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Linking Restoration and Ecological Succession (Springer ... - Inecol

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92 Joachim Schrautzer et al.<br />

basis of theoretical considerations to represent the functionality of l<strong>and</strong>scape<br />

units <strong>and</strong> elements of environmental thermodynamics (Joergensen 2001). This<br />

selection is achieved by coupling gradient theory (Müller 1998) <strong>and</strong> orientor<br />

theory (Müller <strong>and</strong> Fath 1998). The result is a small set of indicators capable of<br />

representing ecosystem states <strong>and</strong> ecosystem integrity as a whole, i.e., focusing<br />

on the potential to develop self-organized processes (Müller et al. 2006). These<br />

characteristics are represented by orientors, that is, ecosystem variables that<br />

should increase throughout an untreated succession following ab<strong>and</strong>onment<br />

(Müller <strong>and</strong> Joergensen 2000). Changes in the indicators associated with fen<br />

restoration measures (rewetting, grazing, <strong>and</strong> mowing without fertilization) or<br />

ab<strong>and</strong>onment are modeled using a data set from our long-term experimental<br />

sites to parameterize the model. The Water <strong>and</strong> Substance Simulation Model<br />

WASMOD of Reiche (1994) was used for the simulations. Simulation modeling<br />

is used because data concerning the long-term changes in the process drivers<br />

of the water, carbon, <strong>and</strong> nutrient budgets are scarce. We use our own data to<br />

illustrate the establishment of species on fen sites, <strong>and</strong> what happens to species<br />

richness on these sites given cattle grazing <strong>and</strong> mowing. Finally, we include<br />

data concerning the longevity of seeds in the soils to assess the potential for<br />

reintroduction of target species in degraded fens. We conclude with a discussion<br />

of factors limiting the success of these restoration measures <strong>and</strong> the broader<br />

implications for the restoration of fens elsewhere in the region.<br />

5.2 Methods, Concepts, <strong>and</strong> Data Sets<br />

5.2.1 The Basic Set of Ecosystem Indicators<br />

The indicators chosen for this study have been compiled to represent ecosystem<br />

states as holistic entities. The variables refer to the following components of<br />

ecosystems (see Table 5.2):<br />

Ecosystem structures: Following the orientor approach for successional phases<br />

in undisturbed ecosystems, it can be hypothesized that the number of species<br />

increases through time, <strong>and</strong> that abiotic mechanisms become more complex.<br />

These changes are accompanied by increased ecosystem heterogeneity <strong>and</strong><br />

complexity.<br />

Ecosystem functions: Ecosystem processes can follow orientor behavior during<br />

succession. Due to increasing numbers of structural elements, the processes<br />

Table 5.2 Indicators selected to represent basic ecosystem components.<br />

Ecosystem component Indicator(S)<br />

Biotic structures Number of plant species<br />

Energy budgets, exergy capture Net primary production (NPP)<br />

Energy budgets, entropy production Microbial soil respiration (MSR)<br />

Energy budgets—metabolic efficiency NPP/soil respiration<br />

Hydrological budgets—biotic water flows NPP/transpiration<br />

Chemical budgets—nutrient loss Net nitrogen mineralization (NNM)<br />

Nitrate leaching<br />

Denitrification<br />

Chemical budgets, storage capacity Nitrogen balance<br />

Carbon balance

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