Holly K. Gibbs

Land use has generally been considered a local environmental issue, but it is becoming a force of global importance. Worldwide changes to forests, farmlands, waterways, and air are being driven by the need to provide food, fiber, water, and shelter to more than six billion people. Global croplands, pastures, plantations, and urban areas have expanded in recent decades, accompanied by large increases in energy, water, and fertilizer consumption, along with considerable losses of biodiversity. Such changes in land use have enabled humans to appropriate an increasing share of the planet's resources, but they also potentially undermine the capacity of ecosystems to sustain food production, maintain freshwater and forest resources, regulate climate and air quality, and ameliorate infectious diseases. We face the challenge of managing trade-offs between immediate human needs and maintaining the capacity of the biosphere to provide goods and services in the long term.

Global demand for agricultural products such as food, feed, and fuel is now a major driver of cropland and pasture expansion across much of the developing world. Whether these new agricultural lands replace forests, degraded forests, or grasslands greatly influences the environmental consequences of expansion. Although the general pattern is known, there still is no definitive quantification of these land-cover changes. Here we analyze the rich, pan-tropical database of classified Landsat scenes created by the Food and Agricultural Organization of the United Nations to examine pathways of agricultural expansion across the major tropical forest regions in the 1980s and 1990s and use this information to highlight the future land conversions that probably will be needed to meet mounting demand for agricultural products. Across the tropics, we find that between 1980 and 2000 more than 55% of new agricultural land came at the expense of intact forests, and another 28% came from disturbed forests. This study underscores the potential consequences of unabated agricultural expansion for forest conservation and carbon emissions.

Reducing carbon emissions from deforestation and degradation in developing countries is of central importance in efforts to combat climate change. Key scientific challenges must be addressed to prevent any policy roadblocks. Foremost among the challenges is quantifying nations’ carbon emissions from deforestation and forest degradation, which requires information on forest clearing and carbon storage. Here we review a range of methods available to estimate national-level forest carbon stocks in developing countries. While there are no practical methods to directly measure all forest carbon stocks across a country, both ground-based and remote-sensing measurements of forest attributes can be converted into estimates of national carbon stocks using allometric relationships. Here we synthesize, map and update prominent forest biomass carbon databases to create the first complete set of national-level forest carbon stock estimates. These forest carbon estimates expand on the default values recommended by the Intergovernmental Panel on Climate Change’s National Greenhouse Gas Inventory Guidelines and provide a range of globally consistent estimates.

Degraded lands have often been suggested as a solution to issues of land scarcity and as an ideal way to meet mounting global demands for agricultural goods, but their locations and conditions are not well known. Four approaches have been used to assess degraded lands at the global scale: expert opinion, satellite observation, biophysical models, and taking inventory of abandoned agricultural lands. We review prominent databases and methodologies used to estimate the area of degraded land, translate these data into a common framework for comparison, and highlight reasons for discrepancies between the numbers. Global estimates of total degraded area vary from less than 1 billion ha to over 6 billion ha, with equally wide disagreement in their spatial distribution. The risk of overestimating the availability and productive potential of these areas is severe, as it may divert attention from efforts to reduce food and agricultural waste or the demand for land-intensive commodities.

The Amazon Basin is one of the world's most important bioregions, harboring a rich array of plant and animal species and offering a wealth of goods and services to society. For years, ecological science has shown how large-scale forest clearings cause declines in biodiversity and the availability of forest products. Yet some important changes in the rainforests, and in the ecosystem services they provide, have been underappreciated until recently. Emerging research indicates that land use in the Amazon goes far beyond clearing large areas of forest; selective logging and other canopy damage is much more pervasive than once believed. Deforestation causes collateral damage to the surrounding forests – through enhanced drying of the forest floor, increased frequency of fires, and lowered productivity. The loss of healthy forests can degrade key ecosystem services, such as carbon storage in biomass and soils, the regulation of water balance and river flow, the modulation of regional climate patterns, and the amelioration of infectious diseases. We review these newly revealed changes in the Amazon rainforests and the ecosystem services that they provide.

Supply-chain governance is needed to avoid deforestation

Science-based policy is essential for guiding an environmentally sustainable approach to cellulosic biofuels.

Biofuels from land-rich tropical countries may help displace foreign petroleum imports for many industrialized nations, providing a possible solution to the twin challenges of energy security and climate change. But concern is mounting that crop-based biofuels will increase net greenhouse gas emissions if feedstocks are produced by expanding agricultural lands. Here we quantify the 'carbon payback time' for a range of biofuel crop expansion pathways in the tropics. We use a new, geographically detailed database of crop locations and yields, along with updated vegetation and soil biomass estimates, to provide carbon payback estimates that are more regionally specific than those in previous studies. Using this cropland database, we also estimate carbon payback times under different scenarios of future crop yields, biofuel technologies, and petroleum sources. Under current conditions, the expansion of biofuels into productive tropical ecosystems will always lead to net carbon emissions for decades to centuries, while expanding into degraded or already cultivated land will provide almost immediate carbon savings. Future crop yield improvements and technology advances, coupled with unconventional petroleum supplies, will increase biofuel carbon offsets, but clearing carbon-rich land still requires several decades or more for carbon payback. No foreseeable changes in agricultural or energy technology will be able to achieve meaningful carbon benefits if crop-based biofuels are produced at the expense of tropical forests.

The life cycle greenhouse gas (GHG) emissions induced by increased biofuel consumption are highly uncertain: individual estimates vary from each other and each has a wide intrinsic error band. Using a reduced-form model, we estimated that the bounding range for emissions from indirect land-use change (ILUC) from US corn ethanol expansion was 10 to 340 g CO2 MJ−1. Considering various probability distributions to model parameters, the broadest 95% central interval, i.e., between the 2.5 and 97.5%ile values, ranged from 21 to 142 g CO2e MJ−1. ILUC emissions from US corn ethanol expansion thus range from small, but not negligible, to several times greater than the life cycle emissions of gasoline. The ILUC emissions estimates of 30 g CO2 MJ−1 for the California Air Resources Board and 34 g CO2e MJ−1 by USEPA (for 2022) are at the low end of the plausible range. The lack of data and understanding (epistemic uncertainty) prevents convergence of judgment on a central value for ILUC emissions. The complexity of the global system being modeled suggests that this range is unlikely to narrow substantially in the near future. Fuel policies that require narrow bounds around point estimates of life cycle GHG emissions are thus incompatible with current and anticipated modeling capabilities. Alternative policies that address the risks associated with uncertainty are more likely to achieve GHG reductions.

Cultivation of corn and soybeans in the United States reached record high levels following the biofuels boom of the late 2000s. Debate exists about whether the expansion of these crops caused conversion of grasslands and other carbon-rich ecosystems to cropland or instead replaced other crops on existing agricultural land. We tracked crop-specific expansion pathways across the conterminous US and identified the types, amount, and locations of all land converted to and from cropland, 2008–2012. We found that crop expansion resulted in substantial transformation of the landscape, including conversion of long-term unimproved grasslands and land that had not been previously used for agriculture (cropland or pasture) dating back to at least the early 1970s. Corn was the most common crop planted directly on new land, as well as the largest indirect contributor to change through its displacement of other crops. Cropland expansion occurred most rapidly on land that is less suitable for cultivation, raising concerns about adverse environmental and economic costs of conversion. Our results reveal opportunities to increase the efficacy of current federal policy conservation measures by modifying coverage of the 2014 US Farm Bill Sodsaver provision and improving enforcement of the US Renewable Fuels Standard.

Abstract An accurate estimate of carbon fluxes associated with tropical deforestation from the last two decades is needed to balance the global carbon budget. Several studies have already estimated carbon emissions from tropical deforestation, but the estimates vary greatly and are difficult to compare due to differences in data sources, assumptions, and methodologies. In this paper, we review the different estimates and datasets, and the various challenges associated with comparing them and with accurately estimating carbon emissions from deforestation. We performed a simulation study over legal Amazonia to illustrate some of these major issues. Our analysis demonstrates the importance of considering land‐cover dynamics following deforestation, including the fluxes from reclearing of secondary vegetation, the decay of product and slash pools, and the fluxes from regrowing forest. It also suggests that accurate carbon‐flux estimates will need to consider historical land‐cover changes for at least the previous 20 years. However, this result is highly sensitive to estimates of the partitioning of cleared carbon into instantaneous burning vs. long‐timescale slash pools. We also show that carbon flux estimates based on ‘committed flux’ calculations, as used by a few studies, are not comparable with the ‘annual balance’ calculation method used by other studies.

A major reduction in global deforestation is needed to mitigate climate change and biodiversity loss. Recent private sector commitments aim to eliminate deforestation from a company’s operations or supply chain, but they fall short on several fronts. Company pledges vary in the degree to which they include time-bound interventions with clear definitions and criteria to achieve verifiable outcomes. Zero-deforestation policies by companies may be insufficient to achieve broader impact on their own due to leakage, lack of transparency and traceability, selective adoption and smallholder marginalization. Public–private policy mixes are needed to increase the effectiveness of supply-chain initiatives that aim to reduce deforestation. We review current supply-chain initiatives, their effectiveness, and the challenges they face, and go on to identify knowledge gaps for complementary public–private policies. In this Perspective, private company supply-chain initiatives designed to reduce deforestation are assessed. Public–private policy mixes are advocated to increase their efficacy.

Abstract Deforestation is a main driver of climate change and biodiversity loss. An incentive mechanism to reduce emissions from deforestation and forest degradation (REDD) is being negotiated under the United Nations Framework Convention on Climate Change. Here we use the best available global data sets on terrestrial biodiversity and carbon storage to map and investigate potential synergies between carbon and biodiversity‐oriented conservation. A strong association ( r S = 0.82) between carbon stocks and species richness suggests that such synergies would be high, but unevenly distributed. Many areas of high value for biodiversity could be protected by carbon‐based conservation, while others could benefit from complementary funding arising from their carbon content. Some high‐biodiversity regions, however, would not benefit from carbon‐focused conservation, and could become under increased pressure if REDD is implemented. Our results suggest that additional gains for biodiversity conservation are possible, without compromising the effectiveness for climate change mitigation, if REDD takes biodiversity distribution into account.

