmental variables (temperature, productivity, and habitat) influence them. By applying a multivariate analysis on 20 metrics of food web topology, we found that food web structural variations are represented by two distinct complementary and independent structural descriptors. The first is related to the overall trophic diversity, whereas the second is related to the vertical structure. Interestingly, the trophic diversity descriptor was mostly explained by habitat size (26.7% of total deviance explained) and habitat complexity (20.1%) followed by productivity (dissolved organic carbon: 16.4%; nitrate: 9.1%) and thermal variations (10.7%). Regarding the vertical structure descriptor, it was mostly explained by water thermal seasonality (39.0% of total deviance explained) and habitat depth (31.9%) followed by habitat complexity (8.5%) and size (5.5%) as well as annual mean temperature (5.6%). Overall, we found that temperature, productivity, and habitat characteristics collectively shape lake food web structure. We also found that intermediate levels of productivity, high levels of temperature (mean and seasonality), as well as large habitats are associated with the largest and most complex food webs. Our findings, therefore, highlight the importance of focusing on these three components especially in the context of global change, as significant structural changes in aquatic food webs could be expected under increased temperature, pollution, and habitat alterations.

Modeling nutrient flows from land to rivers and seas - A review and synthesis

Water quality modeling facilitates management of nutrient flows from land to rivers and seas, in addition to environmental pollution management in watersheds. In the present paper, we review advances made in the development of seven water quality models and highlight their respective strengths and weaknesses. Afterward, we propose their future development directions, with distinct characteristics for different scenarios. We also discuss the practical problems that such models address in the same region, China, and summarize their different characteristics based on their performance. We focus on the temporal and geographical scales of the models, sources of pollution considered, and the main problems that can be addressed. Summary of such characteristics could facilitate the selection of appropriate models for resolving practical challenges on nutrient pollution in the corresponding scenarios globally by stakeholders. We also make recommendations for model enhancement to expand their capabilities.

Effects of temporal abiotic drivers on the dynamics of an allometric trophic network model

Current ecological research and ecosystem management call for improved understanding of the abiotic drivers of community dynamics, including temperature effects on species interactions and biomass accumulation. Allometric trophic network (ATN) models, which simulate material (carbon) transfer in trophic networks from producers to consumers based on mass‐specific metabolic rates, provide an attractive framework to study consumer–resource interactions from organisms to ecosystems. However, the developed ATN models rarely consider temporal changes in some key abiotic drivers that affect, for example, consumer metabolism and producer growth. Here, we evaluate how temporal changes in carrying capacity and light‐dependent growth rate of producers and in temperature‐dependent mass‐specific metabolic rate of consumers affect ATN model dynamics, namely seasonal biomass accumulation, productivity, and standing stock biomass of different trophic guilds, including age‐structured fish communities. Our simulations of the pelagic Lake Constance food web indicated marked effects of temporally changing abiotic parameters on seasonal biomass accumulation of different guild groups, particularly among the lowest trophic levels (primary producers and invertebrates). While the adjustment of average irradiance had minor effect, increasing metabolic rate associated with 1–2°C temperature increase led to a marked decline of larval (0‐year age) fish biomass, but to a substantial biomass increase of 2‐ and 3‐year‐old fish that were not predated by ≥4‐year‐old top predator fish, European perch (Perca fluviatilis). However, when averaged across the 100 simulation years, the inclusion of seasonality in abiotic drivers caused only minor changes in standing stock biomasses and productivity of different trophic guilds. Our results demonstrate the potential of introducing seasonality in and adjusting the average values of abiotic ATN model parameters to simulate temporal fluctuations in food‐web dynamics, which is an important step in ATN model development aiming to, for example, assess potential future community‐level responses to ongoing environmental changes.

Predicting effects of multiple interacting global change drivers across trophic levels

Global change encompasses many co-occurring anthropogenic drivers, which can act synergistically or antagonistically on ecological systems. Predicting how different global change drivers simultaneously contribute to observed biodiversity change is a key challenge for ecology and conservation. However, we lack the mechanistic understanding of how multiple global change drivers influence the vital rates of multiple interacting species. We propose that reaction norms, the relationships between a driver and vital rates like growth, mortality, and consumption, provide insights to the underlying mechanisms of community responses to multiple drivers. Understanding how multiple drivers interact to affect demographic rates using a reaction-norm perspective can improve our ability to make predictions of interactions at higher levels of organization-that is, community and food web. Building on the framework of consumer-resource interactions and widely studied thermal performance curves, we illustrate how joint driver impacts can be scaled up from the population to the community level. A simple proof-of-concept model demonstrates how reaction norms of vital rates predict the prevalence of driver interactions at the community level. A literature search suggests that our proposed approach is not yet used in multiple driver research. We outline how realistic response surfaces (i.e., multidimensional reaction norms) can be inferred by parametric and nonparametric approaches. Response surfaces have the potential to strengthen our understanding of how multiple drivers affect communities as well as improve our ability to predict when interactive effects emerge, two of the major challenges of ecology today.

