GAP Bulletin Number 5
June 1996

Some Scales for Describing Biodiversity

One of the first principles of Gap Analysis is that the most efficient overall strategy for biological conservation is to complement intensive species-by-species management, necessary for those species now in danger of extinction, with management of habitat types or natural assemblages of plant and animal species that are still relatively common and viable (Scott et al. 1993). Adequate representation of the full complement of natural habitat types within a network of conservation lands is fundamentally required if we are going to conserve plant and animal species in their natural habitats rather than in zoos (Shaffer 1990).

Because of this, the relationships among and between (a) the pattern of dominant land cover types, (b) vertebrate species diversity, and (c) spatial scale are all critical for Gap Analysis. Measures of species diversity must be expressed relative to biogeographic units of a determined spatial scale if they are to be meaningful (Levin 1981). Unfortunately, confusion about the differences between types of diversity ("thematic resolution") and cartographic scale is persistent (e.g., Short and Hestbeck 1995, Davis 1995, Edwards 1995, Scott et al. 1995). Below, I briefly present some nomenclature that is useful when dealing with the issue of diversity and scale.

Whittaker (1960, 1977) suggested seven categories as a framework for describing species diversity in relation to ecological patterns and spatial scale (Table 1). The linkage between types of diversity and spatial scale makes this framework especially useful. Figure 1 (Stoms and Estes 1993) shows how four of these categories ("inventory diversities") are used to describe species diversity within sampling units of four approximate sequential sizes and corresponding with four hierarchical levels of biotic organization: a single ground sampling point (point diversity), a natural community (alpha diversity), a landscape (gamma diversity), and a large geographic region (epsilon diversity). Three other terms ("differentiation diversities") are used when comparing the amount of change in species composition between individual sampling points (pattern diversity), natural communities (beta diversity), and landscapes (delta diversity).

Inventory diversities   Differentiation diversities
1. Point diversity: A small, or microhabitat, sample of species diversity from within an alpha unit. Generally 10 to 100 sq meters.  
  2. Pattern diversity: The change in diversity between points within a community.
3. Alpha diversity: A single within-habitat measure of species diversity regardless of internal pattern. Generally 0.1 to 1,000 hectares.  
  4. Beta diversity: The change in diversity among different communities of a landscape; an index of between-habitat diversity.
5. Gamma diversity: The species diversity of a landscape made up of more than one kind of natural community. Generally, 1,000 to 1,000,000 hectares.  
  6. Delta diversity: The change in diversity between landscapes along major climatic or physiographic gradients.
7. Epsilon diversity: The species diversity of a broad region of differing landscapes. Generally 1,000,000 to 100,000,000 ha.  

Table 1. Levels and types of species diversity (Wittaker 1977, Stoms and Estes 1993).

The minimum thematic object that Gap Analysis is mapping is the Natural Community Alliance (Grossman et al. 1994). This corresponds most closely with the units of alpha diversity (a sample representing a community regarded as homogeneous despite its internal pattern) in order to conduct analyses at the beta, gamma, delta, and epsilon levels. As indicated by between-habitat diversity, a spatial depiction of beta diversity represents the pattern of landscape heterogeneity. For Gap Analysis, the central concept is that the structural and taxonomic characteristics of vegetation or, in the absence of vegetation, dominant land features, can be used systematically to delineate and map patterns of beta diversity. Models of these patterns are important for generating and evaluating landscape-level conservation options.

Literature Cited

Davis, F.W. 1995. The nature of gap analysis. Letter. BioScience 46:74-75.

Edwards, T.C., Jr. 1995. Data defensibility and gap analysis. Letter. BioScience 46:74-75.

Grossman, D., K.L. Goodin, X. Li, C. Wisnewski, D. Faber-Langendoen, M. Anderson, L. Sneddon, D. Allard, M. Gallyoun, and A. Weakley. 1994. Standardized national vegetation classification system. Report by The Nature Conservancy and Environmental Systems Research Institute for the NBS/NPS Vegetation Mapping Program. National Biological Service, Denver, Colorado.

Levin, S.A. 1981. The problem of pattern and scale in ecology. Ecology 73:1942-1968.

Scott, J.M., F. Davis, B. Csuti, R. Noss, B. Butterfield, C. Groves, H. Anderson, S. Caicco, F. D'Erchia, T. C. Edwards, Jr., J. Ulliman, and G. Wright. 1993. Gap analysis: A geographic approach to protection of biological diversity. Wildlife Monographs 123.

Scott, J.M., M.D. Jennings, R.G. Wright, and B. Csuti. 1995. Landscape approaches to mapping biodiversity. Letter. BioScience 46:74-75.

Shaffer, M.L. 1990. Population viability analysis. Conservation Biology 4:39-40.

Short, H.L., and J.B. Hestbeck. 1995. National biotic resource inventories and GAP analysis. BioScience 45:535-539.

Stoms, D.M., and J.E. Estes. 1993. A remote sensing research agenda for mapping and monitoring biodiversity. International Journal of Remote Sensing 14:1839-1860.

Whittaker, R.H. 1960. Vegetation of the Siskiyou mountains, Oregon and California. Ecological Monographs 30:279-338.

Whittaker, R.H. 1977. Species diversity in land communities. Evolutionary Biology 10:1-67.

Michael D. Jennings, National Coordinator
Gap Analysis Program
Moscow, Idaho


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