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Water Levels Impacting Great Lakes Coastal Wetlands: An update of metric development Donald Uzarski, Mathew Cooper, and Brent Murry June 14, 2010.

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Presentation on theme: "Water Levels Impacting Great Lakes Coastal Wetlands: An update of metric development Donald Uzarski, Mathew Cooper, and Brent Murry June 14, 2010."— Presentation transcript:

1 Water Levels Impacting Great Lakes Coastal Wetlands: An update of metric development Donald Uzarski, Mathew Cooper, and Brent Murry June 14, 2010

2 Contents Invertebrate community metrics –Les Cheneaux Islands Region of N. Lake Huron Fish assemblage metrics –Saginaw Bay Invertebrate and fish response to vegetation zone loss –Saginaw Bay and northern Lake Huron

3 Invertebrate community metrics Background and Hypothesis Many studies suggest that changes in hydrology do produce significant changes in macrophyte community composition. Results of our past published studies relate macroinvertebrate community composition to dominate vegetation types with pronounced differences among types. Here we attempt to develop indicators while keeping vegetation type and depth relatively constant, therefore isolating the effect of annual water level. We hypothesized a shift in macroinvertebrate community composition related to water level change and direction that was independent of depth and dominant vegetation type. A shift of this nature could be used to infer fine scale changes in ecosystem structure and function related to hydrology.

4 Methods - Invertebrates Study Sites –Les Cheneaux Islands Region of N. Lake Huron. –10 Fringing Coastal Wetlands. Macroinvertebrate Samples –Collected from Schoenoplectus 1997 – 2002 –Water Levels Declined ~ 1 m. –Followed Migration of Plant Zone w/Declining Water –D-Frame Dip Net –3 Replicates Per Site Per Year Data Analysis –NMDS of Most Data Rich Site (Mackinac Bay) –Pearson Correlation – Mean Water Level and Dim 1 –Determined Abundant Taxa Most Responsible

5 Pearson Correlation r = ; p = Significant Correlation between NMDS Dim 1 and Water Levels Keeping Plant Zone Constant Keeping Depth Constant Caenidae and Asellidae Weighted Heaviest in the Relationship Mackinaw Bay the most data-rich site

6 The collector/gatherer Caenidae Populations Seems to Reflect the Previous Years Water Levels

7 The Shredder Asellidae Populations Seems to Reflect the Previous Years Water Levels

8 At all 10 Les Cheneaux fringing wetland sites

9 The collector/gatherer Caenidae Populations Seems to Reflect the Previous Years Water Levels

10 The Shredder Asellidae Populations Seems to Reflect the Previous Years Water Levels

11 Discussion – invertebrate metrics Water depth and the dominant vegetation type was kept constant yet there was still a significant relationship between invertebrate community composition and water levels. This was likely driven, in part, by a shift from a detritus based food web to and algal based food web. As water levels rose, more protected areas with denser vegetation were inundated with water. Through time, the deeper water with more hydrologic energy likely reduced vegetation density resulting in an abundance of detritus favoring shredders and collector/gatherers. As water levels declined, areas of sparse vegetation became benign allowing sunlight to penetrate gradually favoring algae. During declining water level years, scrapers trended towards becoming more abundant, but there was no significant relationship between their numbers and water levels.

12 Conclusions – invertebrate metrics Macroinvertebrates metrics that respond to changes in water level and direction independent of large scale vegetation shifts can be developed. There appears to be a shift from shredders and collector/gatherers to grazers as water levels decline. This shift may be the result of the wetland moving from a detritus based food web in response to rising water levels to an algal based food web as water levels decline. Rising and falling water levels result in a temporally diverse macroinvertebrate community as well as dynamic ecosystem structure and function.

13 Fish assemblage metrics Water level drivers derived from several components of the natural flow regime concept Fish assemblage attributes investigated thus far include: –Total mean abundance –Species richness –Simpson evenness

14 NATURAL FLOW REGIME MAGNITUDE FREQUENCY DURATION TIMING RATE OF CHANGE WATERENERGYPHYSICALBIOTA QUALITYSOURCESHABITAT ECOLOGICAL INTEGRITY (modified from Poff et al. 1997)

15 Water Level Metrics Magnitude * Timing –Logic Water elevation (magnitude) affects wetland area which will influence the species abundance and composition Monthly changes (timing) in WL elevation will differentially affect habitat use of species depending on their unique life histories –Metrics: Monthly (March – Aug.) mean, min., max. water level (m) Monthly (March – Aug.) change (STDEV)

