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Statistical modeling of ecological data is often faced with a large number of variables as well as possible nonlinear relationships and higher-order interaction effects. Gradient boosted trees (GBT) have been successful in addressing these issues and have shown a good predictive performance in modeling nonlinear relationships, in particular in classification settings with a categorical response variable. They also tend to be robust against outliers. However, their black-box nature makes it difficult to interpret these models. We introduce several recently developed statistical tools to the environmental research community in order to advance interpretation of these black-box models. To analyze the properties of the tools, we applied gradient boosted trees to investigate biological health of streams within the contiguous USA, as measured by a benthic macroinvertebrate biotic index. Based on these data and a simulation study, we demonstrate the advantages and limitations of partial dependence plots (PDP), individual conditional expectation (ICE) curves and accumulated local effects (ALE) in their ability to identify covariate–response relationships. Additionally, interaction effects were quantified according to interaction strength (IAS) and Friedman’s $$H^2$$ H 2 statistic. Interpretable machine learning techniques are useful tools to open the black-box of gradient boosted trees in the environmental sciences. This finding is supported by our case study on the effect of impervious surface on the benthic condition, which agrees with previous results in the literature. Overall, the most important variables were ecoregion, bed stability, watershed area, riparian vegetation and catchment slope. These variables were also present in most identified interaction effects. In conclusion, graphical tools (PDP, ICE, ALE) enable visualization and easier interpretation of GBT but should be supported by analytical statistical measures. Future methodological research is needed to investigate the properties of interaction tests. Supplementary materials accompanying this paper appear on-line.

Many questions relevant to conservation decision‐making are characterized by extreme uncertainty due to lack of empirical data and complexity of the underlying ecologic processes, leading to a rapid increase in the use of structured protocols to elicit expert knowledge. Published ecologic applications often employ a modified Delphi method, where experts provide judgments anonymously and mathematical aggregation techniques are used to combine judgments. The Sheffield elicitation framework (SHELF) differs in its behavioral approach to synthesizing individual judgments into a fully specified probability distribution for an unknown quantity. We used the SHELF protocol remotely to assess extinction risk of three subterranean aquatic species that are being considered for listing under the U.S. Endangered Species Act. We provided experts an empirical threat assessment for each known locality over a video conference and recorded judgments on the probability of population persistence over four generations with online submission forms and R‐shiny apps available through the SHELF package. Despite large uncertainty for all populations, there were key differences between species’ risk of extirpation based on spatial variation in dominant threats, local land use and management practices, and species’ microhabitat. The resulting probability distributions provided decision makers with a full picture of uncertainty that was consistent with the probabilistic nature of risk assessments. Discussion among experts during SHELF's behavioral aggregation stage clearly documented dominant threats (e.g., development, timber harvest, animal agriculture, and cave visitation) and their interactions with local cave geology and species’ habitat. Our virtual implementation of the SHELF protocol demonstrated the flexibility of the approach for conservation applications operating on budgets and time lines that can limit in‐person meetings of geographically dispersed experts., Article Impact Statement: Remote expert elicitation can facilitate endangered species decision‐making when available data, budgets, and time frames are limiting.

Regionally scaled assessments of hydrologic alteration for small streams and its effects on freshwater taxa are often inhibited by a low number of stream gages. To overcome this limitation, we paired modeled estimates of hydrologic alteration to a benthic macroinvertebrate index of biotic integrity data for 4522 stream reaches across the Chesapeake Bay watershed. Using separate random-forest models, we predicted flow status (inflated, diminished, or indeterminant) for 12 published hydrologic metrics (HMs) that characterize the main components of flow regimes. We used these models to predict each HM status for each stream reach in the watershed, and linked predictions to macroinvertebrate condition samples collected from streams with drainage areas less than 200 km2. Flow alteration was calculated as the number of HMs with inflated or diminished status and ranged from 0 (no HM inflated or diminished) to 12 (all 12 HMs inflated or diminished). When focused solely on the stream condition and flow-alteration relationship, degraded macroinvertebrate condition was, depending on the number of HMs used, 3.8–4.7 times more likely in a flow-altered site; this likelihood was over twofold higher in the urban-focused dataset (8.7–10.8), and was never significant in the agriculture-focused dataset. Logistic regression analysis using the entire dataset showed for every unit increase in flow-alteration intensity, the odds of a degraded condition increased 3.7%. Our results provide an indication of whether altered streamflow is a possible driver of degraded biological conditions, information that could help managers prioritize management actions and lead to more effective restoration efforts.

Anthropogenic alterations have resulted in widespread degradation of stream conditions. To aid in stream restoration and management, baseline estimates of conditions and improved explanation of factors driving their degradation are needed. We used random forests to model biological conditions using a benthic macroinvertebrate index of biotic integrity for small, non-tidal streams (upstream area ≤200 km

Random forests have become an established tool for classification and regression, in particular in high-dimensional settings and in the presence of non-additive predictor-response relationships. For bounded outcome variables restricted to the unit interval, however, classical modeling approaches based on mean squared error loss may severely suffer as they do not account for heteroscedasticity in the data. To address this issue, we propose a random forest approach for relating a beta dis-tributed outcome to a set of explanatory variables. Our approach explicitly makes use of the likelihood function of the beta distribution for the selection of splits dur-ing the tree-building procedure. In each iteration of the tree-building algorithm it chooses one explanatory variable in combination with a split point that maximizes the log-likelihood function of the beta distribution with the parameter estimates de-rived from the nodes of the currently built tree. Results of several simulation studies and an application using data from the U.S.A. National Lakes Assessment Survey demonstrate the properties and usefulness of the method, in particular when compared to random forest approaches based on mean squared error loss and parametric regression models.

