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Thomas F. Cuffney

Publications and source records attributed to Thomas F. Cuffney.

At least 19 recordsLinked to original sources
USGS2023

Unravelling the influence of landscape alteration from flow alteration on benthic macroinvertebrate assemblage response in the Delaware River Basin

Quantifying the effects of streamflow alteration on assemblage response is central to understanding the role humans play in shaping aquatic environments. These changes represent a level of complexity that impedes developing quantitative links between flow and ecological response because stream hydrology is strongly intertwined with natural and anthropogenic factors. Better management outcomes require disentangling these linkages. Benthic macroinvertebrate data were combined with GIS-derived natural and anthropogenic basin characteristics to identify factors associated with changes in flow processes and assemblage characteristics. Models linking streamflow metrics and macroinvertebrate response at basin and subregion scales were developed using boosted regression tree (BRT) analysis. Basin-scale BRT analyses revealed that links between macroinvertebrate response and flow metrics were often obscured, whereas more homogeneous subregions were better able to discern relations with flow. Urban land cover was the primary factor accounting for changes in flow characteristics. Elevation, land cover, and high flow frequency were the principal variables driving changes in assemblage structure within subregions. Assemblage metrics and traits were equally useful for building response models and were affected similarly by streamflow alteration. Results indicate that response models should be developed based on upland and coastal subregions. However, when defining subregions, care should be taken to maintain data sufficiency. Developing practical flow-protection standards that support a balance between human water requirements and ecological integrity requires models that reduce uncertainty and identify management-relevant drivers. However, effective management often differs by location and models developed at the subregion level may be more applicable to management and stakeholder interests.

Delaware, New Jersey, New York, Pennsylvania↗
USGS2019

South Atlantic Water Science Center Strategic Science Plan: 2019–23

Executive Summary The South Atlantic Water Science Center Strategic Science Planning Team has developed a unified strategic science plan to guide the science vision of the South Atlantic Water Science Center (SAWSC) in response to the merging of the Georgia, North Carolina, and South Carolina Water Science Centers. This plan proposes a path forward to keep SAWSC science activities relevant to the many diverse needs of stakeholders in the South Atlantic region (Georgia, North Carolina, and South Carolina) and considers the hydrologic setting and issues of the region. This plan advises the creation of five working groups to address five priority science topics for the period 2019–23 and beyond. The five priority science topics are (1) Foundational Data, (2) Effects of Land-Use Change, (3) Coastal Plain Science, (4) Water Availability, and (5) Hazards. From the goals laid forth in this plan for each priority science topic, the working groups plan to devise a set of strategic actions and milestones to be achieved by the SAWSC to provide valuable and relevant data, research, and assessments in the South Atlantic region. In this report, the “South Atlantic region” is used to describe the area encompassed by the States of North Carolina, South Carolina, and Georgia.

Open-File Report↗
USGS2018

Trends in water quality of selected streams and reservoirs used for water supply in the Triangle area of North Carolina, 1989–2013

As the population of the Triangle area in central North Carolina increases, the demand for good quality drinking water from streams and lakes within the upper Neuse and upper Cape Fear River Basins also increases. The Triangle area includes Raleigh, Cary, Research Triangle Park, Durham, Chapel Hill, and the surrounding communities. The U.S. Geological Survey examined temporal trends in water quality for 13 stream and 8 reservoir sites in the two basins on the basis of data collected during 1989–2013. Trends were analyzed using a fitted time-series model that accommodated for shifting trends and variations in streamflow at multiple time scales. Seventeen water-quality properties and constituents were evaluated, including specific conductance and major ions, nutrients, and organic carbon. Suspended solids and suspended sediment were examined at stream sites; chlorophyll a and Secchi transparency were examined at lake sites. The investigation identified considerable changes in population, land cover, streamflow, and selected water-quality characteristics in the study area over the 25-year period. Specific conductance and concentrations of calcium, magnesium, potassium, sodium, and chloride tended to increase throughout the study area. Area-wide increases were also observed for organic nitrogen. Trends for other water-quality constituents varied on a more site-specific basis because of local watershed influences such as changes to wastewater-treatment processes and substantial shifts from rural to urban land use. Water quality is influenced by multiple, often confounding factors, and thus may change in a non-uniform manner over time. Long-term monitoring is critical for tracking these trends and ensuring resiliency of water supplies for the future. Results from this study may promote the understanding of water-quality response to a growing population and land-cover changes and can assist water-resource managers in the Triangle area in tracking progress toward water-quality goals.

