Glossary

This website is meant to be accessible, but sometimes the language has to be technical to be accurate and precise. The following are some of the most common technical terms used.

AIM: The Assessment, Inventory, and Monitoring program which provides an approach for integrated, cross-program assessment, inventory, and monitoring of renewable resources at multiple scales of management.


Analysis: The process of turning monitoring data into information to answer a question.


AquADat: National Aquatic monitoring Database.


Base Points: The original set of points in a panel of a design which are intended to be sampled in a given year.


Benchmarks: Indicator values, or ranges of values, that establish desired conditions and are meaningful for management.  Benchmarks are used to compare observed indicator values at assessed points to desired conditions.  For example, achieving a benchmark value of plant density may tell you that a seeding project was successful; failure to achieve it may trigger reevaluation of seeding methods.  Likewise, observed conductivity values characterize the amount of dissolved cations and anions in water at an assessed point, but without appropriate benchmarks, such values lack context and cannot be used to assess condition or the attainment of management objectives.  Benchmarks for a given indicator may vary by potential (e.g., Ecological Sites) thus different benchmark groups may be necessary within a project area so that points are understood as meeting or not meeting an objective relative to potential. Also see a more detailed discussion of benchmarks


Benchmark Group: A geographic area or group of monitoring points that have the same benchmark for evaluating the success of a particular monitoring objective.  For example, if you have points across your entire field office but want to  evaluate a sage grouse habitat objective, only the points that are within sage grouse habitat should be considered for that particular objective.  Likewise, the ecoregion, ecological site or stream type, the evaluation area or stream type must be taken into account for determining whether an objective is met when benchmarks vary by ecoregion or ESD.  


Biophysical Setting (BpS): A remote sensing-derived layer is conceptually very similar to NRCS Ecological Sites.  BpS represents the vegetation that may have been dominant on the landscape prior to Euro-American settlement.  BpS is based on both the current biophysical environment and an approximation of the historical disturbance regime. BpS describe the following physical characteristics of a BpS environment: vegetation, geography, biophysical characteristics, succession stages, and disturbance regimes (and major disturbance types). For more information see the LANDFIRE BpS website. (Landfire, 2017)


Condition: The status of a renewable resource in comparison with a specific reference value or benchmark (adapted from Bureau of Land Management Rangeland Resource Assessment-2011).  When describing condition, a condition category may be assigned (e.g., Suitable, Marginal, Unsuitable or Minimal, Moderate, or Major departure) relative to the benchmark or reference value.  


Confidence Interval: Range of values that likely includes the true value of a population mean.  Confidence intervals help understand uncertainty in indicator estimates.  For example, an 80% confidence interval indicates that 80% of sampling events will result in estimates that fall within this range; 20% will not.  The confidence level (e.g., 80%) indicates the probability that the confidence interval includes the true value and is chosen by the monitoring data user.  Also see Elzinga et al. 2003 or any statistics textbook.


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.


Core Indicators: Measurable ecosystem components applicable across many different ecosystems, management objectives, and agencies.


Data Management: Organizing and storing data so that they can be accessed and used to create information for management decisions.


DIMA: Database for Inventory, Monitoring, and Assessment (DIMA) is an MS Access application developed by the Jornada Experimental Range to collect field data, manipulate data in the office, and run preliminary reports. DIMA is the Terrestrial AIM electronic data capture tool and can be found here.


Ecological Site Descriptions (ESDs): Information and data pertaining to a particular ecological site is organized into a reference document known as an Ecological Site Description (ESD).  ESDs function as a primary repository of ecological knowledge regarding an ecological site.  ESDs are maintained on the NRCS Ecological Site Information System (ESIS), which is the repository for information associated with ESDs and the collection of all site data. (NRCS, 2017)


Ecological Sites: An ecological site is defined as a distinctive kind of land with specific soil and physical characteristics that differ from other kinds of land in its ability to produce a distinctive kind and amount of vegetation and its ability to respond similarly to management actions and natural disturbances. For more information visit the NRCS Ecological Site page. (NRCS, 2017)


ES&R: Burned Area Emergency Stabilization and Rehabilitation, planned actions to stabilize and prevent unacceptable degradation to natural and cultural resources, to minimize threats to life and property resulting from the effects of a fire, or to repair/replace/construct physical improvements necessary to prevent degradation of land or resources.


Final Designation: Final outcome of a potential monitoring point identified in a monitoring design. The final designation of the point has implications for how points are used in analyses and the subsequent inference to  reporting units. Categories are as follows:  

  • Target sampled points are locations on BLM lands where monitoring data were collected
  • Inaccessible points are on BLM lands, but the data collectors could not physically access the site (e.g., needed to cross private land and access was denied, road was washed out)
  • Non-target points are locations that upon further review were determined to not be part of the target population, (e.g., points not on BLM-managed lands).
  • Unknown points are those for which their fate was not recorded or points that were not assessed, as such we do not know if they are within the target population or not.
  • Not Needed points are locations that were selected for the design but do not need to be sampled because the necessary sampled sizes were obtained or the definition of the target population changed (see Sample Size).

