AIM Monitoring Project DesignWorksheet
This worksheet provides a step-by-step template for designing BLM Assessment, Inventory, and Monitoring (AIM) projects. For additional information on the concepts described here, see the AIM SharePoint site (log in with BLM email address and BLM email password) and the AIM Landscape Toolbox site. We encourage you to work through the implementation steps as a field office, but completion of the worksheet should be done in coordination with the AIM team at the NOC. To request assistance contact Emily Kachergis (), AIM Terrestrial Implementation Lead at the BLM National Operations Center, or Scott Miller (), AIM Aquatic Implementation Lead at the BLM National Operations Center.
The process of designing and implementing a monitoring and assessment project can be broken down into a series of steps (Figure 1). This template captures the development of monitoring program objectives, study area specification, sample design, and steps to ensure data quality (Figure 1, Steps 1 -7).
The steps in Figure 1 are intentionally broad. They provide general guidance while also recognizing that each monitoring project has unique needs and not all parts of each step may be necessary. For some steps, standard AIM protocols and language are already in place. The steps are listed in the order they are normally completed, but there is no “single” way to design a monitoring program and the steps should be viewed as an iterative process. Each of the first seven steps illustrated in Figure 1 is described in detail in the Monitoring Manual for Grassland, Shrubland, and Savanna Ecosystems, Volume II (.
Designing an AIM project is an iterative process. After completing each step, be sure to review the results of previous steps, as the outcome of later steps may cause a need to modify earlier decisions. Revisiting earlier steps is helpful and often necessary. For example, design decisions completed in Step 3 often reveal issues that lead to new management or monitoring objectives (Steps 1 and 2).
Figure 1. Process for developing, implementing, and interpreting AIM projects to inform management decisions. Note that decisions made in previous steps may be revisited and revised when necessary. Adopted from BLM Technical Note 445.
Step 1: Develop management objectives; select additional ecosystem attributes and indicators to monitor
Step 1a: Develop management objectives
●One of the first and most important steps in the AIM process model is the identification of management objectives that will be the focus of your monitoring effort. Management objectives should provide the context for why monitoring information is needed and how it will be used. Together, management and monitoring objectives (Step 2b) inform all subsequent decisions, including where and how points are selected and what will be measured and at what frequency.
●To begin this effort, work as an interdisciplinary team to review existing documents which describe the management history, planned management actions, previous data collection efforts, and relevant policy. Examples are listed below. Since many of these documents refer back to the Land Health Standards, we suggest that Land Health Standards are a good place to start for developing management objectives.
oBLM Land Health Handbook (4180)
oLand Health Standards:
▪Ecological processes
▪Watershed function
▪Water quality and yield
▪T&E and Native Species
●Sage grouse management objectives
oResource Management Plans
oCommitments in NEPA documents or Biological Opinions
●During this step, it is helpful to think broadly across programs and jurisdictions to identify the desired conditions in the landscape of interest. Then determine whether efficiencies can be gained in the combination of monitoring and assessment efforts if they share similar management objectives. If multiple management objectives are to be addressed, ensure that adequate resources exist (e.g., sample points, crews, funding), as multiple objectives usually translate to more sample points.
●Based on this review, what management objectives would you synthesize? Provide citations to the relevant supporting background documents. Since many of these documents relate back to the Land Health Standards for the area, Land Health Standards are a good place to start. Then add objectives not covered by Land Health Standards as needed.
oExample: Ensure achievement of land health standards for T/E species; maintain sage grouse habitat according to the habitat standards as described in the Resource Management Plan.
oExample: Manage streams and rivers using the sustained yield principle and in compliance with Federal Land Policy and Management Act and the Clean Water Act.
