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Understanding the spatio‐temporal distribution of ungulates is important for effective wildlife management, particularly for economically and ecologically important species such as wild boar (Sus scrofa). Wild boars are generally considered to exhibit substantial behavioral flexibility, but it is unclear how their behavior varies across different conservation management regimes and levels of human pressure. To analyze if and how wild boars adjust their space use or their temporal niche, we surveyed wild boars across the core and buffer zones (collectively referred to as the conservation zone) and the transition zone of a biosphere reserve. These zones represent low and high levels of human pressure, respectively. Specifically, we employed a network of 53 camera traps distributed in the Schaalsee UNESCO Biosphere Reserve over a 14‐month period (19,062 trap nights) and estimated circadian activity patterns, diel activity levels, and occupancy of wild boars in both zones. To account for differences in environmental conditions and day length, we estimated these parameters separately for seven 2‐month periods. Our results showed that the wild boars were primarily nocturnal, with diurnal activity occurring dominantly during the summer months. The diel activity patterns in the two zones were very similar overall, although the wild boars were slightly less active in the transition zone than in the conservation zone. Diel activity levels also varied seasonally, ranging from 7.5 to 11.0 h day−1, and scaled positively with the length of the night (R 2 = 0.66–0.67). Seasonal occupancy estimates were exceptionally high (point estimates ranged from 0.65 to 0.99) and similar across zones, suggesting that the wild boars used most of the biosphere reserve. Overall, this result suggests that different conservation management regimes (in this case, the zoning of a biosphere reserve) have little impact on wild boar behavior. This finding is relevant for wildlife management in protected areas where possibly high wild boar densities could interfere with conservation goals within these areas and those of agricultural land use in their vicinity., In this study, we analyzed whether wild boars adjust their space use or their temporal niche according to spatial differences in management within a biosphere reserve. We employed a network of 53 camera traps distributed in the Schaalsee UNESCO Biosphere Reserve over a 14‐month period (19,062 trap nights) and estimated the circadian activity patterns, activity levels, and occupancy of wild boars in the conservation and transition zones; these zones represent low and high levels of human pressure, respectively. Wild boars were primarily nocturnal, diel activity levels were positively correlated with the length of the night and did not differ markedly between zones; occupancy estimates were high and were similar in both zones . Overall, these results suggests that different conservation management regimes (in this case, the zoning of a biosphere reserve) have little impact on wild boar behavior.

Agricultural expansion into subtropical and tropical forests causes major environmental damage, but its wider social impacts often remain hidden. Forest-dependent smallholders are particularly strongly impacted, as they crucially rely on forest resources, are typically poor, and often lack institutional support. Our goal was to assess forest-smallholder dynamics in relation to expanding commodity agriculture. Using high-resolution satellite images across the entire South American Gran Chaco, a global deforestation hotspot, we digitize individual forest-smallholder homesteads (n = 23,954) and track their dynamics between 1985 and 2015. Using a Bayesian model, we estimate 28,125 homesteads in 1985 and show that forest smallholders occupy much larger forest areas (>45% of all Chaco forests) than commonly appreciated and increasingly come into conflict with expanding commodity agriculture (18% of homesteads disappeared; n = 5,053). Importantly, we demonstrate an increasing ecological marginalization of forest smallholders, including a substantial forest resource base loss in all Chaco countries and an increasing confinement to drier regions (Argentina and Bolivia) and less accessible regions (Bolivia). Our transferable and scalable methodology puts forest smallholders on the map and can help to uncover the land-use conflicts at play in many deforestation frontiers across the globe. Such knowledge is essential to inform policies aimed at sustainable land use and supply chains.

Summary Maintaining or restoring connectivity among wildlife populations is a primary strategy to overcome the negative impacts of habitat fragmentation. Yet, current connectivity planning efforts typically assess landscape resistance, the ability of organisms to cross various biophysical elements in a landscape, while overlooking the various ways in which human behaviors influence connectivity. Here, we introduce the concept of “anthropogenic resistance” to capture the impacts of human behaviors on species' movement through a landscape. We discuss psychological and socioeconomic factors that influence the degree of anthropogenic resistance, such as the economic value or the risks posed by a species, and suggest methods to estimate and include anthropogenic resistance in connectivity analyses. Finally, we highlight how addressing anthropogenic resistance through a social-ecological perspective can lead to better outcomes for both humans and wildlife. We call for multidisciplinary approaches in connectivity planning to ensure the functionality of landscapes and sustainability of populations in the long term.

Better balancing agricultural production and biodiversity conservation is a central goal for many landscapes. Yet, empirical work on how to best achieve such a balance has focused mainly on the local scale, thereby disregarding that landscape context might mediate biodiversity-agriculture trade-offs. Focusing on vertebrates in the Argentine Chaco, we evaluate how trade-offs between agriculture and biodiversity vary with landscape context, from landscapes where agricultural and natural areas are separated to landscapes where both are interspersed. We modelled the distributions of 226 vertebrates and use the resulting maps to describe the species richness of ecosystem-service providing guilds. We calculated three agricultural intensity metrics, and evaluated how both species richness and agricultural intensity vary along a gradient of landscape configuration, while controlling for landscape composition. Species richness and agricultural yields both varied with landscape configuration. Biodiversity was highest in mixed landscapes where agricultural and natural area are interspersed, whereas agricultural yields showed a more heterogeneous response, with some yield metrics highest in mixed and others in separated landscapes. As a result, agriculture/biodiversity trade-offs depended strongly on landscape configuration, irrespective of landscape composition. We also identified large areas with low vertebrate richness and agricultural yields, suggesting considerable potential for improving in at least one dimension. Agriculture/biodiversity trade-offs varied with landscape configuration, suggesting that landscape design can balance these trade-offs. Our simple and broadly applicable approach can provide baseline information for landscape planning aimed at realizing co-benefits between agriculture and biodiversity—in the Gran Chaco and elsewhere.

ContextMany large carnivores depend on habitat patches outside protected areas, as well as safe corridors between them. However, corridor assessments typically ignore potential conflicts between carnivores and people, which can undermine corridor effectiveness and thus conservation success.ObjectivesWe identified safe dispersal corridors and conflict-prone movement bottlenecks for Persian leopard (Panthera pardus saxicolor) between protected areas in the Alborz Mountains, Iran, by mapping habitat, landscape permeability, and conflict risk. We then identified priority areas for conservation interventions according to the intensities of different threats.MethodsWe mapped land cover using Landsat satellite images, gathered data on leopard and prey distributions and livestock depredation events via interview surveys in 69 cells of 6 × 6 km each. We then used occupancy modeling to identify habitat patches, used circuit theory modeling to analyze landscape permeability, and assessed human-leopard conflict risk using generalized linear models.ResultsLeopard habitat use increased with prey availability and decreased with elevation. Prey distribution, in turn, was mostly negatively influenced by agricultural lands and distance from protected areas. Conflict risk (i.e., probability of leopard depredation on livestock) was high in landscapes where agriculture was widespread and historical forest loss high. Not accounting for conflicts overestimated connectivity among habitat patches substantially.ConclusionsHuman-carnivore conflicts are an important constraint to connectivity and should be considered in corridor assessments. Our study shows how habitat analysis, connectivity assessment, and conflict risk mapping can be combined to guide conservation planning for identifying habitat networks and safe corridors for carnivores in human-dominated landscapes.

Archetype analysis is a key tool in landscape and sustainability research to organize social-ecological complexity and to identify social-ecological systems (SESs). While inductive archetype analysis can characterize the diversity of SESs within a region, deductively derived archetypes have greater interpretative power to compare across regions. Here, we developed a novel archetype approach that combines the strengths of both perspectives. We applied inductive clustering to an integrative dataset to map 15 typical SESs for 2016 and 12 social-ecological changes (1999–2016) in Andalusia region (Spain). We linked these types to deductive types of human-nature connectedness, resulting in a nested archetype classification. Our analyses revealed combinations of typical SESs and social-ecological changes that shape them, such as agricultural intensification and peri-urbanization in agricultural SESs, declining agriculture in natural SESs or population de-concentration (counter-urbanization) in urban SESs. Likewise, we identified a gradient of human-nature connectedness across SESs and typical social-ecological changes fostering this gradient. This allowed us to map areas that face specific sustainability challenges linked to ongoing regime shifts (e.g., from rural to urbanized systems) and trajectories towards social-ecological traps (e.g., cropland intensification in drylands) associated with decreasing human-nature connectedness. This provides spatial templates for targeting policy responses related to the sustainable intensification of agricultural systems, the disappearance of traditional cropping systems and abandonment of rural lands, or the reconnection of urban population with the local environment, among others. Generally, our approach allows for different levels of abstraction, keeping regional context-specificity while linking to globally recognisable archetypes, and thus to generalization and theory-building efforts.