North Carolina↗
USGS2018

The multiple-comparison trap and the Raven’s paradox—perils of using null hypothesis testing in environmental assessment

Detecting and quantifying environmental thresholds is frequently an important step in understanding ecological responses to environmental stressors. We discuss two statistical issues often encountered in threshold detection and quantification when statistical null hypothesis testing is used as a main analytical tool.The hidden multiple-comparison trap (leading to a much higher risk of a false detection) and Raven’s paradox(rendering a "detection" meaningless) are often obscured when statistical hypothesis testing is used as part of a more elaborate model, especially models based on computer-intensive methods. Using two examples, we show that the hidden multiple-comparison trap can be exposed using computer simulation to estimate the probability of making a false detection; Raven’s paradox can be avoided by clearly stating the null and alternative hypotheses using scientific terms to substantiate that the rejection of the null is equivalent to proving that the alternative of interest is true. The hidden multiple-comparison trap implies that a null hypothesis testing based on a computer-intensive method should be used with caution. The implication of Raven’s paradox re-quires that we focus on providing evidence supporting the proposed hypothesis or model, rather than seeking evidence against the frequently irrelevant null hypothesis. These two problems, and many others related to null hypothesis testing, suggest that statistical hypothesis testing should be used only as a component of the body of evidence, perhaps, as the devil’s advocate.

Environmental Monitoring and Assessment↗
USGS2017

Fish and invertebrate flow-biology relationships to support the determination of ecological flows for North Carolina

A method was developed to characterize fish and invertebrate responses to flow alteration in the state of North Carolina. This method involved using 80th percentile linear quantile regressions to relate six flow metrics to the diversity of riffle-run fish and benthic Ephemeroptera, Plecoptera, and Trichoptera (EPT) richness. All twelve flow-biology relationships were found to be significant, with both benthos and fish showing negative responses to ecodeficits and reductions in flow. The responses of benthic richness to reduced flows were consistent and generally greater than that of fish diversity. However, the riffle-run fish guild showed the greatest reductions in diversity in response to summer ecodeficits. The directional consistency and differential seasonal sensitivities of fish and invertebrates to reductions in flow highlight the need to consider seasonality when managing flows. In addition, all relationships were linear, and therefore do not provide clear thresholds to support ecological flow determinations and flow prescriptions to prevent the degradation of fish and invertebrate communities in North Carolina rivers and streams. A method of setting ecological flows based on the magnitude of change in biological condition that is acceptable to society is explored.

North Carolina↗
USGS2014

Stream macroinvertebrate response models for bioassessment metrics: addressing the issue of spatial scale

