Background: Agricultural production is highly susceptible to weather-related uncertainties, which are expected to increase due to climate change. While most studies address production risks, market risks are often overlooked despite their growing impact on farm income. Crop diversification is a strategy to reduce both production and market risks. Objectives: This study investigates how temporal and spatial diversification strategies influence farm incomes and risk exposure across different arable farm types in Eastern Germany. Methods: A stochastic bio-economic farm model (MODAM) was implemented to optimize decision-making. The farm model integrates yield variability from a crop growth model and market volatility through Monte Carlo simulations of crop and fertilizer prices. Nine showcase farms were analyzed under three diversification strategies: temporal diversification, subfield division, and strip cropping, against narrow rotations with sole cropping. All diversification strategies included (among other crops) soybean cultivation. The model assessed two climate scenarios (1990-2020 and 2020-2060) and two policy environments: the CAP 2023 area payment system and a novel premium, paid based on the field perimeter, promoting smaller field units. Results: Soybean integration into cereal dominated cropping systems was limited under temporal and subfield diversification but increased with strip cropping. Expected gross margins improved under future climate conditions compared to historical conditions across all strategies. Diversification consistently reduced economic risk relative to narrow rotations and sole cropping, with subfield division and strip cropping showing the most substantial effects. Strip cropping reduced economic risk but involved higher trade-offs. Subfield division significantly reduced economic risk without sacrificing gross margins, especially under risk-averse behavioral preferences and future climate scenarios. A modest perimeter-based payment (1.5 & euro;/100 m length of field edge) replacing area-based premiums helped maintain gross margins under strip cropping while significantly reducing the conditional-Value-at-Risk. Conclusions: Spatial diversification like subfield division and strip cropping, are effective in mitigating farm income risks under climatic and market uncertainty. Policy instruments such as perimeter-based payments can enhance these effects.

Weather index insurance (WII) has been proposed as an effective risk transfer measure against extreme weather events affecting smallholder farmers in Sub-Saharan Africa. Despite the potential of this insurance type to stabilize farm income under extreme weather conditions, subscription rates by farmers have been very low. One of the reasons for the low subscription is basis risk, which relates to mismatches between payouts and losses, leading to misunderstanding and distrust on the part of farmers. Using an integrated bio-economic modelling approach for Northern Ghana, we quantify basis risk arising from three misalignments: spatial mismatch in rainfall inputs, temporal mismatch due to heterogeneity in planting dates, and biophysical mismatch linked to soil water-holding capacity (proxied by soil depth). Spatial basis risk was assessed by adjusting the daily precipitation data decreasing the values by up to the 10th percentile and increasing them up to the 90th percentile compared to the reference. For temporal basis risk planting dates were varied by delaying them by 7 to 21 days and increasing them by 14 days. To assess the sensitivity of index performance to soil variability, reference soil depths were increased and decreased by 30 cm. We evaluate insurance performance on maize crops using household outcomes (gross margin and assets). Results show that misalignment can substantially weaken risk protection, with the largest effects in product basis risk where soil water storage differs from insurance contract reference assumptions. Consistent with prior work, our results reinforce that WII contracts should align with local agronomic and environmental conditions; we add incremental evidence by quantifying how residual misalignment, especially soil-depth heterogeneity and planting-date shifts can weaken protection in shock years.

Halting biodiversity loss on semi-natural grassland has become a key priority of agri-environmental policies in Estonia. However, to what extent current schemes are sufficient to achieve biodiversity targets and the role of landscape factors is still insufficiently understood in this context. This study explored trade-offs between profitability and biodiversity conservation across heterogeneous Estonian agricultural landscapes to support the development of economically effective grassland conservation schemes. To this end, we selected twelve ‘landscape windows’ in a grassland-rich region that represent a gradient of several biodiversity-related landscape factors (semi-natural grassland share, yield potential and landscape complexity). Profitability was assessed using total gross margins derived from a bio-economic model, while biodiversity was evaluated through habitat values for different bird species, based on model outputs. We found that landscapes with higher complexity, which currently maintain higher biodiversity levels, had a corresponding lower farm profitability. In particular, landscape windows dominated by semi-natural grasslands with low grass yields showed the lowest profitability, largely due to limited capacity for feeding beef cattle. In contrast, arable land-dominated landscapes (i.e. those with higher yield potential) demonstrated considerable potential for enhancing biodiversity outcomes while minimising profitability losses. Therefore, conservation policy faces two main challenges: 1. preserving landscapes with high biodiversity value against further decline in profitability, 2. highlighting the need to explore and design biodiversity measures in arable-dominated landscapes that could improve biodiversity outcomes while limiting impacts on farm profitability. This study illustrates that landscape factors deserve greater attention in conservation planning.