Sustainable intensification of agricultural production is expected to be an important pathway for achieving future food security while protecting the environment. Recognizing that there is no single answer to how different dimensions of intensification can be achieved sustainably, we identify opportunities for research across spatial scales. We focus specifically on research questions around advances in technology and management and suggest that progress on these questions can be made by (i) improving understanding of trade-offs, especially across scales, (ii) recognition of the context-specificity of how agricultural intensification can become more sustainable, and (iii) development, access and wider use of global datasets for integrative research.

Agricultural expansion and intensification drive the conversion of natural areas worldwide. Scenarios are powerful tools to explore possible future changes in agricultural land use, how these may affect the environment, and how policies may influence land-use patterns. Focusing on Argentina's prime agricultural areas, the Pampas, Espinal and Chaco, we developed spatially-explicit future land-use scenarios from 2010 to 2030, considering both agricultural expansion (i.e., conversions from woodland to either grazing land or cropland) and agricultural intensification (i.e., conversions from grazing land to cropland). Our simulations were based on an econometric model of net returns, which assumes economically rational land-use actors. Using this model, we assessed the rates and spatial patterns of future land-use change under current land zoning in our study region, and contrasted this with a forecast of future land use based on land-conversion rates from 2000–2010. We systematically tested the impact of economic policies (e.g., taxes or subsidies), infrastructure improvement (e.g., road paving), and technological innovation (i.e., yield increases) on the spatial patterns of land-use conversions. Our model suggests future land-use change will mainly happen along intensification pathways, with deforestation slowing down, if land-use actors would be profit-maximizing. This general pattern did not change even for policy interventions that impacted profits from agriculture in major ways, cautioning against overestimating the leverage that economic policies provide for halting deforestation. Improving the region's road network would create a strong incentive to expand cropland further into remaining woodlands and over grazing lands. However, low agricultural profits and higher yields could curb deforestation in marginal areas to some extent. We also highlight that priority areas for conservation are particularly likely to experience high land-use pressure in the future. Given the lower-than-expected power of economic policies to alter deforestation patterns in our models, zoning, if properly enforced, appears to be a more straightforward tool for avoiding unwanted environmental impacts in the Chaco. Fil: Piquer Rodríguez, María. Universidad Nacional de Tucumán. Instituto de Ecología Regional. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Ecología Regional; Argentina. Universität zu Berlin; Alemania Fil: Baumann, Matthias. Universität zu Berlin; Alemania Fil: Butsic, Van. University of California at Berkeley; Estados Unidos Fil: Gasparri, Nestor Ignacio. Universidad Nacional de Tucumán. Instituto de Ecología Regional. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Ecología Regional; Argentina Fil: Gavier Pizarro, Gregorio. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación de Recursos Naturales. Instituto de Recursos Biológicos; Argentina Fil: Volante, José Norberto. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Salta. Estación Experimental Agropecuaria Salta; Argentina Fil: Müller, Daniel. Universität zu Berlin; Alemania. Leibniz Institute of Agricultural Development in Transition Economies; Alemania Fil: Kuemmerle, Tobias. Universität zu Berlin; Alemania

Strong trade-offs between agriculture and the environment occur in deforestation frontiers, particularly in the world's rapidly disappearing tropical and subtropical dry forests. Pathways to mitigate these trade-offs are often unclear, as well as how deforestation or different policies alter the option space of available pathways. Using a spatial optimization framework based on linear programming, we develop a landscape-scale possibility frontier describing trade-offs between agricultural profit, biodiversity, and carbon stock for the Argentinean Dry Chaco, a global deforestation hotspot. We use this framework to assess how current land-use zoning, as well as past and future land-use-trajectories, alter the option space to minimize trade-offs between biodiversity, carbon, and agriculture. Our analyses yield four major insights. First, we found substantial co-benefits between biodiversity and carbon, yet strong trade-offs of both with agriculture. Second, development according to the current zoning could lead to highly suboptimal socio-ecological outcomes; our analysis pinpoints how this zoning could be improved. Third, high landscape-scale multifunctionality can be achieved using different land-use strategies, but maintaining >40% of forest is essential in all of them, and silvopasture systems appear to be central for achieving high overall multifunctionality. Finally, our results suggest the window of opportunity is closing rapidly: recent land-use changes since 2000 have rapidly moved the Chaco within the option space, with forest extent declining towards critical thresholds for maintaining balanced, multifunctional landscapes. Our results emphasize that the time for sustainability planning in the Chaco is now. More broadly, we show how multi-criteria optimization can describe dynamic trade-offs between agriculture and the environment at landscape and regional scales. This can help to identify land-system tipping points that, once crossed, would inhibit more sustainable futures, and policies to avoid such potential traps. Instituto de Recursos Biológicos Fil: Law, Elizabeth A. Humboldt-Universität zu Berlin. Geography Department; Alemania Fil: Law, Elizabeth A. Norwegian Institute for Nature Research; Noruega Fil: Macchi, Leandro. Humboldt-Universität zu Berlin. Geography Department; Alemania Fil: Macchi, Leandro. Universidad Nacional de Tucumán. Facultad de Ciencias Naturales e Instituto Miguel Lillo. Instituto de Ecología Regional; Argentina Fil: Macchi, Leandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tucumán. Instituto de Ecología Regional; Argentina Fil: Baumann, Mathias. Humboldt-University. Geography Department; Alemania. Fil: Decarre, Julieta. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Recursos Biológicos; Argentina Fil: Gavier Pizarro, Gregorio Ignacio. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Recursos Biológicos; Argentina Fil: Levers, Christian. Humboldt-University. Geography Department; Alemania. Fil: Levers, Christian. Vrije Universiteit Amsterdam. Department of Environmental Geography. Institute for Environmental Studies (IVM); Países Bajos Fil: Mastrangelo, Matias Enrique. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias. Grupo de Estudio de Agroecosistemas y Paisajes Rurales; Argentina. Fil: Mastrangelo, Matias Enrique. Consejo Nacional de Investigaciones Científicas y Técnicas. Grupo de Estudio de Agroecosistemas y Paisajes Rurales; Argentina. Fil: Murray, Francisco. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria San Luis. Agencia de Extensión Rural San Luis; Argentina Fil: Murray, Francisco. Universidad Nacional de San Luis. Grupo de Estudios Ambientales; Argentina Fil: Murray, Francisco. Consejo Nacional de Investigaciones Científicas y Técnicas. Grupo de Estudios Ambientales; Argentina Fil: Müller, Daniel. Humboldt-University Berlin. Geography Department; Alemania. Fil: Müller, Daniel. Leibniz Institute of Agricultural Development in Transition Economies; Alemania Fil: Müller, Daniel. Humboldt-University Berlin. Integrative Research Institute for Transformations in Human Environment Systems; Alemania Fil: Piquer Rodriguez, María. Humboldt-Universität zu Berlin. Geography Department; Alemania Fil: Piquer Rodriguez, María. Freie Universität Berlin. Lateinamerika-Institut; Alemania Fil: Torres, Ricardo. Universidad Nacional de Córdoba. Instituto de Diversidad y Ecología Animal ; Argentina. Fil: Torres, Ricardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Diversidad y Ecología Animal ; Argentina. Fil: Wilson, Kerrie A. Queensland University of Technology; Australia Fil: Kuemmerle, Tobias. Humboldt-University Berlin. Geography Department; Alemania. Fil: Kuemmerle, Tobias. Humboldt-University Berlin. Integrative Research Institute for Transformations in Human Environment Systems; Alemania

As wild areas disappear and agricultural lands expand, understanding how people and wildlife can coexist becomes increasingly important. Human–wildlife conflicts (HWCs) are obstacles to coexistence and negatively affect both wildlife populations and the livelihood of people. To facilitate coexistence, a number of frameworks have been developed to both understand the drivers of conflict and then to find solutions that mitigate conflict. However, each framework has different foci and strengths in particular stages of analysis. Here, we propose an integrated framework that leverages the individual strengths of previously fairly isolated methodologies, allowing for holistic HWC analysis. The framework for participatory impact assessment (FoPIA) provides a toolset for developing wildlife scenarios, selecting assessment indicators and assessing the impact of different scenarios. The social-ecological framework of ecosystem services and disservices (SEEDS) analyzes the ecosystem services trade-offs related to scenarios, and the 3i stakeholder analysis approach, supports the identification of stakeholders and provides a mechanism to explore, in detail stakeholders' interests, relative influence, and how outcomes of research are likely to impact different stakeholders. We apply these approaches to eastern Germany, where the increase in several wildlife populations (i.e., wild boar, common crane, gray wolf, and European bison) has contributed to conflict with people. We demonstrate the complementarity of FoPIA, SEEDS, and 3i in identifying stakeholder needs and showing how wildlife dynamics may affect coexistence and create imbalanced ecosystem service and disservice distributions. The integrated framework introduced here provides guidelines for analyzing the multistage process of stakeholder participation and enables a comprehensive approach to the complex challenge of HWCs. Leibniz Centre for Agricultural Landscape Research Marianne and Dr. Fritz Walter Fischer‐Foundation

