Transformation scenarios towards multifunctional landscapes: A multi-criteria land-use allocation model applied to Jambi Province, Indonesia.

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.

Severe and frequent extreme weather events undermine economic adaptation gains of tree-species diversification.

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 [Formula: see text], [Formula: see text], and [Formula: see text]-diversity of stand types. [Formula: see text]-diversity refers to the number and evenness of stand types in local planning units, [Formula: see text]-diversity to the dissimilarity of the species composition across planning units, and [Formula: see text]-diversity to the number and evenness of stand types in the entire enterprise. Local planning led to stand-type diversification within planning units ([Formula: see text]-diversity), while regionally coordinated planning led to diversification across planning units ([Formula: see text]-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.

Evaluation of the Site Form as a Site Productive Indicator in Temperate Uneven-Aged Multispecies Forests in Durango, Mexico.

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.

Accelerated Physical Emulation of Bayesian Inference in Spiking Neural Networks.

The massively parallel nature of biological information processing plays an important role due to its superiority in comparison to human-engineered computing devices. In particular, it may hold the key to overcoming the von Neumann bottleneck that limits contemporary computer architectures. Physical-model neuromorphic devices seek to replicate not only this inherent parallelism, but also aspects of its microscopic dynamics in analog circuits emulating neurons and synapses. However, these machines require network models that are not only adept at solving particular tasks, but that can also cope with the inherent imperfections of analog substrates. We present a spiking network model that performs Bayesian inference through sampling on the BrainScaleS neuromorphic platform, where we use it for generative and discriminative computations on visual data. By illustrating its functionality on this platform, we implicitly demonstrate its robustness to various substrate-specific distortive effects, as well as its accelerated capability for computation. These results showcase the advantages of brain-inspired physical computation and provide important building blocks for large-scale neuromorphic applications.