Cover. (Top) Four geographic regions described in this report and locations of 91 long-term surface-water status 

and trend sites. (Bottom, left to right) Photographs showing achnanthidium minutissimum, a monoraphid diatom (Potapova, 2009); 

neophylax, (Autumn Mottled Sedges) Caddisfly Larva (Photograph by Steven Fend, USGS); Oncorhynchus mykiss, Rainbow Trout 

(Photograph by Terry Maret, USGS).

National Water-Quality Assessment Program

Multi-Regional Synthesis of Temporal Trends in Biotic 

Assemblages in Streams and Rivers of the Continental 

United States

Scientific Investigations Report 2013–5046

U.S. Department of the Interior

U.S. Geological Survey
Cover. (Top) Four geographic regions described in this report and locations of 91 long-term surface-water status and trend sites. (Bottom, 

left to right) Photographs showing Achnanthidium minutissimum, a monoraphid diatom (Potapova, 2009); Neophylax, (Autumn Mottled Sedges) 

Caddisfly Larva (Photograph by Steven Fend, USGS); Oncorhynchus mykiss, Rainbow Trout (Photograph by Terry Maret, USGS).
Multi-Regional Synthesis of Temporal 

Trends in Biotic Assemblages in Streams 

and Rivers of the Continental United States

By Matthew P. Miller, Anne M.D. Brasher, and Jonathan G. Kennen

National Water-Quality Assessment Program 

Scientific Investigations Report 2013–5046

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

KEN SALAZAR, Secretary

U.S. Geological Survey

Suzette M. Kimball, Acting Director

U.S. Geological Survey, Reston, Virginia: 2013

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Suggested citation:

Miller, M.P., Brasher, A.M.D., and Kennen, J.G., 2013, Multi-regional synthesis of temporal trends in biotic 

assemblages in streams and rivers of the continental United States: U.S. Geological Survey Scientific Investigations 

Report 2013–5046, 20 p.
iii

Foreword

The U.S. Geological Survey (USGS) is committed to providing the Nation with reliable scientific information that helps to 

enhance and protect the overall quality of life and that facilitates effective management of water, biological, energy, and mineral 

resources (http://www.usgs.gov/). Information on the Nation’s water resources is critical to ensuring long-term availability of 

water that is safe for drinking and recreation and is suitable for industry, irrigation, and fish and wildlife. Population growth and 

increasing demands for water make the availability of that water, measured in terms of quantity and quality, even more essential 

to the long-term sustainability of our communities and ecosystems.

The USGS implemented the National Water-Quality Assessment (NAWQA) Program in 1991 to support national, regional, 

State, and local information needs and decisions related to water-quality management and policy (http://water.usgs.gov/nawqa). 

The NAWQA Program is designed to answer: What is the quality of our Nation’s streams and groundwater? How are conditions 

changing over time? How do natural features and human activities affect the quality of streams and groundwater, and where 

are those effects most pronounced? By combining information on water chemistry, physical characteristics, stream habitat, and 

aquatic life, the NAWQA Program aims to provide science-based insights for current and emerging water issues and priorities. 

From 1991 to 2001, the NAWQA Program completed interdisciplinary assessments and established a baseline understanding of 

water-quality conditions in 51 of the Nation’s river basins and aquifers, referred to as Study Units (http://water.usgs.gov/nawqa/

studies/study_units.html).

In the second decade of the Program (2001–2012), a major focus is on regional assessments of water-quality conditions and 

trends. These regional assessments are based on major river basins and principal aquifers, which encompass larger regions of the 

country than the Study Units. Regional assessments extend the findings in the Study Units by filling critical gaps in characterizing the quality of surface water and groundwater, and by determining water-quality status and trends at sites that have been 

consistently monitored for more than a decade. In addition, the regional assessments continue to build an understanding of how 

natural features and human activities affect water quality. Many of the regional assessments employ modeling and other scientific tools, developed on the basis of data collected at individual sites, to help extend knowledge of water quality to unmonitored, 

yet comparable areas within the regions. The models thereby enhance the value of our existing data and our understanding of 

the hydrologic system. In addition, the models are useful in evaluating various resource-management scenarios and in predicting 

how our actions, such as reducing or managing nonpoint and point sources of contamination, land conversion, and altering flow 

and (or) pumping regimes, are likely to affect water conditions within a region.

Other activities planned during the second decade include continuing national syntheses of information on pesticides, volatile organic compounds (VOCs), nutrients, trace elements, and aquatic ecology; and continuing national topical studies on the 

fate of agricultural chemicals, effects of urbanization on stream ecosystems, bioaccumulation of mercury in stream ecosystems, 

effects of nutrient enrichment on stream ecosystems, and transport of contaminants to public-supply wells.

The USGS aims to disseminate credible, timely, and relevant science information to address practical and effective waterresource management and strategies that protect and restore water quality. We hope this NAWQA publication will provide you 

with insights and information to meet your needs, and will foster increased citizen awareness and involvement in the protection 

and restoration of our Nation’s waters. 

The USGS recognizes that a national assessment by a single program cannot address all water-resource issues of interest. 

External coordination at all levels is critical for cost-effective management, regulation, and conservation of our Nation’s water 

resources. The NAWQA Program, therefore, depends on advice and information from other agencies—Federal, State, regional, 

interstate, Tribal, and local—as well as nongovernmental organizations, industry, academia, and other stakeholder groups. Your 

assistance and suggestions are greatly appreciated.

William H. Werkheiser

USGS Associate Director for Water
iv

Contents

Foreword ........................................................................................................................................................iii

Abstract...........................................................................................................................................................1

Introduction.....................................................................................................................................................1

Purpose and Scope ..............................................................................................................................2

Approach and Methods................................................................................................................................3

Sites.........................................................................................................................................................3

Sample Collection and Data Processing ..........................................................................................3

Biota...............................................................................................................................................3

Environmental Variables.............................................................................................................4

Statistical Analyses..............................................................................................................................4

Multi-Regional Comparisons of Biotic Trends and Drivers of Trends...................................................5

Trends in Biotic Assemblages ...........................................................................................................5

Trends as a Function of Biotic Assemblage............................................................................5

Trends as a Function of Region .................................................................................................6

Trends as a Function of Land Use.............................................................................................7

Environmental Drivers of Trends ........................................................................................................9

Study Limitations and Future Directions..................................................................................................11

Summary and Conclusions.........................................................................................................................12

Acknowledgments.......................................................................................................................................13

References Cited..........................................................................................................................................13
v

Figures

1. Map showing the spatial distribution of the 91 long-term surface-water status and 

trend sites in the continental United States.............................................................................2

2. Graphs showing non-metric multidimensional scaling (NMDS) seriation plots for 

the Buffalo River near Boxley, Arkansas, for A, macroinvertebrate assemblage and 

B, fish assemblage .......................................................................................................................6

3. Graph showing percentage of sites where significant temporal trends were 

identified for each biotic assemblage when data from all regions were combined.........6

4. Graphs showing percentage of sites in each region where significant temporal 

trends were identified for A, one or more of the biotic assemblages, B, algal 

assemblages, C, macroinvertebrate assemblages, and D, fish assemblages ...................7

5. Graphs showing percentage of sites in each land-use category where significant 

temporal trends were identified for A, all biotic assemblages combined, B, algal 

assemblages, C, macroinvertebrate assemblages, and D, fish assemblages ...................8

6. Graph showing percentage of sites with significant correlations between one 

or more biotic assemblages and environmental-variable category ....................................9

7. Graphs showing percentage of sites in each region with significant correlations 

between the biotic assemblage and environmental-variable categories for A, all 

biotic assemblages combined, B, algal assemblages, C, macroinvertebrate 

assemblages, and D, fish assemblages..................................................................................11

Tables

1. General site characteristics for the 91 U.S. Geological Survey National WaterQuality Assessment Program long-term surface-water status and trend sites ..............17

2. Environmental-variable categories found to be significantly correlated with the 

biotic assemblage for sites/biotic assemblages that were identified as having 

significant temporal trends in the northeastern/north-central, southeastern, 

and south-central regions.........................................................................................................10
vi

Conversion Factors and Abbreviations

Inch/Pound to SI

Multiply By To obtain

Length

mile (mi) 1.609 kilometer (km)

SI to Inch/Pound

Multiply By To obtain

Length

kilometer (km) 0.6214 mile (mi)

meter (m) 1.094 yard (yd) 

Area

square meter (m2) 0.0002471 acre 

square kilometer (km2) 247.1 acre

square meter (m2) 10.76 square foot (ft2) 

square kilometer (km2) 0.3861 square mile (mi2)

Abbreviations

ADAS Algal Data Analysis System

IDAS Invertebrate Data Analysis System

NARS National Aquatic Resource Survey

NAWQA National Water-Quality Assessment

NMDS Non-metric multidimensional scaling

NWIS National Water Information System

NWQL National Water-Quality Laboratory

PRIMER Plymouth Routines In Multivariate Ecological Research

PRISM Parameter elevation Regressions on Independent Slopes Model 

PTI Pesticide toxicity index

USGS U.S. Geological Survey
Multi-Regional Synthesis of Temporal Trends in Biotic 

