EPA REGION VII R-EMAP PROJECT: LANDSCAPE ANALYSIS AND CHARACTERIZATION TO SUPPORT REGIONAL ENVIRONMENTAL ASSESSMENT (LACRA) The University of Kansas Principal Investigators

Executive Summary The EPA Region VII R-EMAP project seeks to determine the condition of fisheries resources in the states of Missouri, Kansas, and Nebraska. Preliminary evidence from fish tissue studies has suggested that fisheries resources in these states have been adversely impacted by chemical pollutants. The Region VII R-EMAP study consequently focuses on the following questions: 1) What is the status of the health of fisheries in Region VII?, and 2) What associations exist between selected indicators of natural and anthropogenic stresses and indicators of fisheries health? To help answer these questions, Region VII conducted systematic field sampling based on a set of randomly selected hexagons using EMAP ecological indicator protocols. Under the LACRA study, the University of Kansas developed various landscape components, including composition and pattern, that were derived from several remote sensing sources and used to characterize area sampling units. A time-series of normalized difference vegetation index (NDVI) values derived from satellite data was also developed to characterize area sampling units. Correlation and regression analyses were used to find statistical relationships between the field data and the landscape components and NDVI data. Two hundred ninety randomly selected stream sites in Nebraska, Kansas, and Missouri were sampled once during late spring through summer of 1994 or 1995 for several parameters including: conductivity, turbidity, total phosphorus, nitrate-nitrite nitrogen, the Index of Biotic Integrity (IBI), and a habitat index (HI). Based on landscape data from watersheds that were delineated for each sampling location, interrelationships were examined between these water quality parameters and land use/land cover, the normalized difference vegetation index (NDVI) derived from AVHRR satellite data, and vegetation phenological metrics (VPMs) derived from time-series NDVI data. Statistically significant relationships were found between NDVI values and derived VPMs with the stream condition parameters (r values to 0.8, α = 0.05). The NDVI or VPMs were more highly correlated to the selected stream condition parameters than were the land use/land cover proportions. Knowledge of the general land use/land cover setting within the watersheds, however, was important for interpreting these relationships. The most common variables associated with the stream data were early spring NDVI values or VPMs associated with the date of onset of greenness. This finding suggests the possibility of forecasting summer iv stream conditions with spring AVHRR satellite data. Maps depicting the distribution of three sample parameters were developed that illustrate the use of these results. Such maps may be useful for …