Temperature and nutrients drive eco-phenotypic dynamics in a microbial food web

Anthropogenic increases in temperature and nutrient loads will likely impact food web structure and stability. Although their independent effects have been reasonably well studied, their joint effects-particularly on coupled ecological and phenotypic dynamics-remain poorly understood. Here we experimentally manipulated temperature and nutrient levels in microbial food webs and used time-series analysis to quantify the strength of reciprocal effects between ecological and phenotypic dynamics across trophic levels. We found that (1) joint-often interactive-effects of temperature and nutrients on ecological dynamics are more common at higher trophic levels, (2) temperature and nutrients interact to shift the relative strength of top-down versus bottom-up control, and (3) rapid phenotypic change mediates observed ecological responses to changes in temperature and nutrients. Our results uncover how feedback between ecological and phenotypic dynamics mediate food web responses to environmental change. This suggests important but previously unknown ways that temperature and nutrients might jointly control the rapid eco-phenotypic feedback that determine food web dynamics in a changing world.

Rising temperature drives tipping points in mutualistic networks

The effect of climate warming on species' physiological parameters, including growth rate, mortality rate and handling time, is well established from empirical data. However, with an alarming rise in global temperature more than ever, predicting the interactive influence of these changes on mutualistic communities remains uncertain. Using 139 real plant-pollinator networks sampled across the globe and a modelling approach, we study the impact of species' individual thermal responses on mutualistic communities. We show that at low mutualistic strength plant-pollinator networks are at potential risk of rapid transitions at higher temperatures. Evidently, generalist species play a critical role in guiding tipping points in mutualistic networks. Further, we derive stability criteria for the networks in a range of temperatures using a two-dimensional reduced model. We identify network structures that can ascertain the delay of a community collapse. Until the end of this century, on account of increasing climate warming many real mutualistic networks are likely to be under the threat of sudden collapse, and we frame strategies to mitigate this. Together, our results indicate that knowing individual species' thermal responses and network structure can improve predictions for communities facing rapid transitions.

Changes in invertebrate food web structure between high- and low-productivity environments are driven by intermediate but not top-predator diet shifts

Predator-prey interactions shape ecosystem stability and are influenced by changes in ecosystem productivity. However, because multiple biotic and abiotic drivers shape the trophic responses of predators to productivity, we often observe patterns, but not mechanisms, by which productivity drives food web structure. One way to capture mechanisms shaping trophic responses is to quantify trophic interactions among multiple trophic groups and by using complementary metrics of trophic ecology. In this study, we combine two diet-tracing methods: diet DNA and stable isotopes, for two trophic groups (top predators and intermediate predators) in both low- and high-productivity habitats to elucidate where in the food chain trophic structure shifts in response to changes in underlying ecosystem productivity. We demonstrate that while top predators show increases in isotopic trophic position (δ15N) with productivity, neither their isotopic niche size nor their DNA diet composition changes. Conversely, intermediate predators show clear turnover in DNA diet composition towards a more predatory prey base in high-productivity habitats. Taking this multi-trophic approach highlights how predator identity shapes responses in predator-prey interactions across environments with different underlying productivity, building predictive power for understanding the outcomes of ongoing anthropogenic change.

Eutrophication status assessment in the Laizhou Bay, Bohai Sea: Further evidence for the ecosystem degradation

Laizhou Bay is plagued by many environmental problems (e.g., acidification and eutrophication) that are likely to increase in the coming decades along with social and demographic trends. We thus conducted 12 cruises from July 2019 to December 2021 in the Laizhou Bay to evaluate the potential influences of human activities on its eutrophication status. The results showed that the parameters of dissolved inorganic nitrogen (DIN) and oxygen (DO) exceeded the water quality standard in some cases during the past 3 years, suggesting DIN and DO were the crucial factors controlling water quality in the bay. Meanwhile, DIN was identified as a major pollutant in the region, and played an important role in driving the phytoplankton dynamics. Furthermore, with the increases in human-related nutrient inputs (especially DIN), the bay environment reached the mild eutrophication level and was probably at risk from excessive nutrient loads at present, further evidencing the ecosystem degradation.

