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Land use is both a major cause of the biodiversity crises and a potential solution to it. Decisions about land use are made in complex social–ecological systems, yet conservation research, policy, and practice often neglect the diverse and dynamic nature of land use. A deeper integration of land system science and conservation science provides major opportunities in this context, through a transfer of concepts, data, and methodologies. Specifically, a closer exchange between land‐use data developers and users will enable common terminology and better data use, allowing to move beyond coarse land‐cover representations of land use. Similarly, archetyping and regionalization approaches can help to embrace, rather than oversimplify, the diversity of land‐use actors and practices. Finally, systematically linking land‐use actors to portfolios of pressures on biodiversity, beyond their direct impact on habitat, can better represent and map co‐occurring and interacting threats. Together, this will enable conservation policymakers and planners to recognize the often‐complex and wicked nature of conservation challenges related to land, allowing for more context‐specific conservation policymaking and planning, and more targeted conservation interventions.

Humans have encroached upon a majority of Earth's lands. The current extinction crisis is a testament to human impacts on wilderness. If there is any hope of retaining a biodiverse planetary system, we must begin to learn how to coexist with, and leave space for, other species. The practice of “rewilding” has emerged as a method for returning wild lands, and wildness, to landscapes we have altered. Perino et al. review this concept and present a framework for implementing it broadly and in a way that considers ongoing human interaction. Science , this issue p. eaav5570 The practice of rewilding has been both promoted and criticized in recent years. Benefits include flexibility to react to environmental change and the promotion of opportunities for society to reconnect with nature. Criticisms include the lack of a clear conceptualization of rewilding, insufficient knowledge about possible outcomes, and the perception that rewilding excludes people from landscapes. Here, we present a framework for rewilding that addresses these concerns. We suggest that rewilding efforts should target trophic complexity, natural disturbances, and dispersal as interacting processes that can improve ecosystem resilience and maintain biodiversity. We propose a structured approach to rewilding projects that includes assessment of the contributions of nature to people and the social-ecological constraints on restoration.

Aligning food production with biodiversity conservation is one of the greatest challenges of our time. One framing of this challenge is the land-sharing vs. land-sparing debate. Much empirical research has focused on identifying the relationship between agricultural yields and species populations, and using the relative number of species with particular relationships to inform landscape-level management. We feel this is misguided, as such an approach does not guarantee the existence of every species of conservation concern. Here, we show that constrained optimization methods can be used to identify landscape-level solutions which maximize agricultural yields and populations for any number of species. Our results suggest that the relative number of species with particular yield-density curves is not a good indicator as to how landscapes should be managed. Likewise, choosing between blanket sharing or sparing strategies leads to suboptimal outcomes at the landscape scale in many cases. Our framework makes maximum use of the rich information contained in yield-density curves to move beyond black-and-white choices and toward more nuanced, context-specific solutions to aligning biodiversity conservation and agricultural production. Such optimal landscapes will likely have features of both sharing and sparing strategies.

Global agricultural production will likely need to increase in the future due to population growth, changing diets, and the rising importance of bioenergy. Intensifying already existing cropland is often considered more sustainable than converting more natural areas. Unfortunately, our understanding of cropping patterns and intensity is weak, especially at broad geographic scales. We characterized and mapped cropping systems in Europe, a region containing diverse cropping systems, using four indicators: (a) cropping frequency (number of cropped years), (b) multi-cropping (number of harvests per year), (c) fallow cycles, and (d) crop duration ratio (actual time under crops) based on the MODIS Normalized Difference Vegetation Index (NDVI) time series from 2000 to 2012. Second, we used these cropping indicators and self-organizing maps to identify typical cropping systems. The resulting six clusters correspond well with other indicators of agricultural intensity (e.g., nitrogen input, yields) and reveal substantial differences in cropping intensity across Europe. Cropping intensity was highest in Germany, Poland, and the eastern European Black Earth regions, characterized by high cropping frequency, multi-cropping and a high crop duration ratio. Contrarily, we found lowest cropping intensity in eastern Europe outside the Black Earth region, characterized by longer fallow cycles. Our approach highlights how satellite image time series can help to characterize spatial patterns in cropping intensity-information that is rarely surveyed on the ground and commonly not included in agricultural statistics: our clustering approach also shows a way forward to reduce complexity when measuring multiple indicators. The four cropping indicators we used could become part of continental-scale agricultural monitoring in order to identify target regions for sustainable intensification, where trade-offs between intensification and the environmental should be explored.

