Sponseller, R.A., E.F. Benfield, and H.M. Valett. 2001

Freshwater Biology (2001) 46,1409-1424 

APPLIED ISSUES 

Relationships between land use, spatial scale 

and stream macroinvertebrate communities 

R. A. SPONSELLER, E. F. BENFIELD andH. M. VALETT 

Department of Biology, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, U.S.A. 

SUMMARY 

1. The structure of lotic macroinvertebrate communities may be strongly influenced by 

land-use practices within catchments. However, the relative magnitude of influence on 

the benthos may depend upon the spatial arrangement of different land uses in the 

catchment. 

2. We examined the influence of land-cover patterns on in-stream physico-chemical 

features and macroinvertebrate assemblages in nine southern Appalachian headwater 

basins characterized by a mixture of land-use practices. Using a geographical information 

system (GIS)/remote sensing approach, we'quantified land-cover at five spatial scales; the 

entire catchment, the-Tiparian corridojvand three riparian 'sub-corridors' extending 200, 

1000 and 2000 m upstream of sampling reaches. 

3. Stream water chemistry was generally related to features at the catchment scale. 

Conversely, stream temperature and substratum characteristics were strongly influenced 

by land-cover patterns at the riparian corridor and sub-corridor scales. 

4. Macroinvertebrate assemblage structure was quantified using the slope of rankabundance 

plots, and further described using diversity and evenness indices. Taxon 

richness ranged from 24 to 54 among sites, and the analysis of rank-abundance curves 

defined three distinct groups with high, medium and low diversity. In general, other 

macroinvertebrate indices were in accord with rank-abundance groups, with richness and 

evenness decreasing among sites with maximum stream temperature. 

5. Macroinvertebrate indices were most closely related to land-cover patterns evaluated at 

the 200 m sub-corridor scale, suggesting that local, streamside development effectively 

alters assemblage structure. 

6. Results suggest that differences in macroinvertebrate assemblage structure can be 

explained by land-cover patterns when appropriate spatial scales, are employed. In 

actdition, the influence of riparian forest patches on in-stream habitat features (e.g. the 

thermal regime) may be critical to the distribution of many taxa in headwater streams 

draining catchments with mixed land-use practices. 

Keywords: geographical information system, land use, macroinvertebrates, riparian corridor, 

temperature 

Introduction 

Maintenance of stream biodiversity in the face of 

•• encroaching human development has received much 

Correspondence: R. A. Sponseller, Department of Biology, attention in recent years (e.g. Allan & Flecker, 1993; 

Arizona State University, Tempe, Arizona 85287-1501, AZ, Harding et al., 1998). Furthermore, research has 

U.S.A. E-mail: rsponse@asu.edu 

© 2001 BlackweU Science Ltd 1409

1410 R.A. Sponseller et al. 

demonstrated that the conversion of forests to pastures 

and/or residential areas may influence 

in-stream habitat and macroinvertebrate communities 

in several ways. Loss of terrestrial vegetation (Swank, 

Swift & Douglas, 1988) and an increased area of 

impervious surfaces (Changnon & Demissie, 1996) 

can influence evapotranspiration and infiltration and 

alter natural flow regimes (Poff et al., 1997). Many 

land-use practices increase sediment inputs to 

streams, altering substratum characteristics and channel 

morphology, often reducing macroinvertebrate 

diversity (Lenat & Crawford, 1994; Waters, 1995; 

Quinn et al., 1997). Removal of streamside vegetation 

and subsequent increased solar radiation reaching the 

stream channel can increase temperature (Burton & 

Likens, 1973; Rutherford et al., 1997; Quinn et al, 

1997) and alter thermal regimes that are critical to 

the life history and ecology of macroinvertebrates 

(Vannote & Sweeney, 1980; Ward & Stanford, 1982; 

Quinn et al., 1994). In association with.altered catchment- 

hydrology and land use, inputs of inorganic 

-nutrients from terrestrial sources (e.g. Omernik, 1977; 

Hunsaker & Levine, 1995; Johnson et al., 1997) may 

interact with increased light availability and stream 

temperature to enhance in-stream primary production 

(Webster et al., 1983), resulting in changes in the 

trophic structure of benthic communities (e.g. Gurtz 

& Wallace, 1984). 

The relative magnitude of land-use effects may 

depend upon the spatial distribution of land use in 

catchments (Allan & Johnson, 1997). Catchment 

hydrology, as well as the availability of inorganic 

nutrients in streams, is often related to processes that 

occur across the terrestrial landscape (Omernik, 1977; 

Swank, Swift & Douglas, 1988; Hunsaker & Levine, 

1995). Conversely, the availability of light and organic 

carbon in streams is often related to processes restricted 

to the scale of streamside vegetation (Gregory 

et al., 1991). Several studies have shown that in-stream 

physico-chemical and biotic features may be constrained 

by catchment properties operating at different 

spatial scales. For example, Richards, Johnson & 

Host (1996) identified catchment-scale characteristics, 

particularly basin geology and the distribution of 

arable agriculture, as features mediating channel 

morphology and stream hydrology. At the same time, 

land-cover in the riparian corridor had a strong 

influence on bank erosion and in-stream sedimentrelated 

variables. Further, they found that basin-wide 

features were the best predictors for macroinvertebrate 

assemblage structure. Conversely, Richards et al. 

(1997) showed that despite a close relationship 

between catchment-scale properties and channel 

structure and hydrology, macroinvertebrate species 

traits were correlated with local (reach-scale) features. 

In addition, spatial scales of catchment control may 

vary temporally. For example, Johnson et al. (1997) 

found that the strength of relationship between 

stream-water chemistry and catchment scale versus 

riparian scale land-cover patterns varied among season 

and with dissolved chemical constituents in 

Michigan streams. 

The southern Appalachian region of the United 

States has been subject to a variety of land-use 

changes during the last century (Benfield, 1995). 

Between 1880 and 1920, almost all of the timber in 

the states of Virginia, West Virginia, North Carolina 

and Tennessee was harvested (Yarnell, 1998). This 

•was followed by agricultural activity, which 

increased in importance through to the 1960s. Since 

1970 human population in the southern Appalachians 

has increased by nearly 30% and agricultural 

activity has declined by 31%, leading to a largescale 

conversion of agricultural land to either 

forests or residential areas (SAMAB, 1996). This 

history has resulted in a mosaic of different landuse 

patches across the landscape. Current landcover 

patterns in many Southern Appalachian 

catchments are characterized by high gradient 

headwater areas that are difficult to develop and 

are often forested, and low gradient areas subject to 

active agriculture or conversion to urban land 

(Wear & Bolstad, 1998). 

In this study, we investigated the effects of land-use 

on benthic macroinvertebrate assemblages in southern 

Appalachian headwater streams. Specifically, we 

address how differences in land use among catchments 

influences in-stream physico-chemical features 

and macroinvertebrate assemblage structure. In addition, 

we sought to determine how changes in 

in-stream features (both biotic and abiotic) relate to 

the spatial arrangement of land use within catchments. 

To do this, we quantified the relationship 

between land-cover and in-stream variables at multiple 

spatial scales. This approach allowed us to 

evaluate the ecological implications of land-use practices 

that occur streamside versus those that occur 

across the catchment. 

