Unraveling complex causal processes that affect sustainability requires more integration between empirical and modeling approaches.

Scientists seek to understand the causal processes that generate sustainability problems and determine effective solutions. Yet, causal inquiry in nature-society systems is hampered by conceptual and methodological challenges that arise from nature-society interdependencies and the complex dynamics they create. Here, we demonstrate how sustainability scientists can address these challenges and make more robust causal claims through better integration between empirical analyses and process- or agent-based modeling. To illustrate how these different epistemological traditions can be integrated, we present four studies of air pollution regulation, natural resource management, and the spread of COVID-19. The studies show how integration can improve empirical estimates of causal effects, inform future research designs and data collection, enhance understanding of the complex dynamics that underlie observed temporal patterns, and elucidate causal mechanisms and the contexts in which they operate. These advances in causal understanding can help sustainability scientists develop better theories of phenomena where social and ecological processes are dynamically intertwined and prior causal knowledge and data are limited. The improved causal understanding also enhances governance by helping scientists and practitioners choose among potential interventions, decide when and how the timing of an intervention matters, and anticipate unexpected outcomes. Methodological integration, however, requires skills and efforts of all involved to learn how members of the respective other tradition think and analyze nature-society systems.

Empirical evidence of widespread exaggeration bias and selective reporting in ecology.

In many scientific disciplines, common research practices have led to unreliable and exaggerated evidence about scientific phenomena. Here we describe some of these practices and quantify their pervasiveness in recent ecology publications in five popular journals. In an analysis of over 350 studies published between 2018 and 2020, we detect empirical evidence of exaggeration bias and selective reporting of statistically significant results. This evidence implies that the published effect sizes in ecology journals exaggerate the importance of the ecological relationships that they aim to quantify. An exaggerated evidence base hinders the ability of empirical ecology to reliably contribute to science, policy, and management. To increase the credibility of ecology research, we describe a set of actions that ecologists should take, including changes to scientific norms about what high-quality ecology looks like and expectations about what high-quality studies can deliver.

Create a culture of experiments in environmental programs.

Organizations need a better "learning by doing" approach.

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.

The choice of message and messenger to drive behavior change that averts the health impacts of wildfires: an online randomized controlled experiment.

BACKGROUND: To reduce the negative health effects from wildfire smoke exposure, effective risk and health communication strategies are vital. We estimated the behavioral effects from changes in message framing and messenger in public health messages about wildfire smoke on Facebook. METHODS: During September and October 2021, we conducted a preregistered online randomized controlled experiment in Facebook. Adult Facebook users (n = 1,838,100), living in nine wildfire-prone Western U.S. states, were randomly assigned to see one of two ad versions (narrative frame vs. informational frame) from one of two messengers (government vs. academic). We estimated the effects of narrative framing, the messenger, and their interactions on ad click-through rates, a measure of recipient information-seeking behavior. RESULTS: Narrative frame increased click-through rates by 25.3% (95% CI = 22.2, 28.4%), with larger estimated effects among males, recipients in areas with less frequent exposure to heavy wildfire smoke, and in areas where predominant political party affiliation of registered voters was Republican (although not statistically different from predominantly-Democrat areas). The estimated effect from an academic messenger compared to a government messenger was small and statistically nonsignificant (2.2%; 95% CI = - 0.3, 4.7%). The estimated interaction effect between the narrative framing and the academic messenger was also small and statistically nonsignificant (3.9%; 95% CI = - 1.1, 9.1%). CONCLUSIONS: Traditional public service announcements rely heavily on communicating facts (informational framing). Shifting from a fact-focused, informational framing to a story-focused, narrative framing could lead to more effective health communication in areas at risk of wildfires and in public health contexts more broadly. TRIAL REGISTRATION: Date registered: August 19, 2021; Registration DOI: https://doi.org/10.17605/OSF.IO/JMWUF.

Private costs of carbon emissions abatement by limiting beef consumption and vehicle use in the United States.

A popular strategy for mitigating climate change is to persuade or incentivize individuals to limit behaviors associated with high greenhouse gas emissions. In this study, adults in the mid-Atlantic United States bid in an auction to receive compensation for eliminating beef consumption or limiting vehicle use. The auction incentivized participants to reveal their true costs of accepting these limits for periods ranging from one week to one year. Compliance with the conditions of the auction was confirmed via a random field audit of the behavioral changes. The estimated median abatement costs were greater than $600 per tCO2e for beef consumption and $1,300 per tCO2e for vehicle use, values much higher than the price of carbon offsets and most estimates of the social cost of carbon. Although these values may decline over time with experience or broader social adoption, they imply that policies that encourage innovations to reduce the costs of behavior change, such as meat alternatives or emission-free vehicles, may be a more fruitful than those that limit beef consumption or vehicle use.