Step 1b: Select additional ecosystem attributes and indicators to monitor
●Review the terrestrial and aquatic core and contingent indicators (TN440, TR 1735-1). These were selected to both have relevance across BLM managed ecosystems and to address many BLM monitoring and assessment requirements, including Land Health Standards. For example, vegetative cover and composition data might be useful to address habitat, grazing, and fire recovery objectives. If there are management and monitoring objectives which will not be satisfied by the Core or Contingent Indicators, consider adding supplemental indicators. See additional guidance in Step 4.
Step 2: Set the study area and reporting units; develop monitoring objectives
Step 2a: Set the study area and reporting units
●What is the geographic extent of the resource (e.g., vegetation, animals, streams) you want to report on (e.g., grazing allotment, 5th field HUC, field office, district, state)?
●What geospatial layers will you use to define the study area (e.g., state BLM ownership layer, RMP boundaries)?
●What are the desired reporting units (e.g., grazing allotment, 5th field HUC, field office, district, state)?
oReporting units are the geographic areas for which indicator averages and error estimates will be computed and thus minimal sample sizes are required. Reporting units can be nested within the study area depending on the monitoring objectives.
Step 2b: Develop monitoring objectives
●Objectives are quantitative statements that provide a means of evaluating whether management goals or objectives were achieved. Monitoring objectives should be specific, including what indicator(s) will be reported and over what geographic and temporal scale, quantifiable, and attainable based on available resources and the sensitivity of the methods. Quantitative monitoring objectives may be available in your resource management plans (e.g., for sage grouse, Clean Water Act requirements) or they may be developed in the planning process.
●The use of monitoring data to inform management decisions requires the establishment of benchmarks or thresholds, which, if exceeded, will trigger changes in management (e.g., Table 1) or conversely the success of a given project or action. When establishing monitoring objectives, the AIM project team should also start identifying thresholds and allowable departures from a given threshold. These values can be gleaned from policy (e.g., sage grouse habitat standards; state water quality standards), scientific literature, and professional judgment. To assist in this process, start developing both thresholds and allowable departures from a threshold for each of the indicators of interest by using columns 3-5 of Table 1. This exercise will quickly reveal indicators for which you will need to seek professional judgement, the development of ecological site descriptions, or other resources to aid in future data interpretation.
●At a minimum, monitoring objectives should include an: 1. indicator; 2. management objective (i.e., threshold) for the indicator; 3. allowable extent of departure for the indicator; and 4. reporting unit.
●Example monitoring objectives:
Terrestrial:
▪Management objectives: Ensure achievement of land health standards for T/E species; maintain sage grouse habitat according to the habitat standards as described in the Resource Management Plan.
●Monitoring objective: Determine whether sagebrush cover of 15% or greater is maintained across 70% of the Resource Management Planning area with 80% confidence.
oAquatic:
▪Management objective: Manage streams and rivers using the sustained yield principle and in compliance with Federal Land Policy and Management Act and the Clean Water Act.
●Monitoring objective: Determine whether salinity levels are at or below 300 µS/cm in 90% of perennial wadeable stream miles in the planning area with 80% confidence.
Step 4: Select and document supplemental monitoring methods; estimate sample sizes; set sampling frequency; develop implementation rules
Step 4a: Select and document supplemental monitoring methods (if required)
●If supplemental indicators are necessary to meet management and monitoring objectives, evaluate the core methods to determine if these supplemental indicators can be calculated using a core or contingent method. If they cannot, select a supplemental method. If possible, select supplemental methods that are used by other national monitoring programs and are documented clearly in a peer-reviewed method manual.
●Examples of supplemental methods
○Terrestrial:
■Supplemental Indicator: Sagebrush height
●Supplemental method: Not necessary, this can be derived from the vegetation height core method described in the Monitoring Manual for Grassland, Shrubland, and Savanna Ecosystems (
■Supplemental Indicator: Forb density for vegetation treatment effectiveness monitoring.
