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Despite the looming land scarcity for agriculture, cropland abandonment is widespread globally. Abandoned cropland can be reused to support food security and climate change mitigation. Here, we investigate the potentials and trade-offs of using global abandoned cropland for recultivation and restoring forests by natural regrowth, with spatially-explicit modelling and scenario analysis. We identify 101 Mha of abandoned cropland between 1992 and 2020, with a capability of concurrently delivering 29 to 363 Peta-calories yr -1 of food production potential and 290 to 1,066 MtCO 2 yr -1 of net climate change mitigation potential, depending on land-use suitability and land allocation strategies. We also show that applying spatial prioritization is key to maximizing the achievable potentials of abandoned cropland and demonstrate other possible approaches to further increase these potentials. Our findings offer timely insights into the potentials of abandoned cropland and can inform sustainable land management to buttress food security and climate goals., (© 2023. Springer Nature Limited.)

Natural climate solutions (NCS) are an essential complement to climate mitigation and have been increasingly incorporated into international mitigation strategies. Yet, with the ongoing population growth, allocating natural areas for NCS may compete with other socioeconomic priorities, especially urban development and food security. Here, we projected the impacts of land-use competition incurred by cropland and urban expansion on the climate mitigation potential of NCS. We mapped the areas available for implementing 9 key NCS strategies and estimated their climate change mitigation potential. Then, we overlaid these areas with future cropland and urban expansion maps projected under three Shared Socioeconomic Pathway (SSP) scenarios (2020-2100) and calculated the resulting mitigation potential loss of each selected NCS strategy. Our results estimate a substantial reduction, 0.3-2.8 GtCO 2 yr -1 or 4-39 %, in NCS mitigation potential, of which cropland expansion for fulfilling future food demand is the primary cause. This impact is particularly severe in the tropics where NCS hold the most abundant mitigation potential. Our findings highlight immediate actions prioritized to tropical areas are important to best realize NCS and are key to developing realistic and sustainable climate policies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Delivering the Sustainable Development Goals (SDGs) requires balancing demands on land between agriculture (SDG 2) and biodiversity (SDG 15). The production of vegetable oils and, in particular, palm oil, illustrates these competing demands and trade-offs. Palm oil accounts for ~40% of the current global annual demand for vegetable oil as food, animal feed and fuel (210 Mt), but planted oil palm covers less than 5-5.5% of the total global oil crop area (approximately 425 Mha) due to oil palm's relatively high yields. Recent oil palm expansion in forested regions of Borneo, Sumatra and the Malay Peninsula, where >90% of global palm oil is produced, has led to substantial concern around oil palm's role in deforestation. Oil palm expansion's direct contribution to regional tropical deforestation varies widely, ranging from an estimated 3% in West Africa to 50% in Malaysian Borneo. Oil palm is also implicated in peatland draining and burning in Southeast Asia. Documented negative environmental impacts from such expansion include biodiversity declines, greenhouse gas emissions and air pollution. However, oil palm generally produces more oil per area than other oil crops, is often economically viable in sites unsuitable for most other crops and generates considerable wealth for at least some actors. Global demand for vegetable oils is projected to increase by 46% by 2050. Meeting this demand through additional expansion of oil palm versus other vegetable oil crops will lead to substantial differential effects on biodiversity, food security, climate change, land degradation and livelihoods. Our Review highlights that although substantial gaps remain in our understanding of the relationship between the environmental, socio-cultural and economic impacts of oil palm, and the scope, stringency and effectiveness of initiatives to address these, there has been little research into the impacts and trade-offs of other vegetable oil crops. Greater research attention needs to be given to investigating the impacts of palm oil production compared to alternatives for the trade-offs to be assessed at a global scale.

Expansion of oil palm plantations has led to extensive wildlife habitat conversion in Southeast Asia [1]. This expansion is driven by a global demand for palm oil for products ranging from foods to detergents [2], and more recently for biofuels [3]. The negative impacts of oil palm development on biodiversity [1, 4, 5], and on orangutans (Pongo spp.) in particular, have been well documented [6, 7] and publicized [8, 9]. Although the oil palm is of African origin, Africa's production historically lags behind that of Southeast Asia. Recently, significant investments have been made that will likely drive the expansion of Africa's oil palm industry [10]. There is concern that this will lead to biodiversity losses similar to those in Southeast Asia. Here, we analyze the potential impact of oil palm development on Africa's great apes. Current great ape distribution in Africa substantially overlaps with current oil palm concessions (by 58.7%) and areas suitable for oil palm production (by 42.3%). More importantly, 39.9% of the distribution of great ape species on unprotected lands overlaps with suitable oil palm areas. There is an urgent need to develop guidelines for the expansion of oil palm in Africa to minimize the negative effects on apes and other wildlife. There is also a need for research to support land use decisions to reconcile economic development, great ape conservation, and avoiding carbon emissions., (Copyright © 2014 Elsevier Ltd. All rights reserved.)

