title: Lake ecosystem health assessment: indicators and methods.
abstract: A set of ecological indicators including structural, functional, and system-level aspects were proposed for a lake ecosystem health assessment, according to the structural, functional, and system-level responses of lake ecosystems to chemical stresses including acidification, eutrophication and copper, oil and pesticide contamination. The structural indicators included phytoplankton cell size and biomass, zooplankton body size and biomass, species diversity, macro- and micro-zooplankton biomass, the zooplankton phytoplankton ratio, and the macrozooplankton microzooplankton ratio. The functional indicators encompassed the algal C assimilation ratio, resource use efficiency, community production, gross production/respiration (i.e. P/R) ratio, gross production standing crop biomass (i.e. P/B) ratio, and standing crop biomass unit energy flow (i.e. B/E) ratio. The ecosystem-level indicators conisisted of ecological buffer capacities, energy, and structural energy. Based on these indicators, a direct measurement method (DMM) and an ecological modeling method (EMM) for lake ecosystem health assessment were developed. The DMM procedures were designed to: (1) identify key indicators; (2) measure directly or calculate indirectly the selected indicators; and, (3) assess ecosystem health on the basis of the indicator values. The EMM procedures were designed to: (1) determine the structure and complexity of the ecological model according to the lake's ecosystem structure; (2) establish an ecological model by designing a conceptual diagram, establishing model equations, and estimating model pararmeters; (3) compare the simulated values of important state variables and process rates with actual observations; (4) calculate ecosystem health indicators using the ecological model; and, (5) assess lake ecosystem health according to the values of the ecological indicators. The results of a case study demonstrated that both methods provided similar results which corresponded with the lake's actual trophic state.
authors.affiliation: Department of Urban and Environmental Sciences, Peking University, Beijing, China. xufl@urban.pku.edu.cn
authors.forename: F L
authors.initials: FL
authors.lastname: Xu
authors.forename: S
authors.initials: S
authors.lastname: Tao
authors.forename: R W
authors.initials: RW
authors.lastname: Dawson
authors.forename: P G
authors.initials: PG
authors.lastname: Li
authors.forename: J
authors.initials: J
authors.lastname: Cao
mesh_terms: D000818:Animals; D018533:Biomass; D002681:China; D003247:Conservation of Natural Resources; D017753:Ecosystem; D056890:Eukaryota / Q000302:isolation & purification / Q000502:physiology; D020387:Food Chain; D005618:Fresh Water / Q000737:chemistry* / Q000469:parasitology*; D008954:Models, Biological; D010839:Phytoplankton / Q000166:cytology / Q000302:isolation & purification / Q000502:physiology; D013997:Time Factors; D014871:Water Microbiology / Q000592:standards*; D014874:Water Pollutants, Chemical / Q000009:adverse effects / Q000032:analysis*; D015048:Zooplankton / Q000166:cytology / Q000302:isolation & purification / Q000502:physiology
chemical_list: D014874:Water Pollutants, Chemical