Expanding croplands to meet the needs of a growing population, changing diets, and biofuel production comes at the cost of reduced carbon stocks in natural vegetation and soils. Here, we present a spatially explicit global analysis of tradeoffs between carbon stocks and current crop yields. The difference among regions is striking. For example, for each unit of land cleared, the tropics lose nearly two times as much carbon (∼120 tons·ha −1 vs. ∼63 tons·ha −1 ) and produce less than one-half the annual crop yield compared with temperate regions (1.71 tons·ha −1 ·y −1 vs. 3.84 tons·ha −1 ·y −1 ). Therefore, newly cleared land in the tropics releases nearly 3 tons of carbon for every 1 ton of annual crop yield compared with a similar area cleared in the temperate zone. By factoring crop yield into the analysis, we specify the tradeoff between carbon stocks and crops for all areas where crops are currently grown and thereby, substantially enhance the spatial resolution relative to previous regional estimates. Particularly in the tropics, emphasis should be placed on increasing yields on existing croplands rather than clearing new lands. Our high-resolution approach can be used to determine the net effect of local land use decisions.

Previous estimates of the land area available for future cropland expansion relied on global-scale climate, soil and terrain data. They did not include a range of constraints and tradeoffs associated with land conversion. As a result, estimates of the global land reserve have been high. Here we adjust these estimates for the aforementioned constraints and tradeoffs. We define potentially available cropland as the moderately to highly productive land that could be used in the coming years for rainfed farming, with low to moderate capital investments, and that is not under intact mature forests, legally protected, or already intensively managed. This productive land is underutilized rather than unused as it has ecological or social functions. We also define potentially available cropland that accounts for trade-offs between gains in agricultural production and losses in ecosystem and social services from intensified agriculture, to include only the potentially available cropland that would entail low ecological and social costs with conversion to cropland. In contrast to previous studies, we adopt a “bottom-up” approach by analyzing detailed, fine scale observations with expert knowledge for six countries or regions that are often assumed to include most of potentially available cropland. We conclude first that there is substantially less potential additional cropland than is generally assumed once constraints and trade offs are taken into account, and secondly that converting land is always associated with significant social and ecological costs. Future expansion of agricultural production will encounter a complex landscape of competing demands and tradeoffs.

Brazil's inability to tackle illegal deforestation puts the future of its agribusiness at risk

Many major corporations and countries have made commitments to purchase or produce only "sustainable" palm oil, a commodity responsible for substantial tropical forest loss. Sustainability certification is the tool most used to fulfill these procurement policies, and around 20% of global palm oil production was certified by the Roundtable on Sustainable Palm Oil (RSPO) in 2017. However, the effect of certification on deforestation in oil palm plantations remains unclear. Here, we use a comprehensive dataset of RSPO-certified and noncertified oil palm plantations (∼188,000 km2) in Indonesia, the leading producer of palm oil, as well as annual remotely sensed metrics of tree cover loss and fire occurrence, to evaluate the impact of certification on deforestation and fire from 2001 to 2015. While forest loss and fire continued after RSPO certification, certified palm oil was associated with reduced deforestation. Certification lowered deforestation by 33% from a counterfactual of 9.8 to 6.6% y-1 Nevertheless, most plantations contained little residual forest when they received certification. As a result, by 2015, certified areas held less than 1% of forests remaining within Indonesian oil palm plantations. Moreover, certification had no causal impact on forest loss in peatlands or active fire detection rates. Broader adoption of certification in forested regions, strict requirements to avoid all peat, and routine monitoring of clearly defined forest cover loss in certified and RSPO member-held plantations appear necessary if the RSPO is to yield conservation and climate benefits from reductions in tropical deforestation.

New supply chain interventions offer promise to reduce deforestation from expansion of commercial agriculture, as more multinational companies agree to stop sourcing from farms with recent forest clearing. We analyzed the zero-deforestation cattle agreements signed by major meatpacking companies in the Brazilian Amazon state of Pará using property-level data on beef supply chains. Our panel analysis of daily purchases by slaughterhouses before and after the agreements demonstrates that they now avoid purchasing from properties with deforestation, which was not the case prior to the agreements. Supplying ranchers registered their properties in a public environmental registry nearly 2 years before surrounding non-supplying properties, and 85% of surveyed ranchers indicated that the agreements were the driving force. In addition, supplying properties had significantly reduced deforestation rates following the agreements. Our results demonstrate important changes in the beef supply chain, but the agreements’ narrow scope and implementation diminish outcomes for forest conservation.

Commodity crop expansion, for both global and domestic urban markets, follows multiple land change pathways entailing direct and indirect deforestation, and results in various social and environmental impacts. Here we compare six published case studies of rapid commodity crop expansion within forested tropical regions. Across cases, between 1.7% and 89.5% of new commodity cropland was sourced from forestlands. Four main factors controlled pathways of commodity crop expansion: (i) the availability of suitable forestland, which is determined by forest area, agroecological or accessibility constraints, and land use policies, (ii) economic and technical characteristics of agricultural systems, (iii) differences in constraints and strategies between small-scale and large-scale actors, and (iv) variable costs and benefits of forest clearing. When remaining forests were unsuitable for agriculture and/or policies restricted forest encroachment, a larger share of commodity crop expansion occurred by conversion of existing agricultural lands, and land use displacement was smaller. Expansion strategies of large-scale actors emerge from context-specific balances between the search for suitable lands; transaction costs or conflicts associated with expanding into forests or other state-owned lands versus smallholder lands; net benefits of forest clearing; and greater access to infrastructure in already-cleared lands. We propose five hypotheses to be tested in further studies: (i) land availability mediates expansion pathways and the likelihood that land use is displaced to distant, rather than to local places; (ii) use of already-cleared lands is favored when commodity crops require access to infrastructure; (iii) in proportion to total agricultural expansion, large-scale actors generate more clearing of mature forests than smallholders; (iv) property rights and land tenure security influence the actors participating in commodity crop expansion, the form of land use displacement, and livelihood outcomes; (v) intensive commodity crops may fail to spare land when inducing displacement. We conclude that understanding pathways of commodity crop expansion is essential to improve land use governance.

Abstract Remotely sensed biomass carbon density maps are widely used for myriad scientific and policy applications, but all remain limited in scope. They often only represent a single vegetation type and rarely account for carbon stocks in belowground biomass. To date, no global product integrates these disparate estimates into an all-encompassing map at a scale appropriate for many modelling or decision-making applications. We developed an approach for harmonizing vegetation-specific maps of both above and belowground biomass into a single, comprehensive representation of each. We overlaid input maps and allocated their estimates in proportion to the relative spatial extent of each vegetation type using ancillary maps of percent tree cover and landcover, and a rule-based decision schema. The resulting maps consistently and seamlessly report biomass carbon density estimates across a wide range of vegetation types in 2010 with quantified uncertainty. They do so for the globe at an unprecedented 300-meter spatial resolution and can be used to more holistically account for diverse vegetation carbon stocks in global analyses and greenhouse gas inventories.

Avoiding catastrophic climate change requires rapid decarbonization and improved ecosystem stewardship. To achieve the latter, ecosystems should be prioritized by responsiveness to direct, localized action and the magnitude and recoverability of their carbon stores. Here, we show that a range of ecosystems contain ‘irrecoverable carbon’ that is vulnerable to release upon land use conversion and, once lost, is not recoverable on timescales relevant to avoiding dangerous climate impacts. Globally, ecosystems highly affected by human land-use decisions contain at least 260 Gt of irrecoverable carbon, with particularly high densities in peatlands, mangroves, old-growth forests and marshes. To achieve climate goals, we must safeguard these irrecoverable carbon pools through an expanded set of policy and finance strategies. In order to limit warming and the most severe consequences of climate change, net global carbon emissions must reach zero by 2050. Many ecosystems contain carbon that would be irrecoverable on this timescale if lost and must be protected to meet climate goals.

Abstract Recent expansion of croplands in the United States has caused widespread conversion of grasslands and other ecosystems with largely unknown consequences for agricultural production and the environment. Here we assess annual land use change 2008–16 and its impacts on crop yields and wildlife habitat. We find that croplands have expanded at a rate of over one million acres per year, and that 69.5% of new cropland areas produced yields below the national average, with a mean yield deficit of 6.5%. Observed conversion infringed upon high-quality habitat that, relative to unconverted land, had provided over three times higher milkweed stem densities in the Monarch butterfly Midwest summer breeding range and 37% more nesting opportunities per acre for waterfowl in the Prairie Pothole Region of the Northern Great Plains. Our findings demonstrate a pervasive pattern of encroachment into areas that are increasingly marginal for production, but highly significant for wildlife, and suggest that such tradeoffs may be further amplified by future cropland expansion.

Integrated high-resolution maps of carbon stocks and biodiversity that identify areas of potential co-benefits for climate change mitigation and biodiversity conservation can help facilitate the implementation of global climate and biodiversity commitments at local levels. However, the multi-dimensional nature of biodiversity presents a major challenge for understanding, mapping and communicating where and how biodiversity benefits coincide with climate benefits. A new integrated approach to biodiversity is therefore needed. Here, we (a) present a new high-resolution map of global above- and below-ground carbon stored in biomass and soil, (b) quantify biodiversity values using two complementary indices (BIp and BIr) representing proactive and reactive approaches to conservation, and (c) examine patterns of carbon-biodiversity overlap by identifying 'hotspots' (20% highest values for both aspects). Our indices integrate local diversity and ecosystem intactness, as well as regional ecosystem intactness across the broader area supporting a similar natural assemblage of species to the location of interest. The western Amazon Basin, Central Africa and Southeast Asia capture the last strongholds of highest local biodiversity and ecosystem intactness worldwide, while the last refuges for unique biological communities whose habitats have been greatly reduced are mostly found in the tropical Andes and central Sundaland. There is 38 and 5% overlap in carbon and biodiversity hotspots, for proactive and reactive conservation, respectively. Alarmingly, only around 12 and 21% of these proactive and reactive hotspot areas, respectively, are formally protected. This highlights that a coupled approach is urgently needed to help achieve both climate and biodiversity global targets. This would involve (1) restoring and conserving unprotected, degraded ecosystems, particularly in the Neotropics and Indomalaya, and (2) retaining the remaining strongholds of intactness. This article is part of the theme issue 'Climate change and ecosystems: threats, opportunities and solutions'.

Zero-deforestation commitments are a type of voluntary sustainability initiative that companies adopt to signal their intention to reduce or eliminate deforestation associated with commodities that they produce, trade, and/or sell. Because each company defines its own zero-deforestation commitment goals and implementation mechanisms, commitment content varies widely. This creates challenges for the assessment of commitment implementation or effectiveness. Here, we develop criteria to assess the potential effectiveness of zero-deforestation commitments at reducing deforestation within a company supply chain, regionally, and globally. We apply these criteria to evaluate 52 zero-deforestation commitments made by companies identified by Forest 500 as having high deforestation risk. While our assessment indicates that existing commitments converge with several criteria for effectiveness, they fall short in a few key ways. First, they cover just a small share of the global market for deforestation-risk commodities, which means that their global impact is likely to be small. Second, biome-wide implementation is only achieved in the Brazilian Amazon. Outside this region, implementation occurs mainly through certification programs, which are not adopted by all producers and lack third-party near-real time deforestation monitoring. Additionally, around half of all commitments include zero-net deforestation targets and future implementation deadlines, both of which are design elements that may reduce effectiveness. Zero-net targets allow promises of future reforestation to compensate for current forest loss, while future implementation deadlines allow for preemptive clearing. To increase the likelihood that commitments will lead to reduced deforestation across all scales, more companies should adopt zero-gross deforestation targets with immediate implementation deadlines and clear sanction-based implementation mechanisms in biomes with high risk of forest to commodity conversion.

