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Forests and their provision of ecosystem services are endangered by climate change. Tree-species diversification has been identified as a key adaptation strategy to balance economic risks and returns in forest stands. Yet, whether this synergy between ecology and economics persists under large-scale extreme weather events remains unanswered. Our model accounts for both, small-scale disturbances in individual stands and extreme weather events that cause spatio-temporally correlated disturbances in a large number of neighboring stands. It economically optimizes stand-type allocations in a large forest enterprise with multiple planning units. Novel components are: spatially explicit site heterogeneity and a comparison of economic diversification strategies under local and regionally coordinated planning by simplified measures for α , β , and γ -diversity of stand types. α -diversity refers to the number and evenness of stand types in local planning units, β -diversity to the dissimilarity of the species composition across planning units, and γ -diversity to the number and evenness of stand types in the entire enterprise. Local planning led to stand-type diversification within planning units ( α -diversity), while regionally coordinated planning led to diversification across planning units ( β -diversity). We observed a trend towards homogenization of stand-type composition likely selected under economic objectives with increasing extreme weather events. No diversification strategy fully buffered the adverse economic consequences. This led to fatalistic decisions, i.e., selecting stand types with low investment risks but also low resistance to disturbances. The resulting forest structures indicate potential adverse consequences for other ecosystem services. We conclude that high tree-species diversity may not necessarily buffer economic consequences of extreme weather events. Forest policies reducing forest owners’ investment risks are needed to establish stable forests that provide multiple ecosystem services.

High landscape diversity is assumed to increase the number and level of ecosystem services. However, the interactions between ecosystem service provision, disturbance and landscape composition are poorly understood. Here we present a novel approach to include uncertainty in the optimization of land allocation for improving the provision of multiple ecosystem services. We refer to the rehabilitation of abandoned agricultural lands in Ecuador including two types of both afforestation and pasture rehabilitation, together with a succession option. Our results show that high compositional landscape diversity supports multiple ecosystem services (multifunction effect). This implicitly provides a buffer against uncertainty. Our work shows that active integration of uncertainty is only important when optimizing single or highly correlated ecosystem services and that the multifunction effect on landscape diversity is stronger than the uncertainty effect. This is an important insight to support a land-use planning based on ecosystem services. Land use becomes more diverse when it considers uncertain interactions of multiple ecosystem services. Here, Knoke and colleagues show that uncertainty plays a larger role if ecosystem services are optimized only for a single service, or if services correlate.

Even though the site index is a popular method for describing forest productivity, its use is limited in uneven-aged multispecies forests. Accordingly, the site form (SF) is an alternative measure of productivity to the site index based on the tree height–diameter relationship. Our study aims to evaluate SF as a measure of productivity in the temperate uneven-aged multispecies forests of Durango, Mexico, applying three methods to estimate SF: (i) as the mean height of dominant trees at a reference diameter (SFH-D); (ii) as the expected mean height of dominant trees at a reference mean diameter (SFMH-MD), and (iii) as the expected height at a reference diameter for a given site (SFh-dbh). We assess the effectiveness of the SF based on two hypotheses: (i) the SF correlates to the total volume production, and (ii) the SF is independent of stand density. The SFH-D and the SFh-dbh showed a high correlation with productivity. However, they also did so with density. Contrary to this, the SFMH-MD had a weak correlation with density and productivity. We conclude that the SF is a suitable approach to describe site quality. Nonetheless, its effectiveness as a site quality indicator may be affected according to the method used.

Given the drastic changes in the environment, resilience is a key focus of ecosystem management. Yet, the quantification of the different dimensions of resilience remains challenging, particularly for long-lived systems such as forests. Here we present an analytical framework to study the economic resilience of different forest management systems, focusing on the rate of economic recovery after severe disturbance. Our framework quantifies the post-disturbance gain in the present value of a forest relative to a benchmark system as an indicator of economic resilience. Forest values and silvicultural interventions were determined endogenously from an optimization model and account for risks affecting tree survival. We consider the effects of differences in forest structure and tree growth post disturbance on economic resilience. We demonstrate our approach by comparing the economic resilience of continuous cover forestry against a clear fell system for typical conditions in Central Europe. Continuous cover forestry had both higher economic return and higher economic resilience than the clear fell system. The economic recovery from disturbance in the continuous cover system was between 18.2 and 51.5% faster than in the clear fell system, resulting in present value gains of between 1733 and 4535 € ha−1. The advantage of the continuous cover system increased with discount rate and stand age, and was driven by differences in both stand structure and economic return. We conclude that continuous cover systems can help to address the economic impacts of increasing disturbances in forest management.

Agroforestry 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.