We developed independent predictive disturbance models for a full regional data set and four individual ecoregions (Full Region vs. Individual Ecoregion models) to evaluate effects of spatial scale on the assessment of human landscape modification, on predicted response of stream biota, and the effect of other possible confounding factors, such as watershed size and elevation, on model performance. We selected macroinvertebrate sampling sites for model development (n = 591) and validation (n = 467) that met strict screening criteria from four proximal ecoregions in the northeastern U.S.: North Central Appalachians, Ridge and Valley, Northeastern Highlands, and Northern Piedmont. Models were developed using boosted regression tree (BRT) techniques for four macroinvertebrate metrics; results were compared among ecoregions and metrics. Comparing within a region but across the four macroinvertebrate metrics, the average richness of tolerant taxa (RichTOL) had the highest R 2 for BRT models. Across the four metrics, final BRT models had between four and seven explanatory variables and always included a variable related to urbanization (e.g., population density, percent urban, or percent manmade channels), and either a measure of hydrologic runoff (e.g., minimum April, average December, or maximum monthly runoff) and(or) a natural landscape factor (e.g., riparian slope, precipitation, and elevation), or a measure of riparian disturbance. Contrary to our expectations, Full Region models explained nearly as much variance in the macroinvertebrate data as Individual Ecoregion models, and taking into account watershed size or elevation did not appear to improve model performance. As a result, it may be advantageous for bioassessment programs to develop large regional models as a preliminary assessment of overall disturbance conditions as long as the range in natural landscape variability is not excessive.

North Central Appalachians;Northeastern Highlands;↗
USGS2014

Aquatic ecosystems as indicators of status and trends in water quality

This chapter provides an introduction and overview of the use of aquatic ecosystems as indicators of water quality. The monitoring of biological communities (fish, algae, and invertebrates) as a means of assessing water quality conditions is emphasized along with ecotoxicological studies and measures of ecosystem function. Issues related to the design, implementation, and analysis of monitoring programs are reviewed and discussed with the objective of continually improving water quality conditions through adaptive management .

Book chapter↗
USGS2013

A critique of the use of indicator-species scores for identifying thresholds in species responses

Identification of ecological thresholds is important both for theoretical and applied ecology. Recently, Baker and King (2010, King and Baker 2010) proposed a method, threshold indicator analysis (TITAN), to calculate species and community thresholds based on indicator species scores adapted from Dufrêne and Legendre (1997). We tested the ability of TITAN to detect thresholds using models with (broken-stick, disjointed broken-stick, dose-response, step-function, Gaussian) and without (linear) definitive thresholds. TITAN accurately and consistently detected thresholds in step-function models, but not in models characterized by abrupt changes in response slopes or response direction. Threshold detection in TITAN was very sensitive to the distribution of 0 values, which caused TITAN to identify thresholds associated with relatively small differences in the distribution of 0 values while ignoring thresholds associated with large changes in abundance. Threshold identification and tests of statistical significance were based on the same data permutations resulting in inflated estimates of statistical significance. Application of bootstrapping to the split-point problem that underlies TITAN led to underestimates of the confidence intervals of thresholds. Bias in the derivation of the z-scores used to identify TITAN thresholds and skewedness in the distribution of data along the gradient produced TITAN thresholds that were much more similar than the actual thresholds. This tendency may account for the synchronicity of thresholds reported in TITAN analyses. The thresholds identified by TITAN represented disparate characteristics of species responses that, when coupled with the inability of TITAN to identify thresholds accurately and consistently, does not support the aggregation of individual species thresholds into a community threshold.

Freshwater Science↗
USGS2013

Relation of watershed setting and stream nutrient yields at selected sites in central and eastern North Carolina, 1997-2008