Stoichiometric constraints modulate temperature and nutrient effects on biomass distribution and community stability

Temperature and nutrients are two of the most important drivers of global change. Both can modify the elemental composition (i.e. stoichiometry) of primary producers and consumers. Yet their combined effect on the stoichiometry, dynamics and stability of ecological communities remains largely unexplored. To fill this gap, we extended the Rosenzweig-MacArthur consumer-resource model by including thermal dependencies, nutrient dynamics and stoichiometric constraints on both the primary producer and the consumer. We found that stoichiometric and nutrient conservation constraints dampen the paradox of enrichment and increased persistence at high nutrient levels. Nevertheless, stoichiometric constraints also reduced consumer persistence at extreme temperatures. Finally, we also found that stoichiometric constraints and nutrient dynamics can strongly influence biomass distribution across trophic levels by modulating consumer assimilation efficiency and resource growth rates along the environmental gradients. In the Rosenzweig-MacArthur model, consumer biomass exceeded resource biomass for most parameter values whereas, in the stoichiometric model, consumer biomass was strongly reduced and sometimes lower than resource biomass. Our findings highlight the importance of accounting for stoichiometric constraints as they can mediate the temperature and nutrient impact on the dynamics and functioning of ecological communities.

Food web rewiring drives long-term compositional differences and late-disturbance interactions at the community level

Multiple anthropogenic disturbances affect the structure and functioning of communities. Recent evidence highlighted that, after pulse disturbance, the functioning a community performs may be recovered fast due to functional redundancy, whereas community multivariate composition needs a longer time. Yet, the mechanisms that drive the different community recovery times have not been quantified empirically. We use quantitative food-web analysis to assess the influence of species interactions on community recovery. We found species-interactions strength to be the main mechanism driving differences between structural and functional recovery. Additionally, we show that interactions between multiple disturbances appear in the long term only when both species-interaction strength and food-web architecture change significantly.

Ecological communities are constantly exposed to multiple natural and anthropogenic disturbances. Multivariate composition (if recovered) has been found to need significantly more time to be regained after pulsed disturbance compared to univariate diversity metrics and functional endpoints. However, the mechanisms driving the different recovery times of communities to single and multiple disturbances remain unexplored. Here, we apply quantitative ecological network analyses to try to elucidate the mechanisms driving long-term community-composition dissimilarity and late-stage disturbance interactions at the community level. For this, we evaluate the effects of two pesticides, nutrient enrichment, and their interactions in outdoor mesocosms containing a complex freshwater community. We found changes in interactions strength to be strongly related to compositional changes and identified postdisturbance interaction-strength rewiring to be responsible for most of the observed compositional changes. Additionally, we found pesticide interactions to be significant in the long term only when both interaction strength and food-web architecture are reshaped by the disturbances. We suggest that quantitative network analysis has the potential to unveil ecological processes that prevent long-term community recovery.

Biotic filtering by species' interactions constrains food-web variability across spatial and abiotic gradients

Despite intensive research on species dissimilarity patterns across communities (i.e. β-diversity), we still know little about their implications for variation in food-web structures. Our analyses of 50 lake and 48 forest soil communities show that, while species dissimilarity depends on environmental and spatial gradients, these effects are only weakly propagated to the networks. Moreover, our results show that species and food-web dissimilarities are consistently correlated, but that much of the variation in food-web structure across spatial, environmental, and species gradients remains unexplained. Novel food-web assembly models demonstrate the importance of biotic filtering during community assembly by (1) the availability of resources and (2) limiting similarity in species' interactions to avoid strong niche overlap and thus competitive exclusion. This reveals a strong signature of biotic filtering processes during local community assembly, which constrains the variability in structural food-web patterns across local communities despite substantial turnover in species composition.

Refocusing multiple stressor research around the targets and scales of ecological impacts

Ecological communities face a variety of environmental and anthropogenic stressors acting simultaneously. Stressor impacts can combine additively or can interact, causing synergistic or antagonistic effects. Our knowledge of when and how interactions arise is limited, as most models and experiments only consider the effect of a small number of non-interacting stressors at one or few scales of ecological organization. This is concerning because it could lead to significant underestimations or overestimations of threats to biodiversity. Furthermore, stressors have been largely classified by their source rather than by the mechanisms and ecological scales at which they act (the target). Here, we argue, first, that a more nuanced classification of stressors by target and ecological scale can generate valuable new insights and hypotheses about stressor interactions. Second, that the predictability of multiple stressor effects, and consistent patterns in their impacts, can be evaluated by examining the distribution of stressor effects across targets and ecological scales. Third, that a variety of existing mechanistic and statistical modelling tools can play an important role in our framework and advance multiple stressor research.