HAF: The Sage-Grouse Habitat Assessment Framework, a method to consistently evaluate suitability of sage-grouse habitat across the range and at multiple scales.


Indicator: A component of a system whose characteristics (e.g., presence or absence, quantity, distribution) are used as an index of an attribute (e.g., biotic integrity) that is too difficult, inconvenient or expensive to measure.


Intensification: An effort that increases the density of monitoring locations within an area of special interest to increase the accuracy (mean estimate closer to the population mean) and precision (smaller confidence interval) of indicator estimates.  Typically performed in anticipation of special management decisions (e.g., permit renewal) that require greater accuracy and precision than provided by existing monitoring designs within the same area.  Alternatively, performed because special areas have few or even no monitoring locations.


Jornada: A USDA-ARS unit, the Jornada Experimental Range has partnered with BLM to develop and support AIM from since 2006.The Jornada works with BLM Field, District, and State offices as well as the NOC and Washington office to implement AIM and analyze AIM data. In particular the Jornada assists with sample design, training, method questions, DIMA, R analysis tools, and analysis and interpretation of AIM data. To learn more, visit their website.


LHS: Land Health Standards, statements of physical and biological condition or degree of function required for healthy sustainable rangelands.


LUP: Land Use Plans, also known as Resource Management Plans (RMPs), that form the basis for every action and approved use on the public lands.


Management Objective (Management Goal): Broad goals or desired outcomes land managers are trying to achieve with land management.  Management objectives and goals provide the context for why monitoring information is needed and how it will be used.  Often, these are derived from planning documents and policy. Examples include maintaining forage production for livestock or high-quality habitat for big game animals.


Master Sample: A large number of pre-selected, random sample locations from which project-level designs can be selected.  Across the western U.S (12 states), terrestrial AIM master sample  locations consist of 1 point per 35 hectares, and aquatic AIM master sample locations are 1 point per 0.5 km of stream length. These points can be used for comparable, complementary monitoring among separate monitoring organizations and across geographic scales.  The Master Sample retains the principles of Randomization and Spatial Balance. Further reading: Larsen, D.P., A.R. Olsen, and D.L. Stevens. 2008. Using a master sample to integrate stream monitoring programs. JABES 13: 243-254. (Monitoring Resources, 2017).  For more about the AIM master samples, see Understand the Master Sample.


Monitoring Design Worksheet: A step-by-step template for completing an AIM sample design. This worksheet serves many purposes including documenting decisions and reasons for completing monitoring, providing the necessary information for drawing sample points and completing analyses once data are collected.  The worksheet can be found on the Design page.


Monitoring Objective: Quantitative statements that provide a means of evaluating whether management objectives or goals were achieved.  Monitoring objectives should be specific, 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 monitoring planning process.  At a minimum, monitoring objectives should include: 1. indicator; 2. benchmark for the indicator; 3.  a time frame for evaluating the indicator, and 4. the reporting unit(s) over which the monitoring results will be reported.If making inference to a broader amount of resource (i.e. beyond the individual site scale) is pertinent to your objective, be sure to include the proportion of the resource that is desired to achieve certain conditions (i.e. benchmarks) and a confidence interval in the objective.

  • Example objectives:
    • Bare ground in Loamy ecological sites is between 15 and 35% for 80% of the land use plan area with 80% confidence with three years of data.
    • Maintain bank stability of greater than or equal to 75% for 80% of perennial wadeable streams in the planning area with 95% confidence over 10 years.

NAMC: The National Aquatic Monitoring Center (NAMC),is a joint venture between the BLM and Utah State University. The mission of NAMC is  to foster and support scientifically sound aquatic monitoring programs on public lands. NAMC plays a large role in leading AIM monitoring efforts for rivers and streams.


National Hydrography Dataset (NHD): The NHD is a national geospatial dataset that represents surface water on the landscape. The NHDPlus medium resolution is broken into stream segments each of which is associated with several attributes including the Strahler Stream Order, and whether the segment has been designated as perennial, intermittent, an artificial path, etc.


NOC: National Operations Center, a BLM center to provide operational and technical program support to BLM State, District, and Field offices as well as collaborators. The National AIM team is largely housed in the Division of Resource Services (DRS) at the NOC. The DRS provides a technical interface between national policy and field operations through scientific and specialized products, resource data stewardship, and technical program support.


Objective: a formal statement detailing a desired outcome of a project.


Oversample Points: Extra sample points which are selected at the time of the base sample draw. These points are used to supplement the base points when a base point is rejected or not sampled (see Final Designation).


