Protocol for monitoring standing crop in grasslands using visual obstruction

Abstract

Assessment of standing crop on grasslands using a visual obstruction technique provides valuable information to help plan livestock grazing management and indicate the status of wildlife habitat. The objectives of this study were to: (1) develop a simple regression model using easily measured visual obstruction to estimate standing crop on sandy lowland range sites in the Nebraska Sandhills, (2) provide sampling and monitoring suggestions in the use of visual obstruction on this grassland type, and (3) compare the visual obstruction technique to the standard clip and weigh procedure. Visual obstruction precisely predicted average standing crop dry weights for the sandy lowland range sites (r2=0.88). A prediction accuracy of ± 295 kg ha-1was found using a test data set. Two sampling options (A and B) were evaluated using a 2-stage sampling protocol. Option A (1 transect/quarter section) provided more precise estimates applicable to extensive grasslands than option B. However, option A was not applicable to a section (259 ha) or a few sections. Option B (3 transects/section) provided estimates applicable to each section and to the entire area, but it required more intensive sampling than option A to attain the same precision. The visual obstruction technique provided more precise estimates of standing crop than the standard clip and weigh technique when clipping and weighing up to 6 plots per transect. When 7 or more clipped and weighed plots per transect were sampled, standing crop estimates were more precise than using visual obstruction readings. However, since 20 visual obstruction readings/transect (25 minutes) can be sampled in about half the time spent clipping and weighing 6 plots/transect (45 minutes), visual obstruction in combination with a previously estimated regression model provides a simple, reliable, and cost effective alternative to the clip and weigh technique. Regression models should be developed for other grassland types following the methodology described in this paper.