Data collected between 1997 and 2008 at 48 stream sites were used to characterize relations between watershed settings and stream nutrient yields throughout central and eastern North Carolina. The focus of the investigation was to identify environmental variables in watersheds that influence nutrient export for supporting the development and prioritization of management strategies for restoring nutrient-impaired streams. Nutrient concentration data and streamflow data compiled for the 1997 to 2008 study period were used to compute stream yields of nitrate, total nitrogen (N), and total phosphorus (P) for each study site. Compiled environmental data (including variables for land cover, hydrologic soil groups, base-flow index, streams, wastewater treatment facilities, and concentrated animal feeding operations) were used to characterize the watershed settings for the study sites. Data for the environmental variables were analyzed in combination with the stream nutrient yields to explore relations based on watershed characteristics and to evaluate whether particular variables were useful indicators of watersheds having relatively higher or lower potential for exporting nutrients. Data evaluations included an examination of median annual nutrient yields based on a watershed land-use classification scheme developed as part of the study. An initial examination of the data indicated that the highest median annual nutrient yields occurred at both agricultural and urban sites, especially for urban sites having large percentages of point-source flow contributions to the streams. The results of statistical testing identified significant differences in annual nutrient yields when sites were analyzed on the basis of watershed land-use category. When statistical differences in median annual yields were noted, the results for nitrate, total N, and total P were similar in that highly urbanized watersheds (greater than 30 percent developed land use) and (or) watersheds with greater than 10 percent point-source flow contributions to streamflow had higher yields relative to undeveloped watersheds (having less than 10 and 15 percent developed and agricultural land uses, respectively) and watersheds with relatively low agricultural land use (between 15 and 30 percent). The statistical tests further indicated that the median annual yields for total P were statistically higher for watersheds with high agricultural land use (greater than 30 percent) compared to the undeveloped watersheds and watersheds with low agricultural land use. The total P yields also were higher for watersheds with low urban land use (between 10 and 30 percent developed land) compared to the undeveloped watersheds. The study data indicate that grouping and examining stream nutrient yields based on the land-use classifications used in this report can be useful for characterizing relations between watershed settings and nutrient yields in streams located throughout central and eastern North Carolina. Compiled study data also were analyzed with four regression tree models as a means of determining which watershed environmental variables or combination of variables result in basins that are likely to have high or low nutrient yields. The regression tree analyses indicated that some of the environmental variables examined in this study were useful for predicting yields of nitrate, total N, and total P. When the median annual nutrient yields for all 48 sites were evaluated as a group (Model 1), annual point-source flow yields had the greatest influence on nitrate and total N yields observed in streams, and annual streamflow yields had the greatest influence on yields of total P. The Model 1 results indicated that watersheds with higher annual point-source flow yields had higher annual yields of nitrate and total N, and watersheds with higher annual streamflow yields had higher annual yields of total P. When sites with high point-source flows (greater than 10 percent of total streamflow) were excluded from the regression tree analyses (Models 2–4), the percentage of forested land in the watersheds was identified as the primary environmental variable influencing stream yields for both total N and total P. Models 2, 3 and 4 did not identify any watershed environmental variables that could adequately explain the observed variability in the nitrate yields among the set of sites examined by each of these models. The results for Models 2, 3, and 4 indicated that watersheds with higher percentages of forested land had lower annual total N and total P yields compared to watersheds with lower percentages of forested land, which had higher median annual total N and total P yields. Additional environmental variables determined to further influence the stream nutrient yields included median annual percentage of point-source flow contributions to the streams, variables of land cover (percentage of forested land, agricultural land, and (or) forested land plus wetlands) in the watershed and (or) in the stream buffer, and drainage area. The regression tree models can serve as a tool for relating differences in select watershed attributes to differences in stream yields of nitrate, total N, and total P, which can provide beneficial information for improving nutrient management in streams throughout North Carolina and for reducing nutrient loads to coastal waters.

North Carolina↗
USGS2012

Comparison of stream invertebrate response models for bioassessment metric

We aggregated invertebrate data from various sources to assemble data for modeling in two ecoregions in Oregon and one in California. Our goal was to compare the performance of models developed using multiple linear regression (MLR) techniques with models developed using three relatively new techniques: classification and regression trees (CART), random forest (RF), and boosted regression trees (BRT). We used tolerance of taxa based on richness (RICHTOL) and ratio of observed to expected taxa (O/E) as response variables and land use/land cover as explanatory variables. Responses were generally linear; therefore, there was little improvement to the MLR models when compared to models using CART and RF. In general, the four modeling techniques (MLR, CART, RF, and BRT) consistently selected the same primary explanatory variables for each region. However, results from the BRT models showed significant improvement over the MLR models for each region; increases in R 2 from 0.09 to 0.20. The O/E metric that was derived from models specifically calibrated for Oregon consistently had lower R 2 values than RICHTOL for the two regions tested. Modeled O/E R 2 values were between 0.06 and 0.10 lower for each of the four modeling methods applied in the Willamette Valley and were between 0.19 and 0.36 points lower for the Blue Mountains. As a result, BRT models may indeed represent a good alternative to MLR for modeling species distribution relative to environmental variables.

