Monitoring of Net Primary Production in California Rangelands Using Landsat and MODIS Satellite Remote Sensing

Abstract

In this study, we present results from the CASA (Carnegie-Ames-Stanford Approach) model to estimate net primary production (NPP) in grasslands under different management (ranching versus unmanaged) on the Central Coast of California. The latest model version called CASA Express has been designed to estimate monthly patterns in carbon fixation and plant biomass production using moderate spatial resolution (30 m to 250 m) satellite image data of surface vegetation characteristics. Landsat imagery with 30 m resolution was adjusted by contemporaneous Moderate Resolution Imaging Spectroradiometer (MODIS) data to calibrate the model based on previous CASA research. Results showed annual NPP predictions of between 300 - 450 grams C per square meter for coastal rangeland sites. Irrigation increased the predicted NPP carbon flux of grazed lands by 59 grams C per square meter annually compared to unmanaged grasslands. Low intensity grazing activity appeared to promote higher grass regrowth until June, compared to the ungrazed grassland sites. These modeling methods were shown to be successful in capturing the differing seasonal growing cycles of rangeland forage production across the area of individual ranch properties

Understanding Climate Change on the California Coast: Accounting for Extreme Daily Events among Long-Term Trends

“…On a statewide basis, surface air temperatures have been warming between 1950 and 2005 [7]. Almost all increases detected were due to changes in Tmin in the dry summer season, since Tmax showed either no change or cooling.…”

“…Plant growth on the Central Coast can be highly variable from year-to-year and is generally limited by declines of soil moisture in the summer and by cool temperatures in the winter [4]. The annual production pattern for coastal grasses is rapid growth in the late fall (November) after the first rains have returned, slow winter growth (December-February), and rapid growth again in spring (March-May) [7][8][9]. BSP represents the longest, complete climate record on the Monterey County coast south of Carmel, dating back to 1950 for rainfall measurements.…”

Monitoring the Impact of Grazing on Rangeland Conservation Easements Using MODIS Vegetation Indices

“…Washington-Allen et al (2006) used Landsat time series to monitor degradation on rangelands and measure productivity, composition, soil erosion, and soil quality. More recently, Li et al (2012) have demonstrated a model based on MODIS EVI and NDVI to measure Net Primary Production and forage production in pastures with different grazing regimens in California. Despite both these advancements and landowner interest, remote-sensing tools are not widely applied in rangeland management (Butterfield and Malmstrom, 2006;Karl et al, 2012), and remote sensing is not used for monitoring RDM.…”

Temporal profiles of vegetation indices for characterizing grazing intensity on natural grasslands in Pampa biome

“…However, a limited number of studies have evaluated the temporal behavior of natural grasslands under different grazing intensities and have addressed the influence of management on the definition of vegetation dynamics. Regular observations of grassland conditions using vegetation indices can be employed to monitor biomass and can assist in management decisions that benefit species composition and forage production during livestock husbandry (Li et al, 2012), thus helping reconcile the conservation vs production dilemma (Carvalho and Batello, 2009).…”

“…Satellite imagery provides an important data source for monitoring vegetation cover dynamics because it generates objective information with adequate spatial and temporal characteristics (Li et al, 2012). The Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI) are considered indicators of plant growth and can be employed in the determination of correlated biophysical variables, such as the leaf area index (LAI), biomass, photosynthetic activity and grain yields (Xavier et al, 2006;Fernandes et al, 2011;Monteiro et al, 2012).…”