Theory of temperature-dependent consumer-resource interactions

Changes in temperature affect consumer-resource interactions, which underpin the functioning of ecosystems. However, existing studies report contrasting predictions regarding the impacts of warming on biological rates and community dynamics. To improve prediction accuracy and comparability, we develop an approach that combines sensitivity analysis and aggregate parameters. The former determines which biological parameters impact the community most strongly. The use of aggregate parameters (i.e., maximal energetic efficiency, ρ, and interaction strength, κ), that combine multiple biological parameters, increases explanatory power and reduces the complexity of theoretical analyses. We illustrate the approach using empirically derived thermal dependence curves of biological rates and applying it to consumer-resource biomass ratio and community stability. Based on our analyses, we generate four predictions: (1) resource growth rate regulates biomass distributions at mild temperatures, (2) interaction strength alone determines the thermal boundaries of the community, (3) warming destabilises dynamics at low and mild temperatures only and (4) interactions strength must decrease faster than maximal energetic efficiency for warming to stabilise dynamics. We argue for the potential benefits of directly working with the aggregate parameters to increase the accuracy of predictions on warming impacts on food webs and promote cross-system comparisons.

Eutrophication causes invertebrate biodiversity loss and decreases cross-taxon congruence across anthropogenically-disturbed lakes

Eutrophication is a major problem currently impacting many surface water ecosystems. Impacts of increased nutrient concentrations on biodiversity may differ between different scales, different organism groups, and different trophic states. Surveys at different spatial scales have suggested that biodiversity of different taxa may exhibit significant cross-taxon congruence. In our study, we examined the diversity of zooplankton and zoobenthos across 261 lakes in the Lake Taihu watershed, an area that is undergoing a severe eutrophication process. We tested the cross-taxon congruence in species richness and Shannon-Wiener diversity between zooplankton and zoobenthos along a nutrient gradient across the lakes. Our findings were consistent with the intermediate disturbance hypothesis, considering nutrient input as the disturbance. Also, we found significant cross-taxon congruence between zooplankton and zoobenthos diversities. Our results confirmed that excess nutrient levels resulted in diversity loss and community simplification. Zoobenthos were more sensitive to nutrient increases compared with zooplankton, which decreased cross-taxon congruence because these organism groups did not respond similarly to the anthropogenic disturbance.

The ecological impacts of multiple environmental stressors on coastal biofilm bacteria

Ecological communities are increasingly exposed to multiple interacting stressors. For example, warming directly affects the physiology of organisms, eutrophication stimulates the base of the food web, and harvesting larger organisms for human consumption dampens top-down control. These stressors often combine in the natural environment with unpredictable results. Bacterial communities in coastal ecosystems underpin marine food webs and provide many important ecosystem services (e.g. nutrient cycling and carbon fixation). Yet, how microbial communities will respond to a changing climate remains uncertain. Thus, we used marine mesocosms to examine the impacts of warming, nutrient enrichment, and altered top-predator population size structure (common shore crab) on coastal microbial biofilm communities in a crossed experimental design. Warming increased bacterial α-diversity (18% increase in species richness and 67% increase in evenness), but this was countered by a decrease in α-diversity with nutrient enrichment (14% and 21% decrease for species richness and evenness, respectively). Thus, we show some effects of these stressors could cancel each other out under climate change scenarios. Warming and top-predator population size structure both affected bacterial biofilm community composition, with warming increasing the abundance of bacteria capable of increased mineralization of dissolved and particulate organic matter, such as Flavobacteriia, Sphingobacteriia, and Cytophagia. However, the community shifts observed with warming depended on top-predator population size structure, with Sphingobacteriia increasing with smaller crabs and Cytophagia increasing with larger crabs. These changes could alter the balance between mineralization and carbon sequestration in coastal ecosystems, leading to a positive feedback loop between warming and CO₂ production. Our results highlight the potential for warming to disrupt microbial communities and biogeochemical cycling in coastal ecosystems, and the importance of studying these effects in combination with other environmental stressors.

Genetic and plastic rewiring of food webs under climate change

Climate change is altering ecological and evolutionary processes across biological scales. These simultaneous effects of climate change pose a major challenge for predicting the future state of populations, communities and ecosystems. This challenge is further exacerbated by the current lack of integration of research focused on these different scales.

We propose that integrating the fields of quantitative genetics and food web ecology will reveal new insights on how climate change may reorganize biodiversity across levels of organization. This is because quantitative genetics links the genotypes of individuals to population‐level phenotypic variation due to genetic (G), environmental (E) and gene‐by‐environment (G × E) factors. Food web ecology, on the other hand, links population‐level phenotypes to the structure and dynamics of communities and ecosystems.

We synthesize data and theory across these fields and find evidence that genetic (G) and plastic (E and G × E) phenotypic variation within populations will change in magnitude under new climates in predictable ways. We then show how changes in these sources of phenotypic variation can rewire food webs by altering the number and strength of species interactions, with consequences for ecosystem resilience. We also find evidence suggesting there are predictable asymmetries in genetic and plastic trait variation across trophic levels, which set the pace for phenotypic change and food web responses to climate change. Advances in genomics now make it possible to partition G, E and G × E phenotypic variation in natural populations, allowing tests of the hypotheses we propose.

