European forests provide essential ecosystem services, with current policies focused on four key demands: carbon sequestration, timber provision, bioenergy use, and biodiversity conservation. These policies pursue multiple objectives simultaneously, creating conflicts over forest resources and services that intensify as climate change reduces forests' capacity to deliver multiple services. We synthesize here scientific evidence for these conflicting demands, their interactions and impacts on forests, revealing that current policy frameworks inadequately address fundamental trade-offs between them. Climate change impacts have begun to seriously challenge mitigation targets through negative impacts on the European forest carbon sink. Material substitution benefits face uncertainties in scale and timing as other sectors decarbonize. Bioenergy use conflicts with higher-value applications and biodiversity conservation, while existing policy frameworks inadequately enforce cascade use principles. Climate adaptation towards mixed forests faces implementation barriers including industry infrastructure optimized for softwood, fragmented ownership structures complicating coordination, and local management constraints. While innovative approaches such as Climate-Smart Forestry and landscape-scale triad zoning show potential for integrating multiple demands, they require substantial policy support and institutional capacity. Our review shows that neither technical improvements nor current policies can resolve these fundamental resource conflicts. Sustainable European forest management in the twenty-first century requires enhanced adaptation efforts alongside demand-side management to avoid overexploitation of European forests and environmental impact displacement that could undermine intended policy benefits globally.

Globalisation in the food system has led to interdependencies between countries for food security and has distributed the environmental impacts of the food consumption. In the UK, food imports account for nearly half of domestic consumption. However, there has been limited research quantifying the UK's current global land use footprint, and no previous work has explored how this might evolve under future scenarios. We provide an update on the historical land footprint of UK food and feed imports from 2010 to 2020 and produce spatially explicit estimates of the land footprint from 2020 to 2100. Food and feed demand, agricultural production and trade are simulated using a food system model under four global socioeconomic and climate scenarios. Using biophysical accounting, we estimate that 11 Mha of agricultural land is currently linked to UK food and feed imports. Across all scenarios, we estimate that the global land footprint of UK food and feed imports will reach 10-12 Mha of agricultural land by 2050 and 10-16 Mha by 2100. With 17 Mha of UK land currently used for agriculture, the land footprint of food and feed imports should be an important focus when evaluating the environmental consequences of UK food consumption.

Abstract. Land systems are increasingly influenced not only by land-use change but also by land management intensity. However, there limitations exist in data and in systematic understanding of management intensity and how it is shaped by socioeconomic, biophysical and human behaviour. We develop a global dataset of land management intensity for 2020 at 0.01 ° spatial resolution, distinguishing unmanaged, very extensive, extensive, and intensive management across cropland, pasture, and forest systems. Intensive management occupies about 22 % of global managed land, while extensive and very extensive management dominate (78 %). Intensive cropland management accounts for around 44 % of cropland area, but intensive pasture is limited to 10 % of pasture area, and intensive forest systems to only 5 % of forest area, revealing distinct sectoral contrasts. Management intensity is highly heterogeneous, with intensive cropland concentrated in North America, Europe, and South and East Asia, while extensive management dominates in Africa and Latin America. Five countries account for nearly half of global intensive cropland. Income, market access, population density, and aridity influences cropland management intensity, whereas pastures and forests show more complex relationships. Comparison with global land decision-making types shows spatial consistency (68 %), suggesting that land management intensity is influenced by land-user behaviour.