1.Where agriculture expands into tropical and subtropical forests, social–ecological impacts are typically strong. However, where and how frontier development impacts on ecosystem functioning and services is often unclear, including which services trade‐off against agricultural production. This constitutes a major barrier towards planning for more sustainable outcomes in deforestation frontiers. 2. Here we assessed spatiotemporal change in multiple ecosystem services in the Argentine Chaco, a global deforestation hotspot. We modelled and mapped five ecosystem functions (i.e. carbon storage in biomass, carbon storage in soil, erosion control, excess rainfall retention by vegetation and soil fertility) which together provide three ecosystem services (i.e. agricultural suitability, climate regulation and flood regulation) for 1985, 2000 and 2013. We then employed this information to identify and map: (a) main trade‐offs between ecosystem services and agricultural production, and (b) bundles of changes in ecosystem services through the use of Self‐Organizing Maps. 3. Our results highlight that land‐use changes since 1985 have led to widespread and drastic declines in ecosystem functions and services across the Argentine Chaco. Mean losses of ecosystem services ranged between 6% and 10% for flood regulation, climate regulation and agricultural suitability. The largest losses occurred in the Dry Chaco subregion between 2000 and 2013. 4. We find two main types of trade‐offs between regulating ecosystem services and agricultural production. Increases in crop and pasture production occurred along with large and moderate losses, respectively, in flood regulation and climate regulation over 20% of the region. 5. Our mapping of bundles identified five common patterns of change in ecosystem services, delineating areas of stable or degrading ecosystem service supply. This provides a powerful template for adaptive spatial planning. 6. Synthesis and applications. Using the Argentinean Chaco as an example, we demonstrate how combining fine‐scale land‐use maps with biophysical models provides deep insights into the spatiotemporal patterns of changes in ecosystem services, and their trade‐offs with agricultural production. The periodic updating of maps of trade‐offs and bundles of change in ecosystem services provides key inputs for the adaptive management of highly dynamic and threatened landscapes, such as those in tropical and subtropical deforestation frontiers. EEA Balcarce Fil: Barral, María Paula. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; Argentina. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias; Argentina. Fil: Villarino, Sebastián Horacio. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Fil: Levers, Christian. Humboldt-Universität zu Berlin. Geography Department; Alemania Fil: Baumann, Mathias. Humboldt-Universität zu Berlin. Geography Department; Alemania Fil: Kuemmerle, Tobias. Humboldt-Universität zu Berlin. Geography Department; Alemania Fil: Mastrangelo, Matías Enrique. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina

Understanding how biodiversity responds to intensifying agriculture is critical to mitigating the trade‐offs between them. These trade‐offs are particularly strong in tropical and subtropical deforestation frontiers, yet it remains unclear how changing landscape context in such frontiers alters agriculture–biodiversity trade–offs. We focus on the Argentinean Chaco, a global deforestation hotspot, to explore how landscape context shapes trade‐off curves between agricultural intensity and avian biodiversity. We use a space‐for‐time approach and integrate a large field dataset of bird communities (197 species, 234 survey plots), three agricultural intensity metrics (meat yield, energy yield and profit) and a range of environmental covariates in a hierarchical Bayesian occupancy framework. Woodland extent in the landscape consistently determines how individual bird species, and the bird community as a whole, respond to agricultural intensity. Many species switch in their fundamental response, from decreasing occupancy with increased agricultural intensity when woodland extent in the landscape is low (loser species), to increasing occupancy with increased agricultural intensity when woodland extent is high (winner species). This suggests that landscape context strongly mediates who wins and loses along agricultural intensity gradients. Likewise, where landscapes change, such as in deforestation frontiers, the very nature of the agriculture–biodiversity trade–offs can change as landscapes transformation progresses. Synthesis and applications . Schemes to mitigate agriculture–biodiversity trade–offs, such as land sparing or sharing, must consider landscape context. Strategies that are identified based on a snapshot of data risk failure in dynamic landscapes, particularly where agricultural expansion continues to reduce natural habitats. Rather than a single, fixed strategy, adaptive management of agriculture–biodiversity trade–offs is needed in such situations. Here we provide a toolset for considering changing landscape contexts when exploring such trade‐offs. This can help to better align agriculture and biodiversity in tropical and subtropical deforestation frontiers. Instituto de Recursos Biológicos Fil: Macchi, Leandro. Universidad Nacional de Tucumán. Facultad de Ciencias Naturales e Instituto Miguel Lillo. Instituto de Ecología Regional; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tucumán; Argentina Fil: Decarre, Julieta. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Recursos Biológicos; Argentina Fil: Goijman, Andrea Paula. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Recursos Biológicos; Argentina Fil: Mastrangelo, Matias Enrique. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias. Grupo de Estudio de Agroecosistemas y Paisajes Rurales; Argentina. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; Argentina Fil: Blendinger, Pedro G. Universidad Nacional de Tucumán. Facultad de Ciencias Naturales e Instituto Miguel Lillo. Instituto de Ecología Regional; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tucumán; Argentina. Fil: Gavier Pizarro, Gregorio Ignacio. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Recursos Biológicos; Argentina Fil: Murray, Francisco. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria San Luis. Agencia de Extensión Rural San Luis; Argentina Fil: Piquer Rodriguez, María. Universidad Nacional de Tucumán. Facultad de Ciencias Naturales e Instituto Miguel Lillo. Instituto de Ecología Regional; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tucumán; Argentina Fil: Semper-Pascal, Asunción. Humboldt-University Berlin. Geography Department; Alemania Fil: Kuemmerle, Tobias. Humboldt-University Berlin. Geography Department; Alemania. Humboldt-University Berlin. Integrative Research Institute for Transformations in Human Environment Systems; Alemania

Agricultural expansion drives biodiversity loss globally, but impact assessments are biased towards recent time periods. This can lead to a gross underestimation of species declines in response to habitat loss, especially when species declines are gradual and occur over long time periods. Using Cold War spy satellite images (Corona), we show that a grassland keystone species, the bobak marmot ( Marmota bobak ), continues to respond to agricultural expansion that happened more than 50 years ago. Although burrow densities of the bobak marmot today are highest in croplands, densities declined most strongly in areas that were persistently used as croplands since the 1960s. This response to historical agricultural conversion spans roughly eight marmot generations and suggests the longest recorded response of a mammal species to agricultural expansion. We also found evidence for remarkable philopatry: nearly half of all burrows retained their exact location since the 1960s, and this was most pronounced in grasslands. Our results stress the need for farsighted decisions, because contemporary land management will affect biodiversity decades into the future. Finally, our work pioneers the use of Corona historical Cold War spy satellite imagery for ecology. This vastly underused global remote sensing resource provides a unique opportunity to expand the time horizon of broad-scale ecological studies.

Aims: Primary forests are critical for forest biodiversity and provide key ecosystem services. In Europe, these forests are particularly scarce and it is unclear whether they are sufficiently protected. Here we aim to: (a) understand whether extant primary forests are representative of the range of naturally occurring forest types, (b) identify forest types which host enough primary forest under strict protection to meet conservation targets and (c) highlight areas where restoration is needed and feasible. Location: Europe. Methods: We combined a unique geodatabase of primary forests with maps of forest cover, potential natural vegetation, biogeographic regions and protected areas to quantify the proportion of extant primary forest across Europe's forest types and to identify gaps in protection. Using spatial predictions of primary forest locations to account for underreporting of primary forests, we then highlighted areas where restoration could complement protection. Results: We found a substantial bias in primary forest distribution across forest types. Of the 54 forest types we assessed, six had no primary forest at all, and in two-thirds of forest types, less than 1% of forest was primary. Even if generally protected, only ten forest types had more than half of their primary forests strictly protected. Protecting all documented primary forests requires expanding the protected area networks by 1,132km2 (19,194km2 when including also predicted primary forests). Encouragingly, large areas of non-primary forest existed inside protected areas for most types, thus presenting restoration opportunities. Main conclusion: Europe's primary forests are in a perilous state, as also acknowledged by EU's “Biodiversity Strategy for 2030.” Yet, there are considerable opportunities for ensuring better protection and restoring primary forest structure, composition and functioning, at least partially. We advocate integrated policy reforms that explicitly account for the irreplaceable nature of primary forests and ramp up protection and restoration efforts alike.

Impacts of cattle production vary among different production systems, but data on their distribution is scarce for most world regions. In this work, we combine datasets on cattle vaccination locations and land cover in a regression framework to define and map major cattle production systems in the Argentinean Dry Chaco. We also explore how cattle occurrence relates to spatial determinants. Results indicate that the region harbors about 5.5 million heads. Cattle density was mainly described by the share of pasture (69.9%), cropland (28.1%) and aridity (23.8%). We identified 12-major cattle production systems: six cow-calf, three whole-cycle, and three fattening systems. Of these, four systems had high woodland cover (>85%). Data generated is available in a website. Understanding the distribution of cattle production systems is important to assess the environmental impacts of beef production at broad scales. Integrating vaccination data with land-cover information provides a promising avenue to identify livestock systems.

