22 research outputs found

    Long-Term Variability in Bioassessments: A Twenty-Year Study from Two Northern California Streams

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    Long-term variability of bioassessments has not been well evaluated. We analyzed a 20-year data set (1984–2003) from four sites in two northern California streams to examine the variability of bioassessment indices (two multivariate RIVPACS-type O/E scores and one multimetric index of biotic integrity, IBI), as well as eight metrics. All sites were sampled in spring; one site was also sampled in summer. Variability among years was high for most metrics (coefficients of variation, CVs ranging from 16% to 246% in spring) but lower for indices (CVs of 22–26% for the IBI and 21–32% for O/E scores in spring), which resulted in inconsistent assessments of biological condition. Variance components analysis showed that the time component explained variability in all metrics and indices, ranging from 5% to 35% of total variance explained. The site component was large (i.e., >40%) for some metrics (e.g., EPT richness), but nearly absent from others (e.g., Diptera richness). Seasonal analysis at one site showed that variability among seasons was small for some metrics or indices (e.g., Coleoptera richness), but large for others (e.g., EPT richness, O/E scores). Climatic variables did not show consistent trends across all metrics, although several were related to the El Niño Southern Oscillation Index at some sites. Bioassessments should incorporate temporal variability during index calibration or include climatic variability as predictive variables to improve accuracy and precision. In addition, these approaches may help managers anticipate alterations in reference streams caused by global climate change and high climatic variability

    How Low Can You Go?: Widespread Challenges in Measuring Low Stream Discharge and a Path Forward

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    Low flows pose unique challenges for accurately quantifying streamflow. Current field methods are not optimized to measure these conditions, which in turn, limits research and management. In this essay, we argue that the lack of methods for measuring low streamflow is a fundamental challenge that must be addressed to ensure sustainable water management now and into the future, particularly as climate change shifts more streams to increasingly frequent low flows. We demonstrate the pervasive challenge of measuring low flows, present a decision support tool (DST) for navigating best practices in measuring low flows, and highlight important method developmental needs

    Characterizing benthic macroinvertebrate and algal biological condition gradient models for California wadeable Streams, USA

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    The Biological Condition Gradient (BCG) is a conceptual model that describes changes in aquatic communities under increasing levels of anthropogenic stress. The BCG helps decision-makers connect narrative water quality goals (e.g., maintenance of natural structure and function) to quantitative measures of ecological condition by linking index thresholds based on statistical distributions (e.g., percentiles of reference distributions) to expert descriptions of changes in biological condition along disturbance gradients. As a result, the BCG may be more meaningful to managers and the public than indices alone. To develop a BCG model, biological response to stress is divided into 6 levels of condition, represented as changes in biological structure (abundance and diversity of pollution sensitive versus tolerant taxa) and function. We developed benthic macroinvertebrate (BMI) and algal BCG models for California perennial wadeable streams to support interpretation of percentiles of reference-based thresholds for bioassessment indices (i.e., the California Stream Condition Index [CSCI] for BMI and the Algal Stream Condition Index [ASCI] for diatoms and soft-bodied algae). Two panels (one of BMI ecologists and the other of algal ecologists) each calibrated a general BCG model to California wadeable streams by first assigning taxa to specific tolerance and sensitivity attributes, and then independently assigning test samples (264 BMI and 248 algae samples) to BCG Levels 1–6. Consensus on the assignments was developed within each assemblage panel using a modified Delphi method. Panels then developed detailed narratives of changes in BMI and algal taxa that correspond to the 6 BCG levels. Consensus among experts was high, with 81% and 82% expert agreement within 0.5 units of assigned BCG level for BMIs and algae, respectively. According to both BCG models, the 10th percentiles index scores at reference sites corresponded to a BCG Level 3, suggesting that this type of threshold would protect against moderate changes in structure and function while allowing loss of some sensitive taxa. The BCG provides a framework to interpret changes in aquatic biological condition along a gradient of stress. The resulting relationship between index scores and BCG levels and narratives can help decision-makers select thresholds and communicate how these values protect aquatic life use goals

    Reach-scale models show heterogeneity of stream benthic invertebrate responses to eutrophication stress