Significance This investigation provides a comprehensive evaluation of the geochemical and biological effects of shale gas development on 25 small watersheds over the course of 2 y. Sampling headwater streams seasonally over two consecutive years yielded no statistically significant relationships between the intensity, presence, or absence of shale gas development and any signal in a comprehensive set of chemical constituents (including those recognized as oil and gas geochemical tracers) or any changes in microbial or benthic macroinvertebrate community composition. This work provides a framework for investigations of anthropogenic effects stemming from natural resource development, and highlights the importance of conducting studies which control for regional and temporal variability., The number of horizontally drilled shale oil and gas wells in the United States has increased from nearly 28,000 in 2007 to nearly 127,000 in 2017, and research has suggested the potential for the development of shale resources to affect nearby stream ecosystems. However, the ability to generalize current studies is limited by the small geographic scope as well as limited breadth and integration of measured chemical and biological indicators parameters. This study tested the hypothesis that a quantifiable, significant relationship exists between the density of oil and gas (OG) development, increasing stream water concentrations of known geochemical tracers of OG extraction, and the composition of benthic macroinvertebrate and microbial communities. Twenty-five headwater streams that drain lands across a gradient of shale gas development intensity were sampled. Our strategy included comprehensive measurements across multiple seasons of sampling to account for temporal variability of geochemical parameters, including known shale OG geochemical tracers, and microbial and benthic macroinvertebrate communities. No significant relationships were found between the intensity of OG development, shale OG geochemical tracers, or benthic macroinvertebrate or microbial community composition, whereas significant seasonal differences in stream chemistry were observed. These results highlight the importance of considering spatial and temporal variability in stream chemistry and biota and not only the presence of anthropogenic activities in a watershed. This comprehensive, integrated study of geochemical and biological variability of headwater streams in watersheds undergoing OG development provides a robust framework for examining the effects of energy development at a regional scale.

Land‐use and climate change are significantly affecting stream ecosystems, yet understanding of their long‐term impacts is hindered by the few studies that have simultaneously investigated their interaction and high variability among future projections. We modeled possible effects of a suite of 2030, 2060, and 2090 land‐use and climate scenarios on the condition of 70,772 small streams in the Chesapeake Bay watershed, United States. The Chesapeake Basin‐wide Index of Biotic Integrity, a benthic macroinvertebrate multimetric index, was used to represent stream condition. Land‐use scenarios included four Special Report on Emissions Scenarios (A1B, A2, B1, and B2) representing a range of potential landscape futures. Future climate scenarios included quartiles of future climate changes from downscaled Coupled Model Intercomparison Project ‐ Phase 5 (CMIP5) and a watershed‐wide uniform scenario (Lynch2016). We employed random forests analysis to model individual and combined effects of land‐use and climate change on stream conditions. Individual scenarios suggest that by 2090, watershed‐wide conditions may exhibit anywhere from large degradations (e.g., scenarios A1B, A2, and the CMIP5 25th percentile) to small degradations (e.g., scenarios B1, B2, and Lynch2016). Combined land‐use and climate change scenarios highlighted their interaction and predicted, by 2090, watershed‐wide degradation in 16.2% (A2 CMIP5 25th percentile) to 1.0% (B2 Lynch2016) of stream kilometers. A goal for the Chesapeake Bay watershed is to restore 10% of stream kilometers over a 2008 baseline; our results suggest meeting and sustaining this goal until 2090 may require improvement in 11.0%–26.2% of stream kilometers, dependent on land‐use and climate scenario. These results highlight inherent variability among scenarios and the resultant uncertainty of predicted conditions, which reinforces the need to incorporate multiple scenarios of both land‐use (e.g., development, agriculture, etc.) and climate change in future studies to encapsulate the range of potential future conditions., Maps showing small NHDplusV2 catchments (

Stream ecosystems are complex networks of interacting terrestrial and aquatic drivers. To untangle these ecological networks, efforts evaluating the direct and indirect effects of landscape, climate, and instream predictors on biological condition through time are needed. We used structural equation modeling and leveraged a stream survey program to identify and compare important predictors driving condition of benthic macroinvertebrate and fish assemblages. We used data resampled 14 years apart at 252 locations across Maryland, USA. Sample locations covered a wide range of conditions that varied spatiotemporally. Overall, the relationship directions were consistent between sample periods, but their relative strength varied temporally. For benthic macroinvertebrates, we found that the total effect of natural landscape (e.g., elevation, longitude, latitude, geology) and land use (i.e., forest, development, agriculture) predictors was 1.4 and 1.5 times greater in the late 2010s compared to the 2000s. Moreover, the total effect of water quality (e.g., total nitrogen and conductivity) and habitat (e.g., embeddedness, riffle quality) was 1.2 and 4.8 times lower in the 2010s, respectively. For fish assemblage condition, the total effect of land use-land cover predictors was 2.3 times greater in the 2010s compared to the 2000s, while the total effect of local habitat was 1.4 times lower in the 2010s, respectively. As expected, we found biological assemblages in catchments with more agriculture and urban development were generally comprised of tolerant, generalist species, while assemblages in catchments with greater forest cover had more-specialized, less-tolerant species (e.g., Ephemeroptera, Plecoptera, and Trichoptera taxa, clingers, benthic and lithophilic spawning fishes). Changes in the relative importance of landscape and land-use predictors suggest other correlated, yet unmeasured, proximal factors became more important over time. By untangling these ecological networks, stakeholders can gain a better understanding of the spatiotemporal relationships driving biological condition to implement management practices aimed at improving stream condition.

A primary goal for Chesapeake Bay watershed restoration is to improve stream health and function in 10% of stream miles by 2025. Predictive spatial modeling of stream conditions, when accur...

Oil and gas development is changing the landscape in many regions of the United States and globally. However, the nature, extent, and magnitude of landscape change and development, and precisely how this development compares to other ongoing land conversion (e.g. urban/sub-urban development, timber harvest) is not well understood. In this study, we examine land conversion from oil and gas infrastructure development in the upper Susquehanna River basin in Pennsylvania and New York, an area that has experienced much oil and gas development over the past 10 years. We quantified land conversion in terms of forest canopy geometric volume loss in contrast to previous studies that considered only areal impacts. For the first time in a study of this type, we use fine-scale lidar forest canopy geometric models to assess the volumetric change due to forest clearing from oil and gas development and contrast this land change to clear cut forest harvesting, and urban and suburban development. Results show that oil and gas infrastructure development removed a large volume of forest canopy from 2006 to 2013, and this removal spread over a large portion of the study area. Timber operations (clear cutting) on Pennsylvania State Forest lands removed a larger total volume of forest canopy during the same time period, but this canopy removal was concentrated in a smaller area. Results of our study point to the need to consider volumetric impacts of oil and gas development on ecosystems, and to place potential impacts in context with other ongoing land conversions.