Trade agreements could help to protect human rights, critical ecosystems, and the climate—but only if sustainability becomes a cornerstone of international trade. The EU-Mercosur trade agreement fails to meet our three tenets of sustainable trade agreements: (1) inclusion of local communities, (2) transparency mechanisms to trace commodities and provide open-access information, and (3) enforcement to legally uphold sustainability commitments.

© 2018 Elsevier Ltd Changes in land systems generate many sustainability challenges. Identifying more sustainable land-use alternatives requires solid theoretical foundations on the causes of land-use/cover changes. Land system science is a maturing field that has produced a wealth of methodological innovations and empirical observations on land-cover and land-use change, from patterns and processes to causes. We take stock of this knowledge by reviewing and synthesizing the theories that explain the causal mechanisms of land-use change, including systemic linkages between distant land-use changes, with a focus on agriculture and forestry processes. We first review theories explaining changes in land-use extent, such as agricultural expansion, deforestation, frontier development, and land abandonment, and changes in land-use intensity, such as agricultural intensification and disintensification. We then synthesize theories of higher-level land system change processes, focusing on: (i) land-use spillovers, including land sparing and rebound effects with intensification, leakage, indirect land-use change, and land-use displacement, and (ii) land-use transitions, defined as structural non-linear changes in land systems, including forest transitions. Theories focusing on the causes of land system changes span theoretically and epistemologically disparate knowledge domains and build from deductive, abductive, and inductive approaches. A grand, integrated theory of land system change remains elusive. Yet, we show that middle-range theories – defined here as contextual generalizations that describe chains of causal mechanisms explaining a well-bounded range of phenomena, as well as the conditions that trigger, enable, or prevent these causal chains –, provide a path towards generalized knowledge of land systems. This knowledge can support progress towards sustainable social-ecological systems.

The world’s grasslands, both natural and managed, provide food and many non-provisioning ecosystem services. Although most grasslands today are used for livestock grazing or fodder production, little is known about the spatial patterns of grassland management intensity, especially at broad geographic scales. Using the European Union as a case study, we mapped mowing frequency as a key indicator of grassland management intensity. We used MODIS NDVI time series from 2000–2012 to map mowing frequency using a spline-fitting algorithm that detects up to five mowing events within a single growing season. We combined mowing frequency maps with existing maps of livestock distribution and grassland management frequency to identify clusters of similar grassland management intensity across Europe. Our results highlight generally high mowing frequency in areas of high grassland productivity, especially in Ireland, northern and central France, and the Netherlands. Our analyses also show distinct clusters of similar grassland management, representing different grassland-management intensity regimes. High intensity clusters occurred particularly in western and southern Europe, especially in Ireland, in the northern and central parts of France and Spain, and the Netherlands but also in northern and southern Germany and eastern Poland. Low intensity clusters were found mainly in central and eastern Europe and in mountainous regions but also in Extremadura in Spain, Wales and western England (UK). Generally, our analyses emphasize the usefulness of jointly using satellite time series and agricultural statistics to monitor grassland intensity across broad geographic extents. Our maps allow for a new, spatially-detailed view of management intensity in grassland systems and may help to improve regionally targeted land-use and conservation policies.

Agricultural land abandonment is a common land-use change, making the accurate mapping of both location and timing when agricultural land abandonment occurred important to understand its environmental and social outcomes. However, it is challenging to distinguish agricultural abandonment from transitional classes such as fallow land at high spatial resolutions due to the complexity of change process. To date, no robust approach exists to detect when agricultural land abandonment occurred based on 30-m Landsat images. Our goal here was to develop a new approach to detect the extent and the exact timing of agricultural land abandonment using spatial and temporal segments derived from Landsat time series. We tested our approach for one Landsat footprint in the Caucasus, covering parts of Russia and Georgia, where agricultural land abandonment is widespread. First, we generated agricultural land image objects from multi-date Landsat imagery using a multi-resolution segmentation approach. Second, we estimated the probability for each object that agricultural land was used each year based on Landsat temporal-spectral metrics and a random forest model. Third, we applied temporal segmentation of the resulting agricultural land probability time series to identify change classes and detect when abandonment occurred. We found that our approach was able to accurately separate agricultural abandonment from active agricultural lands, fallow land, and re-cultivation. Our spatial and temporal segmentation approach captured the changes at the object level well (overall mapping accuracy = 97 ± 1%), and performed substantially better than pixel-level change detection (overall accuracy = 82 ± 3%). We found strong spatial and temporal variations in agricultural land abandonment rates in our study area, likely a consequence of regional wars after the collapse of the Soviet Union. In summary, the combination of spatial and temporal segmentation approaches of time-series is a robust method to track agricultural land abandonment and may be relevant for other land-use changes as well.

Plausible scenarios of future land use derived from model projections may differ substantially from what is actually desired by society, and identifying such mismatches is important for identifying policies to resolve them. This paper presents an approach to link explorative projections of future land use for the European Union to normative visions of desired land-use futures. We used the results of 24 scenario projections obtained from seven linked simulation models to explore uncertainty in future land-use developments. Land-use projections were linked to statements made by stakeholders for three normative visions of desired, future land use. The visions differed in the scale of multifunctionality of land use: at European (Best Land in Europe), regional (Regional Connected) or local (Local Multifunctional) level. To identify pathways to these visions, we analysed in which cases projected land-use changes matched with the land-use changes desired in the visions. We identified five pathways to the vision Regional Connected, two pathways to the vision Best Land in Europe, but no pathway to the vision Local Multifunctional. Our results suggest that policies have the ability to change the development of land use such that it is more in line with land-use futures desired by society. We believe our approach represents an interesting avenue for foresight studies on land use, as it combines the credibility from explorative scenarios with legitimacy and saliency of normative visions.

Land cover maps increasingly underlie research into socioeconomic and environmental patterns and processes, including global change. It is known that map errors impact our understanding of these phenomena, but quantifying these impacts is difficult because many areas lack adequate reference data. We used a highly accurate, high-resolution map of South African cropland to assess (1) the magnitude of error in several current generation land cover maps, and (2) how these errors propagate in downstream studies. We first quantified pixel-wise errors in the cropland classes of four widely used land cover maps at resolutions ranging from 1 to 100 km, and then calculated errors in several representative "downstream" (map-based) analyses, including assessments of vegetative carbon stocks, evapotranspiration, crop production, and household food security. We also evaluated maps' spatial accuracy based on how precisely they could be used to locate specific landscape features. We found that cropland maps can have substantial biases and poor accuracy at all resolutions (e.g., at 1 km resolution, up to ∼45% underestimates of cropland (bias) and nearly 50% mean absolute error (MAE, describing accuracy); at 100 km, up to 15% underestimates and nearly 20% MAE). National-scale maps derived from higher-resolution imagery were most accurate, followed by multi-map fusion products. Constraining mapped values to match survey statistics may be effective at minimizing bias (provided the statistics are accurate). Errors in downstream analyses could be substantially amplified or muted, depending on the values ascribed to cropland-adjacent covers (e.g., with forest as adjacent cover, carbon map error was 200%-500% greater than in input cropland maps, but ∼40% less for sparse cover types). The average locational error was 6 km (600%). These findings provide deeper insight into the causes and potential consequences of land cover map error, and suggest several recommendations for land cover map users.

Almost all rural areas in Europe have been shaped or altered by humans and can be considered cultural landscapes, many of which now are considered to entail valuable cultural heritage. Current dynamics in land management have put cultural landscapes under a huge pressure of agricultural intensification and land abandonment. To prevent the loss of cultural landscapes, knowledge on the location of different types of cultural landscapes is needed. In this paper, we present a characterization of European cultural landscapes based on the prevalence of three key dimensions of cultural landscapes: landscape structure, management intensity, and value and meaning. We mapped these dimensions across Europe at a 1-km resolution by combining proxies on management intensity and landscape structure with new indicators such as social media usage and registered traditional food products. We integrated the three dimensions into a continuous “cultural landscape index” that allows for a characterization of Europe’s rural landscapes. The characterization identifies hotspots of cultural landscapes, where all three dimensions are present, such as in the Mediterranean. On the other hand, Eastern and Northern European cultural landscapes are mostly characterized by only one of the dimensions. Our paper can help to identify pressures to cultural landscapes and thus to target measures for the conservation of these landscapes, to link similar landscapes in different regions, and to inform policy design on the most important characteristics of cultural landscapes at a regional scale.

Land system archetypes are unique patterns of land-use intensity within prevailing environmental and socio-economic conditions that occur repeatedly across the terrestrial surface of the earth [1].

