Analytical Components

This list describes a number of operations and models that may be potentially useful to represent as actors and workflows (analytical models) within Kepler. When possible each such "component" includes a brief description and potential impact (e.g., for semantic mediation) as well as one or more citations for the component (e.g., where we spotted the use of the method and definitive papers describing or introducing the method).

Species Density Estimates (D)

• Citation: (Gross et al. 1999).
• Description: D is defined as the measured or estimated number of species per m^2. A number of methods are used for estimating D from data sets of different scale (e.g., not at m^2 plots). Each method used taken from other sources. The methods are:
• Percent cover from smaller plots (Inouye et al. 1987, Inouye 1998)
• ANPP (annual primary productivity) harvested plots (Huberty et al. 1998)
• ANPP harvested plots, combined for a transect estimate of D (Milchunas et al. 1990, Inouye 1998)
• Percent cover adjacent to ANPP plots, interopolated for a per m^2 transect estimate of D (Briggs and Knapp 1995)
• Censused in m^2 plots containing smaller quadrats used for ANPP estimates (Shaver 1986, Chapin et al. 1995)
• Species presence censused at 200 points in each m^2 plot sampled for ANPP (Walker et al. 1994)
• Application: As a set of operations to be included in a library for integration, for automated/semi-automated scaling.
• Status: Need to see if these are actually useful or practical to incoporate.

Determing Plot Layout

• Citation: (Sheiner 2003)
• Description: In Sheiner's paper, he described various plot "topologies" and the associated sampling schemes from such layouts. It seems like this would be a useful component: given a collection of data sets, display the plot topology across those datasets on a map.
• Application: This could be expressed as a query against an ontology that describes the spatial characteristics of a data set, and answered by the semantic description of the dataset to the ontology. The result of the query could then be used to display the topology of the plots across the heterogeneous data sets.
• Status: Is this useful?

Species-Area Curve Predictions

• Citation: (Sheiner 2003)
• Description: The properties of species-area curves have been predicted from models of community processes (Preston 1962a, Preston 1962b, Coleman 1981, Caswell and Cohen 1993, He and Legendre 2002, Plotkin and Muller-Landau 2002), which begin with an analytical model of species dispersal and interaction and then predict the relationship between species and area.
• Issues: In testing these models, it is important that the sampling scheme mirror the model assumptions, e.g., assuming metapopulation patch structure with no spatial component (Caswell and Cohen 1993), or assuming a contiguous spatial structure (Plotkin and Muller-Landau 2002).
• Application: These may be interesting examples of scientific workflows that could be incorporated into Kepler. There may be interesting semantic mediation issues.
• Status: Need to see if this is actually useful or practical.

Site by species matrix

• Citation: From Beam Working Group meeting (BeamKnowledgeRepSept04)
• Description: In the matrix, every row is a site, like a different quadrat, every column is a different species in the matrix, the value could be abundance, but typically is just species/absence (1 or 0's). Then, if you sum across the row, you know the number of species, e.g.. There might be also be a separate set of columns for location of the plot. You can then compute/estimate, via re-sampling (different algorithms for this), the species-area curves. Also, the goal is to capture the abundance, not just the presence/absence ... you want to use the abundance when possible. Also, there are tons of uses of these matrices. Abundance measured in various ways: relative and absolute, you can compute relative to absolute but not the other way; total biomass is an absolute / percent cover is a relative. Relative: hits, cover, touches. Absolute: count stems, biomass.
• Application: Given any marked up dataset, we should be able to construct one of these matrixes automatically.
• Caveat: The species area curves are really used within a decision making context typically... You want ways to analyze the species/area relationship varies with productivity.

References

1. (Briggs and Knapp 1995) J. Briggs and K. Knapp. Interannual variability in primary productivity in tallgrass prairie: climate, soil moisture, topographic position, and fire as determinants of aboveground biomass. Am. J. Bot. 82:1024-1030, 1995.
2. (Caswell and Cohen 1993) H. Caswell and J. Cohen. Local and regional regulation of species-area relations: a patch-occupancy model. Species diversity in ecological communities, pp. 99-107, 1993.
3. (Chapin et al. 1995) F. Chapin III, R. Shaver, A. Giblin, et al. Responses of artic tundra to experimental and observed changes in climate. Ecology 76:694-711, 1995.
4. (Coleman 1981) B. Coleman. On random placement and species-area relations. Mathematical Biosciences, 54:191-215, 1981.
5. (Gross et al. 1999) K. Gross, M. Willig, L. Gough, R. Inouye, S. Cox. et al. Patterns of species density and productivity at different spatial scales in herbaceous plant communities. OIKOS 89:417-427, 2000.
6. (He and Legendre 2002) F. He and P. Legendre. Species diversity patterns derived from species-area models. Ecology
7. (Huberty et al. 1998) L. Huberty, K. Gross, and C. Miller. Effects of nitrogen addition on successional dynamics and diversity in Michigan old-fields. J. Ecol. 86:794-803, 1998.
8. (Inouye et al. 1987) R. Inouye, N. Huntley, D. Tilman, et al. Old-field succession on a Minnesota sandplain. Ecology 68:12-26, 1987.
9. (Inouye 1998) R. Inouye. Species-area curves and estimates of total species richness in an old-field chronosequence. Plan Ecol. 37:31-40, 1998.
10. (Milchunas et al. 1990) D. Milchunas, W. Laurenroth, P. Chapman, and M. Kazempour. Community attributes along a perturbation gradient in a shortgrass steppe. J. Veg. Sci. 1:375-384, 1990.
11. (Plotkin and Muller-Landau 2002) J. Plotkin and H. Muller-Landau. Sampling the species composition of a landscape. Ecology, 83:3344-3356, 2002.
12. (Preston 1962a) F. Preston. The canonical distribution of commonness and rarity, part I. Ecology, 43:185-215, 1962.
13. (Preston 1962b) F. Preston. The canonical distribution of commonness and rarity, part II. Ecology, 43:410-432, 1962.
14. (Shaver 1986) G. Shaver. Woody stem productions in Alaskan tundra shrubs. Ecology 67:660-669, 1986.
15. (Sheiner 2003) S. Sheiner. Six types of species-area curves. Global Ecology and Biogeography, 12:441-447, 2003.
16. (Walker et al. 1994) M. Walker, J. Webber, E. Arnold, and D. Ebert-May. Effects of interannual climate variation on above-ground phytomass in alpine vegetation. Ecology 75:393-408.