Deriving site-specific assessment benchmarks for physical habitat from interagency networks of reference sites

Networks of interagency reference sites are commonly used to define benchmarks for assessing status and trend in ecological assessments (Stoddard et al. 2006). Development of these reference site networks to date has focused primarily on reference sites for macroinvertebrates and water quality (Ode et al. 2016, Miller et al. 2016). This focus has been due to clear regulatory mandates in the Clean Water Act, similarity of field protocols used (Rehn et al. 2007, need WQ citation), and empirical relationships in the literature tying land use alteration to alteration of water quality and biota (e.g. Vander Laan et al. 2013).  While the Clean Water Act addresses chemical, physical and biological integrity of the Nation’s waters, few states have specific physical habitat criteria. Physical habitat field protocols used differ widely, and empirical relationships tying land use alteration to local habitat alteration are scant (Allan 2004).

Use of physical habitat assessment data is receiving increasing attention in monitoring programs and more physical habitat data is becoming available. The BLM has a policy mandate to determine resource management plan effectiveness and land health status and trends. This includes maintaining and improving chemical, physical, and biological integrity of water resources . Specifics depend on administrative boundary unit but examples include “Maintaining stream channel integrity, channel processes and the sediment regime (including the elements of timing, volume, and character of sediment input and transport) under which the riparian and aquatic ecosystems developed ”. To meet these objectives, the BLM has developed a National Aquatic Monitoring Framework within the Assessment Inventory and Monitoring program within the BLM. This framework was developed to maximize compatibility with existing interagency monitoring protocols including the USFS Northwest Forest Plan’s Aquatic Riparian Effectiveness Monitoring Program (AREMP), the USFS PacFish InFish Biological Opinion Monitoring Program (PIBO MP), and EPA’s National Rivers and Stream Assessment (NRSA) surveys. Compatible indicators differ among programs but include percent fine sediment less than 2 mm, percent pools, canopy cover (overhead and bank), large wood frequency and volume, and bank angle (Figure 1). A compiled interagency dataset that includes these indicators is now available (Sully et al. 2023). Additionally, datasets such as EPA’s StreamCat dataset now make attempts to determine relationships between land use and local field data much easier. 

A Venn diagram showing protocol compatibility for each indicator and the number of unique site locations available for each indicator from 2000-2021. The four main sets are AIM with 2,615 independent sites, AREMP with 1,327, PIBO with 2,292, and EPA with 2,445. The subset of AIM, AREMP, and PBIO has 2,897 “Pools” sites. The subset of AIM, EPA, and PBIO has 5,253 “Sediment” sites. The subset of AIM and EPA has 4,519 “Canopy” sites and 4,746 “Large wood” sites. The subset of AIM and PBIO has 1,901 “Bank angle” sites.
Venn diagram showing protocol compatibility for each indicator and the number of unique site locations available for each indicator from 2000-2021

Our objective in this study is to develop site specific models predicting natural conditions for percent fine sediment less than 2 mm, geometric mean particle diameter, percent and frequency of pools, percent canopy cover (overhead and bank), large wood frequency and volume, bank angle, and percent undercut banks.  We will use these models to answer the following research questions: 1) What physical habitat indicators are most predictable across natural gradients? 2) What physical habitat indicators are most responsive to anthropogenic disturbance after accounting for natural environmental gradients? 3) Are there clear empirical relationships and thresholds between physical habitat indicators and anthropogenic disturbances that could be used to inform reference and degraded site classifications and management practices?

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