●Supplemental Method: Plant density as documented in the Monitoring Manual for Grassland, Shrubland, and Savanna Ecosystems (
○Aquatic:
■Supplemental Indicator: Fish density and species composition
●Supplemental Method: two-pass depletion estimate with blocknets to ensure a closed population (Zale et al. 2013)
■Supplemental indicator: Fecal coliform
●Supplemental method: State regulatory agency methods, which call for a minimum number of samples (e.g., 10) over a specified time period (e.g., month)
Step 4b: Estimate sample sizes
●The required number of monitoring plots or reaches is one of the most commonly asked questions. This question is critically important as it determines both the requisite resources required by a project and the resulting precision of indicator estimates (e.g., stream bank stability is estimated at 70% +/- 40% versus 70% +/- 10%, with the latter requiring greater sample sizes).
●Determining the number of monitoring plots or reaches is a function of: 1. the desired indicator estimates from the survey data; 2. the precision and confidence for each estimate; 3. the variability expected for a given indicator; and 4. available resources. Consult with the NOC to develop your final answer, but considerations may include:
○The number of acres or stream kilometers in the study area and/or reporting unit (sample size increases as these increase)
○Physiographic or other variability in the study area (sample sizes increase as indicator variability increases)
○Required confidence level in your data - what are the consequences of saying a standard is not attained when it really is and visa-versa (sample sizes increase with higher levels of confidence [e.g., 80% versus 95%])
○Magnitude of change you seek to detect (sample sizes decrease for bigger changes)
○Funding and personnel availability (higher samples sizes require more resources)
●Most management and monitoring objectives require estimating both the condition of a given indicator at a single point in time, as well as the magnitude of change through time. The former requires consideration of the variability among plots or reaches, while the latter is influenced by the variability through time.
●With some pilot data on hand or by using some worse case scenarios, you may be able to use a sample size calculator, such as:
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■Type of analysis: Confidence interval (CI) for one proportion
■Finite population: Yes, type in area or stream kilometers
■pi (variance estimate, assume the worst case of 0.5 or 50%)
■Confidence (your choice, but we recommend between 80 and 90%
Step 4c: Set sampling frequency (if required)
●Detecting change in condition through time (i.e., trend) is a common monitoring objective that requires an interval to be set for plot or reach re-visits through time. Factors to consider when setting sampling frequency include:
○The proportion of sites to be revisited
○What sampling frequency makes sense relative to the disturbance or management event? For example, ES&R monitoring dictates annual re-visits for three years, whereas monitoring stream geomorphic changes following livestock removal might occur on a 3-5 year basis, and changes in upland condition might occur over 5-10 years.
○Available resources (e.g., budget or staff)
●Some projects will not need to determine sampling frequencies on account of various project constraints or intentional design.
Step 4d: Develop implementation rules
●Review standard AIM Implementation Rules (forthcoming). Customize if necessary and in consultation with the NOC.
Step 5: Collect and evaluate pilot data to determine sampling sufficiency and the validity of the strata (if available)
●In many cases, pilot or other data are available from nearby AIM sampling, target sampling (e.g., key areas), or other localized monitoring efforts. A brief review of these data can help to evaluate your strata and determine required sample sizes.
●Use regional data from AquADat or TerrADat as inputs in the sample size calculator, such as this one:
●Consult with the NOC, USU, and Jornada to implement this step.
Step 6: Apply stratification and select statistically valid monitoring locations
●Standard AIM statistically valid sample designs are developed using the GRTS method (Stephens and Olsen 2004). Consult with the NOC, USU, and Jornada to implement this step.
●Review points to make sure they will meet design criteria described in steps 1-3.
●If needed, refine the sample design.
Step 7: Develop quality assurance and quality control (QA and QC) procedures and data management plans
●Data management for BLM AIM projects is supported by the NOC through digital data collection and management.
○Terrestrial data collection and local storage using the Database for Inventory, Monitoring, and Assessment (DIMA, and is standard for BLM AIM projects. These data are then rolled up into TerrADat, which serves as a national repository for terrestrial AIM data.
