Applications of Remote Sensing and Ecosystem Modeling for Monitoring and Management of U.S. National Parks F Melton 1*,2, A Michaelis 1,2, W Wang 1,2, S Hiatt 1,2, H Hashimoto 1,2, P Votava 1,2, C Milesi 1,2, R Nemani 2 1 California State University Monterey Bay, Seaside, CA, USA; * 2 Ecological Forecasting Lab, NASA Ames Research Center, Moffett Field, CA, USA Summary NPS Indicators of Park Vital Signs Managers of U.S. national parks are under increasing pressure to monitor changes in park ecosystems resulting from climate and land use change within and adjacent to park boundaries. In response, the National Park Service (NPS) has worked for the past decade to develop and implement the NPS Inventory & Monitoring (I&M) system to provide a coordinated framework for monitoring and decision support. Until recently, however, use of remote sensing and ecosystem modeling within the I&M system has been limited, largely due to issues associated with data volumes, data pre-processing requirements, and lack of technical expertise. To overcome these Technology & System Architecture Protected areas are often sparsely instrumented, which currently makes it difficult for resource managers to quickly identify trends and changes in park ecosystem conditions. Remote sensing and ecosystem modeling offer protected area managers important tools for comprehensive monitoring of ecosystem conditions and scientifically based decision-making. NASA sensors onboard satellites, aircraft, and UAVs collect terabytes of data per day that cannot be manually processed and analyzed. The TOPS software architecture includes components for streamlined data processing, data management, and modeling. These components facilitate rapid, autonomous processing of sensor web data streams. In addition, the modeling layers within TOPS allow exploration of the direct impacts of future climate trends on ecosystem conditions, allowing TOPS to provide both a monitoring and forecasting capability. Data from TOPS is delivered to the NPS I&M system via WMS, WCS, FTP, and a browser-based data gateway to encourage use and adoption by NPS personnel. The TOPS software architecture obstacles, the Terrestrial Observation and Prediction System (TOPS) is currently being applied to automate the production, analysis, and delivery of a suite of data products derived from NASA satellites and ecosystem models to assist managers of U.S. national parks. TOPS uses ecosystem models to combine satellite data with ground-based observations to produce nowcasts and forecasts of ecosystem conditions. We are utilizing TOPS to deliver data products via the TOPS data gateway to NPS resource managers in near real-time for use in landscape monitoring and operational decision-making. Current products include measures of vegetation condition, ecosystem productivity, phenology, soil moisture, snow cover, climate, and fire occurrence, as well as forecasts of future climate scenarios on park ecosystems. In addition, the use of TOPS to automate the identification of trends and anomalies in ecosystem conditions enables protected area managers to track park-wide conditions daily, identify changes, focus monitoring efforts, and improve decision making through use of NASA data. The NPS I&M system is organized around quantitative indicators of key park vital signs. Successful integration of TOPS data products into the NPS I&M framework has required linking TOPS data to corresponding indicators in collaboration with NPS. TOPS data is currently being integrated with the I&M system through inclusion in NPS standard operating procedure (SOP) manuals and through a browser-based data gateway developed to facilitate data visualization by NPS personnel. NPS / SIEN Vital Sign Related TOPS Products Vital Sign Indicator Landscapes dynamics and effects of disturbance events on plant communities NDVI/EVI, LAI/FPAR, soil moisture, evapotranspiration, vegetation stress (LWP) Annual trends + trends in max / min values; % of park experiencing significant anomaly on monthly / annual basis Phenology EVI / FPAR based phenology (PST & PAT) Estimated leaf on / leaf off dates; % at threshold by phenoregion / elevational bands SnowpackSnow cover (extent and timing) Snow cover (extent and timing); trends in snow off / snow on dates and total snow extent on Apr 1 / Oct 1 Surface water dynamics Watershed outflow, soil moisture Annual soil moisture trends / Days above threshold Net primary productivity / carbon GPP, NPPMonthly / annual averages and long term trends in average GPP, NPP Weather and climate Daily meteorology, impacts of long-term predicted change Trend tracking (seasonal/annual); impacts of long-term predicted change This work is supported by the NASA Applied Sciences program with grants from the REASoN and Decision Support through Earth Science Research Results solicitations.

The TOPS-NPS Data Gateway A primary barrier to use of NASA data within NPS has been the varying extent of experience of NPS personnel with satellite and model data formats. To overcome this barrier, we have developed a browser-based data gateway based on ka-Map, Geoserver, and the PostGRID database extensions. This data gateway provides direct access to TOPS data for NPS personnel, and includes tools for visualizing raster and vector layers, querying/graphing current and historical data, as well as direct access to the raster data layers via WCS, WMS, and FTP. This data gateway allows all NPS I&M and park personnel to browse a suite of satellite and model-based indicators of park vital signs (LAI/FPAR, NDVI/EVI, gross primary production, thermal anomalies/fires, gridded meteorological fields, soil water content, and evapotranspiration), and explore maps of trends and anomalies in park conditions. In addition, in collaboration with NPS, Montana State Univ, Colorado State Univ, and Woods Hole Oceanographic Inst, we are currently working to incorporate data on land use and land cover change, and to model the combined long-term impacts of climate and land use change on park ecosystems. Tracking Ecosystem Conditions The extensive archive of satellite and meteorological data in TOPS enables rapid identification and mapping of trends and anomalies in ecosystem conditions, providing an early warning capability and allowing park managers to focus ground-based monitoring efforts on locations showing evidence of change. Ongoing analyses indicate that many negative anomalies are correlated with identifiable events (e.g., fires and insect infestations). Using the TOPS-NPS data gateway, NPS personnel can browse maps of current and persistent anomalies and explore potential causes to identify indicators of ecosystem change or stress. Examples of the TOPS-NPS data gateway, showing current NDVI conditions (above) and maximum temperature (below) for the greater park ecosystem boundary for Yosemite and Sequoia-Kings Canyon National Parks. NPS personnel can use the data gateway to query raster layers and obtain numeric estimates of current and historic conditions at locations of interest (below). For more information, please visit: A map of current positive and negative FPAR anomalies in the Yosemite / Sequoia National Park greater park ecosystem. Forecasting Change In addition to monitoring current conditions, protected area managers need to be able to anticipate change to effectively allocate resources and adjust management strategies. A key component of TOPS is the ability to use outputs from general circulation models (GCMs) to drive ecosystem models to predict future ecosystem states. Long-term simulations of ecosystem conditions were conducted for Yosemite National Park to allow park managers to assess potential outcomes of climate change. Climate scenarios from the NOAA GFDL GCM were downscaled and used to drive TOPS from 1950 to Forecasted impacts by 2100 include declines in snow water equivalent, earlier snow melt, reduced summer stream flow, and declines in average park-wide GPP. Work is currently being conducted to extend this framework for use in other parks, and to evaluate the impact of these changes on fire regimes and habitat availability. For the YOSE/SEKI greater park ecosystems, from , an anomaly threshold of -6% detected a total of over 700,00 monthly negative anomaly events after QA filtering. The TOPS algorithm correctly flagged 74% of fire events > 300 acres in size. In total, 84% of FPAR anomalies detected were explained through cross-referencing with other data layers. Forecasted reductions in snow water equivalent (SWE) show significant reductions in average SWE by 2100 relative to the period from TOPS simulations predict shifts in the intra-annual patterns in GPP, with a % reduction in average summer GPP as a result of decreased soil moisture. Over the long-term, TOPS forecasts a sustained negative trend in annual mean GPP for Yosemite for , suggesting corresponding changes in fire dynamics.