Introduction to AIM

How to Use this Website

The AIM landscape toolbox website was created to provide information and tools for each step of the AIM implementation process. This website provides a step-by-step template for designing BLM Assessment, Inventory, and Monitoring (AIM) projects. If you are beginning an AIM project, it is best to begin with the Planning & Funding tab and work through to the Analysis & Reporting tab. 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.

What is AIM?

The Assessment, Inventory, and Monitoring (AIM) program was initiated to improve the effectiveness of monitoring activities on BLM land. The AIM program provides a standardized process for the BLM to collect quantitative information on the status, condition, trend, amount, location, and spatial pattern of resources on the nation’s public lands. The BLM uses data derived from the AIM program to make necessary management adjustments to meet resource management objectives described at project, activity plan, resource management plan, and national program levels.

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The “BLM Assessment, Inventory, and Monitoring Strategy for Integrated Renewable Resources Management” (AIM Strategy) was completed in 2011 in response to a request from the Office of Management and Budget. The strategy describes an approach for integrated, crossprogram assessment, inventory, and monitoring of renewable resources (e.g., vegetation, soils, water, fish and wildlife habitat) at multiple scales of management. Following the AIM Strategy, the BLM is modernizing its resource monitoring approach to more efficiently and effectively meet local, regional, and national resource information needs.

The AIM monitoring approach is based on five key elements: 1) a standardized set of core and contingent indicators for both terrestrial and aquatic ecosystems, 2) a statistically valid sampling design, 3) a structured implementation process, 4) electronic data capture, 5) integration with remote sensing. These five elements are thoroughly described in BLM Technical Note 445 and a brief description of each element is provided below and in the AIM factsheet

Standard Core Indicators

The core terrestrial and aquatic indicators were selected because the are known to be both ecologically relevant and clearly tied to rangeland health and state and federal clean water standards. It is important to note that not only are the indicators standardized, but the methods used to collect the data are also standardized.  This means that the same data are collected in the same way at each sampled site. The use of standardized methods helps the ensure that AIM data are comparable.
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Some resource management questions may not be answered by using the core indicators alone.  In this case, project managers may want to collect additional data in order to compute one or more contingent or supplemental indicators. A basic table of core indicators is shown below, but the core and contingent indicators for terrestrial and aquatic ecosystems are a described in detail in the following two technical documents: the  BLM Core Terrestrial Indicators and Methods – Technical Note 440, and the AIM National Aquatic Monitoring Framework Technical Reference 1735-1. Supplemental indicators are those indicators that are not listed as core or contingent but that resource mangers need to measure in order to meet their monitoring objectives.

Aquatic Core Indicators Terrestrial Core Indicators
Acidity (pH) Bare Ground
Conductivity Non-native Invasive Species
Temperature Plant species of Management Concern
Pool depth, length, and frequency Proportion of Large Gaps in Plant Canopy
Streambed particle size Vegetation Composition
Floodplain Connectivity Vegetation Height
Large Woody Debris
Macroinvertebrate Biological Integrity
Riparian vegetation cover and and structure*
Canopy Cover
Statistically Valid Sampling Design

The heart of an AIM monitoring project is a statistical design. What that means in practice is that, within a project area, monitoring activities are carried out at predetermined locations that were randomly identified during the design stage. Because the locations are not hand-picked, we can make larger inferences from AIM data and more robustly describe the resources within the project area than that if we use the traditional “targeted” approach (e.g. key areas, use areas, etc).

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Probabilistic sample designs require structured implementation in order to maintain statistical validity. Probabilistic sample designs randomly sample a defined target population.  In landscape monitoring, the target population is the study area or resource that you seek to report on and each sample point represents a site. Probabilistic sampling enables us to learn about the entire study area because every point in the study area has a chance of being sampled.

Structured Implementation Process

The BLM has begun collecting and analyzing AIM monitoring data in a variety of locations on several different scales (see Current AIM projects) and all of these efforts have been coordinated with each other. This coordination ensures that monitoring efforts are not being duplicated, and that resource managers and specialists are aware of and able to use data that others have collected.

Electronic Data Capture

AIM data is collected on tablet computers that have been weather-proofed.  AIM-specific data collection applications are used on the tablets so that field technicians can enter their data in a format that is readily compatible with the AIM databases (Aquadat and TerraDat).  Electronic data capture at the time of sampling maximizes data collection efficiency and minimizes data entry errors.

Integration with Remote Sensing

Remote sensing refers to the acquisition of resource data collected by any device (e.g., satellites or lowflying aircraft) not in direct contact with the object of interest. Field-collected monitoring data can be integrated with remotely sensed data, such as vegetation maps produced from satellite imagery. Remotely sensed data can extend the utility of some field data by providing the location, amount, and spatial pattern of resources and the status, condition, and trend of these resource attributes across broad geographic extents.

Want to know more?

Check out some maps of the BLM’s current AIM projects.

 

Additional Resources
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