Balancing multiple management objectives as climate change transforms ecosystems.

As climate change facilitates significant and persistent ecological transformations, managing ecosystems according to historical baseline conditions may no longer be feasible. The Resist-Accept-Direct (RAD) framework can guide climate-informed management interventions, but in its current implementations RAD has not yet fully accounted for potential tradeoffs between multiple - sometimes incompatible - ecological and societal goals. Key scientific challenges for informing climate-adapted ecosystem management include (i) advancing our predictive understanding of transformations and their socioecological impacts under novel climate conditions, and (ii) incorporating uncertainty around trajectories of ecological change and the potential success of RAD interventions into management decisions. To promote the implementation of RAD, practitioners can account for diverse objectives within just and equitable participatory decision-making processes.

Extreme precipitation promotes invasion in managed grasslands.

Climate change is increasing the frequency and intensity of extreme events like drought and flooding, which threaten to amplify other global change drivers such as species invasion. We investigate the effect of wet and dry extreme precipitation regimes on invasive species' abundances in northern tallgrass prairies. Because soil moisture is a key determinant of prairie composition, theory and evidence suggest drought conditions will hinder invasion, whereas wetter conditions will enhance invasion. To test this hypothesis, we explored the effect of precipitation on invasive plant species abundance from 2010 to 2019 in 25 managed prairies using observations from 267 transects comprising 6675 plots throughout western Minnesota, USA. We estimated how increases in the number of extremely wet or dry months in a year altered overall invasive species abundance and the abundance of the highly invasive grasses Poa pratensis and Bromus inermis. We found that a greater occurrence of abnormally wet months increased invasive species abundance but found mixed evidence that abnormally dry conditions hindered invasion. Further, more moderately wet and dry months reduced native grass abundance. Together, these results suggest that more frequent extremely wet months may intensify invasive dominance and that dry months may not counterbalance these trends. Given the considerable uncertainty still surrounding the interactive effects of climate change and invasion on native plant communities, this research represents an important step toward quantifying the complex influence of precipitation extremes on invasion dynamics in managed ecosystems of critical conservation concern.

Clarifying the effect of biodiversity on productivity in natural ecosystems with longitudinal data and methods for causal inference.

Causal effects of biodiversity on ecosystem functions can be estimated using experimental or observational designs - designs that pose a tradeoff between drawing credible causal inferences from correlations and drawing generalizable inferences. Here, we develop a design that reduces this tradeoff and revisits the question of how plant species diversity affects productivity. Our design leverages longitudinal data from 43 grasslands in 11 countries and approaches borrowed from fields outside of ecology to draw causal inferences from observational data. Contrary to many prior studies, we estimate that increases in plot-level species richness caused productivity to decline: a 10% increase in richness decreased productivity by 2.4%, 95% CI [-4.1, -0.74]. This contradiction stems from two sources. First, prior observational studies incompletely control for confounding factors. Second, most experiments plant fewer rare and non-native species than exist in nature. Although increases in native, dominant species increased productivity, increases in rare and non-native species decreased productivity, making the average effect negative in our study. By reducing the tradeoff between experimental and observational designs, our study demonstrates how observational studies can complement prior ecological experiments and inform future ones.

Decision-making under uncertainty for species introductions into ecological networks.

Ecological communities are increasingly subject to natural and human-induced additions of species, as species shift their ranges under climate change, are introduced for conservation and are unintentionally moved by humans. As such, decisions about how to manage ecosystems subject to species introductions and considering multiple management objectives need to be made. However, the impacts of gaining new species on ecological communities are difficult to predict due to uncertainty in introduced species characteristics, the novel interactions that will be produced by that species, and the recipient ecosystem structure. Drawing on ecological and conservation decision theory, we synthesise literature into a conceptual framework for species introduction decision-making based on ecological networks in high-uncertainty contexts. We demonstrate the application of this framework to a theoretical decision surrounding assisted migration considering both biodiversity and ecosystem service objectives. We show that this framework can be used to evaluate trade-offs between outcomes, predict worst-case scenarios, suggest when one should collect additional data, and allow for improving knowledge of the system over time.

Merging theory and experiments to predict and understand coextinctions.