Nature-based solutions (NbS) can considerably reduce risks arising from weather extremes for society, and in addition provide multiple societal and environmental co-benefits. NbS are typically designed by the public sector, but the private sector, such as the financial sector, could also contribute to the finances needed to enable NbS uptake. However, a barrier to these investments and NbS implementation is the challenge to quantify NbS co-benefits. Through a systematic literature review, we investigate the methods available for evaluating co-benefits of NbS, beyond risk reduction. We examine their strengths and weaknesses in order to assess their applicability in the broader context of nature-based insurance and investment solutions. The review identified several (economic and non-economic) methods available that can provide a (semi-)quantitative assessment of co-benefits, with different levels of overall effort and knowledge requirements. The study showed there is no single method that is widely used to assess a specific co-benefit or NbS. Critical aspects of NbS co-benefits assessment arise from the temporal and spatial scales covered, and data availability. Previous work has been predominantly context-specific and applied to specific cases, but in principle the methods applied are replicable and scalable to different contexts. Most of the methods showed the possibility of identifying multiple co-benefits and dealing with possible disbenefits. A key limitation identified in the reviewed papers is the lack of consideration of impacts of future climate change on the NbS. We discuss challenges and advantages of the applied methods to facilitate the integration of a more comprehensive assessment of NbS co-benefits in a broader context that could help to overcome some issues and strengthen a robust evidence base for NbS performance.

Abstract We present a spatially explicit, global-scale index to assess the effects of the five direct anthropogenic drivers of biodiversity loss identified by the IPBES: land use change, natural resource extraction, climate change, pollution, and invasive alien species. The Biodiversity Pressure Index (BPI) covers 30 years (1990-2020) with an annual time-step and a spatial resolution of 0.1°. We find that the coverage of drivers in available data varies and we highlight the key uncertainties that result from this. Using the best available data, we show that large parts of the terrestrial biosphere (approximately 89%, including Antarctica and Greenland) are under medium or high human pressure and that almost all areas (approximately 96%) have experienced an increase in pressure over the past three decades. The BPI shows varied spatial and temporal patterns across world regions and biomes, but many of these areas are dominated by pressures associated with rising temperatures and trade flows. Tropical and subtropical areas are subject to particularly rapidly-growing pressures, while wetlands consistently show the highest pressure levels across biomes. In revealing these and other patterns, the BPI provides a basis for improved understanding and management of biodiversity impacts in the future.

Climate change mitigation scenarios often include a substantial bioenergy component, raising concerns about the land use impacts of large-scale energy crop production. However, agrivoltaic systems have the potential to generate electricity with a higher land use efficiency than bioenergy by integrating photovoltaic panels into agricultural land. Here, we model the global land system to explore the land use impacts of energy crops, agrivoltaics, and photovoltaics under a 1.5 °C climate change mitigation scenario. Bioenergy demand in the bioenergy scenario increases almost six-fold from 2020 to 2060. Replacing all bioenergy with agrivoltaics requires 30 times less land, leading to 106 Mha more natural land cover, 52 Mt. less nitrogen fertiliser applied, and 305 km3 less irrigation water withdrawn per year by 2060. Similar but smaller reductions in land use are achieved with standard photovoltaic systems. Our findings suggest that future net cropland expansion can be avoided by prioritising agrivoltaic and photovoltaic systems over bioenergy. Policies that incentivise the adoption of agrivoltaics could increase global land use efficiency, reducing the trade-offs between energy supply, food production, and nature protection.

Achieving national climate targets while balancing land-use and biodiversity goals is a shared challenge for countries undergoing large-scale solar energy transitions. Strategic deployment of photovoltaic (PV) systems is essential to maximise energy output while minimising land use. This study explores strategies for land-efficient PV deployment by assessing the technical PV potential of ground mounted systems under varying land-use restrictions and PV technology scenarios. Using Germany as a case study, we integrated high-resolution climate data, PV potential modelling, and land suitability assessment across three levels of land-restriction (least, intermediate, most) and three PV technology efficiency levels (low, medium, high) to evaluate how land suitability and technology choices affect energy outcomes. Our results show that deploying high efficiency PV systems can more than double electricity generation from the same land area. Prioritising the most suitable land could produce up to 759 TWh of energy, whereas stricter land-use restrictions could limit this potential to just 97 TWh. We find that energy targets can be met using <1% of Germany’s land area, without compromising protected areas or biodiversity objectives, provided PV deployment is targeted to optimal sites and paired with advanced technologies. By aligning PV deployment with high-suitability land and advanced technologies, countries can reduce land demand and environmental trade-offs. This study proposes a scalable pathway to strengthen the renewable energy transition while supporting sustainable outcomes – making it relevant beyond Germany for global land-energy planning.