© 2001 Bkckwell Science Ltd, Freshwater Biology, 46,1409-1424

Methods 

Site description 

The study was conducted in the Upper Roanoke River 

Basin (URRB) in south-western Virginia (Fig. 1) at the 

interface of the Appalachian Valley and Ridge and 

Blue Ridge physiographic provinces. The URRB is 

topographically and geologically diverse, and.is characterized 

by Precambrian and Cambrian metamorphics 

and elastics at higher altitude and Cambrian and 

Ordovician carbonates lower in the valley (Waller, 

1976). Nine catchments with second or third order 

streams were selected for study. Catchments ranged in 

altitude from 325 to 575 m above sea level, and varied 

from 278 to 1014 hectares. Six of nine catchments were 

characterized by some degree of human activity (e.g. 

agricultural or urban development); the remaining 

three had no such development. One 50-m stream 

North Fork 

Influences of land use on stream macroinvertebrates 1411 

reach was selected within each catchment as our study 

site. Benthic habitat at all streams consisted of particles 

ranging from silt to cobbles, although the relative 

proportion of these size classes varied among sites. 

Land use quantification 

A geographical information system (GIS) (Arcview 3.1; 

ESRI, Redland, CA, U.S.A.) was used to quantify land 

cover within each basin. Digital land-cover information 

for the Roanoke Valley was obtained from a 

preliminary land-cover map of Virginia, produced 

through the Virginia Gap Analysis Project (VAGAP) 

for 1992 (Morton, 1998). This statewide data set was 

generated from 14 Landsat thematic mapper scenes, 

and classified using both unsupervised and enhanced 

supervised methods (Morton, 1998). Pixels provided 

30 x 30 m resolution and included information from 

North 

10 km 

Fig. 1 Upper Roanoke River Basin (URRB), showing North and South Fork sub-basins, and selected study sites. Site names correspond 

as follows: (1) Powers Branch, (2) Sugar Run, (3) Purgatory Tributary, (4) Martins Creek, (5) Little Back Creek, (6) Greenbriar Branch, 

(7) Mudlick Creek, (8) Earnhardt Creek, (9) Franklin Creek. 

© 2001 BlackweU Science Ltd, Freshwater Biology, 46,1409-1424


seven land-use categories: deciduous forest, coniferous 

forest, mixed forest, shrub/scrubland, herbaceous 

(mostly agriculture), open water and disturbed (areas 

lacking vegetation). We further categorized the data 

into forest and non-forest. The forest category included 

all forest types, but was dominated by the 

deciduous class. The non-forest category included 

both agricultural and urban/suburban areas. 

Morton (1998) used aerial videography to acquire 

reference data and assess the accuracy of the statewide 

land-cover data set, which was found to be 81%. 

This level of accuracy may not hold for riparian 

corridors, which are more difficult to classify, particularly 

in mountainous areas. Our accuracy assessment 

of riparian corridors, from 25 locations across five 

study catchments with the greatest land-cover heterogeneity, 

found approximately 75% of the streamside 

pixels were correctly classified. However, of the pixels 

classified as non-forest, 50% had' thin' ;strips (e.g. 

< 1 m) of riparian vegetation but otherwise lacked 

forested 'area. Incorrect classifications encountered in 

-the assessment generally occurred when pixels classified 

as forest had small residences but were otherwise 

well forested. 

Sampling reach 

Riparian subcorridor 

polygons 

Catchments were delineated using a watershed 

delineator (ESRI & Texas Natural Resource Conservation 

Commission, 1997) which uses neighbourhood 

functions with data from US Geologic Survey (USGS) 

digital elevation maps to quantify the surface area 

contributing to drainage through a given point. The 

outputs were converted to catchment polygons, which 

included the entire drainage area upstream of the 

sampling reach. Land-cover derived from all pixels 

within catchment polygons were used to characterize 

catchment scale land-use patterns. Within each catchment 

polygon, a 60-m riparian corridor polygon was 

created with 30 m of width extending laterally, 

beginning at the sampling reach and continuing for 

the entire length of the stream. The influence of 

riparian land-cover at specific distances upstream of 

the study reach was assessed by dividing riparian 

corridors longitudinally into sub-corridor polygons. 

We used five spatial scales for analysis: (1) the 

•catchment scale, including all of the area within its 

watershed, (2) riparian corridor scale, extending over 

the entire length of the stream, (3) 2000 m riparian 

sub-corridors, (4) 1000 m riparian sub-corridors and 

(5) 200 m riparian sub-corridors (Fig. 2). Associated 

Catchment polygon 

Riparian corridor 

polygon 

Fig. 2 Examples of GIS polygons used to analyse land-cover patterns at five spatial scales, including the entire catchment, riparian 

corridor and three riparian sub-corridors extending 200,1000 and 2000 m upstream from the sampling reach. 

© 2001 Blackwell Science Ltd, Freshwater Biology, 46,1409-1424

catchment, riparian corridor and sub-corridor polygons 

were overlaid onto the digital land-cover data 

for each study basin. Percentages for land-cover 

categories were quantified within all spatial polygons. 

Regression analysis was used to relate physicochemical 

and biological variables to land cover at the 

catchment, riparian corridor and sub-corridor scale. 

Percent non-forest values were transformed .(arcsine 

square root) for statistical analyses. 

Physical and chemical characterizations 

Physical and chemical measurements were made for 

each stream from January to December 1999. Triplicate 

water samples were collected monthly from each site, 

passed through glass fibre filters (Whatman GFF, 

Gelman Type AE, Maidstone, U.K.), and kept frozen 

until analysed. Samples were analysed for ammonium-nitrogen 

(NH4-N) using the phenaj;e' ,'frtethod 

(Soloranzo, 1969) and nitrate-nitrogen, (NO3-N) by 

colormetric 'techniques following reduction by Cd 

(Wood, Armstrong & Richards, 1967) on a Technicon 

Auto-analyser (Bran & Luebbe, Buffalo Grove, IL, 

U.S.A.). Total inorganic nitrogen (TIN) was calculated 

as the sum of NH4-N and NO3-N. Ortho-phosphate 

(PO4-P) was analysed as soluble reactive phosphorus 

(SRP) using the molybdate colorimetric method 

(Murphy & Riley, 1962; Wetzel & Likens, 1991). Specific 

conductance was measured seasonally using a YSI 

Model 30/50- (YSI, Yellow Springs, OH, U.S.A.) conductivity 

meter. Alkalinity was determined once 

at each site by standard methods (APHA, 1998). 

Temperature was recorded monthly until continuous 

temperature data recorders (HOBO, Polasset, MA, 

U.S.A.) were installed in March 1999, after which it was 

recorded hourly through November 1999. Temperature 

variables used in analyses included the overall 

mean temperature (T, °C), and maximum summer 

temperature (Tmax, °C). Discharge was measured at 

least monthly at each site using velocity determined 

with an electronic flowmeter (FLOW-MATE, Marsh- 

McBirney, Frederick, MD, U.S.A.) and cross-sectional 

area (Gore, 1996). Mean substratum particle size (MPS) 

was determined using standard granulometry techniques 

(sensu Wolman, 1954) on 100 randomly selected 

rocks at each site with a USGS gravelometer. We also 

quantified the percentage of all particles measured at 

each site small enough to be categorized as coarse 

gravel, sand and silt (% < 16 mm). 

