Daren M. Carlisle

GAGES: A stream gage database for evaluating natural and altered flow conditions in the conterminous United States

Stream flow is a controlling element in the ecology of rivers and streams. Knowledge of the natural flow regime facilitates the assessment of whether specific hydrologic attributes have been altered by humans in a particular stream and the establishment of specific goals for stream-flow restoration. Because most streams are ungaged or have been altered by human influences, characterizing the natural flow regime is often only possible by estimating flow characteristics based on nearby stream gages of reference quality, i.e., gaged locations that are least disturbed by human influences. The ability to evaluate natural stream flow, that which is not altered by human activities, would be enhanced by the existence of a nationally consistent and up-to-date database of gages in relatively undisturbed watersheds. As part of a national effort to characterize stream-flow effects on ecological condition, data for 6785 U.S. Geological Survey (USGS) stream gages and their upstream watersheds were compiled. The sites comprise all USGS stream gages in the conterminous United States with at least 20 years of complete-year flow record from 1950–2007, and for which watershed boundaries could reliably be delineated (median size = 578 km2). Several hundred watershed and site characteristics were calculated or compiled from national data sources, including environmental features (e.g., climate, geology, soils, topography) and anthropogenic influences (e.g., land use, roads, presence of dams, or canals). In addition, watersheds were assessed for their reference quality within nine broad regions for use in studies intended to characterize stream flows under conditions minimally influenced by human activities. Three primary criteria were used to assess reference quality: (1) a quantitative index of anthropogenic modification within the watershed based on GIS-derived variables, (2) visual inspection of every stream gage and drainage basin from recent high-resolution imagery and topographic maps, and (3) information about man-made influences from USGS Annual Water Data Reports. From the set of 6785 sites, we identified 1512 as reference-quality stream gages. All data derived for these watersheds as well as the reference condition evaluation are provided as an online data set termed GAGES (geospatial attributes of gages for evaluating stream flow). The complete data sets corresponding to abstracts published in the Data Papers section of the journal are published electronically in Ecological Archives at 〈http://esapubs.org/archive〉. (The accession number for each Data Paper is given directly beneath the title.)

Alteration of streamflow magnitudes and potential ecological consequences: a multiregional assessment

Human impacts on watershed hydrology are widespread in the US, but the prevalence and severity of stream-flow alteration and its potential ecological consequences have not been quantified on a national scale. We assessed streamflow alteration at 2888 streamflow monitoring sites throughout the conterminous US. The magnitudes of mean annual (1980–2007) minimum and maximum streamflows were found to have been altered in 86% of assessed streams. The occurrence, type, and severity of streamflow alteration differed markedly between arid and wet climates. Biological assessments conducted on a subset of these streams showed that, relative to eight chemical and physical covariates, diminished flow magnitudes were the primary predictors of biological integrity for fish and macroinvertebrate communities. In addition, the likelihood of biological impairment doubled with increasing severity of diminished streamflows. Among streams with diminished flow magnitudes, increasingly common fish and macroinvertebrate taxa poss...

Biological assessments of Appalachian streams based on predictive models for fish, macroinvertebrate, and diatom assemblages

Abstract We developed empirical models for fish, macroinvertebrate, and diatom assemblages to assess the biological condition of 268 streams sampled from 1993 to 2002 in 7 major river basins in the Appalachian region of the USA. These models estimate the expected taxonomic composition at each site based on observed variation in taxonomic composition at reference sites. The index, O/E, is the ratio of the number of predicted taxa that were observed (O) to that expected (E) to occur at a site and is a measure of taxonomic completeness. We compared how O/E for each assemblage varied among major landuse settings and whether impaired assemblages were associated with particular physicochemical conditions. We also examined concordance among assemblages in their response to stress. Biological, chemical, and physical data were collected following consistent protocols. We used land-cover criteria, published data, and topographic maps to classify sites by major landuse setting. Fish, macroinvertebrate, and diatom assemblages had been sampled at 73, 108, and 52, respectively, of the least disturbed sites used to establish reference conditions. The models accounted for a substantial portion of the natural variation in taxonomic composition across sites that was associated with biogeographic, climatic, and basin-scale factors and generally were unbiased across the range of environmental gradients observed in the region. Assessments at nonreference sites showed that impairment of fish and macroinvertebrate assemblages was most strongly associated with agriculture and urban land uses, whereas impairment of diatom assemblages was most strongly associated with mining in the basin. Concordance in assessments among assemblages was not strong. Assessments based on 2 assemblages differed in 28 to 57% of cases, and assessments were never concordant for cases where all 3 assemblages were sampled. Furthermore, only ½ of these cases would have been assessed as ecologically impaired had only 1 assemblage been sampled. Differences between observed and predicted frequencies of occurrence for individual taxa were generally consistent with known tolerances to environmental stressors and might aid in identifying causes of biological impairment.

