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Ian R. Waite

Publications and source records attributed to Ian R. Waite.

At least 37 records · Page 2Linked to original sources
USGS2018

Can data from disparate long-term fish monitoring programs be used to increase our understanding of regional and continental trends in large river assemblages?

Understanding trends in the diverse resources provided by large rivers will help balance tradeoffs among stakeholders and inform strategies to mitigate the effects of landscape scale stressors such as climate change and invasive species. Absent a cohesive coordinated effort to assess trends in important large river resources, a logical starting point is to assess our ability to draw inferences from existing efforts. In this paper, we use a common analytical framework to analyze data from five disparate fish monitoring programs to better understand the nature of spatial and temporal trends in large river fish assemblages. We evaluated data from programs that monitor fishes in the Colorado, Columbia, Illinois, Mississippi, and Tallapoosa rivers using non-metric dimensional scaling ordinations and associated tests to evaluate trends in fish assemblage structure and native fish biodiversity. Our results indicate that fish assemblages exhibited significant spatial and temporal trends in all five of the rivers. We also document native species diversity trends that were variable within and between rivers and generally more evident in rivers with higher species richness and programs of longer duration. We discuss shared and basin-specific landscape level stressors. Having a basic understanding of the nature and extent of trends in fish assemblages is a necessary first step towards understanding factors affecting biodiversity and fisheries in large rivers.

PLoS ONE↗
USGS2018

Assessing the influence of multiple stressors on stream diatom metrics in the upper Midwest, USA

Water resource managers face increasing challenges in identifying what physical and chemical stressors are responsible for the alteration of biological conditions in streams. The objective of this study was to assess the comparative influence of multiple stressors on benthic diatoms at 98 sites that spanned a range of stressors in an agriculturally dominated region in the upper Midwest, USA. The primary stressors of interest included: nutrients, herbicides and fungicides, sediment, and streamflow; although the influence of physical habitat was incorporated in the assessment. Boosted Regression Tree was used to examine both the sensitivity of various diatom metrics and the relative importance of the primary stressors. Percent Sensitive Taxa, percent Highly Motile Taxa, and percent High Phosphorus Taxa had the strongest response to stressors. Habitat and total phosphorous were the most common discriminators of diatom metrics, with herbicides as secondary factors. A Classification and Regression Tree (CART) model was used to examine conditional relations among stressors and indicated that fine-grain streams had a lower percentage of Sensitive Taxa than coarse-grain streams, with Sensitive Taxa decreasing further with increased water temperature (>30 °C) and triazine concentrations (>1500 ng/L). In contrast, streams dominated by coarse-grain substrate contained a higher percentage of Sensitive Taxa, with relative abundance increasing with lower water temperatures (<29 °C) and shallower water depth (<0.3 m). Quantile regression indicated that maximum water temperature appears to be a major limiting factor in Midwest streams; whereas both total phosphorus and percent fines showed a slight subsidy-stress response. While using benthic algae for assessing stream quality can be challenging, field-based studies can elucidate stressor effects and interactions when the response variables are appropriate, sufficient stressor resolution is achieved, and the number and type of sites represent a gradient of stressor conditions and at least a quasi-factorial design.

Ecological Indicators↗
USGS2018

Nutrient enrichment in wadeable urban streams in the piedmont ecoregion of the southeastern United States

The U.S. Geological Survey (USGS) Southeastern Stream Quality Assessment (SESQA) collected weekly samples for nitrogen and phosphorus in 76 wadeable streams in the urbanized Piedmont ecoregion of the Southeastern United States, during April–June 2014. Total nitrogen (TN) concentrations in excess of EPA guidelines and statistically greater than at reference locations indicated nitrogen-nutrient enrichment in streams draining poultry confined animal feeding operations (CAFO) or urban centers. Nitrate plus nitrite (NO3 + NO2) dominated TN species in urban/CAFO-influenced streams. Streams that drained poultry CAFO and Washington DC had statistically higher NO3 + NO2 concentrations than streams draining Atlanta, Charlotte, Greenville, or Raleigh. In contrast, total phosphorus (TP) concentrations in Atlanta and Washington DC streams statistically were comparable to and lower than, respectively, reference stream concentrations. Over 50% of TP concentrations in Greenville, Charlotte, Raleigh and CAFO-influenced streams exceeded the EPA guideline and reference location mean concentrations, indicating phosphorus-nutrient enrichment. Urban land use, permitted point sources, and soil infiltration metrics best predicted TN exceedances. Elevated TN and NO3 + NO2 concentrations in urban streams during low flow were consistent with reduced in-stream dilution of point-source or groundwater contributions. Urban land use, permitted point sources, and surface runoff metrics best predicted TP exceedances. Elevated TP in CAFO and urban streams during high flow were consistent with non-point sources and particulate transport.