© 2001 BlackweU Science Ltd, Freshwater Biology, 46,1409-1424 


Benthic algal biomass 

Epilithic biomass (g m" 2 ) and chlorophyll a (mg m" 2 ) 

were determined monthly at each site from the 

surfaces of five rocks collected along each 50 m reach. 

Upon collection, rocks were packed in ice, and 

returned to the laboratory for processing. Upper 

surfaces were scrubbed and the resultant slurry subsampled 

and collected on preweighed glass fibre filters 

(Whatman GFF, Gelman Type AE). Filters were incubated 

in a 90% buffered acetone solution for 24 h (sensu 

Steinman & Lamberti, 1996). Photosynthetic pigments 

(chlorophyll a and phaeophytin) were measured using 

spectrophotometry (at 664, 665 and 750 nm) on a 

Shimadzu UV-1601 spectrophotometer. An additional 

subsample was taken to determine epilithic ash-free 

dry mass (AFDM) by gravimetric techniques (drying at 

50 °C for 48 h, followed by ashing at 550 °C for 1 h). 

Photo'synthetic pigment concentration (mg m" 2 ) and 

^AFDM (g m~ 2 ) were normalized to surface area determined 

by covering scraped surfaces with aluminium 

foil of known mass per unit area. 

Invertebrate assemblages 

Benthic invertebrates were collected from all sites in 

April 1999. Five Hess samples (surface area, 

0.08 m 2 sample" 1 ; mesh size, 250 mm) were taken 

along each 50 m reach. Samples were preserved in 

80% ethanol, and individuals identified to genus 

following Merritt & Cummins (1996), Stewart & Stark 

(1993) and Wiggins (1996). Chironomid larvae from 

all samples within a site were combined, quantitatively 

subsampled, mounted and identified following 

Epler (1995) and Merritt & Cummins (1996). 

To address changes in benthic community structure 

among sites, we quantified traditional measures of 

richness and evenness, and a compositional index 

commonly used to indicate environmental stress. 

Indices used to assess diversity included taxon number 

(S), and the Shannon-Weiner Diversity Index: 

where 

Pi represents the proportion of individuals found 

in the ith taxon, with values summed across all taxa 

(S). We also used the associated evenness measure


calculated from H'. This index assumes that maximum 

diversity occurs when all taxa are equally 

abundant (i.e. H' = H'max = hi S). Therefore, the ratio 

of H'/H'max represents a measure of evenness where 

an assemblage with an equal abundance of taxa 

would have a value of 1 (Pielou, 1969). As an 

additional measure of evenness we quantified the 

percentage of the total numbers accounted for by the 

five most dominant taxa at each site (% 5 Dominant) 

(Barbour et al., 1999). Finally, to assess compositional 

differences among sites, we quantified the taxonomic 

richness of commonly intolerant taxa (Ephemeroptera 

+ Plecoptera + Trichoptera, EFT), widely used as an 

indicator of disturbance to stream communities (Lenat 

& Crawford, 1994; Wallace et al., 1996). 

Rank-abundance curves (sensu; Hawkins, Murphy 

& Anderson, 1982; Marsh-Mathews & Mathews, 2000) 

were generated for invertebrate assemblages at each 

site. Curves consisted of lognormal;:'proportional 

abundance (pi) for each taxon plptted against the 

corresponding taxonomic abundance ranking. The 

-slope of this line (Alog p;/n, where n = number of 

taxa) was used as an integrative measure of taxon 

richness and evenness. Diversity is maximized when 

the slope of the curve approaches zero. Slopes become 

increasingly negative when the proportional abundance 

(pi) of the more dominant taxa increases 

(i.e. evenness decreases), or when taxon richness 

decreases. We used the absolute value of the slope 

for all analyses; therefore, larger values represent 

steeper rank-abundance curves, and thus, less diverse 

assemblages. 

Data analysis 

Bivariate regression analysis was used to relate land 

cover variables (e.g. % non-forest) at each spatial scale 

to the in-stream physico-chemical variables and 

macroinvertebrate indices measured at all sites. In 

Site number 

Scale 

Catchment 

Entire riparian 

corridor 

Sub-corridors (m) 

200 

1000 

2000 

1 

7.5 

1.2 

0.0 

0.0 

0.0 

2 

11.7 

1.9 

0.0 

0.0 

0.8 

3 

13.9 

1.3 

0.0 

3.1 

1.5 

4 

20.3 

56.3 

75.0 

92.2 

77.6 

5 

8.4 

10.8 

23.1 

7.3 

3.7 

6 

34.2 

19.2 

14.3 

4.3 

22.8 

addition, macroinvertebrate indices were used as 

dependent variables in stepwise multiple regression 

analyses with in-stream physico-chemical parameters. 

Variables that failed to meet a 0.05 probability value 

were removed from multiple regression models. 

Regression analysis was used to test rank-abundance 

curves for linearity and the slope of the lognormal 

plots was compared among sites using methods 

described in Zar (1996) with a Bonferroni correction 

for multiple comparisons. All regression analyses 

were performed on SAS 7.0 (SAS Inc., Gary, NC, 

U.S.A.). 

Results 

The magnitude and spatial arrangement of nonforested 

land varied considerably among drainage 

basins at the catchment, riparian corridor and subcpTridor 

scales (Table 1). In addition, the proportion 

•of non-forested area within any given riparian corridor 

often varied greatly when compared with that of 

the associated catchment. For example, in four basins 

(Table 1, sites 1, 2, 3 and 6), the percentage non-forest 

in the entire riparian corridor was approximately 25% 

of that observed at the scale of the entire catchment; 

indeed sites 2 and 3 were nearly an order of 

magnitude lower. At the same time, the percentage 

non-forest within the riparian corridor increased 2.8 

(site 4), 1.3 (site 5), 1.4 (site 8) fold at three other sites. 

Within riparian corridors, the distribution of nonforested 

area varied in proximity to the study reach 

(Table 1). In basins with low non-forest cover at both 

the catchment and total riparian corridor scales, nonforest 

cover in sub-corridors was also low. For 

example, at sites 1-3, six of nine riparian sub-corridors 

were entirely forested and a maximum of only 3% 

was non-forest (Table 1). For basins less forested at 

broader spatial scales, the percentage non-forest in 

sub-corridors often increased substantially. For the 

7 

41.4 

34.7 

85.7 

80.8 

49.3 

8 

19.3 

26.4 

92.9 

55.9 

51.1 

9 

19.7 

19.9 

84.6 

77.0 

54.6 

Table 1 Land-cover patterns for the nine 

study basins. Values are percent nonforested 

land within each scale category. 

Sub-corridor values are the percent of 

non-forested land within a polygon of 

60 m width and progressively greater 

distances upstream from the sampling 

reach 


four basins with the least forest cover at the catchment 

scale,% non-forest in the sub-corridors averaged 58% 

and was as great as 93%. Finally, longitudinal 

changes in forest cover within riparian corridors 

varied greatly among basins. For instance, at site 9. 

20% of land cover was non-forest at both the catchment 

and entire riparian corridor scales. However, if 

only the first kilometre of the riparian corridor was 

considered, 80% of the landscape was non-forest. 

