Publications

Wildfire activity in the western United States has been increasing since the 1970s, with many fires occurring on land managed by government agencies. Over six million acres of public lands are surrounded by private land and lack road access, making them legally inaccessible to federal and state agencies and potentially constraining management and suppression of wildfires. In this paper, we assemble data on all fires that started on public lands in the western US over the period 1992–2015 and estimate the effect of legal accessibility on fire size. We find that ignitions are 14%–23% more likely to become large (greater than one acre) if they occur on inaccessible land. We provide evidence that this effect may be driven in part by agencies’ inability to conduct fuels management and in part by slower suppression responses on legally inaccessible land. Our results suggest that wildfire prevention and suppression could be bolstered by improved access to public lands and underscore the need for ongoing research on the relationship between land ownership and wildfire.

Estimates of global economic damage caused by carbon dioxide (CO₂) emissions can inform climate policy^1,2,3. The social cost of carbon (SCC) quantifies these damages by characterizing how additional CO₂ emissions today impact future economic outcomes through altering the climate^4,5,6. Previous estimates have suggested that large, warming-driven increases in energy expenditures could dominate the SCC^7,8, but they rely on models^9,10,11 that are spatially coarse and not tightly linked to data^{2,3,6,7,12,13}. Here we show that the release of one ton of CO₂ today is projected to reduce total future energy expenditures, with most estimates valued between −US$3 and −US$1, depending on discount rates. Our results are based on an architecture that integrates global data, econometrics and climate science to estimate local damages worldwide. Notably, we project that emerging economies in the tropics will dramatically increase electricity consumption owing to warming, which requires critical infrastructure planning. However, heating reductions in colder countries offset this increase globally. We estimate that 2099 annual global electricity consumption increases by about 4.5 exajoules (7 per cent of current global consumption) per one-degree-Celsius increase in global mean surface temperature (GMST), whereas direct consumption of other fuels declines by about 11.3 exajoules (7 per cent of current global consumption) per one-degree-Celsius increase in GMST. Our finding of net savings contradicts previous research^7,8, because global data indicate that many populations will remain too poor for most of the twenty-first century to substantially increase energy consumption in response to warming. Importantly, damage estimates would differ if poorer populations were given greater weight¹⁴.

With human food production a major driver of global environmental change, there is increasing recognition of the importance of shifting towards more sustainable dietary patterns. With wholesale dietary change notoriously difficult to implement at scale, various new food analogues have emerged to serve as qualitatively similar (e.g. taste, texture) but lower environmental impact alternatives for existing foods, particularly animal protein. While new foods may have low environmental impacts, very little is known about how reliably new products drive the disadoption (permanently reduced or ceased consumption) of existing foods. Using simple models of the interplay between adoption levels, substitution ratios of new and existing foods, and different products targeted for replacement, we explore the role of food disadoption on the global warming potential of protein consumption by a theoretical human population. We show how counterintuitive changes to the total environmental impacts attributable to food consumption are plausible following widespread uptake of ‘sustainable’ new foods if they do not reliably drive the disadoption of existing high-impact alternatives. Greater empirical evidence of how effectively new foods drive the disadoption of their intended targets is needed to prevent mass development of alternatives that exacerbate the environmental impact of human diets.

Market approaches to environmental conservation, by which mechanisms such as property rights, prices, and contracts are used to advance environmental goals, have gained traction globally in recent decades (1). But in many cases, antiquated rules limit their role in conserving public natural resources. “Use-it-or-lose-it” requirements, together with narrow definitions of eligible “uses,” can preclude environmental groups from participating in markets for natural resources. These restrictions can bias resource management in favor of extractive users, even when conservation interests are willing to pay more to protect resources from development. We argue that acquisition of public natural resource rights for the purpose of withholding them from development should be allowed. Policies should be reformed to include conservation as a legally valid form of “use.” Allowing such “nonuse rights” to public natural resources would enable markets to advance environmental goals, leading to more stable and less contentious outcomes.