Tropical forests are vital for global biodiversity, carbon storage and local livelihoods, yet they are increasingly under threat from human activities. Large-scale land acquisitions have emerged as an important mechanism linking global resource demands to forests in the Global South, yet their influence on tropical deforestation remains unclear. Here we perform a multicountry assessment of the links between large-scale land acquisitions and tropical forest loss by combining a new georeferenced database of 82,403 individual land deals—covering 15 countries in Latin America, sub-Saharan Africa and Southeast Asia—with data on annual forest cover and loss between 2000 and 2018. We find that land acquisitions cover between 6% and 59% of study-country land area and between 2% and 79% of their forests. Compared with non-investment areas, large-scale land acquisitions were granted in areas of higher forest cover in 11 countries and had higher forest loss in 52% of cases. Oil palm, wood fibre and tree plantations were consistently linked with enhanced forest loss while logging and mining concessions showed a mix of outcomes. Our findings demonstrate that large-scale land acquisitions can lead to elevated deforestation of tropical forests, highlighting the role of local policies in the sustainable management of these ecosystems.Tropical deforestation rates are linked to large-scale land investments, according to georeferenced land deal records and remote sensing of forest loss over the past two decades.

Agriculture is the leading driver of biodiversity loss. However, its future impact on biodiversity remains unclear, especially because agricultural intensification is often neglected, and high path-dependency is assumed when forecasting agricultural development—although the past suggests that shock events leading to considerable agricultural change occur frequently. Here, we investigate the possible impacts on biodiversity of pathways of expansion and intensification. Our pathways are not built to reach equivalent production targets, and therefore they should not be directly compared; they instead highlight areas at risk of high biodiversity loss across the entire option space of possible agricultural change. Based on an extensive database of biodiversity responses to agriculture, we find 30% of species richness and 31% of species abundances potentially lost because of agricultural expansion across the Amazon and Afrotropics. Only 21% of high-risk expansion areas in the Afrotropics overlap with protected areas (compared with 43% of the Neotropics). Areas at risk of biodiversity loss from intensification are found in India, Eastern Europe and the Afromontane region (7% species richness, 13% abundance loss). Many high-risk regions are not adequately covered by conservation prioritization schemes, and have low national conservation spending and high agricultural growth. Considering rising agricultural demand, we highlight areas where timely land-use planning may proactively mitigate biodiversity loss. SUMMARY The authors predict biodiversity loss under potential future agricultural change. Agricultural expansion threatens species richness and abundance worldwide (up to one-third in some areas), often with little overlap between protected areas and high-risk expansion areas.

Widespread changes of agricultural land use occurred in Eastern Europe since the collapse of socialism and the European Union’s eastward expansion, but the rates and patterns of recent land changes remain unclear. Here we assess agricultural land change for the entire Carpathian ecoregion in Eastern Europe at 30 m spatial resolution with Landsat data and for two change periods, between 1985–2000 and 2000–2010. The early period is characterized by post-socialist transition processes, the late period by an increasing influence of EU politics in the region. For mapping and change detection, we use a machine learning approach (random forests) on image composites and variance metrics which were derived from the full decadal archive of Landsat imagery. Our results suggest that cropland abandonment was the most prevalent change process, but we also detected considerable areas of grassland conversion and forest expansion on non-forest land. Cropland abandonment was most extensive during the transition period and predominantly occurred in marginal areas with low suitability for agriculture. Conversely, we observed substantial recultivation of formerly abandoned cropland in high-value agricultural areas since 2000. Hence, market forces increasingly adjust socialist legacies of land expansive production and agricultural land use clusters in favorable areas while marginal lands revert to forest.