Conversely, site 6 was classified as 34% non-forest 

at the catchment scale, but only 19 and 4% was 

non-forest at the entire riparian corridor and 1000 m 

sub-corridor scales, respectively. 

Physical responses 

Variation in several in-stream physical properties was 

related to catchment features and/or land-cover 

patterns at multiple spatial scales (Table;2). For 

example, stream discharge ranged from 15.3 L s" 1 

(site 3) to-55.4 L s" 1 (site 5), varied temporally to a 

similar extent among streams with annual CVs 

ranging from 46 to 83% and was closely related to 

basin area (r 2 = 0.85, n = 9, P - 0.004). Mean stream 

temperature varied by only 4.3 °C among sites, but 

maximum temperature varied by 6.7 °C, with the 

greatest mean temperature and highest maximum 

temperature both at site 7. Mean stream temperature 

decreased with increasing altitude (r 2 = 0.78, n = 9, 

P = 0.002), and multiple regression indicated that the 

combination of altitude and the percentage non-forest 

at the entire riparian corridor scale explained 93% of 

the variation in temperature (n = 9, P = 0.02). Maximum 

stream temperature increased with the percentage 

of non-forested land at the entire riparian 

corridor scale (^^.79, n = 9, P = 0.001) and at the 

sub-corridor scales of 2000 and 1000 m (r 2 = 0.71, 

n = 9, P = 0.005; r 2 = 0.71, n = 9, P = 0.005, respectively). 

However, the strongest relationship between 

maximum stream temperature and the percentage 

non-forest was found at the 200 m riparian subcorridor 

scale (r 2 = 0.81, n = 9, P = 0.001). The mean 

size of coarse substratum ranged from 44.8 mm 

at site 8 to 72.4 mm at site 2, and decreased with 

the percentage of non-forested land at the catchment 

(r 2 = 0.56, K = 9, P = 0.02), riparian corridor 

(r 2 = 0.74, n = 9,P= 0.003) and 2000,1000 and 200 m 

and sub-corridor (r 2 = 0.80, n - 9, P = 0.001; r 2 = 

0.61, n = 9, P = 0.013; ^ = 0.74, n = 9, P = 0.003, 

© 2001 Blackwell Science Ltd, Freshwater Biology, 46,1409-1424 


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respectively) scales. The percentage of particles 

< 16 mm ranged from 17.1 at site 3 to 44.4 at site 8, 

and was only weakly related to the percentage nonforest 

within 200 m sub-corridor polygons (r 2 = 0.52, 

n = 9, P = 0.03). 

Chemical responses 

Chemical variables were also related to catchment 

features or land-cover patterns at the catchment 

scale. Alkalinity ranged from 16 mg IT 1 at site 1 to 

98 mg LT 1 at site 9 and decreased with catchment 

altitude (r 2 = 0.63, n = 9, P = 0.01). In addition, 

specific conductance (us cm" 1 ) varied among sites 

from 47.3 at site 1 to 261.8 at site 9, and was strongly 

related to alkalinity (r 2 = 0.95, n = 9, P = 0.0001) and 

altitude (r 2 = 0.67, n = 9, P = 0.007). Total inorganic 

N varied among sites (CV = 80%), with minimum 

values of 0.105 mg IT 1 (site 5) and ma)drrnlm values 

of 0.932 mg LT 1 (site 6), and increased with the 

percentage of non-forested land at the catchment 

-scale (r 2 = 0.59, n=9,P = 0.02). Soluble reactive 

phosphorus did not differ greatly among sites 

(CV = 38%) and did not correspond to any physical 

features of the catchment, or indeed land-cover at 

any spatial scale. 

Biological responses 

Based on field observation, algal assemblages were 

generally dominated by diatoms, although filamentous 

algae (e.g. Cladophora sp.) were found in abundance 

in streams draining catchments with extensive 

agricultural or urban development (e.g. sites 8 and 9). 

Mean annual epilithic chlorophyll a concentration 

ranged from a"rnjnimum of just 7.0 mg m~ 2 at site 3 to 

121.1 mg m~ 2 at site 8. Chlorophyll a values were 

lowest for sites 1-3, where averages ranged from 7.02 

to 27.9 mg m~ 2 ; concentrations were higher at the 

remaining sites with averages ranging from 

54.8 mg m~ 2 (site 6) to 121.1 mg m~ 2 (site 8) (Table 2). 

Bivariate regression analysis did show a relationship 

between chlorophyll a concentration and mean stream 

temperature (r 2 = 0.66, n = 9, P = 0.008). However, 

multiple regression analysis incorporated only maximum 

temperature into the model, explaining 73% of 

the variability in chlorophyll a, (n = 9, P = 0.003). 

Epilithic biomass ranged from 5.3 g m~ 2 at site 3 

to 33.8 g rrf 2 at site 9, and was closely related to 

epilithic chlorophyll a concentration (r 2 = 0.80, n = 9, 

P = 0.001). 

Macroinvertebrate density varied among sites from 

6974 m" 2 at site 3 to 15 730 m~ 2 at site 9 (Table 3). 

Multiple regression analysis with density as the 

dependent variable incorporated only epilithic biomass 

into the model, accounting for 87% of the 

variability among sites (n = 9, P- 0.0003). A total of 

77 macroinvertebrate taxa were identified from the 

nine sites. Taxon richness ranged from 24 at site 8 to 

54 at site 3 with five EFT taxa at site 8 and 22 EFT taxa 

at sites 2 and 3 (Table 3). Results of the comparison of 

rank-abundance slopes indicated significant among 

site differences (P < 0.001, after Bonferroni correction), 

with three general groups emerging that represent 

high, medium and low diversity (Fig. 3). All 

rank-abundance curves fit linear models (r 2 > 0.9, 

P > 0.001) and slope values ranged from -0.0470 at 

bbth sites 1 and 2 to -0.1100 at site 7. Stepwise 

'multiple regression analyses between macroinvertebrate 

indices and in-stream physico-chemical variables 

generally incorporated a single independent 

variable into the models (Table 4). For example, 

the slope of rank-abundance curves increased with 

epilithic chlorophyll a concentration (r 2 = 0.64, 

n = 9, P = 0.009). Total taxon richness (S) and EFT 

richness decreased with maximum stream temperature 

(^ = 0.54, n=9, P = 0.02, 7^ = 0.75, n = 9, 

P = 0.003). Similarly, diversity (HO and evenness 

(H'/H'max) also decreased with maximum stream 

temperature (r 2 = 0.72, n = 9,P = 0.004; r 2 = 0.83, 

« = 9, P = 0.002, respectively). The percent 5 dominant 

taxa ranged from 55% at site 3 to 93% at site 8, 

and increased with increasing maximum stream 

temperature (r 2 = 0.75, « = 9, P = 0.003). 

The structure of macroinvertebrate assemblages 

corresponded to the variance in land-cover patterns 

among catchments (Table 5). Macroinvertebrate density 

was most closely related to the percentage of 

non-forest land at the 2000 m sub-corridor scale. 