A growing number of companies have announced zero-deforestation commitments (ZDCs) to eliminate commodities produced at the expense of forests from their supply chains. Translating these aspirational goals into forest conservation requires forest mapping and monitoring (M&M) systems that are technically adequate and therefore credible, salient so that they address the needs of decision makers, legitimate in that they are fair and unbiased, and scalable over space and time. We identify 12 attributes of M&M that contribute to these goals and assess how two prominent ZDC programs, the Amazon Soy Moratorium and the High Carbon Stock Approach, integrate these attributes into their M&M systems. These programs prioritize different attributes, highlighting fundamental trade-offs in M&M design. Rather than prescribe a one-size-fits-all solution, we provide policymakers and practitioners with guidance on the design of ZDC M&M systems that fit their specific use case and that may contribute to more effective implementation of ZDCs.

Environmental markets are widely prescribed as an alternative to open access regimes for natural resources. We develop a model of dynamic groundwater extraction to demonstrate how a spatial regression discontinuity design that exploits a spatially incomplete market for groundwater rights recovers a lower bound on the market’s net benefit. We apply this estimator to a major aquifer in water-scarce southern California and find that a groundwater market generated substantial net benefits, as capitalized in land values. Heterogeneity analyses point to gains arising in part from rights trading, enabling more efficient water use across sectors. Additional findings suggest that the market increased groundwater levels.

Combining satellite imagery with machine learning (SIML) has the potential to address globalchallenges by remotely estimating socioeconomic and environmental conditions in data-poorregions, yet the resource requirements of SIML limit its accessibility and use. We show that asingle encoding of satellite imagery can generalize across diverse prediction tasks (e.g., forestcover, house price, road length). Our method achieves accuracy competitive with deep neuralnetworks at orders of magnitude lower computational cost, scales globally, delivers labelsuper-resolution predictions, and facilitates characterizations of uncertainty. Since imageencodings are shared across tasks, they can be centrally computed and distributed tounlimited researchers, who need only fit a linear regression to their own ground truth data inorder to achieve state-of-the-art SIML performance.

In 2017 and 2018, wildfires in California burned millions of hectares and caused billions of dollars in structure damages. This paper puts these recent fires in a long-term historical context by assembling four decades of data on wildfires in California. We combine administrative data of structure loss due to wildfire with economic data on replacement costs and spatial data on fire locations and sizes. We find that over the period 1979–2018, wildfires in California have been getting larger and that the trend is accelerating. This same trend is seen in the wildland–urban interface. As well, total structure damage from wildfires has grown steadily during the past four decades. Our conclusion is that the recent California fires are not an anomaly, but rather part of a trend towards larger and increasingly destructive wildfires.

Marine protected areas (MPAs) cover 3–7% of the world's ocean, and international organizations call for 30% coverage by 2030. Although numerous studies show that MPAs produce conservation benefits inside their borders, many MPAs are also justified on the grounds that they confer conservation benefits to the connected populations that span beyond their borders. A network of MPAs covering roughly 20% of the Channel Islands National Marine Sanctuary was established in 2003, with a goal of providing regional conservation and fishery benefits. We used a spatially explicit bioeconomic simulation model and a Bayesian difference-in-difference regression to examine the conditions under which MPAs can provide population-level conservation benefits inside and outside their borders and to assess evidence of those benefits in the Channel Islands. As of 2017, we estimated that biomass densities of targeted fin-fish had a median value 81% higher (90% credible interval: 23–148) inside the Channel Island MPAs than outside. However, we found no clear effect of these MPAs on mean total biomass densities at the population level: estimated median effect was –7% (90% credible interval: –31 to 23) from 2015 to 2017. Our simulation model showed that effect sizes of MPAs of <30% were likely to be difficult to detect (even when they were present); smaller effect sizes (which are likely to be common) were even harder to detect. Clearly, communicating expectations and uncertainties around MPAs is critical to ensuring that MPAs are effective. We provide a novel assessment of the population-level effects of a large MPA network across many different species of targeted fin-fish, and our results offer guidance for communities charged with monitoring and adapting MPAs.

Data sets providing repeated observations of land use at fine spatial scales have enabled a new generation of land-use studies. In the past decade, these analyses have put increasing emphasis on empirical research designs that provide more convincing causal estimates. I review the use of instrumental variables, matching, difference-in-differences, regression discontinuity design, and randomized controlled trials in the recent land-use economics literature, exploring how new data have made possible the use of these research designs. I show that these estimators have produced different results than were obtained with traditional approaches and have provided new insights into important land-use policy issues such as additionality and spillover effects.