Fire is an important disturbance in grassland ecosystems. Anthropogenic factors, especially land use, have drastically altered fire regimes in many regions, but how changing land-use intensity affects fire patterns remains weakly understood. Here, we reconstruct changes in fire regimes between 1989 and 2016 for the understudied Eurasian steppes, where major land-use changes happened after the dissolution of the Soviet Union in 1991. We mapped burned areas in a 540,000 km² study region in northern Kazakhstan for 3-year periods centered on 1990, 2000, and 2015, based on all available Landsat imagery. We then used these maps to assess changes in the extent, number, and size of fires over time, and to explore links between changes in fire regimes and agriculture. We found a sevenfold increase in total burned area and an eightfold increase in fire numbers between 1990 and 2000. After 2000, burned area and fire numbers declined slightly, while fire size remained stable. Most of the observed increase in fires in the 1990s occurred on cropland, most likely due to the agricultural burning. The abandonment of cropland and pastures was also associated with intensified fire regimes, likely due to increased aboveground biomass and thus higher fuel loads. Overall, our results suggest that intensifying fire regimes on the Eurasian steppe are clearly linked to post-Soviet changes in agriculture. Given that fires on Eurasia’s steppes have wide-ranging consequences, affecting regions as far away as the Arctic, better regulation of agricultural practices, better fire monitoring, and more proactive fire management are needed.

Aim: Primary forests have high conservation value but are rare in Europe due to historic land use. Yet many primary forest patches remain unmapped, and it is unclear to what extent they are effectively protected. Our aim was to (1) compile the most comprehensive European-scale map of currently known primary forests, (2) analyse the spatial determinants characterizing their location and (3) locate areas where so far unmapped primary forests likely occur. Location: Europe. Methods: We aggregated data from a literature review, online questionnaires and 32 datasets of primary forests. We used boosted regression trees to explore which biophysical, socio-economic and forest-related variables explain the current distribution of primary forests. Finally, we predicted and mapped the relative likelihood of primary forest occurrence at a 1-km resolution across Europe. Results: Data on primary forests were frequently incomplete or inconsistent among countries. Known primary forests covered 1.4 Mha in 32 countries (0.7% of Europe's forest area). Most of these forests were protected (89%), but only 46% of them strictly. Primary forests mostly occurred in mountain and boreal areas and were unevenly distributed across countries, biogeographical regions and forest types. Unmapped primary forests likely occur in the least accessible and populated areas, where forests cover a greater share of land, but wood demand historically has been low. Main conclusions: Despite their outstanding conservation value, primary forests are rare and their current distribution is the result of centuries of land use and forest management. The conservation outlook for primary forests is uncertain as many are not strictly protected and most are small and fragmented, making them prone to extinction debt and human disturbance. Predicting where unmapped primary forests likely occur could guide conservation efforts, especially in Eastern Europe where large areas of primary forest still exist but are being lost at an alarming pace.

The wealth of complementary data available from remote sensing missions can hugely aid efforts towards accurately determining land use and quantifying subtle changes in land use management or intensity. This study reviewed 112 studies on fusing optical and radar data, which offer unique spectral and structural information, for land cover and use assessments. Contrary to our expectations, only 50 studies specifically addressed land use, and five assessed land use changes, while the majority addressed land cover. The advantages of fusion for land use analysis were assessed in 32 studies, and a large majority (28 studies) concluded that fusion improved results compared to using single data sources. Study sites were small, frequently 300–3000 km 2 or individual plots, with a lack of comparison of results and accuracies across sites. Although a variety of fusion techniques were used, pre-classification fusion followed by pixel-level inputs in traditional classification algorithms (e.g., Gaussian maximum likelihood classification) was common, but often without a concrete rationale on the applicability of the method to the land use theme being studied. Progress in this field of research requires the development of robust techniques of fusion to map the intricacies of land uses and changes therein and systematic procedures to assess the benefits of fusion over larger spatial scales.