○Aquatic data collection and local storage using AquADat, which includes a field data collection application, centralized data storage and analysis capabilities.
●Review the standard QA and QC procedures for AIM projects, which can be found in the Monitoring Manual for Grassland, Shrubland, and Savanna Ecosystems ( the Terrestrial AIM QC Protocol (forthcoming), and in the Aquatic QC manual.
●Fill QA/QC Timeline Worksheet in Appendix B.
Literature cited/additional resources:
Stevens, D. L., Jr. and A. R. Olsen (2004). "Spatially-balanced sampling of natural resources." Journal of American Statistical Association 99(465): 262-278. Abstract (pdf 9KB) Document (pdf 1.4MB)
Table 1. Example management objectives, indicators, and the methods to be used for determining condition thresholds and the proportion of allowable departure of a resource from a condition threshold before changes in management are required. Combined, columns 2-5 form the monitoring objectives for this effort.Management objective / Monitoring Indicator (core + supplemental) / Condition determination method / Condition thresholds / Proportion of allowable departure (e.g., acres or stream km)
Special Status Species Habitat (sage grouse) / Sagebrush cover / Research/professional judgment (threshold in Sage Grouse Plan Amendment for Nesting Habitat) / e.g., >=20% / e.g., 20%
Water quality / specific conductance / State standards / 700 µS/cm / e.g., 20%
Appendix A: Glossary
Core Indicators: measurable ecosystem component applicable across many different ecosystems, management objectives, and agencies. Core aquatic indicators are recommended for application wherever the BLM implements monitoring and assessment of wadeable perennial streams.
Contingent Indicators: measurable ecosystem component having the same characteristics of cross-program utility and consistent definition as core indicators, but that are measured only where applicable. Contingent indicators are not informative everywhere and, thus, are only measured when there is reason to believe they will be important for management purposes.
Supplemental Indicators: a measurable ecosystem component that is specific to a given ecosystem, land use, or management objective. No specific supplemental indicators or associated methodologies are recommended in the NAMF given the diversity of probable indicators.
Stratification: Stratification is dividing a population or study area (e.g., rangeland landscape) up into subgroups or subunits called strata. Stratification enables data collection focused on management questions, supports data interpretation, helps land managers set realistic monitoring objectives – improves efficiency in monitoring efforts, and separates and reduces variability
Appendix B: QA/QC Timeline Worksheet
Task / Who / When / Date to be CompletedAttended training/ learn field protocols / Anyone collecting field data (i.e., field crews) / Before data collection begins
Calibration / Anyone collecting field data (i.e., field crews) / Before data collection begins and various times throughout field season (i.e., changing landscapes, etc.)
QC checks / Field Crew Lead / Daily (i.e., before you leave a plot) and weekly (i.e., after a hitch)
Early- and mid-season check / Project Lead / After the field crew’s first hitch and half way through the field season
End of season QC check / Crew Lead / After all data collection has ceased
End of season QC check / Project Lead or State Lead / After crew lead has finished QC check
End of season QC check / NOC / After project lead/state lead has signed off on the data
Data Upload / NOC / After last round of QC
Example of a completed AIM Monitoring Project Design Worksheet focusing on:
Land Use Plan Effectiveness with Intensifications in Sage Grouse Habitat
This example shows how a field office might walk through the steps described above. However, remember that this is a generic example. Your field office could have different, and likely more, objectives.
Step 1: Develop management objectives; select additional ecosystem attributes and indicators to monitor
Field office management objectives are presented in the State Land Health Standards (LHS), Resource Management Plan and the Sage Grouse RMP Amendment; All highlight the importance of healthy ecosystems, including vegetation, soil, water, and wildlife. In addition, RMP goals highlight the importance of monitoring for improving understanding of ecosystem functioning and carrying out adaptive management.
The following represents a synthesis of ecosystem management objectives from the LHS, RMP, and Sage Grouse Plan Amendment (Table 1):