The Renewable Fuel Standard (RFS) specifies the use of biofuels in the United States and thereby guides nearly half of all global biofuel production, yet outcomes of this keystone climate and environmental regulation remain unclear. Here we combine econometric analyses, land use observations, and biophysical models to estimate the realized effects of the RFS in aggregate and down to the scale of individual agricultural fields across the United States. We find that the RFS increased corn prices by 30% and the prices of other crops by 20%, which, in turn, expanded US corn cultivation by 2.8 Mha (8.7%) and total cropland by 2.1 Mha (2.4%) in the years following policy enactment (2008 to 2016). These changes increased annual nationwide fertilizer use by 3 to 8%, increased water quality degradants by 3 to 5%, and caused enough domestic land use change emissions such that the carbon intensity of corn ethanol produced under the RFS is no less than gasoline and likely at least 24% higher. These tradeoffs must be weighed alongside the benefits of biofuels as decision-makers consider the future of renewable energy policies and the potential for fuels like corn ethanol to meet climate mitigation goals.

Climate change and land use change can affect multiple infectious diseases of humans, acting either independently or synergistically. Expanded efforts in empiric and future scenario-based risk assessment are required to anticipate problems. Moreover, the many health impacts of climate and land use change must be examined in the context of the myriad other environmental and behavioral determinants of disease. To optimize prevention capabilities, upstream environmental approaches must be part of any intervention, rather than assaults on single agents of disease. Clinicians must develop stronger ties, not only to public health officials and scientists, but also to earth and environmental scientists and policy makers. Without such efforts, we will inevitably benefit our current generation at the cost of generations to come.

Global climate policy initiatives are now being proposed to compensate tropical forest nations for reducing carbon emissions from deforestation and forest degradation (REDD). These proposals have the potential to include developing countries more actively in international greenhouse gas mitigation and to address a substantial share of the world's emissions which come from tropical deforestation. For such a policy to be viable it must have a credible benchmark against which emissions reduction can be calculated. This benchmark, sometimes termed a baseline or reference emissions scenario, can be based directly on historical emissions or can use historical emissions as input for business as usual projections. Here, we review existing data and methods that could be used to measure historical deforestation and forest degradation reference scenarios including FAO (Food and Agricultural Organization of the United Nations) national statistics and various remote sensing sources. The freely available and corrected global Landsat imagery for 1990, 2000 and soon to come for 2005 may be the best primary data source for most developing countries with other coarser resolution high frequency or radar data as a valuable complement for addressing problems with cloud cover and for distinguishing larger scale degradation. While sampling of imagery has been effectively useful for pan-tropical and continental estimates of deforestation, wall-to-wall (or full coverage) allows more detailed assessments for measuring national-level reference emissions. It is possible to measure historical deforestation with sufficient certainty for determining reference emissions, but there must be continued calls at the international level for making high-resolution imagery available, and for financial and technical assistance to help countries determine credible reference scenarios. The data available for past years may not be sufficient for assessing all forms of forest degradation, but new data sources will have greater potential in 2007 and after. This paper focuses only on the methods for measuring changes in forest area, but this information must be coupled with estimates of change in forest carbon stocks in order to quantify emissions from deforestation and forest degradation.

Poverty and biodiversity loss are two of the world's dire challenges. Claims of conservation's contribution to poverty alleviation, however, remain controversial. Here, we assess the flows of ecosystem services provided to people by priority habitats for terrestrial conservation, considering the global distributions of biodiversity, physical factors, and socioeconomic context. We estimate the value of these habitats to the poor, both through direct benefits and through payments for ecosystem services to those stewarding natural habitats. The global potential for biodiversity conservation to support poor communities is high: The top 25% of conservation priority areas could provide 56%–57% of benefits. The aggregate benefits are valued at three times the estimated opportunity costs and exceed $1 per person per day for 331 million of the world's poorest people. Although trade-offs remain, these results show win–win synergies between conservation and poverty alleviation, indicate that effective financial mechanisms can enhance these synergies, and suggest biodiversity conservation as a fundamental component of sustainable economic development.

Monitoring agricultural land is important for understanding and managing food production, environmental conservation efforts, and climate change. The United States Department of Agriculture's Cropland Data Layer (CDL), an annual satellite imagery-derived land cover map, has been increasingly used for this application since complete coverage of the conterminous United States became available in 2008. However, the CDL is designed and produced with the intent of mapping annual land cover rather than tracking changes over time, and as a result certain precautions are needed in multi-year change analyses to minimize error and misapplication. We highlight scenarios that require special considerations, suggest solutions to key challenges, and propose a set of recommended good practices and general guidelines for CDL-based land change estimation. We also characterize a problematic issue of crop area underestimation bias within the CDL that needs to be accounted for and corrected when calculating changes to crop and cropland areas. When used appropriately and in conjunction with related information, the CDL is a valuable and effective tool for detecting diverse trends in agriculture. By explicitly discussing the methods and techniques for post-classification measurement of land-cover and land-use change using the CDL, we aim to further stimulate the discourse and continued development of suitable methodologies. Recommendations generated here are intended specifically for the CDL but may be broadly applicable to additional remotely-sensed land cover datasets including the National Land Cover Database (NLCD), Moderate Resolution Imaging Spectroradiometer (MODIS)-based land cover products, and other regional, national, and global land cover classification maps.

Supply chain interventions, which include certification schemes and zero-deforestation commitments that aim to produce environmentally and socially beneficial outcomes, are increasingly common, but evidence of their efficacy is scarce. We quantified avoided deforestation from Brazil's zero-deforestation cattle agreements by exploiting variation in the policy's rollout and the acquisition of slaughterhouses by the agreements’ signatories from 2007 to 2015 in the Amazonian states of Mato Grosso and Pará. We found no average impact of the agreements on forest cover in the regions surrounding signatory slaughterhouses by the end of 2014. Our results show avoided deforestation of about 6% from the agreements on properties that enrolled early in the rural environmental land registry. However, forest loss increased commensurately on those properties that registered later, thus washing out the positive conservation effects from the early registrants. Our results also highlight that slaughterhouses bought plants in regions with higher deforestation both before and after the agreement, suggesting that companies are not avoiding these important hotspots. We conclude that the agreements have led to some avoided deforestation on registered properties, whose boundaries are transparent and publicly accessible, but that more robust reductions in deforestation will require additional action. The agreements could be made more effective by expanding monitoring to include all properties in the supply chain, as well as ensuring that all slaughterhouses monitor.

Although the United States has pursued rapid development of corn ethanol as a matter of national biofuel policy, relatively little is known about this policy's widespread impacts on agricultural land conversion surrounding ethanol refineries. This knowledge gap impedes policy makers' ability to identify and mitigate potentially negative environmental impacts of ethanol production. We assessed changes to the landscape during initial implementation of the Renewable Fuel Standard v2 (RFS2) from 2008 to 2012 and found nearly 4.2 million acres of arable non-cropland converted to crops within 100 miles of refinery locations, including 3.6 million acres of converted grassland. Aggregated across all ethanol refineries, the rate of grassland conversion to cropland increased linearly with proximity to a refinery location. Despite this widespread conversion of the landscape, recent cropland expansion could have made only modest contributions to mandated increases in conventional biofuel capacity required by RFS2. Collectively, these findings demonstrate a shortcoming in the existing 'aggregate compliance' method for enforcing land protections in the RFS2 and suggest an alternative monitoring mechanism would be needed to appropriately capture the scale of observed land use changes.

Accurate and timely information on the distribution of irrigated croplands is crucial to research on agriculture, water availability, land use, and climate change. While agricultural land use has been well characterized, less attention has been paid specifically to croplands that are irrigated, in part due to the difficulty in mapping and distinguishing irrigation in satellite imagery. In this study, we developed a semi-automatic training approach to rapidly map irrigated croplands across the conterminous United States (CONUS) at 30 m resolution using Google Earth Engine. To resolve the issue of lacking nationwide training data, we generated two intermediate irrigation maps by segmenting Landsat-derived annual maximum greenness and enhanced vegetation index using county-level thresholds calibrated from an existing coarse resolution irrigation map. The resulting intermediate maps were then spatially filtered to provide a training data pool for most areas except for the upper midwestern states where we visually collected samples. We then used random samples extracted from the training pool along with remote sensing-derived features and climate variables to train ecoregion-stratified random forest classifiers for pixel-level classification. For ecoregions with a large training pool, the procedure of sample extraction, classifier training, and classification was conducted 10 times to obtain stable classification results. The resulting 2012 Landsat-based irrigation dataset (LANID) identified 23.3 million hectares of irrigated croplands in CONUS. A quantitative assessment of LANID showed superior accuracy to currently available maps, with a mean Kappa value of 0.88 (0.75–0.99), overall accuracy of 94% (87.5–99%), and producer’s and user’s accuracy of the irrigation class of 97.3% and 90.5%, respectively, at the aquifer level. Evaluation of feature importance indicated that Landsat-derived features played the primary role in classification in relatively arid regions while climate variables were important in the more humid eastern states. This methodology has the potential to produce annual irrigation maps for CONUS and provide insights into the field-level spatial and temporal aspects of irrigation.

Abstract The Cerrado biome is Brazil's breadbasket and a major provider of ecosystem services, though these dual roles are increasingly at odds, in part because there are few mechanisms to protect remaining vegetation from large‐scale agricultural expansion. We assessed Cerrado conversion to soy using over 580,000 property boundaries, covering 77% of the biome that is eligible for commercial land use, and using microwatersheds, to cover 100% of eligible areas. Soy expansion accounted for 22% of conversion during 2003–14. Only 15% of clearing exceeded restrictions on private properties under the Forest Code (FC). However, 51% of soy farms have violated the FC, five times the rate of other farms. As a leading cause of both Cerrado conversion and FC violations, the soy sector has environmental and economic incentives to shift production to already cleared land. We used suitability maps to identify potential pathways for soy expansion across both old and new cropland frontiers.

