National Aquatic Monitoring Framework FAQs

Is the National Aquatic Monitoring Framework (NAMF) a new BLM monitoring program?

What are common applications of the NAMF?

Is the NAMF intended to replace local-scale monitoring efforts?

Do I have to collect all of the aquatic core indicators anytime stream monitoring is conducted?

How is data collected at coarse spatial scales, such as Level III ecoregions, states, or field offices, relevant to individual field offices?

Why should I randomly locate sample points?

How are local or site-specific problems evaluated by the NAMF?

I have been collecting data for multiple years on one of the core indicators but using a different method. Do I need to change the method, and if so, how will historical data be incorporated?

 
 
 
 
 
 
 
 
 


 
Is the National Aquatic Monitoring Framework (NAMF) a new BLM monitoring program?

The NAMF is new, but many of its components build upon existing BLM monitoring and assessment programs. For example, the NAMF does not recommend indicators new to the BLM but, rather, consistent methods to measure some of the most common indicators contained within the land health standards (and to functioning stream systems). In addition to core indicators, the NAMF promotes integrated data collection throughout the BLM by providing guidance for selection of sample reaches, electronic data capture and storage and tools for consistent data analysis, and interpretation to inform management questions. Rather than a new process, the NAMF can be thought of as a standardized approach for how the BLM can meet multiple monitoring requirements in a consistent, quantitative, and credible manner.

 

 
What are common applications of the NAMF?

This framework has been designed to address several BLM monitoring needs, including:

  • Land use plan assessments and effectiveness monitoring.
  • Regional mitigation strategies.
  • Restoration effectiveness monitoring.
  • Assessing landscape-scale impacts resulting from permitted uses (e.g., grazing, oil and gas development, mining).
  • Prioritizing stressors to inform more intensive monitoring efforts.
  • Establishing ecoregional-, state-, or field office-level baseline conditions and trends.
  • Collecting national-scale data for Department of the Interior reporting measures and the annual Public Land Statistics publication.

 

 
Is the NAMF intended to replace local-scale monitoring efforts?

No, local monitoring to meet site- or project-specific data needs may require indicators beyond the NAMF aquatic core and contingent indicators. The AIM Strategy allows for flexibility to collect data on supplemental indicators to meet project-specific needs, in addition to the core and contingent indicators (see supplemental monitoring indicators in Section 7.3). Data collected under the NAMF should complement existing monitoring programs, not necessarily replace them, especially when supplemental information is needed to inform management of a particular land use. In developing the AIM Strategy, a review of numerous field office monitoring programs revealed similarities in the types of required data, particularly the need for information regarding the locations, amounts, conditions, and trends of aquatic resources. In such instances, the land health standards provide a framework for the monitoring and assessment of the condition of a consistent set of indicators, and the NAMF specifies a set of methods for doing so regardless of the spatial scale of inference.


 
Do I have to collect all of the aquatic core indicators anytime stream monitoring is conducted?

No, the core and contingent indicators may not be applicable to some monitoring types (e.g., use-based, compliance, restoration efficacy). However, where information for a core or contingent indicator(s) is required, the NAMF methods should be followed. If baseline condition and trend information is sought for a stream or population of streams, the NAMF should be applied.

 

 
How is data collected at coarse spatial scales, such as Level III ecoregions, states, or field offices, relevant to individual field offices?

The use of core indicators and consistent methods allows data to be compared among sites and through time, while minimizing sample error associated with disparate data collection methodologies. For example, sample points collected at the field office scale can be applied to local questions such as grazing permit renewals; however, additional sample points may be required (see the following question regarding probability-based site selection).

A second way to leverage data collected at broader spatial scales is for interpretation of locally collected data. Since BLM core monitoring data will now mesh with data collected by other field offices and agencies, locally collected data can be compared to the range of conditions among existing reference site networks to assess degrees of departure. Reference, or least disturbed, conditions set expectations for the conditions one would expect to occur in the absence of anthropogenic activities and thus facilitate objective data interpretation. The use of existing reference networks and analytical tools can save considerable time and money during local monitoring efforts, while also increasing the certainty and defensibility of management decisions.

 

 
Why should I randomly locate sample points?

Most monitoring programs benefit from a mix of targeted and probability-based (i.e., random) site selection. Targeted sites are appropriate for site-specific evaluations, where known problems occur, or to isolate the geographic extent of impacts, but when used as “representative” sites, they are subject to different interpretations of what is “representative” and may incorporate bias. Thus, targeted sites only allow the BLM to learn about the set of sampled locations and may underestimate the variability of indicators within the sampling area. Given the thousands of stream kilometers contained within any field office, probability-based site selection is a credible and efficient way to estimate the condition and trend of the entire population with known levels of uncertainty. Additionally, probability-based sample selection allows monitoring locations selected for one application to be used for other applications but at different spatial scales (i.e., data recycling in a statistically valid manner).

 

 
How are local or site-specific problems evaluated by the NAMF?

The NAMF is applicable to both local and regional monitoring questions. For both scales of questions, supplemental indicators may be required (e.g., fish assemblage composition and surveyed channel cross sections from Section 7.2) to address project-specific questions. Additionally, “season of use” type indicators may be required to assess local, use-based impacts (e.g., bank alteration and residual stubble height for cattle grazing). Such indicators can be used to inform decisions regarding the use(s) associated with the condition and trend of the NAMF indicators (e.g., the determination phase of a land health assessment). Furthermore, local condition and trend type questions may change the method by which sample points are located. For systems experiencing localized impacts such as placer mining (e.g., Section 7.2) or small-scale restoration, site selection could be targeted (i.e., nonrandom) to ensure sampling occurs in the impacted or restored area, respectively.

 

 
I have been collecting data for multiple years on one of the core indicators but using a different method. Do I need to change the method, and if so, how will historical data be incorporated?

The objective of the AIM Strategy is to standardize a minimum set of indicators and the methods for measuring the indicators across the BLM; therefore, it is recommended that field offices use the core indicator methodologies in instances where an NAMF indicator is being measured. To assess the feasibility of jointly analyzing “old” and “new” monitoring data, the BLM recommends simultaneous sampling using both methods for a period of time to assess the comparability of the resulting indicator values. In instances where two methods produce disparate results, correction factors can be applied if the magnitude and direction of the deviation is consistent through time.

 

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