Assemblages in Streams and Rivers of the Continental 

United States

By Matthew P. Miller, Anne M.D. Brasher, and Jonathan G. Kennen

Abstract

Biotic assemblages in aquatic ecosystems are excellent 

integrators and indicators of changing environmental conditions within a watershed. Therefore, temporal changes in 

abiotic environmental variables often can be inferred from 

temporal changes in biotic assemblages. Algae, macroinvertebrate, and fish assemblage data were collected from 91 

sampling sites in 4 geographic regions (northeastern/northcentral, southeastern, south-central, and western), collectively 

encompassing the continental United States, from 1993 to 

2009 as part of the U.S. Geological Survey National WaterQuality Assessment Program. This report uses a multivariate 

approach to synthesize temporal trends in biotic assemblages 

and correlations with relevant abiotic parameters as a function 

of biotic assemblage, geographic region, and land use. Of the 

three groups of biota, algal assemblages had temporal trends at 

the greatest percentage of sites. Of the regions, a greater percentage of sites in the northeastern/north-central and western 

regions had temporal trends in biotic assemblages. In terms of 

land use, a greater percentage of watersheds draining agricultural, urban, and undeveloped areas had significant temporal 

changes in biota, as compared to watersheds with mixed use. 

Correlations between biotic assemblages and abiotic variables 

indicate that, in general, macroinvertebrate assemblages correlated with water quality and fish assemblages correlated with 

physical habitat. Taken together, results indicate that there 

are regional differences in how individual biotic assemblages 

(algae, macroinvertebrates, and fish) respond to different abiotic drivers of change. 

Introduction

Biotic assemblages (algae, macroinvertebrates, and fish) 

in aquatic ecosystems are influenced by hydrologic, physicalhabitat, water-quality, and land-use conditions in the stream 

and watershed. Consequently, temporal changes taking place 

in the abiotic environment often can be inferred from observed 

temporal changes in the composition of biotic assemblages. 

Monitoring temporal change in biotic assemblages can provide 

an early indication of abiotic environmental change; can 

complement information on hydrologic, physical, and waterquality conditions; and is important to understanding the 

long-term incremental effects of human and natural effects on 

ecosystems. Additionally, understanding how biotic assemblages change over time is important for characterizing biological integrity, which is a major focus of the Clean Water Act 

(Cairns, 1975; Frey, 1975; Karr, 1981; Karr and Chu, 1997). 

While numerous studies have investigated temporal trends 

in biotic metrics and (or) assemblages (Jackson and Füreder, 

2006 and references therein), broad multi-regional temporal 

changes in biotic assemblages have been poorly documented 

because of a lack of long-term datasets and an inability to 

identify a common approach for evaluating trends. Synthesizing common temporal patterns at large geographic scales (for 

example, the regional scale) is one way to better understand 

how environmental and anthropogenic conditions are more 

broadly affecting aquatic ecosystems.

The U.S. Geological Survey (USGS) National WaterQuality Assessment (NAWQA) Program evaluated ecological 

trends in each of four geographic regions (northeastern/northcentral, southeastern, south-central, and western) in order to 

document temporal change and the processes responsible for 

change in each region (fig. 1). Within each region, temporal 

change in biotic assemblages has been assessed among a 

broad range of abiotic environmental conditions and in diverse 

land-use settings. These region-specific studies have identified 

biotic metrics that are representative of, and abiotic metrics 

that may be responsible for, observed temporal change in 

biotic assemblages. In addition to the region-specific findings described in these studies, the data collected as part of 

these efforts provide a foundation from which among-region 

differences in trends in biotic assemblages can be synthesized 

and compared. Specifically, data presented in the regionspecific reports provide an opportunity to identify—at a broad 

spatial scale—how the percentage of sites with temporal 
2 Multi-Regional Synthesis of Temporal Trends in Biotic Assemblages in Streams and Rivers of the United States

MAD

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FRIO SALD

CHAM TRIN

MERM

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BTHMP SUGAR

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FANNO EFDAR

ZOLLN

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ROCRK

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GRANG

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OREST

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SAGUC

WHITE CLEAR

WHISK

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URB-NEUS

Geographic region

Northeastern/North-Central

Southeastern

South-Central

Western

Land-use category

Agriculture

Urban

Undeveloped

Mixed

Location of long-term surface-water 

status and trend site and station code

WCLCK

50° 120° 110° 100° 90° 80° 70°

40°

30°

0 250 500 MILES

0 250 500 KILOMETERS

EXPLANATION

Base modified from U.S. Geological Survey

1:2,000,000-scale digital data

Figure 1. The spatial distribution of the 91 long-term surface-water status and trend sites in the continental United States. The 

four geographic regions described in the report are shown, and dominant land use at each site is indicated by the color of the 

site symbols.

trends in biotic assemblages vary among (1) biotic assemblages (for example, if one biotic assemblage—algae—tends 

to change at a greater percentage of sites than another biotic 

assemblage—fish); (2) geographic regions; and (3) land-use 

categories. Such a multi-regional analysis is relevant to the 

management of stream ecosystems at the regional and national 

scale and can provide information that may be useful in 

developing public policy necessary for land-use and resource 

development decisions.

Purpose and Scope

The purpose of this report is to summarize and synthesize the findings of four regional studies of temporal trends 

in biotic assemblages (algae, macroinvertebrates, and fish) 

collected as part of the NAWQA Program. These reports 

include published journal articles describing trends in the 

combined northeastern and north-central United States (U.S.) 

(Kennen and others, 2012) and the south-central U.S. (Miller 

and others, 2012), a journal article that is currently in review 

describing trends in the southeastern U.S. (Daniel Calhoun, 

USGS, unpub. data, October 5, 2011) and a USGS Open-File 

Report describing trends in the western U.S. (Wiele and others, 2012). Regional differences are examined in the percentage of sites that have been identified as having statistically 

significant temporal trends in one or more of the three biotic 

assemblages. The synthesis of biologic data collected from 

the four regions has resulted in a dataset that includes many 

sites that span a gradient of land use, and the potential role 

of land use in determining biotic trends is explored. Finally, 

generalized abiotic environmental variables that are correlated with, and are possible drivers of, the biotic assemblages 

are examined.
Approach and Methods 3

Approach and Methods

This section describes the general approach used for 

summarizing and synthesizing temporal trends in biotic assemblages as well as correlated abiotic environmental variables among regions, sites included in the four trends reports, 

sampling and data-processing methodology, and statistical 

approaches to data analysis. Given the differences in the methodological approaches among the four regions, the general 

approach used for the present study was to summarize the 

major commonalities and differences in the methods applied 

in each of the region-specific reports. In turn, by focusing 

on the commonalities and accounting for the differences in 

methodology among regions, a quantitative comparison of the 

findings among regions was possible. Details on the frequency 

and dates of sample collection and lists of final environmental 

variables selected for analysis in each region are available in 

the region-specific reports. 

Sites

A total of 91 sampling sites, located in four geographic 

regions, sampled from 1993 to 2009 are included in this 

report (table 1, at end of report; fig. 1). Twenty-seven sites 

are located in northeastern and north-central United States, 

13 sites are located in southeastern U.S., 15 sites are located 

in south-central U.S., and 36 sites are located in western U.S. 

Drainage areas range from 19 square kilometers (km2) at 

Red Butte Creek at Fort Douglas, near Salt Lake City, UT, to 

220,908 km2 at the Platte River at Louisville, NE, with an average drainage area of 8,585 km2

. Sites were classified based 

on dominant land use in the watershed. Land-use categories 

include agricultural, urban, and undeveloped. Additionally, 

some sites in the southeastern and south-central U.S. were 

categorized as having mixed land use (urban plus agriculture).

Sample Collection and Data Processing

Biota

Algae, macroinvertebrates, and fish were collected using 

standard methods as part of the NAWQA Program (Cuffney 

and others, 1993; Meador and others, 1993a; Porter and others, 1993; Moulton and others, 2002). It is important to note 

that not all biotic assemblages were analyzed for temporal 

trends at all sites (table 1). Algae (benthic periphyton) were 

collected by scraping five rocks or snags within each stream 

reach, composited into a single sample, and the area sampled 

was recorded (Porter and others, 1993; Moulton and others, 

2002). Algae were preserved in 5-percent formalin and identified/enumerated to the lowest practical taxonomic level at the 

Philadelphia Academy of Sciences (Charles and others, 2002). 

Achnanthidium minutissimum, a monoraphid diatom; scale bar = 1 micrometer 

(μm). (Potapova, 2009).

