Publications

Anticipating precipitation (PPT) extremes across sub-Saharan Africa can help mobilize interventions, trigger anticipatory actions, and promote beneficial actions like water harvesting. Reliable crop model forecasts can help identify when and where food aid interventions can be most beneficial. To date, however, there has been little research evaluating the utility of rainfall forecasts. This study, therefore, assesses the efficacy of the Subseasonal Consortium database (SubC) for use in a regional crop water balance model—the water requirement satisfaction index (WRSI)—in east Africa. We find that combining two dekads (20 d) of statistically downscaled and bias-corrected SubC PPT data with climatological information delivers improved estimates of end-of-season conditions over a 17 year test period. Our results show that SubC forecasts provide a 35%–55% reduction in EOS WRSI root mean squared error in 60% of the east African agropastoral areas during the short rains, with the highest accuracy being in areas that are most vulnerable to inconsistent PPT timing and quantities. Across the 17 tested seasons, 1999/00–2015/16, use of the SubC either improved or did not degrade the accuracy of WRSI prediction compared to a benchmark model for over 70% of the seasons and for 90% of the study region. In general, the improved accuracy provided by two dekads of SubC forecast is nearly equivalent to what can be attained with one dekad of a ‘perfect’ forecast (i.e. observation data). In effect, a 20 day forecast provides a 10 day advance in our early warning capabilities. During extreme events, such as during the 2005/2006 drought in east Africa, the SubC-driven WRSI could provide advanced warning of poor cropping conditions and potential crop failure up to 3 months before the end of the season. Overall, these improvements provide earlier and more accurate estimates of the likely seasonal water balance outcomes, and allow for the identification of locations where interventions may be needed.

We propose and analyze the application of statistical functional depth metrics for the selection of extreme scenarios for realized electric load, as well as solar and wind generation in day-ahead grid planning. Our primary motivation is screening probabilistic scenarios to identify those most relevant for operational risk mitigation. To handle the high-dimensionality of the scenarios across asset classes and intra-day periods, we employ functional measures of depth to sub-select outlying scenarios that are most likely to be the riskiest for the grid operation. We investigate a range of functional depth measures, as well as a range of operational risks, including load shedding, operational costs, reserve shortfalls, and variable renewable energy curtailment. The effectiveness of the proposed screening approach is demonstrated through a case study on the realistic Texas-7k grid.

We examine whether the mobility of a transboundary stock can incentivize a bilateral marine reserve agreement, where one fishing country pays its neighbor to become a marine reserve. The key insight is that precisely because fish move across borders, non-cooperative extraction is likely to be excessive, which lowers fishery profits for both countries. Under our proposal, the payor benefits from the spillover and elimination of non-cooperative extraction, both of which raise fishing profits. The payee benefits from direct financial compensation in exchange for creating the marine reserve. We create a dynamic and spatial game between two countries sharing a transboundary stock. We determine the mobility conditions under which the payor is willing to pay and the payee is willing to accept the payment. We illuminate the biological and economic conditions under which an agreement is incentive-compatible for both countries and conditions under which one or both countries would oppose such an agreement. We find that larval dispersal plays little role in agreement acceptance if adult movement is high. However, if adult movement is low, high larval dispersal can promote agreement acceptance. We also find that this agreement can fully reproduce the conservation and economic benefits gained under a cooperative fishing agreement if adult movement from the fishing patch to the reserve patch is low (≤ 40%) and adult movement to the fishing patch is high (≥ 60%). We discuss the implementation challenges using four real-world transboundary stocks and highlight global issues that bilateral marine reserve agreements can help solve.

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.

Sustainable fisheries are crucial to Indonesia’s economic growth and the nutritional needs and livelihoods of millions of Indonesians. Evidence suggests that Indonesia's fisheries have yet more to offer. Key regulatory instruments and strategic documents—including the Medium-Term National Development Plan 2020-2024 and Indonesia’s Ocean Policy (Presidential Regulation 16/2017)—outline targets for the fisheries sector to deliver growth, jobs, food security, and government and export revenues. An important target is the goal of increasing total fishery production by one-third. Achieving these targets will require policies and investments that align interests: short- and long-term interests, industry and regulator interests, and national and sub-national interests. This report examines policy options to support higher-performing fisheries, defined as those fisheries that deliver maximum sustainable potential in line with the Government of Indonesia’s goals. The government is taking important steps towards a high-performing fisheries sector with reforms such as Penangkapan Ikan Terukur, or Quota-Based Sustainable Fisheries, introduced by the Ministry of Marine Affairs and Fisheries (MMAF) at the end of 2021 and stipulated by Government Regulation No.11/2023. This policy, which would see fishers or firms given well-defined harvest allocations in return for meeting certain conditions, represents a shift to align incentives for greater economic and social returns from fisheries. This policy, along with other enhancements in governance and management capacity underway, offer opportunities for important gains. The report quantifies the costs and benefits of management enhancements and considers policy measures that could contribute towards the realization of these benefits. A bioeconomic model was developed focusing on three demonstration fisheries (skipjack tuna, snapper-grouper, and scads) spanning three fishery management areas (WPP-714, WPP-715, and WPP-718) that together encompass most of Eastern Indonesia. These fisheries have contrasting biological, commercial, and food security characteristics, enabling the costs and benefits of management reforms to be examined under a range of scenarios. Fisheries were selected based on their: (1) overall significance (value and volume); (2) representativeness of multiple government objectives (e.g., food security and export earnings); and (3) analytical tractability and data availability. Four stylized levels of management performance were modeled: (i) lowperforming; (ii) moderately-well performing; (iii) high performing; and (iv) very high performing. Higher performing fisheries were defined as those with the ability to match fishing capacity and effort with stated management objectives (e.g., to control harvests in line with reference points such as maximum sustainable yield) and to maximize efficiency (i.e., maximize the harvest revenues retained after accounting for the costs of fishing effort). Modeling results were complemented with detailed insights from fishery stakeholder consultations including government, private sector, academia, and civil society.

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.