USGS

RELATION OF ENVIRONMENTAL CHARACTERISTICS TO THE COMPOSITION OF AQUATIC ASSEMBLAGES ALONG A GRADIENT OF URBAN LAND USE IN NEW JERSEY, 1996-98

U.S. Geological Survey Water-Resources Investigations Report 02-4069

By Jonathan G. Kennen and Mark A. Ayers


ABSTRACT

Community data from 36 watersheds were used to evaluate the response of fish, invertebrate, and algal assemblages in New Jersey streams to environmental characteristics along a gradient of urban land use that ranged from 3 to 96 percent. Aquatic assemblages were sampled at 36 sites during 1996-98, and more than 400 environmental attributes at multiple spatial scales were summarized. Data matrices were reduced to 43, 170, and 103 species of fish, invertebrates, and algae, respectively, by means of a predetermined joint frequency and relative abundance approach. White sucker (Catostomus commersoni) and Tessellated darter (Etheostoma olmstedi) were the most abundant fishes, accounting for more than 20 and 17 percent, respectively, of the mean abundance. Net-spinning caddisflies (Hydropsychidae) were the most commonly occurring benthic invertebrates and were found at all but one of the 36 sampling sites. Blue-green (for example, Calothrix sp. and Oscillatoria sp.) and green (for example, Protoderma viride) algae were the most widely distrib-uted algae; however, more than 81 percent of the algal taxa collected were diatoms.


Principal-component and correlation analyses were used to reduce the dimensionality of the environmental data. Multiple linear regression analysis of extracted ordination axes then was used to develop models that expressed effects of increasing urban land use on the structure of aquatic assemblages. Significant environmental variables identified by using multiple linear regression analysis then were included in a direct gradient analysis. Partial canonical correspondence analysis of relativized abundance data was used to restrict further the effects of residual natural variability, and to identify relations among the environmental variables and the structure of fish, invertebrate, and algal assemblages along an urban land-use gradient. Results of this approach, combined with the results of the multiple linear regression analyses, were used to identify human population density (311-37,594 persons/km2), amount and type of impervious surface cover (0.12-1,350 km2), nutrient concentrations (for example, 0.01-0.29 mg/L of phosphorus), hydrologic instability (for example, 100-8,955 ft3/s for 2-year peak flow), the amount of forest and wetlands in a basin (0.01-6.25 km2), and substrate quality (0-87 percent cobble substrate) as variables that are highly correlated with aquatic-assemblage structure. Species distributions in ordination space clearly indicate that tolerant species are more abundant in the streams impaired by urbanization and sensitive taxa are more closely associated with the least impaired basins. The distinct differences in aquatic assemblages along the urban land-use gradient demonstrate the deleterious effects of urbanization on assemblage structure and indicate that conserving landscape attributes that mitigate anthropogenic influences (for example, stormwater-management practices emphasizing infiltration and preservation of existing forests, wetlands, and riparian corridors) will help to maintain the relative abundance of sensitive taxa. Complementary multiple linear regression models indicate that aquatic community indices were correlated with many of the anthropogenic factors that were found to be significant along the urban land-use gradient. These indices appear to be effective in differentiating the moderately and severely impaired streams from the minimally impaired streams. Evaluation of disturbance thresholds for aquatic assemblages indicates that moderate to severe impairment is detectable in New Jersey streams when impervious surface cover in the drainage basin reaches approximately 18 percent.

CONTENTS

Glossary

Abstract

Introduction

Purpose and Scope

Study area

Acknowledgments

Approach

Design of land-use gradient

Aggregation of anthropogenic factors used in assessment

Data collection

Stream Characteristics

Habitat

Ichthyofauna

Macroinvertebrates

Attached algae (periphyton)

Water quality

Volatile organic compounds (VOCs)

Pesticides

Trace elements and organochlorine compounds in bed sediment

Watershed characteristics

Interpretation of digital data

Derivation of the index of impervious area

Flow-path length and topography

Analytical methods

Spatial and temporal assessment

Univariate and multivariate approaches

Principal components analysis

Detrended correspondence analysis

Multiple linear regression

Indices of aquatic community impairment

Partial canonical correspondence analysis

Analysis of benchmark communities

Resolution of taxonomic ambiguities and data censoring

Variability of aquatic communities

Species abundance

Spatial and temporal variability in aquatic assemblages

Distinctions among benchmark community groups

Identification of important environmental variables

Indirect gradient assessment of aquatic assemblages

Significant environmental factors

Environmental associations across multiple pCCA axes

Relation of environmental characteristics to aquatic assemblages

Impervious surfaces

Hydrologic instability

Effects of runoff quality

Erosion, sedimentation, and stream-channel modification

Trace elements

Riparian conditions and stream buffers

Forest and wetlands

Relation of land-use changes to assemblage structure of long-lived species

Community indices

Indicator taxa

Complementary analytical techniques

Summary and conclusions

References cited


For additional information write to:


NAWQA Project Chief

U.S. Geological Survey

Mountain View Office Park

810 Bear Tavern Road, Suite 206

West Trenton, NJ 08628

 

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U.S. Geological Survey

Branch of Information Services

Box 25286, Federal Center

Denver, CO 80225-0286

 

Information about the National Water-Quality Assessment (NAWQA) Program is available on the Internet through the World Wide Web at http://water.usgs.gov/nawqa/nawqa_home or http://nj.usgs.gov/nawqa/.

 

 


 

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