Extraction of oil and gas from unconventional sources, such as shale, has dramatically increased over the past ten years, raising the potential for spills or releases of chemicals, waste materials, and oil and gas. We analyzed spill data associated with unconventional wells from Colorado, New Mexico, North Dakota and Pennsylvania from 2005 to 2014, where we defined unconventional wells as horizontally drilled into an unconventional formation. We identified materials spilled by state and for each material we summarized frequency, volumes and spill rates. We evaluated the environmental risk of spills by calculating distance to the nearest stream and compared these distances to existing setback regulations. Finally, we summarized relative importance to drinking water in watersheds where spills occurred. Across all four states, we identified 21,300 unconventional wells and 6622 reported spills. The number of horizontal well bores increased sharply beginning in the late 2000s; spill rates also increased for all states except PA where the rate initially increased, reached a maximum in 2009 and then decreased. Wastewater, crude oil, drilling waste, and hydraulic fracturing fluid were the materials most often spilled; spilled volumes of these materials largely ranged from 100 to 10,000L. Across all states, the average distance of spills to a stream was highest in New Mexico (1379m), followed by Colorado (747m), North Dakota (598m) and then Pennsylvania (268m), and 7.0, 13.3, and 20.4% of spills occurred within existing surface water setback regulations of 30.5, 61.0, and 91.4m, respectively. Pennsylvania spills occurred in watersheds with a higher relative importance to drinking water than the other three states. Results from this study can inform risk assessments by providing improved input parameters on volume and rates of materials spilled, and guide regulations and the management policy of spills.

Rapid growth in unconventional oil and gas (UOG) has produced jobs, revenue, and energy, but also concerns over spills and environmental risks. We assessed spill data from 2005 to 2014 at 31 481 UOG wells in Colorado, New Mexico, North Dakota, and Pennsylvania. We found 2–16% of wells reported a spill each year. Median spill volumes ranged from 0.5 m3 in Pennsylvania to 4.9 m3 in New Mexico; the largest spills exceeded 100 m3. Seventy-five to 94% of spills occurred within the first three years of well life when wells were drilled, completed, and had their largest production volumes. Across all four states, 50% of spills were related to storage and moving fluids via flowlines. Reporting rates varied by state, affecting spill rates and requiring extensive time and effort getting data into a usable format. Enhanced and standardized regulatory requirements for reporting spills could improve the accuracy and speed of analyses to identify and prevent spill risks and mitigate potential environmental damage. Tran...

Pennsylvania’s rapid unconventional oil and gas (UOG) development—from a single well in 2004 to more than 6700 wells in 2013—has dramatically increased UOG waste transport by heavy trucks. This study quantified the amount of UOG waste and the distance it traveled between wells and disposal facilities on each type of road in each county between July 2010 and December 2013. In addition, the study estimated the associated financial costs to each county’s road infrastructure over that period. We found that UOG wells produced a median wastewater volume of 1294 m 3 and a median of 89,267 kg of solid waste. The median number of waste-transport truck trips per well was 122. UOG wells existed in 38 Pennsylvania counties, but we estimated trucks transporting well waste traveled through 132 counties, including counties in West Virginia, Ohio, and New York. Median travel distance varied by disposal type, from 106 km to centralized treatment facilities up to 237 km to injection wells. Local roads experienced the greatest amount of truck traffic and associated costs ($1.1–6.5 M) and interstates, the least ($0.3–1.6 M). Counties with oil and gas development experienced the most truck traffic and incurred the highest associated roadway costs. However, many counties outside the active development area also incurred roadway repair costs, highlighting the extension of UOG development’s spatial footprint beyond the active development area. An online data visualization tool is available here: www.nicholasinstitute.duke.edu/transportation-of-hydraulic-fracturing-waste .

Defining habitat suitability criteria (HSC) of aquatic biota can be a key component to environmental flow science. HSC can be developed through numerous methods; however, few studies have evaluated the consistency of HSC developed by different methodologies. We directly compared HSC for depth and velocity developed by the Delphi method (expert opinion) and by two primary literature meta-analyses (literature-derived range and interquartile range) to assess whether these independent methods produce analogous criteria for multiple species (rainbow trout, brown trout, American shad, and shallow fast guild) and life stages. We further evaluated how these two independently developed HSC affect calculations of habitat availability under three alternative reservoir management scenarios in the upper Delaware River at a mesohabitat (main channel, stream margins, and flood plain), reach, and basin scale. In general, literature-derived HSC fell within the range of the Delphi HSC, with highest congruence for velocity habitat. Habitat area predicted using the Delphi HSC fell between the habitat area predicted using two literature-derived HSC, both at the basin and the site scale. Predicted habitat increased in shallow regions (stream margins and flood plain) using literature-derived HSC while Delphi-derived HSC predicted increased channel habitat. HSC generally favoured the same reservoir management scenario; however, no favoured reservoir management scenario was the most common outcome when applying the literature range HSC. The differences found in this study lend insight into how different methodologies can shape HSC and their consequences for predicted habitat and water management decisions. Published 2016. This article is a U.S. Government work and is in the public domain in the USA.

Many at-risk species lack standardized surveys across their range or quantitative data capable of detecting demographic trends. As a result, extinction risk assessments often rely on ordinal categories of risk based on explicit criteria or expert elicitation. This study demonstrates a Bayesian approach to assessing extinction risk based on this common data structure, using three freshwater mussel species being considered for listing under the US Endangered Species Act. The probability that a population is classified under each risk category was modeled as a function of projected landscape change using ordered probit regression, assuming observed categories reflect a latent, continuous probability of persistence. All three species were more likely than not (mean probability >0.5) to be classified as extirpated or low condition throughout their range based on effects of urban development and hydrologic alteration. Spatial variation in estimates revealed strongholds and high-risk areas relevant to conservation decision making. Projected change in probabilities of each risk category based on multiple land-use and climate models was generally small relative to high baseline risk resulting from past landscape changes. Assessing extinction risk based on probabilities of ordinal condition as a function of landscape patterns may provide a flexible and robust approach for many at-risk taxa by adjusting species' demographic criteria to match relative risk categories, following standardized criteria, or using expert elicitation for data-deficient species. This approach provides decision makers with a useful measure of uncertainty around ordinal classifications and provides a framework for estimating future risk based on projections of anthropogenic stressors.

Demand for high-volume, short duration water withdrawals could create water stress to aquatic organisms in Fayetteville Shale streams sourced for hydraulic fracturing fluids. We estimated potential water stress using permitted water withdrawal volumes and actual water withdrawals compared to monthly median, low, and high streamflows. Risk for biological stress was considered at 20% of long-term median and 10% of high- and low-flow thresholds. Future well build-out projections estimated potential for continued stress. Most water was permitted from small, free-flowing streams and "frack" ponds (dammed streams). Permitted 12-h pumping volumes exceeded median streamflow at 50% of withdrawal sites in June, when flows were low. Daily water usage, from operator disclosures, compared to median streamflow showed possible water stress in 7-51% of catchments from June-November, respectively. If 100% of produced water was recycled, per-well water use declined by 25%, reducing threshold exceedance by 10%. Future water stress was predicted to occur in fewer catchments important for drinking water and species of conservation concern due to the decline in new well installations and increased use of recycled water. Accessible and precise withdrawal and streamflow data are critical moving forward to assess and mitigate water stress in streams that experience high-volume withdrawals.