This study develops a six-objective optimization framework for crop and irrigation allocation in the Gorganroud watershed, Iran, to support agricultural water management under contrasting development priorities. The model maximizes profit and agricultural employment, minimizes carbon footprint, minimizes the blue and grey shares of total water footprint, and maximizes the green share. Scenario-specific objective weights are derived from Shared Socioeconomic Pathways (SSPs), allowing alternative socioeconomic priorities to be translated into quantitative land- and water-allocation decisions. A profit-maximizing baseline is also solved for comparison. The optimization is subject to land availability, renewable groundwater and surface-water limits, nitrogen-loss ceilings, soil-degradation limits, crop-diversity requirements, minimum wheat production, minimum profit, and restrictions on irrigated-area expansion. Across SSP scenarios, the optimized solutions reduce carbon footprint, grey water footprint, surface-water use, and total water use relative to the constrained profit-maximizing baseline, while increasing agricultural employment. Compared with the current system, the framework also reduces groundwater abstraction and keeps groundwater use within renewable limits, indicating a shift from structurally unsustainable exploitation toward hydrologically feasible allocation. The results show that SSPbased weighting produces systematic reallocation of crop areas and irrigation strategies, with moderate profit trade-offs but clear gains in water sustainability and environmental performance. Overall, the framework provides a policy-relevant decision-support approach for comparing crop-water allocation trade-offs in water-scarce agricultural regions, although application to other basins would require local recalibration of datasets, constraints, and policy priorities.

CONTEXTThe use of feed concentrates in dairy production results in high feed costs and considerable environmental impacts, particularly through land-use change and nutrient imports. Alfalfa cultivated on farm offers a viable forage alternative, provided its quality is maintained through appropriate cutting frequency and timing. OBJECTIVE This study analyses the economic effects of alfalfa-based feeding strategies on an average Brandenburg dairy farm using the bio-economic farm optimisation model FarmDyn. METHODS Three scenarios were compared: a baseline without alfalfa (BL), common-practice alfalfa (CPA), and high-quality alfalfa (HQA), which all differed in harvest timing and resulting feed value. Following this comparison, a global sensitivity analysis was conducted to test the robustness of the model results.RESULTS AND CONCLUSIONSSimulation results showed that HQA reduced feed concentrate costs and increased farm-level profit by 24%. However, on-farm production of high-quality forage involves a trade-off: the extra cuts raise labour demand and intensify summer labour demand. The sensitivity analysis identified alfalfa quality as the most influential factor affecting feed costs. Quality improvements directly enhance the feed concentrate substitution and drive the economic viability of alfalfa integration. Achieving and maintaining high forage quality, however, requires consistent management and prioritisation of harvest operations. The results highlight a critical trade-off between yield and quality as well as labour, that must be addressed to realize the potential of alfalfa as a cost-efficient forage crop. SIGNIFICANCE This study demonstrates that prioritising harvest timing to secure high-quality alfalfa can substantially reduce reliance on purchased feed concentrates and improve farm-level profitability on Brandenburg dairy farms.

Biodiversity conservation schemes in collaboration with agriculture have been criticized in part for their limited ecological effectiveness. In this regard, biosphere reserves are internationally recognized as playing a model role in developing sustainable land use systems. To learn about farmers’ perspectives on insects, the role of biosphere reserves in their farm management, and their experiences with biodiversity measures, we interviewed farmers in the German biosphere reserves (BRs) Schaalsee, Schorfheide-Chorin, Middle Elbe, Bavarian Rhön and Black Forest, thereby drawing on the model function of these reserves for insect conservation. Their perceptions were then assessed by BR staff and insect conservation managers. Juxtaposing the views of farmers and insect conservation stakeholders provides comparative insights from multiple perspectives. Interviewed farmers perceived BR staff as holding substantial regional knowledge, which gives them a reputation as competent intermediaries between biodiversity conservation and agriculture. Although the economic incentives to change farm management are perceived as low, most farmers can be engaged in biodiversity conservation through their intrinsic motivations. Farmers were clustered into four motivational patterns that require targeted communication. Across motivational patterns, farmers identified administrative burdens, farm-level costs, and the limited reliability and flexibility of existing measures as major barriers. To better conserve insects and promote insect conservation measures among farmers, extension services are needed. BR staff and insect conservation managers agreed on most of the farmers’ needs identified through the interviews. Therefore, BR administrations may play a crucial role in insect conservation as they recognize the contribution of agriculture and can engage additional stakeholders beyond the sector. To establish insect conservation in BRs in the long term, regional extension staff for nature conservation and regional support schemes are most needed to provide site-specific, regionally adapted conservation measures.

