Connecting Wildlands & CommunitiesIntegrating ecological research into planning efforts is key to IEMM's goal of delivering actionable science. With new funding from the California State Strategic Growth Council, IEMM and the Climate Science Alliance will lead an interdisciplinary team of planners, environmental engineers, ecologist, and geographers to explore how connected landscapes can support adaptation and resilience to climate change for both ecosystems and local communities in southern California. This new project takes a comprehensive planning approach to meet State objectives on protecting rural communities, mitigating wildfire risk, supporting water sustainability, and protecting biodiversity. The goal of this research is to provide an integrated planning and decision-making framework that supports multi-benefit landscape-scale planning and facilitates science-informed climate adaptation and strategies across the region.
Visit the CWC websiteRecent publications
Rojas, I. M., Jennings, M., Lewison, R.L. et al. 2021. A landscape-scale framework to identify refugia from multiple stressors. Conservation Biology. https://doi.org/10.1111/cobi.13834 Storey, E.A., Stow, D.A., Roberts, D.A., O’Leary, J.F. and Davis, F.W., 2021. Evaluating Drought Impact on Postfire Recovery of Chaparral Across Southern California. Ecosystems, 24(4), pp.806-824. https://doi.org/10.1007/s10021-020-00551-2 Storey, E.A., Stow, D.A., O'Leary, J.F., Davis, F.W. and Roberts, D.A., 2021. Does short-interval fire inhibit postfire recovery of chaparral across southern California?. Science of The Total Environment, 751, p.142271. https://doi.org/10.1016/j.scitotenv.2020.142271 Storey, E.A., Lee West, K.R. and Stow, D.A., 2021. Utility and optimization of LANDSAT-derived burned area maps for southern California. International Journal of Remote Sensing, 42(2), pp.486-505. https://doi.org/10.1080/01431161.2020.1809741 Storey, E.A., Stow, D.A. and O'Leary, J.F., 2016. Assessing postfire recovery of chamise chaparral using multi-temporal spectral vegetation index trajectories derived from Landsat imagery. Remote Sensing of Environment, 183, pp.53-64. https://doi.org/10.1016/j.rse.2016.05.018 |
Project partners & Sponsors
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