Rank-abundance slopes increased with the percentage 

of non-forested land at the entire riparian corridor, 

and at 2000 and 1000 m sub-corridor scales, but 

were most strongly associated with land-cover patterns 

at the 200 m sub-corridor scale. In general, other 

measures of diversity, evenness and composition 

most closely corresponded to the percentage nonforest 

at the 200 m sub-corridor scale. Shannon's 

evenness decreased with the percentage non-forest, 


aence Ltd, Freshwater Biology, 4 

\ 

Table 3 Benthic macroinvertebrate indices for each study site. Density data are mean ± SE for five Hess samples from each 50 m study reach. Sites are presented in groups 

with other sites having statistically similar rank-abundance slopes 

Rank abundance 

diversity group 

Site number 

Density 

Taxonrichness (S) 

EFT taxa 

H' 

W'/H'max 

%5 Dominant 

W 

o ' 

CO 

o ' 

o 

1* 

o 

IO 

L* 

Jco 

IcD 

9 

15730 ± 1334 

40 

16 

1.98 

0.54 

83.3 

fe 

Low 

8 

13907 ± 671 

30 

11 

1.78 

0.52 

89.5 

7 

8923 ± 2664 

24 

5 

1.20 

0.38 

92.9 

Proportional abundance (P,) 

p p -» _* _k 

2 - ° S


Table 5 Regression coefficients (r 2 ) for significant bivariate regressions (n = 9, P < 0.05) between macroinvertebrate indices and 

the percentage non-forest at five spatial scales. R-A slope = absolute value of rank-abundance slopes, ns = Not significant 

Catchment 

Riparian corridor 

Sub-corridors (m) 

2000 

1000 

200 

Density 

ns 

ns 

0.57 

ns 

0.54 

R-A slope 

ns 

0.44 

0.51 

0.61 

0.82 

Taxon richness 

ns 

ns 

ns 

0.42 

0.64 

only at the 200 m sub-corridor scale. Taxon richness, 

diversity, the percent five dominant taxa and EPT taxa 

richness were most strongly related to land cover 

within 200 m sub-corridors, but were also significantly 

related to land-cover patterns in other subcorridors. 

In addition, EPT taxa richness was related 

to the percentage non-forest at catchment scale 

and was the only macroinvertebrate' irtdex that 

corresponded to land-cover patterns at all spatial . 

scales evaluated. 

Discussion 

The observed variability in many of the chemical 

constituents studied in the URRB streams can be 

attributed to physical features (e.g. altitude) or landcover 

patterns at the catchment scale. The relationships 

between alkalinity, specific conductance and 

altitude probably reflect shifts in catchment geology 

(Waller, 1976). In this part of the URRB, catchments at 

high altitude are dominated by clastic materials (both 

granitic and sedimentary) and have relatively low 

alkalinity and specific conductance when compared 

with low altitude streams that are influenced more by 

soluble parenHithology. The three catchments nearest 

the town of Salem, Virginia (sites 7, 8 and 9) include 

both clastic and carbonate materials, and subsequently 

had the highest alkalinity and specific conductance 

concentrations among sites. Variation in 

stream-water TIN was only related to the percentage 

non-forest at the catchment scale. This is consistent 

with many studies that have shown land-cover at the 

catchment scale to be a good predictor of in-stream 

nutrient concentration, particularly nitrate (Omernik, 

1977; Close & Davies-Colley, 1990; Hunsaker & 

Levine, 1995; Johnson et al, 1997). 

In-stream physical variables were also closely 

related to land-cover patterns, particularly at the 

H' 

ns 

ns 

ns 

0.43 

0.64 

H'/Hmax 

ns 

ns 

ns 

ns 

0.60 

%5 Dominant 

ns 

ns 

0.44 

0.50 

0.76 

EPTtaxa 

0.46 

0.52 

0.45 

0.52 

0.68 

riparian corridor and sub-corridor scales. Mean 

stream temperature, although related to altitude, 

was also influenced by land-cover patterns within 

riparian corridors. Moreover, maximum temperature 

was strongly related to the percentage non-forest at 

the scale of the 200 m riparian sub-corridor. High 

mean and maximum stream temperature may result 

from solar radiation reaching the stream channel 

'(Burton & Likens, 1973; Beschta & Taylor, 1988; 

Rutherford et al., 1997), and/or from run-off heated 

by impervious surfaces in residential areas (Galli, 

1991). The local influence of land-cover on stream 

thermal regimes (i.e. at the 200 m sub-corridor scale) 

supports the idea that temperature can change quickly 

(with respect to longitudinal distance) when streamside 

vegetation is removed in headwater catchments. 

Burton & Likens (1973) found summer stream-water 

temperature fluctuations of 4-5 °C, alternating 

between 50 m reaches where riparian vegetation had 

been experimentally removed or left intact in Hubbard 

Brook streams. Similarly, Storey & Cowley (1997) 

showed that high temperature in pasture streams of 

New Zealand return to 'forested control' levels after 

running through approximately 300 m of remnant 

riparian forests. 

Substratum characteristics were also influenced by 

catchment land use. Mean substratum particle size 

was inversely related to the percentage non-forest at 

all spatial scales, but the strongest relationships were 

observed at the 2000 m sub-corridor scale. The 

percentage of particles

particularly when these occur adjacent to the channel 

(Lenat et al., 1981; Waters, 1995; Richards et al., 1996). 

Several- studies have also reported that intact 

streamside vegetation inhibits the delivery of sediments 

to streams. Peterjohn & Correll (1984) found 

that 19 m of riparian forests removed up to 90% of the 

particulate materials moving overland from agricultural 

areas. Similarly, Robinson, Ghaffarzadeh & 

Cruse (1996) showed that the initial 3 m of riparian 

forests removed more than 70% of sediment run-off to 

Iowa streams. 

Among site variability in chlorophyll a and epilithic 

standing crop was also related to in-stream physicochemical 

changes induced by land-cover patterns 

within riparian corridors. Chlorophyll a was closely 

related to thermal regimes in URRB streams, probably 

reflecting the influence of both stream temperature 

and light availability on benthic algae. Several studies 

have demonstrated a positive relationship-between 

stream temperature arid algal growth (Bothwell, 1988; 

Duncan &-Biinn, 1989; Suzuki & Takahashi, 1995) and 

others have attributed greater algal biomass in forested 

regions to local increases in light availability 

(Lowe, Golladay & Webster, 1986; Hill & Harvey, 

1990; Quinn et al, 1997). Interestingly, while many 

studies have linked algal abundance and nutrient 

availability (Fairchild, Lowe & Richardson, 1985; 

Grimm & Fisher, 1986; Biggs, 1995), variability in 

algal biomass in this study was not related to 

in-stream concentrations of TIN or SRP. However, 

neither TIN nor SRP were low enough at our study 

sites to be considered limiting (Grimm & Fisher, 1986; 

Lohman, Jones & Baysinger-Daniel, 1991). The interplay 

between thermal regime and nutrient availability 

was demonstrated by Bothwell (1988); in the absence 

of nutrient limitation, stream temperature explained 

90% of the annual variability in benthic algal growth. 