Piedmont Ecoregion↗
USGS2017

Long-term fish monitoring in large rivers: Utility of “benchmarking” across basins

In business, benchmarking is a widely used practice of comparing your own business processes to those of other comparable companies and incorporating identified best practices to improve performance. Biologists and resource managers designing and conducting monitoring programs for fish in large river systems tend to focus on single river basins or segments of large rivers, missing opportunities to learn from those conducting fish monitoring in other rivers. We briefly examine five long-term fish monitoring programs in large rivers in the United States (Colorado, Columbia, Mississippi, Illinois, and Tallapoosa rivers) and identify opportunities for learning across programs by detailing best monitoring practices and why these practices were chosen. Although monitoring objectives, methods, and program maturity differ between each river system, examples from these five case studies illustrate the important role that long-term monitoring programs play in interpreting temporal and spatial shifts in fish populations for both established objectives and newly emerging questions. We suggest that deliberate efforts to develop a broader collaborative network through benchmarking will facilitate sharing of ideas and development of more effective monitoring programs.

Colorado River, Columbia River, Illinois River, Mi↗
USGS2017

Influence of sediment chemistry and sediment toxicity on macroinvertebrate communities across 99 wadable streams of the Midwestern USA

Simultaneous assessment of sediment chemistry, sediment toxicity, and macroinvertebrate communities can provide multiple lines of evidence when investigating relations between sediment contaminants and ecological degradation. These three measures were evaluated at 99 wadable stream sites across 11 states in the Midwestern United States during the summer of 2013 to assess sediment pollution across a large agricultural landscape. This evaluation considers an extensive suite of sediment chemistry totaling 274 analytes (polycyclic aromatic hydrocarbons, organochlorine compounds, polychlorinated biphenyls, polybrominated diphenyl ethers, trace elements, and current-use pesticides) and a mixture assessment based on the ratios of detected compounds to available effects-based benchmarks. The sediments were tested for toxicity with the amphipod Hyalella azteca (28-d exposure), the midge Chironomus dilutus (10-d), and, at a few sites, with the freshwater mussel Lampsilis siliquoidea (28-d). Sediment concentrations, normalized to organic carbon content, infrequently exceeded benchmarks for aquatic health, which was generally consistent with low rates of observed toxicity. However, the benchmark-based mixture score and the pyrethroid insecticide bifenthrin were significantly related to observed sediment toxicity. The sediment mixture score and bifenthrin were also significant predictors of the upper limits of several univariate measures of the macroinvertebrate community (EPT percent, MMI (Macroinvertebrate Multimetric Index) Score, Ephemeroptera and Trichoptera richness) using quantile regression. Multivariate pattern matching (Mantel-like tests) of macroinvertebrate species per site to identified contaminant metrics and sediment toxicity also indicate that the sediment mixture score and bifenthrin have weak, albeit significant, influence on the observed invertebrate community composition. Together, these three lines of evidence (toxicity tests, univariate metrics, and multivariate community analysis) suggest that elevated contaminant concentrations in sediments, in particular bifenthrin, is limiting macroinvertebrate communities in several of these Midwest streams.

Science of the Total Environment↗
USGS2017

Multistressor predictive models of invertebrate condition in the Corn Belt, USA

Understanding the complex relations between multiple environmental stressors and ecological conditions in streams can help guide resource-management decisions. During 14 weeks in spring/summer 2013, personnel from the US Geological Survey and the US Environmental Protection Agency sampled 98 wadeable streams across the Midwest Corn Belt region of the USA for water and sediment quality, physical and habitat characteristics, and ecological communities. We used these data to develop independent predictive disturbance models for 3 macroinvertebrate metrics and a multimetric index. We developed the models based on boosted regression trees (BRT) for 3 stressor categories, land use/land cover (geographic information system [GIS]), all in-stream stressors combined (nutrients, habitat, and contaminants), and for GIS plus in-stream stressors. The GIS plus in-stream stressor models had the best overall performance with an average cross-validation R 2 across all models of 0.41. The models were generally consistent in the explanatory variables selected within each stressor group across the 4 invertebrate metrics modeled. Variables related to riparian condition, substrate size or embeddedness, velocity and channel shape, nutrients (primarily NH 3 ), and contaminants (pyrethroid degradates) were important descriptors of the invertebrate metrics. Models based on all measured in-stream stressors performed comparably to models based on GIS landscape variables, suggesting that the in-stream stressor characterization reasonably represents the dominant factors affecting invertebrate communities and that GIS variables are acting as surrogates for in-stream stressors that directly affect in-stream biota.