The Kunming-Montreal Global Biodiversity Framework calls for restoring at least 30% of degraded ecosystems by 2030, while the IPCC and IPBES emphasize restoration as central to addressing climate change and biodiversity loss. Rewilding, defined as the promotion of self-sustaining, complex ecosystems through minimal human intervention, has emerged as a prominent restoration strategy, yet its climate change mitigation potential is often underexplored. Here, we propose a climate-smart rewilding framework that explicitly integrates biodiversity recovery with climate mitigation, climate adaptation, and socio-economic considerations. Using Europe as a case study, we map potential synergies and trade-offs among carbon sequestration, ecosystem resilience to climate change, wildlife-based tourism opportunities, and the risk of livestock predator conflict. We argue that this integrative framework provides a practical basis for identifying and assessing restoration strategies that deliver multiple benefits across regional and continental scales.

The loss of biodiversity from human activities on land is a widely-recognized, worldwide problem. Since the advent of the industrial revolution the loss of plant and animal species has increased dramatically, with 25% of species now at risk of extinction. Conventions and targets to protect biodiversity have been implemented, but with limited success. The Aichi targets for 2020, for example, were almost all missed, with worsening trends for 12 out of the 20 targets. One reason for this failure is the ineffective application of broad-scale measures that are not tailored to the underlying causes of biodiversity loss. Knowledge on the spatial and temporal distribution of anthropogenic drivers of biodiversity loss would therefore enable targeted interventions that address location-specific stressors and thus would be better-adapted measures to protect biodiversity. The Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) has identified five main drivers of anthropogenic origin as the causes of biodiversity loss: land use, natural resource extraction, climate change, pollution, and invasive alien species. However, when seeking to quantify impacts on biodiversity, these drivers are still usually treated separately. We develop a Biodiversity Pressure Index (BPI) by quantifying and mapping data for nine indicators of the five drivers into a single, annually changing index with a spatial resolution of 0.1° at global scale covering the period 1990-2020. We find that large areas (approximately 86%, including Antarctica, Greenland) are under major human pressure and that almost all areas have experienced an increase (about 96% of land) in pressure over the past thirty years. Industrialised regions had high pressure levels already in 1990 and continue to do so in 2020, whereas regions with rapid economic growth setting in after 2000 where low in pressure in 1990, but show high pressure levels today. Whilst areas impacted by human activities are increasing, areas of wilderness are decreasing to a point that in 2020, only 0.02% of the terrestrial land are entirely free from human influence. (Sub-) tropical wetlands and temperate grasslands are the biomes with the highest pressures today. And whilst land use is still one of the main factors, climate change - especially increasing temperature - is one of the major recent and future threats to biodiversity.

The assessment of forest-based climate change mitigation strategies relies on computationally intensive scenario analyses, particularly when dynamic vegetation models are coupled with socioeconomic models in multi-model frameworks. In this study, we developed surrogate models for the LPJ-GUESS dynamic global vegetation model to accelerate the prediction of carbon stocks and fluxes, enabling quicker scenario optimization within a multi-model coupling framework. We trained two machine learning methods: random forest and neural network. We assessed and compared the emulators using performance metrics and Shapley-based explanations. Our emulation approach accurately captured global and biome-specific forest carbon dynamics, closely replicating the outputs of LPJ-GUESS for both historical (1850–2014) and future (2015–2100) periods under various climate scenarios. Among the two trained emulators, the neural network extrapolated better at the end of the century for carbon stocks and fluxes and provided more physically consistent predictions, as verified by Shapley values. Overall, the emulators reduced the simulation execution time by 95 %, bridging the gap between complex process-based models and the need for scalable and fast simulations. This offers a valuable tool for scenario analysis in the context of climate change mitigation, forest management, and policy development.