Changes in algal cover among sites had a strong 

influence on the benthos, as macroinvertebrate density 

was highest at sites with the highest algal biomass 

and biofUm standing stocks. This relationship is most 

likely driven by differences in chironomid abundance, 

which ranged in two orders of magnitude among 

sites. Many studies have indicated that invertebrate 

density and production may increase with greater 

algal biomass (e.g. Dudley, Cooper & Hemphill, 1986; 

Behmer & Hawkins, 1986; Richards & Minshall, 1988; 

Death & Winterbourn, 1995). Furthermore, studies in 

impacted stream ecosystems (mostly agricultural) 

© 2001 Blackwell Science Ltd, Freshwater biology, 46,1409-1424 


have documented high macroinvertebrate density, 

often associated with numerical dominance by environmentally 

tolerant taxa (Lenat & Crawford, 1994; 

Harding & Winterbourn, 1995; Quinn et al, 1997). 

High density at some sites in the URRB may also be 

related to the presence of filamentous algae. Dudley, 

. Hemphill & Cooper (1986) suggested that the abundance 

of Cladophora sp. might influence invertebrate 

density directly as a food source or by accumulating 

other food resources (e.g. detritus, smaller epiphytes), 

or indirectly by increasing habitat availability. In our 

study, highest algal standing crops, and macroinvertebrate 

density were measured at sites 8 and 9, where 

the epilithon was commonly dominated by filamentous 

green algae. 

The use of rank-abundance curves allowed us 

statistically to assess differences in macroinvertebrate 

assemblage structure among sites. We identified 

three groups of streams that differed in the 

number and relative proportion of benthic taxa. Sites 

""with low diversity and high dominance had the 

steepest rank-abundance slopes (sites 7 and 8) and 

were characterized by large numbers of only a few 

chironomid taxa, particularly members of the Orthocladius/Cricocladius 

group. The group with intermediate 

rank-abundance slopes (sites 4, 5 and 9) had 

either slightly higher overall diversity, in conjunction 

with high dominance by Orthocladius/'Cricocladius 

chironomids (site 9), or had relatively diverse 

chironomid assemblages (sites 4 and 5). The group 

with rank-abundance slopes approaching zero had 

the most diverse macroinvertebrate assemblages, 

including a greater abundance of more sensitive 

taxa (e.g. EPT taxa), and frequently more than 10 

chironomid taxa. As was the case with macroinvertebrate 

density, rank-abundance slopes increased 

among sites with algal biomass, probably reflecting 

the numerical dominance of Orthodadius/Cricocladius 

chironomids at sites with the highest algal cover 

(e.g. sites 7 and 8). 

Other macroinvertebrate indices corresponded well 

to the three groups that emerged from the comparison 

of rank-abundance slopes, suggesting these curves 

adequately described assemblage structure in URRB 

streams. In addition, results from multiple regression 

analyses indicated that variation in index values 

among sites was most closely related to the thermal 

regimes, with diversity, evenness and EPT taxa 

richness being lowest at sites with the highest


maximum stream temperature. Results from these 

analyses should be interpreted with some caution, 

however (see MacNally, 2000). Although each multiple 

regression incorporated only maximum stream 

temperature into the model, it is probable that other 

instream features (e.g. substratum size, flow regime, 

etc.) interact with the thermal regime to generate the 

habitat template (sensu Southwood, 1977; Poff & 

Ward, 1990) upon which macroinvertebrate assemblages 

are structured. 

The influence of temperature on the life history and 

ecology of aquatic insects is well documented (Vannote 

& Sweeney, 1980; Ward & Stanford, 1982; 

Sweeney & Vannote, 1986; Quinn et al., 1994). Ward 

& Stanford (1982) suggested that large diel fluctuations 

in stream temperature might lead to increased 

macroinvertebrate diversity by generating acceptable 

thermal conditions, and the potential for niche segregation 

among a wide range of benthic-taxa. In the 

current study, this relationship between thermal 

regime and diversity may not hold if maximum 

-stream temperatures become too high, especially for 

thermally sensitive taxa such as many stoneflies 

(Vannote & Sweeny, 1980; Sweeney, Vannote & 

Dodds, 1986; Quinn et al, 1994). Sweeney (1993) 

suggested that changes in temperature of 3-5 °C in 

Piedmont streams lacking riparian cover is sufficient 

to deleteriously alter larval recruitment and growth 

for many mayfly taxa. In addition to this, reduced 

macroinvertebrate diversity has been attributed to 

high maximum temperatures in both large regulated 

rivers (Fraley, 1979) and New Zealand pasture 

streams (Quinn & Hickey, 1990; Quinn et al, 1997; 

Storey & Cowley, 1997). In the URRB, both mean and 

maximum temperature in streams draining forested 

catchments (sites 1-3) were ~3-6 °C lower than 

streams draining catchments with current land use 

activities (sites 4-9). Moreover, sites 1-3 also had the 

most diverse and even macroinvertebrate assemblages 

among streams in this study. 

Macroinvertebrate diversity decreased among 

catchments with the percentage of non-forested land, 

although only when appropriate spatial scales were 

used in analyses. Several studies comparing macroinvertebrate 

assemblages among basins characterized 

by different land-use practices (e.g. native forest 

versus pasture) or parent geology have documented 

predictive ability at the catchment-scale (Lenat & 

Crawford, 1994; Harding & Winterbourn, 1995; 

Richards et al, 1996; Quinn et al, 1997). However, in 

our study, the relationship between land-cover and 

macro-invertebrate assemblage structure was strongest 

at the 200 m sub-corridor scale. This suggests that 

changes induced by local, near-stream development 

are sufficient to alter community structure, regardless 

of land-cover patterns found further upstream. For 

example, the catchment of site 5 was over 90% 

forested when classified at the catchment scale, yet 

the first 200 m of riparian corridor upstream of the 

study reach was classified as ~25% non-forested as a 

result of recent (~5-15 year) residential development. 

Assemblage structure at site 5 had low taxon richness 

(40 taxa), and EFT taxa richness (15 taxa), suggesting 

that local land-cover patterns had a strong influence 

on habitat quality. Similarly, studies investigating the 

importance of road construction (Lenat et al, 1981) 

and run-off from agricultural areas (Lemly, 1982) have 

documented the influence of local, streamside development 

on macroinvertebrate assemblages, including 

shifts in numeric dominance to intolerant taxa like 

chironomids. Sponseller & Benfield (2001) found that 

riparian land-cover within 1 km of the study sites was 

the strongest landscape predictor for leaf breakdown 

rate in URRB streams. Current results suggest that 

community structure may be more sensitive to local 

land-use disturbances than ecosystem processes that 

incorporate both biotic and abiotic components, which 

appear to be organized at broader spatial scales. This 

supports the idea that functional and taxonomic 

responses to disturbance do not necessarily correspond 

to one another (e.g. Wallace, Vogel & Cuffney, 

1986). 

The spatial relationship between land-cover and 

macroinvertebrate indices also suggests that local, 

upstream patches of riparian forest may have an 

ameliorative effect on macroinvertebrate assemblages. 

For example, the stream at site 6 drains a catchment 

subject to a mixture of land-use practices (both 

agriculture and residential), yet several hundred 

metres of riparian corridor remain forested upstream 

of the sampling site. The macroinvertebrate assemblage 

at site 6.was fairly diverse (51 taxa), and analysis 

of rank-abundance curves grouped this stream with 

those completely lacking urban or agricultural development. 