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    Statistical stressor-response models are a common approach to derive biologically relevant water quality criteria for the management of waterbody health. These types of models are typically derived at state-wide or ecoregional scales and consequently incorporate a large amount of natural and disturbance-related variability that may obscure the relationship that one is interested in quantifying. We demonstrate an alternative approach termed “reach-specific modeling” to identify potential biological response thresholds to eutrophication in the Santa Margarita River watershed (California, U.S.A.). Individual models of benthic invertebrate response to eutrophication stress were created for both bioassessment sampling sites and NHD + stream-segments in the watershed (46 sites, 832 segments). Each model was built using only data from environmentally similar sites from a state-wide dataset to minimize variation from natural environmental gradients, while allowing eutrophication stress to vary. Thresholds of potential biological impact were extracted from each stressor-response model. Across the whole watershed thresholds varied from location-to-location: total nitrogen (1.14–1.26 mg L-1 TN), total phosphorus (0.12–0.15 mg L-1 TP), benthic algal biomass (29–39 mg m−2 benthic chl-a), and benthic ash-free dry mass (2.5––3.0 mg cm−2 AFDM). Notably, nearly all of the thresholds derived from these reach-specific models were ∼10–90 % higher than those from a similar state-wide model. Furthermore, there were a number of spatial groupings of thresholds for each eutrophication indicator across the watershed, suggesting reach-scale natural gradients in hydrogeomorphology and natural land cover type may mediate the stressor-biology interaction. Reach-scale models tended to have better fits than their state-wide counterparts, but had equivalent or slightly worse accuracy. The reach-specific approach to threshold development illustrates that the biological response to stress is likely not uniform within a single system, much less between systems. As a consequence, this approach can allow managers to identify systems that are more sensitive or resistant to a given stressor across diverse landscapes and make better informed decisions on their management accordingly

    Evaluating ethanol-based sample preservation to facilitate use of DNA barcoding in routine freshwater biomonitoring programs using benthic macroinvertebrates.

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    Molecular methods, such as DNA barcoding, have the potential to enhance biomonitoring programs worldwide. Altering routinely used sample preservation methods to protect DNA from degradation may pose a potential impediment to application of DNA barcoding and metagenomics for biomonitoring using benthic macroinvertebrates. Using higher volumes or concentrations of ethanol, requirements for shorter holding times, or the need to include additional filtering may increase cost and logistical constraints to existing biomonitoring programs. To address this issue we evaluated the efficacy of various ethanol-based sample preservation methods at maintaining DNA integrity. We evaluated a series of methods that were minimally modified from typical field protocols in order to identify an approach that can be readily incorporated into existing monitoring programs. Benthic macroinvertebrates were collected from a minimally disturbed stream in southern California, USA and subjected to one of six preservation treatments. Ten individuals from five taxa were selected from each treatment and processed to produce DNA barcodes from the mitochondrial gene cytochrome c oxidase I (COI). On average, we obtained successful COI sequences (i.e. either full or partial barcodes) for between 93-99% of all specimens across all six treatments. As long as samples were initially preserved in 95% ethanol, successful sequencing of COI barcodes was not affected by a low dilution ratio of 2∶1, transfer to 70% ethanol, presence of abundant organic matter, or holding times of up to six months. Barcoding success varied by taxa, with Leptohyphidae (Ephemeroptera) producing the lowest barcode success rate, most likely due to poor PCR primer efficiency. Differential barcoding success rates have the potential to introduce spurious results. However, routine preservation methods can largely be used without adverse effects on DNA integrity

    Proportion of specimens successfully amplified for two different sequence length criteria, Partial barcodes (top) and Full barcodes (bottom).

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    <p>Replicates are represented by different shapes (circles, pluses and triangles). Treatment designations (A–F) are as indicated in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0051273#pone-0051273-t001" target="_blank">Table 1</a>.</p

    Cumulative frequency graphs of sequence length (base pairs) by treatment.

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    <p>Circles represent the points at which additional sequences are accumulated. Dashed horizontal lines represent the cutoff between partial barcodes (to the left) and full barcodes (to the right).</p
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