Armed conflicts are globally widespread and can strongly influence societies and the environment. However, where and how armed conflicts affect agricultural land-use is not well-understood. The Caucasus is a multi-ethnic region that experienced several conflicts shortly after the collapse of the Soviet Union, most notably the two Chechen Wars, raising the question how agricultural lands were changed. Here, we investigated how the distance to conflicts and conflict intensity, measured as the number of conflicts and the number of casualties, affected agricultural land abandonment and subsequent re-cultivation, by combining social, environmental and economic variables with remotely-sensed maps of agricultural change. We applied logistic and panel regression analyses for both the First Chechen War (1994–1996) and the Second Chechen War (1999–2009) and interacted conflict distance with conflict intensity measures. We found that agricultural lands closer to conflicts were more likely to be abandoned and less likely to be re-cultivated, with stronger effects for the First Chechen War. Conflict intensity was positively correlated with agricultural land abandonment, but the effects differed based on distance to conflicts and the intensity measure. We found little re-cultivation after the wars, despite abundant subsidies, indicating the potentially long-lasting effects of armed conflicts on land-use. Overall, we found a clear relationship between the Chechen Wars and agricultural land abandonment and re-cultivation, illustrating the strong effects of armed conflicts on agriculture.

Understanding the trade-offs between biodiversity conservation and agricultural production has become a fundamental question in sustainability science. Substantial research has focused on how species’ populations respond to agricultural intensification, with the goal to understand whether conservation policies that spatially separate agriculture and conservation or, alternatively, integrate the two are more beneficial. Spatial heterogeneity in both species abundance and agricultural productivity have been largely left out of this discussion, although these patterns are ubiquitous from local to global scales due to varying land capacity. Here, we address the question of how to align agricultural production and biodiversity conservation in heterogeneous landscapes. Using model simulations of species abundance and agricultural yields, we show that trade-offs between agricultural production and species’ abundance can be reduced by minimizing the cost (in terms of species abundance) of agricultural production. We find that when species’ abundance and agricultural yields vary across landscapes, the optimal strategy to minimize trade-offs is rarely pure land sparing or land sharing. Instead, landscapes that combine elements of both strategies are optimal. Additionally, we show how the reference population of a species is defined has important influences on optimization results. Our findings suggest that in the real world, understanding the impact of heterogeneous land capacity on biodiversity and agricultural production is crucial to designing multi-use landscapes that jointly maximize conservation and agricultural benefits. Fil: Butsic, Van. University of California at Berkeley; Estados Unidos. Berkeley University; Estados Unidos Fil: Kuemmerle, Tobias. Universität zu Berlin; Alemania Fil: Pallud, Leo. ENSTA ParisTech; Francia Fil: Helmstedt, Kate J.. Queensland University of Technology; Australia Fil: Macchi, Leandro. Universidad Nacional de Tucumán. Instituto de Ecología Regional. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Ecología Regional; Argentina. Universität zu Berlin; Alemania Fil: Potts, Matthew D.. University of California at Berkeley; Estados Unidos

Traditional farming landscapes in the temperate zone that have persisted for millennia can be exceptionally species-rich and are therefore key conservation targets. In contrast to Europe’s West, Eastern Europe harbours widespread traditional farming landscapes, but drastic socio-economic and political changes in the twentieth century are likely to have impacted these landscapes profoundly. We reconstructed long-term land-use/cover and biodiversity changes over the last 150 years in a traditional farming landscape of outstanding species diversity in Transylvania. We used the Regional Estimates of Vegetation Abundance from Large Sites model applied to a pollen record from the Transylvanian Plain and a suite of historical and satellite-based maps. We documented widespread changes in the extent and location of grassland and cropland, a loss of wood pastures as well as a gradual increase in forest extent. Land management in the socialist period (1947–1989) led to grassland expansion, but grassland diversity decreased due to intensive production. Land-use intensity has declined since the collapse of socialism in 1989, resulting in widespread cropland abandonment and conversion to grassland. However, these trends may be temporary due to both ongoing woody encroachment as well as grassland management intensification in productive areas. Remarkably, only 8% of all grasslands existed throughout the entire time period (1860–2010), highlighting the importance of land-use history when identifying target areas for conservation, given that old-growth grasslands are most valuable in terms of biodiversity. Combining datasets from different disciplines can yield important additional insights into dynamic landscape and biodiversity changes, informing conservation actions to maintain these species-rich landscapes in the longer term.

Comprehensive maps that characterize the variation in agricultural landscapes across Europe are lacking. In this paper we present a new Europe-wide, spatially-explicit typology and inventory of the diversity in composition, spatial structure and management intensity of European agricultural landscapes. Agricultural landscape types were characterized at a 1 km 2 resolution based on Europe-wide datasets that represent land cover, landscape structure and land management intensity. Two alternative approaches for typology development were used: an expert-based top-down approach, and a bottom-up approach based on automated clustering using Self Organizing Maps (SOMs). Comparison with available national and European landscape typologies showed that our typology deviates from existing biophysical and anthropocentric typologies relevant to agricultural landscapes as result of the inclusion of land management aspects. Concordance occurred between specific European typology classes, while the comparison with national landscape typologies showed a correspondence in agricultural landscape patterns. Our agricultural landscape typology can provide a basis for landscape assessment at a European-scale to help to identify agricultural landscape types prone to change and landscapes that may require policy response.

The recent rise in agricultural commodity prices and the expectation that high price will persist have triggered a wave of farmland expansion in regions where land resources are still available. One such region is the former Soviet Union, where the collapse of socialism caused massive agricultural abandonment and where some of these lands are now being brought back into production. Yet, the extent and spatial patterns of recultivation, and what determines these patterns, remains unclear. We examined the extent of recultivation of abandoned agricultural land in Ukraine since 2007 using a new, satellite-based recultivation map and assessed the effect of biophysical and socioeconomic determinants on recultivation patterns using boosted regression trees. We found key predictors of recultivation to be related to the suitability of land for agriculture (i.e., soil quality, temperature). Accessibility to major cities was also important, with most recultivation happening closer to settlements, but this influence varied across Ukraine. Variables related to agricultural management (fertilizer input, mechanization) and demography were negligible in explaining recultivation in our analyses. These factors suggest that recultivation patterns were primarily driven by factors related to land productivity, with recultivation focusing on the most promising areas. Given the remaining large amount of unused agricultural land in Eastern Europe and the former Soviet Union, and considering that much abandonment occurred in areas only marginally suited to agriculture, our findings provide important insights into where recultivation can be expected to happen and thus for assessing the potential socioeconomic and environmental impacts of recultivation.

The global demand for agricultural products will increase in the 21st century, unless major transformations in consumptive behaviour occur. To a large extent, production increases in agriculture will depend on intensifying existing agricultural systems. Yet, our understanding of what determines the spatial pat- terns of agricultural intensity and changes therein is limited. Here, we analysed agricultural intensity changes in Europe focussing on yields and fertiliser application for six major crop-type groups for the period 1990–2007. We applied random effects panel regressions to analyse the spatial determinants of intensity changes using a suite of biophysical and socio-economic variables. We found that yields increased and mineral nitrogen application decreased by approximately 10%, suggesting a decoupling of changes in output and input intensity in Europe’s agricultural systems. Yields and nitrogen application across crop-type groups were particularly high in Western and Central Europe, whereas Eastern Europe was characterised by lower yields and nitrogen application. We also found strong sub-national variation in intensity levels in respect to crop-type groups and indicators. Higher yields were typically related to higher fertilisation, high soil quality, less growing degree days, and high labour productivity. Higher nitrogen application rates, in turn, were related to high soil water and carbon contents, and high labour productivity. Our study provides insights into broad-scale agricultural intensity patterns in Europe that allow for identifying trade-offs between agriculture and the environment, as well as entry points for regionalised, targeted policy making towards a more sustainable management of Europe land systems.

Assessments of land-system change have dominantly focused on conversions among broad land-use categories, whereas intensity changes within these categories have received less attention. Considering that both modes of land change typically result in diverse patterns and trajectories of land-system change, there is a need to develop approaches to reduce this complexity. Using Europe as a case study, we applied a clustering approach based on self-organising maps and 12 land-use indicators to map (1) land-system archetypes for the year 2006, defined as characteristic patterns of land-use extent and intensity, and (2) archetypical change trajectories, defined as characteristic changes in these indicators between 1990 and 2006. Our analysis identified 15 land-system archetypes, with low-intensity archetypes dominating (ca. 55 % coverage) followed by high-intensity archetypes (ca. 26 %). In terms of change, we identified 17 archetypical change trajectories, clustered in four broad categories. Stable land systems were most widespread (ca. 40 % of the EU27), followed by land systems characterised by land-use conversions (ca. 26 %), de-intensification trends (ca. 18 %), and intensification trends (ca. 15 %). Intensively used and intensifying land systems were particularly widespread in Western Europe, whereas low-intensity and de-intensifying land systems dominated in Europe’s east. Comparing our archetypes with environmental and socio-economic factors revealed that good accessibility and favourable topographic, climatic, and soil conditions characterised intensively managed areas. Intensification was also most common in these areas, suggesting an ongoing polarisation of intensification in favourable areas and de-intensification and abandonment trends in more marginal areas. By providing spatially and thematically improved maps of land-use patterns and changes therein, our archetypes could serve as useful inputs for more detailed assessments of ecosystem service demand and supply, as well as explorations of land-system change trade-offs, especially with regard to land-use intensity. Further, they could serve useful for identifying regions within which similar policy tools could be valuable to develop regionalised, context-specific land-management policies to steer European land systems onto desired pathways.