Illinois, Indiana, Iowa, Kansas, Kentucky, Minneso↗
USGS2016

Metformin and other pharmaceuticals widespread in wadeable streams of the southeastern United States

Pharmaceutical contaminants are growing aquatic-health concerns and largely attributed to wastewater treatment facility (WWTF) discharges. Five biweekly water samples from 59 small Piedmont (United States) streams were analyzed for 108 pharmaceuticals and degradates using high-performance liquid chromatography and tandem mass spectrometry. The antidiabetic metformin was detected in 89% of samples and at 97% of sites. At least one pharmaceutical was detected at every site (median of 6, maximum of 45), and several were detected at ≥10% of sites at concentrations reported to affect multiple aquatic end points. Maximal cumulative (all detected compounds) concentrations per site ranged from 17 to 16000 ng L –1 . Watershed urbanization, water table depth, soil thickness, and WWTF metrics correlated significantly with in-stream pharmaceutical contamination. Comparable pharmaceutical concentrations and detections at sites with and without permitted wastewater discharges demonstrate the importance of non-WWTF sources and the need for broad-scale mitigation. The results highlight a fundamental biochemical link between global human-health crises like diabetes and aquatic ecosystem health.

Environmental Science & Technology Letters↗
USGS2014

Correspondence of biological condition models of California streams at statewide and regional scales

We used boosted regression trees (BRT) to model stream biological condition as measured by benthic macroinvertebrate taxonomic completeness, the ratio of observed to expected (O/E) taxa. Models were developed with and without exclusion of rare taxa at a site. BRT models are robust, requiring few assumptions compared with traditional modeling techniques such as multiple linear regression. The BRT models were constructed to provide baseline support to stressor delineation by identifying natural physiographic and human land use gradients affecting stream biological condition statewide and for eight ecological regions within the state, as part of the development of numerical biological objectives for California&rsquo;s wadeable streams. Regions were defined on the basis of ecological, hydrologic, and jurisdictional factors and roughly corresponded with ecoregions. Physiographic and land use variables were derived from geographic information system coverages. The model for the entire state ( n &thinsp;=&thinsp;1,386) identified a composite measure of anthropogenic disturbance (the sum of urban, agricultural, and unmanaged roadside vegetation land cover) within the local watershed as the most important variable, explaining 56 % of the variance in O/E values. Models for individual regions explained between 51 and 84 % of the variance in O/E values. Measures of human disturbance were important in the three coastal regions. In the South Coast and Coastal Chaparral, local watershed measures of urbanization were the most important variables related to biological condition, while in the North Coast the composite measure of human disturbance at the watershed scale was most important. In the two mountain regions, natural gradients were most important, including slope, precipitation, and temperature. The remaining three regions had relatively small sample sizes ( n &thinsp;&le;&thinsp;75 sites) and had models that gave mixed results. Understanding the spatial scale at which land use and land cover affect taxonomic completeness is imperative for sound management. Our results suggest that invertebrate taxonomic completeness is affected by human disturbance at the statewide and regional levels, with some differences among regions in the importance of natural gradients and types of human disturbance. The construction and application of models similar to the ones presented here could be useful in the planning and prioritization of actions for protection and conservation of biodiversity in California streams.

California↗
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↗
USGS2014

Contaminants of legacy and emerging concern in largescale suckers (Catostomus macrocheilus) and the foodweb in the lower Columbia River, Oregon and Washington, USA

