1,720,969 research outputs found
How Much Agroforestry Is Needed to Achieve Multifunctional Landscapes at the Forest Frontier?—Coupling Expert Opinion with Robust Goal Programming
No full textAgroforestry has been promoted as a key forest landscape restoration (FLR) option to restore ecosystem services in degraded tropical landscapes. We investigated the share and type of agroforestry selected in an optimized landscape, accounting for a mosaic of alternative forest landscape restoration options (reforestation and natural succession) and forest and common agricultural land-uses. We extend previous studies on multi-objective robust optimization and the analytic hierarchy process by a systematic sensitivity analysis to assess the influence of incorporating agroforestry into a landscape. This approach accounts for multiple objectives concurrently, yet data and computational requirements are relatively low. Our results show that experts from different backgrounds perceive agroforestry (i.e., alley cropping and silvopasture) very positively. Inclusion of large shares of agroforestry (41% share of landscape) in the FLR mix enhanced simulated ecosystem service provision. Our results demonstrate that landscapes with high shares of agroforestry may also comprise of high shares of natural forest. However, landscapes dominated by single agroforestry systems showed lower landscape multifunctionality than heterogeneous landscapes. In the ongoing effort to create sustainable landscapes, our approach contributes to an understanding of interrelations between land-covers and uncertain provisions of ecosystem services in circumstances with scarce data
Exploring trade-offs in agro-ecological landscapes: Using a multi-objective land-use allocation model to support agroforestry research
No full textFinding the optimal land allocation for providing ecosystem services, conserving biodiversity and maintaining rural livelihoods is a key challenge of agricultural management and land-use planning. Agroforestry has been widely discussed as a sustainable land-use solution and as one strategy to improve the provision of multiple ecological and economic functions in agricultural landscapes. In this study, we use the backdrop of agroforestry research to evaluate a method from the multi-criteria decision analysis toolbox: robust multi-objective optimization. The key feature of this modelling approach is its capacity to integrate uncertain ecological and socio-economic data. We illustrate the optimization model with a case study from eastern Panama, showing how the model can bring together scientific and practical knowledge to provide potentially desirable landscape compositions from the perspective of farmers, a public perspective, and a compromise solution. Example results of our case study show how to assess whether agroforestry is a desirable component in a landscape composition to satisfy multiple objectives of different interest groups. Furthermore, we use the model to demonstrate how different objectives influence the optimal area share and type of agroforestry. Due to its parsimonious nature, the model could be used as a starting point of an interactive co-learning process with decision-makers, researchers and other stakeholders. The model, however, is not yet suitable for an exact prediction of future land-use dynamics, for questions of spatially explicit land-use configuration, studies going beyond the regional scale or for socio-economic interactions of agents. Therefore, we outline future research needs and recommendations for other types of models or hybrid approaches
How Integrated Ecological-Economic Modelling Can Inform Landscape Pattern in Forest Agroecosystems
No full textPurpose of Review The purpose of this review is to analyse recent advances in ecological-economic modelling designed to inform desirable landscape composition and configuration. We explore how models capture the economic and ecological consequences of landscape pattern, and potential feedbacks to the responses by policy or landholders. Recent Findings Modelling approaches are becoming increasingly interlinked, coupling components of empirical-statistical modelling, spatial and bioeconomic simulation, land-use optimization and agent-based models. We analyse recent methodological advances and find that only few examples capture feedbacks between landscape pattern and decision-making. Summary We outline how future hybrid models could build on these recent advances by inter alia an improved representation of landscape patterns, refining the theory behind decision-making, incorporating uncertainty and reducing model complexity. We conclude that coupling recent developments in land-use optimization and agent-based models may help bridge gaps between modelling philosophies as well as parsimony vs. complexity. This fruitful field of research could help to improve understanding on the role of landscape pattern in social-ecological systems
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