Developing linkages between species traits and multiscaled environmental variation to explore vulnerability of stream benthic communities to climate change

Abstract Forecasting responses of benthic community structure and function to anthropogenic climate change is an emerging scientific challenge. Characterizing benthic species by biological attributes (traits) that are responsive to temperature and streamflow conditions can support a mechanistic approach for assessing the potential ecological responses to climate change. However, nonclimatic environmental factors also structure benthic communities and may mitigate transient climatic conditions, and these must be considered in evaluating potential impacts of climate change. Here we used macroinvertebrate and environmental data for 279 reference-quality sites spanning 12 states in the western US. For each sampling location, we described 45 environmental variables that spanned reach to catchment scales and that represented contemporary climate drivers, hydrologic metrics, and nonclimatic habitat features, as well as purely spatial metrics. We described benthic community composition at each site in terms of 7 species traits, including those considered sensitive to temperature increases and streamflow changes. All combined environmental variables explained 67% of the total trait variation across the sites, and catchment-scale climatic and hydrologic variables independently accounted for 19%. Sites were clustered into 3 community types based on trait composition, and a classification-tree analysis confirmed that climatic and hydrologic variables were important in partitioning these groups. Sensitivity of benthic communities to projected climate change was assessed by quantifying the proportion of taxa at sites having the traits of either cold stenothermy or obligate rheophily. Regression-tree analysis showed that temperature and hydrologic variables mostly accounted for the differences in proportion of sensitivity traits across the sites. We examined the vulnerability of sites to climate change by superimposing regional-scale projections of late-21st-century temperature and runoff change on the spatial distribution of temperature- and runoff-sensitive assemblages. Sites with high proportions of cold stenotherms and obligate rheophiles occur throughout the western US, but the degree of temperature and runoff change is projected to be greatest for reference sites in the Upper Colorado River and Great Basin. Thus, our results suggest that traits-based sensitivity coupled with intraregional variation in projected changes in temperature and runoff will cause reference sites in the western US to be differentially vulnerable to future climate change.

Growth and secondary production of aquatic insects along a gradient of Zn contamination in Rocky Mountain streams

Secondary production estimates from several Rocky Mountain streams were used to test hypotheses about the effects of chronic metal contamination on insect populations and ecosystem processes. Quantitative samples of chemistry, habitat, and benthic insects were collected monthly during the ice-free period (May–November) from five 2nd- to 3rd-order streams that varied primarily in Zn contamination. Secondary production was estimated for the 19 dominant taxa using increment-summation, size-frequency, and P/B methods. Uncertainty was estimated by bootstrapping estimates of mean abundance, biomass, and cohort production intervals. Secondary production of metal-sensitive Heptageniidae (Rhithrogena robusta, Cinygmula spp., and Epeorus longimanus) was lower in lightly to moderately contaminated streams than in reference streams. Experiments were done to determine whether herbivore growth was influenced by food quality in contaminated streams. Growth estimates from field and microcosm experiments revealed that low mayfly production in contaminated streams was caused mostly by reduced population abundances. Production of predatory stoneflies was also lower in contaminated streams than reference streams. Estimates of the trophic basis of production revealed that, although the relative contribution to community production from various food sources was similar among streams, total production attributable to algae and animal prey declined in contaminated streams. Much of the reduction in herbivory in contaminated streams was the result of lower production of heptageniids, especially R. robusta. Assemblage and taxon-specific estimates of secondary production were sensitive to variation in metal contamination and indicated that relatively low metal concentrations may have ecosystem-wide consequences for energy flow.

Stream biomonitoring using macroinvertebrates around the globe: a comparison of large-scale programs

Water quality agencies and scientists are increasingly adopting standardized sampling methodologies because of the challenges associated with interpreting data derived from dissimilar protocols. Here, we compare 13 protocols for monitoring streams from different regions and countries around the globe. Despite the spatially diverse range of countries assessed, many aspects of bioassessment structure and protocols were similar, thereby providing evidence of key characteristics that might be incorporated in a global sampling methodology. Similarities were found regarding sampler type, mesh size, sampling period, subsampling methods, and taxonomic resolution. Consistent field and laboratory methods are essential for merging data sets collected by multiple institutions to enable large-scale comparisons. We discuss the similarities and differences among protocols and present current trends and future recommendations for monitoring programs, especially for regions where large-scale protocols do not yet exist. We summarize the current state in one of these regions, Latin America, and comment on the possible development path for these techniques in this region. We conclude that several aspects of stream biomonitoring need additional performance evaluation (accuracy, precision, discriminatory power, relative costs), particularly when comparing targeted habitat (only the commonest habitat type) versus site-wide sampling (multiple habitat types), appropriate levels of sampling and processing effort, and standardized indicators to resolve dissimilarities among biomonitoring methods. Global issues such as climate change are creating an environment where there is an increasing need to have universally consistent data collection, processing and storage to enable large-scale trend analysis. Biomonitoring programs following standardized methods could aid international data sharing and interpretation.