We investigated occurrence, transport pathways, and effects of polybrominated diphenyl ether (PBDE) flame retardants and other endocrine disrupting chemicals (EDCs) in aquatic media and the foodweb in the lower Columbia River. In 2009 and 2010, foodweb sampling at three sites along a gradient of contaminant exposure near Skamania (Washington), Columbia City (Oregon) and Longview (Washington) included water (via passive samplers), bed sediment, invertebrate biomass residing in sediment, a resident fish species (largescale suckers [ Catostomus macrocheilus ]), and eggs from osprey ( Pandion haliaetus ). This paper primarily reports fish tissue concentrations. In 2009, composites of fish brain, fillet, liver, stomach, and gonad tissues revealed that overall contaminant concentrations were highest in livers, followed by brain, stomach, gonad, and fillet. Concentrations of halogenated compounds in tissue samples from all three sites ranged from < 1 to 400 nanograms per gram of wet tissue. Several chemical classes, including PBDEs, organochlorine pesticides, and polychlorinated biphenyls (PCBs), were detected at all sites and in nearly all fish tissues sampled. In 2010, only fish livers were sampled and inter-site concentration differences were not as pronounced as in 2009. Chemical concentrations in sediments, fish tissues, and osprey eggs increased moving downstream from Skamania to the urbanized sites near Columbia City and Longview. Numerous organochlorine (OC) pesticides, both banned and currently used, and PBDEs, were present at each site in multiple media and concentrations exceeded environmental quality benchmarks in some cases. Frequently detected OC compounds included hexachlorobenzene, pentachloroanisole, dichlorodiphenyltrichloroethane (DDT) and its degradates, chlorpyrifos, and oxyfluorofen. Biomagnification of BDE47, 100, 153, and 154 occurred in largescale suckers and osprey eggs. Results support the hypothesis that contaminants in the environment lead to bioaccumulation and potential negative effects in multiple levels of the foodweb.

Oregon, Washington↗
USGS2014

A survey of benthic sediment contaminants in reaches of the Columbia River Estuary based on channel sedimentation characteristics

While previous studies have documented contaminants in fish, sediments, water, and wildlife, few specifics are known about the spatial distribution of contaminants in the Columbia River Estuary (CRE). Our study goal was to characterize sediment contaminant detections and concentrations in reaches of the CRE that were concurrently being sampled to assess contaminants in water, invertebrates, fish, and osprey (Pandion haliaetus) eggs. Our objectives were to develop a survey design based on sedimentation characteristics and then assess whether sediment grain size, total organic carbon (TOC), and contaminant concentrations and detections varied between areas with different sedimentation characteristics. We used a sediment transport model to predict sedimentation characteristics of three 16 km river reaches in the CRE. We then compartmentalized the modeled change in bed mass after a two week simulation to define sampling strata with depositional, stable, or erosional conditions. We collected and analyzed bottom sediments to assess whether substrate composition, organic matter composition, and contaminant concentrations and detections varied among strata within and between the reaches. We observed differences in grain size fractions between strata within and between reaches. We found that the fine sediment fraction was positively correlated with TOC. Contaminant concentrations were statistically different between depositional vs. erosional strata for the industrial compounds, personal care products and polycyclic aromatic hydrocarbons class (Indus–PCP–PAH). We also observed significant differences between strata in the number of detections of Indus–PCP–PAH (depositional vs. erosional; stable vs. erosional) and for the flame retardants, polychlorinated biphenyls, and pesticides class (depositional vs. erosional, depositional vs. stable). When we estimated mean contaminant concentrations by reach, we observed higher contaminant concentrations in the furthest downstream reach with a decreasing trend in the two upstream reaches. Contaminant survey designs that account for sedimentation characteristics could increase the probability that sampling is allocated to areas likely to be contaminated.

Columbia River Estuary↗
USGS2013

Agricultural disturbance response models for invertebrate and algal metrics from streams at two spatial scales within the U.S.

As part of the USGS study of nutrient enrichment of streams in agricultural regions throughout the United States, about 30 sites within each of eight study areas were selected to capture a gradient of nutrient conditions. The objective was to develop watershed disturbance predictive models for macroinvertebrate and algal metrics at national and three regional landscape scales to obtain a better understanding of important explanatory variables. Explanatory variables in models were generated from landscape data, habitat, and chemistry. Instream nutrient concentration and variables assessing the amount of disturbance to the riparian zone (e.g., percent row crops or percent agriculture) were selected as most important explanatory variable in almost all boosted regression tree models regardless of landscape scale or assemblage. Frequently, TN and TP concentration and riparian agricultural land use variables showed a threshold type response at relatively low values to biotic metrics modeled. Some measure of habitat condition was also commonly selected in the final invertebrate models, though the variable(s) varied across regions. Results suggest national models tended to account for more general landscape/climate differences, while regional models incorporated both broad landscape scale and more specific local-scale variables.