Anticipating future socioeconomic conditions through scenarios supports effective land-use planning and management that safeguards biodiversity and ecosystem services (BES). This study introduces a novel participatory scenario development protocol to design consistent, nested regional scenarios tailored for BES assessments of agricultural land-use. The protocol is applied in four European case studies (subnational regions in Austria, Estonia, Germany, and Switzerland), combining regional narratives with quantitative developments aligned with the Shared Socioeconomic Pathways for European agri-food systems for 2050 (Eur-Agri-SSPs). Two innovative scenario components are introduced: (i) land-use and management practices and (ii) land-use-biodiversity actions, including private and public instruments. These components are typically neglected in larger-scale scenario applications. Despite shared European boundary conditions from the Eur-Agri-SSPs, the regional scenarios exhibit substantial variation, driven by current land-use structures and stakeholder input. Scenario elements, shaped by existing funding schemes and socioeconomic contexts, vary substantially across scenarios and regions. Examples include the share of organic farms and the level of payments for agri-environment-climate measures. In Münsterland (Germany) and Lääne County (Estonia), current agri-environment payments are significantly lower than in Schwarzbubenland (Switzerland) or the Wienerwald (Austria), and this is reflected in the SSP1 (“..sustainable paths”) and SSP2 (“..established paths”) scenarios. This study demonstrates the value of regional extensions of the SSP framework, grounded in participatory processes, to support context-specific BES assessments. It contributes to scenario research by presenting key challenges and recommendations for nested participatory scenario design and by bridging the gap between global and continental frameworks and subnational implementation needs.

Abstract The transition to Agroforestry (AF) marks a pivotal shift from traditional agricultural practices towards more integrated, sustainable, and diversified farming systems. However, this transition is complex and poses several challenges requiring the cultivation of diverse species alongside crops, demanding careful management and knowledge of forestry and agricultural practices. This study aims to identify distinct farmer categories based on their stated intentions to maintain or adopt agroforestry practices. Then, the effect of sociodemographic, structural and economic factors on the probability of maintaining or adopting AF practices has been analysed among farmers of 4 European countries. Information was gathered through an online questionnaire from a sample of 376 European farms across five countries: Germany, Italy, Greece and Serbia. A multiple correspondence analysis (MCA) has been carried out to classify farmers into ‘active’ and ‘passive’ adopters as well as into ‘conditional-non adopters’ and ‘resistant non-adopters’ categories, by taking into account four future policy scenarios for 2030. Then, the determinants of AF maintenance or adoption were estimated using a multinomial logit model (MNL). Results show that both farm and farmer characteristics affect the probability of belonging to a specific category. Moreover, differences among countries have emerged. The results highlight the need for targeted policy interventions to support farmers in transitioning towards these practices. In addition, it is essential to design such measures in a way that accounts for farms and farmers’ differences and specific socio-economic and environmental contexts. The study findings would contribute to the scientific literature by providing empirical evidence on the heterogeneity of farmers’ intention to maintain or adopt agroforestry practices across some European countries. Furthermore, the findings would offer insights for policymakers to design effective supporting mechanisms to facilitate the maintenance and the adoption of AF.

The integration of ecosystem services (ESs) valuation into agricultural policy frameworks is critical for fostering sustainable land management practices. This study leverages the redesigned version of the bio-economic farm model MODAM (Multi-Objective Decision Support Tool for Agro-Ecosystem Management) to estimate the shadow prices of ESs, enabling the derivation of demand and supply curves for nitrate leaching and soil erosion control, respectively. Two hypothetical farms in Brandenburg, Germany—a smaller, arable farm in Märkisch-Oderland and a larger, diversified farm with livestock in Oder-Spree—are analyzed to explore the heterogeneity in shadow prices and corresponding cropping patterns. The results reveal that larger farms exhibit greater elasticity in response to green taxes on nitrate use and lower costs for supplying erosion control compared to smaller farms. This study highlights the utility of shadow prices as proxies for setting green taxes and payments for ecosystem services (PESs), while emphasizing the need for differentiated policy designs to address disparities between farm types. This research underscores the potential of model-based ESs valuation to provide robust economic measures for policy design, fostering sustainable agricultural practices and ecosystem conservation.