Models are essential to assess the socio-economic credentials of new agroforestry systems. In this study, we showcase robust optimisation as a tool to evaluate agroforestry’s potential to meet farmers’ multiple goals. Our modelling approach has three parts. First, we use a discrete land-use model to evaluate two agroforestry systems (alley cropping and silvopasture) and conventional land uses against five socio-economic objectives, focusing on the forest frontier in eastern Panama. Next, we couple the land-use model with robust optimisation, to determine the mix of land uses (farm portfolio) that minimises trade-offs between the five objectives. Here we consider uncertainty to simulate the land-use decisions of a risk-averse farmer. Finally, we assess how the type and amount of agroforestry included in the optimal land-use portfolio changes under different environmental, socio-economic and political scenarios, to explore the conditions that may make agroforestry more attractive for farmers. We identify silvopasture as a promising land use for meeting farmers’ goals, especially for farms with less productive soils. The additional labour demand compared to conventional pasture, however, may prove an important barrier to adoption for farms facing acute labour shortages. The selection of agroforestry responded strongly to changes in investment costs and timber prices, suggesting that cost-sharing arrangements and tax incentives could be effective strategies to enhance adoption. We found alley cropping to be less compatible with farmers’ risk aversion, but this agroforestry system may still be a desirable complement to the land-use portfolio, especially for farmers who are more profit-oriented and tolerant of risk.

Restoration of degraded pasture lands in the tropics through afforestation is widely supported. The greatest obstacle to afforestation, however, is the long delay before initial financial returns from wood harvesting are realized. Interplanting young trees with food or energy crops has been proposed as a strategy to help overcome this obstacle. We investigated the impact of this practice on the survival and growth performance of young tropical tree seedlings in Panama. Five native timber tree species and the exotic species Tectona grandis were interplanted with four different crop rotations and monitored over 2 years. Survival of young tree seedlings was up to eight times higher when planted in association with Manihot esculenta. Only during the first 3 months after maize sowing was a significant negative effect of intercropping on tree seedling survival found. Here, survival rate of tree seedlings was up to four times lower than in the pure plantation. Tree growth was not adversely affected by crops. In fact, Astronium graveolens, Cedrela odorata and Terminalia amazonia showed significantly superior growth performance in association with both Zea mays and Cajanus cajan. When combined with the latter, the height increment of these tree species was up to four times that achieved in pure plantations. We conclude that intercropping can be an important silvicultural practice to facilitate forest restoration. Multi-purpose shrubby crop species with cropping cycles of more than 6 months are particularly beneficial, as they quickly shade out grasses, thus reducing the need for herbicides.

Understanding farmers’ perceptions of and preferences towards agroforestry is essential to identify systems with the greatest likelihood of adoption to inform successful rural development projects. In this study we offer a novel approach for evaluating agroforestry systems from the farmer perspective. The approach couples rapid rural appraisal and normative optimisation techniques to determine favourable land-use compositions for meeting various socio-economic and ecological goals, based on farmers’ empirical knowledge and preferences. We test our approach among smallholder farmers in Eastern Panama, obtaining data from household interviews and using hierarchical cluster analysis to identify farm groups with similar land-use and income characteristics. We found that moderate differences in farmers’ perceptions between these groups altered the type and share of agroforestry included in the optimised land-use portfolios that balance the achievement of 10 pre-selected socio-economic and ecological objectives. Such differences provide valuable information about potential acceptability of agroforestry within each group. For example, we found that farmers who derive most of their farm income from crops may be more willing to adopt silvopasture, whereas farmers who are more economically dependent on cattle may benefit from diversifying their land-use with alley cropping. We discuss the potential of this modelling approach for participatory land-use planning, especially when dealing with small sample sizes and uncertainty in datasets.

Modeling disturbance-based tree mortality is becoming increasingly important in the discussion of how to adapt forests to climate change and to preserve their ecosystem services and mitigate the risk of economic losses. In this study, we fitted species-specific interval-censored Accelerated Failure Time models for five major tree species to derive the influence of climate, soil, silvicultural measures, stand and tree characteristics on survival times. We coded all disturbance-based mortality causes as events and analyzed 473,501 individual trees distributed across 2248 long-term (1929–2014) forest growth and yield plots in southwestern Germany. We observed different survival probabilities among tree species with Douglas-fir having the lowest survival probability at age 100 years, followed by Norway spruce and Silver fir. Contrastingly, beech and oak had survival probabilities above 0.98 at age 100 years. Most important factor influencing these survival times was climate. Higher summer temperature shortens the survival time of beech, Silver fir and oak, while Norway spruce suffers more from warmer and wetter winters. Beside climatic factors, base saturation showed a significant positive relationship to survival time for all investigated tree species, except for Norway spruce, which had shorter survival times with increasing cation exchange capacity of the soil. Additionally, short-term effects of destabilization after thinning were found. In conclusion, favoring broadleaved tree species, avoiding heavy thinning in older stands and limiting tree age reduce the probability of disturbance-based tree mortality. However, some of the effects found that cause-unspecific mortality modeling has limited potential to describe the mortality–climate change relation.