Brazil is the second largest soybean producer in the world with a planted area in the crop year 2017/18 of 33.347 million hectares, distributed in the Pampa, Atlantic Forest, Cerrado, and Amazon biomes. Through remote sensing techniques we show that the new agricultural frontier of soy is no longer in the Amazon, but in the last continuous areas of Cerrado, present in the region known as MATOPIBA. The soybean production chain has been striving to present to its overseas customers a soy produced in a sustainable way, without the removal of forests. Our data challenge its main program, the Amazonian Soy Moratorium, and we call attention to the conservation need of the MATOPIBA Cerrado, which is not monitored by Soy Moratorium.

Systems of intensive animal farming, such as the confinement of beef cattle, are widespread in the developed world. Such practices have been under scrutiny since the 1960s for animal welfare and pollution issues. Here, we document the expansion of intensive beef farming to the Brazilian Amazon in order to assess socio-environmental implications. Using a combination of data mining and field surveys, we developed a georeferenced dataset of 201 cattle confinements in the states of Mato Grosso (Cerrado and Amazon biomes), Pará and Rondônia (Amazon biome), collected in 2017. In Mato Grosso, the country’s agribusiness powerhouse, confinements are well established and account for ˜20% of the cattle slaughter. But rapid expansion in Pará and Rondônia remains largely unnoticed due to the absence of data since 2012. We used the new dataset to map cattle confinements across space and time. For the first time, (1) we document an expansion to the Amazon biome; (2) we also show that confinements are associated with substantially higher productivity rates, though intensified pasture-based systems can reach comparable yields; (3) that confinements have crop production levels 2-3 times higher than comparable properties, both in- and out-of-farm; and (4) that confinements tend to slow down on-property deforestation when compared to fattening ranches in the Amazon biome, although off-property effects could be substantial and need further study. Overall, the implications of intensive beef farming for animal welfare and local waste generation in Brazil require attention as pressure to avoid deforestation continues to stimulate the practice.

The U.S. Department of Agriculture’s (USDA) Cropland Data Layer (CDL) is a 30 m resolution crop-specific land cover map produced annually to assess crops and cropland area across the conterminous United States. Despite its prominent use and value for monitoring agricultural land use/land cover (LULC), there remains substantial uncertainty surrounding the CDLs’ performance, particularly in applications measuring LULC at national scales, within aggregated classes, or changes across years. To fill this gap, we used state- and land cover class-specific accuracy statistics from the USDA from 2008 to 2016 to comprehensively characterize the performance of the CDL across space and time. We estimated nationwide area-weighted accuracies for the CDL for specific crops as well as for the aggregated classes of cropland and non-cropland. We also derived and reported new metrics of superclass accuracy and within-domain error rates, which help to quantify and differentiate the efficacy of mapping aggregated land use classes (e.g., cropland) among constituent subclasses (i.e., specific crops). We show that aggregate classes embody drastically higher accuracies, such that the CDL correctly identifies cropland from the user’s perspective 97% of the time or greater for all years since nationwide coverage began in 2008. We also quantified the mapping biases of specific crops throughout time and used these data to generate independent bias-adjusted crop area estimates, which may complement other USDA survey- and census-based crop statistics. Our overall findings demonstrate that the CDLs provide highly accurate annual measures of crops and cropland areas, and when used appropriately, are an indispensable tool for monitoring changes to agricultural landscapes.

Deforestation for cattle production persists in the Brazilian Amazon despite ongoing efforts by the public and private sectors to combat it. The complexity of the cattle supply chain, which we describe in depth here, creates challenges for the landmark Zero-Deforestation Cattle Agreements in particular and for enforcement of deforestation policies in general. Here, we present a holistic analysis that is increasingly relevant as the number of policies, initiatives, and markets affecting the region increases. We provide the first property-level analysis of which ranchers decided to deforest in the last decade and identify the characteristics that are most related to deforestation. We rely on newly available animal transit and property boundary data to examine 113,000 properties in the three major cattle-producing states in the Brazilian Amazon. We consider characteristics related to a property's role in the supply chain, location, land characteristics, and the policy environment. We find that deforestation is most likely to occur on properties that sell fewer cattle and earlier in the supply chain, are located in remote locations, and have a high percent of remaining forest. Our results can be used to improve enforcement of existing policies by targeting resources to properties and location where deforestation is more likely.

Deforestation for agriculture is a key threat to global carbon stocks, biodiversity, and indigenous ways of life. In the absence of strong territorial governance, zero-deforestation commitments (ZDCs), corporate policies to decouple food production from deforestation, remain a central tool to combat this issue. Yet evidence on their effectiveness remains mixed and the mechanisms limiting effectiveness are poorly understood. To advance understanding of ZDCs’ potential at reducing deforestation, we developed the first spatially explicit estimates of farmers’ exposure to ZDC companies in the Brazilian Amazon cattle sector. Exposure was measured by determining the market share of ZDC firms from the first full year of ZDC adoption in 2010 until 2018. Our analysis evaluated how variation in this exposure influenced deforestation. We found the G4 Agreement, the most widespread and strongly implemented cattle ZDC, reduced cattle-driven deforestation by 7,000 ± 4,000 km2 (15 ± 8%) between 2010 and 2018. Additionally, had all firms adopted and implemented an effective ZDC, cattle-driven deforestation could have dropped by 24,000 ± 13,000 km2 (51 ± 28%). These results for the world’s principal deforestation hotspot suggests supply chain policies can substantially reduce deforestation. However, their effectiveness is contingent on widespread adoption and rigorous implementation, both of which are currently insufficient to prevent large scale deforestation. Increased adoption and implementation could be incentivized through greater pressure from the Brazilian government and import countries.

Climate change is projected to have adverse impacts on public health. Cobenefits may be possible from more upstream mitigation of greenhouse gases causing climate change. To help measure such cobenefits alongside averted disease-specific risks, a health impact assessment (HIA) framework can more comprehensively serve as a decision support tool. HIA also considers health equity, clearly part of the climate change problem. New choices for energy must be made carefully considering such effects as additional pressure on the world's forests through large-scale expansion of soybean and oil palm plantations, leading to forest clearing, biodiversity loss and disease emergence, expulsion of subsistence farmers, and potential increases in food prices and emissions of carbon dioxide to the atmosphere. Investigators must consider the full range of policy options, supported by more comprehensive, flexible, and transparent assessment methods.

Abstract Forest loss and degradation in the tropics contribute 6–17% of all greenhouse gas emissions. Protected areas cover 217.2 million ha (19.6%) of the world’s humid tropical forests and contain c. 70.3 petagrams of carbon (Pg C) in biomass and soil to 1 m depth. Between 2000 and 2005, we estimate that 1.75 million ha of forest were lost from protected areas in humid tropical forests, causing the emission of 0.25–0.33 Pg C. Protected areas lost about half as much carbon as the same area of unprotected forest. We estimate that the reduction of these carbon emissions from ongoing deforestation in protected sites in humid tropical forests could be valued at USD 6,200–7,400 million depending on the land use after clearance. This is > 1.5 times the estimated spending on protected area management in these regions. Improving management of protected areas to retain forest cover better may be an important, although certainly not sufficient, component of an overall strategy for reducing emissions from deforestation and forest degradation (REDD).

The Roundtable on Sustainable Palm Oil has emerged as the leading sustainability certification system to tackle socioenvironmental issues associated with the oil palm industry. However, the effectiveness of certification by the Roundtable on Sustainable Palm Oil in achieving its socioeconomic objectives remains uncertain. We evaluate the impact of certification on village-level well-being across Indonesia by applying counterfactual analysis to multidimensional government poverty data. We compare poverty across 36,311 villages between 2000 and 2018, tracking changes from before oil palm plantations were first established to several years after plantations were certified. Certification was associated with reduced poverty in villages with primarily market-based livelihoods, but not in those in which subsistence livelihoods were dominant before switching to oil palm. We highlight the importance of baseline village livelihood systems in shaping local impacts of agricultural certification and assert that oil palm certification in certain village contexts may require additional resources to ensure socioeconomic objectives are realized. A study of over 36,000 villages in Indonesia shows that palm oil eco-certification reduces poverty in market-oriented villages but increases it in subsistence villages.

Across the tropics, development banks and conservation donors are investing millions in property mapping and registration projects to improve accountability for deforestation. An evaluation of the effectiveness and accuracy of existing environmental registries is crucial to assure the success of future efforts. This study presents an evaluation of deforestation and registration behavior in response to one of the largest of these property registration programs to date — the Rural Environmental Registry (CAR) in the Amazonian state of Pará. From late 2007 to 2013, approximately 100,000 properties covering 30 million hectares of self-declared claims were entered in this digital registry. We used fixed effects regression models and property level data to assess how registration influenced deforestation on different sizes of properties. Registration had little impact on deforestation behavior, with the exception of a significant reduction on "smallholder" properties in the size range of 100–300 ha. We link this reduction to interacting incentives from forest protection and land regularization policies and suggest that desire to strengthen land claims motivates these landholders' response to the environmental registry. We also present evidence that some landholders may be registering incomplete or inaccurate parcels into the self-declared system to strategically benefit from policy incentives. Our results for smallholder properties indicate that environmental registries may have potential to facilitate reductions in deforestation if combined with a favorable combination of incentives. However, in places where land tenure is still being negotiated, the utility of environmental registries for forest policy enforcement and research may be limited without ongoing investment to resolve uncertainty around land claims.

After decades of decline, croplands are once again expanding across the United States. A recent spatially explicit analysis mapped nearly three million hectares of US cropland expansion that occurred between 2008 and 2012. Land use change (LUC) of this sort can be a major source of anthropogenic carbon (C) emissions, though the effects of this change have yet to be analyzed. We developed a data-driven model that combines these high-resolution maps of cropland expansion with published maps of biomass and soil organic carbon stocks (SOC) to map and quantify the resulting C emissions. Our model increases emphasis on non-forest—i.e. grassland, shrubland and wetland—above and belowground biomass C stocks and the response of SOC to LUC—emission sources that are frequently neglected in traditional C accounting. These sources represent major emission conduits in the US, where new croplands primarily replace grasslands. We find that expansion between 2008–12 caused, on average, a release of 55.0 MgC ha−1 (SDspatial = 39.9 MgC ha−1), which resulted in total emissions of 38.8 TgC yr−1 (95% CI = 21.6–55.8 TgC yr−1). We also find wide geographic variation in both the size and sensitivity of affected C stocks. Grassland conversion was the primary source of emissions, with more than 90% of these emissions originating from SOC stocks. Due to the long accumulation time of SOC, its dominance as a source suggests that emissions may be difficult to mitigate over human-relevant time scales. While methodological limitations regarding the effects of land use legacies and future management remain, our findings emphasize the importance of avoiding LUC emissions and suggest potential means by which natural C stocks can be conserved.