Paying Americans to take the vaccine-would it help or backfire?

This research investigates the extent to which financial incentives (conditional cash transfers) would induce Americans to opt for vaccination against coronavirus disease of 2019. We performed a randomized survey experiment with a representative sample of 1000 American adults in December 2020. Respondents were asked whether they would opt for vaccination under one of three incentive conditions ($1000, $1500, or $2000 financial incentive) or a no-incentive condition. We find that-without coupled financial incentives-only 58 per cent of survey respondents would elect for vaccination. A coupled financial incentive yields an 8-percentage-point increase in vaccine uptake relative to this baseline. The size of the cash transfer does not dramatically affect uptake rates. However, incentive responses differ dramatically by demographic group. Republicans were less responsive to financial incentives than the general population. For Black and Latino Americans especially, very large financial incentives may be counter-productive.

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.

Conservation outreach that acknowledges human contributions to climate change does not inhibit action by U.S. farmers: Evidence from a large randomized controlled trial embedded in a federal program on soil health.

Technologies and practices that reduce the environmental impacts of US agriculture are well documented. Less is known about how best to encourage their adoption. We report on the results of a large randomized controlled trial conducted with nearly 10,000 agricultural producers in the United States. The experiment was embedded in US Department of Agriculture outreach efforts to improve soil conservation practices. USDA varied the content of mailings to test two sets of competing theories about outreach to agricultural producers. Contrary to conventional wisdom, we find no evidence that acknowledging the link between climate change and agricultural production discourages conservation action. Furthermore, we find that producers who were invited to a webinar were less likely to take any action to learn more about conservation practices than producers who were not told about the webinar, a result that runs counter to the popular wisdom that offering more options leads to more action.

Community-based monitoring to facilitate water management by local institutions in Costa Rica.

Water scarcity is a global problem that can be compounded by inefficient water management, including underinvestment in infrastructure, underpricing of water use, and underenforcement of user rules. Here, we explore whether these inefficiencies can be reduced in rural Costa Rica via an externally driven community monitoring program (i.e., a program initiated by an outside organization and run by citizens). The monitoring program aimed to reduce groundwater extraction from aquifers, as well as to improve water quality and user satisfaction, by supplying additional information about field conditions and additional scrutiny of user and management authority activities and by fostering citizen engagement in water management. Using a specially designed smartphone application (app) and WhatsApp, monitors could report weekly on the conditions of the water system, including service disruptions, water quality, leaks, and source contamination. The app automatically compiled the individual reports into a summary report, which was then made available to the community water management committees and water users. The program was randomly implemented in 80 of 161 communities that expressed an interest in participating. One year after the program started, we detect modest, albeit imprecisely estimated, effects of the program in the predicted directions: less groundwater extracted, better water quality, and more satisfied users. Although the estimated effects are imprecise, the monitoring program appears to be equally or more cost effective for reducing groundwater extraction than another program in the same region that encouraged households to adopt water-efficient technologies.

Adoption of community monitoring improves common pool resource management across contexts.

Pervasive overuse and degradation of common pool resources (CPRs) is a global concern. To sustainably manage CPRs, effective governance institutions are essential. A large literature has developed to describe the institutional design features employed by communities that successfully manage their CPRs. Yet, these designs remain far from universally adopted. We focus on one prominent institutional design feature, community monitoring, and ask whether nongovernmental organizations or governments can facilitate its adoption and whether adoption of monitoring affects CPR use. To answer these questions, we implemented randomized controlled trials in six countries. The harmonized trials randomly assigned the introduction of community monitoring to 400 communities, with data collection in an additional 347 control communities. Most of the 400 communities adopted regular monitoring practices over the course of a year. In a meta-analysis of the experimental results from the six sites, we find that the community monitoring reduced CPR use and increased user satisfaction and knowledge by modest amounts. Our findings demonstrate that community monitoring can improve CPR management in disparate contexts, even when monitoring is externally initiated rather than homegrown. These findings provide guidance for the design of future programs and policies intended to develop monitoring capabilities in communities. Furthermore, our harmonized, multisite trial provides sustainability science with a new way to study the complexity of socioecological systems and builds generalizable insights about how to improve CPR management.

Biodiversity conservation as a promising frontier for behavioural science.

