Water Levels Impacting Great Lakes Coastal Wetlands: An update of metric development

Water Levels Impacting Great Lakes Coastal Wetlands: An update of metric

development

Donald Uzarski, Mathew Cooper, and Brent Murry

June 14, 2010

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

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.

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

Invertebrate Community Compostions and 1997-2002 Water Levels Mackinac Bay, Northern Lake Huron

Lake Huron/Michigan Water Levels (m)

175.8 176.0 176.2 176.4 176.6 176.8 177.0 177.2

Inve

rteb

rate

Com

mun

ity C

ompo

sitio

n

(N

MD

S D

imen

sion

1 (

48%

))

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

Scrapers

Shredders

Collector/Gatherers

Pearson Correlationr = -0.823; p = 0.044

Significant Correlation between NMDS Dim 1 and Water Levels

Keeping Plant Zone ConstantKeeping Depth Constant

Caenidae and Asellidae Weighted Heaviest in the Relationship

Mackinaw Bay the most data-rich site

Invertebrate Community 1997-2002 Water Levels Mackinac Bay, Northern Lake Huron


175.8 176.0 176.2 176.4 176.6 176.8 177.0 177.2

Ca

enid

ae

Nu

mb

ers

0

10

20

30

40

50

60

70

Pearson Correlationr = 0.823p = 0.044

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

Invertebrate Community 1997-2002 Water Levels Mackinac Bay, Northern Lake Huron


175.8 176.0 176.2 176.4 176.6 176.8 177.0 177.2

Ase

llid

ae

Nu

mb

ers

0

10

20

30

40

50

60

70


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

Lakes Michigan and Huron

Year

1995 1996 1997 1998 1999 2000 2001 2002 2003

Wat

er L

evel

s (m

)

175.8

176.0

176.2

176.4

176.6

176.8

177.0

177.2

Invert Data Seem to Reflect the Previous Year

At all 10 Les Cheneaux fringing wetland sites

Invertebrate Community 1997-2002 Water Levels Northern Lake Huron (10 Sites)


175.8 176.0 176.2 176.4 176.6 176.8 177.0 177.2

Ca

en

ida

e M

ea

n N

um

be

rs

1

0 S

ites

0

5

10

15

20

25


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

Invertebrate Community 1997-2002 Water Levels 10 Northern Lake Huron Sites


175.8 176.0 176.2 176.4 176.6 176.8 177.0 177.2

Ase

llida

e M

ean

Num

bers

5

10

15

20

25

30

35

40

Pearson CorrelationNS

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

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.

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.

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

NATURAL FLOW REGIME

MAGNITUDE FREQUENCY DURATION TIMING RATE OF CHANGE WATER ENERGY PHYSICAL BIOTA

QUALITY SOURCES HABITAT

ECOLOGICAL INTEGRITY (modified from Poff et al. 1997)

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)

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)

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

Ecoregion region Habitat Zone YearTotal #

nets#Nets for Model

Development# Nets for model

validation

Saginaw BayInner

Schoenoplectus 2002 12 8 4

Saginaw BayInner


Saginaw BayInner


Saginaw BayInner


Saginaw BayInner


Saginaw BayOuter


Saginaw BayOuter


Saginaw BayOuter


Saginaw BayOuter


Saginaw BayOuter


Sample distribution among years and zones

Annual sites sampled and effort

Ecoregion Year Site Name Total # nets

Saginaw Bay 2002 Bradleyville 3

Saginaw Bay 2002 Pinconning 6

Saginaw Bay 2002 Vanderbilt Park 6

Saginaw Bay 2002 Wigwam Bay 6

Saginaw Bay 2002 Wildfowl Bay 3

Saginaw Bay 2003 Almeda Beach 3

Saginaw Bay 2003 Nyanquing 3




Saginaw Bay 2004 Bayport 4

Saginaw Bay 2004 Linwood Beach 3

Saginaw Bay 2004 Nyanquing 3

Saginaw Bay 2004 Whites Beach 3


Saginaw Bay 2006 Sebawing 6






Outer Schoenplectus Total Mean Fish Abundance

Mean Total Fish Abundance = -70,897 + 398.53526 * MaxMayWL – 20,629 * STDEVMayWL + 46,926 * STDEVJulyWL

• Model based on 5 years: 2002, 2003, 2004, 2006, 2008• Adj. r2 = 0.99, F3,4 = 13,036.2, P = 0.0064