Tropical forests store 340 billion tons of carbon, equivalent to more than 40 years' worth of human fossil fuel emissions ([ 1 ][1]). Tropical deforestation and degradation are responsible for an estimated 20% of global carbon emissions to the atmosphere ([ 2 ][2]). In response, a new policy that

Abstract To understand the changing role of funding sources in shaping conservation science in the United States, we analyzed acknowledgments from published studies, trends in research funding, and survey responses from conservation scientists. Although the U.S. federal government was the most frequently acknowledged source of support overall, U.S. foundations and NGOs were the predominant sources for tropical and socioeconomic research. Acknowledgments of foundation support for conservation research increased over the last two decades, while recognition of federal funds declined. Concordant trends in funding and acknowledgments indicated a changing landscape for conservation science, in which federal support has not kept pace with the growth in conservation research efforts or needs. Survey responses from conservation scientists about their funding sources were consistent with acknowledgment data, and most (64%) indicated that shifts in funding sources and amounts affected the type of research they conduct. Ongoing changes in the funding landscape shape the direction of conservation research and may make conservation science more vulnerable to economic recessions.

Agricultural suitability maps are a key input for land use zoning and projections of cropland expansion. Suitability assessments typically consider edaphic conditions, climate, crop characteristics, and sometimes incorporate accessibility to transportation and market infrastructure. However, correct weighting among these disparate factors is challenging, given rapid development of new crop varieties, irrigation, and road networks, as well as changing global demand for agricultural commodities. Here, we compared three independent assessments of cropland suitability to spatial and temporal dynamics of agricultural expansion in the Brazilian state of Mato Grosso during 2001–2012. We found that areas of recent cropland expansion identified using satellite data were generally designated as low to moderate suitability for rainfed crop production. Our analysis highlighted the abrupt nature of suitability boundaries, rather than smooth gradients of agricultural potential, with little additional cropland expansion beyond the extent of the flattest areas (0–2% slope). Satellite-based estimates of the interannual variability in the use of existing crop areas also provided an alternate means to assess suitability. On average, cropland areas in the Cerrado biome had higher utilization (84%) than croplands in the Amazon region of northern Mato Grosso (74%). Areas of more recent expansion had lower utilization than croplands established before 2002, providing empirical evidence for lower suitability or alternative management strategies (e.g., pasture–soya rotations) for lands undergoing more recent land use transitions. This unplanted reserve constitutes a large area of potentially available cropland (PAC) without further expansion, within the management limits imposed for pest management and fallow cycles. Using two key constraints on future cropland expansion, slope and restrictions on further deforestation of Amazon or Cerrado vegetation, we found little available flat land for further legal expansion of crop production in Mato Grosso. Dynamics of cropland expansion from more than a decade of satellite observations indicated narrow ranges of suitability criteria, restricting PAC under current policy conditions, and emphasizing the advantages of field-scale information to assess suitability and utilization.

The production of soy is one of the most important economic activities in the Brazilian Amazon, though the expansion of this industry has come at the cost of huge swaths of forest. Since 2006, the private firms that buy and trade soybeans globally have assumed a key role in ensuring that soy producers comply with forest protection policies, including the Soy Moratorium and public policies banning the use of illegally deforested land. We used evidence from field interviews and a GIS of property boundaries and soy-production areas to describe the private sector governance process and to characterize the variety of property arrangements underlying soy production in Mato Grosso, the leading soy-producing state in the Brazilian Amazon. These increasingly complex property arrangements include ownership of multiple properties by a single producer, use of rental properties owned by others, and soy and cattle production on a single property. This complexity could create loopholes allowing soy associated with deforestation to enter the supply chain. Comprehensive soy-governance strategies that include more robust procedures for verifying the provenance of soy across all properties, that account for the entire property rather than only the area planted to soy, and that use more transparent verification systems could achieve greater reductions in deforestation.

Abstract. Data on irrigation patterns and trends at field-level detail across broad extents are vital for assessing and managing limited water resources. Until recently, there has been a scarcity of comprehensive, consistent, and frequent irrigation maps for the US. Here we present the new Landsat-based Irrigation Dataset (LANID), which is comprised of 30 m resolution annual irrigation maps covering the conterminous US (CONUS) for the period of 1997–2017. The main dataset identifies the annual extent of irrigated croplands, pastureland, and hay for each year in the study period. Derivative maps include layers on maximum irrigated extent, irrigation frequency and trends, and identification of formerly irrigated areas and intermittently irrigated lands. Temporal analysis reveals that 38.5×106 ha of croplands and pasture–hay has been irrigated, among which the yearly active area ranged from ∼22.6 to 24.7×106 ha. The LANID products provide several improvements over other irrigation data including field-level details on irrigation change and frequency, an annual time step, and a collection of ∼10 000 visually interpreted ground reference locations for the eastern US where such data have been lacking. Our maps demonstrated overall accuracy above 90 % across all years and regions, including in the more humid and challenging-to-map eastern US, marking a significant advancement over other products, whose accuracies ranged from 50 % to 80 %. In terms of change detection, our maps yield per-pixel transition accuracy of 81 % and show good agreement with US Department of Agriculture reports at both county and state levels. The described annual maps, derivative layers, and ground reference data provide users with unique opportunities to study local to nationwide trends, driving forces, and consequences of irrigation and encourage the further development and assessment of new approaches for improved mapping of irrigation, especially in challenging areas like the eastern US. The annual LANID maps, derivative products, and ground reference data are available through https://doi.org/10.5281/zenodo.5548555 (Xie and Lark, 2021a).

We examine two potential economic benefits of environmental policy, increased agricultural investment and productivity. This is important because if these benefits are realized, environmental policy could optimize land use for food production while minimizing the negative environmental impacts. We employ multiple empirical techniques to analyze a market-led and a public-led anti-deforestation policy that influence the vast cattle ranching sector in the Brazilian Amazon. We show that both policies increased cattle productivity, while the market-led policy also increased investment. We find no evidence that the two policies were substitutes or complements. Results indicate that the policies were each effective in different market- and land-use-contexts, so that enforcement of both policies increased productivity for a larger set of properties. Our research reveals both indirect and unintended benefits of environmental regulation, which have implications for the design of policies that affect the agricultural sector, a major driver of land-use change.

Abstract We quantified the avoided deforestation impacts of environmental land registration in Brazil's Amazonian states of Mato Grosso and Pará between 2005 and 2014. We find that the program reduced deforestation on registered lands. The magnitude of the effect implies that deforestation in the two states would have been 10% higher in the absence of the program. The impacts of registration varied over time, likely due to changing suites of policies linking environmental registration to land use incentives. Our results also reveal that agriculturally suitable lands and those located in regions undergoing the most land‐use change were more likely to be registered than those in less suitable, less dynamic regions. We conclude that environmental registration is an important first step in implementing avoided deforestation policies targeting private landholders.

Global attention to the role of cattle production in Amazon deforestation led to the development of new public and private-sector supply chain policies designed to control deforestation in Brazil. These zero-deforestation Cattle Agreements (hereafter, CA) are between meatpacking companies and Greenpeace and other nongovernmental organizations, as well as with Brazil’s public prosecutors. However, after over a decade of concerted efforts to reduce deforestation linked to the cattle sector, the problem persists. Here, we use field surveys of ranchers, slaughterhouse managers, and key industry personnel to characterize cattle supply chain actors in southeastern Pará and their responses to the CA. We show that loopholes weaken the CA and enable ranchers to evade full compliance, and we highlight strategies and challenges for ranchers seeking to intensify production. We conclude by discussing how the findings presented in this study suggest that ongoing efforts to reduce Amazon deforestation may require both support for improved efficiency in the cattle sector and the tightening of several loopholes currently utilized by ranchers to avoid detection of ongoing deforestation.

"Indirect land use change for biofuels: Testing predictions and improving analytical methodologies" by S. Kim and B. Dale [1], presents a principal inference not supported by its results, that rests on a fundamental conceptual error, and that has no place in the current discussion of biofuels' climate effects. The paper takes correlation between two variables in a system with many interacting factors to indicate (or contraindicate) causation, and draws a completely incorrect inference from observed sample statistics and their significance levels.

Summary Unplowed native grasslands are among the most endangered ecosystems in the world, due in large part to their agricultural suitability and widespread conversion to cropland. Despite this, remaining locations of these species- and carbon-rich landscapes are neither well monitored nor effectively protected. A recent spike in US prices for corn ( Zea mays ) and soybeans ( Glycine max ) intensified incentives to bring new land into production, potentially hastening the conversion of grasslands to crops. We combined satellite-based land cover data with aerial photographs and a field-based inventory of remaining native grassland (hereafter prairie) in Minnesota to assess the areas, rates, and locations of prairie conversion since 2008. Our results reveal that during 2008–2012, prairie was converted at average annual rates more than four times greater than the previous decade and a half. Corn and soybeans were the initial crops planted on 73% of converted prairie, and more than 80% of conversion occurred in recently established conservation priority zones, thereby magnifying the urgency to protect these sites. Broader land-use trends in Minnesota suggest that expansion of both croplands and developed lands continues to threaten all grasslands, including the subset that is prairie, and that the growth of developed or built-up land may be amplifying the conversion pressure exerted by agriculture, though further research is needed. Despite the small total area of prairie lost, the multi-fold increase in conversion rates and the confirmation of native habitat clearing may have substantial conservation implications, especially given the very limited prairie that remains in the region. The overall results reveal challenges for federal policies, including a loophole in the crop insurance Sodsaver provision surrounding alfalfa hay and limitations in the current enforcement of the Renewable Fuel Standard.

Abstract The cattle industry in the Brazilian Amazon causes vast deforestation while producing at only one-third of the sustainable capacity. Slaughtering cattle at a younger age directly increases production per hectare per year, all else equal, and provides a potential path for sustainable intensification. Here we show that slaughter age is decreasing in the Amazon biome, but this increase in productivity varies across space and throughout the cattle supply chain. We characterize the properties and municipalities that have reduced slaughter age, providing insights into the incentives and barriers to this form of intensification. Most notably, reductions in slaughter age occurred in regions with low remaining forest cover and on properties with little current deforestation, suggesting that ranchers intensify via slaughter age as an alternative to deforestation. We then estimate how changing production practices to reduce slaughter age can reduce enteric methane emissions, accounting for production of additional feed. Our results indicate that reducing slaughter age through improved pasture and feed sources are a path to lower global GHG emissions from cattle production, particularly as beef is increasingly produced in developing countries with historically higher emissions. Yet in the Amazon, deforestation remains the leading source of GHG emissions, necessitating that any effort to reduce slaughter age must be coupled with strict enforcement of zero-deforestation policy. Our findings demonstrate the potential of policy limiting deforestation as a means to reduce both emissions from deforestation and enteric emissions from cattle.