In an era of mass extinction, predicting the consequences of species loss has become a priority for ecologists. Extinction of one species can trigger the loss of dependent species, sometimes leading to cascades of extinctions. Simulations predict that cascading extinctions should be commonplace, but empirical observations of extinction cascades rarely match those predicted by simulation. By contrast, species-removal field experiments have yielded surprises, such as novel interactions following removals. Thus, given this mismatch, the true predictive value of extinction simulation studies is unknown. We explore the value of validating extinction simulations with observational and experimental studies. We propose a new framework that unites both approaches to studying extinction cascades, and which reveals new opportunities to couple theory and data.

Invasive species do not exploit early growing seasons in burned tallgrass prairies.

Invasive species management is key to conserving critically threatened native prairie ecosystems. While prescribed burning is widely demonstrated to increase native diversity and suppress invasive species, elucidating the conditions under which burning is most effective remains an ongoing focus of applied prairie ecology research. Understanding how conservation management interacts with climate is increasingly pressing, because climate change is altering weather conditions and seasonal timing around the world. Increasingly early growing seasons due to climate change are shifting the timing and availability of resources and niche space, which may disproportionately advantage invasive species and influence the outcome of burning. We estimated the effects of burning, start time of the growing season, and their interaction on invasive species relative cover and frequency, two metrics for species abundance and dominance. We used 25 observed prairie sites and 853 observations of 267 transects spread throughout Minnesota, USA from 2010 to 2019 to conduct our analysis. Here, we show that burning reduced the abundance of invasive cool-season grasses, leading to reduced abundance of invasive species as a whole. This reduction persisted over time for invasive cover but quickly waned for their frequency of occurrence. Additionally, and contrary to expectations that early growing season starts benefit invasive species, we found evidence that later growing season starts increased the abundance of some invasive species. However, the effects of burning on plant communities were largely unaltered by the timing of the growing season, although earlier growing season starts weakened the effectiveness of burning on Kentucky bluegrass (Poa pratensis) and smooth brome (Bromus inermis), two of the most dominant invasive species in the region. Our results suggest that prescribed burning will likely continue to be a useful conservation tool in the context of earlier growing season starts, and that changes to growing season timing will not be a primary mechanism driving increased invasion due to climate change in these ecosystems. We propose that future research seek to better understand abiotic controls on invasive species phenology in managed systems and how burning intensity and timing interact with spring conditions.

Analyzing ecosystem services as part of ecological networks in three salt marsh ecosystems.

Biodiversity plays important roles in nature's contributions to people (i.e., ecosystem services), but the critical details of how biodiversity contributes are challenging to determine. Efforts to identify the components of an ecosystem that provide services have improved our understanding of which species, functional groups, population, or habitats directly provide services. However, species do not exist in isolation and considerably less is known about how species indirectly influence ecosystem services through interacting with those species directly providing services. This uncertainty is even greater when considering that species interact in complex networks. As such, detailed analyses of species interdependencies are rarely included in ecosystem services assessments or conservation decisions. To date, most studies on food webs and on ecosystem services have developed largely in parallel for many services, but these fields and data are ripe for empirical integration. To further this integration, we compiled data sets that linked three existing ecological networks to seven ecosystem functions and services: wave attenuation, shoreline stabilization, carbon sequestration, water filtration, fisheries, birdwatching, and waterfowl hunting. We leveraged high-resolution ecological interaction network data sets from three coastal salt marsh ecosystems including detailed species information (e.g., consumer strategy, body size, biomass) on several hundred species from Carpinteria Salt Marsh in California, USA, and for Estero de Punta Banda and Bahia Falsa in Baja, Mexico from Hechinger et al. (2011). Through an extensive literature synthesis and use of citizen science data, we identified which species in the Hechinger et al. (2011) data provided each ecosystem services directly. We augmented the Hechinger et al. (2011) data published in Ecology, particularly the link (or edge) list to include species-service links to indicate a species providing a service, in which species are listed as "Resources" and services are listed as "Consumers." Connecting these data to the previously published ecological networks with species interactions (i.e., trophic, parasitism) formed a topological network with species and service nodes. We also provided a protocol for assigning services to ecological networks that can be used in other ecosystems. This data set provides a step toward advancing the knowledge of important supporting species for ecosystem services and to developing new ecological network methods for ecosystem services. There are no copyright restrictions; please cite this data paper when the data are used in publications.

