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Water: Monitoring & Assessment

1. "AREM" and What it Can Do

User's Manual:
Avian Richness Evaluation Method (AREM)
for Lowland Wetlands of the Colorado Plateau

This manual describes how to use and interpret the "Avian Richness Evaluation Method" (AREM), a standardized procedure for estimating the bird species composition and richness of lowland wetlands of the Colorado Plateau (Figure 1).  Instructions for using AREM are found in Section 2.0, and no additional training courses should be needed.  To apply AREM correctly, you should first read the information in Tables 1-3.  If you desire an in-depth understanding of the concepts and database programming logic of AREM, you may refer to Section 5.0 of Adamus (1993a).  However, it is not essential to review that information before using AREM.  Section 3.0 of the present manual provides documentation for some of AREM's individual indicators.

When used correctly, you can expect AREM to do the following:

  • Assign a score to each evaluated wetland, which represents the number of bird species that could occur in the wetland, multiplied by an estimate of the suitability of the wetland for each species.
  • List the species likely to occur in the evaluated wetland.  Such a list can be combined with lists predicted for other wetlands, to identify minimum combinations of wetlands that will provide habitat for all bird species in an area.
  • Tally the number of species likely to occur in the evaluated wetland and which have particular characteristics, e.g., neotropical migrants, uncommon or game species.  If desired, users can assign scores to these characteristics and use them as "weights" in deriving the wetland score.

Some examples of situations where AREM might be used to assist and document resource decisions are as follows:

Situation 1. Mitigation Calculations.  Resource agencies currently spend time "cover-typing" lands that will be altered in connection with salinity control projects, water diversions, and other developments where compensatory mitigation has been deemed necessary.  This process involves measuring various categories of habitat before a project is begun and then estimating any shifts in acreage that will occur among categories as a result of the project.  Acreages in each cover type category that are believed to exist both before and after the project are multiplied by coefficients, determined through use of HEP1, that indicate suitability of each category for selected species during both time periods.  In this manner, net change in habitat suitability is predicted, at least for a few selected species.   Where wetland and riparian cover types are the habitats that are expected to change, AREM might be used in lieu of (or in addition to) HEP to calculate the habitat suitability coefficients.  If non-wetland cover types are also present, AREM could be expanded and modified by a knowledgeable ornithologist to include these (see Section 2.7 for guidance in adapting AREM to other habitats or regions).

Situation 2. Diagnosing Impaired Wetland Quality.  Where wetlands are officially considered by agencies to be "waters of a state" or where they exist within certain public trust lands (e.g., National Wildlife Refuges), a legal need sometimes arises to determine the degree to which wetland quality has been impaired.  AREM alone cannot determine this.  However, AREM can assist in diagnosing the presence of contamination problems by defining which species "should" be present in a wetland having a particular habitat structure.  If properly designed surveys then fail to find the predicted species, it might be because non-physical (e.g., chemical) factors unmeasured by AREM are discouraging wetland use by birds.  Some caution is necessary because species absence could be due to weather conditions, to demographic factors (e.g., suitable habitats being "undersaturated" with individuals because of impacts to populations that have migrated from neotropical wintering areas2), or weaknesses in particular species models that comprise AREM.  Nonetheless, AREM could be useful as an initial screening tool to help decide whether more effort should be committed to verify that a problem exists.

Situation 3. Selecting Appropriate Indicator Species.  By defining which species to expect in particular types of wetlands, AREM can narrow the list of species to be considered for potential use as "indicators" in programs to monitor water quality or physical habitat suitability.  Selecting appropriate indicator species is crucial to proper use of HEP, as well as to the development of wetland biocriteria and the accurate monitoring of wetland contamination.

Situation 4. Targeting Habitat Enhancements.  Active management of wetlands will usually be most effective when it focuses on improving conditions for species with low species habitat scores, while maintaining conditions suitable for species with high species habitat scores.   In combination with other considerations, AREM can be used in this manner to suggest habitat features whose enhancement will support the largest variety of species overall, or of species having a particular attribute.

