How to Use this Website
The AIM Landscape Toolbox website is provided by USDA-ARS Jornada to provide information and tools for each step of the AIM implementation process. This website guides users through a step-by-step process for designing BLM Assessment, Inventory, and Monitoring (AIM) projects. If you are beginning an AIM project, it is best to begin with the Planning & Project Implementation 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.
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, cross-program 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 approach is based on five key elements: 1) a standardized set of core and contingent indicators for both terrestrial and aquatic ecosystems, 2) statistically valid sampling design (where appropriate), 3) a structured implementation process, 4) electronic data capture, and 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 Fact Sheet.
Standard Core Indicators and Methods
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.
|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 Between Plant Canopies|
|Streambed particle size||Vegetation Composition|
|Floodplain Connectivity||Vegetation Height|
|Large Woody Debris|
|Macroinvertebrate Biological Integrity|
|Riparian vegetation cover and and structure*|
Statistically Valid Sampling Design (where appropriate)
The heart of an AIM project is a statistically valid sample design. What that means in practice is that, within a landscape of interest, monitoring information is gathered at predetermined locations that were randomly identified during the design stage. During the randomization process, every possible location has a chance of being selected, which enables one to report on the condition and trend of all monitored renewable resources within an area of interest with known levels of precision and accuracy. Additionally, by using similar field methods among monitoring efforts, data can be combined among monitoring efforts and used to inform land management decisions at multiple spatial scales and across data needs. However, to realize these benefits, sample designs must be conducted and implemented in a consistent, compatible manner including the geospatial layers used to define the study area.
Structured Implementation Process
AIM follows a structured implementation framework. Each effort begins by collecting background information, including what is known about the ecosystem, critical management questions, and regulatory requirements. Monitoring objectives, indicators, and activities are planned and implemented over the long-term. Periodic analysis and reporting of monitoring data inform an iterative process of adaptive management, by which land managers learn from and adjust their management actions. Sound data management, including detailed records, quality assurance/quality control, and storing data in a national geospatial infrastructure are key components of this framework.
Collectively, AIM information provides a basis for land managers to adaptively manage resources, improve understanding of the ecosystem, and adjust monitoring efforts as necessary using a well-documented and consistent approach. Using a structured implementation process provides additional support to project leads in the event that the data collected is ever challenged.
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 examples of how BLM staff are using AIM data to inform decisions of many kinds.