16 Water Level Metrics Rate of Change –Logic: Environmental cues including (primarily) photoperiod, temperature, and (secondarily) water level changes initiate spawning activity in fish and potentially metamorphosis and emergence of some invertebrates Broad seasonal changes and timing relative to photoperiod (equinox and solstice key photoperiod endpts.) are potentially important cues –Metrics Winter to summer rate of WL change –(July mean WL - Jan Mean WL) / # days –assumed Jan 15th and July 15th for # days count, leap years = 182 (2000, 2004, 2008), otherwise 181 Rate of WL change spring equinox to summer solstice –Calc as June mean WL - March mean WL / 92 days (March 21 to June 21 = 92 days)

17 Saginaw Bay Fish Data – Primary Response Variables Total mean CPUE –GLCWC standardized trap-nets –Inner and outer Schoenoplectus zones Species Richness –Not presently rarified, very different # fish among sites but same effort –Inner and outer Schoenoplectus zones Simpson Evenness –Inner and outer Schoenoplectus zones Simpson Diversity –Inner and outer Schoenoplectus zones

18 Ecoregion regionHabitat ZoneYear Total # nets #Nets for Model Development # Nets for model validation Saginaw Bay Inner Schoenoplectus Saginaw Bay Inner Schoenoplectus Saginaw Bay Inner Schoenoplectus Saginaw Bay Inner Schoenoplectus Saginaw Bay Inner Schoenoplectus Saginaw Bay Outer Schoenoplectus Saginaw Bay Outer Schoenoplectus Saginaw Bay Outer Schoenoplectus Saginaw Bay Outer Schoenoplectus Saginaw Bay Outer Schoenoplectus Sample distribution among years and zones

19 Annual sites sampled and effort EcoregionYearSite NameTotal # nets Saginaw Bay2002Bradleyville3 Saginaw Bay2002Pinconning6 Saginaw Bay2002Vanderbilt Park6 Saginaw Bay2002Wigwam Bay6 Saginaw Bay2002Wildfowl Bay3 Saginaw Bay2003Almeda Beach3 Saginaw Bay2003Nyanquing3 Saginaw Bay2003Vanderbilt Park3 Saginaw Bay2003Wigwam Bay6 Saginaw Bay2004Wigwam Bay3 Saginaw Bay2004Bayport4 Saginaw Bay2004Linwood Beach3 Saginaw Bay2004Nyanquing3 Saginaw Bay2004Whites Beach3 Saginaw Bay2006Pinconning6 Saginaw Bay2006Sebawing6 Saginaw Bay2006Wigwam Bay6 Saginaw Bay2006Vanderbilt Park6 Saginaw Bay2008Pinconning6 Saginaw Bay2008Vanderbilt Park3 Saginaw Bay2008Wigwam Bay6

20 Outer Schoenplectus Total Mean Fish Abundance Mean Total Fish Abundance = -70, * MaxMayWL – 20,629 * STDEVMayWL + 46,926 * STDEVJulyWL Model based on 5 years: 2002, 2003, 2004, 2006, 2008 Adj. r 2 = 0.99, F 3,4 = 13,036.2, P = Predictions tend to underestimate abundance Strong correlation between observed and predicted, but there is 1 high leverage point (influential) 1:1 line

21 Outer Schoenplectus Fish Species Richness Model based on five years: 2002, 2003, 2004, 2006, 2008 SpR = – 4, * Rate of WL increase Spring Equinox – Summer Solstice R2 = 0.90, F1,4 = P = R 2 = 0.59 Moderate correlation between observed and predicted species richness model tended to over-estimate species richness

22 Outer Schoenplectus Fish Assemblage Simpson Evenness Evaluation based on 5 years: 2002, 2003, 2004, 2006, 2008 Simpson Evenness = no suitable model found –The only significant model showed high multicollinearity and poor observed/predicted concordance

23 Summary of water level influence on fish abundance and diversity – Outer Schoenplectus Fish responseWL attributeDirection of influence Total mean abundance May max. WL May WL STDEV July WL STDEV Species richnessRate of change Equinox – solstice - Simpson evennessn/a

24 Inner Schoenplectus Total Mean Fish Abundance Mean Total Fish Abundance = , * AprilWLSTDEV – 5, *MayWLSTDEV – * JulyWLRange Model based on 5 years: 2002, 2003, 2004, 2006, 2008 Adj. r 2 = 1.00; F 3,4 = 5,688,984; P = Three of four years predictions were near 1:1 line, but a fourth year (2004) was predicted far lower than observed resulting in a relatively weak correlation between observed and predicted

25 Inner Schoenplectus Fish Assemblage Species Richness Evaluation based on 5 years: 2002, 2003, 2004, 2006, 2008 Species richness = no suitable model found –A significant model was found but predictions were extremely poorly correlated to observed values (r 2 = 0.01)