Predicting the biological condition of streams: use of geospatial indicators of natural and anthropogenic characteristics of watersheds

We developed and evaluated empirical models to predict biological condition of wadeable streams in a large portion of the eastern USA, with the ultimate goal of prediction for unsampled basins. Previous work had classified (i.e., altered vs. unaltered) the biological condition of 920 streams based on a biological assessment of macroinvertebrate assemblages. Predictor variables were limited to widely available geospatial data, which included land cover, topography, climate, soils, societal infrastructure, and potential hydrologic modification. We compared the accuracy of predictions of biological condition class based on models with continuous and binary responses. We also evaluated the relative importance of specific groups and individual predictor variables, as well as the relationships between the most important predictors and biological condition. Prediction accuracy and the relative importance of predictor variables were different for two subregions for which models were created. Predictive accuracy in the highlands region improved by including predictors that represented both natural and human activities. Riparian land cover and road-stream intersections were the most important predictors. In contrast, predictive accuracy in the lowlands region was best for models limited to predictors representing natural factors, including basin topography and soil properties. Partial dependence plots revealed complex and nonlinear relationships between specific predictors and the probability of biological alteration. We demonstrate a potential application of the model by predicting biological condition in 552 unsampled basins across an ecoregion in southeastern Wisconsin (USA). Estimates of the likelihood of biological condition of unsampled streams could be a valuable tool for screening large numbers of basins to focus targeted monitoring of potentially unaltered or altered stream segments.

Predicting thermal reference conditions for USA streams and rivers

Abstract. Temperature is a primary driver of the structure and function of stream ecosystems. However, the lack of stream temperature (ST) data for the vast majority of streams and rivers severely compromises our ability to describe patterns of thermal variation among streams, test hypotheses regarding the effects of temperature on macroecological patterns, and assess the effects of altered STs on ecological resources. Our goal was to develop empirical models that could: 1) quantify the effects of stream and watershed alteration (SWA) on STs, and 2) accurately and precisely predict natural (i.e., reference condition) STs in conterminous USA streams and rivers. We modeled 3 ecologically important elements of the thermal regime: mean summer, mean winter, and mean annual ST. To build reference-condition models (RCMs), we used daily mean ST data obtained from several thousand US Geological Survey temperature sites distributed across the conterminous USA and iteratively modeled ST with Random Forests to identify sites in reference condition. We first created a set of dirty models (DMs) that related STs to both natural factors (e.g., climate, watershed area, topography) and measures of SWA, i.e., reservoirs, urbanization, and agriculture. The 3 models performed well (r2  =  0.84–0.94, residual mean square error [RMSE]  =  1.2–2.0°C). For each DM, we used partial dependence plots to identify SWA thresholds below which response in ST was minimal. We then used data from only the sites with upstream SWA below these thresholds to build RCMs with only natural factors as predictors (r2  =  0.87–0.95, RMSE  =  1.1–1.9°C). Use of only reference-quality sites caused RCMs to suffer modest loss of predictor space and spatial coverage, but this loss was associated with parts of ST response curves that were flat and, therefore, not responsive to further variation in predictor space. We then compared predictions made with the RCMs to predictions made with the DMs with SWA set to 0. For most DMs, setting SWAs to 0 resulted in biased estimates of thermal reference condition.

Predictive Models for Fish Assemblages in Eastern U.S. Streams: Implications for Assessing Biodiversity

Abstract Management and conservation of aquatic systems require the ability to assess biological conditions and identify changes in biodiversity. Predictive models for fish assemblages were constructed to assess biological condition and changes in biodiversity for streams sampled in the eastern United States as part of the U.S. Geological Surveys National Water Quality Assessment Program. Separate predictive models were developed for northern and southern regions. Reference sites were designated using land cover and local professional judgment. Taxonomic completeness was quantified based on the ratio of the number of observed native fish species expected to occur to the number of expected native fish species. Models for both regions accurately predicted fish species composition at reference sites with relatively high precision and low bias. In general, species that occurred less frequently than expected (decreasers) tended to prefer riffle areas and larger substrates, such as gravel and cobble, whereas i...

River flow changes related to land and water management practices across the conterminous United States.

The effects of land and water management practices (LWMP)--such as the construction of dams and roads--on river flows typically have been studied at the scale of single river watersheds or for a single type of LWMP. For the most part, assessments of the relative effects of multiple LWMP within many river watersheds across regional and national scales have been lacking. This study assesses flow alteration--quantified as deviation of several flow metrics from natural conditions--at 4196 gauged rivers affected by a variety of LWMP across the conterminous United States. The most widespread causes of flow changes among the LWMP considered were road density and dams. Agricultural development and wastewater discharges also were associated with flow changes in some regions. Dams generally reduced most attributes of flow, whereas road density, agriculture and wastewater discharges tended to be associated with increased flows compared to their natural condition.