Grantee Research Project Results
Final Report: Ecological Thresholds and Responses of Stream Benthic Communities to Heavy Metals
EPA Grant Number: R832441Title: Ecological Thresholds and Responses of Stream Benthic Communities to Heavy Metals
Investigators: Clements, William , Noon, Barry , Wang, Haonan
Institution: Colorado State University
EPA Project Officer: Packard, Benjamin H
Project Period: July 31, 2005 through December 30, 2007 (Extended to December 30, 2008)
Project Amount: $295,760
RFA: Exploratory Research: Understanding Ecological Thresholds In Aquatic Systems Through Retrospective Analysis (2004) RFA Text | Recipients Lists
Research Category: Aquatic Ecosystems , Water
Objective:
The primary goal of our research was to identify and validate ecological thresholds for stream communities impacted by heavy metal contamination from historic mining operations. We hypothesize that the location of ecological thresholds along a well-defined gradient of metal contamination varies among state variables and is influenced by local (reach-scale) and landscape-level environmental drivers. We integrated results of 16 microcosm experiments and two spatially extensive surveys of > 150 Colorado streams to identify ecological thresholds along a gradient of heavy metal contamination. For the purposes of this project, we define an ecological threshold (Xr ) as a metal concentration that, when exceeded, results in pronounced changes in the values of one or more state variables. Using parametric and nonparametric regression techniques, we identified thresholds for state variables across several levels of biological organization. To validate and test the ecological significance of these thresholds, we examined long-term changes in response variables in a mining impacted stream where metal concentrations were recently reduced below threshold levels.
Summary/Accomplishments (Outputs/Outcomes):
Figure 1. Results of locally weighted polynomial regression (LWPR) analysis (a)
and SiZer (b) showing the relationships between conductivity and a multimetric
index. A LWPR model fitted to the dta at 3 bandwidths shows 95 percent
confidence intervals. Color changes in the SiZer map indicate significant changes
in the 1st derivative. Reading from left to right at any given value of h, a significantly
decreasing 1st derivative is showin in red and a zero derivative is shown in purple.
The horizontal distance between the white lines = 2h and represents the effective
width of the locally weighted polynomial. At h = 0.25 (log10 h = -0.6), the first
derivative changed from 0 to significantly negative at approximately 1.7 (= 55 µS/cm).
Figure 2. Application of locally weighted polynomial regression (upper panels) and SiZer
analysis (lower panels) to locate ecological thresholds for 153 streams in Colorado. Metal
the measured dissolved-metal concentration to the hardness-adjusted U.S. EPA criteria
maximum concentration for each metal. The thresholds for total macroinvertebrate
abundance and species richness are indicated by the arrows. Color changes in teh SiZer
map indicate significant changes in the 1st derivative. See Fig. 1 for details.
Figure 3. Application of locally weighted polynomial regression (upper panels)
and SiZer (lower panels) to locate ecological thresholds based on the mesocosm
experiments. Color changes in the SiZer map indicate significant changes in the 1st
derivative. Same color scheme as Fig. 1 except that a significantly increasing 1st
Figure 4. Long-term variation in Zn concentrations at the
Arkansas River, Co.
Figure 5. a. Results of locally weighted polynomial regression analysis showing the relationship between
abundance of metal-sensitive taxa and year at 3 bandwidths. The SiZer map (b) shows changes to the
1st derivative as a function of year and bandwidth. Reading rrom left to right at any given value of h, a
significantly increasing 1st derivative is shown in yello and possibly zero derivative is shown in purple.
The 2 horizontal dashed lines show bandwidths corresponging to the 2 smaller values in 5a. At a
bandwidth of 2.0 (log10 h = 0.30), the 1st derivative changed significantly from positive to 0 in 2003
(arrow). At a smaller bandwidth of 1.0 (log10 h = 0.0) there are several instances where the 1st
derivative changed significantly, reflecting hte elevated metal levels observed in the mid 1990's and
final recovery of the system.
Figure 6. Canonical descriminant analysis of the Arkansas River data based on abundance of 20
dominant taxa. The figure shows means (± s.e.) of canonical variables 1 and 2 by year (1989-2006)
and the percent of cariation explained by each canonical variable. b. Results of locally weighted
polynomial regression analyses showing the relationship between canonical variable 1 and year
(h = 1.0). c. SiZer map showing changes in the 1st derivative as a function of year and bandwidth.
Reading from left to right at a specific value for h, a significantly increasing 1st derivative is shown in
yellow, decreasing is red and 0 is purple. The SiZer map shows three distinct thresholds where
benthic communities changes abruptly betwen 1989 and 2006.
Figure 7. Left: CCU versus time along wit hthe smoothing function. Right: The
number of mayflies versus naive CCU (solid line) and de-noised CCU (dashed line).
