Biodiversity at the SEV Long-term Ecological Research Site

Authors: Bruce T. Milne

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Abstract

Extensive holdings of the six divisions of the UNM Museum of Southwestern Biology date to 1890 (the mammal collection is the oldest, and contains over 105,000 specimens) although collecting began in earnest with the work of E. F. Castetter in the 1920s. William J. Koster began formal curation of the collection in 1936 and established the six major divisions of the museum. The vertebrate collection grew rapidly to 36,000 specimens under the direction of J. S. Findley. The plant collection started in 1926 (86,500 specimens, 6600 species). Since the 1930s, the museum has maintained collections of arthropods (25,000 and 15,000), fish (91,000 and 220), reptiles (57,015 and 737), birds (21,000 and 960), and cryotissues (70,000 and 526).

Inventory activities center around both conventional museum collections and the world's largest collection of cryogenically preserved tissue samples of parasites and their corresponding host individuals. The inventory had direct application in solving a mystery about an ominous infectious disease. Following the 1991 El Nio event, which brought high spring moisture to New Mexico, the rodent population exploded by a factor of 10 and was associated with the 1993 hantavirus epidemic in humans. Professor Terry Yates and colleagues "mined" the collection to prove that the newly discovered Sin Nombre hantavirus actually occurred in animals collected in 1982, 11 years before the epidemic. The discovery prompted pathologists to examine archived serum samples from humans who died of unknown respiratory infections as early as the 1970s, and thereby determined that the victims had been infected with the virus. This example highlights the value of long term collections obtained from LTER sites and has led to recommendations regarding the handling of specimens which may be infected, not only in the Southwest, but elsewhere in the US and Latin America (Mills et al. 1995).

In keeping with the mission of the Sevilleta LTER, biodiversity inventory entails assessments at multiple scales, because occurrences and densities of organisms are scale-dependent (Gosz and Sharpe 1989, Milne 1991, 1992, Milne et al. 1996). Thus, explicit descriptions of the spatial and temporal resolution of biodiversity measurements should be made to characterize the actions of nonlinear processes which may govern the spread of organisms. Interactions between demographic growth and diffusion (Andow et al. 1990) or interactions between dispersal and landscape structure at particular scales (Johnson et al. 1995) may induce anomalous diffusion over a particular domain of scales (Johnson et al. 1992). Part of the ambiguity of traditional diversity indices, or even the classical species area relation used in ecology, may be due to the scale dependence of information theoretic measures (Milne 1988, Loehle and Li 1995) or due to the role of complex terrain which modifies the expected scaling relation between island area and species richness (Scheuring 1991, Milne 1997).

Functionally, biodiversity relates to both the goods and services provided by nature and to nature's capacity to detoxify or store wastes (Goodland 1995), such as carbon dioxide and methane. In the Sevilleta, water is the limiting factor that regulates the rates of carbon fixation and the return of water to the air via evapotranspiration. Currie (1990) surveyed vertebrate and tree species richness in relation to potential evapotranspiration (PET, a measure of energy available for photosynthesis, some fraction of which is converted to production depending on water availability (Stephenson 1990), and another fraction which represents thermal energy used especially by poikilotherms). Several hypotheses can be drawn from Currie's (1990) work which are directly applicable across the network of LTER sites. For example, latitude, which is correlated with PET, is a predictor of the number of species present in various classes of organisms. Based on studies at a wealth of sites, Currie's (1990) results provide the simplest expectations for diversity. For example, the expected and observed numbers, respectively, of species in the Sevilleta (34**o N Latitude) are: (1) Aves, 160 and 207; (2) Reptilia, 65 and 58; (3) Mammalia minus bats, 58 and 63; and (4) Amphibia (30 and 15). Immediately we see that the rank order of observed richness does not match the expected, with unexpectedly higher homeotherm richness and low poikilotherm richness. Thus, rejecting Currie's (1990) predictions for individual classes, but tentatively accepting it for vertebrate richness overall (135 observed, 150 expected with large standard deviation), suggests that a tradeoff has been made among the classes with losses of some compensating for gains in others. The nature of such tradeoffs deserves examination across a wide variety of environments.

Thus, biodiversity studies in the Sevilleta benefit from extensive archival collections, a legacy of interest in biodiversity, broad environmental gradients throughout the region that enable a full expression of biotic responses to climate and biome origins (McLaughlin 1986), and rich conceptual and methodological frameworks.

Andow, D.A., P.M. Kareiva, S.A. Levin, and A. Okubo. 1990. Spread of invading organisms. Landscape Ecology 4:177-188.

Currie, D.J. 1991. Energy and large-scale patterns of animal- and plant-species richness. American Naturalist. 137:27-49.

Goodland, R. 1995. The concept of environmental sustainability. Annual Review Ecology Systematics 26:1-24.

Gosz, J.R. and J.H. Sharpe. 1989. Broad-scale concepts for interactions of climate, topography, and biota at biome transitions. Landscape Ecology 3:229-243.

Johnson, A.R., B.T. Milne, and J.A. Wiens. 1992. Diffusion in fractal landscapes: Simulations and experimental studies of Tenebrionid beetle movements. Ecology 73:1968-1983.

Johnson, A.R., C.A. Hatfield, and B.T. Milne. 1995. Simulated diffusion dynamics in river networks. Ecological Modelling 83:311-325.

Loehle, C. and B-L. Li. 1995. Statistical properties of ecological and geologic fractals. Ecological Modelling 85:271-284.

McLaughlin, S.P. 1986. Floristic analysis of the southwestern United States. Great Basin Naturalist 46:46-65.

Mills, J.N., T.L. Yates., J.E. Childs, R. R. Parmenter, T. G. Ksiazek, P.E. Rollin, and C.J. Peters. 1995. Guidelines for working with rodents potentially infected with hantavirus. Journal of Mammology 76:716-722.

Milne, B. T. 1988. Measuring the fractal geometry of landscapes. Applied Mathematics and Computation 27:67-79. Milne, B.T. 1991. Lessons from applying fractal models to landscape patterns. pp. 199-235 In Quantitative Methods in Landscape Ecology. M.G. Turner and R.H. Gardner, (eds.). Springer- Verlag, New York.

Milne, B.T. 1992. Spatial aggregation and neutral models in fractal landscapes. American Naturalist 139:32-57.

Milne, B.T. 1997. Applications of fractal geometry in wildlife biology. pp. 32-69 In Wildlife and Landscape Ecology, J. A. Bissonette (ed.). Springer Verlag.

Milne, B.T., A.R. Johnson, T.H. Keitt,C. A. Hatfield, J. David, and P. Hraber. 1996. Detection of critical densities associated with pinon-juniper woodland ecotones. Ecology 77:805-821.

Scheuring, I. 1991. The fractal nature of vegetation and the species-area relation. Theoretical Population Biology 39:170- 177.

Stephenson, N.L. 1990. Climatic control of vegetation distribution: the role of water balance. American Naturalist 135:649-670.