The future of biodiversity conservation depends on efforts applied across large landscapes, the scale at which many key ecological and evolutionary processes take place. Because the seeds of the National Park system were sown in the United States over 130 years ago, conservation practitioners have increasingly demonstrated that critical conservation goals—including responsiveness to climate change and representation of species, ecosystems, and habitats—can be achieved only if protected areas are functionally connected and embedded within larger, permeable landscapes (Trombulak and Baldwin 2010).

The recovery of wild tigers in India and Nepal is a remarkable conservation achievement, but it sets the stage for increased human–wildlife conflict where parks are limited in size and where tigers reside outside reserves. We deployed an innovative technology, the TrailGuard AI camera-alert system, which runs on-the-edge artificial intelligence algorithms to detect tigers and poachers and transmit real-time images to designated authorities responsible for managing prominent tiger landscapes in India. We successfully captured and transmitted the first images of tigers using cameras with embedded AI and detected poachers. Notifications of tiger images were received in real time, approximately 30 seconds from camera trigger to appearing in a smart phone app. We review use cases of this AI-based real-time alert system for managers and local communities and suggest how the system could help monitor tigers and other endangered species, detect poaching, and provide early warnings for human–wildlife conflict.

Systematic conservation planning has been used extensively throughout the world to identify important areas for maintaining biodiversity and functional ecosystems, and is well suited to address large-scale biodiversity conservation challenges of the twenty-first century. Systematic planning is necessary to bridge implementation, scale, and data gaps in a collaborative effort that recognizes competing land uses. Here, we developed a conservation planning process to identify and unify conservation priorities around the central and southern Appalachian Mountains as part of the Appalachian Landscape Conservation Cooperative (App LCC). Through a participatory framework and sequential, cross-realm integration in spatial optimization modeling we highlight lands and waters that together achieve joint conservation goals from LCC partners for the least cost. This process was driven by a synthesis of 26 multi-scaled conservation targets and optimized for simultaneous representation inside the program Marxan to account for roughly 25% of the LCC geography. We identify five conservation design elements covering critical ecological processes and patterns including interconnected regions as well as the broad landscapes between them. Elements were then subjected to a cumulative threats index for possible prioritization. The evaluation of these elements supports multi-scaled decision making within the LCC planning community through a participatory, dynamic, and iterative process.

Conservation decisions should be evaluated for how they meet conservation goals at multiple spatial extents. Conservation easements are land use decisions resulting from a combination of social and environmental conditions. An emerging area of research is the evaluation of spatial distribution of easements and their spatial correlates. We tested the relative influence of interacting social and environmental variables on the spatial distribution of conservation easements by ownership category and conservation status. For the Appalachian region of the United States, an area with a long history of human occupation and complex land uses including public-private conservation, we found that settlement, economic, topographic, and environmental data associated with spatial distribution of easements (N = 4813). Compared to random locations, easements were more likely to be found in lower elevations, in areas of greater agricultural productivity, farther from public protected areas, and nearer other human features. Analysis of ownership and conservation status revealed sources of variation, with important differences between local and state government ownerships relative to non-governmental organizations (NGOs), and among U.S. Geological Survey (USGS) GAP program status levels. NGOs were more likely to have easements nearer protected areas, and higher conservation status, while local governments held easements closer to settlement, and on lands of greater agricultural potential. Logistic interactions revealed environmental variables having effects modified by social correlates, and the strongest predictors overall were social (distance to urban area, median household income, housing density, distance to land trust office). Spatial distribution of conservation lands may be affected by geographic area of influence of conservation groups, suggesting that multi-scale conservation planning strategies may be necessary to satisfy local and regional needs for reserve networks. Our results support previous findings and provide an ecoregion-scale view that conservation easements may provide, at local scales, conservation functions on productive, more developable lands. Conservation easements may complement functions of public protected areas but more research should examine relative landscape-level ecological functions of both forms of protection.