Aquatic macroinvertebrates were collected from an area 

of 0.25 square meter (m2) in each of five riffle habitats within 

each stream reach using a slack sampler (500 μm mesh) and 

composited into a single sample (Cuffney and others, 1993; 

Moulton and others, 2002). At sites where riffles were not 

present, macroinvertebrates were collected from five snags, 

composited into a single sample, and the area sampled was 

recorded. Samples were preserved in 10-percent formalin and 

sent to the USGS National Water-Quality Laboratory (NWQL) 

in Denver, Colorado, for identification (Moulton and others, 

2000). In the laboratory, a quantitative fixed-count processing 

method was used to identify and estimate the abundance of 

each taxon sorted in the samples. 

Fish were collected from all habitat types in the stream 

reach (20 times the wetted width, a minimum of 150 meters 

(m)) using backpack, towed barge, or boat mounted electrofishing units and regularly supplemented with three seine 

hauls, following standard NAWQA protocols (Meador and 

others, 1993a; Moulton and others, 2002). Fish were identified 

Neophylax (Autumn Mottled Sedges) Caddisfly Larva. (Photograph by Steven 

Fend, USGS).
4 Multi-Regional Synthesis of Temporal Trends in Biotic Assemblages in Streams and Rivers of the United States

Oncorhynchus mykiss, Rainbow Trout. (Photograph by Terry Maret, USGS).

to species, enumerated, weighed, and measured in the field 

before being released back into the stream.

Algal and macroinvertebrate density (abundance per unit 

area) data as well as fish abundance data were used to calculate a variety of biotic metrics. The methods for metric calculation and final metric selection varied by region. However, in 

addition to the use of some region-specific metrics, the USGS 

Algal Data Analysis System (ADAS; ftp://ftpext.usgs.gov/

pub/er/nc/raleight/tfc/ADAS/Manual/) and Invertebrate Data 

Analysis System (IDAS; Cuffney, 2003) software packages 

were used to generate a common subset of algal and macroinvertebrate metrics, respectively, at all sites where algae and 

macroinvertebrates were analyzed (table 1). Algal metrics 

include a range of indicators for selected water-quality variables including nitrogen tolerance, pollution tolerance, salinity 

tolerance, and oxygen tolerance (Porter, 2008). Macroinvertebrate metrics include those based on community composition, 

life history, mobility, morphology, and ecology (Cummins, 

1973; Barbour and others, 1999; Cuffney, 2003; Poff and 

others, 2006). Fish metrics include status (native, endemic, 

or introduced), tolerance, trophic ecology, and reproductive 

strategy (Barbour and others, 1999; Meador and others, 1993a; 

Goldstein and Meador; 2004; Whittier and others, 2007a, b; 

Frimpong and Angermeier, 2009; Froese and Pauly, 2009). 

Environmental Variables

The specific environmental variables/metrics tested for 

correlations with biotic assemblages varied by region. Therefore, it was not possible to quantitatively compare and contrast 

specific environmental variables identified as being significantly correlated with biotic assemblages among regions. To 

address this limitation, information regarding generalized 

abiotic environmental variables (for example, the general 

category of “water quality” as opposed to the specific category 

of “nitrate concentrations”) correlated with biotic assemblages 

was compared and contrasted among regions. The specific environmental variables/metrics assessed in all regions fall into 

one of three general categories: hydrology, physical habitat, 

and water quality (including precipitation and air temperature). 

Additionally, biotic trends were synthesized in the context of 

dominant land-use type (table 1). While environmental variables were compiled in the USGS Open-File Report describing temporal trends in biotic assemblages in the western U.S. 

(Wiele and others, 2012), a report identifying the correlations 

between environmental variables and biotic assemblages for 

sites in the western U.S. has not been published. Therefore, 

correlations between environmental variables and biotic assemblages at sites in the western U.S. are not discussed.

Hydrologic metrics (magnitude, frequency, duration, timing, and rate of change) were calculated using data acquired 

from the USGS National Water Information System (NWIS, 

http://waterdata.usgs.gov/nwis/sw), and a variety of approaches for calculating hydrologic metrics was applied (Richter 

and others, 1996; McMahon and others, 2003; Henriksen 

and others, 2006; The Nature Conservancy, 2009). Physical 

habitat data were acquired following standard USGS methods 

(Meador and others, 1993b; Fitzpatrick and others, 1998), and 

water-quality data (nitrogen and phosphorous, pH, dissolved 

oxygen, specific conductance, water temperature, major ions, 

suspended sediment, and pesticides) were acquired from 

NWIS and the NAWQA Data Waterhouse (http://infotrek.

er.usgs.gov/nawqa). Climate (precipitation and air temperature) metrics were calculated using data acquired from the Parameter elevation Regressions on Independent Slopes Model 

(PRISM, http://prism.oregonstate.edu) and National Oceanic 

and Atmospheric Administration weather observation stations 

(http://www.ncdc.noaa.gov/oa/climateresearch.html). 

Statistical Analyses

Temporal trends in biotic assemblages were investigated at all sites using a multivariate statistical approach. 

This approach allows for temporal change in the entire biotic 

assemblage in question (algae, macroinvertebrates, or fish) 

at a given site to be quantitatively assessed by accounting for 

changes in the abundance of all species, as opposed to, for 

example, quantifying temporal change in the abundance of a 

single species. At all sites and on all sample dates, abundance 

or density data were standardized by total abundance or density, respectively, and either square root- or fourth root-transformed prior to generation of Bray-Curtis similarity resemblance matrixes using the Plymouth Routines In Multivariate 

Ecological Research (PRIMER) program (Clarke and Gorley, 

2006). The type of data (abundance or density) and type of 

transformation (square root or fourth root) varied by region 

and biotic assemblage. PRIMER was then used to generate 

non-metric multidimensional scaling (NMDS) ordination plots 

that included data from all sample dates for each site. NMDS 

plots are graphical representations of the Bray-Curtis similarity matrixes, with points (representing biotic assemblages on a 

given sample date) that have more similar biotic assemblages 

plotting closer to one another than those with more dissimilar 
Multi-Regional Comparisons of Biotic Trends and Drivers of Trends 5

biotic assemblages. The statistical significance of temporal 

change in biotic assemblages at each site was tested using 

PRIMER’s RELATE procedure, which is a non-parametric 

seriation procedure (Clarke and Gorley, 2006; Clarke and 

others, 2006). For the present study, a statistically significant 

temporal trend at a given site was defined as having p < 0.05. 

Fisher’s exact test was used to identify whether the percentage 

of sites with significant temporal trends was significantly different among biotic groups, regions, and land-use categories 

(Fisher, 1922). Fisher’s exact test generally is used to determine if there are non-random associations between categorical 

variables. This test is appropriate to use when dealing with 

small sample sizes because, rather than approximating the 

significance of deviation from the null hypothesis (as is done 

with other tests that can be used to analyze contingency tables, 

such as a chi-square test), Fisher’s exact test calculates the 

exact significance of deviation from the null hypothesis. This 

distinction means that Fisher’s exact test provides greater confidence than other significance tests, especially when dealing 

with small sample sizes.

In contrast to the consistent approach used for the identification of temporal trends described above, the approaches 

used to identify subsets of environmental variables and biotic 

metrics that are strongly correlated with the biotic assemblages varied among regions. At sites where a significant 

temporal trend was identified in the biotic assemblage, subsets 

of environmental variables and biotic metrics were identified that strongly correlated with the biotic assemblage. This 

approach provides insights into which environmental variables 

are likely abiotic drivers of change in the biotic assemblage, 

and which subsets (that is, metrics) of the broader biotic 

assemblage are related to the overall temporal change in the 

biotic assemblage. In the northeastern/north-central and southcentral regions (Kennen and others, 2012; Miller and others, 

2012), the general approach used to identify the aforementioned subsets was to use the PRIMER routines BIOENV 

(for environmental variables; Clarke and Ainsworth, 1993) 

and BVSTEP (for biotic metrics; Clarke and Warwick, 1998). 

Both BIOENV and BVSTEP use Spearman rank correlation 

coefficients (ρ) to compare the biotic-assemblage resemblance 

matrix at a given site with the environmental-variable and 

biotic-metric resemblance matrixes (based on Euclidean distance), respectively. The subset of environmental variables and 

biotic metrics found to have the highest correlation (ρ) to the 

biotic assemblage were then identified. BIOENV compares the 

biotic-assemblage matrix with all possible subsets of environmental-variable matrixes, whereas BVSTEP uses a stepwise 

approach to compare the biotic-assemblage matrix with the 

biotic-metrics matrix. At sites in the southeastern region (Daniel Calhoun, USGS, unpub. data, October 5, 2011) with significant temporal trends in biotic assemblages (as identified by 

RELATE), non-parametric Spearman correlation coefficients 

were calculated to compare Euclidean-resemblance matrixes 

for environmental variables and biotic metrics with the 

biotic-assemblage matrix. This allowed for the identification 

of the subset of environmental variables and biotic metrics 

that were most strongly correlated with the biotic assemblage. 