California, Oregon↗
USGS2012

Effects of urban development on stream ecosystems in nine metropolitan study areas across the United States

Urban development is an important agent of environmental change in the United States. The urban footprint on the American landscape has expanded during a century and a half of almost continuous development. Eighty percent of Americans now live in metropolitan areas, and the advantages and challenges of living in these developed areas—convenience, congestion, employment, pollution—are part of the day-to-day realities of most Americans. Nowhere are the environmental changes associated with urban development more evident than in urban streams. Contaminants, habitat destruction, and increasing streamflow flashiness resulting from urban development have been associated with the disruption of biological communities, particularly the loss of sensitive aquatic species. Every stream is connected downstream to larger water bodies, including rivers, reservoirs, and ultimately coastal waters. Inputs of chemical contaminants or sediments at any point along the stream can cause degradation downstream with adverse effects on biological communities and on economically valuable resources, such as fisheries and tourism. In response to general concerns about the degradation of urban streams, the U.S. Geological Survey (USGS) conducted a national-scale, scientific investigation of the effects of urban development on stream ecosystems. Nine metropolitan study areas of the United States were selected—Portland, Oregon; Salt Lake City, Utah; Birmingham, Alabama; Atlanta, Georgia; Raleigh, North Carolina; Boston, Massachusetts; Denver, Colorado; Dallas, Texas; and Milwaukee, Wisconsin. The studies were conducted in Salt Lake City, Birmingham, and Boston in 1999–2000; in Atlanta, Raleigh, and Denver in 2002–2003; and in Portland, Dallas, and Milwaukee in 2003–2004. The comprehensive investigation of all nine studies focused on three broad questions of interest to decision makers: What are the primary effects of urban development on stream ecosystems? How do the effects of urban development on stream ecosystems vary regionally across the country? Which urban-related stressors are most closely linked to biological community degradation, and how can multiple stressors be managed to protect stream health as a watershed becomes increasingly urbanized?

Alabama;Colorado;Georgia;Massachusetts;North Carol↗
USGS2012

Linking urbanization to the Biological Condition Gradient (BCG) for stream ecosystems in the Northeastern United States using a Bayesian network approach

Urban development alters important physical, chemical, and biological processes that define urban stream ecosystems. An approach was developed for quantifying the effects of these processes on aquatic biota, and then linking those effects to endpoints that can be used for environmental management. These complex, interacting systems are challenging to model from a scientific standpoint. A desirable model clearly shows the system, simulates the interactions, and ultimately predicts results of management actions. Traditional regression techniques that calculate empirical relations between pairs of environmental factors do not capture the interconnected web of multiple stressors, but urban development effects are not yet understood at the detailed scales required to make mechanistic modeling approaches feasible. Therefore, in contrast to a fully deterministic or fully statistical modeling approach, a Bayesian network model provides a hybrid approach that can be used to represent known general associations between variables while acknowledging uncertainty in predicted outcomes. It does so by quantifying an expert-elicited network of probabilistic relations between variables. Advantages of this modeling approach include (1) flexibility in accommodating many model specifications and information types; (2) efficiency in storing and manipulating complex information, and to parameterize; and (3) transparency in describing the relations using nodes and arrows and in describing uncertainties with discrete probability distributions for each variable. In realization of the aforementioned advantages, a Bayesian network model was constructed to characterize the effect of urban development on aquatic macroinvertebrate stream communities through three simultaneous, interacting ecological pathways affecting stream hydrology, habitat, and water quality across watersheds in the Northeastern United States. This model incorporates both empirical data and expert knowledge to calculate the probabilities of attaining desired aquatic ecosystem conditions under different urban stress levels, environmental conditions, and management options. Ecosystem conditions are characterized in terms of standardized Biological Condition Gradient (BCG) management endpoints. This approach to evaluating urban development-induced perturbations in watersheds integrates statistical and mechanistic perspectives, different information sources, and several ecological processes into a comprehensive description of the system that can be used to support decision making. The completed model can be used to infer which management actions would lead to the highest likelihood of desired BCG tier achievement. For example, if best management practices (BMP) were implemented in a highly urbanized watershed to reduce flashiness to medium levels and specific conductance to low levels, the stream would have a 70-percent chance of achieving BCG Tier 3 or better, relative to a 24-percent achievement likelihood for unmanaged high urban land cover. Results are reported probabilistically to account for modeling uncertainty that is inherent in sources such as natural variability and model simplification error.