Parameters | Naive estimator | De-noised estimator | |||||
N | Bias | Length | Coverage | Bias | Length | Coverage | |
30 | -0.006 | 0.480 | 0.952 | -0.002 | 0.441 | 0.934 | |
Ô<<σ | 60 | -0.002 | 0.340 | 0.950 | 0.003 | 0.326 | 0.939 |
120 | -0.005 | 0.240 | 0.951 | 0.000 | 0.265 | 0.946 | |
30 | -0.281 | 0.538 | 0.442 | 0.004 | 0.71 | 0.943 | |
Ô<<σ | 60 | -0.293 | 0.372 | 0.125 | 0.003 | 0.476 | 0.940 |
120 | -0.301 | 0.262 | 0.004 | 0.006 | 0.340 | 0.946 | |
30 | -0.611 | 0.488 | 0.002 | 0.030 | 1.631 | 0.940 | |
Ô<<σ | 60 | -0.628 | 0.329 | 0.000 | 0.010 | 0.885 | 0.944 |
120 | -0.635 | 0.228 | 0.000 | 0.003 | 0.568 | 0.939 |
Conclusions:
Journal Articles on this Report : 32 Displayed | Download in RIS Format
Other project views: | All 45 publications | 38 publications in selected types | All 32 journal articles |
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Bellwood DR, Hughes TP, Folke C, Nystrom M. Confronting the coral reef crisis. Nature 2004;429(6994):827-833. |
R832441 (Final) |
Exit |
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Bernhardt ES, Palmer MA, Allan JD, Alexander G, Barnas K, Brooks S, Carr J, Clayton S, Dahm C, Follstad-Shah J, Galat D, Gloss S, Goodwin P, Hart D, Hassett B, Jenkinson R, Katz S, Kondolf GM, Lake PS, Lave R, Meyer JL, O'donnell TK, Pagano L, Powell B, Sudduth E. Ecology. Synthesizing U.S. river restoration efforts. Science 2005;308(5722):636-637. |
R832441 (Final) |
not available |
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Berumen ML, Pratchett MS. Recovery without resilience:persistent disturbance and long-term shifts in the structure of fish and coral communities at Tiahura reff, Moorea. Coral Reefs 2006;25:647-653. |
R832441 (Final) |
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Carpenter SR, Ludwig D, Brock WA. Management of eutrophication for lakes subject to potentially irreversible change. Ecological Applications 1999;9(3):751-771. |
R832441 (Final) |
Exit |
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Chaudhuri P, Marron JS. Scale space view of curve estimation. The Annals of Statistics 2000;28(2):408-428. |
R832441 (Final) |
Exit |
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Clements WH. Metal tolerance and predator-prey interactions in benthic macroinvertebrate stream communities. Ecological Applications 1999;9(3):1073-1084. |
R832441 (Final) |
Exit |
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Clements WH, Carlisle DM, Lazorchak JM, Johnson PC. Heavy metals structure benthic communities in Colorado mountain streams. Ecological Applications 2000;10(2):626-638. |
R832441 (Final) |
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Clements WH. Small-scale experiments support causal relationships between metal contamination and macroinvertebrate community responses. Ecological Applications 2004;14(3):954-967. |
R832441 (Final) R829515 (2003) R829515 (2004) R829515 (Final) |
Exit |
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Clements WH, Brooks ML, Kashian DR, Zuellig RE. Changes in dissolved organic material determine exposure of stream benthic communities to UV-B radiation and heavy metals: implications for climate change. Global Change Biology 2008;14(9):2201-2214. |
R832441 (Final) |
Exit |
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Clements WH, Rohr JR. Community responses to contaminants: using basic ecological principles to predict ecotoxicological effects. Environmental Toxicology and Chemistry 2009;28(9):1789-1800. |
R832441 (Final) R833835 (2009) R833835 (2010) R833835 (2011) R833835 (Final) |
Exit Exit Exit |
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Clements WH, Kashian D, Sonderegger D, Noon B, Vieira N. The use of ecological thresholds to assess recovery in lotic ecosystems. Journal of North American Benthological Society 2010;29(3):1017-1023. |
R832441 (Final) |
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Connell JH, Sousa WP. On the evidence needed to judge ecological stability or persistence. American Naturalist 1983;121(6):789-824. |
R832441 (Final) |
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Courtney LA, Clements WH. Sensitivity to acidic pH in benthic invertebrate assemblages with different histories of exposure to metals. Journal of the North American Benthological Society 2000;19(1):112-127. |
R832441 (Final) |
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Dodds WK, Clements WH, Gido K, Hilderbrand RH. Thresholds, breakpoints, and nonlinearity in freshwaters as related to management. Journal of the North American Benthological Society 2010;29(3):988-997. |
R832441 (Final) |
and Society for Freshwater Science Exit |
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Durance I, Ormerod SJ. Climate change effects on upland stream macroinvertebrates over a 25-year period. Global Change Biology 2007;13(5):942-957. |
R832441 (Final) |
Exit Exit Exit |
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Folke C, Carpenter S, Walker B, Scheffer M, Elmqvist T, Gunderson L, Holling CS. Regime shifts, resilience, and biodiversity in ecosystem management. Annual Review of Ecology, Evolution, and Systematics 2004;35:557-581. |