Additionally, Kendall’s tau-b correlation coefficients were 

calculated and used to identify temporal trends in environmental variables and biotic metrics at each site. Fisher’s exact 

test was used to identify whether the percentage of sites with 

significant correlations between a given biotic assemblage and 

a given environmental-variable category was significantly different among environmental-variable categories and regions. 

Multi-Regional Comparisons of Biotic 

Trends and Drivers of Trends

The percentage of sites identified as having significant 

temporal trends in biotic assemblages as a function of biotic 

assemblage, region, or land use are presented in the following sections. The percentage of sites within each region that 

were identified as having both significant temporal trends in 

biota and significant correlations among the biota and environmental variables also are discussed. These results provide 

a context for making generalizations about temporal change in 

biotic assemblages and environmental drivers of that change 

across broad geographic regions and place ecosystem trends in 

a national context. 

Trends in Biotic Assemblages 

The multivariate approach differentiated between sites 

with and without significant trends in biotic assemblages. For 

example, NMDS seriation plots for the macroinvertebrate and 

fish assemblages from the Buffalo River near Boxley, Arkansas (fig. 2A and B, respectively), provide a contrast between 

an assemblage with a significant temporal trend (macroinvertebrates) and an assemblage identified as not having a significant temporal trend (fish). In the macroinvertebrate NMDS 

plot (fig. 2A), the points representing the biotic assemblage 

for a given year changed position in multivariate space in a 

unidirectional manner (from left to right in this plot), and the 

assemblage had a significant change over time (p = 0.005). In 

the fish NMDS plot (fig. 2B), the points indicating the earlier 

sampling times folded back upon themselves, indicating little 

directional change in the fish assemblage from 1993 to 2004. 

Subsequently, a significant temporal trend in the fish assemblage was not identified (p = 0.34). 

Trends as a Function of Biotic Assemblage

With data from all regions combined, significant temporal trends in algal assemblages were identified at 27 of the 

49 sites (55 percent) at which temporal trends in algae were 

investigated (table 1; fig. 3). A significantly smaller percentage of sites had significant trends in the macroinvertebrate 

assemblages (30 of 90 sites, 33 percent), and an intermediate percentage of sites (30 of 76, 39 percent) had significant 
6 Multi-Regional Synthesis of Temporal Trends in Biotic Assemblages in Streams and Rivers of the United States

1993

1994

1995

2002

2003

2004

A. Macroinvertebrates

1993

1994

1995

2002

2003

2004

B. Fish

2D Stress: 0

p = 0.005

2D Stress: 0

p = 0.34

Figure 2. Non-metric multidimensional scaling (NMDS) 

seriation plots for the Buffalo River near Boxley, Arkansas, for A, 

macroinvertebrate assemblage and B, fish assemblage. Points 

that plot closer together represent biotic assemblages that are 

more similar to one another, whereas those that plot further 

apart are more dissimilar. The macroinvertebrate assemblage 

changed in such a way that in each progressive sampling year 

the assemblage was more different than any of the previous 

years, and a significant temporal trend in the macroinvertebrate 

assemblage was identified. A significant temporal trend in the 

fish assemblage was not found (that is, the trajectory of the 

assemblage folded back upon itself).

temporal trends in fish assemblages. The percentage of sites 

identified as having trends in fish assemblages, however, was 

not significantly different from the percentage of sites with 

temporal trends in algae or macroinvertebrate assemblages. 

The finding that temporal trends are more frequently 

identified in algal assemblages as compared to macroinvertebrate or fish assemblages may indicate that algae are, in general, more sensitive to and (or) respond more quickly to environmental change than macroinvertebrates or fish. This idea is 

further supported by the findings of previous studies (McCormick and Cairns, 1994; Barbour and others, 1999; Coles and 

others, 2009). The difference in the sensitivity of response of 

different biotic assemblages to environmental change may 

have implications for the design of continued/future monitoring programs. For example, if the goal of a monitoring 

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Algae Macroinvertebrates Fish

Percentage of sites with a significant trend

Biotic assemblage

B

A,B

A

49 90 76

Figure 3. Percentage of sites where significant temporal trends 

were identified for each biotic assemblage when data from all 

regions were combined. The numbers of samples (n) are shown 

at the top of the figure. Letters indicate significant differences 

among biotic assemblages. For example, A is significantly 

different than B, but neither A nor B are significantly different 

from AB.

program were to identify short-term responses to environmental change, it may be beneficial to put greater resources into 

monitoring algal assemblages, whereas programs interested in 

longer term responses may want to place more resources into 

monitoring macroinvertebrate or fish assemblages. Regardless of the monitoring program objectives, understanding the 

relative sensitivity of various biotic assemblages over multiple 

time frames (after 5, 10, and 20 years of monitoring) will aid 

in identification of the time scales at which different stressors 

affect biota.

Trends as a Function of Region

Regional differences were identified in the percentage 

of sites with significant temporal trends in one or more biotic 

assemblages, and for each biotic assemblage individually. 

Significant temporal trends in one or more biotic assemblages 

were identified at 65 of the 91 (71 percent) assessment sites 

(table 1). Significant temporal trends were identified in one 

or more biotic assemblages at 19 of 27 (70 percent) sites in 

the northeastern/north-central region, 7 of 13 (54 percent) 

sites in the southeastern region, 8 of 15 (53 percent) sites in 

the south-central region, and 31 of 36 (86 percent) sites in 

the western region (fig. 4A). The western region had a significantly greater percentage of sites with significant temporal 

trends in one or more biotic assemblages as compared with the 

southeastern or south-central regions. In the western region, 

23 of 34 (68 percent) sites had significant temporal trends 

in algal assemblages, which was significantly more than the 

4 of 15 (27 percent) sites with significant temporal trends in 

algal assemblage in the south-central U.S. (fig. 4B). Ten of 27 

(37 percent), 4 of 13 (31 percent), 4 of 15 (27 percent), and 
Multi-Regional Comparisons of Biotic Trends and Drivers of Trends 7

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Percentage of sites with a significant trend

in one or more biotic assemblage

Region

A A

B

A,B

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D. Fish

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Percentage of sites with a significant trend

in the macroinveretebrate assemblage

A A

A A

27 13 15 35

C. Macroinvertebrates

B. Algae 

Figure 4. Percentage of sites in each region where significant 

temporal trends were identified for A, one or more of the biotic 

assemblages, B, algal assemblages, C, macroinvertebrate 

assemblages, and D, fish assemblages. The numbers of samples 

(n) are shown at the top of each figure. Letters indicate significant 

differences among regions.

12 of 35 (34 percent) sites were identified as having significant temporal trends in macroinvertebrate assemblages in the 

northeastern/north-central, southeastern, south-central, and 

western regions, respectively. However, no significant differences were identified among regions in the percentage of 

sites with trends in macroinvertebrate assemblages (fig. 4C). 

There was no significant difference in the percentage of sites 

with significant temporal trends in fish assemblages among the 

northeastern/north-central (15 of 27, 56 percent), southeastern 

(5 of 12, 42 percent), or western (10 of 23, 43 percent) regions 

(fig. 4D). However, only 1 of 14 (7 percent) sites in the southcentral U.S. had significant temporal trends in the fish assemblage, which is significantly fewer than in the northeastern/

north-central or western regions. 

In general, the northeastern/north-central region and to a 

greater extent the western region was identified as having proportionally more sites with significant temporal trends in biotic 

assemblages than in the southeastern and south-central regions 

(fig. 4A–D). That is, significant temporal changes in biotic 

assemblages were more common in the northeastern/northcentral and western regions. To the best of our knowledge, the 

finding that there were regional differences in the percentage 

of sites with significant temporal trends for all biotic assemblages combined, as well as individually for the algal and fish 

assemblages, has not been reported. Interestingly, the finding that there were no significant inter-regional differences 

in macroinvertebrate trends (fig. 4C) was surprising given 

the significant differences found for algae (fig. 4B) and fish 

(fig. 4D). This result may be, at least in part, an artifact of the 

possibility that greater uncertainty exists in defining the “true” 

algal and fish assemblages because of smaller sample sizes (49 

and 76, respectively, as compared with 90 macroinvertebrate 

samples). Taken together, the results generated from this comparison provide ecological information at a spatial scale that is 

relevant to national monitoring programs such as NAWQA. 