Hydrobiologia↗
USGS2013

Development and application of an agricultural intensity index to invertebrate and algal metrics from streams at two scales

Research was conducted at 28-30 sites within eight study areas across the United States along a gradient of nutrient enrichment/agricultural land use between 2003 and 2007. Objectives were to test the application of an agricultural intensity index (AG-Index) and compare among various invertebrate and algal metrics to determine indicators of nutrient enrichment nationally and within three regions. The agricultural index was based on total nitrogen and phosphorus input to the watershed, percent watershed agriculture, and percent riparian agriculture. Among data sources, agriculture within riparian zone showed significant differences among values generated from remote sensing or from higher resolution orthophotography; median values dropped significantly when estimated by orthophotography. Percent agriculture in the watershed consistently had lower correlations to invertebrate and algal metrics than the developed AG-Index across all regions. Percent agriculture showed fewer pairwise comparisons that were significant than the same comparisons using the AG-Index. Highest correlations to the AG-Index regionally were −0.75 for Ephemeroptera, Plecoptera, and Trichoptera richness (EPTR) and −0.70 for algae Observed/Expected (O/E), nationally the highest was −0.43 for EPTR vs. total nitrogen and −0.62 for algae O/E vs. AG-Index. Results suggest that analysis of metrics at national scale can often detect large differences in disturbance, but more detail and specificity is obtained by analyzing data at regional scales.

Journal of the American Water Resources Associatio↗
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

Predicting biological condition in southern California streams

As understanding of the complex relations among environmental stressors and biological responses improves, a logical next step is predictive modeling of biological condition at unsampled sites. We developed a boosted regression tree (BRT) model of biological condition, as measured by a benthic macroinvertebrate index of biotic integrity (BIBI), for streams in urbanized Southern Coastal California. We also developed a multiple linear regression (MLR) model as a benchmark for comparison with the BRT model. The BRT model explained 66% of the variance in B-IBI, identifying watershed population density and combined percentage agricultural and urban land cover in the riparian buffer as the most important predictors of B-IBI, but with watershed mean precipitation and watershed density of manmade channels also important. The MLR model explained 48% of the variance in B-IBI and included watershed population density and combined percentage agricultural and urban land cover in the riparian buffer. For a verification data set, the BRT model correctly classified 75% of impaired sites (B-IBI < 40) and 78% of unimpaired sites (B-IBI = 40). For the same verification data set, the MLR model correctly classified 69% of impaired sites and 87% of unimpaired sites. The BRT model should not be used to predict B-IBI for specific sites; however, the model can be useful for general applications such as identifying and prioritizing regions for monitoring, remediation or preservation, stratifying new bioassessments according to anticipated biological condition, or assessing the potential for change in stream biological condition based on anticipated changes in population density and development in stream buffers.

California↗
USGS2011

Columbia River Estuary ecosystem classification—Concept and application

This document describes the concept, organization, and application of a hierarchical ecosystem classification that integrates saline and tidal freshwater reaches of estuaries in order to characterize the ecosystems of large flood plain rivers that are strongly influenced by riverine and estuarine hydrology. We illustrate the classification by applying it to the Columbia River estuary (Oregon-Washington, USA), a system that extends about 233 river kilometers (rkm) inland from the Pacific Ocean. More than three-quarters of this length is tidal freshwater. The Columbia River Estuary Ecosystem Classification ("Classification") is based on six hierarchical levels, progressing from the coarsest, regional scale to the finest, localized scale: (1) Ecosystem Province; (2) Ecoregion; (3) Hydrogeomorphic Reach; (4) Ecosystem Complex; (5) Geomorphic Catena; and (6) Primary Cover Class. We define and map Levels 1-3 for the entire Columbia River estuary with existing geospatial datasets, and provide examples of Levels 4-6 for one hydrogeomorphic reach. In particular, three levels of the Classification capture the scales and categories of ecosystem structure and processes that are most tractable to estuarine research, monitoring, and management. These three levels are the (1) eight hydrogeomorphic reaches that embody the formative geologic and tectonic processes that created the existing estuarine landscape and encompass the influence of the resulting physiography on interactions between fluvial and tidal hydrology and geomorphology across 230 kilometers (km) of estuary, (2) more than 15 ecosystem complexes composed of broad landforms created predominantly by geologic processes during the Holocene, and (3) more than 25 geomorphic catenae embedded within ecosystem complexes that represent distinct geomorphic landforms, structures, ecosystems, and habitats, and components of the estuarine landscape most likely to change over short time periods.

Columbia River Estuary↗
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↗