Conceptualizing ecosystem services using social-ecological networks.

Social-ecological networks (SENs) represent the complex relationships between ecological and social systems and are a useful tool for analyzing and managing ecosystem services. However, mainstreaming the application of SENs in ecosystem service research has been hindered by a lack of clarity about how to match research questions to ecosystem service conceptualizations in SEN (i.e., as nodes, links, attributes, or emergent properties). Building from different disciplines, we propose a typology to represent ecosystem service in SENs and identify opportunities and challenges of using SENs in ecosystem service research. Our typology provides guidance for this growing field to improve research design and increase the breadth of questions that can be addressed with SEN to understand human-nature interdependencies in a changing world.

Grand challenges in biodiversity-ecosystem functioning research in the era of science-policy platforms require explicit consideration of feedbacks.

Feedbacks are an essential feature of resilient socio-economic systems, yet the feedbacks between biodiversity, ecosystem services and human wellbeing are not fully accounted for in global policy efforts that consider future scenarios for human activities and their consequences for nature. Failure to integrate feedbacks in our knowledge frameworks exacerbates uncertainty in future projections and potentially prevents us from realizing the full benefits of actions we can take to enhance sustainability. We identify six scientific research challenges that, if addressed, could allow future policy, conservation and monitoring efforts to quantitatively account for ecosystem and societal consequences of biodiversity change. Placing feedbacks prominently in our frameworks would lead to (i) coordinated observation of biodiversity change, ecosystem functions and human actions, (ii) joint experiment and observation programmes, (iii) more effective use of emerging technologies in biodiversity science and policy, and (iv) a more inclusive and integrated global community of biodiversity observers. To meet these challenges, we outline a five-point action plan for collaboration and connection among scientists and policymakers that emphasizes diversity, inclusion and open access. Efforts to protect biodiversity require the best possible scientific understanding of human activities, biodiversity trends, ecosystem functions and-critically-the feedbacks among them.

Causal assumptions and causal inference in ecological experiments.

Causal inferences from experimental data are often justified based on treatment randomization. However, inferring causality from data also requires complementary causal assumptions, which have been formalized by scholars of causality but not widely discussed in ecology. While ecologists have recognized challenges to inferring causal relationships in experiments and developed solutions, they lack a general framework to identify and address them. We review four assumptions required to infer causality from experiments and provide design-based and statistically based solutions for when these assumptions are violated. We conclude that there is no clear demarcation between experimental and non-experimental designs. This insight can help ecologists design better experiments and remove barriers between experimental and observational scholarship in ecology.

On the sensitivity of food webs to multiple stressors.

Evaluating the effects of multiple stressors on ecosystems is becoming increasingly vital with global changes. The role of species interactions in propagating the effects of stressors, although widely acknowledged, has yet to be formally explored. Here, we conceptualise how stressors propagate through food webs and explore how they affect simulated three-species motifs and food webs of the Canadian St. Lawrence System. We find that overlooking species interactions invariably underestimate the effects of stressors, and that synergistic and antagonistic effects through food webs are prevalent. We also find that interaction type influences a species' susceptibility to stressors; species in omnivory and tri-trophic food chain interactions in particular are sensitive and prone to synergistic and antagonistic effects. Finally, we find that apex predators were negatively affected and mesopredators benefited from the effects of stressors due to their trophic position in the St. Lawrence System, but that species sensitivity is dependent on food web structure. In conceptualising the effects of multiple stressors on food webs, we bring theory closer to practice and show that considering the intricacies of ecological communities is key to assess the net effects of stressors on species.

Biodiversity as insurance: from concept to measurement and application.