• Predictions tend to underestimate abundance• Strong correlation between observed and predicted, but there is 1 high

leverage point (influential)

R2 = 0.928

0

100

200

300

400

500

600

700

800

900

0 200 400 600 800 1000

Observed mean total fish abundance (CPUE)

Pre

dic

ted

me

an

to

tal f

ish

a

bu

nd

an

ce

(C

PU

E) 1:1 line

Outer Schoenplectus Fish Species Richness

6

8

10

12

14

16

18

20

0 0.001 0.002 0.003 0.004 0.005

Rate of WL increase spring equinox to summer solstice (m/day)

Ob

se

rve

d s

pe

cie

s r

ich

ne

ss

o

ute

r S

ch

on

op

lec

tus

0

5

10

15

20

25

0 5 10 15 20 25

Observed species richness outer Schoenoplectus zone

Pre

dic

ted

sp

ec

ies

ric

hn

es

s

ou

ter

Sc

ho

en

ple

ctu

s z

on

e

1:1 line

Model based on five years: 2002, 2003, 2004, 2006, 2008

SpR = 32.02170 – 4,918.77561 * Rate of WL increase Spring Equinox – Summer Solstice

R2 = 0.90, F1,4 = 26.60 P = 0.0141

R2 = 0.59

• Moderate correlation between observed and predicted species richness• model tended to over-estimate species richness

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

Summary of water level influence on fish abundance and diversity – Outer Schoenplectus

Fish response WL attribute Direction of influence

Total mean abundance

May max. WL

May WL STDEV

July WL STDEV

+

-

+

Species richness Rate of change

Equinox – solstice

-

Simpson evenness n/a n/a

Inner Schoenplectus Total Mean Fish Abundance

Mean Total Fish Abundance = 422.43192 + 1,726.87296 * AprilWLSTDEV – 5,366.62844 *MayWLSTDEV – 249.52950 * JulyWLRange

• Model based on 5 years: 2002, 2003, 2004, 2006, 2008

• Adj. r2 = 1.00; F3,4 = 5,688,984; P = 0.0003

• 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

R2 = 0.39

0

50

100

150

200

250

0 50 100 150 200 250

Observed mean total fish abundance (CPUE)

Pre

dic

ted

mea

n t

ota

l fi

sh

abu

nd

ance

(C

PU

E)

1:1 line

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 (r2 = 0.01)

Inner Schoenplectus Fish Assemblage Simpson Evenness

Fish Simpson Evenness = 8.21008 – 0.04826*JuneMinWL + 15.70754 * MayWLSTDEV – 2.05742 * AugWLrange

• Model based on 5 years: 2002, 2003, 2004, 2006, 2008• Adj. r2 = 1.00; F3,4 = 3.69x109; P < 0.0001

• 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

R2 = 0.75

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0 0.1 0.2 0.3 0.4 0.5 0.6

Observed Simpson evenness

Pre

dic

ted

Sim

ps

on

e

ve

nn

es

s

Summary of water level influence on fish abundance and diversity – Inner Schoenplectus

Fish response WL attribute Direction of influence

Total mean abundance

April WL STDEV

May WL STDEV

July WL range

+

-

-

Species richness n/a n/a

Simpson evenness June min. WL

May WL STDEV

Aug WL range

-

+

-

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.

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 ofemergent 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.

• Seven paired (vegetated and unvegetated) sites in Saginaw Bay. Vegetation was dominated by bulrushes. Sampling was conducted in Summer, 2005.

• 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:

• 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:

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 2005.

from Cooper et al. (In Prep): GREAT LAKES COASTAL MARSH FRAGMENTATION: EDGE AND AREA

EFFECTS ON ZOOPLANKTON, MACROINVERTEBRATE, AND LARVAL FISH COMMUNITIES

Mean ( ±SE): Paired t-

testsUnvegetated Vegetated p:

ZooplanktonCPUE 17,356±6,684 87,775±47,836 0.19

Richness 6.6±0.9 6.0±0.8 0.07

Shannon diversity 1.17±0.10 1.08±0.20 0.64

AFDM (g) 0.168±0.067 0.552±0.265 0.17

MacroinvertebratesCPUE 440±86 912±433 0.3

Richness 8.9±0.7 12.3±0.91 <0.01


Larval fishCPUE 7±2 47±20 0.08

Richness 1.3±0.3 2.7±0.4 <0.01


Results:

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.

Water Levels Impacting Great Lakes Coastal Wetlands: An update of metric development

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