The UN Decade on Ecosystem Restoration and the Kunming-Montreal Global Biodiversity Framework aim to restore 30% of degraded ecosystems. Both the IPCC and IPBES highlight the crucial role of ecosystem restoration in addressing the interconnected crises of climate change and biodiversity loss. One key restoration strategy is rewilding, which enhances ecosystem complexity with minimal human intervention. While traditional rewilding strategies often focus on benefits for biodiversity, we propose a climate-smart rewilding framework as a new approach designed to deliver climate benefits alongside biodiversity restoration. This framework seeks to integrate biodiversity, climate change adaptation and mitigation, as well as socio-economic benefits and trade-offs. We illustrate how this framework can be utilized to identify areas across Europe where rewilding could increase carbon sequestration, enhance species' abilities to adapt to the velocity of climate change, and maximize wildlife-watching benefits while minimizing the costs associated with livestock-wildlife conflict. Finally, we acknowledge some limitations of climate-smart rewilding, but we argue that its adaptability and low cost render it a promising solution to the challenges facing Europe and beyond ### Competing Interest Statement The authors have declared no competing interest.

Carbon dioxide removal (CDR) is an emerging frontier in climate change litigation1. CDR must play an important role in achieving global climate targets, by compensating for hard-to-abate emissions (such as from international transport). Yet, over-reliance on CDR in government and corporate decarbonisation plans may serve as a strategy to commit to climate action on paper, whilst making inadequate present-day emissions’ reductions. Therefore, litigation may be necessary to highlight where CDR commitments contribute to a credible decarbonisation plan, and where they are primarily employed as a delaying tactic. Hence, litigation arguing that a given level of CDR deployment represents an unacceptable risk to the achievement of legal climate targets must have clarity around plausible levels of real-world delivery. Land-based CDR methods, such as afforestation and bioenergy with carbon capture and storage, frequently appear in both modelled decarbonisation scenarios and government policies. Here, we argue that quantitative assessment of the feasible potential of land-based CDR is vital to the success of CDR-focused litigation. Firstly, we highlight key land system processes that will constrain real-world CDR delivery to levels well-below the techno-economic assessments presented in the IPCC 6th Assessment Report (AR6). These constraining processes include land tenure and food insecurity, monitoring and verification, and impermanence due to biophysical disturbances and policy change. Quantifying the likely impact of such factors can fast-track successful CDR litigation by demonstrating the scale of the gap between CDR pledges and plausible real-world potentials. Further, after Perkins et al., 2, we outline research frameworks that can deliver a quantified feasible potential for land-based CDR within the IPCC AR7 process, and highlight emerging trans-disciplinary methods making progress towards this goal. These methods include geospatial coupled socio-ecological model ensembles, which can capture interactions and feedbacks between socio-economic and biophysical drivers in the land system at global scale. Typically, such ensembles include coupling of spatial agent-based models of land user behaviour with dynamic global vegetation models and non-equilibrium agricultural trade models - which can represent system shocks such as geopolitical instability and extreme weather events. We conclude by arguing that quantitative feasibility assessment must be made a high priority in CDR research to prevent widespread over-reliance on CDR in decarbonisation policies. 1. Stuart-Smith, R.F., Rajamani, L., Rogelj, J., and Wetzer, T. (2023). Legal limits to the use of CO2 removal. Science 382, 772–774. 10.1126/science.adi9332. 2. Perkins, O., Alexander, P., Arneth, A., Brown, C., Millington, J.D.A., and Rounsevell, M. (2023). Toward quantification of the feasible potential of land-based carbon dioxide removal. One Earth 6, 1638–1651. 10.1016/j.oneear.2023.11.011.

