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As climate change increasingly affects biodiversity and ecosystem services, a key challenge in ecology is accurate attribution of these impacts. Though experimental studies have greatly advanced our understanding of climate change impacts on ecological systems, experimental results are difficult to generalize to real-world scenarios. To better capture realized impacts, ecologists can use observational data. Disentangling cause and effect using observational data, however, requires careful research design. Here we describe advances in causal inference that can improve climate change attribution in observational settings. Our framework includes five steps: 1) describe the theoretical foundation, 2) choose appropriate observational data sets, 3) design a causal inference analysis, 4) estimate a counterfactual scenario, and 5) evaluate assumptions and results using robustness checks. We then demonstrate this framework using a case study focused on detecting climate change impacts on whitebark pine growth in California’s Sierra Nevada. We conclude with a discussion of challenges and frontiers in ecological climate change attribution. Our aim is to provide an accessible foundation for applying observational causal inference to climate change attribution in ecology. 

In ecology, multifunctionality metrics measure the simultaneous performance of multiple ecosystem functions. If species diversity describes the variety of species that together build the ecosystem, multifunctionality attempts to describe the variety of functions these species perform. A range of methods have been proposed to quantify multifunctionality, successively attempting to alleviate problems that have been identified with the previous methods. This has led to a proliferation of more‐or‐less closely related metrics which, however, lack an overarching theoretical framework. Here we borrow from the comprehensive framework of species diversity to derive a new metric of multifunctionality. Analogously to the effective number of species used to quantify species diversity, the metric we propose is influenced both by the number of functions as well as, crucially, the evenness of performance levels across functions. In addition, the effective multifunctionality also considers the average level at which the functions are performed. The result is a measure of the cumulative performance of the system were all functions provided equally. The framework allows for the inclusion of the correlation structure among functions, thus allowing it to account for non‐independence between functions. We show that the average metric is a special case of the newly proposed metric when all functions are uncorrelated and performed at equal levels. We hope that by providing a new metric of multifunctionality anchored in the rigorous framework of species diversity based on effective numbers, we will overcome the considerable skepticism that the larger community of ecologists has built against indices of multifunctionality. We thereby hope to help popularize this important concept which, like biological diversity, describes a fundamental property of ecosystems and thus lies at the heart of ecology. 

Abstract Invasive consumers can cause extensive ecological damage to native communities but effects on ecosystem resilience are less understood. Here, we use drone surveys, manipulative experiments, and mathematical models to show how feral hogs reduce resilience in southeastern US salt marshes by dismantling an essential marsh cordgrass-ribbed mussel mutualism. Mussels usually double plant growth and enhance marsh resilience to extreme drought but, when hogs invade, switch from being essential for plant survival to a liability; hogs selectively forage in mussel-rich areas leading to a 50% reduction in plant biomass and slower post-drought recovery rate. Hogs increase habitat fragmentation across landscapes by maintaining large, disturbed areas through trampling of cordgrass during targeted mussel consumption. Experiments and climate-disturbance recovery models show trampling alone slows marsh recovery by 3x while focused mussel predation creates marshes that may never recover from large-scale disturbances without hog eradication. Our work highlights that an invasive consumer can reshape ecosystems not just via competition and predation, but by disrupting key, positive species interactions that underlie resilience to climatic disturbances. 

Abstract 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. 

Human activities are fundamentally altering biodiversity. Projections of declines at the global scale are contrasted by highly variable trends at local scales, suggesting that biodiversity change may be spatially structured. Here, we examined spatial variation in species richness and composition change using more than 50,000 biodiversity time series from 239 studies and found clear geographic variation in biodiversity change. Rapid compositional change is prevalent, with marine biomes exceeding and terrestrial biomes trailing the overall trend. Assemblage richness is not changing on average, although locations exhibiting increasing and decreasing trends of up to about 20% per year were found in some marine studies. At local scales, widespread compositional reorganization is most often decoupled from richness change, and biodiversity change is strongest and most variable in the oceans. 

Abstract Eutrophication is a widespread environmental change that usually reduces the stabilizing effect of plant diversity on productivity in local communities. Whether this effect is scale dependent remains to be elucidated. Here, we determine the relationship between plant diversity and temporal stability of productivity for 243 plant communities from 42 grasslands across the globe and quantify the effect of chronic fertilization on these relationships. Unfertilized local communities with more plant species exhibit greater asynchronous dynamics among species in response to natural environmental fluctuations, resulting in greater local stability (alpha stability). Moreover, neighborhood communities that have greater spatial variation in plant species composition within sites (higher beta diversity) have greater spatial asynchrony of productivity among communities, resulting in greater stability at the larger scale (gamma stability). Importantly, fertilization consistently weakens the contribution of plant diversity to both of these stabilizing mechanisms, thus diminishing the positive effect of biodiversity on stability at differing spatial scales. Our findings suggest that preserving grassland functional stability requires conservation of plant diversity within and among ecological communities.