The capacity for aquaculture to provide an alternative source of fish and seafood to capture fisheries was once promoted as a tool to reduce demand for wild fish and thus tackle overfishing. To date, there is little evidence to suggest that aquaculture growth has successfully reduced fishing effort on wild populations. Recent theory on “blue transitions” suggests that displacement may only occur as aquaculture production surpasses that of capture operations. Yet, there has been no systematic attempt to understand whether aquaculture-driven fisheries displacement has occurred in countries where aquaculture is now the dominant production form. We investigate the role of aquaculture on fisheries landings in these “aquaculture-dominant” countries using national-level production, trade, consumption and socioeconomic data from 1980 to 2017. Importantly, we find that aquaculture growth is associated with fisheries decline in aquaculture-dominant countries, but the marginal effects of aquaculture have a far weaker influence on wild-caught landings than other promoting factors, such as fish consumption and trade. Further, our qualitative analysis of the state of wild fisheries in aquaculture-dominant nations suggests that overexploitation continues to be pervasive and that any minimal displacement effects from aquaculture are unlikely to have offset the environmental impacts imposed by the growing sector. The rise of aquaculture as an alternative production form can provide valuable insights for growing industries developing sustainable new foods. Unless coupled with effective food consumption policy, such products may simply add to rather than displace the environmental impacts of human food production.

To help the State of California achieve its carbon neutrality goal, a team of researchers from the University of California Santa Barbara (UCSB) completed this study commissioned by the California Environmental Protection Agency (CalEPA) that examines options for reducing the state’s supply of transportation fuel in parallel with reductions in demand. The report also considers paths to promote health and economic equity in the process of decarbonizing the transportation sector.

Seaweed aquaculture is capable of removing large quantities of nitrogen and phosphorus from coastal ecosystems, yet seaweed has gained little traction for its potential role in targeted nutrient assimilation. Marine nutrient pollution is increasing around the world, contributing to expanding eutrophic conditions and co-occurring with other stressors that impact the state and stability of aquatic ecosystems. In the United States, climate change, legacy nitrogen, and nonpoint source pollution make it increasingly difficult to curb growing eutrophication and the associated effects, such as hypoxia (dissolved oxygen < 2 mgL^-1). Employing a synthetic semi-quantitative approach, we use the Gulf of Mexico as a case study – a U.S. priority area for aquaculture with substantial nutrient pollution and one of the largest hypoxic zones on the planet – to assess the potential for native seaweed aquaculture to augment upstream pollution control with downstream nutrient assimilation. Results from this analysis suggest that given growing market demand, new product pathways, and nutrient pollution markets, seaweed aquaculture may be a feasible tool for nutrient assimilation that could subsidize, if not pay for itself.

Cell-based seafood is an emerging novel food, with many start-up companies aspiring for ocean conservation benefits through expanded market share that displaces wild-caught seafood. However, the ability for cell-based seafood to achieve this conservation outcome is often oversimplified and will rely on an extensive, and we find somewhat tenuous, chain of events. Here, we outline the technological, behavioural, market and ecological changes that must occur along this pathway, and conclude that fisheries recoveries and collateral ocean benefits are unlikely to result from cell-based seafood technology. In particular, we detail nine necessary steps and argue that failure at any one step could hinder or even eliminate cell-based seafood's conservation effects. We additionally draw comparisons to aquaculture and share broader lessons for other demand-driven product interventions.

This paper designs a reciprocal dumping model to address the control of industrial pollution between two trading partners. Firms generate transboundary pollution from production and environmental taxes represent the pollution control instrument. We ask whether environmental taxes implemented in a non-cooperative setting are more stringent than the globally efficient level. Relative to the globally efficient case, we find in the linear Markov Perfect Nash Equilibrium (MPNE) context that the tax rate for both countries is smaller and individual emissions are larger. However, these results may not hold in the non-linear MPNE case depending on market structure and environmental conditions. Unlike the symmetric equilibrium case, the tax rates are always discontinuous under asymmetric MPNEs. The asymmetric equilibrium scenario can give rise to higher individual payoffs relative to the symmetric equilibrium case.

