Hydrologic variability and the application of Index of Biotic Integrity metrics to wetlands: A great lakes evaluation

Wetlands ◽  
2002 ◽  
Vol 22 (3) ◽  
pp. 588-615 ◽  
Author(s):  
Douglas A. Wilcox ◽  
James E. Meeker ◽  
Patrick L. Hudson ◽  
Brian J. Armitage ◽  
M. Glen Black ◽  
...  
2005 ◽  
Vol 31 ◽  
pp. 171-187 ◽  
Author(s):  
Donald G. Uzarski ◽  
Thomas M. Burton ◽  
Matthew J. Cooper ◽  
Joel W. Ingram ◽  
Steven T.A. Timmermans

Author(s):  
Matthew J. Cooper ◽  
Gary A. Lamberti ◽  
Ashley H. Moerke ◽  
Carl R. Ruetz ◽  
Douglas A. Wilcox ◽  
...  

2007 ◽  
Vol 33 (sp3) ◽  
pp. 224-235 ◽  
Author(s):  
Yakuta Bhagat ◽  
Jan J. H. Ciborowski ◽  
Lucinda B. Johnson ◽  
Donald G. Uzarski ◽  
Thomas M. Burton ◽  
...  

1994 ◽  
Vol 51 (8) ◽  
pp. 1804-1822 ◽  
Author(s):  
Charles K. Minns ◽  
Victor W. Cairns ◽  
Robert G. Randall ◽  
James E. Moore

Karr's Index of Biotic Integrity (IBI) approach provides a biological measure of ecosystem health using a wide spectrum of metrics which can be extracted from fish catch data obtained using standardized methods. Extensive electrofishing surveys of littoral fish assemblages, conducted in three Great Lakes' Areas of Concern, provided the basis for developing a lacustrine IBI that was 12 metrics of three broad types: (i) species composition, (ii) trophic composition, and (iii) abundance and condition. In contrast with lotic IBIs where diversity and abundance metrics have mostly been used, several biomass metrics were adopted to accommodate the large size range of lentic fishes. The variability of repeated measures was low enough to allow valid testing of intertransect differences with three to five samples per transect. Comparisons among survey areas showed significant differences consistent with the varying levels of ecosystem degradation. Analyses of mean IBI values with measures of submerged vegetation density and cover by transect produced significant positive correlations. This IBI developed for the Great Lakes' littoral zone, both by design and by demonstrated correlations, integrates the effects of four main factors influencing fish assemblages and hence revealing ecosystem health: exotic fishes, water quality, physical habitat supply, and piscivore abundance.


Author(s):  
Frank H. McCormick ◽  
Robert M. Hughes ◽  
Philip R. Kaufmann ◽  
David V. Peck ◽  
John L. Stoddard ◽  
...  

2011 ◽  
Vol 71 (3) ◽  
pp. 577-586 ◽  
Author(s):  
NG Machado ◽  
EM. Venticinque ◽  
J. Penha

Over the last 30 years, the Cerrado has been experiencing various antropic impacts that have brought about alterations to species composition, structure and functioning of aquatic habitats. Therefore, studies on negative impacts are useful to prevent future damage and restore environmental quality. The objectives of our study were: i) to adapt an index of biotic integrity of streams in the Rio Cuiabá Basin and ii) to analyze if the Index of Biotic Integrity (IBI) correlated with the environmental quality measured by the Index of Environmental Quality (IEQ) and with the mesohabitat structure. We sampled 26 streams in sub-basins of the Cuiabá River. In each stream, we closed a stretch of 50 m with blockage nets and used electrofishing to capture fish. To obtain a measure of environmental quality in sampled units, we characterized the stream and its micro basin. For the analyses, we used the Spearman Correlation, Kruskal-Wallis test and Analysis of Multiple Regression. We collected 697 individuals distributed into 6 orders, 15 families and 49 species. The IBI followed changes on environmental quality measured by IEQ when we removed streams that present natural barriers from the analysis (r² = 0.4; r² = 0.58). Types of land use did not affect the biotic integrity (n = 26; df = 4; H = 4,860; p = 0.302), but natural and artificial barriers affected it (n = 26; df = 4; H = 11,027; p = 0.026). The IBI was not sensitive to variations in mesohabitat structure (F2,23 = 0.373; r² = 0.031; Axe 1 p = 0.620; Axe 2 p = 0.490). The IBI is certainly a reasonable instrument for evaluating changes in the environment, but we cannot ignore the fact that we were able to obtain the same result with any combinations of metrics. This makes its analysis and interpretation difficult.


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