Temperate grasslands are globally widespread, play an important role as carbon storage, and harbor unique biodiversity. Livestock grazing is the most widespread land use in temperate grasslands, and understanding the impact of grazing on grassland ecosystems is therefore important. However, monitoring grazing pressure and how it changes is hampered by a lack of adequate tools. The Eurasian steppe belt, extending from Eastern Europe to China has experienced marked changes in grazing pressure. Most notably, livestock numbers in the steppes of Kazakhstan and Russia declined by up to 80% after the breakdown of the Soviet Union in 1991, yet how this impacted spatial patterns of grazing pressure is unclear. To address this research gap, we used all available Landsat data from 1985 to 2017 together with extensive ground reference data on grazing pressure to evaluate a broad range of spectral-temporal metrics regarding their ability to capture grazing pressure. While Tasseled Cap-based disturbance indices performed best, combining all spectral-temporal metrics in a binary random forest classification yielded a grazing class membership probability that strongly outperformed all individual metrics. This new index of grazing pressure correlated well with a range of field-based grazing indicators (e.g., number of dung piles, herbaceous biomass) and yielded highly plausible spatial patterns of grazing pressure. We used this index to reconstruct annual changes in grazing pressure across our 360,000 km2 study region, and used LandTrendr time series segmentation to identify trends in grazing pressure. Aggregated grazing pressure followed closely known trends in total livestock numbers over the time period we studied. The spatial footprint of heavy grazing was very large before 1991, but decreased by 73 (±2) % until 2017. This now leaves large areas virtually ungrazed, even in close vicinity to settlements and agricultural areas, and despite a recent recovery of livestock numbers. Our analyses uncovered previously unknown hot-spots of heavy grazing during Soviet times (e.g., around watering points). Our findings suggest potential for a further revival of the livestock sector as well as for the restoration of steppe ecosystems. More broadly, our study highlights how the Landsat archive, in combination with field data on grazing, can be used to map grazing pressure reliably across large areas and over long time spans.

[Aim] Agriculture is a key threat to biodiversity; however, its relationship with biodiversity patterns is understudied. Here, we evaluate how the extent, intensity and history of croplands relate to the global distribution of threatened mammals. We propose two hypotheses to explain these relationships: shelter, which predicts that threatened species concentrate in areas with low human land use; and threat, according to which threatened species should concentrate in areas of high human land use., [Location] Global. [Time period] c. 6000 BC – AD 2014. [Major taxa studied] Terrestrial mammals. [Methods] We used boosted regression trees (BRT) that include spatial autocorrelation to investigate the relationship between the proportion of threatened terrestrial mammals [as defined by the International Union for Conservation of Nature (IUCN) Red List] and multiple metrics describing agricultural extent, intensity and history derived from remote sensing data and statistical projections. Data were analysed with a grain size of c. 110 km × 110 km at both global and biogeographical-realm scales. [Results] Agricultural extent and intensity were the most relevant indicator types, with specific metrics important for each realm. Forest cover (extent) was identified as important in several regions. Tropical regions in early agricultural transition stages (e.g. frontier landscapes) were consistent with the shelter hypothesis, whereas patterns found for regions in later stages (e.g. intensified agricultural landscapes) were mostly found in temperate regions and agreed with the threat hypothesis. [Main conclusions] These results highlight the need to consider multiple land-use indicators when addressing threats to biodiversity and to separately assess areas with divergent human and ecological histories in global-scale studies. Different relationships associated with different agricultural transition stages suggest that high concentrations of threatened species may have contrasting meanings in different regions worldwide. We propose a new unifying hypothesis following a cyclic relationship along agricultural transition stages resulting in alternating negative and positive relationships between agriculture and threatened species richness., This research was supported by the program ‘Junta para la Ampliación de Estudios CSIC’ (JAEPre grant to EPL BOE‐A‐2011–10745, co‐funded by the European Social Fund), the European Commission (FP‐7, grant n° 235897), the Spanish Ministry of Science and Innovation co‐funded by European Regional Development Fund (ERDF) (CGL2009–07301/BOS, CGL2012–35931/BOS and JCI‐2011–09158) and the Einstein Foundation Berlin.

Knowledge of the spatial distribution of agricultural abandonment following the collapse of the Soviet Union is highly uncertain. To help improve this situation, we have developed a new map of arable and abandoned land for 2010 at a 10 arc-second resolution. We have fused together existing land cover and land use maps at different temporal and spatial scales for the former Soviet Union (fSU) using a training data set collected from visual interpretation of very high resolution (VHR) imagery. We have also collected an independent validation data set to assess the map accuracy. The overall accuracies of the map by region and country, i.e. Caucasus, Belarus, Kazakhstan, Republic of Moldova, Russian Federation and Ukraine, are 90±2%, 84±2%, 92±1%, 78±3%, 95±1%, 83±2%, respectively. This new product can be used for numerous applications including the modelling of biogeochemical cycles, land-use modelling, the assessment of trade-offs between ecosystem services and land-use potentials (e.g., agricultural production), among others.

Agricultural abandonment is widespread and growing in many regions worldwide, often because of agricultural intensification on productive lands, conservation policies, or the spatial decoupling of agricultural production from consumption. Abandonment has major environmental and social impacts, which differ starkly depending on the geographical context, as does its potential to serve as a land reservoir for recultivation. Understanding determinants of abandonment patterns, and especially how their influence varies across broad geographic extents, is therefore important. Using a pan-European map of agricultural abandonment derived from MODIS NDVI time series between 2001 and 2012, we quantified the importance of farm management, climatic, environmental, and socio-economic variables in explaining abandonment patterns. We chose a machine learning modelling framework that accounts for spatial variation in the relationship between abandonment and its determinants. We predicted abandonment probability as well as determinant coefficients for the entire study area and summarised them for regions under selected EU support schemes. Our results highlight that agricultural abandonment was mainly explained by climate conditions suboptimal for agriculture (i.e., low/high growing degrees days). Determinants related to farm management (smaller field size, lower yields) and socio-economic conditions (high unemployment, negative migration balance) also contributed to describing agricultural abandonment patterns in Europe. Several determinants influenced abandonment in strongly non-linear ways and we found substantial spatial non-stationarity effects, although abandonment patterns were equally well-explained by predictors specified with spatially constant and varying effects. Predicted abandonment probability was similar inside and outside EU support or conservation zones, whereas observed MODIS-based abandonment was generally higher outside these zones, suggesting that schemes such as Natura 2000 or High Nature Value Farmland likely influence abandonment patterns. Our work highlights the potential value of spatial boosting for gaining insights into land-use change processes and their outcomes, which should increase the ability of such models to inform context-specific, regionalised decision making.

Agricultural expansion and intensification in South America's dry forests and grasslands increase agricultural production, but also result in major environmental trade-offs. The Pampas and Chaco regions of Argentina have been global hotspots of agricultural land-use change since the 2000s, yet our understanding of what drives the spatial patterns of these land-use changes remains partial. We parameterized a net returns model of agricultural land-use change to estimate the probability of agricultural expansion (conversions of woodlands to either cropland or grazing land) and agricultural intensification (conversion of grazing land to cropland) at the 1-km scale for the years 2000 and 2010. Uniquely, our model allowed us to quantify the importance of underlying causes (i.e., changes in agricultural profit) and spatial determinants (i.e., soil fertility, distance to markets, etc.), for Argentina's prime agricultural regions as a whole. We found that cropland and grazing land expansion into woodlands was much less sensitive to changes in profit-related factors than agricultural intensification. Profit-related variables, were a particularly strong cause of intensification in the Pampas, where cropland profits rose by 29% (compared to 18% in the Chaco). This suggests that further conversions of grazing land to cropland in the Pampas and Chaco is likely as long as agricultural demand, and thus returns to agriculture, continue to be high. The moderate impact of profit-related factors on affecting woodland conversion rates also suggests a limited potential of economic policies that affect marginal profits (e.g., taxes or subsidies) to alter deforestation rates and patterns in major ways. Policies that target socio-economic variables not included in our profit-focused framework (e.g., capital availability), area-based interventions (e.g., land zoning), or less-profit oriented actors (e.g., via community-based management) might be more effective in addressing deforestation rates in the Chaco. Fil: Piquer Rodríguez, María. Universität zu Berlin; Alemania Fil: Butsic, Van. University of California at Berkeley; Estados Unidos Fil: Gärtner, P.. Leibniz Centre for Agricultural Landscape Research; Alemania Fil: Macchi, Leandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán; Argentina. Universität zu Berlin; Alemania Fil: Baumann, Matthias. Universität zu Berlin; Alemania Fil: Gavier Pizarro, Gregorio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación de Recursos Naturales. Instituto de Recursos Biológicos; Argentina Fil: Volante, José Norberto. Instituto Nacional de Tecnología Agropecuaria; Argentina Fil: Gasparri, Nestor Ignacio. Universidad Nacional de Tucumán. Instituto de Ecología Regional. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Ecología Regional; Argentina Fil: Kuemmerle, Tobias. Universität zu Berlin; Alemania

