Publications

Sharks are among the most threatened groups of exploited fishes, comprising common bycatch across many fisheries. Management efforts intended to safeguard threatened species have increasingly focused on retention bans to reduce bycatch mortality. However, the population effects of such measures remain unevaluated across species. We combined available data from 160 studies providing estimates of at-vessel or post-release mortality for 147 taxa caught by different fishing gears to create random-forest regression models and predict mortality rates for 341 shark species incidentally captured by longlines or gillnets. Smaller-bodied species inhabiting shallow waters were more likely to suffer at-vessel mortality compared to their deep-water counterparts, for which post-release mortality was more likely to occur. We then used results for longlines to simulate the effect of retention bans in reducing fishing mortality to sustainable levels. Our metric consists of the ratio between the proportion of each species' population caught and discarded (PMAX) under a retention ban divided by the fishing mortality (F) predicted to achieve maximum sustainable yield (FMSY). Our calculations show that a retention ban yielded an average ~ three-fold higher PMAX compared to FMSY, with 18% of the species having PMAX/FMSY < 2, 72.3% having 2 < PMAX/FMSY < 5, and 9.7% having PMAX/FMSY > 5. For threatened species, median PMAX/FMSY = 2.28 and non-threatened ones had median PMAX/FMSY = 2.77. Our study shows that retention bans could reduce shark mortality, but must be combined with additional measures to stop overfishing, especially for low-productivity species. 

Marine and coastal tourism deliver economic benefits to coastal communities that far surpass those generated by fisheries, yet its potential contribution to global marine conservation remains underexamined. Marine Protected Areas (MPAs) help restore biodiversity and enhance nearby fisheries, but their direct tourism benefits are not well understood. Here, we estimate the global demand for recreational scuba dive tourism, map the distribution and protection status of all marine dive sites globally, and develop a bioeconomic model to estimate the revenue gains from upgrading unprotected dive sites to fully protected MPAs. We estimate that 33.1 million scuba dives occur annually in marine environments worldwide, with 70% taking place within MPAs. However, only 15% of these MPA-affiliated dive sites are highly or fully protected. We show that designating all unprotected recreational dive sites, representing less than 1% of the global ocean, as highly or fully protected MPAs would improve fish biomass and biodiversity while generating an additional US$2 billion per year in direct tourism revenue (not including economic multipliers). Importantly, 62% of marine diving currently occurs in developing countries, underscoring the potential for dive tourism to support both marine conservation and local livelihoods in regions where such benefits are most needed.

Input subsidies in natural resource sectors are widely believed to deplete the natural capital on which these sectors depend. However, estimating the causal effect of subsidies on resource extraction has been stymied by identification and data challenges. China’s fishing fleet is the world’s largest, and in 2016 the government changed its fuel subsidy policy for distant water vessels to one that increases with predetermined vessel characteristics. Regression discontinuity estimates imply a long-run equilibrium elasticity of fishing hours with respect to fuel subsidies of 2.2, though these estimates exhibit only modest precision according to randomization inference. Back-of-the-envelope calculations suggest that reducing Chinese distant water fuel subsidies by 50% could increase fish stocks across ocean regions by a median of 5.5%.

Aquatic foods hold a unique potential to contribute to a much-needed transformation of food systems thanks to their high nutritional value, cultural significance, and relatively low environmental impact. However, realizing this potential requires a transformative approach to help overcome two grand challenges: sustainably increasing the production of nutritious aquatic foods and ensuring equitable access to these resources. This paper highlights the key recommendations from the White Paper on Challenge 3 (‘Sustainably nourish the global population’) of the United Nations Decade of Ocean Science for Sustainable Development (hereafter, the Ocean Decade), developed by a group of experts under the Vision 2030 process, on the science needed to support a ‘Blue Transformation’. A holistic, interdisciplinary science agenda is proposed, emphasizing strengthened institutional and public–private partnerships, prioritizing the inclusion of small-scale actors, women, and youth, and focusing on delivering science targeted to solve specific challenges. The Ocean Decade provides a platform to catalyse these efforts, fostering a paradigm shift towards inclusive, co-created science. Achieving these goals will enable aquatic food systems to contribute significantly to global food security and the Sustainable Development Goals by 2030.