Transitioning to a sustainable energy system poses a massive challenge to communities, nations, and the global economy in the next decade and beyond. A growing portfolio of satellite data products is available to support this transition. Satellite data complement other information sources to provide a more complete picture of the global energy system, often with continuous spatial coverage over targeted areas or even the entire Earth. We find that satellite data are already being applied to a wide range of energy issues with varying information needs, from planning and operation of renewable energy projects, to tracking changing patterns in energy access and use, to monitoring environmental impacts and verifying the effectiveness of emissions reduction efforts. While satellite data could play a larger role throughout the policy and planning lifecycle, there are technical, social, and structural barriers to their increased use. We conclude with a discussion of opportunities for satellite data applications to energy and recommendations for research to maximize the value of satellite data for sustainable energy transitions.

Carbon emissions from tropical deforestation have long been recognized as a key component of the global carbon budget, and more recently of our global climate system. Tropical forest clearing accounts for roughly 20% of anthropogenic carbon emissions and destroys globally significant carbon sinks (IPCC 2007). Global climate policy initiatives are now being proposed to address these emissions and to more actively include developing countries in greenhouse gas mitigation (e.g. Santilli et al 2005, Gullison et al 2007). In 2005, at the Conference of the Parties (COP) in Montreal, the United Nations Framework Convention on Climate Change (UNFCCC) launched a new initiative to assess the scientific and technical methods and issues for developing policy approaches and incentives to reduce emissions from deforestation and degradation (REDD) in developing countries (Gullison et al 2007).

The purpose of the agro-ecological zone emission factor model (AEZ-EF) is to estimate the total CO2-equivalent emissions from land use changes, e.g., from an analysis of biofuels impacts or policy analyses such as estimating the effect of changes in agricultural productivity on emissions from land use. The model combines matrices of carbon fluxes (Mg CO2/ha/y) with matrices of changes in land use (ha) according to land-use category as projected by GTAP or similar AEZ-oriented models. As published, AEZ-EF aggregates the carbon flows to the same 19 regions and 18 AEZs used by GTAP-BIO, the version of GTAP currently used by Purdue University researchers for modeling biofuel-induced ("indirect") land-use change (ILUC) (e.g., Tyner, Taheripour et al. 2010). The AEZ-EF model, however, is designed to work with an arbitrary number of regions, as described in the accompanying report.

Abstract. Indonesia and Malaysia have emerged as leading producers of palm oil in the past several decades, expanding production through the conversion of tropical forests to industrial plantations. Efforts to produce sustainable palm oil, including certification by the Roundtable on Sustainable Palm Oil (RSPO), include guidelines designed to reduce the environmental impact of palm oil production. Fire-driven deforestation is prohibited by law in both countries and a stipulation of RSPO certification, yet the degree of environmental compliance is unclear, especially during El Niño events when drought conditions increase fire risk. Here, we used time series of satellite data to estimate the spatial and temporal patterns of fire-driven deforestation on and around oil palm plantations. In Indonesia, fire-driven deforestation accounted for one-quarter of total forest losses on both certified and noncertified plantations. After the first plantations in Indonesia received RSPO certification in 2009, forest loss and fire-driven deforestation declined on certified plantations but did not stop altogether. Oil palm expansion in Malaysia rarely involved fire; only 5 % of forest loss on certified plantations had coincident active fire detections. Interannual variability in fire detections was strongly influenced by El Niño and the timing of certification. Fire activity during the 2002, 2004, and 2006 El Niño events was similar among oil palm plantations in Indonesia that would later become certified, noncertified plantations, and surrounding areas. However, total fire activity was 75 % and 66 % lower on certified plantations than noncertified plantations during the 2009 and 2015 El Niño events, respectively. The decline in fire activity on certified plantations, including during drought periods, highlights the potential for RSPO certification to safeguard carbon stocks in peatlands and remaining forests in accordance with legislation banning fires. However, aligning certification standards with satellite monitoring capabilities will be critical to realize sustainable palm oil production and meet industry commitments to zero deforestation.

Roundtables for sustainable beef have evolved in national contexts as well as at the global level as a multi-stakeholder process to address sustainability concerns in the cattle sector. However, due to their relatively recent inception, the literature on the beef roundtables is extremely limited and very little scholarly work has traced their process or impact. We used semi-structured interviews with key informants to examine the governance, actions, and potential impacts of the roundtables for sustainable beef, and identified opportunities and challenges for achieving greater sustainability impact. We found that the beef roundtables are in different stages of development and implementation and that they have diverse approaches based on their geographic contexts. However, they have universally adopted a model of sector-wide continuous improvement, in contrast to roundtables for other commodities, which have in many cases adopted formal certification programs. Activities by the roundtables for sustainable beef have variously included working towards definitions of sustainable beef; setting sustainability principles and criteria; and creating working groups to address specific aspects of sustainability (e.g., verification, deforestation). Our interviews identified opportunities to expand the roundtables’ roles, activities, and sustainability impacts. This study provides a benchmark of the roundtables’ efforts to date, and generates hypotheses and ideas for how they could evolve in the future.

Since 2013, clearing rates have rapidly increased in the Amazon and Cerrado biomes. This acceleration has raised questions about the efficacy of current regional public and private conservation policies that seek to promote agricultural production while conserving remnants of natural vegetation. In this study, we assessed conservation and agricultural outcomes of four potential policy scenarios that represent perfect adherence to private sector, zero-deforestation commitments (i.e., the Amazon soy moratorium—ASM and the Amazon cattle agreements—CA) and to varying levels of implementation of the Brazilian Forest Code (FC). Under a zero-clearing scenario, we find that the extent of croplands as of 2017 within the two biomes (31 MHa) could double without further clearing if agriculture were to expand on all previously cleared land that is suitable for crops. Moreover, at least 47 MHa of land that is already cleared but unsuitable for crops would remain available for pasture. Under scenarios in which only legal clearing under the FC could occur, 51 MHa of additional natural vegetation could be cleared. This includes as many as 1 MHa of nonforest vegetation that could be cleared in the Amazon biome without triggering the ASM and CA monitoring systems. Two-thirds of the total vegetation vulnerable to legal clearing is located within the Cerrado biome, and 19 MHa of this land is suitable for cropland expansion. Legal clearing of all of these areas could reduce biodiversity persistence by 4% within the two biomes, when compared with the zero-clearing scenario, and release up to 9 PgCO2e, with the majority (75%) coming from the Cerrado biome. However, when we considered the potential outcomes of full implementation of the FC, we found that 22% (11 MHa) of the 51 MHa of vegetation subject to legal clearing could be protected through the environmental quotas market, while an additional 1 MHa should be replanted across the two biomes, predominantly in the Amazon biome (73% of the area subject to replanting). Together, quotas and replanting could prevent the release of 2 PgCO2e that would otherwise be emitted if all legal clearing occurred. Based on our results, we conclude that ongoing legal clearing could create additional space for cropland and cattle production beyond the substantial existing stocks of cleared areas but would significantly impair local carbon and biodiversity stocks.

Several payments for environmental services (PES) schemes to promote large-scale afforestation are currently operational in New Zealand. In addition, the country has the only national greenhouse gas (GHG) Emissions Trading Scheme centred on forest carbon credits in the world. These market-based instruments are paramount in promoting the changes in land use required to achieve New Zealand’s GHG-emission targets under the Paris Agreement, as well as to pave the way towards the goal of a low-carbon economy by 2050. We estimated the impacts of PES schemes on the profitability of Pinus radiata forestry to identify low-productivity grasslands where afforestation is likely to financially offset the current land use (i.e., mainly sheep-and-beef farming), under the assumption of constant returns to scale. We find that even without PES, 56% of these agricultural lands present lower economic returns than forestry. When PES are considered, results suggest that, depending on the PES schemes and carbon prices, 77–100% of the low-productivity grassland areas could financially benefit from afforestation. If realized, afforestation of those lands could result in the long-term removal of 1.2–1.5 Pg CO2 from the atmosphere.

Fanny Moffette, Researcher Nelson Institute for Environmental Studies, Center for Sustainability and the Global Environment (SAGE), and Department of Agricultural and Applied Economics, University of Wisconsin–Madison; Enzyme Institute, Madison, Wisconsin; fanny.moffette{at}wisc.edu

Abstract In their recent contribution, Scully et al (2021 Environ. Res. Lett. 16 043001) review and revise past life cycle assessments of corn-grain ethanol’s carbon (C) intensity to suggest that a current ‘central best estimate’ is considerably less than all prior estimates. Their conclusion emerges from selection and recombination of sector-specific greenhouse gas emission predictions from disparate studies in a way that disproportionately favors small values and optimistic assumptions without rigorous justification nor empirical support. Their revisions most profoundly reduce predicted land use change (LUC) emissions, for which they propose a central estimate that is roughly half the smallest comparable value they review (figure 1). This LUC estimate represents the midpoint of (a) values retained after filtering the predictions of past studies based on a set of unfounded criteria; and (b) a new estimate they generate for domestic (i.e. U.S.) LUC emissions. The filter the authors apply endorses a singular means of LUC assessment which they assert as the ‘best practice’ despite a recent unacknowledged review (Malins et al 2020 J. Clean. Prod. 258 120716) that shows this method almost certainly underestimates LUC. Moreover, their domestic C intensity estimate surprisingly suggests that cropland expansion newly sequesters soil C, counter to ecological theory and empirical evidence. These issues, among others, prove to grossly underestimate the C intensity of corn-grain ethanol and mischaracterize the state of our science at the risk of perversely affecting policy outcomes.

Abstract Cattle production inside Brazil's protected areas (PAs), including indigenous lands, continues to contaminate Amazonian supply chains more than a decade after efforts to reform the sector were launched with the signing of the zero‐deforestation cattle agreements (CAs). During 2013–2018, nearly 1.1 million cattle head were sold directly from private properties inside PAs to slaughterhouses in Mato Grosso, Pará, and Rondônia states. Another 2.2 million head were linked via indirect suppliers located in PAs. Most of these 3.3 million slaughtered head were originated in to sustainable‐use areas (72%), where cattle ranching may be permitted in certain cases; however, production also occurred in strictly protected units (20%) and indigenous lands (8%), where commercial grazing activities are illegal and prohibited by the CAs. Nearly half of the PA properties linked to cattle transactions from 2013 to 2018 also had deforestation. We estimate that approximately 2.8 million cattle head from properties in PAs were sold to slaughterhouses participating in the CAs (86% of the total cattle from indirect suppliers in PAs). Controlling commercial cattle production inside of PAs is crucial to both ensure Brazil's access to international beef markets and protect critical biodiversity regions in the Amazon rainforest.