With nearly every country combating the 2019 novel coronavirus (COVID-19), there is a need to understand how local environmental conditions may modify transmission. To date, quantifying seasonality of the disease has been limited by scarce data and the difficulty of isolating climatological variables from other drivers of transmission in observational studies. We combine a spatially resolved dataset of confirmed COVID-19 cases, composed of 3,235 regions across 173 countries, with local environmental conditions and a statistical approach developed to quantify causal effects of environmental conditions in observational data settings. We find that ultraviolet (UV) radiation has a statistically significant effect on daily COVID-19 growth rates: a SD increase in UV lowers the daily growth rate of COVID-19 cases by 1 percentage point over the subsequent 2.5 wk, relative to an average in-sample growth rate of 13.2%. The time pattern of lagged effects peaks 9 to 11 d after UV exposure, consistent with the combined timescale of incubation, testing, and reporting. Cumulative effects of temperature and humidity are not statistically significant. Simulations illustrate how seasonal changes in UV have influenced regional patterns of COVID-19 growth rates from January to June, indicating that UV has a substantially smaller effect on the spread of the disease than social distancing policies. Furthermore, total COVID-19 seasonality has indeterminate sign for most regions during this period due to uncertain effects of other environmental variables. Our findings indicate UV exposure influences COVID-19 cases, but a comprehensive understanding of seasonality awaits further analysis.

While forced labor in the world’s fishing fleet has been widely documented, its extent remains unknown. No methods previously existed for remotely identifying individual fishing vessels potentially engaged in these abuses on a global scale. By combining expertise from human rights practitioners and satellite vessel monitoring data, we show that vessels reported to use forced labor behave in systematically different ways from other vessels. We exploit this insight by using machine learning to identify high-risk vessels from among 16,000 industrial longliner, squid jigger, and trawler fishing vessels. Our model reveals that between 14% and 26% of vessels were high-risk, and also reveals patterns of where these vessels fished and which ports they visited. Between 57,000 and 100,000 individuals worked on these vessels, many of whom may have been forced labor victims. This information provides unprecedented opportunities for novel interventions to combat this humanitarian tragedy. More broadly, this research demonstrates a proof of concept for using remote sensing to detect forced labor abuses.

Seafood companies rarely disclose what or where they are fishing. To provide a first overview of the fishing industry in the high seas—the area beyond national jurisdiction—we linked fishing activity in the high seas to vessel owners and corporate actors. We identified 1,120 corporate actors for 2,482 vessels (∼2/3 of high seas fishing vessels and effort in 2018) and found that the top 100 corporate actors account for 36% of all high seas fishing effort. As attribution for anthropogenic activities expands beyond a national framework, we demonstrate the feasibility of methods to identify the high seas fishing industry. These results provide a unique lens through which to view accountability for the use and protection of marine biodiversity.

Effective management of aquatic resources, wild and farmed, has implications for the livelihoods of dependent communities, food security, and ecosystem health. Good management requires information on the status of harvested species, yet many gaps remain in our understanding of these species and systems, in particular the lack of taxonomic resolution of harvested species. To assess these gaps we compared the occurrence of landed species (freshwater and marine) from the United Nations Food and Agriculture Organization (FAO) global fisheries production database to those in the International Union for Conservation of Nature (IUCN) Red List and the RAM Legacy Stock Assessment Database, some of the largest and most comprehensive global datasets of consumed aquatic species. We also quantified the level of resolution and trends in taxonomic reporting for all landed taxa in the FAO database. Of the 1,695 consumed aquatic species or groups in the FAO database considered in this analysis, a large portion (35%) are missing from both of the other two global datasets, either IUCN or RAM, used to monitor, manage, and protect aquatic resources. Only a small number of all fished taxa reported in FAO data (150 out of 1,695; 9%) have both a stock assessment in RAM and a conservation assessment in IUCN. Furthermore, 40% of wild caught landings are not reported to the species level, limiting our ability to effectively account for the environmental impacts of wild harvest. Landings of invertebrates (44%) and landings in Asia (>75%) accounted for the majority of harvest without species specific information in 2018. Assessing the overlap of species which are both farmed and fished to broadly map possible interactions – which can help or hinder wild populations - we found 296 species, accounting for 12% of total wild landings globally, and 103 countries and territories that have overlap in the species caught in the wild and produced through aquaculture. In all, our work highlights that while fisheries management is improving in many areas there remain key gaps in data resolution that are critical for fisheries assessments and conservation of aquatic systems into the future.