Evaluation of the Plant Growth as an Ecological Footprint Supporting Indicator

Transcription

1 Evaluation of the Plant Growth as an Ecological Footprint Supporting Indicator Project Report prepared for Environmental Protection Agency, Region 9 Forrest Melton, Hirofumi Hashimoto, Carolyn Rosevelt, Pamela Krone-Davis California State University, Monterey Bay NASA Ames Research Center Cooperative Agreement Draft 3.1 September 12, 2012

2 INTRODUCTION Satellite remote sensing can provide spatially continuous, unbiased assessments of vegetation condition at spatial scales ranging from 1m to 8km. Long-term, continuous timeseries of data from satellite sensors such as the Advanced Very High Resolution Radiometer and the Moderate Resolution Imaging Spectroradiometer (MODIS) allow tracking of vegetation conditions and identification of short-term anomalies and longterm trends in vegetation condition at local to continental scales. There are multiple remote sensing indices that can be used to monitor vegetation condition. The Normalized Difference Vegetation Index (NDVI) (Tucker, 1979) is one of the most commonly used indices, and measures the differential absorption of light at the land surface in the red wavelengths, which are photosynthetically active and absorbed by plants, relative to near-infrared wavelengths. NDVI is commonly used as an indicator of vegetation photosynthetic capacity and is often referred to as a measure of vegetation greeness. Figure 1: A map of the Plant Growth Index for the U.S. from as reported in the 2008 State of the Nation s Ecosystem report, showing strong positive trends across much of the U.S. The Plant Growth Index is an indicator of long-term trends in vegetation condition, and measures the long-term trends in timeseries of peak annual NDVI. The annual maximum NDVI is a function of vegetation density and condition, and declines in maximum NDVI may be caused by changes in land cover or vegetation type, ecosystem disturbance events, or weather conditions which are outside of the biologically optimal range for vegetation at a given location, and thus reduce photosynthesis. The plant growth index

3 is sensitive to these changes, and is a conservative indicator of changes in long-term photosynthetic capacity. Figure 2: An updated PGI map for North America from , as reported in Nemani et al. (2009). The plant growth index was used in the 2008 State of the Nation s Ecosystem report (Heinz Center, 2008) as a key national indicator to assess the overall condition of U.S. ecosystems (Figure 1). At the time of publication of the report, a long-term, consident timeseries of AVHRR data was available for the U.S. from 1982 to 2003, with the plant growth index showing postive trends in peak annual NDVI across much of the U.S. In 2008, the AVHRR timeseries was extended through 2006, and an updated plant growth index analysis was prepared for the North American continent (Figure 2). These results highlighted emerging long-term negative trends across much of the Canadian boreal forests, expanding negative trends across much of the northeastern U.S., and persistent but weakening positive trends across much of the central U.S. (Nemani et al., 2009). The purpose of this study was to evaluate the potential utility of the plant growth index to serve as a supporting sustainability indicator for California. To calculate the plant growth index for California, we analyzed twenty-nine years of AVHRR data, from 1982 through 2010, using the latest available data from the Global Inventory Modeling and Mapping Studies AVHRR 8km NDVI dataset (Tucker et al., 2005). We also calculated the plant

4 growth index from eleven years of MODIS 250m NDVI data, from 2001 through 2011, for California using the Terrestrial Observation and Prediction System (TOPS). The results presented in the following sections highlight the challenge of identifying long-term trends against the significant interannual variability in weather conditions in California, and the significant role of wildfire as a natural disturbance agent in California s ecosystems. METHODS The methods used in this analysis for California followed those used to produce data products for the 2008 State of the Nation s Ecosystems report (Heinz Center, 2008), and are briefly summarized here. The plant growth index reports an index that describes general patterns of plant growth. Specifically, long-term trends in peak annual NDVI are mapped as an indicator of photosynthetic capacity. Trends are summarized by ecosystem type, and estimates are made of the amount of area with yearly increases or decreases in plant growth within major ecosystem classes. Data are reported individually by ecosystem type, as well as synoptically for all ecosystem types combined for the full time period (in this case, from ). The plant growth index was calculated from two long-term satellite data records. The first long-term record is calculated from data collected by the Advanced Very High Radiation Radiometer (AVHRR) onboard the National Oceanographic and Atmospheric Administration s (NOAA) polar-orbiting satellites, and spans the period from 1982 to The second dataset used was from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the NASA Terra satellite, and spans the period from 2001 to NDVI provides a measure of the density of chlorophyll biomass. NDVI = (NIR VIS)/(NIR + VIS), where NIR is near-infrared light reflected by vegetation and VIS is visible light in the red wavelenghts that is reflected by vegetation, as measured remotely by AVHRR. Low values of NDVI (0.1 and below) generally correspond to barren areas of rock, sand, or snow. Moderate values typically represent shrub and grassland (0.2 to 0.3), while high values indicate croplands and temperate and tropical rainforests (0.6 to 0.8). For a given type of vegetation (e.g., forest, shrublands, grasslands, croplands), the index can be used as a metric of physiological state. Healthy vegetation (high value) absorbs most of the visible light that hits it, and reflects a large portion of the nearinfrared light. Unhealthy or sparse vegetation (low value) reflects more visible light and less near-infrared light. Because the relationship between NDVI and absorbed photosynthetically active radiation varies by cover type, the growing-season accumulated NDVI was calculated separately for the forest, farmland, and grasslands, and shrubland areas of California, for each year between 1982 and 2010.