Animal herbivory can have large and diverse impacts on vegetation and hence on the state and function of ecosystems. Despite this, quantitative understanding of vegetation responses to consumption of green leaf tissue by herbivores is currently lacking. The large-scale impacts of changes in herbivore abundance on ecosystem function have yet to be investigated. Process-based modelling can help to quantify how animals affect important processes, such as ecosystem carbon cycling. To do so, we linked the dynamic global vegetation model LPJ-GUESS with Madingley, a model of multi-trophic functional diversity. This implementation allows us to simulate feedbacks between the availability of green vegetation biomass, herbivory and the whole trophic chain in response to monthly consumption of leaf biomass. In the coupled model system, we see an overall reduction in ecosystem productivity (NPP −5.2 %), leaf area index (−9.0 %) and carbon mass (−9.7 %), compared to the stand-alone version of LPJ-GUESS, with the highest impact on carbon mass in the boreal ecosystems (−42 %). We observe ecosystem composition to shift from boreal coniferous forests (without animals) to boreal mixed forests (with animals), as well as a general increase in herbaceous vegetation. Indirect effects like an increased light transfer facilitating growth of lower canopy layers are also captured by the model system. Overall, the results of this study underpin the important role of animals in ecosystem functioning and highlight the important contribution of process-based modelling towards a better understanding of complex food web interconnections.

Forests play a crucial role in Europe's strategy for achieving carbon neutrality. Carbon turnover time - the time that carbon spends in the ecosystem - is a fundamental component in determining forest potential to mitigate climate change. However, there is a significant knowledge gap regarding how current and future forest management practices will affect carbon turnover time. This study aims to compare the effects of various forest management strategies on carbon turnover time in European forests. To achieve this, we used the dynamic global vegetation model LPJ-GUESS to simulate carbon pools and fluxes under stylised forest management scenarios mainly based on changing species composition. We calculated carbon turnover times under two conditions: first, with constant climate and CO2 concentration to assess the isolated impact of forest management; second, under a climate change scenario (SSP3-RCP7.0) to evaluate the combined effects of forest management and climate change. Our results indicate that unmanaged forests and the transition to broadleaved deciduous forests have a similar ecosystem carbon turnover time, which is the longest among all the management options across all the European climatic zones. Climate change decreases ecosystem carbon turnover time in any forest management, in a similar way, especially in cold climates. This study is the first step to include forest management when modelling carbon turnover time and indicates how the shift towards broadleaved forests, which is seen as an important climate-change adaptation strategy in many European regions, can also provide co-benefits for climate-change mitigation.

Land-cover change (LCC) is an important driver of climate change through carbon emissions (biochemical effects), but also through changes in the surface energy balance (biophysical effects). Quantifying magnitude and sign of surface temperature responses to biophysical effects is still challenging and under debate. We develop a new semi-empirical model based on a linearized surface energy balance for biophysical and an empirical model for the biochemical responses to LCC. Neglecting indirect effects, we find average global direct biophysical and biochemical warmings in response to a stylized deforestation scenario (1.22 K and 0.50 K) and historical LCC (0.42 K and 0.15 K), whereas an afforestation experiment leads to cooling (-1.95 K and -0.96 K). Our results underline the non-negligible impact of biophysical effects, especially non-radiative effects, and stress the importance of including these in the assessment of climate change mitigation and adaptation policies.

National greenhouse gas inventories (NGHGIs) and Biennial Transparency Reports (BTRs) on emissions and removals are crucial elements of the Paris Agreement and its Global Stocktake. However, NGHGIs are subject to significant uncertainties, owing to uncertain emission factors and/or insufficient activity data, thus there is a need for their independent verification. One method to do this is through atmospheric inversions, which use atmospheric observations in a statistical optimization framework to estimate surface-to-atmosphere fluxes. This method of verification is referred to in the 2006 IPCC Guidelines on national reporting and in their 2019 refinement. However, atmospheric inversions have been hitherto considered too complex and inaccurate at national scales to be widely used for this purpose. EYE-CLIMA is a Horizon Europe project that aims to develop the atmospheric inversion methodology to a level of readiness where it can be used to support the verification of NGHGIs. The overarching goals are to: i) develop a best practice in atmospheric inverse modelling for estimating emissions at national scale, including a full assessment of the uncertainties, ii) develop the methodology on how to prepare sectorial emission estimates from atmospheric inversions and make these comparable to what is reported in NGHGIs, iii) work together with NGHGI agencies on projects piloting the EYE-CLIMA methodology of emissions verification and iv) develop international best practices for the quality control of NGHGIs. EYE-CLIMA covers CH4, N2O, 5 HFC species, SF6, and the black carbon (BC) aerosol. This presentation will focus on the set-up of the EYE-CLIMA project and provide an overview of the first results in support of NGHGI verification.

