Limits...
A new fish-based multi-metric assessment index for cyprinid streams in the Iranian Caspian Sea Basin.

Mostafavi H, Schinegger R, Melcher A, Moder K, Mielach C, Schmutz S - Limnologica (2015)

Bottom Line: In addition, we used 29 criteria describing major anthropogenic human pressures at sampling sites and generated a regional pressure index (RPI) that accounted for potential effects of multiple human pressures.Finally, seven fish metrics showed the best ability to discriminate between impaired and reference sites.The multi-metric fish index performed well in discriminating human pressure classes, giving a significant negative linear response to a gradient of the RPI.

View Article: PubMed Central - PubMed

Affiliation: Department of Water, Atmosphere and Environment, Institute of Hydrobiology and Aquatic Ecosystem Management, BOKU University of Natural Resources and Life Sciences, Vienna, Austria ; Department of Bio-diversity and Ecosystem Management, Environmental Sciences Research Institute, Shahid Beheshti University, Tehran, Iran.

ABSTRACT

A major issue for water resource management is the assessment of environmental degradation of lotic ecosystems. The overall aim of this study is to develop a multi-metric fish index for the cyprinid streams of the Caspian Sea Basin (MMICS) in Iran. As species diversity and composition as well as population structure in the studied streams are different to other regions, there is a substantial need to develop a new fish index. We sampled fish and environmental data of 102 sites in medium sized streams. We analysed human pressures at different spatial scales and determined applicable fish metrics showing a response to human pressures. In total, five structural and functional types of metrics (i.e. biodiversity, habitat, reproduction, trophic level and water quality sensitivity) were considered. In addition, we used 29 criteria describing major anthropogenic human pressures at sampling sites and generated a regional pressure index (RPI) that accounted for potential effects of multiple human pressures. For the MMICS development, we first defined reference sites (least disturbed) and secondly quantified differences of fish metrics between reference and impaired sites. We used a Generalised Linear Model (GLM) to describe metric responses to natural environmental differences in least disturbed conditions. By including impaired sites, the residual distributions of these models described the response range of each metric to human pressures, independently of natural environmental influence. Finally, seven fish metrics showed the best ability to discriminate between impaired and reference sites. The multi-metric fish index performed well in discriminating human pressure classes, giving a significant negative linear response to a gradient of the RPI. These methods can be used for further development of a standardised monitoring tool to assess the ecological status and trends in biological condition for streams of the whole country, considering its complex and diverse geology and climate.

No MeSH data available.


Multi-metric fish index of original dataset (MMICS) versus environmental predictor variables.
© Copyright Policy - CC BY-NC-ND
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4418740&req=5

fig0040: Multi-metric fish index of original dataset (MMICS) versus environmental predictor variables.

Mentions: Stepwise linear regression between the multi-metric fish index of original dataset (MMICS) and environmental predictor variables (drainage size, slope, minimum air temperature, range temperature and precipitation) showed that none of the environmental variables was retained and the variability in this index (MMICS) explained by these environmental variables was not significant (p > 0.05) (see also Fig. 8).


A new fish-based multi-metric assessment index for cyprinid streams in the Iranian Caspian Sea Basin.

Mostafavi H, Schinegger R, Melcher A, Moder K, Mielach C, Schmutz S - Limnologica (2015)

Multi-metric fish index of original dataset (MMICS) versus environmental predictor variables.
© Copyright Policy - CC BY-NC-ND
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4418740&req=5

fig0040: Multi-metric fish index of original dataset (MMICS) versus environmental predictor variables.
Mentions: Stepwise linear regression between the multi-metric fish index of original dataset (MMICS) and environmental predictor variables (drainage size, slope, minimum air temperature, range temperature and precipitation) showed that none of the environmental variables was retained and the variability in this index (MMICS) explained by these environmental variables was not significant (p > 0.05) (see also Fig. 8).

Bottom Line: In addition, we used 29 criteria describing major anthropogenic human pressures at sampling sites and generated a regional pressure index (RPI) that accounted for potential effects of multiple human pressures.Finally, seven fish metrics showed the best ability to discriminate between impaired and reference sites.The multi-metric fish index performed well in discriminating human pressure classes, giving a significant negative linear response to a gradient of the RPI.

View Article: PubMed Central - PubMed

Affiliation: Department of Water, Atmosphere and Environment, Institute of Hydrobiology and Aquatic Ecosystem Management, BOKU University of Natural Resources and Life Sciences, Vienna, Austria ; Department of Bio-diversity and Ecosystem Management, Environmental Sciences Research Institute, Shahid Beheshti University, Tehran, Iran.

ABSTRACT

A major issue for water resource management is the assessment of environmental degradation of lotic ecosystems. The overall aim of this study is to develop a multi-metric fish index for the cyprinid streams of the Caspian Sea Basin (MMICS) in Iran. As species diversity and composition as well as population structure in the studied streams are different to other regions, there is a substantial need to develop a new fish index. We sampled fish and environmental data of 102 sites in medium sized streams. We analysed human pressures at different spatial scales and determined applicable fish metrics showing a response to human pressures. In total, five structural and functional types of metrics (i.e. biodiversity, habitat, reproduction, trophic level and water quality sensitivity) were considered. In addition, we used 29 criteria describing major anthropogenic human pressures at sampling sites and generated a regional pressure index (RPI) that accounted for potential effects of multiple human pressures. For the MMICS development, we first defined reference sites (least disturbed) and secondly quantified differences of fish metrics between reference and impaired sites. We used a Generalised Linear Model (GLM) to describe metric responses to natural environmental differences in least disturbed conditions. By including impaired sites, the residual distributions of these models described the response range of each metric to human pressures, independently of natural environmental influence. Finally, seven fish metrics showed the best ability to discriminate between impaired and reference sites. The multi-metric fish index performed well in discriminating human pressure classes, giving a significant negative linear response to a gradient of the RPI. These methods can be used for further development of a standardised monitoring tool to assess the ecological status and trends in biological condition for streams of the whole country, considering its complex and diverse geology and climate.

No MeSH data available.