Scientific Investigations Report↗
USGS2012

Invertebrate response to changes in streamflow hydraulics in two urban areas in the United States

Stream hydrology is foundational to aquatic ecosystems and has been shown to be a structuring element for fish and invertebrates. The relations among urbanization, hydraulics, and invertebrate communities were investigated by the U.S. Geological Survey, National Water-Quality Assessment Program by using measures of stream hydraulics in two areas of the United States. Specifically, the hypothesis that the effects of urbanization on streamflow and aquatic biota are transferable across geographic regions was tested. Data from sites in Raleigh, North Carolina, and Milwaukee–Green Bay, Wisconsin, were compared and indicate that increasing urbanization has an effect on hydraulic characteristics (Reynolds number, shear stress, and stream power for example) in each metropolitan area, though limited commonality of significant correlations was noted between areas. Correspondence of significant correlations between invertebrate and hydraulic metrics between study areas also was limited. The links between urbanization, hydraulics, and invertebrates could be seen only in the Raleigh data. Connections among these three elements in the Milwaukee–Green Bay data were not clear and likely were obscured by antecedent land cover. Observed biotic differences due to hydrology and urbanization characteristics are not similar between geographic regions.

Scientific Investigations Report↗
USGS2011

A study of the effects of implementing agricultural best management practices and in-stream restoration on suspended sediment, stream habitat, and benthic macroinvertebrates at three stream sites in Surry County, North Carolina, 2004-2007-Lessons learned