Coherent spatial data are crucial for informed land use and regional planning decisions, particularly in the context of securing a crisis-proof food supply and adapting to climate change. This dataset provides spatial information on climate-robust and high-yield agricultural arable land in Brandenburg, Germany, based on the results of a classification using bio-economic climate simulations. The dataset is intended to support regional planning and policy makers in zoning decisions (e.g., photovoltaic power plants) by identifying climate-robust arable land with high current and stable future production potential that should be reserved for agricultural use. The classification method used to generate the dataset includes a wide range of indicators, including established approaches, such as a soil quality index, drought, water, and wind erosion risk, as well as a dynamic approach, using bio-economic simulations, which determine the production potential under future climate scenarios. The dataset is a valuable resource for spatial planning and climate change adaptation, contributing to long-term food security especially in dry areas such as the state of Brandenburg facing increased production risk under future climatic conditions, thereby serving globally as an example for land use planning challenges related to climate change.

Semi-natural grasslands (SNGLs) in Estonia are threatened by abandonment. This threat is leading to concerns about the degradation of biodiversity within grassland communities. Despite the high relevance of economic incentives in this context, how such incentives influence land managers’ decision-making regarding the agricultural use of SNGLs has not been investigated. To obtain its socio-ecological implications for policy-making, we developed regionally specific agricultural scenarios (compensation payments, livestock capacity, hey export, and bioenergy production) and an interdisciplinary modelling approach that made it possible to simulate agricultural land use changes through land managers' responses to varied economic conditions. Through this approach, we found that some economic factors hampered the use of SNGLs: the moderate profitability of beef production, labour shortages, and the relatively high profitability of mulching. We observed a positive relationship between SNGLs and habitat suitability for breeding and feeding birds. However, due to the high maintenance costs of SNGLs, the modelling results indicated that increasing the use of SNGLs through public budgets caused crowding-out effects, i.e., the deteriorating market integration of regional agriculture. This study emphasises the need for policy measures aimed at cost-effective, labour-efficient management practices for SNGLs.

Ensuring a crisis-proof food supply has become a key political issue. In Germany, official spatial planning allows the use of priority and reserved areas to secure land for agricultural use and regional food supply. The focus should be particularly on climate-resilient areas that also have a stable yield potential in the future. This paper supplements widely used, static approaches for determining priority and reserved areas with a dynamic bio-economic analysis that takes future climate scenarios into account. The results for the German federal state of Brandenburg show a high area equivalence between the static and dynamic approaches. In the case of data gaps, for example, static approaches such as soil quality indices can serve as an adequate proxy for future yield potentials. However, not all climate-robust areas can be classified as potential reserved or priority areas. Furthermore, areas that show low yield potential under future conditions are not released for other land uses. Feedback from stakeholders involved in the study showed that the use of the dynamic approach and a target value using the results of a foodshed model lead to broad acceptance. The method developed here can make a valuable contribution to climate change adaptation in spatial planning instruments.

Context: Smallholder farmers in semi-arid West Africa face challenges such as weather variability, soil infertility, and inadequate market infrastructure, hindering their adoption of improved farming practices. Economic risks associated with uncertain weather, production and market conditions often result in measures such as selling assets and withdrawing children from school, resulting in long-term impoverishment. To break these poverty traps, there is a need for affordable and sustainable risk management approaches at the farm level. Proposed strategies include risk reduction through stress-resistant crop varieties and diversification, additional investments transfer options like crop insurance and contract farming. Despite experimentation with insurance products in sub-Saharan Africa, low adoption persists due to many factors including high premiums, imperfect indices, and cognitive factors. Objective: The objective of this study is to assess the probability of two different index-based insurance products to stabilize smallholder farmers' income and limit asset losses in Northern Ghana using an integrated bioeconomic modelling approach. Method: We adapted an existing integrated bio-economic model comprising a process-based crop model, farm simulation model, and annual optimization model by including insurance contracts to assess their impacts on farmers' income and assets. We collaborated with an insurance service provider in sub-Saharan Africa to design and compare two weather index-based insurance contracts-one covering seeding costs and another addressing full input costs. Additionally, we considered the impact of management adaptations, such as replanting after crop establishment failure. Results: The result from the study suggests that except for the most resource constrained, farmers would be better off purchasing seed insurance and replanting in the event of weather shocks, stabilizing their incomes and reducing the sale of their assets. These insurance options are less expensive than full weather index insurance for the resource-constrained farmers considering that extreme weather conditions do not occur regularly. Significance: This study is significant for smallholder farmers in semi-arid West Africa, who are faced with economic and environmental challenges, challenging efforts to improve livelihoods. Focusing on Northern Ghana, the research assesses the viability of two index-based insurance products using an integrated bio-economic modelling approach. By presenting the probability of outcomes for income and farm assets, particularly through seed insurance incentivizing replanting after extreme weather shocks, the study offers a cost-effective solution for resource-constrained farmers. The results suggest the potential for weather-index insurance contracts to help smallholder farmers avoid bankruptcy or fall into poverty traps, especially after shock years.