In 2004, Navjot Sodhi and colleagues warned that logging and agricultural conversion of Southeast Asia's forests were leading to a biodiversity disaster. We evaluate this prediction against subsequent research and conclude that most of the fauna of the region can persist in logged forests. Conversely, conversion of primary or logged forests to plantation crops, such as oil palm, causes tremendous biodiversity loss. This loss is exacerbated by increased fire frequency. Therefore, we conclude that preventing agricultural conversion of logged forests is essential to conserving the biodiversity of this region. Our analysis also suggests that, because Southeast Asian forests are tightly tied to global commodity markets, conservation payments commensurate with combined returns from logging and subsequent agricultural production may be required to secure long-term forest protection., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

The supposition that agricultural intensification results in land sparing for conservation has become central to policy formulations across the tropics. However, underlying assumptions remain uncertain and have been little explored in the context of conservation incentive schemes such as policies for Reducing Emissions from Deforestation and forest Degradation, conservation, sustainable management, and enhancement of carbon stocks (REDD+). Incipient REDD+ forest carbon policies in a number of countries propose agricultural intensification measures to replace extensive "slash-and-burn" farming systems. These may result in conservation in some contexts, but will also increase future agricultural land rents as productivity increases, creating new incentives for agricultural expansion and deforestation. While robust governance can help to ensure land sparing, we propose that conservation incentives will also have to increase over time, tracking future agricultural land rents, which might lead to runaway conservation costs. We present a conceptual framework that depicts these relationships, supported by an illustrative model of the intensification of key crops in the Democratic Republic of Congo, a leading REDD+ country. A von Thünen land rent model is combined with geographic information systems mapping to demonstrate how agricultural intensification could influence future conservation costs. Once postintensification agricultural land rents are considered, the cost of reducing forest sector emissions could significantly exceed current and projected carbon credit prices. Our analysis highlights the importance of considering escalating conservation costs from agricultural intensification when designing conservation initiatives.

Oil palm is one of the most extensively cultivated biodiesel feedstocks worldwide, and expansion of its cultivation poses a significant threat to ecosystems, biodiversity and potentially the global climate. We evaluate the prospects of land sparing and wildlife-friendly farming, two contrasting approaches for reducing the impacts of oil palm agriculture. We draw on concepts from both approaches to suggest more sustainable production systems and argue that landscapes under threat from oil palm expansion need to be designed in recognition of biodiversity, economic and livelihood needs. Specifically, we advocate agroforestry zones between high conservation value areas and intensive oil palm plantations to create a more heterogeneous landscape benefiting both biodiversity and rural communities. Similar principles could apply to biofuel systems elsewhere.

Conservation of the Sumatran orangutans’ (Pongo abelii) habitat is threatened by change in land use/land cover (LULCC), due to the logging of its native primary forest habitat, and the primary forest conversion to oil palm, rubber tree, and coffee plantations. Frequent LULCC monitoring is vital to rapid conservation interventions. Due to the costs of high-resolution satellite imagery, researchers are forced to rely on cost-free sources (e.g. Landsat), those, however, provide images at a moderate-to-low resolution (e.g. 15–250 m), permitting identification only general LULC classes, and limit the detection of small-scale deforestation or degradation. Here, we combine Landsat imagery with very high-resolution imagery obtained from an unmanned aircraft system (UAS). ​The UAS imagery was used as ‘drone truthing’ data to train image classification algorithms. Our results show that UAS data can successfully be used to help discriminate similar land-cover/use classes (oil palm plantationvs. reforestationvs. logged forest) with consistently high identification of over 75% on the generated thematic map, where the oil palm detection rate was as high as 89%. Because UAS is employed increasingly in conservation proWjects, this approach can be used in a large variety of them to improve land-cover classification or aid-specific mapping needs. [ABSTRACT FROM PUBLISHER]