By synthesizing advances in quantitative genetics and food web ecology, we provide testable predictions for how the structure and dynamics of biodiversity will respond to climate change.

Ocean warming and species range shifts affect rates of ecosystem functioning by altering consumer-resource interactions

Recent warming trends have driven widespread changes in the performance and distribution of species in many regions, with consequent shifts in assemblage structure and ecosystem functioning. However, as responses to warming vary across species and regions, novel communities are emerging, particularly where warm-affinity range-expanding species have rapidly colonized communities still dominated by cold-affinity species. Such community reconfiguration may alter core ecosystem processes, such as productivity or nutrient cycling, yet it remains unclear whether novel communities function similarly to those they have replaced, and how continued warming will alter functioning in the near future. Using simplified kelp forest communities as a model system, we compared rates of respiration, consumption and secondary productivity between current cold-affinity and future warm-affinity kelp assemblages under both present-day temperatures and near-future warming in a series of mesocosm experiments. Overall, respiration rates of gastropods and amphipods increased with warming but did not differ between cold and warm affinity kelp assemblages. Consumption rates of three consumers (urchin, gastropod and amphipod) differed between kelp assemblages but only amphipod consumption rates increased with warming. A diet derived from warm-affinity kelp assemblages led to a decrease in growth and biomass of urchins, whereas the response of other consumers was variable depending on temperature treatment. These results suggest that climate-driven changes in assemblage structure of primary producers will alter per capita rates of ecosystem functioning, and that specific responses may vary in complex and unpredictable ways, with some mediated by warming more than others. Understanding how differences in life history and functional traits of dominant species will affect ecological interactions and, in turn, important ecosystem processes is crucial to understanding the wider implications of climate-driven community reconfiguration.

Warming indirectly increases invasion success in food webs

Climate warming and biological invasions are key drivers of biodiversity change. Their combined effects on ecological communities remain largely unexplored. We investigated the direct and indirect influences of temperature on invasion success, and their synergistic effects on community structure and dynamics. Using size-structured food web models, we found that higher temperatures increased invasion success. The direct physiological effects of temperature on invasions were minimal in comparison with indirect effects mediated by changes on food web structure and stability. Warmer communities with less connectivity, shortened food chains and reduced temporal variability were more susceptible to invasions. The directionality and magnitude of invasions effects on food webs varied across temperature regimes. When invaded, warmer communities became smaller, more connected and with more predator species than their colder counterparts. They were also less stable and their species more abundant. Considering food web structure is crucial to predict invasion success and its impacts along temperature gradients.

Temperature variability alters the stability and thresholds for collapse of interacting species

Temperature variability and extremes can have profound impacts on populations and ecological communities. Predicting impacts of thermal variability poses a challenge, because it has both direct physiological effects and indirect effects through species interactions. In addition, differences in thermal performance between predators and prey and nonlinear averaging of temperature-dependent performance can result in complex and counterintuitive population dynamics in response to climate change. Yet the combined consequences of these effects remain underexplored. Here, modelling temperature-dependent predator-prey dynamics, we study how changes in temperature variability affect population size, collapse and stable coexistence of both predator and prey, relative to under constant environments or warming alone. We find that the effects of temperature variation on interacting species can lead to a diversity of outcomes, from predator collapse to stable coexistence, depending on interaction strengths and differences in species' thermal performance. Temperature variability also alters predictions about population collapse-in some cases allowing predators to persist for longer than predicted when considering warming alone, and in others accelerating collapse. To inform management responses that are robust to future climates with increasing temperature variability and extremes, we need to incorporate the consequences of temperature variation in complex ecosystems. This article is part of the theme issue 'Integrative research perspectives on marine conservation'.

Integrating economic dynamics into ecological networks: The case of fishery sustainability

Understanding anthropogenic impacts on ecosystems requires investigating feedback processes between ecological and economic dynamics. While network ecology has advanced our understanding of large-scale communities, it has not robustly coupled economic drivers of anthropogenic impact to ecological outcomes. Leveraging allometric trophic network models, we study such integrated economic-ecological dynamics in the case of fishery sustainability. We incorporate economic drivers of fishing effort into food-web network models, evaluating the dynamics of thousands of single-species fisheries across hundreds of simulated food webs under fixed-effort and open-access management strategies. Analyzing simulation results reveals that harvesting species with high population biomass can initially support fishery persistence but threatens long-term economic and ecological sustainability by indirectly inducing extinction cascades in non-harvested species. This dynamic is exacerbated in open-access fisheries where profit-driven growth in fishing effort increases perturbation strength. Our results demonstrate how network theory provides necessary ecological context when considering the sustainability of economically dynamic fishing effort.

