Literature DB >> 26404430

Importance of Natural and Anthropogenic Environmental Factors to Fish Communities of the Fox River in Illinois.

Spencer Schnier1, Ximing Cai2, Yong Cao3.   

Abstract

The dominant environmental determinants of aquatic communities have been a persistent topic for many years. Interactions between natural and anthropogenic characteristics within the aquatic environment influence fish communities in complex ways that make the effect of a single characteristic difficult to ascertain. Researchers are faced with the question of how to deal with a large number of variables and complex interrelationships. This study utilized multiple approaches to identify key environmental variables to fish communities of the Fox River Basin in Illinois: Pearson and Spearman correlations, an algorithm based on information theory called mutual information, and a measure of variable importance built into the machine learning algorithm Random Forest. The results are based on a dataset developed for this study, which uses a fish index of biological integrity (IBI) and its ten component metrics as response variables and a range of environmental variables describing geomorphology, stream flow statistics, climate, and both reach-scale and watershed-scale land use as independent variables. Agricultural land use and the magnitude and duration of low flow events were ranked by the algorithms as key factors for the study area. Reach-scale characteristics were dominant for native sunfish, and stream flow metrics were rated highly for native suckers. Regression tree analyses of environmental variables on fish IBI identified breakpoints in percent agricultural land in the watershed (~64%), duration of low flow pulses (~12 days), and 90-day minimum flow (~0.13 cms). The findings should be useful for building predictive models and design of more effective monitoring systems and restoration plans.

Keywords:  Fish IBI; Land use; Mutual information; Regression tree; Stream fish; Stream flow

Mesh:

Year:  2015        PMID: 26404430     DOI: 10.1007/s00267-015-0611-0

Source DB:  PubMed          Journal:  Environ Manage        ISSN: 0364-152X            Impact factor:   3.266


  15 in total

1.  A multiscale conceptual framework for integrated ecogeomorphological research to support stream naturalization in the agricultural Midwest.

Authors:  Kelly M Frothingham; Bruce L Rhoads; Edwin E Herricks
Journal:  Environ Manage       Date:  2002-01       Impact factor: 3.266

2.  The mutual information: detecting and evaluating dependencies between variables.

Authors:  R Steuer; J Kurths; C O Daub; J Weise; J Selbig
Journal:  Bioinformatics       Date:  2002       Impact factor: 6.937

3.  Spatial-scale effects on relative importance of physical habitat predictors of stream health.

Authors:  Emmanuel A Frimpong; Trent M Sutton; Bernard A Engel; Thomas P Simon
Journal:  Environ Manage       Date:  2005-12       Impact factor: 3.266

4.  Random forests for classification in ecology.

Authors:  D Richard Cutler; Thomas C Edwards; Karen H Beard; Adele Cutler; Kyle T Hess; Jacob Gibson; Joshua J Lawler
Journal:  Ecology       Date:  2007-11       Impact factor: 5.499

5.  Identifying biotic integrity and water chemistry relations in nonwadeable rivers of Wisconsin: toward the development of nutrient criteria.

Authors:  Brian M Weigel; Dale M Robertson
Journal:  Environ Manage       Date:  2007-07-18       Impact factor: 3.266

6.  Effects of geomorphology, habitat, and spatial location on fish assemblages in a watershed in Ohio, USA.

Authors:  Jessica L D'Ambrosio; Lance R Williams; Jonathan D Witter; Andy Ward
Journal:  Environ Monit Assess       Date:  2008-02-06       Impact factor: 2.513

7.  Improving accuracy and efficiency of mutual information for multi-modal retinal image registration using adaptive probability density estimation.

Authors:  P A Legg; P L Rosin; D Marshall; J E Morgan
Journal:  Comput Med Imaging Graph       Date:  2013-08-30       Impact factor: 4.790

8.  How novel is too novel? Stream community thresholds at exceptionally low levels of catchment urbanization.

Authors:  Ryan S King; Matthew E Baker; Paul F Kazyak; Donald E Weller
Journal:  Ecol Appl       Date:  2011-07       Impact factor: 4.657

9.  Incorporating traits in aquatic biomonitoring to enhance causal diagnosis and prediction.

Authors:  Joseph M Culp; David G Armanini; Michael J Dunbar; Jessica M Orlofske; N LeRoy Poff; Amina I Pollard; Adam G Yates; Grant C Hose
Journal:  Integr Environ Assess Manag       Date:  2010-08-03       Impact factor: 2.992

10.  Bagging statistical network inference from large-scale gene expression data.

Authors:  Ricardo de Matos Simoes; Frank Emmert-Streib
Journal:  PLoS One       Date:  2012-03-30       Impact factor: 3.240

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  1 in total

1.  Predictive mapping of the biotic condition of conterminous U.S. rivers and streams.

Authors:  Ryan A Hill; Eric W Fox; Scott G Leibowitz; Anthony R Olsen; Darren J Thornbrugh; Marc H Weber
Journal:  Ecol Appl       Date:  2017-11-03       Impact factor: 4.657

  1 in total

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