Human activities are degrading ecosystems worldwide, posing existential threats for biodiversity and humankind. Slowing and reversing this degradation will require profound and widespread changes to human behaviour. Behavioural scientists are therefore well placed to contribute intellectual leadership in this area. This Perspective aims to stimulate a marked increase in the amount and breadth of behavioural research addressing this challenge. First, we describe the importance of the biodiversity crisis for human and non-human prosperity and the central role of human behaviour in reversing this decline. Next, we discuss key gaps in our understanding of how to achieve behaviour change for biodiversity conservation and suggest how to identify key behaviour changes and actors capable of improving biodiversity outcomes. Finally, we outline the core components for building a robust evidence base and suggest priority research questions for behavioural scientists to explore in opening a new frontier of behavioural science for the benefit of nature and human wellbeing.

PROTOCOL: Residential energy efficiency interventions: An effectiveness systematic review.

This review aims to identify, appraise and synthesise the evidence available on the effectiveness of energy efficiency measure installations, including those bundled with behavioural interventions. The synthesis will estimate the overall impact of these interventions as well as examine possible causes of variation in impacts. We will also attempt to assess the cost-effectiveness of residential energy efficiency interventions.

Conditional cash transfers to alleviate poverty also reduced deforestation in Indonesia.

Solutions to poverty and ecosystem degradation are often framed as conflicting. We ask whether Indonesia's national anti-poverty program, which transfers cash to hundreds of thousands of poor households, reduced deforestation as a side benefit. Although the program has no direct link to conservation, we estimate that it reduced tree cover loss in villages by 30% (95% confidence interval, 10 to 50%). About half of the avoided losses were in primary forests, and reductions were larger when participation density was higher. The economic value of the avoided carbon emissions alone compares favorably to program implementation costs. The program's environmental impact appears to be mediated through channels widely available in developing nations: consumption smoothing, whereby cash substitutes for deforestation as a form of insurance, and consumption substitution, whereby market-purchased goods substitute for deforestation-sourced goods. The results imply that anti-poverty programs targeted at the very poor can help achieve global environmental goals under certain conditions.

Causal inference in coupled human and natural systems.

Coupled human and natural systems (CHANS) are complex, dynamic, interconnected systems with feedback across social and environmental dimensions. This feedback leads to formidable challenges for causal inference. Two significant challenges involve assumptions about excludability and the absence of interference. These two assumptions have been largely unexplored in the CHANS literature, but when either is violated, causal inferences from observable data are difficult to interpret. To explore their plausibility, structural knowledge of the system is requisite, as is an explicit recognition that most causal variables in CHANS affect a coupled pairing of environmental and human elements. In a large CHANS literature that evaluates marine protected areas, nearly 200 studies attempt to make causal claims, but few address the excludability assumption. To examine the relevance of interference in CHANS, we develop a stylized simulation of a marine CHANS with shocks that can represent policy interventions, ecological disturbances, and technological disasters. Human and capital mobility in CHANS is both a cause of interference, which biases inferences about causal effects, and a moderator of the causal effects themselves. No perfect solutions exist for satisfying excludability and interference assumptions in CHANS. To elucidate causal relationships in CHANS, multiple approaches will be needed for a given causal question, with the aim of identifying sources of bias in each approach and then triangulating on credible inferences. Within CHANS research, and sustainability science more generally, the path to accumulating an evidence base on causal relationships requires skills and knowledge from many disciplines and effective academic-practitioner collaborations.

Incentives for climate mitigation in the land use sector-the effects of payment for environmental services on environmental and socioeconomic outcomes in low- and middle-income countries: A mixed-methods systematic review.

Unsustainable practices in the land use sector contribute to climate change through the release of greenhouse gases. Payment for environmental services (PESs) provide economic incentives to reduce the negative environmental impacts of land use and are a popular approach to mitigate climate change in low- and middle-income countries. Some PES programmes also aim to improve socioeconomic outcomes and reduce poverty. This systematic review examines the effect of programmes on environmental and socioeconomic outcomes. We identified 44 quantitative impact evaluations and 60 qualitative studies of PES programmes for inclusion in the review, to assess both the effects of PES and identify context, design and implementation features that may influence PES effectiveness. The studies covered 18 programmes from 12 countries in Latin America and the Caribbean, East Asia and Pacific, South Asia and Sub-Saharan Africa. The review finds that PES may increase household income, reduce deforestation and improve forest cover, but the findings are, however, based on low and very low quality evidence from a small number of programmes and should be treated with caution. Qualitative evidence indicates that several factors influence whether PES programmes are likely to be effective in different contexts and suggests that the inclusion of strong governance structures and the effective targeting of both locations and participants may improve intervention effectiveness. Funders, implementing agencies and researchers should collaborate to develop a coordinated programme of rigorous, mixed-methods impact evaluation implemented across contexts. Until such evidence is available, PES programmes remain a high-risk strategy for climate change mitigation.