Nitrogen (N) transformation processes by soil microbes account for significant nitrous oxide (N2O) emissions from natural ecosystems and cropland. However, understanding and quantifying global soil N2O emissions and their responses to changing environmental conditions remain challenging. Here, we implemented a soil nitrification–denitrification module into the dynamic vegetation model LPJ-GUESS to estimate N2O emissions from global lands. The performance of this new development is examined using observed N2O fluxes from natural-soil and cropland field trials and independent global-scale estimates. LPJ-GUESS broadly reproduces the cumulative N2O emissions under different climate conditions and N fertilizer applications that are observed in the field experiments, with some deviations in emission seasonality. Globally, simulated soil N2O emissions from terrestrial ecosystems increase from 5.6±0.2 Tg N yr−1 in the 1960s to 9.9±0.3 Tg N yr−1 in the 2010s, with croplands contributing about two-thirds of the total increase. East Asia and South Asia show the fastest growth rates in N2O emissions over the study period due to the expansion of fertilized croplands. On a global scale, N fertilization (including synthetic fertilizer and manure use), atmospheric N deposition, and climate change contribute 58 %, 46 %, and 24 %, respectively, to the simulated soil N2O emissions in the 2010s. Rising CO2 levels in the atmosphere reduce the simulated emissions by 32 % through increased plant N uptake, whereas land use changes have varied spatial effects on emissions depending on N management intensity after land cover conversion. Our estimates only account for the direct soil N2O emissions, excluding those from fertilized pastures. This study highlights the importance of environmental factors in influencing global soil N2O emissions, particularly for assessing greenhouse gas mitigation potential in agricultural ecosystems.

Global wood harvests have steadily increased over the last several decades and are projected to continue growing to match demand for wood products. How forest managers respond to changes in wood demand depends not just on timber prices and production costs but also on competition with other land uses, changes in forest productivity, and land use policies. Wood demand projections are sensitive to assumptions about socioeconomic development, including population growth, economic growth, and policy changes. Using a spatially detailed, process-based land use model (LandSyMM), we simulate global wood demand, harvests, and forest management intensity under a range of future socioeconomic (Shared Socioeconomic Pathways; SSPs) and climate (Representative Concentration Pathways; RCPs) scenarios. Wood demand is projected for each country using a price-elastic demand system that models changes in demand for industrial roundwood and wood fuel in response to changes in countries' incomes and endogenously modelled wood prices. Competition for land between forestry and agriculture, including for food and animal feed, is explicitly represented. We find that future wood harvests and forest management intensity vary considerably between scenarios. Different regions show heterogeneous responses to changes in wood demand, with global demand increasing between 27% (SSP1-RCP2.6) and 102% (SSP3-RCP7.0) by 2100. The results suggest that additional wood harvests will primarily be met through intensification of forest management and an increase in potential yields arising from climate change and CO2 fertilisation. However, interactions between extreme events, nutrient limitations, and CO2-driven productivity gains remain uncertain and are not fully captured in the modelled results. Understanding how global forest management will change and its impact on forest structure, species composition, and carbon storage is critical in addressing climate change mitigation and biodiversity protection.

Responding to the twin challenges of climate change and biodiversity loss is critical but so is avoiding any unintended consequences of these responses for other sustainability goals such as food security. Here, we explore synergies and trade-offs across the biodiversity-climate-food nexus through the recently developed Green Shoots framework. This approach highlights how different response options (dietary change, sustainable food production and fisheries, afforestation/reforestation, and bioenergy) can have multiple co-benefits, although some can also pose risks to biodiversity, climate change, or food security. Integrated responses are needed, but ultimately, success depends on how effectively they are implemented, and not on the type of response option per se. Society is at a critical juncture for the sustainability of most natural and food systems with today’s choices affecting tomorrow’s outcomes, and the Green Shoots provide an approach to inform these choices.