The objective of this proposal is to develop a practical and operational decision support system that could be used by the jane goodall institute and partners to annually monitor and forecast…

The objective of this proposal is to develop a practical and operational decision support system that could be used by the jane goodall institute and partners to annually monitor and forecast chimpanzee habitat health in africa. Understanding the relative condition, or health, of chimpanzee habitats at finer spatial and temporal resolutions across the entire chimpanzee range is key for planning effective conservation strategies. We propose to integrate earth observations from 30 meter resolution landsat data with a species specific habitat model and a model forecasting future land use change, enhanced by the field data collected by local communities using mobile smartphones. This proposal will predict and map a. The current habitat health status of the chimpanzee in east and central africa and, B. Future habitat health until 2030, taking into account business as usual scenarios of land cover and land use change occurring between 2000 and 2010. We will test our capability retrospectively, building models using 2000 to 2010 data inputs to predict 2013 habitat health. Presence data from four regions that capture the variety of chimpanzee habitat types, from dense humid tropical forests of the congo basin to dry savanna woodlands of western tanzania, will be used to calibrate and evaluate a single habitat health model. The project will specifically focus on community crowdsourcing directly linking earth observation data and models with conservation interventions and people on the ground. This crowdsourcing approach is particularly powerful for conservation because IT will not only increase the availability of limited field data but will also increase the participation and commitment of communities in implementing conservation strategies. We directly respond to NASA's applied sciences ecological forecasting call by proposing an integration of earth observation derived land cover extent and change data sets with species distribution and land cover land use change models to improve regional scale chimpanzee conservation efforts.