Explorations of future land use change are important to understand potential conflicts between competing land uses, trade-offs associated with particular land change trajectories, and the effectiveness of policies to steer land systems into desirable states. Most model-based explorations and scenario studies focused on conversions in broad land use classes, but disregarded changes in land management or focused on individual sectors only. Using the European Union (EU) as a case study, we developed an approach to identifying typical combinations of land cover and management changes by combining the results of multimodel simulations in the agriculture and forest sectors for four scenarios from 2000 to 2040. We visualized land change trajectories by mapping regional hotspots of change. Land change trajectories differed in extent and spatial pattern across the EU and among scenarios, indicating trajectory-specific option spaces for alternative land system outcomes. In spite of the large variation in the area of change, similar hotspots of land change were observed among the scenarios. All scenarios indicate a stronger polarization of land use in Europe, with a loss of multifunctional landscapes. We analyzed locations subject to change by comparing location characteristics associated with certain land change trajectories. Results indicate differences in the location conditions of different land change trajectories, with diverging impacts on ecosystem service provisioning. Policy and planning for future land use needs to account for the spatial variation of land change trajectories to achieve both overarching and location-specific targets.

As the applications of Earth system models (ESMs) move from general climate projections toward questions of mitigation and adaptation, the inclusion of land management practices in these models becomes crucial. We carried out a survey among modeling groups to show an evolution from models able only to deal with land‐cover change to more sophisticated approaches that allow also for the partial integration of land management changes. For the longer term a comprehensive land management representation can be anticipated for all major models. To guide the prioritization of implementation, we evaluate ten land management practices—forestry harvest, tree species selection, grazing and mowing harvest, crop harvest, crop species selection, irrigation, wetland drainage, fertilization, tillage, and fire—for (1) their importance on the Earth system, (2) the possibility of implementing them in state‐of‐the‐art ESMs, and (3) availability of required input data. Matching these criteria, we identify “low‐hanging fruits” for the inclusion in ESMs, such as basic implementations of crop and forestry harvest and fertilization. We also identify research requirements for specific communities to address the remaining land management practices. Data availability severely hampers modeling the most extensive land management practice, grazing and mowing harvest, and is a limiting factor for a comprehensive implementation of most other practices. Inadequate process understanding hampers even a basic assessment of crop species selection and tillage effects. The need for multiple advanced model structures will be the challenge for a comprehensive implementation of most practices but considerable synergy can be gained using the same structures for different practices. A continuous and closer collaboration of the modeling, Earth observation, and land system science communities is thus required to achieve the inclusion of land management in ESMs.

Tropical forests provide critical ecosystem services worldwide. Nonetheless, ongoing agricultural expansion, timber extraction, and mining continue to jeopardize important forest resources. In addition, many tropical forests reside in countries that have experienced violent conflict in recent decades, posing an additional, yet poorly understood threat. Conflict may decrease or increase deforestation depending on the relationship between conflict and other causes of land use change, such as mining expansion or protected area establishment. The Democratic Republic of Congo (DRC), home of the second largest tropical forest in the world, has experienced 20 years of violent conflict, resulting in the death of over 100,000 combatants and up to 5 million civilians. Expanding mining concessions also threaten the DRC's forest, even though nearly 12% of it is under some form of protection. In this study, we used spatially-explicit data on conflict, mining, and protected areas, along with a host of control variables, to estimate the impacts of these factors on forest cover loss from 1990 to 2010. Through a panel instrumental variables approach we found that: i) conflict increased forest cover loss, ii) mining concessions increased forest cover loss, but in times of conflict this impact was lessened, and iii) protected areas reduced forest cover loss, even in high conflict regions. Our results thus suggest that policy interventions designed to reduce violent conflict may have the co-benefit of reducing deforestation, especially in areas with low mining potential. Likewise, protected areas can be effective even in times of war.

Soybean expansion has been a strong driver of deforestation and biodiversity loss in South America. Here we highlight strong similarities in environmental, institutional, and other contextual conditions among South American (SAM) and Southern African (SAFR) dry forest and savanna regions, and compile evidence for an emerging soybean production frontier in Southern Africa. Knowledge transfer, cooperation, and direct investment between South American and Southern African countries constitute crucial elements of soybean expansion in Africa. Comparing maps of soybean suitability, biodiversity, and carbon revealed substantial and spatially diverse trade-offs, suggesting that the emerging soybean frontier in Southern Africa may poses major challenges for conservation. An increased focus of conservation science on agricultural expansion and intensification in Southern African, as well as strong environmental policies for balancing agricultural production and conservation goals, are needed to mitigate potentially large trade-offs. The coupling of production frontiers should be a vehicle for the transfer not only of agricultural technology and production models, but also of experiences in environmental governance on emerging agricultural frontiers.

Forests are critically important for life on earth, prompting a variety of efforts to protect them. Protected areas and logging regulations are the most commonly used forest conservation strategies, but local traditions and religious beliefs can also protect natural resources by limiting exploitative use. We compared the effectiveness of protected areas, a logging ban, and sacred areas to protect forests from logging in Northwest Yunnan, China, a global biodiversity hotspot. We combined Mahalanobis matching and panel regression techniques to measure effectiveness of these three protection strategies paying special attention to old growth forest communities. We found that protected areas had no impact on total forest cover, but effectively conserved old-growth forests relative to non-protected areas. The implementation of the logging ban resulted in positive forest conservation outcomes over most of the landscape. The exception was that logging in old-growth forests inside sacred areas accelerated following the implementation of the logging ban, suggesting that local institutions may have been weakened by official policies. Our research finds little evidence that overlapping conservation policies decrease deforestation and suggests that the implementation of official policies may displace local forms of protection. Our results further highlight that relying on total forest cover as a single indicator of conservation outcomes can lead to misleading conclusions about the impacts of forest protection strategies.

Agricultural expansion is a leading driver of biodiversity loss across the world, but little is known on how future land-use change may encroach on remaining natural vegetation. This uncertainty is, in part, due to unknown levels of future agricultural intensification and international trade. Using an economic land-use model, we assessed potential future losses of natural vegetation with a focus on how these may threaten biodiversity hotspots and intact forest landscapes. We analysed agricultural expansion under proactive and reactive biodiversity protection scenarios, and for different rates of pasture intensification. We found growing food demand to lead to a significant expansion of cropland at the expense of pastures and natural vegetation. In our reference scenario, global cropland area increased by more than 400 Mha between 2015 and 2050, mostly in Africa and Latin America. Grazing intensification was a main determinant of future land-use change. In Africa, higher rates of pasture intensification resulted in smaller losses of natural vegetation, and reduced pressure on biodiversity hotspots and intact forest landscapes. Investments into raising pasture productivity in conjunction with proactive land-use planning appear essential in Africa to reduce further losses of areas with high conservation value. In Latin America, in contrast, higher pasture productivity resulted in increased livestock exports, highlighting that unchecked trade can reduce the land savings of pasture intensification. Reactive protection of sensitive areas significantly reduced the conversion of natural ecosystems in Latin America. We conclude that protection strategies need to adapt to region-specific trade positions. In regions with a high involvement in international trade, area-based conservation measures should be preferred over strategies aimed at increasing pasture productivity, which by themselves might not be sufficient to protect biodiversity effectively.