26 Inner Schoenplectus Fish Assemblage Simpson Evenness Fish Simpson Evenness = – *JuneMinWL * MayWLSTDEV – * AugWLrange Model based on 5 years: 2002, 2003, 2004, 2006, 2008 Adj. r 2 = 1.00; F 3,4 = 3.69x10 9 ; P < Strong correlation between observed and predicted, though one data point (2008) again appears to have a strong influence on this relationship Points are well distributed along 1:1 line

27 Summary of water level influence on fish abundance and diversity – Inner Schoenplectus Fish responseWL attributeDirection of influence Total mean abundance April WL STDEV May WL STDEV July WL range Species richnessn/a Simpson evennessJune min. WL May WL STDEV Aug WL range

28 Conclusions Variance in monthly water levels, in particular May, appear to have the most impact on fish abundance and diversity. –May WL variance was negatively associated with fish abundance in both the inner and outer Schoenoplectus zones, but was positively associated with fish assemblage evenness in the inner zone. –Water level variance likely influences the habitat quality perceived by spawning fish during and may limit reproductive effort and/or success (short-term stranding of eggs in shallow water during low water events, seiches combined with low levels). –Greater WL variance in July and August is associated with lower total abundance and evenness in the inner zone, but higher abundance in the outer zone. This likely reflects fluctuations in the inner zone that reduces water depth and habitat quality pushing fishes into deeper water. Fewer species remain in the inner zone during periods of high fluctuations reducing evenness (i.e. dominance of a few species that remain under generally unfavorable conditions). Species richness in the outer zone was negatively related to the rate of WL increase between the spring equinox and the summer solstice. –The rate of WL change relative to photoperiod (i.e. equinox and solstice) and water temperature is a common cue to many fish species to initiate spawning and other life history actions. –As the rate of WL change increases this may alter habitat suitability conditions, reduce spawning activity or cause young-of-the-year fish to move out of the wetland areas during nursery, alternatively it may allow greater predation pressure as higher water levels might increase large fish use of this habitat type for foraging.

29 Invertebrate and fish community response to vegetation loss or zone contraction A likely response to a reduction in water level variability would be the loss of emergent vegetation or a contraction of emergent vegetation zones. Such changes reduce the area of inundated vegetated habitat for fish and invertebrates. Since macrophytes provide a number of critical resources for fauna, we predict a reduction in the productivity and diversity of these groups if water level variability is reduced and vegetation zones contract. Results from one published study (Uzarski et al. 2009) and one unpublished study (Cooper et al. In Prep) comparing faunal community composition from vegetated and adjacent unvegetated areas provide insight on the likely consequences of such changes.

30 Seven paired (vegetated and unvegetated) sites in Saginaw Bay. Vegetation was dominated by bulrushes. Sampling was conducted in Summer, Triplicate timed dip-net samples. Nets were swept through upper sediment layer for three minutes. Taxa were sorted to lowest operational taxonomic unit in the laboratory. Methods:

31 Unvegetated habitats dominated by small taxa, especially midge larvae (Chironomidae), biting midge larvae (Bezzia), and water mites (Hydracarina) while vegetated sites were dominated by larger taxa such as amphipods and a number of snail taxa. Taxon richness in the vegetated habitats (17.9 ± 1.0) was significantly higher (p = 0.031) than in the open water zones (9.5 ± 1.1). Results: A loss or contraction of vegetated habitat is very likely to have significant impacts on macroinvertebrate community structure. These changes are likely to also affect organisms higher in the food chain such as fish and birds. Conclusions:

32 Comparison of zooplankton, larval fish, and macroinvertebrate communities between vegetated and adjacent unvegetated habitats Methods: Quatrefoil light traps were set overnight in 16 fringing marshes of Lake Huron Compared vegetated and unvegetated habitats. Sampling conducted in Summer of from Cooper et al. (In Prep): GREAT LAKES COASTAL MARSH FRAGMENTATION: EDGE AND AREA EFFECTS ON ZOOPLANKTON, MACROINVERTEBRATE, AND LARVAL FISH COMMUNITIES

33 Mean ( ±SE): Paired t-tests UnvegetatedVegetatedp: Zooplankton CPUE17,356±6,68487,775±47, Richness6.6±0.96.0± Shannon diversity1.17± ± AFDM (g)0.168± ± Macroinvertebrat es CPUE440±86912± Richness8.9± ±0.91<0.01 Shannon diversity0.88± ± Larval fish CPUE7±247± Richness1.3±0.32.7±0.4<0.01 Shannon diversity0.24± ± Results:

34 Conclusions: Macroinvertebrate richness and Shannon diversity were significantly higher in vegetated habitats relative to unvegetated habitats. Larval fish CPUE, richness and Shannon diversity were significantly higher in vegetated habitat relative to unvegetated habitats. Changes to water level regime that result in a loss or constriction of vegetation will likely have significant impacts on these faunal groups.


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