Stopping deforestation linked to agricultural commodity supply chains is crucial for Amazonian biodiversity protection and climate change mitigation. Remote sensing technologies are essential for monitoring deforestation, providing precise data on land-use changes. However, effective deforestation control requires more than monitoring alone. In this Primer, we explain how remote sensing can be applied to effectively monitor deforestation activities. We further elaborate on what is needed to improve transparency and traceability within commodity supply chains so that we can identify and hold accountable those contributing to forest loss, preventing their products from entering the market. While cross-sector initiatives are transforming approaches to this challenge, greater integration is needed to connect these elements and ensure that forest-risk commodities cease driving deforestation in the Amazon.

Coral reef fisheries are a vital source of nutrients for thousands of nutritionally vulnerable coastal communities around the world. Marine protected areas are regions of the ocean designed to preserve or rehabilitate marine ecosystems and thereby increase reef fish biomass. Here, we evaluate the potential effects of expanding a subset of marine protected areas that allow some level of fishing within their borders (sustainable-use MPAs) to improve the nutrition of coastal communities. We estimate that, depending on site characteristics, expanding sustainable-use MPAs could increase catch by up to 20%, which could help prevent 0.3-2.85 million cases of inadequate micronutrient intake in coral reef nations. Our study highlights the potential add-on nutritional benefits of expanding sustainable-use MPAs in coral reef regions and pinpoints locations with the greatest potential to reduce inadequate micronutrient intake level. These findings provide critical knowledge given international momentum to cover 30% of the ocean with MPAs by 2030 and eradicate malnutrition in all its forms.

The increasing availability of high-resolution climate data has greatly expanded the study of how the climate impacts humans and society. However, the processing of these multi-dimensional datasets poses significant challenges for researchers in this growing field, most of whom are social scientists. This paper introduces stagg, or “space-time aggregator”, a new R package that streamlines three critical components of climate data processing for impacts analysis: nonlinear transformation, spatial and temporal aggregation, and spatial weighting by social or economic variables. The package consolidates the data processing pipeline into a few lines of code, lowering barriers to entry for researchers and facilitating a larger and more diverse research community. The paper provides an overview of stagg's functions, followed by an applied example demonstrating the package's utility in climate impacts research. stagg has the potential to be a valuable tool in generating evidence-based estimates of the likely impacts of future climate change.

The expansion of marine protected areas (MPAs) is a core focus of global conservation efforts, with the “30x30” initiative to protect 30% of the ocean by 2030 serving as a prominent example of this trend. We consider a series of proposed MPA network expansions of various sizes, and we forecast the impact this increase in protection would have on global patterns of fishing effort. We do so by building a predictive machine learning model trained on a global dataset of satellite-based fishing vessel monitoring data, current MPA locations, and spatiotemporal environmental, geographic, political, and economic features. We then use this model to predict future fishing effort under various MPA expansion scenarios compared to a business-as-usual counterfactual scenario that includes no new MPAs. The difference between these scenarios represents the predicted change in fishing effort associated with MPA expansion. We find that regardless of the MPA network objectives or size, fishing effort would decrease inside the MPAs, though by much less than 100%. Moreover, we find that the reduction in fishing effort inside MPAs does not simply redistribute outside—rather, fishing effort outside MPAs would also decline. The overall magnitude of the predicted decrease in global fishing effort principally depends on where networks are placed in relation to existing fishing effort. MPA expansion will lead to a global redistribution of fishing effort that should be accounted for in network design, implementation, and impact evaluation.

The replication crisis in empirical research calls for a more mindful approach to how we apply and report statistical models. For empirical research to have a lasting (policy) impact, these concerns are crucial. In this paper, we present Probabilistic Programming (PP) as a way forward. The PP workflow with an explicit data-generating process enhances the communication of model assumptions, code testing and consistency between theory and estimation. By simplifying Bayesian analysis, it also offers advantages for the interpretation, communication and modelling of uncertainty. We outline the advantages of PP to encourage its adoption in our community.

This paper studies how the North American Free Trade Agreement (NAFTA) affected the wage gap between high and low-paid workers within Mexico, considering internal migration. In low-skilled, labor-abundant developing countries, trade liberalization should theoretically increase the wages of low-skilled workers, decreasing income inequality. However, anecdotal evidence indicates that NAFTA increased the gap between rich and poor in Mexico, and empirical evidence is mixed (Hirte et al. 2020; Brülhart 2011; Bosch and Manacorda 2010; Nicita 2009; Chiquiar 2008; Hanson 2007; Gonzalez-Rivas 2007). Because trade may affect wages differently across regions within the country, accurate measures of wage effects must incorporate internal migration; otherwise, apparent wage convergence or divergence might only reflect a geographic resorting of workers. We evaluate wage changes by considering rural-to-urban migration. We first find a slight decrease in both internal and external migration in the years after NAFTA. Then, we find that all male workers see a wage reduction from trade openness, although the harm of high-wage workers almost doubled that of their counterparts with low wages. NAFTA also mitigated some of the wage differentials between the North and South. In summary, trade liberalization has reduced wage differentials among working-age men in urban areas.