Situation 5. Wildlife-based Classification of Wetland Habitats.  Wetland "types" are commonly defined by their vegetative communities.  Wildlife communities or individual species also can be a useful primary or secondary feature in classifying wetlands for scientific or administrative purposes.  AREM can assist such classifications by predicting bird species and richness that are associated not only with vegetation, but also with other environmental factors.  Statistically-defined, wildlife-based classes of wetlands could be identified by applying AREM to a probabilistic sample of wetlands in a region.

Situation 6. Optimizing Biodiversity Protection.  Resource agencies and conservation groups sometimes have opportunities to purchase or trade properties to enhance regional biodiversity.  When biological survey data from the subject properties are lacking, AREM can be applied (at any season) to predict avian richness of individual properties.  The AREM computer program (p. 28) can then be used to pool the predicted species lists from multiple wetlands, to determine which combination of wetlands is likely to support the greatest diversity.  This estimate can be focused further by applying constraints related to land ownership, species characteristics, management costs, or other factors.  As such, AREM can provide a complementary, local refinement of the "gap analysis" approach currently used for ecosystem management and biodiversity planning at state and regional levels by the U.S. Fish and Wildlife Service (Scott et al. 1993).

Intended users of AREM are consultants and employees of government agencies, who have at least a Bachelor's degree in one of the environmental disciplines.  Users must be able to recognize a few of the major vegetation types of the Colorado Plateau (e.g., salt cedar, willow).

Figure 1. Subregions of the Colorado Plateau addressed by this report. [BROKEN]

Table 1.  Advantages of using AREM.
  1. Using AREM is relatively simple and rapid.  Field data collection requires less than 15 minutes per wetland.  Data entry and analyses require less than 30 minutes per wetland.  The models AREM uses to predict habitat suitability for individual species are mathematically simpler than those used by the Habitat Evaluation Procedure (HEP, U.S. Fish & Wildlife Service 1980) and thus may be easier to understand and explain.
  2. AREM is one of only a few rapid evaluation methods that actually have been validated to some degree, i.e., accuracy during the breeding season was measured through comparison of observed with predicted conditions (see Adamus 1993b).
  3. The scores that result from an AREM evaluation have a high level of accountability.  Users can call up the database for any species to closely examine the habitat model supporting that species.  Users can also call up any indicator condition to identify all species predicted by that condition.  This feature is of potential use in predicting a species' response to wetland change, e.g., for impact analysis or planning of wetland enhancements. 
  4. AREM users, even those with limited computer knowledge, can interactively edit the database and revise models for any species.  This allows users to adapt AREM for other regions and wetland/riparian types, provided habitat requirements of all bird species in these areas are known, or can be determined with sufficient accuracy.
  5. AREM is perhaps the only rapid habitat evaluation method whose major organizing theme and endpoint is biodiversity.  Many government agencies are mandated to account for the impacts of their activities on biodiversity, and public concern over the global and regional loss of biodiversity appears to be growing.
  6. In contrast to HEP, AREM does not require the user to base a wetland's score on a few presumed "indicator species."  Users do not need to assume that habitats which are found to be optimum for a few species will also be suitable for many species, i.e., be biodiverse.
  7. Species lists predicted by AREM for various wetlands can be combined in any local area or subregion to determine which particular combination of wetlands cumulatively supports the greatest number of species (see p. 28).  This "optimization process" can be further focused by applying constraints related to species characteristics, land ownership, management costs, or other factors.  As such, use of AREM can provide a complementary, local refinement of the "gap analysis" approach currently being applied at state and regional levels by the U.S. Fish and Wildlife Service (Scott et al. 1993).
  8. One of AREM's outputs -- the "unweighted richness" score -- is the actual number of species predicted to occur in a wetland.  As such, this is an ecological parameter that can be validated empirically.
  9. AREM does not require the user to conduct bird surveys or, for that matter, be an expert on birds or other wildlife.


