How to simultaneously combat biodiversity loss and maintain ecosystem functioning while improving human welfare remains an open question. Optimization approaches have proven helpful in revealing the trade‐offs between multiple functions and goals provided by land‐cover configurations. The R package optimLanduse provides tools for easy and systematic applications of the robust multiobjective land‐cover composition optimization approach of Knoke et al. (2016). The package includes tools to determine the land‐cover composition that best balances the multiple functions a landscape can provide, and tools for understanding and visualizing the reasoning behind these compromises. A tutorial based on a published dataset guides users through the application and highlights possible use‐cases. Illustrating the consequences of alternative ecosystem functions on the theoretically optimal landscape composition provides easily interpretable information for landscape modelling and decision‐making. The package opens the approach of Knoke et al. (2016) to the community of landscape modellers and planners and provides opportunities for straightforward systematic or batch applications.

In tropical regions, shifting from forests and traditional agroforestry to intensive plantations generates conflicts between human welfare (farmers' demands and societal needs) and environmental protection. Achieving sustainability in this transformation will inevitably involve trade-offs between multiple ecological and socioeconomic functions. To address these trade-offs, our study used a new methodological approach allowing the identification of transformation scenarios, including theoretical landscape compositions that satisfy multiple ecological functions (i.e., structural complexity, microclimatic conditions, organic carbon in plant biomass, soil organic carbon and nutrient leaching losses), and farmers needs (i.e., labor and input requirements, total income to land, and return to land and labor) while accounting for the uncertain provision of these functions and having an actual potential for adoption by farmers. We combined a robust, multi-objective optimization approach with an iterative search algorithm allowing the identification of ecological and socioeconomic functions that best explain current land-use decisions. The model then optimized the theoretical land-use composition that satisfied multiple ecological and socioeconomic functions. Between these ends, we simulated transformation scenarios reflecting the transition from current land-use composition towards a normative multifunctional optimum. These transformation scenarios involve increasing the number of optimized socioeconomic or ecological functions, leading to higher functional richness (i.e., number of functions). We applied this method to smallholder farms in the Jambi Province, Indonesia, where traditional rubber agroforestry, rubber plantations, and oil palm plantations are the main land-use systems. Given the currently practiced land-use systems, our study revealed short-term returns to land as the principal factor in explaining current land-use decisions. Fostering an alternative composition that satisfies additional socioeconomic functions would require minor changes ("low-hanging fruits"). However, satisfying even a single ecological indicator (e.g., reduction of nutrient leaching losses) would demand substantial changes in the current land-use composition ("moonshot"). This would inevitably lead to a profit decline, underscoring the need for incentives if the societal goal is to establish multifunctional agricultural landscapes. With many oil palm plantations nearing the end of their production cycles in the Jambi province, there is a unique window of opportunity to transform agricultural landscapes.

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 (SF_H-D); (ii) as the expected mean height of dominant trees at a reference mean diameter (SF_MH-MD), and (iii) as the expected height at a reference diameter for a given site (SF_h-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 SF_H-D and the SF_h-dbh showed a high correlation with productivity. However, they also did so with density. Contrary to this, the SF_MH-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.

Recent mortality pulses indicate pathways to restore maladapted forests towards more natural, mixed, resilient ecosystems. Under climate change, carbon sequestering forests serve as forces for mitigation but face threats from disturbances. The uncertain development of this duality complicates stakeholder-relevant predictions of timber yield or tree species compositions. We analyzed uncertainty in forest development over 50 years, focusing primarily– but not exclusively– on Scots pine, the most important tree species in northern Germany,. Thereunto, i. future survival was examined on a site- and climate-specific basis. The novelty of the simulations lies in ii. quantifying the influence of irregular die-off on forests under stand-wise (discrete) or tree-wise (diffuse) mortality patterns to iii. investigate yield and harvest potentials. By spanning a scenario funnel from two management and two climate projections on 17,551 National Forest Inventory plots in northern Germany, we assess prospective uncertainties. The transition of forest composition through space and time with conditional hazard rates resembles a Markov process via Monte Carlo sampling. Prospectively, i. mortality doubles depending on the species. Compared to undisturbed development, ii. forest restoration outcomes are uncertain; stand-losses can accelerate restoration by up to 10%, while tree-losses might slow it down. Under disturbances, iii. volume increment and stand age decrease as harvests rise in the medium-term with large dimensioned timber increasing fivefold. Driven by climate change and forest demographics, the decline in yield and the remaining 40% monocultures are critical. Forest development is inert, therefore we suggest more differentiated silvicultural concepts for actively adapting forests to alarming changes.