From Information to Action: Monitoring Objectives, Benchmarks and Required Proportions
Monitoring objectives help translate information to action in natural resource management. These statements establish quantitative guidelines to help us determine if the management goals were achieved. For example, robust monitoring objectives can answer the following types of questions: Is there enough suitable sage grouse habitat on the landscape? Are watersheds functioning properly? Are management actions maintaining the health of the public lands? As outlined in the Developing Monitoring Objectives section of the Monitoring Design Worksheet, monitoring objectives at a minimum should include: 1. the focal indicator(s), 2. quantitative benchmarks or thresholds for each indicator, and 3. the proportion of the landscape that is required to meet a given benchmark.
Benchmarks are a key component of every monitoring objective. Benchmarks are indicator values, or ranges of values, that establish desired conditions and are meaningful for management. Benchmarks are used to determine if observed indicator values at assessed points (i.e., monitoring reaches or plots) are within the range of desired conditions. Conversely, failure to set benchmarks can make it difficult to interpret monitoring data. For example, achieving a plant density benchmark value following a seeding treatment may tell you that the project was successful; where failure to meet the benchmark may trigger reevaluation of the seeding methods. On the other hand, observed electrical conductivity (EC) values characterize the amount of cations and anions dissolved in stream water at a monitoring location, but without appropriate benchmarks, these observed values cannot be used to assess condition or the attainment of management objectives.
When considering an area with multiple monitoring locations, some amount of failure to achieve a benchmark is often acceptable. Natural events such as floods, droughts, fire and disease result in natural variability across a landscape. For this reason, monitoring objectives also include the proportion of the landscape that is required to meet a given benchmark. For example, achieving a benchmark density of plants on 80% of seeded acres can indicate success, even if 20% of the acres did not meet the benchmark value. If monitoring information shows that an insufficient amount of the resource has met a benchmark, then management changes will be triggered.
Benchmarks, along with associated required landscape proportions, provide a way to objectively operationalize policy statements such as: “take appropriate action” to make “significant progress toward fulfillment” of land health standards.
Example Monitoring Objectives, with Benchmarks and Required Proportions
- Soils Land Health Standard: In the grazing allotment, maintain soil aggregate stability of 4 or greater on 80% of lands with 80% confidence over 10 years.
- Watershed Function within Land Use Plan Area: Maintain bank stability of greater than or equal to 75% for 80% of perennial wadeable streams in the planning area with 95% confidence over 10 years.
- Sage Grouse Habitat within Land Use Plan Area: In all SFA and PHMA, the desired condition is to maintain all lands ecologically capable of producing sagebrush (but no less than 70%) with a minimum of 15% sagebrush cover or as consistent with specific ecological site conditions over 5 years.
Reporting Monitoring Results with Benchmarks
Using benchmarks to interpret monitoring information is not a new concept for land managers. However, applying benchmarks to estimate the proportion of a landscape that achieves benchmark conditions is new. To accomplish this, first, monitoring locations are assigned a condition class (e.g., meeting vs. not meeting the benchmark) based on the departure of observed indicator value(s) from the benchmark(s). Importantly, benchmarks can vary for different monitoring locations according to biophysical characteristics and ecological potential (see Setting Benchmarks). The use of benchmarks and related condition classes enables you to report the proportion of the landscape meeting objectives even across variable landscapes, simplifying stratification and reducing sample size requirements. After condition classes are assigned, with a probabilistic monitoring design, you can combine site-based results to estimate the proportion of the landscape that is meeting or not meeting objectives. An example monitoring result from a benchmark approach could be: 90% of the grazing allotment has sagebrush height of 30 cm or higher.
References
Elzinga, C. D.W. Salzer and J.W. Willoughby. 2003. Chapter 4: Management Objectives. In Measuring and Monitoring Plant Populations. BLM Technical Reference 1730-1. Denver, CO.
Hill, R.A., C.P. Hawkins, and D.M. Carlisle. 2013. Predicting thermal reference conditions for USA streams and rivers. Freshwater Science 32: 39–55.
Hughes, R.M., D.P. Larsen, and J.M. Omernik. 1986. Regional Reference Sites: A Method for Assessing Stream Potentials. Environmental Management 10 (5): 629–635.
Hawkins, C.P., R.H. Norris, J. Gerritsen, R.M. Hughes, S.K. Jackson, R.K. Johnson, R.J. Stevenson. 2000. Evaluation of the use of landscape classifications for the prediction of freshwater biota: synthesis and recommendations. Journal of the North American Benthological Society 19:541-556.
Hawkins, C. P., J. R. Olson, and R. A. Hill. 2010. The reference condition: predicting baselines for ecological and water-quality assessments. Journal of the North American Benthological Society 29:312-358
Stiver, S.J., E.T. Rinkes, D.E. Naugle, P.D. Makela, D.A. Nance, and J.W. Karl, eds. 2015. Sage-Grouse Habitat Assessment Framework: A Multiscale Assessment Tool. Technical Reference 6710-1. Bureau of Land Management and Western Association of Fish and Wildlife Agencies, Denver, Colorado.
Stoddard, J.L., P. Larsen, C.P. Hawkins, R.K. Johnson, and R.H. Norris. 2006. Setting expectations for the ecological conditions of running waters: the concept of reference conditions. Ecological Applications 16:1267-1276.
USDA NRCS. 1997. Chapter 3: Ecological Sites and Forage Suitability Groups. National Range and Pasture Handbook. Rev. 1, 2003.