SummaryThe Plant Growth Index (PGI) is a measure of long-term changes in plant community condition, based on satellite measurement of the peak annual Normalized Difference Vegetation Index. You can click on "Map Layers" items to the right of the map view to display them in the map. It is possible to turn on more than one map at a time. See more detail below the map view. General Information about this IndicatorWhat is it?: Navigate to the region on the map you are interested in viewing and then click on the checkboxes in the "Map layers" area to display those data. Based on the resolution of these data that are being displayed, this map most effective when you zoomed in a few "levels". Click on the + Key in the upper left corner of the map to zoom in, after which you can click on the map and drag your mouse to move to the area of the state you are interested in. You can also use the arrow buttons near the + key. This map relates a period of fire occurrence data (1982 to 2010) to plant growth trend data over that same period from the Advanced Very High Resolution Radiometer (AVHRR). For comparison, we've also added data compiled by MODIS (Moderate Resolution Imaging Spectroradiometer; http://modis.gsfc.nasa.gov/), which is at a much finer scale than AVHRR, but shorter timeframe. The color scale for the MODIS and Trend maps are similar in that greener values indicate more positive growth while darker red values represent more negative growth. Why is it important?: Productivity of terrestrial ecosystems can influence conditions in adjacent water-bodies. Plant communities provide nutrients, shade, erosion protection, natural disturbance (e.g., fire), and structure to streams and rivers. They also naturally consume water from the ground for photosynthesis, consuming carbon dioxide and producing oxygen. Healthy plant communities will grow and change, making their interactions with water systems dynamic and often unpredictable. For example, many plant communities in California are naturally fire-prone. When fires reduce or eliminate plants in an area, there can be a period when water, sediment, and nutrients increase in downhill streams, until plants naturally regrow in the burnt area. Remote sensing-based measures of plant community cover and plant growth, like the Plant Growth Index are useful for understanding long-term and extensive changes in plant communities.What can Influence or Stress Condition?: Plant growth is a function of the type of plant, age-class, competition, disturbance (e.g., disease), and soil/environmental factors. These conditions can vary with natural and artificial changes to landscapes and climate. Land conversion to fiber production, agriculture, or urban uses are all likely to alter PGI within a watershed. Depletion of groundwater, or hyporheic flows adjacent to streams can reduce PGI in riparian and non-riparian plant communities. Climate change is likely to be the most extensive and potentially most intensive change-agent for PGI. Certain plant types may increase PGI over short to medium timeframes due to increases in carbon dioxide and temperature, but most areas will have declines in PGI and change in component plant communities. It is unknown if plant communities will be able to adapt in place, or move in response to changing climatic conditions at a fast enough rate to survive. It is also unknown how successive plant communities adapted to new climatic conditions in a place will change soil, water, and natural disturbance regimes. The most predictable aspect of climate change effects on terrestrial plant communities is that the changes and impacts from the changes will be unpredictable.Target or Desired Condition: Because plant growth is critical both for maintaining healthy watershed functioning and for consuming carbon dioxide from the atmosphere, the desired condition is for all vegetation types to have PGI similar to their naturally-occurring range most of the time. There will inevitably be times when PGI is lower following natural disturbance. The undesired condition is for PGI in individual or all vegetation types in an area to fall outside (usually lower) their natural range most of the time. Tracking PGI for each plant community over decades provides another type of information. The desired condition is for long-term PGI for an area (e.g., a watershed) to oscillate within a range typical of the mix of plant communities present. The un-desired condition is for PGI to increase or decrease to a condition outside the range expected for the naturally-occurring mix of plant communities in the area.Additional Details: Heinz Center. (2008). The state of the nation’s ecosystems: measur- ing the land, water, and living resources of the United States. Washington, DC. Homer, C., C. Huang, L. Yang, M. Wylie, et al. (2004). Development of a 2001 National land-cover database for the United States (Vol. 70). Bethesda, MD, ETATS-UNIS: American Society for Photogrammetry and Remote Sensing. Melton, F., H. Hashimoto, C. Rosevelt, and P. Krone-Davis. 2012. Evaluation of the plant growth index as an ecological footprint supporting indicator. Report to the USEPA, Pp. 17 Tucker, C. J. (1979). Red and photographic infrared linear combinations for monitoring vegetation. Remote Sensing of Environment, 8(2), 127-150. doi: 10.1016/0034-4257(79)90013-0 Tucker, C. J., J.E. Pinzon, M.E. Brown, D.A. Slayback, E.W. Pak, R. Mahoney, R., et al. (2005). An extended AVHRR 8‐km NDVI dataset compatible with MODIS and SPOT vegetation NDVI data. International Journal of Remote Sensing, 26(20), 4485-4498. doi: 10.1080/01431160500168686 Indicator Preparation InformationData Sources: The information in this indicator report came from Melton et al., 2012. The AVHRR data are available from the Global Land Cover Facility (http://www.landcover.org). The data presented here were obtained directly from NASA (Terrestrial Observation and Prediction System (TOPS) /Ames Research Center).Data Transformations: The raw NOAA-AVHRR sensor data at 8-km spatial and 15-day temporal resolution was reprocessed by the National Aeronautics and Space Administration (NASA) Global Inventory Monitoring and Modeling Studies (GIMMS) group to provide a spatially and temporally consistent representation of global vegetation for climate studies, and to remove effects associated with calibration changes, orbital drift and aerosol contamination of the atmosphere (Tucker et al., 2005). Timeseries of maximum annual NDVI were calculated for each pixel, and linear trends in these timeseries were calculated for each pixel in the 250m MODIS and 8km AVHRR datasets. Linear trends were then filtered for statistical significance using a Mann-Kendall trend test, and a threshold of 0.90 was used to map statistically signficant long-term trends in annual maximum NDVI. To evaluate potential drivers of the observed trends, we evaluated spatial relationships between the plant growth index and fire history perimeters from the California Department of Forestry and Fire Protection (CalFire) Fire and Resource Assessment Program (FRAP; http://www.frap.cdf.ca.gov/data/frapgisdata/download.asp?rec=fire) as well as changes in urban land cover derived from the National Land Cover Database (NLCD; http://www.mrlc.gov/) (Homer et al., 2004). FRAP Fire History Polygons were aggregated by time since fire occurrence relative to 2011 (1-3 years, 4-5 years, 6-7 years, 8-9 years, and 10-20 years) to evaluate relationships between long term trends in the plant growth index and fire history. NLCD data from 2001, and 2006 were used to identify areas of possible urban expansion from 2001 to 2006 to evaluate possible relationships between positive and negative trends in the plant growth index and increases in urban areas and impervious surface area.