The effects of agricultural best management practices and in-stream restoration on suspended-sediment concentrations, stream habitat, and benthic macroinvertebrate assemblages were examined in a comparative study of three small, rural stream basins in the Piedmont and Blue Ridge Physiographic Provinces of North Carolina and Virginia between 2004 and 2007. The study was designed to assess changes in stream quality associated with stream-improvement efforts at two sites in comparison to a control site (Hogan Creek), for which no improvements were planned. In the drainage basin of one of the stream-improvement sites (Bull Creek), several agricultural best management practices, primarily designed to limit cattle access to streams, were implemented during this study. In the drainage basin of the second stream-improvement site (Pauls Creek), a 1,600-foot reach of the stream channel was restored and several agricultural best management practices were implemented. Streamflow conditions in the vicinity of the study area were similar to or less than the long-term annual mean streamflows during the study. Precipitation during the study period also was less than normal, and the geographic distribution of precipitation indicated drier conditions in the southern part of the study area than in the northern part. Dry conditions during much of the study limited opportunities for acquiring high-flow sediment samples and streamflow measurements. Suspended-sediment yields for the three basins were compared to yield estimates for streams in the southeastern United States. Concentrations of suspended sediment and nutrients in samples from Bull Creek, the site where best management practices were implemented, were high compared to the other two sites. No statistically significant change in suspended-sediment concentrations occurred at the Bull Creek site following implementation of best management practices. However, data collected before and after channel stabilization at the Pauls Creek site indicated a statistically significant (p<0.05) decrease in suspended-sediment discharge following in-stream restoration. Stream habitat characteristics were similar at the Bull Creek and Hogan Creek reaches. However, the Pauls Creek reach was distinguished from the other two sites by a lack of pools, greater bankfull widths, greater streamflow and velocity, and larger basin size. Historical changes in the stream channel in the vicinity of the Pauls Creek streamgage are evident in aerial photographs dating from 1936 to 2005 and could have contributed to stream-channel instability. The duration of this study likely was inadequate for detecting changes in stream habitat characteristics. Benthic macroinvertebrate assemblages differed by site and changed during the course of the study. Bull Creek, the best management practices site, stood out as the site having the poorest overall conditions and the greatest improvement in benthic macroinvertebrate communities during the study period. Richness and diversity metrics indicated that benthic macroinvertebrate community conditions at the Hogan Creek and Pauls Creek sites declined during the study, although the status was excellent based on the North Carolina Index of Biotic Integrity. Experiences encountered during this study exemplify the difficulties of attempting to assess the short-term effects of stream-improvement efforts on a watershed scale and, in particular, the difficulty of finding similar basins for a comparative study. Data interpretation was complicated by dry climatic conditions and unanticipated land disturbances that occurred during the study in each of the three study basins. For example, agricultural best management practices were implemented in the drainage basin of the control site prior to and during the study. An impoundment on Bull Creek upstream from the streamgaging station probably influenced water-quality conditions and streamflow. Road construction in the vicinity of the Pauls Creek site potentially masked changes related to stream-improvement efforts. In addition, stream-improvement activities occurred in each of the three study basins over a period of several years prior to and during the study so that there were no discrete before and after periods available for meaningful comparisons. Historical and current land-use activities in each of the three study basins likely affected observed stream conditions. The duration of this study probably was insufficient to detect changes associated with agricultural best management practices and stream-channel restoration.

North Carolina↗
USGS2011

User's manual for the National Water-Quality Assessment Program Invertebrate Data Analysis System (IDAS) software, version 5

The Invertebrate Data Analysis System (IDAS) software was developed to provide an accurate, consistent, and efficient mechanism for analyzing invertebrate data collected as part of the U.S. Geological Survey National Water-Quality Assessment (NAWQA) Program. The IDAS software is a stand-alone program for personal computers that run Microsoft Windows(Registered). It allows users to read data downloaded from the NAWQA Program Biological Transactional Database (Bio-TDB) or to import data from other sources either as Microsoft Excel(Registered) or Microsoft Access(Registered) files. The program consists of five modules: Edit Data, Data Preparation, Calculate Community Metrics, Calculate Diversities and Similarities, and Data Export. The Edit Data module allows the user to subset data on the basis of taxonomy or sample type, extract a random subsample of data, combine or delete data, summarize distributions, resolve ambiguous taxa (see glossary) and conditional/provisional taxa, import non-NAWQA data, and maintain and create files of invertebrate attributes that are used in the calculation of invertebrate metrics. The Data Preparation module allows the user to select the type(s) of sample(s) to process, calculate densities, delete taxa on the basis of laboratory processing notes, delete pupae or terrestrial adults, combine lifestages or keep them separate, select a lowest taxonomic level for analysis, delete rare taxa on the basis of the number of sites where a taxon occurs and (or) the abundance of a taxon in a sample, and resolve taxonomic ambiguities by one of four methods. The Calculate Community Metrics module allows the user to calculate 184 community metrics, including metrics based on organism tolerances, functional feeding groups, and behavior. The Calculate Diversities and Similarities module allows the user to calculate nine diversity and eight similarity indices. The Data Export module allows the user to export data to other software packages (CANOCO, Primer, PC-ORD, MVSP) and produce tables of community data that can be imported into spreadsheet, database, graphics, statistics, and word-processing programs. The IDAS program facilitates the documentation of analyses by keeping a log of the data that are processed, the files that are generated, and the program settings used to process the data. Though the IDAS program was developed to process NAWQA Program invertebrate data downloaded from Bio-TDB, the Edit Data module includes tools that can be used to convert non-NAWQA data into Bio-TDB format. Consequently, the data manipulation, analysis, and export procedures provided by the IDAS program can be used to process data generated outside of the NAWQA Program.