5 The raw NOAA-AVHRR sensor data at 8-km spatial and 15-day temporal resolution has been 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). The MODIS 250m sensor data is derived from the MODIS 250m NDVI data product that is compositied to a 16-day standard product (MOD13Q1). The GIMMS AVHRR datasets and the MODIS MOD13Q1 250m NDVI tiles were mosaicked and subset for California using the NASA Terrestrial Observation and Prediction System (TOPS) (Nemani et al., 2009). GIMMS data are available from the Global Land Cover Facility ( The data presented here were obtained directly from NASA (Terrestrial Observation and Prediction System (TOPS) /Ames Research Center). 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 longterm 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; as well as changes in urban land cover derived from the National Land Cover Database (NLCD; (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 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. RESULTS AND FIGURES A map of the plant growth index calculated from the twenty-nine year GIMMS AVHRR NDVI timeseries spanning is shown in Figure 3. Statistically significant trends over this period range from a positive trend of.008 NDVI/year to a negative trend of NDVI/year. At a resolution of 8 km, much of the state shows no significant trends, and overall pixels showing positive trends outnumber pixels exhibiting negative trends. In total, 1,377 pixels exhibited a statistically significant trend over the study area, representing 88,128 km 2, or 21.3% of the state. Of these, 1,096 pixels (80%) exhibited a positive trend, representing 70,144 km 2. A total of 281 pixels (20%) exhibited a negative trend, representing 17,984 km 2. There are large clusters of pixels exhibiting

6 positive trends in the plant growth index in the northern Sacramento Valley, including portions of Sutter, Butte, Glenn, Colusa, and Yolo Counties, as well as the southern San Joaquin Valley and the Sierra foothills. There are few large clusters of pixels exhibiting strong negative trends, and those clusters of pixels with negative trends in Santa Barbara and Ventura Counties are associated with recent wildfire events. Figure 3: Map of statistically significant trends in the plant growth index from , calculated from the GIMMS AVHRR 8km data record.

7 For comparison, the plant growth index was also calculated from the MODIS 250m NDVI data record for the period from 2001 to 2011 (Figure 4). Maximum and minimum trends over this shorter time period are stronger, and range from NDVI per year to 0.02 NDVI per year. As with the trends in the plant growth index calculated from the AVHRR data, most of California exhibits no statistically significant trends. A total of 529, m pixels representing 33,104 km 2 (8% of the state) exhibited a statistically significant trend in the plant growth index from 2001 to 2011, with 53% of these exhibiting a negative trend and 47% exhibiting a positive trend. There are many distinct clusters of pixels with positive and negative trends, with many of the largest clusters associated with major wildfires that have occurred in the past 20 years (Figures 6-9). Figure 4: Map of statistically significant trends in the plant growth index from , calculated from the MODIS 1km data record.

8 Over the twenty-nine year AVHRR NDVI record, we also summarized trends in the plant growth index by ecosystem type. Figure 5 provides the yearly change in the plant growth index relative to the long term average for forests, shrublands, grasslands, and croplands. Substantial year-to-year variability is evident in the summaries for all ecosystem types. As expected, the multi-year droughts of and are associated with an increase in the area of shrublands and grasslands that are more than 0.02 below the longterm NDVI average, while the record rainfalls in late 2010 correspond with a substantial increase in the area for which PGI is well above average (by >0.05 NDVI) for all ecosystem types. As a general rule, California ecosystems are highly sensitive to the El Nino Southern Oscillation, and the periodic recurrence of El Nino and La Nino climate patterns. Figure 5 highlights the difficulty of identifying long-term trends in ecosystem condition against the natural year-to-year variability in California. Figure 5: Ecosystem Area with Increasing or Decreasing Plant Growth Index Index Relative to Average for to to 0.05 more than 0.5