Relative performance of different data mining techniques for nitrate concentration and load estimation in different type of watersheds

The increasing availability of water quality datasets has led to a greater focus on hydrologic and water quality analysis, thus requiring more efficient and accurate modelling methods. Data mining techniques have been increasingly used for water quality analysis and prediction of the concentration and load of nitrogen pollutants instead of more traditional simulation methods. In this study, we tested the multilayer perceptron (MLP), k-nearest neighbor (k-NN), random forest, and reduced error pruning tree (REPTree) methods, along with the traditional linear regression, to predict nitrate levels based on long-term data from six watersheds with different land-use practices in the midwestern United States. Both the concentration and load results indicated that REPTree had the best performance, with an R² of 0.61-0.85 and a relative absolute error of <75.8%. The different watershed types, however, influenced the performance of the data mining methods, where all four methods showed a higher accuracy for urban dominant watershed and lower accuracy for agricultural and forest watersheds. Out of these four methods, classification tree methods (REPTree and RF) performed better than cluster methods (MLP and k-NN) for agricultural and forested watersheds. Our results indicated that both the data structure based on the dominant land use and type of algorithmic method should be carefully considered for selecting a data mining method to predict nitrate concentration and load for a watershed.

Drought boosts risk of nitrate leaching from grassland fertilisation

Both climate change and agricultural intensification are drivers of global nutrient cycles and biodiversity loss. A potentially great environmental threat can arise when these two drivers interact, for example, when farmers try to compensate reduced soil nutrient availability due to drought by the application of liquid organic fertiliser. As dry soils don't hold back nutrients very well, this approach can lead to nitrate leaching and potentially also to the pollution of drinking water. However, little is known about leaching from dry but fertilised grassland soil, and how this is affected by land use intensity and plant diversity. In this mesocosm study, we transferred 60 grassland sods differing in past land use intensity to a greenhouse and treated them with severe drought, fertilisation and both together. Drought was induced by almost entirely stopping irrigation for seven weeks. Fertilisation was done by three applications of slurry summing up to 168 kg total nitrogen per hectare (111 kg NH₄-N). We assessed nutrient leaching risk with ion-exchange resin (IER) bags installed in the soil of all mesocosms. IER bags were retrieved after drought and extracts were analysed for concentrations of nitrate, ammonium, phosphate and potassium. Fertilisation partially buffered drought-induced losses in yield. However, the interaction of fertilisation and drought resulted in a drastic increase in nitrate leaching risk when soils are rewetted (>300%), while neither drought nor fertilisation alone were significant. Ammonium concentrations followed the same trend as nitrate, but less pronounced. Phosphate and potassium concentrations were not affected by the treatments. Past land use was hardly related to soil nutrient concentrations, rather was plant diversity. However, results indicate that plant diversity was not driving nitrate and ammonium concentrations under drought and/or fertilisation. This study reveals grassland fertilisation during drought to be a severe environmental problem due to significantly increased nitrate leaching risk.

Species multidimensional effects explain idiosyncratic responses of communities to environmental change

Environmental change can alter species' abundances within communities consistently; for example, increasing all abundances by the same percentage, or more idiosyncratically. Here, we show how comparing effects of temperature on species grown in isolation and when grown together helps our understanding of how ecological communities more generally respond to environmental change. In particular, we find that the shape of the feasibility domain (the parameter space of carrying capacities compatible with positive species' abundances) helps to explain the composition of experimental microbial communities under changing environmental conditions. First, we introduce a measure to quantify the asymmetry of a community's feasibility domain using the column vectors of the corresponding interaction matrix. These column vectors describe the effects each species has on all other species in the community (hereafter referred to as species' multidimensional effects). We show that as the asymmetry of the feasibility domain increases the relationship between species' abundance when grown together and when grown in isolation weakens. We then show that microbial communities experiencing different temperature environments exhibit patterns consistent with this theory. Specifically, communities at warmer temperatures show relatively more asymmetry; thus, the idiosyncrasy of responses is higher compared with that in communities at cooler temperatures. These results suggest that while species' interactions are typically defined at the pairwise level, multispecies dynamics can be better understood by focusing on the effects of these interactions at the community level.

How Do Eutrophication and Temperature Interact to Shape the Community Structures of Phytoplankton and Fish in Lakes?

