AIM Q&A
- What is AIM/the AIM Strategy?
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The Assessment, Inventory, and Monitoring (AIM) Strategy provides a process for the BLM to collect quantitative information on location and abundance, condition, and trend of renewable resources on the nation’s public lands.
- What is the purpose of AIM?
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The purpose of AIM is to move the BLM toward an integrated data collection approach that includes three components:
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A standard set of core indicators and associated methods for terrestrial vegetation and soils as well as aquatic systems.
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A probability-based sampling framework that allows unbiased inference datasets collected in different areas and for different objectives to be aggregated at different scales (unbiased inferences).
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Integration of remote sensing and ground-based technologies to maximize the BLM’s capacity to cost effectively address management questions at multiple spatial scales.
AIM also strives to allow management of data as a corporate asset for multiple uses and improve data accessibility for the field and Washington Office.
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- How is AIM data used and what does AIM accomplish?
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AIM data provides the BLM and its partners with the information needed to understand terrestrial and aquatic resource location and abundance, condition, and trend and to provide a basis for effective adaptive management. The AIM Strategy moves the BLM toward a new paradigm in which core data describing resource condition are digitally collected in the field, stored in spatially enabled databases, managed in an enterprise data architecture environment, analyzed to determine effectiveness of management actions, and shared across BLM offices and interested publics.
- What is the difference between AIM and other monitoring efforts by the BLM?
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Many past BLM monitoring efforts have focused on addressing specific management needs for a single objective. In contrast, AIM’s goal is to use a consistent set of monitoring data for multiple resources at multiple scales. In other words, the BLM collects data once and uses it many times. Additional highlights of AIM are that it:
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Provides cross-program assessment of ecosystem health.
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Standardizes monitoring methods.
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Provides probability-based estimates (e.g., random sampling) with a known level of uncertainty.
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Provides scalable data (because of the random sampling based on a known sample area).
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Captures, stores, and analyzes data in a geospatially enabled database.
AIM complements existing monitoring programs and does not necessarily replace them, especially when they are necessary for the management of a particular land use. For example, utilization monitoring provides key information for managing livestock grazing at the local level.
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- What is the difference between core and supplemental indicators?
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Core indicators are the minimum information collected at each plot. These are essential for understanding ecosystem health and creating a standard dataset BLM-wide. In contrast, supplemental indicators are additional information that is collected to meet specific management objectives or local needs.
- How were the core indicators selected?
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The AIM Strategy focuses on detecting changes in three key attributes of ecosystem sustainability—soil/site stability, hydrologic function, and biotic integrity. Collectively, ecosystem status can be determined by comparing measured quantitative indicators of the three attributes to what is expected based on site potential. Terrestrial core indicators were developed by a collaborative process that synthesized knowledge and experiences of nearly 200 scientists, rangeland managers, and ecologists from different agencies and institutions. A large number of potential indicators were rated against 16 criteria, and the most general indicators with the broadest applicability to a range of management questions were selected. Aquatic core indicators were selected via a similar process by an interdisciplinary group of scientists from different agencies and institutions.
- Why are there random plots instead of representative/key area plots?
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Randomly selected monitoring plots—a sample of the landscape in which every possible plot has a chance of being selected—are a key part of the AIM Strategy. Random selection enables monitoring data to provide statistical estimates of indicators with known levels of uncertainty and to be used at multiple scales.
Random monitoring plot locations are generally stratified by ecological sites within management units. This enables the BLM to learn about the condition and trend of the ecological site/allotment as well as larger land units (for example, the effectiveness of the resource management plan across a field office, the status of sage-grouse habitat rangewide). In contrast, hand-selected, “representative” plots are subject to different interpretations of what is “representative” and may incorporate bias. Thus, using hand-selected plots may underestimate the variability of indicators within the sampling area.
- I have an AIM question; who should I contact?
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Emily Kachergis (ekachergis@blm.gov) at the BLM National Operations Center or Gordon Toevs (gtoevs@blm.gov) at the BLM Washington Office.