R832441 (Final) |
Exit |
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Goldstein JN, Hubert WA, Woodward DF, Farag AM, Meyer JS. Naturalized salmonid populations occur in the presence of elevated trace element concentrations and temperatures in the Firehole River, Yellowstone National Park, Wyoming, USA. Environmental Toxicology and Chemistry 2001;20(10):2342-2352. |
R832441 (Final) |
not available |
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Groffman PM, Baron JS, Blett T, Gold AJ, Goodman I, Gunderson LH, Levinson BM, Palmer MA, Paerl HW, Peterson GD, Poff NL, Rejeski DW, Reynolds JF, Turner MG, Weathers KC, Wiens J. Ecological thresholds: the key to successful environmental management or an important concept with no practical application? Ecosystems 2006;9(1):1-13. |
R832441 (Final) R828012 (Final) R828677C001 (Final) R832445 (Final) |
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Huggett AJ. The concept and utility of 'ecological thresholds' in biodiversity conservation. Biological Conservation 2005;124(3):301-310. |
R832441 (Final) |
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Lake PS, Bond N, Reich P. Linking ecological theory with stream restoration. Freshwater Biology 2007;52(4):597-615. |
R832441 (Final) |
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May RM. Thresholds and breakpoints in ecosystems with a multiplicity of stable states. Nature 1977;269:471-477. |
R832441 (Final) |
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Muradian R. Ecological thresholds: a survey. Ecological Economics 2001;38(1):7-24. |
R832441 (Final) |
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Nimick DA, Gammons CH, Cleasby TE, Madison JP, Skaar D, Brick CM. Diel cycles in dissolved metal concentrations in streams:occurrence and possible causes. Water Resources Research 2003;39(9):1247-1264. |
R832441 (Final) R829400E01 (2002) R829400E02 (Final) |
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Penttinen S, Kostamo A, Kukkonen JVK. Combined effects of dissolved organic material and water hardness on toxicity of cadmium to Daphnia magna. Environmental Toxicology and Chemistry 1998;17(12):2498-2503. |
R832441 (Final) |
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Poole GC, Dunham JB, Keenan DM, Sauter ST, Mccullough DA, Mebane C, Lockwood JC, Essig DA, Hicks MP, Sturdevant DJ, Materna EJ, Spalding SA, Risley J, Deppman M. The case for regime-based water quality standards. BioScience 2004;54(2):155-161. |
R832441 (Final) |
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Qian SS, King RS, Richardson CJ. Two statistical methods for the detection of environmental thresholds. Ecological Modelling 2003;166:87-97. |
R832441 (Final) |
Exit Exit |
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Scheffer M, Carpenter S, Foley JA, Folke C, Walker B. Catastrophic shifts in ecosystems. Nature 2001;413:591-596. |
R832441 (Final) |
Exit Exit |
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Scheffer M, Carpenter SR. Catastrophic regime shifts in ecosystems:linking theory to observation. Trends in Ecology & Evolution 2003;18(12):648-656. |
R832441 (Final) |
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Smith JG ,Beauchamp JJ, Stewart AJ. Alternative approach for establishing acceptable thresholds on macroinvertebrate community metrics. Journal of the North American Benthological Society 2005;24(2):428-440. |
R832441 (Final) |
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Sonderegger DL, Wang H, Clements WH, Noon BR. Using SiZer to detect thresholds in ecological data. Frontiers in Ecology and the Environment 2009;7(4):190-195. |
R832441 (2008) R832441 (Final) |
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Sonderegger DL, Wang H, Huang Y, Clements WH. Effects of measurement error on the strength of concentration-response relationships in aquatic toxicology. Ecotoxicology 2009;18(7):824-828. |
R832441 (Final) |
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Yuan LL. Effects of measurement error on inferences of environmental conditions. Journal of the North American Benthological Society 2007;26(1):152-163. |
R832441 (Final) |
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Supplemental Keywords:
Ecological thresholds, ecosystems, benthic communities, streams, metal contamination, heavy metals, RFA, Scientific Discipline, Ecosystem Protection/Environmental Exposure & Risk, POLLUTANTS/TOXICS, Aquatic Ecosystems & Estuarine Research, Chemicals, Aquatic Ecosystem, Environmental Monitoring, Ecology and Ecosystems, Ecological Risk Assessment, anthropogenic stress, estuarine research, ecological thresholds, anthropogenic impact, ecosystem indicators, modeling ecosystem change, stream habitat, benthic indicators, aquatic ecosystems, water quality, ecosystem stress, riverine ecosystems, trophic interactions, aquatic ecosystem restoration, ecosystem response, environmental historyProgress and Final Reports:
Original AbstractThe perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.