Water temperature is an important factor in river ecology. Numerous models have been developed to predict river temperature. However, many were not designed to predict thermally stressful periods. Because such events are rare, traditionally applied analyses are inappropriate. Here, we developed two logistic regression models to predict thermally stressful events in the Delaware River at the US Geological Survey gage near Lordville, New York. One model predicted the probability of an event >20.0 °C, and a second predicted an event >22.2 °C. Both models were strong (independent test data sensitivity 0.94 and 1.00, specificity 0.96 and 0.96) predicting 63 of 67 events in the >20.0 °C model and all 15 events in the >22.2 °C model. Both showed negative relationships with released volume from the upstream Cannonsville Reservoir and positive relationships with difference between air temperature and previous day's water temperature at Lordville. We further predicted how increasing release volumes from Cannonsville Reservoir affected the probabilities of correctly predicted events. For the >20.0 °C model, an increase of 0.5 to a proportionally adjusted release (that accounts for other sources) resulted in 35.9% of events in the training data falling below cutoffs; increasing this adjustment by 1.0 resulted in 81.7% falling below cutoffs. For the >22.2 °C these adjustments resulted in 71.1% and 100.0% of events falling below cutoffs. Results from these analyses can help managers make informed decisions on alternative release scenarios. Copyright © 2016 John Wiley & Sons, Ltd.

We estimated discharge and suspended sediment (SS) yield in a minimally disturbed watershed in North Central Pennsylvania, USA, and compared a typical storm (September storm, 4.80 cm) to a large storm (Superstorm Sandy, 7.47 cm rainfall). Depending on branch, Sandy contributed 9.7–19.9 times more discharge and 11.5–37.4 times more SS than the September storm. During the September storm, the upper two branches accounted for 60.6% of discharge and 88.8% of SS at Lower Branch; during Sandy these percentages dropped to 36.1% for discharge and 30.1% for SS. The branch with close proximity roads had over two-three times per area SS yield than the branch without such roads. Hysteresis loops showed typical clockwise patterns for the September storm and more complicated patterns for Sandy, reflecting the multipeak event. Estimates of SS and hysteresis in minimally disturbed watersheds provide useful information that can be compared spatially and temporally to facilitate management.

In regulated rivers, managers must evaluate competing flow release scenarios that attempt to balance both human and natural needs. Meeting these natural flow needs is complex due to the myriad of interacting physical and hydrological factors that affect ecosystems. Tools that synthesize the voluminous scientific data and models on these factors will facilitate management of these systems. Here, we present the Riverine Environmental Flow Decision Support System (REFDSS), a tool that enables evaluation of competing flow scenarios and other variables on instream habitat. We developed a REFDSS for the Upper Delaware River, USA, a system that is regulated by three headwater reservoirs. This version of the REFDSS has the ability to integrate any set of spatially explicit data and synthesizes modeled discharge for three competing management scenarios, flow-specific 2-D hydrodynamic modeled estimates of local hydrologic conditions (e.g., depth, velocity, shear stress, etc.) at a fine pixel-scale (1 m2), and habitat suitability criteria (HSC) for a variety of taxa. It contains all individual model outputs, computationally integrates these data, and outputs the amount of potentially available habitat for a suite of species of interest under each flow release scenario. Users have the flexibility to change the time period of interest and vary the HSC. The REFDSS was developed to enable side-by-side evaluation of different flow management scenarios and their effects on potential habitat availability, allowing managers to make informed decisions on the best flow scenarios. An exercise comparing two alternative flow scenarios to a baseline scenario for several key species is presented. The Upper Delaware REFDSS was robust to minor changes in HSC (± 10 %). The general REFDSS platform was developed as a user-friendly Windows desktop application that was designed to include other potential parameters of interest (e.g., temperature) and for transferability to other riverine systems.

We conducted a large-scale assessment of unconventional oil and gas (UOG) development effects on brook trout (Salvelinus fontinalis) distribution. We compiled 2231 brook trout collection records from the Upper Susquehanna River Watershed, USA. We used boosted regression tree (BRT) analysis to predict occurrence probability at the 1:24,000 stream-segment scale as a function of natural and anthropogenic landscape and climatic attributes. We then evaluated the importance of landscape context (i.e., pre-existing natural habitat quality and anthropogenic degradation) in modulating the effects of UOG on brook trout distribution under UOG development scenarios. BRT made use of 5 anthropogenic (28% relative influence) and 7 natural (72% relative influence) variables to model occurrence with a high degree of accuracy [Area Under the Receiver Operating Curve (AUC)=0.85 and cross-validated AUC=0.81]. UOG development impacted 11% (n=2784) of streams and resulted in a loss of predicted occurrence in 126 (4%). Most streams impacted by UOG had unsuitable underlying natural habitat quality (n=1220; 44%). Brook trout were predicted to be absent from an additional 26% (n=733) of streams due to pre-existing non-UOG land uses (i.e., agriculture, residential and commercial development, or historic mining). Streams with a predicted and observed (via existing pre- and post-disturbance fish sampling records) loss of occurrence due to UOG tended to have intermediate natural habitat quality and/or intermediate levels of non-UOG stress. Simulated development of permitted but undeveloped UOG wells (n=943) resulted in a loss of predicted occurrence in 27 additional streams. Loss of occurrence was strongly dependent upon landscape context, suggesting effects of current and future UOG development are likely most relevant in streams near the probability threshold due to pre-existing habitat degradation.

The development of unconventional oil and gas (UOG) involves infrastructure development (well pads, roads and pipelines), well drilling and stimulation (hydraulic fracturing), and production; all of which have the potential to affect stream ecosystems. Here, we developed a fine-scaled (1:24,000) catchment-level disturbance intensity index (DII) that included 17 measures of UOG capturing all steps in the development process (infrastructure, water withdrawals, probabilistic spills) that could affect headwater streams ( 50). Well density, often used as a proxy for development, only correlated strongly with well pad coverage and produced materials, and therefore may miss potential effects associated with roads and pipelines, water withdrawals and spills. When analyzed with a future development scenario, 91.1% of EV stream length, 68.7% of Class A streams and 80.0% of patches were in catchments with a moderate to high probability of development. Our method incorporated the cumulative effects of UOG on streams and can be used to identify catchments and reaches at risk to existing stressors or future development.