Trends as a Function of Land Use

Land use was identified as an important determinant of 

the percentage of sites with significant temporal trends in one 

or more biotic assemblages and for each biotic assemblage 

individually. Significant temporal trends were found in one 

or more biotic assemblages at 15 of 22 (68 percent) of the 

agricultural sites, 20 of 23 (87 percent) of the urban sites, 

2 of 8 (25 percent) of the mixed land-use sites, and 28 of 38 

(74 percent) of the undeveloped sites (fig. 5A). The percentage 

of sites with significant temporal trends in one or more biotic 

assemblages was significantly greater at agricultural, urban, 

and undeveloped sites than at mixed land-use sites. However, 

the few sites available for analysis in the mixed category 

(n = 8) relative to the other land-use categories, coupled with 

the fact that the mixed land-use designation was applied to 

sites in only two of the four regions, may be driving that finding. The percentage of sites with significant temporal trends 

in algal assemblages differed little among agricultural (4 of 6, 
8 Multi-Regional Synthesis of Temporal Trends in Biotic Assemblages in Streams and Rivers of the United States

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Agriculture Urban Mix

Percentage of sites with a significant trend

in one or more biotic assemblage

Land use

A

B

A

A

22 23 8 38

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Percentage of sites with a significant

trend in the algal assemblage

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6 8 6 29

Undeveloped

A. All biotic assemblages

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Percentage of sites with a significant 

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D. Fish

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Percentage of sites with a significant trend

in the macroinveretebrate assemblage

A

B

B A, B

A A, B

22 23 8 37

C. Macroinvertebrates

B. Algae 

Figure 5. Percentage of sites in each land-use category 

where significant temporal trends were identified for A, 

all biotic assemblages combined, B, algal assemblages, C, 

macroinvertebrate assemblages, and D, fish assemblages. 

The numbers of samples (n) are shown at the top of each 

figure. Letters indicate significant differences among landuse categories.

67 percent), urban (5 of 8, 63 percent), and undeveloped (18 of 

29, 62 percent) sites (fig. 5B). There were no significant trends 

in algal assemblages at the mixed land-use sites (0 of 6). 

A statistical comparison of trends in algae among land-use 

categories showed mixed land-use sites to be significantly 

different from urban and undeveloped sites, but not agricultural sites (owing to the small sample sizes (n = 6) for both the 

agricultural and mixed land-use sites). Significant temporal 

trends in macroinvertebrate assemblages were identified at 

7 of 22 (32 percent) agricultural sites, 13 of 23 (57 percent) 

urban sites, 0 of 8 mixed land-use sites, and 10 of 37 (27 percent) undeveloped sites (fig. 5C). The percentage of urban 

sites with temporal trends in macroinvertebrate assemblages 

was significantly greater than the percentage of mixed land 

use and undeveloped sites with temporal trends. No significant 

differences in the percentage of sites with temporal trends 

in fish assemblages were found among land-use categories 

(fig. 5D). Fish assemblages showed trends at 6 of 19 (32 percent) agricultural sites, 13 of 22 (59 percent) urban sites, 2 of 

6 (33 percent) mixed land-use sites, and 10 of 29 (34 percent) 

undeveloped sites. 

Observed differences in the percentage of sites with 

significant temporal trends among land-use categories (fig. 5A) 

provides some insight into the potential role of land use as a 

determinant of change in assemblage composition. Sixty eight 

and 87 percent of agricultural and urban sites, respectively, 

had temporal trends in one or more biotic assemblages, indicating that some physical or chemical characteristics of these 

anthropogenically impacted systems may have changed during 

the course of the study. Numerous other studies have identified 

agricultural and urban land uses as impacting biotic assemblages (Lenat and Crawford, 1994; Paul and Meyer, 2001; Roy 

and others, 2003; Brasher and others, 2004; Coles and others, 

2004; Cuffney and others, 2005; Meyer and others, 2005; 

Kennen and others, 2005, Wang and others, 2008; Cuffney and 

others, 2010; and many others). 

For all biotic assemblages combined, 74 percent of undeveloped sites, where direct anthropogenic impacts are limited, 

showed significant temporal trends in one or more biotic 

assemblages (fig. 5A). This finding may indicate that climaterelated processes are driving these trends. This finding (based 

on all four regions combined) supports similar findings to 

that of the northeastern/north-central and south-central region 

reports, that the use of undeveloped sites as an ecological 

baseline for monitoring programs requires careful evaluation 

(Kennen and others, 2012; Miller and others, 2012). It also is 

interesting to note that the percentage of mixed land-use sites 

with temporal trends in biotic assemblages was lower than 

for all other land-use categories. Watersheds categorized as 

having mixed land use are, by definition, draining a large area 

consisting of multiple land uses. Therefore, it is conceivable 

that this diversity in land uses could result in more heterogeneous abiotic environmental conditions, thereby dampening 

temporal trends in biotic assemblages. These findings may 

require additional evaluation because the number of mixed 

land-use sites in the analysis was small (n = 8) relative to the 
Multi-Regional Comparisons of Biotic Trends and Drivers of Trends 9

number of urban (n = 23), agriculture (n = 22), and undeveloped sites (n = 38). The observed differences in response to 

land use among biotic assemblages provide further support 

for the concept that different stressors, including land use, 

act on different time scales for different biotic assemblages, 

which indicates the need for continued support of long-term 

monitoring programs for more effective identification of biotic 

assemblage-specific response times to various stressors.

Environmental Drivers of Trends

The general categories of environmental drivers—hydrology, physical habitat, and water quality—correlated with 

biotic assemblages are discussed in this section. Correlations 

between biotic assemblages and environmental-variable 

categories were investigated only at sites where significant 

temporal trends in biotic assemblages were identified (table 1). 

However, correlations between biotic assemblages and general 

environmental-variable categories for the western geographic 

region were not included in this comparative analysis because 

final results are still pending. Biotic assemblages at 26 of the 

34 (76 percent) sites in the northeastern/north-central, southeastern, and south-central regions were significantly correlated 

with one or more environmental-variable categories (table 2). 

For all three regions combined, one or more of the biotic 

assemblages were found to be significantly correlated with 

hydrology at 12 sites (35 percent), physical habitat at 11 sites 

(32 percent), and water quality at 16 sites (47 percent) (fig. 6). 

However, there were no significant differences among the percentages of correlations with biotic assemblages for the three 

environmental-variable categories (fig. 6). 

Comparison of the percentage of sites identified as having significant correlations with hydrologic, physical habitat, 

and (or) water-quality variables provides insight into the 

0

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100

Hydrology Physical habitat Water quality

Percentage of sites with a significant 

correlation between one or more biotic

assemblage and the environmental variables

Environmental-variable category

A

A

A

34 34 34

Figure 6. Percentage of sites with significant correlations 

between one or more biotic assemblages and environmentalvariable category. The numbers of samples (n) are shown at the 

top of the figure. Letters indicate that there were no significant 

differences among environmental-variable categories.

relative importance of these environmental drivers both among 

and within regions. Figure 7 compares among-region differences for each environmental-variable category (for example, 

differences between the percentage of sites in the northeastern/north-central region with correlations between biotic 

assemblages and hydrology and the percentage of sites in 

the southeastern region with correlations between biotic 

assemblages and hydrology). Figure 7 also compares withinregion differences among environmental-variable categories 

(for example, differences between the percentage of sites 

in the south-central region with correlations between biotic 

assemblages and hydrology and the percentage of sites in the 

south-central region with correlations between biotic assemblages and physical habitat). Among regions, when considering all biotic assemblages combined, there were no significant differences in the percentage of sites with correlations 

between environmental-variable categories and one or more 

biotic assemblages (fig. 7A). Within regions, no differences 

in the percentage of sites with significant assemblage and 

environmental correlations were identified in the northeastern/

north-central or south-central regions (fig. 7A). Within the 

southeastern region, a significantly greater percentage of sites 

had biotic assemblages that were correlated with water quality 

(6 of 7, 86 percent) than those correlated with hydrology (1 

of 7, 14 percent). However, physical habitat (4 of 7, 57 percent) was not significantly different from either hydrology or 

water quality (fig. 7A).

The south-central region was the only region for which 

temporal trends in algal assemblages and correlations between 

algal assemblages and environmental-variable categories were 

evaluated owing to an absence of algal information in the 

other two regions (fig. 7B). Four sites were identified as having significant temporal trends in algal assemblages within the 

south-central region (table 2). Two of the four sites (50 percent) were found to be correlated with each of the environmental variable-categories (fig. 7B). Interestingly, the two sites 

correlated with physical habitat variables were undeveloped 

sites, whereas the two sites correlated with hydrology and 

water quality were developed (agriculture and urban) sites 

(table 2).

The southeastern region had a greater percentage (3 of 4, 

75 percent) of sites with significant correlations between the 

macroinvertebrate assemblage and water quality than the 

northeastern/north-central region (1 of 10, 10 percent, fig. 7C). 

No significant differences were observed among regions in 

the percentage of sites with correlations between macroinvertebrate assemblages and hydrology, or between macroinvertebrate assemblages and physical habitat (fig. 7C). Within 

regions, there were no significant differences in the percentage 

of sites with correlations between macroinvertebrate assemblages and the different environmental-variable categories. 