Multifunctional and diversified agriculture can address diverging pressures and demands by simultaneously enhancing productivity, biodiversity, and the provision of ecosystem services. The use of digital technologies can support this by designing and managing resource-efficient and context-specific agricultural systems. We present the Digital Agricultural Knowledge and Information System (DAKIS) to demonstrate an approach that employs digital technologies to enable decision-making towards diversified and sustainable agriculture. To develop the DAKIS, we specified, together with stakeholders, requirements for a knowledge-based decision-support tool and reviewed the literature to identify limitations in the current generation of tools. The results of the review point towards recurring challenges regarding the consideration of ecosystem services and biodiversity, the capacity to foster communication and cooperation between farmers and other actors, and the ability to link multiple spatiotemporal scales and sustainability levels. To overcome these challenges, the DAKIS provides a digital platform to support farmers' decision-making on land use and management via an integrative spatiotemporally explicit approach that analyses a wide range of data from various sources. The approach integrates remote and in situ sensors, artificial intelligence, modelling, stakeholder-stated demand for biodiversity and ecosystem services, and participatory sustainability impact assessment to address the diverse drivers affecting agricultural land use and management design, including natural and agronomic factors, economic and policy considerations, and socio-cultural preferences and settings. Ultimately, the DAKIS embeds the consideration of ecosystem services, biodiversity, and sustainability into farmers' decision-making and enables learning and progress towards site-adapted small-scale multifunctional and diversified agriculture while simultaneously supporting farmers' objectives and societal demands.

The agricultural land represents the most important form of land use, accounting for almost 48% of the European land area. Europe- Despite its relatively small share of global agriculture land total area (9.8%), has been one of the world’s largest and most productive suppliers of food and fibre. Europe accounted for 17.6% of the global cereal production during 2014–2018, and average yields in EU countries were 6.8% higher than the world average in the same period. As this chapter shows the climate change will pose substantial challenge for provisioning but also for other ecosystem services. The role of modelling in managing impacts and developing adaptation strategies is crucial as demonstrated through several examples. As the agroecosystem models are treasure troves of agronomy knowledge, their further development should be seen as on of the research priorities within the continent´s agricultural research.

Smallholder farmers in Northern Ghana face challenges due to weather variability and market volatility, hindering their ability to invest in sustainable intensification options. Modeling can help understand the relationships between productivity, environmental, and economical aspects, but few models have explored the effects of weather variability on crop management and resource allocation. This study introduces an integrated modeling approach to optimize resource allocation for smallholder mixed crop and livestock farming systems in Northern Ghana. The model combines a process-based crop model, farm simulation model, and annual optimization model. Crop model simulations are driven by a large ensemble of weather time series for two scenarios: good and bad weather. The model accounts for the effects of climate risks on farm management decisions, which can help in supporting investments in sustainable intensification practices, thereby bringing smallholder farmers out of poverty traps. The model was simulated for three different farm types represented in the region. The results suggest that farmers could increase their income by allocating more than 80% of their land to cash crops such as rice, groundnut, and soybeans. The optimized cropping patterns have an over 50% probability of increasing farm income, particularly under bad weather scenarios, compared with current cropping systems.