Summary Water temperature is an important driver of many processes in riverine ecosystems. If reservoirs are present, their releases can greatly influence downstream water temperatures. Models are important tools in understanding the influence these releases may have on the thermal regimes of downstream rivers. In this study, we developed and tested a suite of models to predict river temperature at a location downstream of two reservoirs in the Upper Delaware River (USA), a section of river that is managed to support a world-class coldwater fishery. Three empirical models were tested, including a Generalized Least Squares Model with a cosine trend (GLScos), AutoRegressive Integrated Moving Average (ARIMA), and Artificial Neural Network (ANN). We also tested one mechanistic Heat Flux Model (HFM) that was based on energy gain and loss. Predictor variables used in model development included climate data (e.g., solar radiation, wind speed, etc.) collected from a nearby weather station and temperature and hydrologic data from upstream U.S. Geological Survey gages. Models were developed with a training dataset that consisted of data from 2008 to 2011; they were then independently validated with a test dataset from 2012. Model accuracy was evaluated using root mean square error (RMSE), Nash Sutcliffe efficiency (NSE), percent bias (PBIAS), and index of agreement ( d ) statistics. Model forecast success was evaluated using baseline-modified prime index of agreement (md) at the one, three, and five day predictions. All five models accurately predicted daily mean river temperature across the entire training dataset (RMSE = 0.58–1.311, NSE = 0.99–0.97, d = 0.98–0.99); ARIMA was most accurate (RMSE = 0.57, NSE = 0.99), but each model, other than ARIMA, showed short periods of under- or over-predicting observed warmer temperatures. For the training dataset, all models besides ARIMA had overestimation bias (PBIAS = −0.10 to −1.30). Validation analyses showed all models performed well; the HFM model was the most accurate compared other models (RMSE = 0.92, both NSE = 0.98, d = 0.99) and the ARIMA model was least accurate (RMSE = 2.06, NSE = 0.92, d = 0.98); however, all models had an overestimation bias (PBIAS = −4.1 to −10.20). Aside from the one day forecast ARIMA model (md = 0.53), all models forecasted fairly well at the one, three, and five day forecasts (md = 0.77–0.96). Overall, we were successful in developing models predicting daily mean temperature across a broad range of temperatures. These models, specifically the GLScos, ANN, and HFM, may serve as important tools for predicting conditions and managing thermal releases in regulated river systems such as the Delaware River. Further model development may be important in customizing predictions for particular biological or ecological needs, or for particular temporal or spatial scales.

Fatty acids are integral components of periphyton and differ among algal taxa. We examined seasonal patterns in periphyton fatty acids in six minimally disturbed headwater streams in Pennsylva- nia's Appalachian Mountains, USA. Environmental data and periphyton were collected across four seasons for fatty acid and algal taxa content. Non-metric multidimensional scaling ordination suggested signif- icant seasonal differences in fatty acids; an ordination on algal composition revealed similar seasonal pat- terns, but with slightly weaker separation of summer and fall. Summer and fall fatty acid profiles were driven by temperature, overstory cover, and conduc- tivity and winter profiles by measures of stream size. Ordination on algal composition suggested that sum- mer and fall communities were driven by overstory and temperature, whereas winter communities were driven by velocity. The physiologically important fatty acid 18:3x6 was highest in summer and fall. Winter samples had the highest 20:3x3. Six saturated fatty acids differed among the seasons. Periphyton fatty acids profiles appeared to reflect benthic algal species composition. This suggests that periphyton fatty acid composition can be useful in characterizing basal food resources and stream water quality.

The increasing world demand for energy has led to an increase in the exploration and extraction of natural gas, condensate, and oil from unconventional organic-rich shale plays. However, little is ...

Species distribution models (SDMs) are often used in conservation planning, but their utility can be improved by assessing the relationships between environmental and species response variables. We constructed SDMs for 30 stream fishes of Maryland, USA, using watershed attributes as environmental variables and presence/absence as species responses. SDMs showed substantial agreement between observed and predicted values for 17 species. Most important variables were natural attributes (e.g., ecoregion, watershed area, latitude/longitude); land cover (e.g., %impervious, %row crop) was important for three species. Focused analyses on four representative species (central stoneroller, creek chub, largemouth bass, and white sucker) showed the probability of presence of each species increased non-linearly with watershed area. For these species, SDMs built to predict absent, low, and high densities were similar to presence/absence predictions but provided probable locations of high densities (e.g., probability of high-density creek chub decreased rapidly with watershed area). We applied SDMs to predict suitability of watersheds within the study area for each species. Maps of suitability and the environmental and species response relationships can help develop better management plans.

SUMMARY 1. To manage the environmental flow requirements of sedentary taxa, such as mussels and aquatic insects with fixed retreats, we need a measure of habitat availability over a variety of flows (i.e. a measure of persistent habitat). Habitat suitability measures in current environmental flow assessments are measured on a ‘flow by flow’ basis and thus are not appropriate for these taxa. Here, we present a novel measure of persistent habitat suitability for the dwarf wedgemussel (Alasmidonta heterodon), listed as federally endangered in the U.S.A., in three reaches of the Delaware River. 2. We used a two-dimensional hydrodynamic model to quantify suitable habitat over a range of flows based on modelled depth, velocity, Froude number, shear velocity and shear stress at three scales (individual mussel, mussel bed and reach). Baseline potentially persistent habitat was quantified as the sum of pixels that met all thresholds identified for these variables for flows ‡40 m 3 s )1 , and we calculated the loss of persistently suitable habitat by sequentially summing suitable habitat estimates at lower flows. We estimated the proportion of mussel beds exposed at each flow and the amount of change in the size of the mussel bed for one reach. 3. For two reaches, mussel beds occupied areas with lower velocity, shear velocity, shear stress and Froude number than the reach average at all flows. In the third reach, this was true only at higher flows. Together, these results indicate that beds were possible refuge areas from the effects of these hydrological parameters. Two reaches showed an increase in the amount of exposed mussel beds with decreasing flow. 4. Baseline potentially persistent habitat was less than half the areal extent of potentially suitable habitat, and it decreased with decreasing flow. Actually identified beds and modelled persistent habitat showed good spatial overlap, but identified beds occupied only a portion of the total modelled persistent habitat, indicating either that additional suitable habitat is available or the need to improve habitat criteria. At one site, persistent beds (beds where mussels were routinely collected) were located at sites with stable substratum, whereas marginal beds (beds where mussels were infrequently collected or that were lost following a large flood event) were located in scoured areas. 5. Taken together, these model results support a multifaceted approach, which incorporates the effects of low and high flow stressors, to quantify habitat suitability for mussels and other sedentary taxa. Models of persistent habitat can provide a more holistic environmental flow assessment of rivers.