Over the last several decades, Brazil has become both the world's leading soy producer and the world's leading consumer of hazardous pesticides. Despite identified links between pesticide exposure and carcinogenesis, there has been little population-level research on the effects of pesticide intensification on broader human health in Brazil. We estimate the relationship between expanded soy production-and related community exposure to pesticides-on childhood cancer incidence using 15 y of data on disease mortality. We find a statistically significant increase in pediatric leukemia following expanded local soy production, but timely access to treatment mitigates this relationship. We show that pesticide exposure likely occurs via water supply penetration. Our findings represent only the tip of the iceberg for substantial health externalities of high-input crop production and land use change. Our results are of particular interest in developing contexts with demand for intensified food production systems and underscore the need for stronger regulation of pesticides and increased public health attention to exposure in the broader community.

Historically, the expansion of soy plantations has been a major driver of land-use/cover change (LUCC) in Brazil. While a series of recent public actions and supply-chain commitments reportedly curbed the replacement of forests by soy, the expansion of the agricultural commodity still poses a considerable threat to the Amazonian and Cerrado biomes. Identification of areas under high risk of soy expansion is thus paramount to assist conservation efforts in the region. We mapped the areas suitable for undergoing transition to soy plantations in the Legal Amazon with a machine-learning approach adopted from the ecological modeling literature. Simulated soy expansion for the year 2014 exhibited favorable validation scores compared to other LUCC models. We then used our model to simulate how potential future infrastructure improvements would affect the 2014 probabilities of soy occurrence in the region. In addition to the 2.3 Mha of planted soy in the Legal Amazon in 2014, our model identified another 14.7 Mha with high probability of soy conversion in the region given the infrastructure conditions at that time. Out of those, pastures and forests represented 9.8 and 0.4 Mha, respectively. Under the new infrastructure scenarios simulated, the Legal Amazonian area under high risk of soy conversion increased by up to 2.1 Mha (14.6%). These changes led to up to 11.4 and 51.4% increases in the high-risk of conversion areas of pastures and forests, respectively. If conversion occurs in the identified high-risk areas, at least 4.8 Pg of CO2 could be released into the atmosphere, a value that represents 10 times the total CO2 emissions of Brazil in 2014. Our results highlight the importance of targeting conservation policies and enforcement actions, including the Soy Moratorium, to mitigate future forest cover loss associated with infrastructure improvements in the region.

We synthesized a range of geographically-explicit forest, grassland and cropland biomass and soil carbon input data sources and used geographic information systems (GIS) software to calculate new estimates of soil and biomass carbon stocks for use with global economic models, particularly for the Global Trade and Analysis Project (GTAP). Our results quantify the average amount of carbon stored in soil and biomass in each of the 246 countries, stratified by agro-ecological zones (available in the accompanying spreadsheet). We also provide the data aggregated to the 134 regions defined for the GTAP 8.1 database both in spreadsheet form and in GTAP’s native binary file format. Finally, we provide an add-on to FlexAgg2 program to further aggregate the 134 regions as desired. Our analysis makes substantial refinements to the estimates of carbon stocks used for modeling carbon emissions from indirect land use change. The spatial detail of our analysis is a major advantage over previous databases because it provides estimates tailored to the regions of interest and better accounts for the variation of carbon stocks across the landscape, and between wetland and non-wetland regions.

Summary 1. The governments of Norway and Indonesia are collaborating on a REDD+ partnership that would contribute to reductions in greenhouse gas emissions from deforestation, forest degradation and peatland conversion in Indonesia. Part of this agreement requires Indonesia to implement a 2‐year moratorium to suspend the issuance of new permits for conversion of peat and natural forests for forestry or agriculture. 2. This partnership offers an unprecedented opportunity for Indonesia to mitigate its deforestation and carbon emission levels. However, it has also galvanized intense debates within Indonesian society regarding the scope of the moratorium and its consequent environmental and socioeconomic ramifications. 3. We developed a web‐based application for evaluating the implications and trade‐offs of implementing Indonesia’s forest moratorium in Kalimantan. This spatially explicit tool quantifies the moratorium’s benefits for carbon conservation and its opportunity costs under alternative user‐defined moratorium scenarios. This application could serve as a useful framework for understanding the costs and benefits of REDD+ implementation across Indonesia and other forest‐rich tropical nations.

Our knowledge of how agriculture expands, and the types of land it replaces, is remarkably limited across the tropics. Most remote-sensing studies focus on the net gains and losses in forests and agricultural land rather than the land-use transition pathways (Gibbs et al 2010). Only a handful of studies identify land sources for new croplands or plantations, and then only for farming systems aggregated together (e.g., Koh and Wilcove 2008, Morton et al 2006, Gibbs et al 2010). Gutiérrez-Vélez et al (2011), however, have taken a leap forward by tracking the different expansion pathways for smallholder and industrial oil palm plantations.

Brazil’s Amazon Soy Moratorium (ASM) contributed to overall reductions in Amazon deforestation since its implementation in 2006. Under the ASM, the Amazon soy sector maintains access to the growing share of the market that operates under zero-deforestation commitments. The ASM has been criticized as unfair to law-abiding producers. Only 1% of the approximately 14,000 soy farms in the Amazon Biome have soy-suitable, forested areas that could be deforested lawfully (49,273 ha). More than half of Amazon soy farms have soy-suitable areas that were deforested before 2008 and used for soy in 2019 (1.7 Mha). Taken together, these findings suggest that the opportunity costs of the ASM on current soy farms are low relative to the market access benefits.

1 Overview The purpose of the agro-ecological zone emission factor (AEZ-EF) model is to estimate the total CO2equivalent emissions induced by expanded biofuel production. The model combines matrices of carbon fluxes (Mg CO2 ha -1 y) with matrices of changes in land use (ha) by land-use category projected by the GTAP model. The carbon fluxes in AEZ-EF are aggregated to the same 19 regions (Table 1) and 18 AEZs (Figure 1) used by GTAP-BIO-ADV, the version of GTAP currently used by Purdue University researchers for ILUC modeling (e.g., Tyner, Taheripour et al. 2010).

The state of Mato Grosso is Brazil’s agribusiness powerhouse with a cattle herd of 30.2 million head in 2017. With land use patterns heavily influenced by beef production, which requires substantial land inputs, the state is a key target for environmental conservation. Yet the spatial and temporal dynamics of slaughterhouses in Mato Grosso remain largely unknown due to data limitations. Here, we provide a novel method to map slaughterhouse expansion and contraction. We analyzed the opening and closing of 133 plants between 1967 and 2016 in Mato Grosso and estimated the geographic locations and slaughter volumes. This was achieved by triangulating across multiple data sources including a registry of 21 million companies, government records of three million slaughter transactions (Portuguese acronym GTA), and high resolution satellite imagery. Our study is the first to include longitudinal information and both inspected (for food quality) and uninspected slaughterhouses. The results show that 72 plants operated in 2016 through 52 holding companies. By measuring geographic distances between active plants and pasture areas, we documented a 29% increase in the density of plants during 2000–2016, showing an expansion of the cattle slaughter infrastructure. We identified three periods of expansion: 1967–1995, with 15.1% of the plant openings; 1996–2003, with 24.6%; and 2004–2016, with 60.3%. While closings likely occurred throughout the period studied, no data were available prior to 2002. We estimated a minimum value for the volume of uninspected slaughter as 2–3% for 2013–2016. We conclude by discussing potential applications of the data, a deidentified version of which is made available through an online repository. The method developed here can be replicated for the whole country, which would increase our understanding of the dynamics of cattle slaughter and their impact on land use.

By pooling many sources of hydrologic information, a multilaboratory investigation of a watershed in Kansas identified ways to achieve closure of the water budget in observations and modeling.

This chapter contains sections titled: Introduction Approach and methods Potential ecosystem service value: economic values irrespective of use Realised services: valuing ecosystem services by considering their use Essential services: valuing the ecosystem services the poor rely upon Estimating all benefits to the poor: essential services and payments for environmental services Conclusions: linking ecosystem service flows, people and biodiversity Acknowledgements References

Brazil’s zero-deforestation Cattle Agreements (CAs) have influenced the supply chain but their impact on deforestation has been limited in part because slaughterhouses monitor deforestation only on the properties they buy from directly. Consequently, deforestation continues to enter the supply chain indirectly from properties that are not monitored. Knowledge gaps and data limitations have made it challenging to close this loophole and achieve meaningful reductions in deforestation. Here we leverage our large property-level supply chain database that links together six years of records from the Animal Transport Guide (GTA), high-resolution satellite data, property boundaries, and land cover data to quantify different types of supply chain connections and characterize cattle production in Mato Grosso. We find that a relatively small number of high-volume suppliers—defined as the top 5% of cattle suppliers in terms of the volume of cattle sold–supplied 50–60% of the total volume purchased by major slaughterhouses. One-fourth of high-volume direct suppliers cleared forest between 2009–2018, and 90% of them also bought from indirect suppliers with deforestation, leading these high-volume direct suppliers to act as funnels for deforestation into the supply chain. Because they serve as important hubs in the supply chain, high-volume suppliers may represent a key starting point to expand the CAs to cover large numbers of indirect suppliers.

This report is a rapid assessment analysis undertaken to inform the UK's Eliasch Review on the role of international finance mechanisms to preserve global forests in tackling climate change. The results should be used with an understanding of the caveats specified at the end of the report.

to, protected areas in reducing deforestation.

Mapping slaughterhouse supply zones is crucial for assessing cattle concentration, environmental impact, and promoting sustainable practices. This study combines cattle transit records (GTA in Portuguese) with rural property boundaries (CAR in Portuguese) to map these zones in the Brazilian Amazon. It evaluates the influence of Zero-Deforestation Cattle Agreements (CA) and explores the overlap between CA and non−CA slaughterhouse supply zones. Results reveal that CA slaughterhouse supply zones significantly impact forest preservation and cover a large area equivalent to entire municipalities. Over two-thirds of the study region, including most non-protected areas, falls within these zones. There is a high degree of overlap (95%) with non−CA supply zones, indicating competition for suppliers and limited expansion potential for CA. Direct and indirect suppliers are located nearby, with approximately 80% of indirect suppliers within 100 km of direct suppliers. Consequently, supply zones for both types of suppliers largely overlap. These findings demonstrate that assessing slaughterhouse deforestation risk for the entire supply chain in our study region can be achieved by mapping only the direct suppliers. This research provides valuable insights into cattle concentration, the effectiveness of zero-deforestation commitments, and the need for sustainable practices in the slaughterhouse industry.