9 Ecosystem disturbance resulting from natural, accidental, and prescribed fire events presents an additional complication in identifying emerging trends in ecosystem condition. To evaluate the relationship between trends in the plant growth index and fire events, we performed a spatial comparison between statistically significant trends in the plant growth index and fire history polygons for fires that occurred between 1991 and To simplify the complex patterns in fire history, fires were grouped into five bins according to the time since the fire event relative to 2011: <=3 years ( ); 4-5 years ( ); 6-7 years ( ); 8-9 years ( ); and years ( ). The expectation is that negative trends in the plant growth index will be associated with recent fire events, as ecosystems are still recovering. Inversely, positive trends will be associated with older fire events that occurred between 1991 and 2001, and for which the majority of the MODIS data record is associated with increasing vegetation growth as the ecosystem recovers from the disturbance event. The 250m MODIS NDVI data record was used for this comparison, since the spatial scale is fine enough that individual fire events can easily be resolved in the satellite data record. The spatial relationship between the plant growth index from and fire history from is summarized in Figure 6. Of the 33,104 km 2 that exhibited a statistically significant trend in the MODIS data record from 2001 to 2011, 4,464 km 2 (13.5%, 71, m pixels) occurred within the boundary of at least one fire during this period. Of these, a total of 68% exhibited a negative trend, and 32% exhibited a positive trend over the analysis period. Examples of the close spatial relationship between the fire disturbance events and trends in the plant growth index are provided in Figures 7-9. The figures highlight the often complex spatial patterns in ecosystem disturbance history, as well as the effect of time since disturbance on the direction of the trend in the plant growth index.

10 Figure 6: A map of fire history polygons from 1991 to 2011 overlaid on the trends in the plant growth index calculated from the MODIS NDVI data record from 2001 to 2011.

11 Figure 7: Fire history polygons overlaid on trends in the plant growth index east of Clear Lake, California. Notable features include the Fork Fire (large blue polygon), which occurred in 1996 and is associated with a large cluster of pixels exhibiting a positive trend in the plant growth index, and the Walker Fire (largest red polygon), which occurred in 2008, and is associated with a large cluster of pixels which exhibit a negative trend in the plant growth index.

12 Figure 8: Fire history polygons overlaid on trends in the plant growth index east of Willow Creek, California. Much of this area was burned during the period from 1991 to Recent fires (since 2005) are generally associated with negative trends in the plant growth index, while older fires are associated with positive trends in the plant growth index since the data record is dominated by post-disturbance regrowth of vegetation.

13 Figure 9: Fire history polygons overlaid on trends in the plant growth index in Big Sur, California. Notable features include the Basin Complex and Indians fires (red polygons) that occurred in 2008, and the Kirk Fire (1999) and Wild Fire (1996) (blue polygons).

14 While climate conditions and fire are the two largest drivers of changes in ecosystem condition in California on annual basis, land use change associated with urban development is also a significant driver. In California, population is anticipated to grow from million people in 2010, to 59.5 million people in During this same time period, impervious surface area (ISA) is expected to increase by as much as 33.5% over much of the developed areas in California. Figure 10 provides a map of predicted changes in ISA from the Spatially Explicit Regional Growth Model (SERGoM) under the SRES A2 scenario (Bierwagen et al., 2010). Figure 10: Predicted increase in ISA as a percent of the total area from the SERGoM model under the SRES A2 scenario (Bierwagen et al., 2010). Under this project, we performed an initial analysis to determine whether or not the plant growth index appeared to be sensitive to increases in ISA and expansion of urban land cover types. At an 8km resolution, the AVHRR data record is too coarse for use in evaluation of changes of urban land cover, and thus the analysis relied on the plant growth index calculated from the 250m MODIS time series, and data from the 2001 and 2006 National Land Cover Database (Homer et al., 2004). Sample comparisons are shown in Figure 11.

15 (a) (b) (c) (d) Figure 11: Four examples of spatial comparisons between trends in the plant growth index and increases in urban land cover from the 2001 and 2006 NLCD data. Figures 11a and 11b, from Lathrop and Stockton, provide examples of cases where there is reasonable agreement between negative trends in the plant growth index and expansion of urban land cover. Figures 11c and 11d, from Turlock and Stockton, provide examples of locations where there changes in urban land cover and trends in the plant growth index do not align spatially.