Physical habitat was the only environmental-variable 

category correlated with trends in fish assemblage that 

showed significant differences among regions (fig. 7D). In the 

southeastern region, 4 of 5 sites (80 percent) had significant 

correlations between fish assemblages and physical habitat, 
10 Multi-Regional Synthesis of Temporal Trends in Biotic Assemblages in Streams and Rivers of the United States

Table 2. Environmental-variable categories found to be significantly correlated with the biotic assemblage for 

sites/biotic assemblages that were identified as having significant temporal trends in the northeastern/northcentral, southeastern, and south-central regions. 

[AG, Agricultural land use; URB, Urban land use; UNDEV, Undeveloped land use, MIX, Mixed land use; NA, sites for which temporal 

trends in biotic assemblages were not analyzed; --, sites for which a significant temporal trend was not identified; NS, sites for which 

a significant temporal trend was identified but no environmental variables/metrics were found to be significantly related to the biotic 

assemblage; HYD, Hydrologic variables/metrics; HAB, Physical habitat variables/metrics; WQ, Water-quality variables/metrics]

Station code Land-use 

category Algae Macroinvertebrates Fish

Northeastern/North-Central U.S.

CANA AG NA -- HYD

DUCK AG NA NS --

MAD AG NA -- HYD, HAB

MUD AG NA -- WQ

SFIOWA AG NA HAB --

SUGAR AG NA -- WQ

BOUND URB NA -- NS

CLINT URB NA HYD, HAB, WQ HYD, HAB, WQ

HOLES URB NA NS WQ

LISHA URB NA HYD, HAB --

LBUCK URB NA NS --

LNESH URB NA HYD WQ

NORW URB NA NS NS

SALT URB NA -- HYD, WQ

SHING URB NA -- NS

FRENCH UNDEV NA -- HAB

GREEN UNDEV NA NS WQ

RAISIN UNDEV NA -- NS

WAITES UNDEV NA HYD HYD

Southeastern U.S.

AG-TN1 AG NA WQ --

AG-NEUS AG NA WQ --

AG-TN2 AG NA -- WQ

URB-MOBL URB NA HYD, HAB HYD, HAB

URB-ACF URB NA HAB, WQ HAB, WQ

URB-NEUS URB NA -- HAB, WQ

INT-NEUS MIX NA -- HAB, WQ

South-Central U.S.

YOCM AG HYD, WQ -- --

SALD URB HYD, WQ -- --

WHITE URB -- HYD --

BUFF1 UNDEV -- NS --

CLEAR UNDEV -- HYD, WQ --

FRIO UNDEV HAB -- --

NSYLM UNDEV HAB NS --

YAZ MIX -- -- NS

1

Correlations between the macroinvertebrate assemblage and physical habitat variables at BUFF were not tested because fewer than 5 

years of physical habitat data were available (see Miller and others, 2012).
Study Limitations and Future Directions 11

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Percentage of sites with a significant correlation between the biotic assemblage and environmental variables

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10 4 4

C. Macroinvertebrates

B. Algae 

A

Hydrology

EXPLANATION

Physical habitat

Water quality

Figure 7. Percentage of sites in each region with significant 

correlations between the biotic assemblage and environmentalvariable categories for A, all biotic assemblages combined, B, 

algal assemblages, C, macroinvertebrate assemblages, and D, fish 

assemblages. The numbers of samples (n) are shown at the top of 

each figure. Capital letters (A, B) indicate significant differences 

among regions for a given environmental-variable category. 

Lowercase letters (y, z) indicate significant differences among 

environmental-variable categories within a given region. Note 

that letters indicating significance are shown only for the amongregion or among-environmental-variable category comparisons 

for which significant differences were identified. 

which was significantly greater than in the northeastern/

north-central region (3 of 15 sites, 20 percent). Similar to 

what was observed among regions for the combined biotic 

assemblages (fig. 7A) and the macroinvertebrate assemblage 

(fig. 7C), water quality—while not statistically significant—

was more commonly correlated with fish assemblages in the 

southeastern region than either the northeastern/north-central 

or south-central regions. In contrast, hydrology—while not 

statistically significant—was more commonly an environmental driver in the northeastern/north-central region than 

it was in the southeastern or south-central regions. Within 

regions there were no significant differences in the percentage of sites with correlations between fish assemblages and 

environmental-variable categories.

Study Limitations and Future Directions

The standardized field and laboratory methods used 

as part of the NAWQA Program enable analyses at broad 

spatial and geographic scales, such as those presented herein. 

However, limitations may arise when combining large datasets 

that have been analyzed by scientists in different regions. This 

section reviews some of the data compilation and analysis 

limitations faced when synthesizing and interpreting data collected over multiple decades at the continental scale. Further, 

suggestions for future work that could build upon the results 

presented herein are discussed.

 The collection of a large number of biotic samples for 

quantification of biotic assemblages is often limited by the 

high cost of sample processing. Given this constraint, it is not 

surprising that a relatively small number of samples was available for analyses in this study. Of the published papers upon 

which our analyses were based, not all reports included data 

for specific biotic assemblages. This lack of data in certain 

geographic regions limited our ability to identify differences 

in environmental drivers of temporal trends among biotic 

assemblages in a multi-regional context. For example, the lack 

of data on algal assemblages in the northeastern/north-central 

and southeastern regions greatly limited the broader regional 

comparison for that taxonomic group. However, analysis of 

temporal trends in algal assemblages and correlations of those 

assemblages with environmental variables is currently (2013) 

underway in the northeastern/north-central, southeastern, 

and western regions and should be available soon for a more 

comprehensive comparative analysis. Once completed, it will 

be possible to derive a more complete understanding of the 

differences in important environmental drivers of temporal 

change in algal assemblages among regions. 

Among-region and among-land-use comparisons of the 

percentage of sites with significant trends in biotic assemblages also are limited by data availability. Specifically, the 

southeastern and south-central regions as well as the mixed 

land-use category have fewer sites than other regions or 

land-use categories, respectively. Collection of additional data 
12 Multi-Regional Synthesis of Temporal Trends in Biotic Assemblages in Streams and Rivers of the United States

and consistent categorization of land-use categories among 

regions, would provide the opportunity to further define 

among-region or land-use differences in the percentage of sites 

with significant trends in biotic assemblages. These limitations 

highlight the importance of maintaining a spatially complex 

and numerically robust monitoring program. This finding is 

particularly pertinent as programs like NAWQA transition 

into cycles of reduced funding and a greatly restricted spatial 

sampling framework. However, as the NAWQA Program and 

others like it (for example, The U.S. Environmental Protection 

Agency National Aquatic Resource Survey (NARS) Program) 

continue to collect biological samples across broad spatial 

scales, the extent of valuable trend datasets will be expanded 

and a better understanding of ecosystem response to environmental change will be developed. Further, continued collection 

of ecological data will provide programs such as NAWQA and 

NARS with the opportunity to examine a number of topics of 

management concern including, for example, species-specific 

temporal change and temporal change in biodiversity.

The approach of comparing and contrasting the percentage of correlations between biotic assemblages and general 

categories of environmental variables (hydrology, physical 

habitat, and water quality) was adopted because the suite of 

environmental variables investigated varied among regions. 

While this approach does provide some insight into differences in environmental drivers among regions, a comprehensive analysis that begins with a consistent set of environmental 

variables among regions would provide a broader understanding of how water quality and watershed conditions are changing across the country. For example, the greater percentage of 

sites in the southeastern region with significant correlations 

between water quality and macroinvertebrate and fish assemblages, as compared to the northeastern/north-central and 

south-central regions, may be owing to the fact that pesticides 

were included in the water-quality category in the southeastern 

region but not in the other regions. Specifically, a pesticide 

toxicity index (PTI; Munn and Gilliom, 2001; Munn and 

others, 2006) was negatively correlated with macroinvertebrate-assemblage metrics indicative of “good” water-quality 

conditions (for example, percent Ephemeroptera, Plecoptera, 

and Trichoptera) at all three of the sites with significant correlations between macroinvertebrate assemblages and water 

quality in the southeastern region (Daniel Calhoun, USGS, 

unpub. data, October 5, 2011). While this points to the PTI as 

a potentially important water-quality variable with respect to 

understanding water-quality drivers of trends in biotic assemblages, it is not possible to thoroughly evaluate the importance 

of the correlation between biotic assemblages and the PTI 

among regions because the PTI was only included as a potential driver of change in the report from the southeastern region. 

It is suggested that future ecological-trend analyses include the 

calculation of a common set of environmental variables for all 

the study sties. This would undoubtedly provide an opportunity for a more scientifically rigorous approach to identifying 

and understanding how water-quality and watershed conditions 

are changing at the multi-regional scale and, thereby, providing 

a more robust basis of comparison.

Summary and Conclusions

Temporal trends in biotic assemblages (algae, macroinvertebrates, and fish) from 91 streams and rivers sampled as part 

of the U.S. Geological Survey National Water-Quality Assessment (NAWQA) Program, which were reported in four regionspecific reports and collectively encompass the continental 

U.S., were summarized and synthesized. The percentages of 

sites with significant temporal trends in biotic assemblages 

were compared among biotic assemblages (algae, macroinvertebrates, and fish), geographic regions, and land-use categories. 

