Climate change is raising challenging concerns for systematic conservation planning. Are methods based on the current spatial patterns of biodiversity effective given long-term climate change? Some conservation scientists argue that planning should focus on protecting the abiotic diversity in the landscape, which drives patterns of biological diversity, rather than focusing on the distribution of focal species, which shift in response to climate change. Climate is one important abiotic driver of biodiversity patterns, as different climates host different biological communities and genetic pools. We propose conservation networks that capture the full range of climatic diversity in a region will improve the resilience of biotic communities to climate change compared to networks that do not. In this study we used historical and future hydro-climate projections from the high resolution Basin Characterization Model to explore the utility of directly targeting climatic diversity in planning. Using the spatial planning tool, Marxan, we designed conservation networks to capture the diversity of climate types, at the regional and sub-regional scale, and compared them to networks we designed to capture the diversity of vegetation types. By focusing on the Conservation Lands Network (CLN) of the San Francisco Bay Area as a realworld case study, we compared the potential resilience of networks by examining two factors: the range of climate space captured, and climatic stability to 18 future climates, reflecting different emission scenarios and global climate models. We found that the climate-based network planned at the sub-regional scale captured a greater range of climate space and showed higher climatic stability than the vegetation and regional based-networks. At the same time, differences among network scenarios are small relative to the variance in climate stability across global climate models. Across different projected futures, topographically heterogeneous areas consistently show greater climate stability than homogenous areas. The analysis suggests that utilizing high-resolution climate and hydrological data in conservation planning improves the likely resilience of biodiversity to climate change. We used these analyses to suggest new conservation priorities for the San Francisco Bay Area.

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Background US college students smoke hookah and vape nicotine at higher rates than other young adults. Density/proximity of hookah lounges and vape shops near colleges has been described, but this study is the first to test whether tobacco retailers spatially cluster near college campuses. Methods We created and linked spatial shapefiles for community colleges and 4-year universities/colleges in California with lists of hookah lounges, vape shops and licensed tobacco retailers. We simulated 100 data sets, placing hookah lounges, vape shops and tobacco retailers randomly in census tracts in proportion to population density. A modified version of Ripley’s K-function was computed using the radius (r) from each retailer within retail category. Results In 2018/2019, 50.5% of hookah lounges (n=479), 42.5% of vape shops (n=2,467) and 42.0% of all tobacco retailers (n=31,100) were located within 3 miles of a community college. Spatial clustering was significant (p<0.05) from at least 0.4 miles for hookah lounges, 0.1 mile for vape shops, and 0.3 miles for all tobacco retailers. For 4-year universities/colleges, approximately 46.8% of hookah lounges, 31.3% of vape shops and 31.6% of all tobacco retailers were located within 3 miles. Clustering was significant from 0.2 miles for hookah lounges and 1.3 miles for all tobacco retailers but was not significant for vape shops. Conclusion Evidence that some types of tobacco retailers cluster near community colleges and 4-year universities/colleges implies greater accessibility and exposure to advertising for students. It is also concerning because a higher probability of underage tobacco sales presumably exists near colleges. Implications Prior studies infer that hookah lounges and vape shops cluster near colleges from the density and closer proximity to campuses. This study modified a traditional test of spatial clustering and considered community colleges separately from 4-year universities. Spatial clustering of hookah lounges and all licensed tobacco retailers was evident near both types of campuses, but vape shops clustered only near community colleges. Place-based strategies to limit tobacco retail density could expand state/local laws that prohibit tobacco sales near schools to include retailers near college campuses. In addition, college environments should be a target for reducing hookah smoking and nicotine vaping.