Summary 1. Issues with ecological data (e.g. non-normality of errors, nonlinear relationships and autocorrelation of variables) and modelling (e.g. overfitting, variable selection and prediction) complicate regression analyses in ecology. Flexible models, such as generalized additive models (GAMs), can address data issues, and machine learning techniques (e.g. gradient boosting) can help resolve modelling issues. Gradient boosted GAMs do both. Here, we illustrate the advantages of this technique using data on benthic macroinvertebrates and fish from 1573 small streams in Maryland, USA. 2. We assembled a predictor matrix of 15 watershed attributes (e.g. ecoregion and land use), 15 stream attributes (e.g. width and habitat quality) and location (latitude and longitude). We built boosted and conventionally estimated GAMs for macroinvertebrate richness and for the relative abundances of macroinvertebrates in the Orders Ephemeroptera, Plecoptera and Trichoptera (%EPT); individuals that cling to substrate (%Clingers); and individuals in the collector/gatherer functional feeding group (%Collectors). For fish, models were constructed for taxonomic richness, benthic species richness, biomass and the relative abundance of tolerant individuals (%Tolerant Fish). 3. For several of the responses, boosted GAMs had lower pseudo R2s than conventional GAMs for in-sample data but larger pseudo R2s for out-of-bootstrap data, suggesting boosted GAMs do not overfit the data and have higher prediction accuracy than conventional GAMs. The models explained most variation in fish richness (pseudo R2 = 0·97), least variation in %Clingers (pseudo R2 = 0·28) and intermediate amounts of variation in the other responses (pseudo R2s between 0·41 and 0·60). Many relationships of macroinvertebrate responses to anthropogenic measures and natural watershed attributes were nonlinear. Fish responses were related to system size and local habitat quality. 4. For impervious surface, models predicted below model-average macroinvertebrate richness at levels above c. 3·0%, lower %EPT above c. 1·5%, and lower %Clingers for levels above c. 2·0%. Impervious surface did not affect %Collectors or any fish response. Prediction functions for %EPT and fish richness increased linearly with log10 (watershed area), %Tolerant Fish decreased with log10 (watershed area), and benthic fish richness and biomass both increased nonlinearly with log10 (watershed area). 5. Gradient boosting optimizes the predictive accuracy of GAMs while preserving the structure of conventional GAMs, so that predictor–response relationships are more interpretable than with other machine learning methods. Boosting also avoids overfitting the data (by shrinking effect estimates towards zero and by performing variable selection), thus avoiding spurious predictor effects and interpretations. Thus, in many ecological settings, it may be reasonable to use boosting instead of conventional GAMs.

Measures of species diversity are valuable tools for assessing ecosystem health. However, most assessments have addressed individual sites or regional taxon pools, with few comparisons of differences in assemblage composition within or among regions. We examined the effects of anthropogenic disturbance on local richness (a diversity) and species turnover (b diversity) of benthic macroinvertebrates in small streams within and between 2 ecoregions (Northern Piedmont vs Southeastern Plains ecoregions) of the Patuxent River basin (Maryland, USA). Regional species pools did not differ between ecoregions (Piedmont = 166 taxa, Plains = 162 taxa); however, local richness was lower in the Plains (mean = 17.4 taxa/stream) compared to the Piedmont (mean = 22.2 taxa/stream). When streams were categorized into disturbance classes (low, medium, high), local richness did not differ among categories for either region. However, at the entire Patuxent scale, local richness tended to decrease with % impervious cover in a watershed. Variation in species composition, analyzed with nonmetric multidimensional scaling (nMDS), differed significantly between Piedmont and Plains streams, and Plains streams had higher b diversity than Piedmont streams. When partitioned by disturbance category and region, b diversity differed only between the low-disturbance sites (Plains . Piedmont). Relationships between b diversity and environmental variables varied by region. b diversity was weakly negatively related to % row-crop cover in a watershed at the entire Patuxent scale. For the Piedmont region, b diversity tended to decrease with % forest, % pasture, and % row-crop cover in a watershed. Such negative relationships between b diversity and landuse variables indicate a possible homogenization of the assemblage. The incongruence between diversity measures and composition measures, together with differing effects of anthropogenic land use on b diversity in the 2 regions, emphasizes the need to incorporate both a and b diversity and regional environmental factors in conservation/land management studies.

Explaining the mechanisms underlying patterns of species diversity and composition in riverine networks is challenging. Historically, community ecologists have conceived of communities as largely isolated entities and have focused on local environmental factors and interspecific interactions as the major forces determining species composition. However, stream ecologists have long embraced a multiscale approach to studying riverine ecosystems and have studied both local factors and larger-scale regional factors, such as dispersal and disturbance. River networks exhibit a dendritic spatial structure that can constrain aquatic organisms when their dispersal is influenced by or confined to the river network. We contend that the principles of metacommunity theory would help stream ecologists to understand how the complex spatial structure of river networks mediates the relative influences of local and regional control on species composition. From a basic ecological perspective, the concept is attractive because new evidence suggests that the importance of regional processes (dispersal) depends on spatial structure of habitat and on connection to the regional species pool. The role of local factors relative to regional factors will vary with spatial position in a river network. From an applied perspective, the long-standing view in ecology that local community composition is an indicator of habitat quality may not be uniformly applicable across a river network, but the strength of such bioassessment approaches probably will depend on spatial position in the network. The principles of metacommunity theory are broadly applicable across taxa and systems but seem of particular consequence to stream ecology given the unique spatial structure of riverine systems. By explicitly embracing processes at multiple spatial scales, metacommunity theory provides a foundation on which to build a richer understanding of stream communities.

Indices of biotic integrity have become an established tool to quantify the condition of small non-tidal streams and their watersheds. To investigate the effects of watershed characteristics on stream biological condition, we present a new technique for regressing IBIs on watershed-specific explanatory variables. Since IBIs are typically evaluated on an ordinal scale, our method is based on the proportional odds model for ordinal outcomes. To avoid overfitting, we do not use classical maximum likelihood estimation but a component-wise functional gradient boosting approach. Because component-wise gradient boosting has an intrinsic mechanism for variable selection and model choice, determinants of biotic integrity can be identified. In addition, the method offers a relatively simple way to account for spatial correlation in ecological data. An analysis of the Maryland Biological Streams Survey shows that nonlinear effects of predictor variables on stream condition can be quantified while, in addition, accurate predictions of biological condition at unsurveyed locations are obtained.