Freshwater ecosystems are among the systems most threatened and impacted by anthropogenic activities, but there is still a lack of knowledge on how this multi-pressure environment impacts aquatic communities in situ. In Europe, nutrient enrichment and temperature increase due to global change were identified as the two main pressures on lakes. Therefore, we investigated how the interaction of these two pressures impacts the community structure of the two extreme components of lake food webs: phytoplankton and fish. We modelled the relationship between community components (abundance, composition, size) and environmental conditions, including these two pressures. Different patterns of response were highlighted. Four metrics responded to only one pressure and one metric to the additive effect of the two pressures. Two fish metrics (average body-size and biomass ratio between perch and roach) were impacted by the interaction of temperature and eutrophication, revealing that the effect of one pressure was dependent on the magnitude of the second pressure. From a management point of view, it appears necessary to consider the type and strength of the interactions between pressures when assessing the sensitivity of communities, otherwise their vulnerability (especially to global change) could be poorly estimated.

Comparing artificial intelligence techniques for chlorophyll-a prediction in US lakes

Chlorophyll-a (CHLA) is a key indicator to represent eutrophication status in lakes. In this study, CHLA, total phosphorus (TP), total nitrogen (TN), turbidity (TB), and Secchi depth (SD) collected by the United States Environmental Protection Agency for the National Lakes Assessment in the continental USA were analyzed. Statistical analysis showed that water quality variables in natural lakes have strong patterns of autocorrelations than man-made lakes, indicating the perturbation of anthropogenic stresses on man-made lake ecosystems. Meanwhile, adaptive neuro-fuzzy inference systems (ANFIS) with fuzzy c-mean-clustering algorithm (ANFIS_FC), ANFIS with grid partition method (ANFIS_GP), and ANFIS with subtractive clustering method (ANFIS_SC) were implemented to model CHLA in lakes, and modeling results were compared with the multilayer perceptron neural network models (MLPNN). Results showed that ANFIS_FC models outperformed other models for natural lakes, while for man-made lakes, MLPNN models performed the best. ANFIS_GP models have the lowest accuracies in general. The results indicated that ANFIS models can be screening tools for an overall estimation of CHLA levels of lakes in large scales, especially for natural lakes.

Consistent temperature dependence of functional response parameters and their use in predicting population abundance

Global warming is one of the greatest threats to the persistence of populations: increased metabolic demands should strengthen pairwise species interactions, which could destabilize food webs at the higher organizational levels. Quantifying the temperature dependence of consumer-resource interactions is thus essential for predicting ecological responses to warming. We explored feeding interactions between different predator-prey pairs in controlled-temperature chambers and in a system of naturally heated streams. We found consistent temperature dependence of attack rates across experimental settings, though the magnitude and activation energy of attack rate were specific to each predator, which varied in mobility and foraging mode. We used these parameters along with metabolic rate measurements to estimate energetic efficiency and population abundance with warming. Energetic efficiency accurately estimated field abundance of a mobile predator that struggled to meet its metabolic demands, but was a poor predictor for a sedentary predator that operated well below its energetic limits. Temperature effects on population abundance may thus be strongly dependent on whether organisms are regulated by their own energy intake or interspecific interactions. Given the widespread use of functional response parameters in ecological modelling, reconciling outcomes from laboratory and field studies increases the confidence and precision with which we can predict warming impacts on natural systems.

Predator traits determine food-web architecture across ecosystems

Predator-prey interactions in natural ecosystems generate complex food webs that have a simple universal body-size architecture where predators are systematically larger than their prey. Food-web theory shows that the highest predator-prey body-mass ratios found in natural food webs may be especially important because they create weak interactions with slow dynamics that stabilize communities against perturbations and maintain ecosystem functioning. Identifying these vital interactions in real communities typically requires arduous identification of interactions in complex food webs. Here, we overcome this obstacle by developing predator-trait models to predict average body-mass ratios based on a database comprising 290 food webs from freshwater, marine and terrestrial ecosystems across all continents. We analysed how species traits constrain body-size architecture by changing the slope of the predator-prey body-mass scaling. Across ecosystems, we found high body-mass ratios for predator groups with specific trait combinations including (1) small vertebrates and (2) large swimming or flying predators. Including the metabolic and movement types of predators increased the accuracy of predicting which species are engaged in high body-mass ratio interactions. We demonstrate that species traits explain striking patterns in the body-size architecture of natural food webs that underpin the stability and functioning of ecosystems, paving the way for community-level management of the most complex natural ecosystems.

Temperature directly and indirectly influences food web structure

Understanding whether and how environmental conditions may impact food web structure at a global scale is central to our ability to predict how food webs will respond to climate change. However, such an understanding is nascent. Using the best resolved available food webs to date, I address whether latitude, temperature, or both, explain the number of species and feeding interactions, the proportion of basal and top species, as well as the degree of omnivory, connectance and the number of trophic levels across food webs. I found that temperature is a more parsimonious predictor of food web structure than latitude. Temperature directly reduces the number of species, the proportion of basal species and the number of interactions while it indirectly increases omnivory levels, connectance and trophic level through its direct effects on the fraction and number of basal species. While direct impacts of temperature are routinely taken into account to predict how ecosystems may respond to global climate change, indirect effects have been largely overlooked. These results thus suggest that food webs may be affected by a combination of biotic and abiotic conditions, both directly and indirectly, in a changing world.