Correlations between biotic assemblages and three general 

environmental-variable categories (hydrology, physical habitat, 

and water quality) were compared among and within three geographic regions (northeastern/north central, southeastern, and 

south central). Finally, limitations to the study approach and 

suggestions for future work were discussed, which could avoid 

such limitations and (or) build upon the present study.

Sites with significant temporal trends in algae, macroinvertebrate, and (or) fish assemblages were successfully 

identified using a multivariate statistical approach that allows 

for a quantitative assessment of temporal change for the entire 

ecological community. Synthesis of the region-specific reports 

(Kennen and others, 2012; Miller and others, 2012; Daniel 

Calhoun, USGS, unpub. data, October 5, 2011; and Wiele 

and others, 2012) indicates that significant temporal trends 

in algal assemblages were identified at a greater percentage 

of sites (55 percent) than macroinvertebrate (33 percent) or 

fish (39 percent) assemblages. This finding may indicate that 

algae respond more quickly to environmental change than 

either macroinvertebrates or fish. Such findings could be used 

to more accurately identify the amount of time or number of 

samples required to detect temporal trends in different biotic 

assemblages and also may be used to better inform the allocation of resources for a more effective and efficient design of 

future monitoring or synoptic-sampling efforts.

 In general, a greater percentage of sites with significant 

temporal trends were identified in the northeastern/north-central (70 percent) and western (86 percent) regions than in the 

southeastern (54 percent) or south-central (53 percent) regions. 

The finding that there are among-region differences is a novel 

result, and while the results presented herein are limited by 

data availability and different methodological approaches, as 

previously described, this finding does provide a foundation 

from which future multi-regional analyses can better assess 

how environmental and anthropogenic conditions are affecting 

aquatic ecosystems.

Results also indicate that there was a greater percent-
References Cited 13

age of sites with temporal trends in agricultural (68 percent), 

urban (87 percent), and undeveloped (74 percent) land uses 

than of sites draining mixed (25 percent) land uses. A greater 

percentage of temporal change at the agricultural and urban 

sites, which generally are exposed to a high degree of human 

alteration of the landscape, raises the possibility that there may 

have been changes in the abiotic environment at these sites that 

resulted in temporal change in biotic assemblages. The large 

percentage of sites draining basins with undeveloped land use 

with significant temporal trends in biotic assemblages may 

indicate that climate-related impacts are influencing the more 

sensitive taxa, which tend to be more abundant at undeveloped 

sites. This finding, which is based on data from all four regions 

combined, is consistent with those of previous region-specific 

reports. Results of this comparative analysis also may indicate 

that the few temporal trends identified in mixed land-use basins 

may be a result of dampening of assemblage response owing to 

the heterogeneous abiotic environmental conditions commonly 

found in mixed land-use basins.

Results have identified differences in hydrology, physical habitat, and water quality as potential drivers of trends in 

biotic assemblages among regions. Specifically, results appear 

to indicate that physical habitat and water quality may be more 

important drivers of temporal trends in biotic assemblages in 

the southeastern region than in the northeastern/north-central or 

south-central regions. Macroinvertebrate and fish assemblages 

were more commonly correlated with water quality and physical habitat variables, respectively, in the southeastern region 

than in the northeastern/north-central or south-central regions. 

These results indicate that multiple interacting stressors likely 

are involved in determining trends in biotic assemblages. 

Therefore, additional data compilation and analysis is warranted to support any conclusions regarding potential environmental drivers of change in biotic assemblages among regions. 

Taken together, the region-specific studies and the multiregional synthesis presented herein make evident the potential 

importance of site- and region-specific management approaches 

aimed at mitigating anthropogenic changes in the environment 

to manage and protect ecological resources.

These results highlight the importance of continued longterm monitoring of biotic assemblages similar to what was previously accomplished as part of the NAWQA Program Surface 

Water Status and Trends network. Datasets that include samples 

collected over a broader time scale provide greater certainty 

for understanding long-term temporal change. The insights into 

potential environmental drivers of temporal trends provided 

here, however, could be strengthened by future analyses that 

use a consistent analytical methodology and common subsets 

of environmental variables. Ultimately, such studies would provide a more detailed understanding of how water quality and 

watershed conditions are changing at the multi-regional scale.

Acknowledgments

The authors would like to thank the numerous U.S. 

Geological Survey employees who collected the samples and 

data analyzed in this study. The authors also thank Steven 

Fend and Terry Maret for the photographs they provided and 

Sheryl Boyack for generation of the site map. Additionally, 

the authors thank the authors of the region-specific reports 

from which the results presented herein originated. Lastly, the 

authors thank James Coles and Sarah Spaulding for the helpful 

comments they provided in the early stages of this report. 

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Table 1 17

Table 1. General site characteristics for the 91 U.S. Geological Survey (USGS) National Water-Quality Assessment (NAWQA) Program long-term surface-water status and trend sites.—Continued[USGS, U.S. Geological Survey; km2, square kilometer; AG, Agricultural land use; URB, Urban land use; UNDEV, Undeveloped land use, MIX, Mixed land use; YES, sites for which temporal trends in biotic assemblages were analyzed; No, sites for which temporal trends in biotic assemblages were not analyzed; Bold type indicates sites and biotic assemblages with significant temporal trends; *, p < 0.05; **

, p < 0.01]

USGS station 

identification 

number

Station name Station code Land-use category Drainage area (km2) Algae analyzed1 Macroinvertebrates analyzed Fish analyzed

Northeastern/North-Central United States

04186500 Auglaize River NR Fort Jennings, OH AUG AG 860 No YES YES01349150 Canajoharie Creek NR Canajoharie, NY CANA AG 155 No YES YES**04072050 Duck Creek at Seminary Road NR Oneida, WI DUCK AG 280 No YES* YES05320270 Little Cobb River NR Beauford, MN LCOBB AG 337 No YES YES0395650083504400 Mad River NR highway 41 NR Springfield, OH MAD AG 803 No YES YES*01621050 Muddy Creek at Mount Clinton, VA MUD AG 37 No YES YES**05572000 Sangamon River at Monticello, IL SANG AG 1,425 No YES YES05451210 South Fork Iowa River Northeast of New Providence, IA SFIOWA AG 73 No YES* YES0394340085524601 Sugar Creek at County Road 400 South at New Palestine, IN SUGAR AG 243 No YES YES**05420680 Wapsipinicon River NR Tripoli, IA WAPS AG 896 No YES YES01102500 Aberjona River at Winchester, MA ABERJ URB 64 No YES YES01654000 Accotink Creek NR Annandale, VA ACCO URB 62 No YES YES01403900 Bound Brook at Middlesex, NJ BOUND URB 125 No YES YES*04161820 Clinton River at Sterling Heights, MI CLINT URB 800 No YES** YES**0393944084120700 Holes Creek in Huffman Park at Kettering, OH HOLES URB 48 No YES* YES*01356190 Lisha Kill Northwest of Niskayuna, NY LISHA URB 40 No YES** YES03353637 Little Buck Creek NR Indianapolis, IN LBUCK URB 44 No YES** YES01464907 Little Neshaminy Creek at Valley Road nr Neshaminy, PA LNESH URB 69 No YES* YES**01209700 Norwalk River at South Wilton, CT NORW URB 78 No YES** YES*05531500 Salt Creek at Western Springs, IL SALT URB 298 No YES YES**05288705 Shingle Creek at Queen Ave, Minneapolis, MN SHING URB 580 No YES YES**01472157 French Creek NR Phoenixville, PA FRENCH UNDEV 153 No YES YES**01170095 Green River at Stewartville, MA GREEN UNDEV 107 No YES** YES**04063700 Popple River NR Fence, WI POP UNDEV 360 No YES YES04175600 River Raisin NR Manchester, MI RAISIN UNDEV 342 No YES YES**01095220 Stillwater River NR Sterling, MA STILL UNDEV 82 No YES YES01610400 Waites Run NR Wardensville, WV WAITES UNDEV 33 No YES* YES*
18 Multi-Regional Synthesis of Temporal Trends in Biotic Assemblages in Streams and Rivers of the United States Table 1 18 Table 1. General site characteristics for the 91 U.S. Geological Survey (USGS) National Water-Quality Assessment (NAWQA) Program long-term surface-water status and trend sites.—Continued [USGS, U.S. Geological Survey; km2, square kilometer; AG, Agricultural land use; URB, Urban land use; UNDEV, Undeveloped land use, MIX, Mixed land use; YES, sites for which temporal trends in biotic assemblages were analyzed; No, sites for which temporal trends in biotic assemblages were not analyzed; Bold type indicates sites and biotic assemblages with significant temporal trends; *, p < 0.05; **, p < 0.01] USGS station Drainage Station Land-use Algae Macroinvertebrates Fish identification Station name area code category analyzed1 analyzed analyzed number (km2