Diverse agricultural land uses are a typical feature of multifunctional landscapes. The uncertain change in the drivers of global land use, such as climate, market and policy technology and demography, challenges the long-term management of agricultural diversification. As these global drivers also affect smaller scales, it is important to capture the traits of regionally specific farm activities to facilitate adaptation to change. By downscaling European shared socioeconomic pathways (SSPs) for agricultural and food systems, combined with representative concentration pathways (RCP) to regionally specific, alternative socioeconomic and climate scenarios, the present study explores the major impacts of the drivers of global land use on regional agriculture by simulating farm-level decisions and identifies the socio-ecological implications for promoting diverse agricultural landscapes in 2050. A hilly orchard region in northern Switzerland was chosen as a case study to represent the multifunctional nature of Swiss agriculture. Results show that the different regionalised pathways lead to contrasting impacts on orchard meadows, production levels and biodiversity. Increased financial support for ecological measures, adequate farm labour supplies for more labour-intensive farming and consumer preferences that favour local farm produce can offset the negative impacts of climate change and commodity prices and contribute to agricultural diversification and farmland biodiversity. However, these conditions also caused a significant decline in farm production levels. This study suggests that considering a broader set of land use drivers beyond direct payments, while acknowledging potential trade-offs and diverse impacts across different farm types, is required to effectively manage and sustain diversified agricultural landscapes in the long run.

This scoping review looks at the literature published on the economic performance of temperate agroforestry systems in Europe and North America and tries to answers the following research questions: How does agroforestry (AF) perform economically compared to agriculture and/or forestry? And are there any particular system characteristics or conditions that make them more competitive? Results show that generally, AF is not able to compete with agricultural land use but there are notable exceptions. Especially improved policy conditions and internalising environmental externalities can make AF competitive. Compared to forestry AF is generally able to achieve better economic outcomes. The economic performance is, in addition to ecosystem service payments and policy support, dependent on soil and site characteristic, as well as prices and the profitability of the individual system components. Intensive management and increased knowledge of these systems also increase competitiveness. There are various research gaps such as economic risk on farm- and plot-level, economic performance of AF under future climate change, or a comparison of different sustainability enhancing measures in agriculture.

Climate-induced production risk is expected to increase in the future. This study assesses the effectiveness of adapting crop rotations on arable farms in Brandenburg as a tool to enhance climate resilience. Two risk-minimizing measures are investigated: crop diversification and the inclusion of irrigated crops. Based on state-wide simulated yield data, the study compares two different scenarios. In the first scenario, the most profitable crop rotations based on predicted future weather conditions are chosen for each agro-ecological zone. In the second scenario, cropping plans are derived based on an adaption of the Target MOTAD (Minimization of Total Absolute Deviation) model taking climate-induced risks into account. A comparison of the scenarios shows a high risk reduction effect of diversification, while the economic risk reduction effect of irrigation only increases slightly. The trade-off between the highest possible gross margins and lower possible losses varies depending on the soil and climate conditions. Diversification contributed most to economic resilience in areas with moderate to low agricultural productivity. Subsidies focusing on diversification in less productive areas might be a tool to increase economic resilience with low risk-avoidance costs.

Many studies have explored farmers' perspectives on biodiversity and ecosystem services, but fewer qualitative and cross-country comparisons exist. We develop a socio-ecological system to analyse agricultural landscape services, biodiversity, and drivers that have affected these services in recent decades. Via a systematic stake-holder mapping and 49 semi-structured interviews, we identify stakeholder perceptions of this system. We compare the perceptions across four regional case studies (Austria, Estonia, Germany, Switzerland), and two stakeholder groups (land managers and administrators). The case studies share certain commonalities in perceptions (e.g., provisioning and regulating services discussed in all of them) but also show differences (e.g., changes in biodiversity and landscape services more often perceived in the Swiss and German cases, but less in the Austrian and Estonian case studies). Across all case studies, typical land use change can be attributed to multiple drivers of various strengths, with climate change being the most often perceived driver directly affecting landscape services, followed by policies and market-based drivers, which affect services and biodiversity indirectly via land use. Compared to the administrators (e.g., decision-makers, scientists), the managers (e.g., farmers, NGOs) discuss more often the drivers, like various biodiversity and landscape service categories, as well as climate change, markets, and technologies. However, the administrators focus more on cultural services, policies as drivers, and consider more often links between drivers and landscape services and/or biodiversity. Hence, both of the groups' (administrators and managers) perceptions partly complement each other. Since policy making should be based on the best knowledge of different stakeholder groups, active knowledge exchange between managers and administrators should be supported and outcome considered in decision making. The resulting regional differences in stakeholder perceptions of the drivers and their respective impact on agricultural landscapes suggest that future agricultural policies need regional targeting and the consideration of landscape-specific characteristics.