Panel: A set of sample points that have the same revisit pattern across years. For example, an AIM design might be divided into 5 panels each one visited in a different year. All points within a single panel visited in 2017, would then be visited in 2022, 2027, and so on. The points visited 2017 through 2022 together make up the entire sample design.


Percent Achieving Desired Conditions: The desired percentage of a resource with one or more indicator values that meet benchmark value(s).  For instance, a desired percentage may be  (80%) of the landscape with <20% bare ground, or 80%of sage-grouse summer habitat scored as suitable (based on multiple indicators).  Percentages are derived from weights (see weight definition) of monitoring points or plots, where a point or plot weight indicates the extent of the resource represented by a point or plot.


Percentiles of Regional Reference: An approach to setting benchmarks that uses reference sites or plots grouped by a landscape classification schema (e.g., ecoregions) to create a distribution of reference site indicator values. Benchmarks can then be set by assuming that sites in reference condition should fall within certain percentiles of the reference site distribution of a similar physiographic region. For example, the 90th and 70th percentiles of reference site floodplain connectivity values for the Colorado Plateau can be used to separate “major departure,” “moderate departure,” and “minimal departure” from reference conditions, respectively. For aquatic AIM, this approach can be used for indicators that lack models to compute predicted natural conditions. For terrestrial AIM, this approach is dependent on identifying and establishing a group of regional reference points.


Physiographic Properties: Physical characteristics of a landscape that can be used to understand the potential of that landscape.These properties can be used as supplemental information, or covariates, for interpreting indicators.  Slope, aspect, landform, and soil type are all physiographic properties.


Population: The entire “universe” to which the results of sampling apply. The population is defined by many factors; the area you’re interested in, objectives and constraints.


Project Area: Describes the broadest outline of a project . Usually the boundary of a field office, district office, or other administrative boundary. A project area contains the target population (e.g., BLM land within a field office boundary). See also Study Area. 

Predicted Natural ConditionsAn approach to setting benchmarks where the conditions expected to occur at a plot or reach in the absence of anthropogenic impairment are derived from empirical models. Such models use geospatial predictors (e.g., soil, climate and topographic attributes) to account for natural environmental gradients. Observed field values are compared to potential natural indicator values and any deviation is assumed to result from anthropogenic impacts. This approach is advantageous because it provides spatially explicit predictions of expected conditions with known levels of accuracy and precision. Unfortunately, due to data limitations and the current state of the scientific literature, this approach is only available for a few aquatic AIM indicators.


Quality assurance: proactive process employed to maintain data integrity and is a continuous effort to prevent (e.g. training, calibration, proper technique), detect (e.g. on-plot data review), and correct measurement errors (e.g. readjustments in response to data review).


Quality control: reactive process to detect measurement errors after the data collection process is complete.

Reporting: communicating the results of monitoring data analysis in a manner that is can be used.


Reporting Unit: Subsets of the study area where you need information, such as indicator means and confidence intervals. A study area can have different types of reporting units. Knowing the units ahead of time helps ensure adequate sampling. Reporting units may be different than stratification. Watersheds, allotments, and Greater Sage-grouse habitat units are all examples of reporting units.


Sample Design: Provides information on the target and final sample sizes, strata definitions and the sample selection methodology. This term can be used interchangeable with “sample plan”, “survey design”, “sampling plan” or “sampling design”. In AIM the details of the sample design are covered in the Monitoring Design Worksheet.  (Monitoring Resources, 2017)


Sample Frame: A representation of the target population. The sample frame is often a geospatial feature, but it can also be some list of the element of interest (e.g., BLM acre, wetland, or stream reach).(Monitoring Resources 2017)


Sample Point (Reach or Plot): Location where monitoring information has been collected or data collection is planned.  For terrestrial AIM, this is a plot.  For aquatic AIM, this is typically a stream reach.  In some documents, the phrase sample point is used to refer to both.


Sample size: The number of points or plots in the target population  that need to be sampled within a strata to analyze data to ensure a desired level of precision and accuracy. The sample size across the study area is a function of several factors: 1) existing or legacy monitoring information, 2) statistical considerations (e.g., what analyses do I need, what is my desired confidence level and confidence interval), and 3) funding and personnel limitations (e.g., how many points per year can I accomplish). The sample size may influence the types of analyses you can perform and the uncertainty of the results.


Sampling: using selected members to estimate attributes of a larger population.


Sampled population: That portion of the target population that you could actually sample.


SARAH: Streams And Rivers Assessment Hub is an iPad based FileMaker application used for aquatic AIM field electronic data collection.


Spatially Balanced Sampling: samples are evenly spaced across study area and ordered to maximize spatial dispersion of any sequence of units.