Future Options for Sewage and Drainage Systems Three Scenarios for Transitions and Continuity

The challenge of sustainable development requires cities to aim for drastic improvements in the systems that support its vital functions. Innovating these systems can be extremely hard, and might take lots of time. A transparent and democratic strategy is important to guarantee support for change. Such a process should aim at developing consensus regarding a basic vision to guide the process of systems change. This paper sketches future options for the development of sanitation- and urban drainage systems in industrialized economies. It will provide an analysis of relevant trends for sewage system innovation. In history, sewage systems have emerged from urban sewage and precipitation removal systems, to urban sewage and precipitation removal and cleaning systems. The challenge for the future is recovering energy and resources from sewage systems while maintaining/improving its sanitary service and lowering its emissions.

Predictability of the impact of multiple stressors on the keystone species Daphnia

Eutrophication and climate change are two of the most pressing environmental issues affecting up to 50% of aquatic ecosystems worldwide. Mitigation strategies to reduce the impact of environmental change are complicated by inherent difficulties of predicting the long-term impact of multiple stressors on natural populations. Here, we investigated the impact of temperature, food levels and carbamate insecticides, in isolation and in combination, on current and historical populations of the freshwater grazer Daphnia. We used common garden and competition experiments on historical and modern populations of D. magna ‘resurrected’ from a lake with known history of anthropogenic eutrophication and documented increase in ambient temperature over time. We found that these populations response dramatically differed between single and multiple stressors. Whereas warming alone induced similar responses among populations, warming combined with insecticides or food limitation resulted in significantly lower fitness in the population historically exposed to pesticides. These results suggest that the negative effect of historical pesticide exposure is magnified in the presence of warming, supporting the hypothesis of synergism between chemical pollution and other stressors.

Stabilization of High-Organic-Content Water Treatment Sludge by Pyrolysis

Water treatment sludge from algal blooms were analyzed and compared with general water treatment sludge as the pyrolysis temperature was varied from 300 °C to 900° C. Elemental analysis showed that the water treatment sludge in the eutrophication region has ~12% carbon content, higher than that (8.75%) of general water treatment sludge. X-ray diffraction (XRD) analysis of both types of sludge showed that amorphous silica changed to quartz and weak crystalline structures like kaolinite or montmorillonite were decomposed and changed into stronger crystalline forms like albite. Fourier transform infrared spectroscopy (FT-IR) peaks of humic/fulvic acid that indicated the affinity to combine with heavy metals disappeared above 700 °C. Toxicity characteristic leaching procedure (TCLP), conducted to determine the heavy metal leaching amount of pyrolyzed water treatment sludge, showed the lowest value of 5.7 mg/kg at 500 °C when the humic acid was not decomposed. At 500 °C, the heavy metal leaching ratio to the heavy metal content of high organic content water treatment sludge and low organic content water treatment sludge were 1.87% and 3.19%, respectively, and the water treatment sludge of higher organic content was more stable. In other words, pyrolysis of water treatment sludge with high organic content at 500 °C increases the inorganic matter crystallinity and heavy metal leaching stability.

Temperature-driven selection on metabolic traits increases the strength of an algal-grazer interaction in naturally warmed streams

Trophic interactions are important determinants of the structure and functioning of ecosystems. Because the metabolism and consumption rates of ectotherms increase sharply with temperature, there are major concerns that global warming will increase the strength of trophic interactions, destabilizing food webs, and altering ecosystem structure and function. We used geothermally warmed streams that span an 11°C temperature gradient to investigate the interplay between temperature-driven selection on traits related to metabolism and resource acquisition, and the interaction strength between the keystone gastropod grazer, Radix balthica, and a common algal resource. Populations from a warm stream (~28°C) had higher maximal metabolic rates and optimal temperatures than their counterparts from a cold stream (~17°C). We found that metabolic rates of the population originating from the warmer stream were higher across all measurement temperatures. A reciprocal transplant experiment demonstrated that the interaction strengths between the grazer and its algal resource were highest for both populations when transplanted into the warm stream. In line with the thermal dependence of respiration, interaction strengths involving grazers from the warm stream were always higher than those with grazers from the cold stream. These results imply that increases in metabolism and resource consumption mediated by the direct, thermodynamic effects of higher temperatures on physiological rates are not mitigated by metabolic compensation in the long term, and suggest that warming could increase the strength of algal-grazer interactions with likely knock-on effects for the biodiversity and productivity of aquatic ecosystems.