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This paper integrates a spatial fire behavior model and a stochastic dynamic optimization model to determine the optimal spatial pattern of fuel management and timber harvest. Each year's fire season causes the loss of forest values and lives in the western US. This paper uses a multi-plot analysis and incorporates uncertainty about fire ignition locations and weather conditions to inform policy by examining the role of spatial endogenous risk-where management actions on one stand affect fire risk in that and adjacent stands. The results support two current strategies, but question two other strategies, for managing forests with fire risk.

The stochastic and spatial nature of fire poses challenges for the cost-efficient allocation of fuel treatment over the landscape. A model that addresses complex but important components of fuel management decisions, spatial and dynamic aspects of fire risk, and a carefully designed framework that allows us to draw general insight into the optimal spatial pattern of management are necessary to provide a basis for developing efficient fuel treatment plans. For this purpose, we combine a physical fire model and a spatial-dynamic optimization model to explore harvest and fuel treatment across a hypothetical landscape under risk of a moving fire over a range of physical and economic conditions. Our model is able to describe spatial trade-offs involved in decision process, namely trade-offs between protection of on-site values and protection against fire spread. We found that the spatial configuration of management units can lead to heterogeneity in management across seemingly homogeneous units.

Protected areas function as a lifeboat that can preserve the origins and maintenance of biodiversity. We assessed the representativeness of biodiversity in existing protected areas in Japan using a distribution dataset and phylogenetic tree for 5565 Japanese vascular plant species. We first examined the overlap of species distribution with the existing protected areas and identified the minimum set representing all plant species. Second, we evaluated the relative importance of environmental variables in explaining the spatial arrangement of protected areas using a random forest model. Finally, we clarified how potential drivers of plant diversity were sufficiently captured within the protected areas network. Although the protected areas captured the majority of species, nearly half of the minimum set areas were selected from outside the existing protected areas. The locations of existing protected areas are mainly associated with geographical and socio-economic factors rather than key biodiversity features (including evolutionary distinctiveness). Moreover, critical biodiversity drivers, which include current climate, paleoclimatic stability, and geographical isolation, were biasedly emulated within the existing protected areas. These findings demonstrate that current conservation planning fails to represent the ecological and evolutionary processes relevant to species sorting, dispersal limitation, and allopatric speciation. In particular, under-representativeness of historically stable habitats that function as evolutionary hotspots or refugia in response to climate changes may pose a threat to the long-term persistence of Japan's endemic biota. This study provides a fundamental basis for developing prioritization measures to retain species assembly processes and in situ diversification along current climatic and geohistorical gradients.