SPATIOTEMPORAL VARIABILITY OF TEMPERATE LAKE MACROINVERTEBRATE COMMUNITIES - DETECTION OF IMPACT

Authors
Citation
Rk. Johnson, SPATIOTEMPORAL VARIABILITY OF TEMPERATE LAKE MACROINVERTEBRATE COMMUNITIES - DETECTION OF IMPACT, Ecological applications, 8(1), 1998, pp. 61-70
Citations number
35
Categorie Soggetti
Ecology
Journal title
ISSN journal
10510761
Volume
8
Issue
1
Year of publication
1998
Pages
61 - 70
Database
ISI
SICI code
1051-0761(1998)8:1<61:SVOTLM>2.0.ZU;2-7
Abstract
Field assessments of environmental impacts often are confounded by att empts to isolate effects of interest (perturbation-induced impacts) fr om noise introduced by natural spatial and temporal variability. Detec tion of impact often is constrained by variability of the data, the nu mber of independent samples, the magnitude of impact to be detected, a nd statistical assumptions. Analysis of the spatial and temporal varia bility of macroinvertebrate indicator metrics of 16 Swedish lakes, sit uated in the boreo-nemoral ecoregion, revealed that standardized effec t sizes (i.e., effect sizes expressed in standard deviation units) and estimates of statistical power varied markedly among habitats and wit h choice of indicator metric. In general, indicator metrics relying on measures of the number of taxa (taxon richness, diversity, and ASPT, average score per taxon), and pollution-specific metrics relying on ta xon tolerance to pollution (acidification index) had higher standardiz ed effect size and greater statistical power (primarily due to lower v ariability) than did measures of macroinvertebrate density and biomass . Indicator metrics for macroinvertebrate communities of sublittoral h abitats often revealed greater standardized effect sizes and statistic al power estimates than did metrics for profundal habitats, indicating that sublittoral habitats may provide more robust estimates of acidif ication stress. The greatest standardized effect occurred for the poll ution-specific acidification index of littoral habitats. Selecting ind icator metrics for field assessment of impact should be carefully done , and in particular, more focus should be placed on evaluating the rob ustness of indicator metrics by analyzing indicator metric variance, e xpected effect size, and statistical power.