Biological insurance theory predicts that, in a variable environment, aggregate ecosystem properties will vary less in more diverse communities because declines in the performance or abundance of some species or phenotypes will be offset, at least partly, by smoother declines or increases in others. During the past two decades, ecology has accumulated strong evidence for the stabilising effect of biodiversity on ecosystem functioning. As biological insurance is reaching the stage of a mature theory, it is critical to revisit and clarify its conceptual foundations to guide future developments, applications and measurements. In this review, we first clarify the connections between the insurance and portfolio concepts that have been used in ecology and the economic concepts that inspired them. Doing so points to gaps and mismatches between ecology and economics that could be filled profitably by new theoretical developments and new management applications. Second, we discuss some fundamental issues in biological insurance theory that have remained unnoticed so far and that emerge from some of its recent applications. In particular, we draw a clear distinction between the two effects embedded in biological insurance theory, i.e. the effects of biodiversity on the mean and variability of ecosystem properties. This distinction allows explicit consideration of trade-offs between the mean and stability of ecosystem processes and services. We also review applications of biological insurance theory in ecosystem management. Finally, we provide a synthetic conceptual framework that unifies the various approaches across disciplines, and we suggest new ways in which biological insurance theory could be extended to address new issues in ecology and ecosystem management. Exciting future challenges include linking the effects of biodiversity on ecosystem functioning and stability, incorporating multiple functions and feedbacks, developing new approaches to partition biodiversity effects across scales, extending biological insurance theory to complex interaction networks, and developing new applications to biodiversity and ecosystem management.

How complementarity and selection affect the relationship between ecosystem functioning and stability.

The biotic mechanisms underlying ecosystem functioning and stability have been extensively-but separately-explored in the literature, making it difficult to understand the relationship between functioning and stability. In this study, we used community models to examine how complementarity and selection, the two major biodiversity mechanisms known to enhance ecosystem biomass production, affect ecosystem stability. Our analytic and simulation results show that although complementarity promotes stability, selection impairs it. The negative effects of selection on stability operate through weakening portfolio effects and selecting species that have high productivity but low tolerance to perturbations ("risk-prone" species). In contrast, complementarity enhances stability by increasing portfolio effects and reducing the relative abundance of risk-prone species. Consequently, ecosystem functioning and stability exhibit either a synergy, if complementarity effects prevail, or trade-off, if selection effects prevail. Across species richness levels, ecosystem functioning and stability tend to be positively related, but negative relationships can occur when selection co-varies with richness. Our findings provide novel insights for understanding the functioning-stability relationship, with potential implications for both ecological research and ecosystem management.

An ecological network approach to predict ecosystem service vulnerability to species losses.

Human-driven threats are changing biodiversity, impacting ecosystem services. The loss of one species can trigger secondary extinctions of additional species, because species interact-yet the consequences of these secondary extinctions for services remain underexplored. Herein, we compare robustness of food webs and the ecosystem services (hereafter 'services') they provide; and investigate factors determining service responses to secondary extinctions. Simulating twelve extinction scenarios for estuarine food webs with seven services, we find that food web and service robustness are highly correlated, but that robustness varies across services depending on their trophic level and redundancy. Further, we find that species providing services do not play a critical role in stabilizing food webs - whereas species playing supporting roles in services through interactions are critical to the robustness of both food webs and services. Together, our results reveal indirect risks to services through secondary species losses and predictable differences in vulnerability across services.

Scaling up biodiversity-ecosystem functioning relationships: the role of environmental heterogeneity in space and time.

The biodiversity and ecosystem functioning (BEF) relationship is expected to be scale-dependent. The autocorrelation of environmental heterogeneity is hypothesized to explain this scale dependence because it influences how quickly biodiversity accumulates over space or time. However, this link has yet to be demonstrated in a formal model. Here, we use a Lotka-Volterra competition model to simulate community dynamics when environmental conditions vary across either space or time. Species differ in their optimal environmental conditions, which results in turnover in community composition. We vary biodiversity by modelling communities with different sized regional species pools and ask how the amount of biomass per unit area depends on the number of species present, and the spatial or temporal scale at which it is measured. We find that more biodiversity is required to maintain functioning at larger temporal and spatial scales. The number of species required increases quickly when environmental autocorrelation is low, and slowly when autocorrelation is high. Both spatial and temporal environmental heterogeneity lead to scale dependence in BEF, but autocorrelation has larger impacts when environmental change is temporal. These findings show how the biodiversity required to maintain functioning is expected to increase over space and time.

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'.