Lake Ecosystem Health Assessment: Indicators and Methods
Introduction
During the last decades, the phrase “ecosystem health” has been used with increasing frequency in the literature. With increasing frequency, environmental managers have begun to consider the protection of ecosystem health as one of their primary goals in environmental management. Since the late 1980s, the International Society for Aquatic Ecosystem Health and Management (ISAEHM), the International Ecosystem Health Society (IEHS), and the international publications Aquatic Ecosystem Health and Management and Ecosystem Health have made significant contributions to the theoretical development of this new field. A number of different definitions (e.g. Karr et al., 1986; Schaeffer et al., 1988; Rapport, 1989; Kay, 1991; Norton, 1992; Costanza, 1992; Haskell et al., 1992; Page, 1992; Ulanowicz, 1992) and indicators (e.g. Hannon, 1985; Rapport et al., 1985; Karr et al., 1986; Ulanowicz (1986), Ulanowicz (1992); Kay and Schneider, 1991; Costanza, 1992; Jørgensen (1995a), Jørgensen (1995b)) have been proposed and discussed in the literatures. Costanza, in 1992, summarized the conceptual attributes comprising the definition of ecosystem health as follows: (1) homeostasis; (2) absence of disease, (3) diversity or complexity; (4) stability or resilience; (5) vigor or scope for growth; and, (6) balance between system components. He went on to emphasize that it was necessary to consider all or at least a majority of the definition's attributes simultaneously in order to achieve a viable working understanding.
Historically, ecosystem health was measured using indices for a particular species or other components of the system. Many of those efforts, however, were found to be somewhat restrictive or lacking in terms of completeness of the system as a whole. In order to better reflect ecosystem complexities, a number of new indices have been proposed, e.g. gross ecosystem product (GEP) (Hannon, 1985), ecosystem stress indicators (Rapport et al., 1985), the index of biotic integrity (IBI) (Karr et al., 1986), the index of network ascendancy (Ulanowicz (1986), Ulanowicz (1992)), the overall system health index (HI=V×O×R) (Costanza, 1992), and exergy, structural exergy, and ecological buffer capacities (Jørgensen (1995a), Jørgensen (1995b))). Clearly, the different indicators cover different aspects of ecosystem health. A more complete image, however, of the conditions behind ecosystem health may require the simultaneous application of several such indicators (Jørgensen, 1997). This seems further supported given the breadth in scope of ecosystem health as a concept. Certainly it encompasses not only biophysical dimensions, but also social, economic, and human aspects as well (Karr, 1992; Rapport, 1995).
Several procedures for ecosystem health assessment have been proposed. Schaeffer et al. (1988) suggested seven guidelines. Haskell et al. (1992) suggested the following sequence for those guidelines: (1) identifying symptoms; (2) identifying and measuring vital signs; (3) making a preliminary provisional diagnosis; (4) conducting tests to verify the diagnosis; (5) making a prognosis; and (6) prescribing treatment. Jørgensen (1995a) suggested a tentative procedure for the practical assessment of ecosystem health where the ecological indicators (exergy, structural exergy, and buffer capacities) would be used to: (1) identify the relevant questions related to the health of the ecosystem under consideration; (2) assess the most important mass flows and mass balances related to these questions; (3) make a conceptual diagram of the ecosystem, including the components most important for the mass flows defined in (2); (4) develop a steady state or dynamic model using the conventional procedure (Jørgensen, l994); (5) calculate the exergy, structural exergy, and relevant buffer capacities using a model; and, (6) assess the ecosystem health according to the values of exergy, structural exergy, and buffer capacities obtained from the model.
The objectives of this paper are: (1) to propose a set of comprehensive ecological indicators including structural, functional, and system-level aspects to be used in lake ecosystem health assessments; (2) to propose two methods for lake ecosystem health assessment; and, (3) to apply the suggested ecological indicators and methods to the ecosystem health assessment of a Chinese shallow lake (Lake Chao).
Section snippets
Ecological indicators for assessing lake ecosystem health
Chemical stresses impact Lake ecosystems on a global scale. Ecological indicators for lake ecosystem health assessment resulting from chemical stress are important for both the early warning signs of ecosystem malfunction and confirmation of the presence of a significant ecosystem pathology (Rapport et al., 1985; Rapport, 1995). Ecological indicators, as valid and reliable tools, should include structural, functional, and system-level aspects. Xu (l997b) examined the structural, functional, and
Direct measurement method (DMM)
The procedures established for the direct measurement method (DMM) are as follows: (l) identify the necessary indicators from Table l to be applied in the assessment process; (2) measure directly or calculate indirectly the selected indicators using the formulas in Table 1; and, (3) assess ecosystem health based on the resulting indicator values.
Ecological modeling method (EMM)
The procedures established for the ecological modeling method (EMM) for lake ecological health assessment are shown in Fig. 1. Five steps are necessary
A case study: an ecosystem health assessment of Lake Chao
Lake Chao is one of the largest fresh-water lakes in China. It is also one of the most eutrophied (see Xu, 1997a for details). In the early 1950s, the lake was covered with macrophytes appearing in sequence from floating plants to submerged plants to leafy floating plants to the emergence of plants from the open waters to the shore. More than 190 species of zooplankton were identified along with a large number of benthonic animals and fishery resources dominated by piscivorous fish. The
Assessment results
The results obtained as a result of the two assessment methods, the direct measurement method (DMM) and the ecological modeling method (EMM), are very similar. These results were also correspondence with the observed eutrophic state at Lake Chao. In terms of the observations made from April 1987 to March 1988, the most serious algal bloom occurred between August and October of 1987 (summer–autumn bloom). Another algal bloom occurred between April and May 1987 (spring bloom). These two algal
Conclusions
A set of ecological indicators including structural, functional, and system-level aspects were proposed in this paper for the assessment of lake ecosystem health. Generally speaking, with regard to a lake's ecological structural, a healthy lake ecosystem is characterized by small cell sized phytoplankton, large body sized zooplankton, high zooplankton and macrozooplankton biomasses, low phytoplankton and microzooplankton biomasses, high species diversity, a high zooplankton to phytoplankton
Acknowledgements
The authors are greatly indebted to Professor S. E. Jørgensen, Drs. S. N. Nielson and J. Salomonsen from the Royal Danish School of Pharmacy for their valuable suggestions. The project was supported by National Natural Science Foundation of China (39970121) and Scientific Foundation for Returned Overseas Chinese Scholars, Ministry of Education. Special thanks are also to anonymous reviewers for their helpful comments.
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