Table 2. Limitations and assumptions of AREM.
  1. AREM is a compromise between convenience and technical certainty.  The technical certainty of many of the species habitat models that comprise AREM might be increased by formulating them in a more mathematically complex manner and explaining their details and assumptions at greater length, but in some cases this would sacrifice speed of application, replicability, and clarity to the typical user.  AREM is intended to be intermediate in complexity between the simple, few-indicator wildlife habitat relationship (WHR) models used in landscape classification and the multi-indicator, few-species HEP models used for site evaluations.  AREM shares some of the limitations of WHR's as described by Morrison et al. (1992) and limitations of HEP described by Van Horne and Wiens (1991), but avoids others.
  2. Indicator conditions used in AREM's species models in some cases are related to a species' presence in a loosely deterministic manner, but in other instances are related only empirically, i.e., they correlate with a species' presence but have not necessarily been shown to control use of habitats through explicit effects on food, cover, or reproduction.
  3. Wetlands are dynamic systems, and scores assigned by any evaluation method can change as a result of natural vegetative succession, flood or drought, management actions, or other factors.
  4. AREM pertains only to avian biodiversity.  It is not possible to predict the situations in which wetlands that contain a relatively great variety of bird species also have a relatively great variety of plants, insects, amphibians, or whatever.  
  5. It cannot be assumed that wetlands that are species-diverse will always be diverse at genetic, community, or functional levels, although this is often the case.
  6. It cannot be assumed that wetlands that are species-diverse will contain viable populations of most species, or greater ecological "integrity," "health," or "sustainability," although this is usually the case.


Table 3.  The context for properly using AREM.
  1. AREM is intended for application only to lowland wetlands and riparian areas larger than 0.1 acre, located within the Colorado Plateau region of western Colorado, eastern Utah, and southwestern Wyoming (Figure 1, p. 2).  
  2. Users should be capable of recognizing all indicator conditions specified in the field forms (Appendices B and C).  When evaluating a wetland, users should note situations in which they feel information requested by the field forms required considerable judgement, and report this with the results.
  3. As is true of other rapid methods for habitat assessment, AREM's habitat relationship models for individual species cannot be used to definitively measure the relative or absolute abundance or density of these species' populations.  Many factors not included in the species models, e.g., weather, determine population size and even presence/absence in a given wetland.  In some cases the influence of such factors on species distributions will exceed the influence of habitat quality, but AREM assumes that for most species, their influence on species presence/absence will be less.
  4. AREM should not be used to compare wetland/riparian habitats with other habitats.  Within the Colorado Plateau lowlands, species habitat scores from AREM estimate the suitability of a wetland or riparian habitat relative only to the suitability of other wetland or riparian habitats.  In some circumstances, some species included in AREM might find nonwetland habitats more suitable.
  5. Scores from AREM should not be used in lieu of species occurrence data from actual surveys of a wetland, provided such data have been collected with sufficient intensity and using appropriate methods.
  6. Scores from AREM should be considered as only one of several possible inputs used in the decision-making process.  Under most circumstances it is inappropriate to use AREM as the only means for deciding whether mitigation should be required.  A habitat index, defined as the product of an AREM score and wetland acreage, can be computed if desired.  The values from such an index potentially can be used as one input in mitigation deliberations, monitoring of restoration/enhancement projects, and description of the future biodiversity consequences of specified impacts to the indicator conditions.  However, the commonly associated practice of using values from such indices to rationalize a decision to offset the loss of a collectively large acreage of low-quality wetlands with the creation of a small acreage of high-quality wetlands must be viewed cautiously.  As is true of other methods, caution is needed because use of simple multiplication presumes that species richness is related to habitat acreage (wetland size) in a direct, linear manner.  This is not necessarily valid because (a) the effect of wetland size on richness can vary by species composition, season, surrounding landscape characteristics, wetland shape, and other factors, (b) wetland size is "double-counted," first as it is included in individual species models, and second as it is applied as a multiplier, and (c) "enhanced" habitat quality does not necessarily compensate for lost habitat space.

1 The Habitat Evaluation Procedures (HEP) of the U.S. Fish and Wildlife Service (1980).
2 Local absence of a species whose regional populations appear to be increasing is particularly suggestive of contamination problems in the local habitat when the habitat has been determined to be otherwise suitable (pers. comm., R.J. O'Connor, Dept. of Wildlife, University of Maine, Orono, Maine).

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