South America's tropical dry forests and savannas are under increasing pressure from agricultural expansion. Cattle ranching and soybean production both drive these forest losses, but their relative importance remains unclear. Also unclear is how soybean expansion elsewhere affects deforestation via pushing cattle ranching to deforestation frontiers. To assess these questions, we focused on the Chaco, a 110 million ha ecoregion extending into Argentina, Bolivia, and Paraguay, with about 8 million ha of deforestation in 2000–2012. We used panel regressions at the district level to quantify the role of soybean expansion in driving these forest losses using a wide range of environmental and socio-economic control variables. Our models suggest that soybean production was a direct driver of deforestation in the Argentine Chaco only (0.08 ha new soybean area per ha forest lost), whereas cattle ranching was significantly associated with deforestation in all three countries (0.02 additional cattle per hectare forest loss). However, our models also suggested Argentine soybean cultivation may indirectly be linked to deforestation in the Bolivian and Paraguayan Chaco. We furthermore found substantial time-delayed effects in the relationship of soybean expansion in Argentina and Paraguay (i.e., soybean expansion in one year resulted in deforestation several years later) and deforestation in the Chaco, further suggesting that possible displacement effects within and between Chaco countries may at least partly drive forest loss. Altogether, our study showed that deforestation in the Chaco appears to be mainly driven by the globally surging demand for soybean, although regionally other proximate drivers are sometimes important. Steering agricultural production in the Chaco and other tropical dry forests onto sustainable pathways will thus require policies that consider these scale effects and that account for the regional variation in deforestation drivers within and across countries. Fil: Fehlenberg, Verena. Universität zu Berlin; Alemania Fil: Baumann, Matthias. Universität zu Berlin; Alemania Fil: Gasparri, Nestor Ignacio. Universidad Nacional de Tucumán. Instituto de Ecología Regional. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Ecología Regional; Argentina. Universität zu Berlin; Alemania Fil: Piquer Rodriguez, Maria. Universität zu Berlin; Alemania Fil: Gavier Pizarro, Gregorio. Universidad Nacional de Tucumán. Instituto de Ecología Regional. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Ecología Regional; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación de Recursos Naturales; Argentina Fil: Kuemmerle, Tobias. Universität zu Berlin; Alemania

Carbon emissions from land-use changes in tropical dry forest systems are poorly understood, although they are likely globally significant. The South American Chaco has recently emerged as a hot spot of agricultural expansion and intensification, as cattle ranching and soybean cultivation expand into forests, and as soybean cultivation replaces grazing lands. Still, our knowledge of the rates and spatial patterns of these land-use changes and how they affected carbon emissions remains partial. We used the Landsat satellite image archive to reconstruct land-use change over the past 30 years and applied a carbon bookkeeping model to quantify how these changes affected carbon budgets. Between 1985 and 2013, more than 142 000 km2 of the Chaco's forests, equaling 20% of all forest, was replaced by croplands (38.9%) or grazing lands (61.1%). Of those grazing lands that existed in 1985, about 40% were subsequently converted to cropland. These land-use changes resulted in substantial carbon emissions, totaling 824 Tg C between 1985 and 2013, and 46.2 Tg C for 2013 alone. The majority of these emissions came from forest-to-grazing-land conversions (68%), but post-deforestation land-use change triggered an additional 52.6 Tg C. Although tropical dry forests are less carbon-dense than moist tropical forests, carbon emissions from land-use change in the Chaco were similar in magnitude to those from other major tropical deforestation frontiers. Our study thus highlights the urgent need for an improved monitoring of the often overlooked tropical dry forests and savannas, and more broadly speaking the value of the Landsat image archive for quantifying carbon fluxes from land change. Fil: Baumann, Matthias. Universität zu Berlin; Alemania Fil: Gasparri, Nestor Ignacio. Universidad Nacional de Tucumán. Instituto de Ecología Regional. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Ecología Regional; Argentina. Universität zu Berlin; Alemania Fil: Piquer-Rodríguez, María. Universität zu Berlin; Alemania Fil: Gavier Pizarro, Gregorio. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación de Recursos Naturales. Instituto de Recursos Biológicos; Argentina Fil: Griffiths, Patrick. Universität zu Berlin; Alemania Fil: Hostert, Patrick. Universität zu Berlin; Alemania Fil: Kuemmerle, Tobias. Universität zu Berlin; Alemania

Context: Ecological impacts of past land use can persist for centuries. While present-day land use is relatively easy to quantify, characterizing historical land uses and their legacies on biodiversity remains challenging. Southern Transylvania in Romania is a biodiversity-rich area which has undergone major political and socio-economic changes, from the Austro-Hungarian Empire to two World Wars, communist dictatorship, capitalist democracy, and EU accession—all leading to widespread land-use changes. Objectives: We investigated whether present-day community composition of birds, plants, and butterflies was associated with historical land use. Methods: We surveyed birds, plants, and butterflies at 150 sites and classified those sites as forest, arable land, or managed grassland for six epochs using historical maps from the 1870s, 1930s, and 1970s, satellite imagery from 1985 to 2000, and field visits in 2012. Sites were labelled permanent if they had the same land use at all epochs and non-permanent otherwise. We used clustering and PERMANOVA based on community similarity to test for associations between community composition and land-use history. Results: We found significant differences (p = 0.030) in bird communities between permanent and non-permanent forest sites, and permanent and non-permanent grassland sites (p = 0.051). No significant associations were found among plants or butterflies and land-use history. Conclusions: Bird communities were associated with historical land use, though plants and butterflies were not. Historical land-use change in our study area was likely not sufficiently intense to cross relevant ecological thresholds that would lead to legacy effects in present-day plant and butterfly communities.

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., We thank F. Pötzschner and B. Jakimow for technical support. L.K. and T.K. acknowledge funding by the Einstein Foundation Berlin (Germany).

Historical land use may shape landscapes for centuries into the future, but it remains unclear how much land-use legacies affect contemporary land use. Knowing for how long and how strongly land-use legacies affect agricultural systems is important for contemporary land-use planning and conservation. We assessed the effect of nineteenth-century agricultural legacies for contemporary agricultural abandonment by integrating historic maps and satellite imagery in the Carpathian region. We modeled the choice of agricultural land, and the legacies of Habsburg and Socialist regimes, while controlling for agro-ecological, accessibility and sociopolitical variation. Farming during the Habsburg era was concentrated in agro-ecologically suitable areas, but socialist agricultural expansion occurred mostly in less suitable areas, leading to subsequent abandonment. In addition, our results showed that historic land use affected abandonment even 100 years later. Although legacies diminished over time, their effects were amplified when political transformations occurred, likely due to land tenure systems, land owner attitudes, cultural values and differences in land improvement over time. Taken together, land-use legacies and shifts in political systems can constrain current land management and possible future land-use options, suggesting that contemporary land-use decisions can affect future land use for decades and even centuries.

In the light of daunting global sustainability challenges such as climate change, biodiversity loss and food security, improving our understanding of the complex dynamics of the Earth system is crucial. However, large knowledge gaps related to the effects of land management persist, in particular those human-induced changes in terrestrial ecosystems that do not result in land-cover conversions. Here, we review the current state of knowledge of ten common land management activities for their biogeochemical and biophysical impacts, the level of process understanding and data availability. Our review shows that ca. one-tenth of the ice-free land surface is under intense human management, half under medium and one-fifth under extensive management. Based on our review, we cluster these ten management activities into three groups: (i) management activities for which data sets are available, and for which a good knowledge base exists (cropland harvest and irrigation); (ii) management activities for which sufficient knowledge on biogeochemical and biophysical effects exists but robust global data sets are lacking (forest harvest, tree species selection, grazing and mowing harvest, N fertilization); and (iii) land management practices with severe data gaps concomitant with an unsatisfactory level of process understanding (crop species selection, artificial wetland drainage, tillage and fire management and crop residue management, an element of crop harvest). Although we identify multiple impediments to progress, we conclude that the current status of process understanding and data availability is sufficient to advance with incorporating management in, for example, Earth system or dynamic vegetation models in order to provide a systematic assessment of their role in the Earth system. This review contributes to a strategic prioritization of research efforts across multiple disciplines, including land system research, ecological research and Earth system modelling.

[1] Widespread cropland abandonment occurred after the collapse of socialism across the former Soviet Union, but the rates and spatial patterns of abandoned lands are not well known. As a result, the potential of this region to contribute to global food production and estimates of the carbon sink developing on currently idle lands are highly uncertain. We developed a spatial allocation model that distributes yearly and subnational sown area statistics to the most agriculturally suitable plots. This approach resulted in new, high-resolution (1 km2) annual time series of cropland and abandoned lands in European Russia, Ukraine, and Belarus from 1990 to 2009. A quantitative validation of the cropland map confirms the reliability of this data set, especially for the most important agricultural areas of the study region. Overall, we found a total of 87 Mha of cropland and 31 Mha of abandoned cropland in European Russia, Ukraine, and Belarus combined, suggesting that abandonment has been severely underestimated in the past. The abandonment rates were highest in European Russia. Feeding our new map data set into the dynamic vegetation model LPJmL revealed that cropland abandonment resulted in a net carbon sink of 470 TgC for 1990 to 2009. Carbon sequestration was generally slow in the early years after abandonment, but carbon uptake increased significantly after approximately 10 years. Recultivation of older abandoned lands would be associated with high carbon emissions and lead to substantial amounts of carbon not being sequestered in vegetation formations currently developing on idle croplands. Our spatially and temporally explicit cropland abandonment data improve the estimation of trade-offs involved in reclaiming abandoned croplands and thus in increasing agricultural production in this globally important agricultural region.