The decay of community similarity with distance (distance decay) is reported for many taxa in a variety of geographic settings. However, the importance of scale, distance measure, ecoregions, and ecological transition zones to distance decay has not been thoroughly examined. The goal of our study was to test the effects of these factors on distance decay in two freshwater assemblages (benthic macroinvertebrates and fish) with differing dispersal abilities in small streams within the Patuxent River basin, Maryland, USA. The Patuxent basin contains a geologic Fall Line, an ecological transition zone separating the two main regions of the basin. For both assemblages, we examined distance decay in similarity at several extents: entire Patuxent, Piedmont sub-region, and Plains sub-region using both linear geographic and stream network distances. Decay patterns were observed across all extents and distances. At the Patuxent extent decay rates differed

Aim: We investigate the relationship between local and regional richness in marine fouling assemblages using an expanded and globally replicated approach by incorporating two dimensions of diversity (taxonomic and functional) and different successional stages. Location: Global. Methods: In eight different biogeographic regions (Australia, Brazil, Chile, England, Italy, Japan, Portugal and Sweden) 68 polyvinylchloride (PVC) panels (15 × 15 × 0.3 cm) were deployed for colonization. Communities colonizing panels were analysed by measuring percentage cover at each of four different successional ages: 2, 4, 6 and 8 months. Local richness was assessed as the average number of species and functional groups (FGs) per panel and regional richness was evaluated as the estimated (Jack2) asymptote of the sample-accumulation curves for species and FG on experimental panels. Results: We found that the shape of the relationship between local and regional richness depended on successional stage and the type of richness considered, i.e. taxonomic or functional richness. Hardly any relationship was detectable between local taxonomic richness and regional taxonomic richness at any successional stage. In contrast, the relation between local functional and regional functional richness shows a unimodal pattern of change during succession, passing through the stages ‘independent’, ‘unsaturated rising’, ‘saturated rising’ and once again ‘independent’. Main conclusions: The relationship between local and regional richness, whether taxonomic or functional, frequently displays independence of the two scales, particularly in early and late phases of the successional process.

The ability to classify the biological condition of unsurveyed streams accurately would be an asset to the conservation and management of streams. We compared the ability of 5 modeling methods (classification and regression trees, conditional inference trees, random forests [RF], conditional random forests [cRF], and ordinal logistic regression) to predict stream biological condition (very poor, poor, fair, or good) based on benthic macroinvertebrate Index of Biotic Integrity data taken from the Maryland Biological Stream Survey. Predictor variables included land use and land cover (e.g., impervious surface, row-crop agriculture, and population density) and landscape measures (annual precipitation and watershed area). We included 1561 sites on small nontidal streams in the Maryland portion of the Chesapeake Bay watershed. We used 1248 sites (80%) as a training data set to build models and 313 sites (20%) as an independent evaluation data set. RF and cRF models most accurately predicted observed in...

Observational studies of diversity have consistently found positive correlations between native and exotic species, suggesting that the same environmental factors that drive native species richness also drive exotic species richness, i.e., “the rich get richer”. We examined patterns of native and exotic plant species richness in temperate forests that have been undergoing reforestation since the turn of the twentieth century to test the influence of disturbance arising from land-use history on this relationship. Overall, we found no relationship between native and exotic plant species richness. Instead, we found a positive relationship between native and exotic richness in older but not younger-growth forests, suggesting that the same processes that drove exotic plant richness in older forests also facilitated native plants. In contrast, younger forests had similar numbers of native species relative to older forests, but 41% more exotic species and 24% more compacted soils. Moreover, exotic but not native species richness was positively correlated with increasing soil compaction across all sites. Overall, our results suggest that elevated exotic plant invasions in younger forests are a legacy of soil disturbance arising from agricultural practices at the turn of the century, and that native and exotic plants may respond differentially to disparate environmental drivers.

We present results on changes in soil properties following land use change over an approximately 55-year period at Fort Benning, Georgia, U.S.A. Soil cores were taken at 129 locations that were categorized as reforested (field/ bare ground in 1944 and forest in 1999), disturbed (field/ bare ground in 1944 and 1999), or reference forests (forest in 1944 and 1999). Soil disturbance included historic agriculture (pre-1944) and military training (post-1944). Density in mineral soils exhibited a historic land use legacy effect (reference reforested > disturbed). Soil C stock in all other increments and in particulate organic matter was affected by disturbance; however, no legacy was apparent (reference = reforested > disturbed). For the entire soil profile (O-horizon to 40 cm), rate of C accrual was 28 g m 22 yr 21 (1.5%/yr). Nitrogen stocks were affected by disturbance in the O-horizon and 0- to 10-cm increment; however, no legacy effect was detected (reference = reforested > disturbed). Nitrogen accumulated at 0.56 g m 22 yr 21 (0.6%/yr) for the entire soil profile. At Fort Benning, soil C and N stocks of reforested stands were similar to those of reference forested stands after approximately 55 years. However, soil bulk density was greater on reforested stands than reference forest stands at 55 years and may require an additional century to reach reference levels.

The concept of landscape legacies has been examined extensively in terrestrial ecosystems and has led to a greater understanding of contemporary ecosystem processes. However, although stream ecosystems are tightly coupled with their catchments and, thus, probably are affected strongly by historical catchment conditions, few studies have directly examined the importance of landuse legacies on streams. We examined relationships between historical land use (1944) and contemporary (2000-2003) stream physical, chemical, and biological conditions after accounting for the influences of contemporary land use (1999) and natural landscape (catchment size) variation in 12 small streams at Fort Benning, Georgia, USA. Most stream variables showed strong relationships with contemporary land use and catchment size; however, after accounting for these factors, residual variation in many variables remained significantly related to historical land use. Residual variation in benthic particulate organic matter, diatom density, % of diatoms in Eunotia spp., fish density in runs, and whole-stream gross primary productivity correlated negatively, whereas streamwater pH correlated positively, with residual variation in fraction of disturbed land in catchments in 1944 (i.e., bare ground and unpaved road cover). Residual variation in % recovering land (i.e., early successional vegetation) in 1944 was correlated positively with residual variation in streambed instability, a macroinvertebrate biotic index, and fish richness, but correlated negatively with residual variation in most benthic macroinvertebrate metrics examined (e.g., Chironomidae and total richness, Shannon diversity). In contrast, residual variation in whole-stream respiration rates was not explained by historical land use. Our results suggest that historical land use continues to influence important physical and chemical variables in these streams, and in turn, probably influences associated biota. Beyond providing insight into biotic interactions and their associations with environmental conditions, identification of landuse legacies also will improve understanding of stream impairment in contemporary minimally disturbed catchments, enabling more accurate assessment of reference conditions in studies of biotic integrity and restoration.