Status: a measured indicator value or range of values.


Strahler Stream Order: A hierarchical numeric system used to classify stream size. Stream size as determined by this method is used in most if not all aquatic designs as a stratum. First order streams are small headwater streams. When two first order stream come together a second order stream is formed, when two second order streams come together a third order stream is formed, and so on. Two different order streams (e.g., first and second) coming together do not create a higher order stream (e.g., third), the stream below the confluence of the two different orders will remain the same order as the larger order stream (e.g., second order). Common groupings of stream orders for aquatic AIM strata are SS- Small streams (1-2 order streams), LS- Large streams (3-4 order streams), and RV-Rivers (5+ order streams).


Strata: Subdivisions of the study area to divide up sampling efforts to control for heterogeneity. Strata are ideally defined as particular parts of the landscape (e.g., flood basin or hill summit) within which soil type, vegetation, management and current status are relatively similar. All areas classified by the same stratum are expected to respond similarly to changes in management and disturbances. Strata DO NOT have to be sampled with the same intensity.


Stratification: Stratification refers to dividing a population or study area up into sub-groups or subunits called strata for the purposes of sampling or data analysis. Reason to stratify: 1) variability in indicators is different across types of land; 2) ensure different types of land or uncommon portions of a study area get sampled; 3) to deal with differences in land potential. Examples of strata include biophysical settings (see BpS), stream order (see Strahler stream order) , management unit boundary, and ecological sites (see Ecological Sites) (Monitoring Manual for Grassland, Shrubland, and Savanna Ecosystems, Volume II).


Supplemental Design: Additional points that were drawn for a pre-existing design because we used all pre-existing points and have not yet met needed sample sizes or completed monitoring objectives.


Supplemental Indicators: a measurable ecosystem component that is specific to a given ecosystem, land use, or management objective.


Study Area: Defines the extent of your population and is the maximum area you want to draw conclusions about. See Project Area.


Target population: refers to the resource to be described. Sample points (see site or plots) are selected from within the population. The definition of the target population should contain specific information resource of interest,: its spatial extent; its ownership status ; its size (all stream sizes? Just first order streams?). The definition should be specific enough that an individual could determine whether a sample point is part of the target population. In some cases, membership in the target population might be determined after data have been collected at the sample point (e.g., sage-grouse seasonal habitat).Examples of the target population include: all BLM lands within a reporting unit, all perennial, wadeable streams on BLM land, and sage grouse habitat on BLM lands. (Monitoring Resources, 2017)


TerrADat: national Terrestrial monitoring database.


Trend: the direction of change in ecological status or resource value rating observed over time.


Weight: A weight is the area (in acres or hectares) or length (in stream kilometers) represented by an individual sample point.  In general, point weights are equal to the total extent or amount of a monitored resource divided by the number of monitoring points.  Weights are used to generate statistical estimates of resource status or condition across the landscape..  Specifically, the weight is used to adjust the relative influence each point has on the final estimates; points with larger weights have more influence, and points with smaller weights have less. The weight of each point depends on the design and how it was implemented (see final designations) as well as the reporting area of interest.  

 

References

Bureau of Land Management, 2001, H-4180-1 Rangeland health standards: Department of the Interior Bureau of Land Management, Washington, D.C., accessed October 12, 2016, at http://www.blm.gov/style/medialib/blm/wo/Information_Resources_Management/policy/blm_handbook.Par.61484.File.dat/h4180-1.pdf.

Bureau of Land Management, 2016, Rapid Ecoregional Assessments: Bureau of Land Management, accessed March 7, 2016, at http://www.blm.gov/wo/st/en/prog/more/Landscape_Approach/reas.html.

Carter, S.K., Carr, N.B., Miller, K.H., and Wood, D.J.A., eds., 2017, Multiscale guidance and tools for implementing a landscape approach to resource management in the Bureau of Land Management: U.S. Geological Survey Open-File Report 2016–1207, 79 p., https://doi.org/10.3133/ofr20161207.

Elzinga et al. 2003

Karl, M.G. “Sherm,” Kachergis, Emily, and Karl, J.W., 2016, Bureau of Land Management Rangeland Resource Assessment—2011: Bureau of Land Management, National Operations Center, Denver, Colo., 112 p.

Larsen, D.P., A.R. Olsen, and D.L. Stevens. 2008. Using a master sample to integrate stream monitoring programs. JABES 13: 243-254.

Monitoringresources.org

NRCS Ecological Site page

Pellant, Mike, Shaver, Patrick, Pyke, D.A., and Herrick, J.E., 2005, Interpreting indicators of rangeland health, version 4, Technical Reference 1734-6: Denver, Colo., Bureau of Land Management National Science and Technology Center, accessed October 12, 2016, at http://jornada.nmsu.edu/files/IIRHv4.pdf.

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