Storey & Cowley (1997) compared macroinvertebrate 

assemblages in upstream pasture reaches 

with downstream sites, after streams ran through 

approximately 600 m of native riparian forest. They 

© 2001 Blackwell Science Ltd, freshwater Biology, 46,1409-1424


Close M.E. & Davies-Colley R.J. (1990) Baseflow chemistry 

in New Zealand rivers 2. Influence of environmental 

factors. New Zealand Journal of Marine and 

Freshwater Research, 24,343-356. 

Death R.G. & Winterbourn M.J. (1995) Diversity patterns 

in stream benthic invertebrate communities: the influence 

of habitat stability. Ecology, 76,1446-1460. . 

Dudley T.L., Cooper S.D. & Hemphill N. (1986) Effects of 

macroalgae on a stream invertebrate community. 

Journal of the North American Benthological Society, 5, 

93-106. 

Duncan S.W. & Blinn D.W. (1989) Importance of physical 

variables on the seasonal dynamics of epilithic algae in 

a highly shaded canyon stream. Journal ofPhycology, 25, 

455-461. 

Epler J.H. (1995) Identification Manual for the Larval 

Chironomidae (Diptera) of Florida. Revised edition. Florida 

Department of Environmental Protection, Tallahassee, 

FL. 

Fairchild G.W., Lowe R.L. & Richardson W.B. (1985) 

Algal periphyton growth on nutrientTdiffusing substrates: 

an in situ bioassay. Ecology,.€6, 465-472. ___,, 

Fraley J.J. (1979) Effects of elevated stream temperatures 

- below a shallow reservoir on a cold water macroinvertebrate 

fauna. In: The Ecology of Regulated Streams 

(Eds J.V. Ward & J.A. Stanford), pp. 257-272. Plenum 

Press, New York. 

Galli J. (1991) Thermal Impacts Associated with Urbanization 

and Stormwater Management, Best Management Practices. 

Metropolitan Washington Council of Governments. Maryland 

Department of Environment, Washington, DC, 

188 pp. 

Gore J.A. (1996) Discharge measurements and streamflow 

analysis. In: Methods in Stream Ecology (Eds 

F.R. Hauer & G.A. Lamberti), pp. 53-74. Academic 

Press, San Diego, CA. 

Gregory S.V., Swanson F.J., Mckee W.A. & Cummins 

K.W. (1991) An ecosystem perspective of riparian 

zones. Bioscience, 41, 540-551. 

Grimm N.B. & Fisher S.G. (1986) Nitrogen limitation in a 

Sonoran Desert stream. Journal of the North American 

Benthological Society, 5, 2-15. 

Gurtz E.G. & Wallace J.B. (1984) Substrate-mediated 

response of stream invertebrates to disturbance. Ecology, 

65,1556-1569. 

Harding J.S., Benfield E.F., Bolstad P.V., Helfman G.S. & 

Jones E.B.D. (1998) Stream biodiversity: the ghost of 

land use past. Proceedings of the National Academy of 

Science, 95,14843-14847. 

Harding J.S. & Winterbourn M.J. (1995) Effects of 

contrasting land use on physico-chemical conditions 

and benthic assemblages of streams in a Canterbury 

(South Island, New Zealand) river system. New 

Zealand Journal of Marine and Freshwater Research, 29, 

479-192. 

Hawkins C.P., Murphy M.L. & Anderson N.H. (1982) 

The effects of canopy, substrate composition, and 

gradient on the structure of macroinvertebrate communities 

in Cascade Range streams of Oregon. Ecology, 

63,1840-1856. 

Hill W.R. & Harvey B.C. (1990) Periphyton responses to 

higher trophic levels and light in a shaded stream. 

Canadian Journal of Fisheries and Aquatic Science, 47, 

2307-2314. 

Hunsaker C.T. & Levine D.A. (1995) Hierarchical approaches 

to the study of water quality in rivers. Bioscience, 

45,193-203. 

Johnson L.B., Richards C, Host G. & Arthur J.W. (1997) 

Landscape influences on water chemistry in Midwest 

stream ecosystems. Freshwater Biology, 37,193-208. 

Lemly D. (1982) Modification of benthic insect communities 

in polluted streams: combined effects of sedimentation 

and nutrient enrichment. Hydrobiologia, 87, 

/229-24S. 

Lenat D.R. & Crawford J.K. (1994) Effects of land use on 

water quality and aquatic biota of three North Carolina 

Piedmont streams. Hydrobiologia, 294,185-199. 

Lenat D.R., Penrose D.L. & Eagleson K.W. (1981) Variable 

effects of sediment addition on stream benthos. 

Hydrobiologia, 79,187-199. 

Lohman K., Jones R.K. & Baysinger-Daniel C. (1991) 

Experimental evidence for nitrogen limitation in a 

northern Ozark stream. Journal of the North American 

Benthological Society, 10,14-23. 

Lowe R.L., Golloday S.W. & Webster J.R. (1986) Periphyton 

response to nutrient manipulation in streams 

draining clearcut and forested watersheds. Journal of 

the North American Benthological Society, 5,221-229. 

MacNally R. (2000) Regression and model building in 

conservation biology, biogeography and ecology: The 

distinction between - and reconciliation of - 'predictive' 

and 'explanatory' models. Biodiversity and Conservation, 

9, 655-671. 

Marsh-Mathews E. & Mathews W.J. (2000) Spatial variation 

in relative abundance of a widespread, numerically 

dominant fish species and its effect on fish 

assemblage structure. Oecologia, 125,283-292. 

Merritt R.W. & Cummins K.W. (1996) An Introduction to 

the Aquatic Insects of North America, 3rd edn. Kendall/ 

Hunt Publishing Co., Dubuque, Iowa. 

Morton D.D. (1998) Land Cover of Virginia from Landsat 

Thematic Mapper Images. Master's Thesis. Virginia 

Polytechnic Institute and State University, Blacksburg, 

VA. 

Murphy J. & Riley J.P. (1962) Determination of phosphate 

in natural waters. Analytica Chimica Acta, 27,31-36. 


Omernik J.M. (1977) Nonpoint source - stream nutrient 

level relationships: a nationwide study. US EPA - 600/ 

3-77-105; Corvallis, Oregon. 

Peterjohn W.T. & Correll D.L. (1984) Nutrient dynamics 

in an agricultural watershed: observations on the role 

of a riparian forest. Ecology, 65,1466-1475. 

Pielou B.C. (1969) An Introduction to Mathematical Ecology.- 

Wiley, New York. 

Poff N.L., Allan J.D., Bain M.B., Karr J.R., Prestegaard 

K.L., Richter B.R., Sparks R.E. & Stromberg J.C. (1997) 

The natural flow regime. Bioscience, 47, 769-784. 

Poff N.L. & Ward J.V. (1990) Physical habitat template of 

lotic systems: recovery in the context of historical 

pattern of spatiotemporal heterogeneity. Environmental 

Management, 14, 629-645. 

Quinn J.M., Cooper A.B., Davies-Colley R.J., Rutherford 

J.C. & Williamson R.B. (1997) Land use effects on 

habitat, water quality, periphyton, and benthic invertebrates 

in Waikato, New Zealand hill country streams. 