After decades of fits and starts, the ambition to protect 30% of land and sea by 2030 (30x30) (1) is gaining some momentum, but only modest progress has been made. One reason is that signing on to protect 30x30 will be much more costly for some nations than others; many nations facing low costs of conserving have already protected, while other nations foresee enormous costs and are reluctant to sign on. Focusing on the context of marine habitats contained by nation’s exclusive economic zones (EEZs), we propose an alternative approach to meeting these ambitious conservation targets in a way that lowers the costs to all nations: allowing nations to trade their conservation obligations with other nations. Some nations would voluntarily end up conserving more than 30% of their waters and others would end up conserving less, all within well-defined and ecologically informed constraints that ensure protection across marine habitats.

We price the transboundary externality of mobile public bads such as diseases and invasive species. We focus on the marginal cost to country B of an increase in the stock (i.e. an “outbreak”) in country A. These cross-jurisdiction marginal costs depend not only on economic, ecological, and spatial features of both jurisdictions but also on jurisdictions’ strategic reactions to the outbreak. Using a spatial dynamic game, we calculate the “cross-jurisdiction shadow costs” of an outbreak of mobile public bad under the Markov-perfect Nash equilibrium of control efforts. We find that under reasonable conditions, the source country has private incentives to control the outbreak itself, which can lead to a situation where the cross-jurisdiction shadow cost is, in fact, zero. We also derive conditions where a country optimally fails to control the outbreak (for example, damages in that country are small), in which case cross-jurisdiction shadow costs are positive. Finally, we note that since cooperative control of the mobile public bad delivers substantially higher welfare than non-cooperative control, we derive an externality pricing instrument that perfectly internalizes the externality and induces cooperative control among all countries.

Voluntary Sustainability Standards (VSS) are transnational governance instruments that can be leveraged to pursue sustainable development in global value
chains. They have proliferated since the 1990s in terms of their number and the
share of global production they govern. This paper shares some key insights arising from the considerable body of literature that has analysed the role of these
instruments for sustainable production and trade. First, it introduces VSS, traces
the evolution of their adoption and takes stock of the research on their sustainability impacts. Next, some major developments in the VSS realm are discussed,
related to public policy and the emergence of national sustainability standards.
The paper then zooms in on the challenges and limitations of VSS in transforming
value chains towards sustainability, focusing on the shortcomings related to inclusiveness and the problems arising from their proliferation. The paper concludes
by distilling recommendations on overcoming these challenges, especially in light
of recent policy developments, and outlines what different stakeholders can do to
make VSS more effective and inclusive instruments for sustainable value chains.

Credit markets and property rights are fundamental for modern economies, but their implications for the commons are unknown. Using a dynamic model of competitive resource extraction, we show that improving property right security unambiguously increases conservation incentives, but the effect of credit markets on resource extraction effort hinges on the security of property rights. We test these predictions using data on global fisheries, credit markets, and the largest ever marine property rights assignment. We find that property right security reduces resource extraction and that credit market development increases resource extraction under insecure property rights but reduces resource extraction under secure property rights.

Inequities in access to energy efficiency programs for public sector entities such as schools and local government directly impact the communities they serve. Using California as a case study, we assess the distributional justice within energy efficiency programs by investigating disparities in program budgets targeting public sector entities, specifically local governments (cities, n = 417; and counties, n = 58) and kindergarten to 12th grade (K−12) public schools (student ages 5/6 to 17/18 years, n = 58). We employ t-tests and multivariate regressions to investigate potential drivers of differences in program budget including rurality, tax revenues, income, race, and disadvantaged status indicators. Our results show that both local governments and K-12 public schools in more rural counties have lower total program budgets because of their lower population compared to more urban counties. Furthermore, energy efficiency programs in local governments and K-12 public schools in counties with a higher share of disadvantaged communities have a lower budget per capita. For K-12 public schools, counties with a higher proportion of students from lower income households or disadvantaged communities have both lower program budgets overall and per capita. These results highlight inequities in energy efficiency program budgets for local governments and K-12 public schools. Better targeting of programs at rural, low income, and disadvantaged communities is essential to ensure equitable access to energy efficiency program resources across communities and regions.