)

Southeastern United States

03466208 Big Limestone Creek NR Limestone, TN AG-TN1 AG 205 No YES* YES

02091500 Contentnea Creek at Hookerton, NC AG-NEUS AG 1,898 No YES** YES

02174250 Cow Castle Creek NR Bowman, SC AG-SANT AG 61 No YES YES

0357479650 Hester Creek at Buddy Williamson Rd NR Plevna, AL AG-TN2 AG 85 No YES YES*02350080 Lime Creek NR Cobb, GA AG-ACF AG 159 No YES YES

0242354750 Cahaba Valley Creek at Cross Cr Rd at Pelham, AL URB-MOBL URB 66 No YES* YES*

02169570 Gills Creek at Columbia, SC URB-SANT URB 154 No YES YES

02335870 Sope Creek NR Marietta, GA URB-ACF URB 76 No YES** YES*

02087580 Swift Creek NR Apex, NC URB-NEUS URB 54 No YES YES**

02338523 Hillabahatchee Creek at Thaxton Rd, NR Frankling, GA REF-ACF UNDEV 44 No YES YES

02172300 McTier Creek (RD 209) NR Monetta, SC REF-SANT UNDEV 40 No YES YES

02089500 Neuse River at Kinston, NC INT-NEUS MIX 6,972 No YES YES*

02318500 Withlacoochee River at US 84, NR Quitman, GA INT-SUWA MIX 3,833 No YES No

South-Central United States

07288650 Bogue Phalia BLW Leland, MS BOGPH AG 1,301 YES YES YES

07053250 Yocum Creek NR Oak Grove, AR YOCM AG 134 YES** YES YES

08178800 Salado Creek at Loop 13 San Antonio, TX SALD URB 506 YES* YES YES

08057200 White Rock Creek at Greenville Ave Dallas, TX WHITE URB 173 YES YES* YES

07055646 Buffalo River NR Boxley, AR BUFF UNDEV 153 YES YES** YES

08051500 Clear Creek NR Sanger, TX CLEAR UNDEV 763 YES YES* YES

08195000 Frio River at Concan, TX FRIO UNDEV 1,028 YES* YES YES

07060710 North Sylamore Creek NR Fifty Six, AR NSYLM UNDEV 150 YES** YES** YES

08014500 Whiskey Chitto Creek NR Oberlin, LA WHISK UNDEV 1,305 YES YES YES

08064100 Chambers Creek NR Rice, TX CHAM MIX 2,136 YES YES No

08012150 Mermentau River at Mermentau, LA MERM MIX 3,576 YES YES YES

08181800 San Antonio River NR Elmendorm, TX SANANT MIX 4,528 YES YES YES

08057410 Trinity River BLW Dallas, TX TRIN MIX 16,227 YES YES YES

07030392 Wolf River at Lagrange, TN WOLF MIX 543 YES YES YES

07288955 Yazoo River BLW Steele Bayou NR Long Lake, MS YAZ MIX 34,850 YES YES YES*
Table 1 19

Table 1. General site characteristics for the 91 U.S. Geological Survey (USGS) National Water-Quality Assessment (NAWQA) Program long-term surface-water status and trend sites.—Continued[USGS, U.S. Geological Survey; km2, square kilometer; AG, Agricultural land use; URB, Urban land use; UNDEV, Undeveloped land use, MIX, Mixed land use; YES, sites for which temporal trends in 

biotic assemblages were analyzed; No, sites for which temporal trends in biotic assemblages were not analyzed; Bold type indicates sites and biotic assemblages with significant temporal trends; *, p < 0.05; 

**

, p < 0.01]

USGS station Drainage Station Land-use Algae Macroinvertebrates Fish identification Station name area code category analyzed1 analyzed analyzed number (km2)

Western United States

12464770 Crab Creek at Rocky Ford Road NR Ritzville, WA CRAB AG 1,188 YES* YES YES**

12505450 Granger Drain at Granger, WA GRANG AG 160 No YES** No

06800000 Maple Creek NR Nickerson, NE MAPLE AG 954 YES** YES YES

11274538 Orestimba Creek at River RD NR Crows Landing CA OREST AG 28 YES* YES** No

14201300 Zollner Creek NR Mt Angel, OR ZOLLN AG 39 YES YES* No

11447360 Arcade Creek NR Del Paso Heights CA ARCD URB 82 YES* YES** No

06713500 Cherry Creek at Denver, CO CHERRY URB 1,063 YES** YES YES

14206950 Fanno Creek at Durham, OR FANNO URB 81 YES** YES YES

10168000 Little Cottonwood Creek at Jordan River NR SLC, UT LCOTTN URB 117 YES YES* YES**

11074000 Santa Ana R BLW Prado Dam CA PRADO URB 3,727 YES** YES** YES**

12128000 Thornton Creek NR Seattle, WA THORT URB 29 YES YES* YES*

402114105350101 Big Thompson BLW Moraine Park NR Estes Park, CO BTHMP UNDEV 103 YES YES YES*09163500 Colorado River NR Colorado-Utah State Line COLOR UNDEV 46,274 YES** YES* YES

11335000 Cosumnes River ABV Michigan Bar, CA CONSM UNDEV 1,389 YES** YES No

06775900 Dismal River NR Thedford, NE DISML UNDEV 2,503 YES* YES YES

10309010 E FK Carson River NR Dresslerville, NV EFCAR2 UNDEV 970 YES* YES No

14205400 East Fork Dairy Creek NR Meacham Corner, OR EFDAR UNDEV 88 YES* YES** YES

14200400 Little Abiqua Creek NR Scotts Mills, OR LABIQ UNDEV 25 YES YES* YES

06324970 Little Powder River ABV Dry Creek, NR Weston, WY LPOWD UNDEV 3,204 YES YES YES*

06753990 Lonetere Creek NR Greeley, CO LTREE UNDEV 1,478 YES* YES No

11273500 Merced River ABV River Road Bridge NR Newman CA MERC2 UNDEV 3,621 YES* YES YES

12056500 NF Skokomish River BLW Staircase RPDS NR Hoodsport, WA NFSK UNDEV 147 YES* YES No

06805500 Platte River at Louisville, NE PLATTE UNDEV 220,908 YES No No

10172200 Red Butte Creek at Fort Douglas, NR SLC, UT RBUTT UNDEV 19 YES YES No

08364000 Rio Grande at El Paso, TX RIOGR UNDEV 77,556 YES** YES No

13092747 Rock Creek ABV Hwy30/93 Xing at Twin Falls ID ROCRK UNDEV 623 YES** YES YES**

08227000 Saguache Creek NR Saguache, CO SAGUC UNDEV 1,327 YES YES YES

11303500 San Joaquin River NR Vernalis CA SJOAQ UNDEV 19,153 No YES YES*
20 Multi-Regional Synthesis of Temporal Trends in Biotic Assemblages in Streams and Rivers of the United States Table 1 20 Table 1. General site characteristics for the 91 U.S. Geological Survey (USGS) National Water-Quality Assessment (NAWQA) Program long-term surface-water status and trend sites.—Continued [USGS, U.S. Geological Survey; km2, square kilometer; AG, Agricultural land use; URB, Urban land use; UNDEV, Undeveloped land use, MIX, Mixed land use; YES, sites for which temporal trends in biotic assemblages were analyzed; No, sites for which temporal trends in biotic assemblages were not analyzed; Bold type indicates sites and biotic assemblages with significant temporal trends; *, p < 0.05; **, p < 0.01] USGS station Drainage Station Land-use Algae Macroinvertebrates Fish identification Station name area code category analyzed1 analyzed analyzed number (km2

)

Western United States—Continued

09471000 San Pedro River at Charleston, AZ SPEDR UNDEV 3,257 YES YES YES

340843117032501 Santa Ana River ABV Upper PH NR Running Springs CA STANA1 UNDEV 398 YES** YES YES13010065 Snake River ABV Jackson Lake at Flagg Ranch WY SNRIV UNDEV 1,324 YES* YES YES

13154500 Snake River at King Hill ID KNHILL UNDEV 92,942 YES** YES** YES

06754000 South Platte River NR Kersey, CO SPLATT UNDEV 25,016 YES* YES YES**

10350500 Truckee River at Clark, NV TRUCK3 UNDEV 4,310 YES* YES No

09505800 West Clear Creek NR Camp Verde, AZ WCLCK UNDEV 615 YES** YES* YES**

06329500 Yellowstone River NR Sidney, MT YSTON UNDEV 177,139 YES YES No

1Algae samples collected in the northeastern/north-central and southeastern regions currently (2013) are being analyzed as part of a separate study.
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Or visit the USGS National Water-Quality Assessment Program web site:

http://water.usgs.gov/nawqa/

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Miller and others—Multi-Regional Synthesis of Temporal Trends in Biotic Assemblages in Streams and Rivers of the United States—Scientific Investigatons Report 2013–5046