Monitoring Streams and Riparian Vegetation to Detect Effects of Grazing Management on Fish Habitat Using Multiple Indicators

Numerous studies have demonstrated the affects of livestock grazing on riparian and aquatic habitats and fish.   The general consensus among investigators has been that improper livestock grazing can degrade these habitats resulting in decreased fish productivity.   Most have concentrated on grazing effects to streambanks which, when degraded, affect stream temperature, channel erosion, sediment input, and hiding cover and suitable living space for fish.   More recently research in Wyoming demonstrated that improper grazing resulted in half the riparian vegetation, half the terrestrial invertebrates recruited to streams and trout diets, and also half the trout abundance compared to properly grazed riparian areas.   The complexity and diversity of grazing effects calls for a robust riparian monitoring protocol.   To be effective, the protocol must include techniques with enough precision and accuracy to detect changes through time, yet feasible and cost-efficient.   After a thorough review, the University of Idaho’s Stubble Height Review Team concluded that simple single indicators, such as stubble height, should not be used alone to assess the riparian management success of a grazing system.  Because riparian grazing should achieve, or make measurable progress towards achieving the desired conditions for fish, monitoring multiple indicators to evaluate both implementation success and management effectiveness is necessary.  To implement such monitoring, the interagency National Riparian Service Team, developed and published the BLM Technical Reference titled “Monitoring Stream Channels and Riparian Vegetation - Multiple Indicators – MIM” (TR-1737-23,  www.blm.gov/riparian).  It is based on the following objectives: 1) address multiple short- and long-term indicators, 2) measure the most important indicators relevant to detecting change, 3) use existing procedures to the extent possible, 4) improve efficiency through the use of electronic data collection, 5)  yield statistically acceptable results within realistic time constraints, and 6) provide useful data to inform management decisions.  The MIM protocol evaluates multiple indicators, based on existing, commonly used techniques.  Because multiple techniques are brought together in one protocol, and all the observations are made at the same time and place, the approach improves efficiency, reduces costs and time to sample, and allows statistical comparisons between short- and long-term variables.