16 In general, results from this initial comparison suggested very poor spatial agreement between increases in land cover and trends in the plant growth index. There are a number of likely reasons for this, which are discussed in the following section. DISCUSSION While satellite data is unquestionably useful for monitoring changes in ecosystem conditions and quantifying the effects of land cover change on ecosystem state and function, use of the plant growth index as a sustainability indictor for California may prove more complex. Previously published results for the U.S. (Heinz Center, 2008) and North America (Nemani et al., 2009) demonstrate the ability of the plant growth index to capture long-term trends in vegetation condition over large areas. In California, however, the substantial year-to-year variability in weather conditions, coupled with the natural role of fire in California s ecosystems, may make it harder to detect emerging long-term trends in the plant growth index. Overall, the long-term trends in the plant growth index in California present a mixed pattern of positive and negative trends, with a majority of the state exhibiting no significant trend. Based on the analysis of the MODIS data record, of the 414,000 km 2 encompassed by California, 33,104 km 2 (529, m pixels) or 8% of the state exhibited statistically significant trends in the plant growth index from 2001 to 2011, with the total area of negative trends slightly outweighing positive trends. However, during the 11-year data record, California experienced both a significant 3-year drought (from ) as well as a very wet water year in , which set a number of monthly rainfall records around the state. Comparisons between the plant growth index and fire history polygons show clear spatial relationships at a resolution of 250m, demonstrating that the plant growth index is sensitive to local changes associated with ecosystem disturbance. Spatial agreement with changes in urban land cover was less well defined, and generally the spatial agreement was not strong, even using the MODIS 250m dataset. However, urban development, especially for residential housing, typically results in a short-term reduction in the plant growth index, as irrigated lawns and other landscaping can achieve maximum NDVI values that are comparable to grassland, shrubland, and savannah ecosystems. As such, the plant growth index is expected to be less sensitive to replacement of natural ecosystems with residential development. Other satellite derived indicators may be much more sensitive to changes in land cover type, however, and can be used to reliably map increases in urban land cover and ISA (Homer et al., 2004). SUMMARY In this study, we evaluated the potential utility of the plant growth index as a supplemental sustainability indicator for California. Results for the period from 1982 to 2010, as well as 2001 to 2011, show that for the majority of the state no statistically significant trends are evident, and patterns of positive and negative trends are generally mixed across the state, with the largest clusters of negative trends associated with recent

17 wildfire events. In the short-term, the plant growth index may have limited utility for communicating climate vulnerabilities to the citizens of California. As warming continues to advance over the coming decades, however, the plant growth index may serve as a useful indicator for mapping regional trends in ecosystem condition as trends begin to emerge against the historic interannual variability in temperature and precipitation in California. In addition, there are numerous other satellite indicators that may provide highly useful spatial summaries of changes in land cover, snow cover, groundwater, evapotranspiration, evaporative stress, biomass and carbon fluxes, and other key indicators of the condition of California s natural resources. REFERENCES Bierwagen, B. G., Theobald, D. M., Pyke, C. R., Choate, A., Groth, P., Thomas, J. V., & Morefield, P. (2010). National housing and impervious surface scenarios for integrated climate impact assessments. Proceedings of the National Academy of Sciences, 107(49), doi: /pnas 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, #160, Collin, HUANG, C., YANG, L., WYLIE,... Michael. (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. Nemani, R., Hashimoto, H., Votava, P., Melton, F., Wang, W., Michaelis, A.,... White, M. (2009). Monitoring and forecasting ecosystem dynamics using the Terrestrial Observation and Prediction System (TOPS). Remote Sensing of Environment, 113(7), doi: /j.rse Tucker, C. J. (1979). Red and photographic infrared linear combinations for monitoring vegetation. Remote Sensing of Environment, 8(2), doi: / (79) Tucker, C. J., Pinzon, J. E., Brown, M. E., Slayback, D. A., Pak, E. W., Mahoney, R.,... El Saleous, N. (2005). An extended AVHRR 8 km NDVI dataset compatible with MODIS and SPOT vegetation NDVI data. International Journal of Remote Sensing, 26(20), doi: / ACKNOWLEDGEMENTS This research was supported by a grant from the Environmental Protection Agency, Region 9 (Award #PR R ) to the University Corporation at Monterey Bay, the non-profit auxiliary foundation of California State University, Monterey Bay.