资源环境科技发展态势分析平台

Balancing the needs of increasing yields of productive systems while adhering to principles of sustainability is one of the most pressing challenges of the 21st century. However, baselines for management guidelines aimed at mitigating the impacts of working landscapes on biodiversity are lacking for the most biodiverse regions in the world. In addition, there is a scarcity of empirical examples of how information collected using community based approaches can be used to both define management guidelines and measure outcomes for sustainability. In this study, we used bird observations collected by community monitors to identify the functional relationships between bird occupancy and habitat traits to inform management of productive landscapes. Our results indicated that relationships between bird occupancy and habitat traits depended on species residence status and their affinity to urban-cropfield areas. Percentage of shrub cover was found to significantly influence the probability of occurrence across bird species in the landscape, followed by tree diameter, tree species richness, and time since anthropogenic disturbance. Tree species richness was the only habitat trait that was found to have a positive relationship across all species groups. Seasonal variation in the number of bird species related to habitat traits was only important for shrub cover. Following our results, we identified specific management targets for current land use categories (i.e., conservation forests, forestry plots, urban-cropfield areas) to benefit birds. Overall, we concluded that selective forestry management was not entirely detrimental for birds, as it preserves habitat heterogeneity and vegetation structure. In contrast, intensive forestry management was found to be unfavorable for most bird species, likely driven by the clearing of critical vegetation from the area. Our participatory approach for defining research objectives and collecting data to directly inform management guidelines for communal lands, while using robust analytical tools, shows great potential for promoting sustainable working landscapes in biodiverse regions across the globe.