SUMMARY 1. Dam removal has great potential for restoring rivers and streams, yet limited data exist documenting recovery of associated biota within these systems following removals, especially on larger systems. This study examined the effects of a dam breach on benthic macroinvertebrate and fish assemblages in the Fox River, Illinois, U.S.A. 2. Benthic macroinvertebrates and fish were collected above and below the breached dam and three nearby intact dams for 1 year pre- and 3 years post-breach (2 years of additional pre-breach fish data were obtained from previous surveys). We also examined the effects of the breach on associated habitat by measuring average width, depth, flow rate and bed particle size at each site. 3. Physical habitat at the former impoundment (IMP) became comparable to free-flowing sites (FF) within 1 year of the breach (width and depth decreased, flow rate and bed particle size increased). We also found a strong temporal effect on depth and flow rate at all surveyed sites. 4. Following the breach, relative abundance of Ephemeroptera, Plecoptera and Trichoptera (largely due to hydropsychid caddisflies) increased, whereas relative abundance of Ostracoda decreased, in the former IMP to levels comparable to FF sites. High variation in other metrics (e.g. total taxa, diversity) precluded determination of an effect of the breach on these aspects of the assemblage. However, non-metric multidimensional scaling (NMDS) ordinations indicated that overall macroinvertebrate assemblage structure at the former IMP shifted to a characteristically FF assemblage 2 years following the breach. 5. Total fish taxa and a regional fish index of biotic integrity became more similar in the former IMP to FF sites following the breach. However, other fish metrics (e.g. biomass, diversity, density) did not show a strong response to the breach of the dam. Ordinations of abundance data suggested the fish assemblage only slightly shifted to FF characteristics 3 years after the breach. 6. Effects of the breach to the site immediately below the former dam included minor alterations in habitat (decreased flow rate and increased particle size) and short-term changes in several macroinvertebrate metrics (e.g. decreased assemblage diversity and EPT richness for first post-year), but longer-term alterations in several fish metrics (e.g.

We examined relationships between catchment-scale disturbance from military training and two dominant fish species, Pteronotropis euryzonus (broadstripe shiner) and Semotilus thoreauianus (Dixie chub) in headwater streams at the Fort Benning Military Installation (FBMI), GA. Disturbance was estimated as the percent of the catchment that was bare ground and unpaved road cover. Relative abundance of broadstripe shiners and Dixie chubs were negatively and positively related to disturbance, respectively. This complementarity likely resulted from contrasting life histories, feeding behaviors, and habitat preferences between the two species. Absolute abundance of broadstripe shiners increased, whereas relative abundance of Dixie chubs decreased, with stream discharge, suggesting that both species were affected by local habitat conditions. Additionally, the average body size of both species was lower in high-disturbance streams, signifying that both species were affected by disturbance. Results also sug...

Stream benthic macroinvertebrates are useful indicators of the impacts of disturbances on catchment and stream conditions because they integrate many catchment-scale ecological processes. We tested the ability of macroinvertebrate assemblages over a 3-year period to indicate the impacts of a range of disturbances resulting from military training at the Fort Benning Military Installation, Georgia. We studied seven small streams that drained catchments spanning disturbances that ranged from light infantry movements to heavy disturbances from tracked vehicle movements. The main disturbance to streams was influx of sediment associated with training and use of unpaved roads. We quantified disturbance level as the % of catchment occurring as bare ground on slopes >3% and as unpaved road cover. Disturbance level values ranged from about 3 to 15%. Nonmetric multidimensional scaling ordinations revealed macroinvertebrate assemblages were associated with catchment disturbance. Irrespective of season, several richness measures (e.g., number of Ephemeroptera, Plecoptera, and Trichoptera taxa and richness of Chironomidae) negatively corresponded with catchment disturbance, however except for chironomid richness all measures showed high variation among seasons and annually. Compositional and functional feeding group measures also showed high seasonal and annual variation, with only the % of macroinvertebrates clinging to benthic habitats (=% clingers) corresponding with disturbance. Both tolerance metrics tested, the Florida index and North Carolina biotic index, showed little seasonal and annual variation, however only the Florida index related to disturbance. A regional multimetric, the Georgia stream condition index, consistently corresponded with catchment disturbance and showed the least temporal variability. Our results further suggest a threshold at 8‐10% of the catchment as bare ground and unpaved road cover, a disturbance threshold similar to that reported for other land uses. # 2005 Elsevier Ltd. All rights reserved.

Absorption of solar ultraviolet radiation (UVR) in aquatic ecosystems is primarily controlled by dissolved organic carbon (DOC). The role of iron (Fe) has also been suggested to contribute to UVR attenuation either directly or by interactions with DOC. Here we present findings from three laboratory manipulations of Fe and DOC on changes to the dissolved UVR absorption (ad,320) in a mid-latitude, dimictic, humic lake. In a laboratory simulation of lake turnover where anoxic, hypolimnetic water was oxygenated ad,320 significantly increased from 23.3 to 81.7 m−1 (p

We investigated whether two characteristics of stream diurnal dissolved oxygen profiles, the daily amplitude and maximum value of the dissolved oxygen saturation deficit, are useful indicators of stream metabolism and the effects of catchment-scale disturbances. The study was conducted at the U.S. Army's Fort Benning installation where vegetation loss and high rates of erosion from intensely used training areas and unpaved roads have resulted in extensive sedimentation in some streams. Diurnal profiles of dissolved oxygen were measured in 10 second-order streams draining catchments which exhibited a range of disturbance levels. Rates of gross primary production (GPP) and total ecosystem respiration (R) per unit surface area were determined for each stream using the single-station diurnal dissolved oxygen change method with direct measurement of air–water oxygen exchange rates. The daily amplitude of the diurnal dissolved oxygen deficit profile was highly correlated with daily rates of GPP, and multiplying the daily amplitude by average stream depth to account for differences in water volume did not improve the correlation. The daily maximum dissolved oxygen deficit was highly correlated with daily rates of R, and multiplying by average stream depth improved the correlation. In general, these indicators of stream metabolism declined sharply with increasing catchment disturbance level, although the indicators of R showed a more consistent relationship with disturbance level than those of GPP. Our results show that the daily amplitude and maximum value of diurnal dissolved oxygen deficit profiles are good indicators of reach-scale rates of metabolism and the effects of catchment-scale disturbance on these metabolism rates. At Fort Benning, and presumably at other military installations, they are useful tools for evaluating trends in impacts from military training or rates of recovery following restoration activities.