Understanding the costs and the spatial distribution of health and employment outcomes of low-carbon electricity pathways is critical to enable an equitable transition. We integrate an electricity system planning model (GridPath), a health impact model (InMAP), and a multiregional input–output model to quantify China’s provincial-level impacts of electricity system decarbonization on costs, health outcomes, employment, and labor compensation. We find that even without specific CO2 constraints, declining renewable energy and storage costs enable a 26% decline in CO2 emissions in 2040 compared to 2020 under the Reference scenario. Compared to the Reference scenario, pursuing 2 °C and 1.5 °C compatible carbon emission targets (85% and 99% decrease in 2040 CO2 emissions relative to 2020 levels, respectively) reduces air pollution-related premature deaths from electricity generation over 2020–2040 by 51% and 63%, but substantially increases annual average costs per unit of electricity demand in 2040 (21% and 39%, respectively). While the 2 °C pathway leads to a 3% increase in electricity sector-related net labor compensation, the 1.5 °C pathway results in a 19% increase in labor compensation driven by greater renewable energy deployment. Although disparities in health impacts across provinces narrow as fossil fuels phase out, disparities in labor compensation widen with wealthier East Coast provinces gaining the most in labor compensation because of materials and equipment manufacturing, and offshore wind deployment.

In response to growing scrutiny surrounding commodity-driven deforestation, companies have introduced zero-deforestation commitments (ZDCs) with ambitious environmental and social targets. However, such initiatives may not effectively reduce deforestation if they are not aligned with the spatial extent of remaining forests at risk. They may also fail to avert socio-economic risks if ZDCs do not consider smallholder farmers’ needs. We assess the spatial and functional fit of ZDCs by mapping commodity-driven deforestation and socio-economic risks, and comparing them to the spatial coverage and implementation of ZDCs in the Indonesian palm oil sector. Our study finds that companies’ ZDCs often underperform in four areas: traceability, compliance support for high-risk palm oil mills, transparency, and smallholder inclusion. In 2020, only one-third of companies sourcing from their own mills, and just 6% of those sourcing from external suppliers, achieved full traceability to plantations. Comparing the reach of ZDCs adopted by downstream buyers with those adopted by mill owners located further upstream, we find that high-quality ZDCs from buyers covered 62% of forests at risk, while mill owners’ ZDCs only covered 23% of forests at risk within the mill supply base. In Kalimantan and Papua, the current and future deforestation frontiers, the forests most at risk of conversion were predominantly covered by weak ZDCs lacking in policy comprehensiveness and implementation. Additionally, we find that only 46% of independent smallholder oil palm plots are in mill supply sheds whose owners offer programs and support for independent smallholders, indicating that smallholder inclusion is a significant challenge for ZDC companies. These results highlight the lack of spatial and functional alignment between supply chain policies and their local context as a significant gap in ZDC implementation and a challenge that the EU Deforestation Regulation will face.

As the climate changes, efficient climate policy requires a better understanding of how individuals adapt. Despite extensive research on various climate adaptation frictions, including financial and technological constraints, models of adaptive decision-making assume that agents have perfect information and accurate beliefs about climate. Combining rural household data in Bangladesh with a meteorological measure of dryness, this paper studies the role of individual drought beliefs and their accuracy in irrigation decisions as a key adaptive margin. In a theoretical model, I introduce a behavioral friction to document how heterogeneous beliefs differentially influence responsiveness to the same meteorological signal in dryness. The empirical analysis reveals an asymmetric response to dry shocks in irrigation conditional on the accuracy of prior beliefs. A counterfactual analysis shows lower technology adoption levels and higher monetary losses when beliefs are inaccurate.

Efficiently managing agricultural irrigation is vital for food security today and into the future under climate change. Yet, evaluating agriculture’s hydrological impacts and strategies to reduce them remains challenging due to a lack of field-scale data on crop water consumption. Here, we develop a method to fill this gap using remote sensing and machine learning, and leverage it to assess water saving strategies in California’s Central Valley. We find that switching to lower water intensity crops can reduce consumption by up to 93%, but this requires adopting uncommon crop types. Northern counties have substantially lower irrigation efficiencies than southern counties, suggesting another potential source of water savings. Other practices that do not alter land cover can save up to 11% of water consumption. These results reveal diverse approaches for achieving sustainable water use, emphasizing the potential of sub-field scale crop water consumption maps to guide water management in California and beyond.