A comparison of three approaches for predicting C4 species cover of northern mixed grass prairie

The C4 composition of Canadian mixed-grass communities is more sensitive to environmental change than other grasslands. Reliable methods of detecting such changes are necessary if these landscapes are to be properly managed. One approach is to use satellite remote sensing systems. Various studies have shown that the asynchronous seasonality of C3 and C4 species allows the relative abundance of each photosynthetic type to be estimated using temporal trajectory indices (TTIs) of sensor-derived normalized difference vegetation index (NDVI). In this study, we compared three approaches for predicting C4 species cover at Grasslands National Park (GNP) (Saskatchewan, Canada). TTIs related to Approach I were calculated from plots of NDVI vs. day-of-year (DOY). TTIs related to Approach II were calculated from plots of normalized cumulative NDVI vs. growing degree day (GDD). TTIs related to Approach III were calculated as ratios of early-season NDVI to late-season NDVI. Our analyses were conducted at two separate ecological scales. A within-community analysis used field-sampled data from upland grassland to compare techniques at sampling resolutions of 0.5, 2.5, 10, and 50 m. An across-community analysis compared techniques using a vegetation survey of the GNP region and TTIs calculated from Advanced Very High Resolution Radiometer (AVHRR) data (1 km). At both scales, TTIs related to the timing of specific phenological events were the best predictors of C4 species cover. While all techniques performed well in the within-community study, Approach III performed best. Here, the predictive ability of each approach was weak at a resolution of 0.5 m but stronger at 2.5, 10, and 50 m resolutions. We also found that the optimal sampling dates for Approach III fell within a certain GDD range. This is encouraging for the a priori selection of sample dates, which would make the need for full seasonal time series redundant. In the across-community analysis, the AVHRR-derived Approach II TTIs were better able to discriminate among grasslands of different C4 composition than any other technique (overall accuracy=74%). However, for some C4 cover classes, the predictive accuracy of this approach was low. While these results are encouraging for the use of spectral data in monitoring the C4 cover of northern prairie, various research issues remain. At the within-community level, these include (a) further attempts to define objective criteria for the a priori identification of sampling dates for Approach III, and (b) and the extension of such studies to other growing seasons and community types/grassland regions. At the across-community level, these include the expansion of such techniques to a larger geographical region that contains a wider range in C4 cover values and land use types (e.g. ungrazed vs. grazed grasslands).