S Ss Ss

FIGURE 5.3 Costs of different aspects of strip mine reclamation. (Adapted from Atwood, G. 1975. Scientific American. 233(6):23-29.)

seems to have acted to restore certain natural conditions of the river ecosystem (Webb et al., 1999). Pulsing of energy sources is characteristic of many — perhaps all — ecosystems and was articulated in overview sense first by E. P. Odum (1971) in his pulse-stability concept (see also H. T. Odum, 1982; W. E. Odum et al., 1995; Richardson and H. T. Odum, 1981). Thus, full restoration may require pulsing disturbances that provide for periodic system rejuvenation as part of the energy signature. Middleton's (1999) excellent text on wetland restoration and disturbance dynamics supports this contention.

Although the examples described above focus on a single forcing function within an energy signature, most restoration involves multiple sources, stresses, etc. Figure 5.3 illustrates the many inputs to strip mine reclamation with cost data for different actions. Eleven costs are listed, ranging over an order of magnitude in cost per acre. This complex case is probably more typical of a restoration project with a diverse set of inputs required. In this particular case, it is interesting to note that restoration of soils and landforms has the highest costs, while inputs from seed and fertilizer are the lowest. This difference is indirect evidence of nature's scaling of values in a typical landscape. Soils and landforms represent storages that have developed over much longer time scales than the vegetation, which is restored with seed and fertilizers. Cost of restoration is thus directly proportional to the scale of the storage being restored.

Decreasing opportunity for mitigation after perturbation Increasing opportunity for recovery from perturbation

FIGURE 5.4 Energy circuit diagram depicting the role of different kinds of stress on ecosystems. (Adapted from Brown, S., M. M. Brinson, and A. E. Lugo. 1979. Gen. Tech. Rept. WO-12, USDA. Forest Service, Washington, DC.)

Decreasing opportunity for mitigation after perturbation Increasing opportunity for recovery from perturbation

FIGURE 5.4 Energy circuit diagram depicting the role of different kinds of stress on ecosystems. (Adapted from Brown, S., M. M. Brinson, and A. E. Lugo. 1979. Gen. Tech. Rept. WO-12, USDA. Forest Service, Washington, DC.)

The energy signature approach also has the potential to clarify semantic problems between the different concepts in the field of restoration ecology, noted in the introduction to this chapter (restoration vs. recovery vs. reclamation vs. rehabilitation, etc.). Diagramming the energy signature and system structure in a restoration project provides clear notions of stressors and actions needed for mitigation. In this regard, the energy signature diagrams prepared by A. Lugo and his associates are especially instructive. Figure 5.4 from Brown et al. (1979) is an example showing a spectrum of different stressors and the relative difficulty involved in appropriate restoration actions. According to the hypothesis shown in the diagram, impacts directly involving or close to the primary energy sources are difficult to mitigate, while impacts far up the chain of energy flow have greater opportunity for recovery. Lugo and others produced a number of energy circuit diagrams illustrating this concept and a complete review of them is useful, especially for those learning this symbolic modelling language (Lugo, 1978, Figures 5 and 8; Lugo, 1982, Figure 3; Lugo and Snedaker, 1974, Figure 1; Lugo et al., 1990, Figure 4.9).

The energy signature approach emphasizes a systems perspective, but a somewhat similar approach has evolved which portrays inputs or factors necessary to support a particular species. This species-oriented approach attempts to quantify the quality of a site for a particular species based on assessments of key elements. It involves the calculation of a habitat suitability index (HSI) in a way that is reminiscent of an engineering design equation. Habitat is a critical concept in ecology and refers to a place that provides the life needs (food, cover, water, space, mates, etc.) of a species (Hall et al., 1997; Harris and Kangas, 1989). In this sense, there is one optimal habitat for each species, just as there is one energy signature for each ecosystem. Historically, habitat was a qualitative concept that was best understood after long natural history study. The HSI model approach was developed by the U.S. Fish and Wildlife Service in order to formalize the habitat concept and to create a quantitative tool for field personnel to evaluate the conservation value of sites. An HSI model is an algorithm that is solved to calculate a numerical index that ranges from 0.0 to 1.0, with 0.0 representing unsuitable habitat and 1.0 representing optimal habitat, always relative to a particular species. More than 160 HSI models were developed, mostly in the 1980s, each of which is a very interesting synthesis of scattered information about a species. The algorithm of an HSI model consists of a series of graphical assessments of individual environmental factors that are combined in an equation to calculate the index value. For example, the HSI for muskrats (Allen and Hoffman, 1984) includes nine separate relationships dealing with hydrology and marsh vegetation that are used for calculating the quality of the habitat. In one sense, this is another expression of the niche of the muskrat. Reviews of the HSI model concept and other habitat evaluation approaches are given by Garshelis (2000) and Morrison et al. (1992), and a problem solving exercise on the HSI is given by Gibbs et al. (1998). In conclusion, the HSI model is useful in species-specific restoration ecology because it indicates the key factors that must be restored or created for a particular species. It also is useful in the larger context of ecological engineering because it represents an approach that can be used, as could be a design equation in traditional engineering, when restoring a habitat.

Biotic Inputs

Although there are many inputs to restoration projects, the genetic inputs in the biota that are planted or introduced are usually the primary emphasis (even though they are not always the most costly). These inputs actually are part of the energy signature of the project but they are practically never considered in energy units. Within the biological realm, focus is most often on higher plants. This is appropriate because plants almost always provide the three-dimensional structure of an ecosystem and are necessary for full ecological development of a site.

Active planting is not a particularly complex task per se, but a great many options and considerations are involved (Table 5.2). The basic decisions are (1) what species to plant, and (2) what structure or life form to plant. A broad knowledge of natural history and ecology is useful for making these decisions. For example, there are advantages and disadvantages to seeds vs. transplanting juvenile or adult plants, depending on the species and the site conditions. Experience is the best guide to successful planting programs (Erickson, 1964), and a number of useful texts have been published as aids, such as given by Galatowitsch and van der Valk (1994), Kurtz (2001), and Packard and Mutel (1997b). Practical experience on successful planting approaches is accumulating because of the large number of restoration projects that are taking place in all kinds of ecosystems. Some projects are conducted by the large industry of environmental consultants who work mostly on legally mandated programs (such as strip mine reclamation or wetland mitigation) while others are volunteer efforts which are often local or community-based. A side result

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