1. Species–area (SA) models have often been used to predict biodiversity loss resulting from habitat loss. This application of SA models hinges on two fundamental assumptions: the resultant landscape matrix is inhospitable to the taxa of interest; and edge effects do not factor into extinction risks. Despite growing consensus that these assumptions are unrealistic, the SA approach continues to be used in assessments of biodiversity decline and conservation planning. 2. We propose an overhaul of the SA approach by accounting for taxon-specific responses to landscape-specific matrix quality and deleterious effects of habitat edges. We pitted nine variants of an improved SA model (calibrated for edge and/or matrix) against two variants of the conventional model (calibrated with island or continental z values) to predict species extinction and endangerment in 15 tropical biodiversity hotspots. 3. The matrix-calibrated SA model received the highest Akaike’s Information Criterion weight (birds: 66·8%; mammals: 63·3%), which reflects the weight of evidence in support of it being the most parsimonious model given the set of candidate models and data considered. Additionally, the matrix-calibrated (MC) model produced species extinction predictions that were the most accurate and least biased. 4. The second best model (for both birds and mammals) was one that simultaneously corrected for matrix and edge effects. 5. The conventional SA model (particularly when calibrated with an island z value) performed worse than the matrix-calibrated and/or edge-corrected models. 6. Synthesis and applications. Our results suggest that accounting for the landscape matrix per se is a sufficient and significant improvement to the SA approach in terms of assessing species extinction risks from land-use change. More importantly, given that the MC model was also the most parsimonious model (in that it requires only one additional model parameter than the conventional SA model), it could prove to be a cost-effective heuristic tool for conservation scientists and decision makers to accurately evaluate extinction risks resulting from land-use decisions. We argue that, henceforth, the MC model, which takes account of both the extent of deforestation and quality of the resultant matrix, should replace the conventional SA model for predicting biodiversity loss. [ABSTRACT FROM AUTHOR]

Abstract: Southeast Asia experiences one of the highest rates of deforestation in the tropics due to agricultural expansion, logging, habitat fragmentation and urbanization, which are expected to result in species declines and extinctions. In particular, growing global demands for food, biofuel and other commodities are driving the rapid expansion of oil palm and paper-and-pulp industries at the expense of lowland dipterocarp forests, further jeopardizing Southeast Asian forest biotas. We synthesize recent findings on the effects of land-use changes on plants, invertebrates, vertebrates and ecosystem functioning/services in Southeast Asia. We find that species richness and abundance/density of forest-dependent taxa generally declined in disturbed compared to mature forests. Species with restricted ranges and those with habitat and foraging specialization were particularly vulnerable. Forest loss also disrupted vital ecosystem services (e.g. crop pollination). Long-term studies are needed to understand biotic sustainability in regenerating and degraded forests, particularly in the context of the synergistic or additive effects of multiple agents of biodiversity loss (e.g. invasive species and climate change). The preservation of large tracts of mature forests should remain the principal conservation strategy in the tropics. In addition, reforestation and reintroductions of native species, as well as improved connectivity among forest patches could enhance the conservation value of forest remnants in human-dominated landscapes. [ABSTRACT FROM AUTHOR]

Application of island biogeography theory to prediction of species extinctions resulting from habitat loss is based on the assumption that the transformed landscape matrix is completely inhospitable to the taxa considered, despite evidence demonstrating the nontrivial influence of matrix on populations within habitat remnants. The island biogeography paradigm therefore needs refining to account for specific responses of taxa to the area of habitat “islands” and to the quality of the surrounding matrix. We incorporated matrix effects into island theory by partitioning the slope ( value) of species–area relationships into two components: γ, a constant, and σ, a measure of taxon-specific responses to each component of a heterogeneous matrix. We used our matrix-calibrated model to predict extinction and endangerment of bird species resulting from land-use change in 20 biodiversity hotspots and compared these predictions with observed numbers of extinct and threatened bird species. We repeated this analysis with the conventional species–area model and the countryside species–area model, considering alternative z values of 0.35 (island) or 0.22 (continental). We evaluated the relative strength of support for each of the five candidate models with Akaike's information criterion (AIC). The matrix-calibrated model had the highest AIC weight (wi = 89.21%), which means the weight of evidence in support of this model was the optimal model given the set of candidate models and the data. In addition to being a valuable heuristic tool for assessing extinction risk, our matrix-calibrated model also allows quantitative assessment of biodiversity benefits (and trade-offs) of land-management options in human-dominated landscapes. Given that processes of secondary regeneration have become more widespread across tropical regions and are predicted to increase, our matrix-calibrated model will be increasingly appropriate for practical conservation in tropical landscapes. [ABSTRACT FROM AUTHOR]