Background: Soil erosion is still identified as the main cause of land degradation worldwide, threatening soil functions and driving several research and policy efforts to reverse it. Trees are commonly associated to some of the most successful land-use systems to achieve soil protection goals, but the extent to which forest ecosystems reduce erosion risks can largely depend on management decisions and associated silvicultural practices. Optimization tools can assist foresters in solving the complex planning problem they face, concerning the demand for different, and often conflicting, ecosystem services. A resource capability model (RCM), based on a linear programming approach, was built and solved for a forest landscape management problem in Northwest Portugal, over a 90-years planning horizon, divided in 10-years periods. Results: Timber provision and soil erosion were found to be in trade-off. The management alternatives included in the model were proven to be sufficiently flexible to obtain the desired level of timber yield, both in volume and even distribution along the planning horizon, while ensuring lower levels of soil loss estimates (below 35 Mg∙ha^− 1∙year^− 1). However, under climate change conditions, compatible with an increasing greenhouse gases emission scenario, potential landscape soil erosion may be enhanced up to 46 Mg∙ha^− 1∙year^− 1 in critical periods. Conclusions: Soil conservation concerns in landscape-level forest management planning can be addressed by LP-based optimization methods. Besides providing an optimal management solution at landscape level, this approach enables a comprehensive analysis of the RCM, possible trade-offs and potential changes towards uncertainties.

Background: Climate change may strongly influence soil erosion risk, namely through variations in the precipitation pattern. Forests may contribute to mitigate the impacts of climate change on soil erosion and forest managers are thus challenged by the need to define strategies that may protect the soil while addressing the demand for other ecosystem services. Our emphasis is on the development of an approach to assess the impact of silvicultural practices and forest management models on soil erosion risks under climate change. Specifically, we consider the annual variation of the cover-management factor (C) in the Revised Universal Soil Loss Equation over a range of alternative forest management models to estimate the corresponding annual soil losses, under both current and changing climate conditions. We report and discuss results of an application of this approach to a forest area in Northwestern Portugal where erosion control is the most relevant water-related ecosystem service.Results: Local climate change scenarios will contribute to water erosion processes, mostly by rainfall erosivity increase. Different forest management models provide varying levels of soil protection by trees, resulting in distinct soil loss potential.Conclusions: Results confirm the suitability of the proposed approach to address soil erosion concerns in forest management planning. This approach may help foresters assess management models and the corresponding silvicultural practices according to the water-related services they provide.

Sustainable forest management needs to address biodiversity conservation concerns. For that purpose, forest managers need models and indicators that may help evaluate the impact of management options on biodiversity under the uncertainty of climate change scenarios. In this research we explore the potential for designing mosaics of stand-level forest management models to address biodiversity conservation objectives on a broader landscape-level. Our approach integrates (i) an effective stand-level biodiversity indicator that reflect tree species composition, stand age, and understory coverage under divergent climate conditions; and (ii) linear programming optimization techniques to guide forest actors in seeing optimal forest practices to safeguard future biodiversity. Emphasis is on the efficiency and effectiveness of an approach to help assess the impact of forest management planning on biodiversity under scenarios of climate change. Results from a resource capability model are discussed for an application to a large-scale problem encompassing 14,765 ha, extending over a 90-years planning horizon and considering two local-climate scenarios. They highlight the potential of the approach to help assess the impact of both stand and landscape-level forest management models on biodiversity conservation goals. They demonstrate further that the approach provides insights about how climate change, timber demand and wildfire resistance may impact plans that target the optimization of biodiversity values. The set of optimized long-term solutions emphasizes a multifunctional forest that guarantees a desirable local level of biodiversity and resilience to wildfires, while providing a balanced production of wood over time at the landscape scale.

Vast montado areas are threatened by degradation, as the result of a long history of land use changes. Since improved pastures have been installed aiming soil quality improvement and system sustainability, it is crucial to evaluate the effects of these management changes on soil organic matter status and soil biological activity, as soil quality indicators. Therefore, a 35-yr old improved pasture and a natural pasture were studied, considering areas beneath tree canopy and in the open. Total organic C, total N, hot water soluble (HWS) and particulate (POM) C, microbial biomass C (MBC) and N (MBN), C mineralization rate (CMR) and net N mineralization rate (NMR) were determined. In addition, for a 1-yr period, soil β-glucosidase, urease, proteases and acid phosphomonoesterase were periodically determined. Improved pasture promoted the increase of soil C and N through POM-C increment, particularly beneath the trees canopies. The two study pastures did not show differences regarding soil microbial biomass, but variations in CMR, HWS-C and N availability (proteases and urease activities) suggest divergent soil microbial communities. Tree regulator role on C, N and P transformation processes in soil was confirmed.