Techniques and Methods↗
USGS2010

Effect of land cover change on runoff curve number estimation in Iowa, 1832-2001

Within the first few decades of European-descended settlers arriving in Iowa, much of the land cover across the state was transformed from prairie and forest to farmland, patches of forest, and urbanized areas. Land cover change over the subsequent 126 years was minor in comparison. Between 1832 and 1859, the General Land Office conducted a survey of the State of Iowa to aid in the disbursement of land. In 1875, an illustrated atlas of the State of Iowa was published, and in 2001, the US Geological Survey National Land Cover Dataset was compiled. Using these three data resources for classifying land cover, the hydrologic impact of the land cover change at three points in time over a period of 132+ years is presented in terms of the effect on the area-weighted average curve number, a term commonly used to predict peak runoff from rainstorms. In the four watersheds studied, the area-weighted average curve number associated with the first 30 years of settlement increased from 61·4 to 77·8. State-wide mapped forest area over this same period decreased 19%. Over the next 126 years, the area-weighted average curve number decreased to 76·7, despite an additional forest area reduction of 60%. This suggests that degradation of aquatic resources (plants, fish, invertebrates, and habitat) arising from hydrologic alteration was likely to have been much higher during the 30 years of initial settlement than in the subsequent period of 126 years in which land cover changes resulted primarily from deforestation and urbanization.

Iowa↗
USGS2010

Comparison of watershed disturbance predictive models for stream benthic macroinvertebrates for three distinct ecoregions in western US

The successful use of macroinvertebrates as indicators of stream condition in bioassessments has led to heightened interest throughout the scientific community in the prediction of stream condition. For example, predictive models are increasingly being developed that use measures of watershed disturbance, including urban and agricultural land-use, as explanatory variables to predict various metrics of biological condition such as richness, tolerance, percent predators, index of biotic integrity, functional species traits, or even ordination axes scores. Our primary intent was to determine if effective models could be developed using watershed characteristics of disturbance to predict macroinvertebrate metrics among disparate and widely separated ecoregions. We aggregated macroinvertebrate data from universities and state and federal agencies in order to assemble stream data sets of high enough density appropriate for modeling in three distinct ecoregions in Oregon and California. Extensive review and quality assurance of macroinvertebrate sampling protocols, laboratory subsample counts and taxonomic resolution was completed to assure data comparability. We used widely available digital coverages of land-use and land-cover data summarized at the watershed and riparian scale as explanatory variables to predict macroinvertebrate metrics commonly used by state resource managers to assess stream condition. The “best” multiple linear regression models from each region required only two or three explanatory variables to model macroinvertebrate metrics and explained 41–74% of the variation. In each region the best model contained some measure of urban and/or agricultural land-use, yet often the model was improved by including a natural explanatory variable such as mean annual precipitation or mean watershed slope. Two macroinvertebrate metrics were common among all three regions, the metric that summarizes the richness of tolerant macroinvertebrates (RICHTOL) and some form of EPT (Ephemeroptera, Plecoptera, and Trichoptera) richness. Best models were developed for the same two invertebrate metrics even though the geographic regions reflect distinct differences in precipitation, geology, elevation, slope, population density, and land-use. With further development, models like these can be used to elicit better causal linkages to stream biological attributes or condition and can be used by researchers or managers to predict biological indicators of stream condition at unsampled sites.

Ecological Indicators↗