New Zealand Journal of Marine and Freshwater Research, 

31,569-577. ' /•'*" 

Quinn J.M. & Rickey C.W. (1990) Characterization and 

classification of benthic invertebrate communities in 88 

New Zealand rivers in relation to environmental 

factors. New Zealand Journal of Marine and Freshwater 

Research, 24,387-409. 

Quinn J.M., Steele G.L., Hickey C.W. & Vickers M.L. 

(1994) Upper thermal tolerances of twelve common 

New Zealand stream invertebrate species. New Zealand 

Journal of Marine and Freshwater Research, 28,391-397. 

Richards C, Haro R.J., Johnson L.B. & Host G.E. (1997) 

Catchment and reach-scale properties as indicators of 

macroinvertebrate species traits. Freshwater Biology, 37, 

219-230. 

Richards C., Johnson L.B. & Host G.E. (1996) Landscapescale 

influences on stream habitats and biota. Canadian 

Journal of Fisheries and Aquatic Sciences, 53, 295-311. 

Richards C. & Minshall G.W. (1988) The influence of 

periphyton abundance on Baetis bicaudatus distribution 

and colonization in a small stream. Journal of the North 

American Benthobgical Society, 7, 77-86. 

Robinson C.A., Ghaffarzadeh M. & Cruse R.M. (1996) 

Vegetative filter strip effects on sediment concentration 

in cropland runoff. Journal of Soil and Water Conservation, 

50, 227-230. 

Rutherford J.C., Blackett 5., Blackett C., Saito L. & Davies- 

Colley R.J. (1997) Predicting the effects of shade on 

water temperature in small streams. New Zealand 

Journal of Marine and Freshwater Research, 31,707-721. 

SAS Institute (1998) Version 7. Gary, NC. 

Soloranzo L. (1969) Determination of ammonium in 

natural waters by the phenolhypochlorite method. 

Limnology and Oceanography, 14,799-801. 

© 2001 BlackweU Science Ltd, Freshwater Biology, 46,1409-1424 


Southern Appalachian Man and the Biosphere (SAMAB) 

(1996) The Southern Appalachian assessment Summary 

Report: Report 1 of 5. US Department of Agriculture, 

Forest Service, Southern Region, Atlanta. 

Southwood T.R.E. (1977) Habitat, the templet for ecological 

strategies? Journal of Animal Ecology, 46,337-365. 

Sponseller R.A. & Benfield E.F. (2001) Influences on land 

use on leaf breakdown in southern Appalachian 

headwater streams: a multiple scale analysis. Journal 

of the North American Benthological Society, 20,44-59. 

Steinman A.D. & Lamberti G.A. (1996) Biomass and 

pigments of benthic algae. In: Methods in Stream Ecology 

(Eds F.R. Hauer & G.A. Lamberti), pp. 295-314. 

Academic Press, San Diego, CA. 

Stewart K.W. & Stark B.P. (1993) Nymphs of North 

American Stonefly Genera (Plecoptera). University of 

North Texas Press, Denton, Texas. 

Storey R.G. & Cowley D.R. (1997) Recovery of three New 

Zealand rural streams as they pass through native 

forest remnants. Hydrobiologia, 353, 63-76. 

Suzuki Y. & Takahashi M. (1995) Growth resonses of 

, • several diatoms species from various environments to 

temperature. Journal ofPhycobgy, 31, 880-888. 

Swank W.T., Swift L.W. & Douglass J.E. (1988) Streamflow 

changes associated with forest cutting, species 

conversions, and natural disturbances. In: Ecological 

Studies 66. Forest Hydrology and Ecology at Coweeta (Eds 

W.T. Swank & D.A. Crossely), pp. 297-312. Springer- 

Verlag, New York, NY. 

Sweeney B.W. (1993) Effects of streamside vegetation on 

macroinvertebrate communities of White Clay Creek 

in eastern North America. Proceedings of the Academy of 

Natural Sciences of Philadelphia, 144,291-340. 

Sweeney B.W. & Vannote R.L. (1986) Growth and 

production of a stream stonefly: influences of diet 

and temperature. Ecology, 67,1396-1410. 

Sweeney B.W., Vannote R.L. & Dodds P.J. (1986) The 

relative importance of temperature and diet to larval 

development and adult size of the winter stonefly, 

Soyedma carolinensis (Plecoptera: Nemouridae). Freshwater 

Biology, 16, 39-48. 

Vannote R.L. & Sweeney B.W. (1980) Geographic analysis 

of thermal equilibria: a conceptual model for 

evaluating the effect of natural and modified thermal 

regimes on aquatic insect communities. American 

Naturalist, 115, 667-695. 

Wallace J.B., Grubaugh J.W. & Whiles M.R. (1996) Biotic 

indices and stream ecosystem processes: results from an 

experimental study. Ecological Applications, 6,140-151. 

Wallace J.B., Vogel D.S. & Cuffney T.F. (1986) Recovery 

of a headwater stream from an insecticide-induced 

community disturbance. Journal of the North American 

Benthological Society, 5,115-126.


Waller J.O. (1976) Geohydrology of the Upper Roanoke River 

Basin, Virginia. Virginia State Water Control Board - 

Planning Bulletin 302. Bureau of Water Control Management, 

Richmond, Virginia, 148 p. 

Ward J.V. & Stanford J.A. (1982) Thermal response in the 

evolutionary ecology of aquatic insects. AnnwlReview 

of Entomology, 27,97-117. 

Waters T.F. (1995) Sediment in Streams: Sources, Biological 

Effects and Control. American Fisheries Society Monograph 

7. American Fisheries Society, Bethesda, Maryland. 

Wear D.N. & Bolstad P. (1998) Land-use changes in 

southern appalachian landscapes: spatial analysis and 

forecast evaluation. Ecosystems, \, 575-594. 

Webster J.R., Gurtz M.E., Hains J.J., Meyer J.L., Swank 

W.T., Waide J.B. & Wallace J.B. (1983) Stability of 

stream ecosystems. In: Stream Ecology (Eds J.B. Barnes 

& G.W. Minshall), pp. 355-394. Plenum Press, New 

York. 

Wetzel R.G. & Likens G.E. (1991) Limnokgical Analyses, 

2nd edn. Springer-Verlag, New York, NY: 

Wiggins G.B. (1996) larvae of the North American Caddisfly 

Genera (Trichoptera). University of Toronto Press Inc, 

Toronto, Canada. 

Wolman M.G. (1954) A new method of sampling coarse 

riverbed. Transactions of the American Geophysical Union, 

35, 951-956. 

Wood E.D., Armstrong F.A.J. & Richards F.A. (1967) 

Determination of nitrate in seawater by cadmiumcopper 

reduction to nitrate. Journal of the Marine Biology 

Association of the United Kingdom, 47, 23-31. 

Yarnell S.L. (1998) The Southern Appalachians: a History of 

the Landscape. General Technical Report SRS-18. U.S. 

Department of Agriculture, Forest Service, Southern 

Research Station, Asheville, NC, 45 pp. 

Zar J.H. (1996) Biostatistical Analysis, 3rd edn. Prentice 

Hall Inc., Upper Saddle River, NJ. 

(Manuscript accepted 5 January 2001)

Sponseller, R.A., E.F. Benfield, and H.M. Valett. 2001

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