Abstract. Soil and vegetation carbon densities play a critical role in global and regional human-Earth system models and MultiSector Dynamics Models. These densities affect variables such as land use change emissions and also influence land use change pathways under climate forcing scenarios where terrestrial carbon is assigned a carbon price. Recently, more spatially explicit, fine resolution data have become available for both soil and vegetation carbon. However, for models to effectively use these data the fine resolution data need to be reharmonized to the initial land use and land cover conditions represented by these models. Without such reharmonization the carbon values may be inaccurate for particular land types and places where the source data and the model disagree on the land use/cover type. Here we present reharmonized soil and vegetation carbon densities both at the 5-arcmin resolution grid cell level and also aggregated to 235 water sheds for 4 land use types and 15 land cover types. These data are particularly useful as initial land carbon conditions for global Multisectoral Dynamic Models (MSD). Moreover, these data include six different statistical states calculated using distinct resampling methods for each of the land use and land cover types. These statistical states are used to define a range of possible carbon values for each land classification, and any state can be used for defining initial conditions of soil and vegetation carbon in MSD models. Users can also estimate any percentile of the carbon distribution defined by these six summary states. We make use of these statistical states to calculate spatially distinct uncertainties in the carbon densities by land type. We have implemented these data in a state-of-the-art multi sector dynamics model, namely the Global Change Analysis Model (GCAM), and show that these new data improve several land use responses in the model, especially when terrestrial carbon is assigned a carbon price. The statistical states in our data are validated against similar estimates in the literature both at a grid cell level and at a regional level.

SI Figure 2: Topsoil (0-30 cms) carbon densities in MgC/ha by land cover type for the Q3 state.Carbon values are shown here for unmanaged land types.

Soil and vegetation carbon densities play a critical role in global and regional human-Earth system models. These densities affect variables such as land use change emissions and also influence land use change pathways under climate mitigation scenarios where terrestrial carbon is assigned a carbon price. Recently, more spatially explicit, fine resolution data have become available for both soil and vegetation carbon. However, for models to effectively use these data the fine resolution data need to be reharmonized to initial land use and land cover conditions represented by these models. Without such reharmonization the carbon values may be very inaccurate for particular land types and places where the source data and the model disagree on the land use/cover type. Here we present reharmonized soil and vegetation carbon densities both at the grid cell level at 5 arcmin resolution and also aggregated to 235 water sheds for 4 different land use and 15 land cover types. These data are particularly useful as initial land carbon conditions for global Multisectoral Dynamic Models (MSD). Moreover, these data include six different statistical states calculated using distinct resampling methods for each of the land use, land cover types. These statistical states are used to define a range of possible carbon values for each land classification, and any state can be used for defining initial conditions of soil and vegetation carbon in MSD models. We make use of these statistical states to calculate spatially distinct uncertainties in the carbon densities by land type. We have implemented these data in a state-of-the-art multi sector dynamics model, namely the Global Change Analysis Model (GCAM), and show that these new data improve several land use responses in the model, especially when terrestrial carbon is assigned a carbon price. The statistical states in our data are validated against similar estimates in the literature both at a grid cell level and at a regional level. This is a data record which corresponds to the paper "Spatially explicit re-harmonized terrestrial carbon densities for calibrating Integrated Multisectoral Models" (Narayan et al. 2023, in prep)

Soil and vegetation carbon densities play a critical role in global and regional human-Earth system models. These densities affect variables such as land use change emissions and also influence land use change pathways under climate mitigation scenarios where terrestrial carbon is assigned a carbon price. Recently, more spatially explicit, fine resolution data have become available for both soil and vegetation carbon. However, for models to effectively use these data the fine resolution data need to be reharmonized to initial land use and land cover conditions represented by these models. Without such reharmonization the carbon values may be very inaccurate for particular land types and places where the source data and the model disagree on the land use/cover type. Here we present reharmonized soil and vegetation carbon densities both at the grid cell level at 5 arcmin resolution and also aggregated to 235 water sheds for 4 different land use and 15 land cover types. These data are particularly useful as initial land carbon conditions for global Multisectoral Dynamic Models (MSD). Moreover, these data include six different statistical states calculated using distinct resampling methods for each of the land use, land cover types. These statistical states are used to define a range of possible carbon values for each land classification, and any state can be used for defining initial conditions of soil and vegetation carbon in MSD models. We make use of these statistical states to calculate spatially distinct uncertainties in the carbon densities by land type. We have implemented these data in a state-of-the-art multi sector dynamics model, namely the Global Change Analysis Model (GCAM), and show that these new data improve several land use responses in the model, especially when terrestrial carbon is assigned a carbon price. The statistical states in our data are validated against similar estimates in the literature both at a grid cell level and at a regional level. This is a data record which corresponds to the paper "Spatially explicit re-harmonized terrestrial carbon densities for calibrating Integrated Multisectoral Models" (Narayan et al. 2023, in prep)

The processed data supporting the Global Environmental Change publication "Deforestation in the Brazilian Amazon could be halved by scaling up the implementation of zero-deforestation cattle commitments". These data can be analyzed and visualized with the code at: https://github.com/sam-a-levy/Levyetal2023_cattlemarketshare For a description of each file & the variables contained, please look to the README file.

The processed data supporting the Global Environmental Change publication "Deforestation in the Brazilian Amazon could be halved by scaling up the implementation of zero-deforestation cattle commitments". These data can be analyzed and visualized with the code at: https://github.com/sam-a-levy/Levyetal2023_cattlemarketshare For a description of each file & the variables contained, please look to the README file.

Deforestation for agriculture is the primary threat to global aboveground carbon stocks. In the absence of strong territorial-governance, zero-deforestation commitments (ZDCs), corporate policies to decouple food production from deforestation, remain a central tool to combat this issue. Yet evidence on their effectiveness remains mixed. To advance understanding of ZDCs potential at reducing deforestation, we developed the first spatially explicit estimates of farmers exposure to ZDC companies in the Brazilian Amazon cattle sector in terms of market share and evaluated how variation in this exposure influenced deforestation. We find the G4 Agreement, the most widespread and strongly implemented cattle ZDC, reduced deforestation by 7,000±4,000 km2 (15±8%) and had all firms adopted an effective ZDC, deforestation could have dropped by 24,000±13,000 km2 (50±28%). These results for the world’s principal deforestation hotspot suggests supply chain policies can substantially reduce deforestation, but their effectiveness is contingent on increasing adoption and implementation through import regulations

Abstract. Data on irrigation patterns and trends at field-level detail across broad extents is vital for assessing and managing limited water resources. Until recently, there has been a scarcity of comprehensive, consistent, and frequent irrigation maps for the U.S. Here we present the new Landsat-based Irrigation Dataset (LANID), which is comprised of 30-m resolution annual irrigation maps covering the conterminous U.S. (CONUS) for the period of 1997–2017. The main dataset identifies the annual extent of irrigated croplands, pastureland, and hay for each year in the study period. Derivative maps include layers on maximum irrigated extent, irrigation frequency and trends, and identification of formerly irrigated areas and intermittently irrigated lands. Temporal analysis reveals that 38.5 million hectares of croplands and pasture/hay have been irrigated, among which the yearly active area ranged from ~22.6 to 24.7 million hectares. The LANID products provide several improvements over other irrigation data including field-level details on irrigation change and frequency, an annual time step, and a collection of ~10,000 visually interpreted ground reference locations for the eastern U.S. where such data has been lacking. Our maps demonstrated overall accuracy above 90 % across all years and regions, including in the more humid and challenging-to-map eastern U.S., marking a significant advancement over other products, whose accuracies ranged from 50 to 80 %. In terms of change detection, our maps yield per-pixel transition accuracy of 81 % and show good agreement with U.S. Department of Agriculture reports at both county and state levels. The described annual maps, derivative layers, and ground reference data provide users with unique opportunities to study local to nationwide trends, driving forces, and consequences of irrigation and encourage the further development and assessment of new approaches for improved mapping of irrigation especially in challenging areas like the eastern U.S. The annual LANID maps, derivative products, and ground reference data are available through https://doi.org/10.5281/zenodo.5003976 (Xie et al., 2021).

The Roundtable on Sustainable Palm Oil (RSPO) has emerged as the leading sustainability certification system to tackle socio-environmental issues associated with the oil palm industry. To date, the effectiveness of RSPO certification for achieving its socioeconomic objectives remains uncertain. We evaluate the impact of certification on village-level well-being across Indonesia by applying counterfactual analysis to multi-dimensional government poverty data. We compare poverty across 36,311 villages between 2000 and 2018, tracking changes from before oil palm plantations were first established to several years after plantations were certified. Certification was associated with reduced poverty in villages with primarily market-based livelihoods, but not with those in which subsistence livelihoods were dominant before switching to oil palm. We highlight the importance of baseline village livelihood systems in shaping local impacts of agricultural certification, and assert that oil palm certification in certain village contexts may require additional resources to ensure certification’s socioeconomic objectives are realised.

We synthesized a range of geographically-explicit forest, grassland and cropland biomass and soil carbon input data sources and used geographic information systems (GIS) software to calculate new estimates of soil and biomass carbon stocks for use with global economic models, particularly for the Global Trade and Analysis Project (GTAP). Our results quantify the average amount of carbon stored in soil and biomass in each of the 246 countries, stratified by agro-ecological zones (available in the accompanying spreadsheet). We also provide the data aggregated to the 134 regions defined for the GTAP 8.1 database both in spreadsheet form and in GTAP’s native binary file format. Finally, we provide an add-on to FlexAgg2 program to further aggregate the 134 regions as desired. Our analysis makes substantial refinements to the estimates of carbon stocks used for modeling carbon emissions from indirect land use change. The spatial detail of our analysis is a major advantage over previous databases because it provides estimates tailored to the regions of interest and better accounts for the variation of carbon stocks across the landscape, and between wetland and non-wetland regions.

The purpose of the agro-ecological zone emission factor model (AEZ-EF) is to estimate the total CO2-equivalent emissions from land use changes, e.g., from an analysis of biofuels impacts or policy analyses such as estimating the effect of changes in agricultural productivity on emissions from land use. The model combines matrices of carbon fluxes (Mg CO2/ha/y) with matrices of changes in land use (ha) according to land-use category as projected by GTAP or similar AEZ-oriented models. As published, AEZ-EF aggregates the carbon flows to the same 19 regions and 18 AEZs used by GTAP-BIO, the version of GTAP currently used by Purdue University researchers for modeling biofuel-induced (indirect) land-use change (ILUC) (e.g., Tyner, Taheripour et al. 2010). The AEZ-EF model, however, is designed to work with an arbitrary number of regions, as described in the accompanying report.