temporal response patterns in fish and benthic ... · null hypothesis testing ho1: aquatic...

Temporal response patterns in fish Temporal response patterns in fish

and benthic invertebrate and benthic invertebrate

communities in streams of the communities in streams of the

North Central and Northeastern North Central and Northeastern

U.S.U.S.� Jason May-California

� Amanda Bell-Wisconsin

� Jonathan Kennen- New Jersey

� Dan Sullivan-Wisconsin

� Karen Beaulieu-Connecticut

US Geological Survey-WRD

National Water-Quality Assessment Program Surface-Water Regions (Major River Basins)

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Null Hypothesis Testing

� Ho1: Aquatic assemblages will not exhibit significant changes in composition over time.

� Ho2: Fish and invertebrate assemblages will not differ in their response to environment degradation.

� Ho3: Aquatic assemblages response will not be related to temporal changes in environmental processes.

� Ho4 Natural variability does not influence temporal changes in assemblage composition.

� HA1: Sites which have been significantly altered over time periods prior to or exceeding the NAWQA sampling effort will show little or no trends in biotic assemblages and/or abiotic parameters.

Types of potential trends response

patterns/trajectories for specific

sites over time

� No response

� Upward/downward trends

� Recover trends

� Caveats

� Pre-disturbed prior our sampling

� Human influenced

� Antecedent Influenced conditions

Identify changes in Biota over time

(Temporal Separation)

Effects of Natural

Variability

2: BiologicalCondition

1:TaxonomicComposition

3: SpeciesTraits

Land UseHydrologyQW Habitat

Assemblage Trajectory over time – Examplehdsn12cs, 2/7/2009 8:41:34 PM

LISHA KILL NORTHWEST OF NISKAYUNA NYTransform: Square root

Resemblance: S17 Bray Curtis similarity

1993

1994

1995

2002

2003

2004

2005

2006

2D Stress: 0.01

Departure Distance (=temporal separation)

hdsn12cs, LISHA KILL NORTHWEST OF NISKAYUNA NYGroup average

20

06

20

05

20

03

20

04

19

94

19

93

19

95

20

02

Samples

100

80

60

40

Sim

ilari

ty

Transform: Square root

Resemblance: S17 Bray Curtis s imilarity

�Null hypothesis: “No tendency to show temporal separation”.�In general: assemblages with adjacent samples are closest in species composition, those further apart differ the most.

Same site

Inverts-significant

change over time

&

fish-N.S.

19 9 3

1 99 4

19 9 5

20 0 2

2 00 3

2 00 4

20 0 5

20 0 6

(√)-S tress : 0 .01LISHA-INVT

1 99 3

19 9 4

1 99 5

20 0 2

20 0 3

2 00 4

20 0 5

2 00 8

(√√)-Stress: 0.05LISHA-FISH

Data ElementsData Elements� 32 sites within NC-NE US (MRB 1 & 3), 5 larger river sites dropped after

some initial analyses

� Sites were required to have at least 6 years of sequential invertebrate and fish data to be included in these analyses- mean of 8 years of data max 11yrs

� A single year ‘best’ representative sample was selected for each site

� Biotic Data: � Inverts & fish assemblage , metrics, and species traits data

� Abiotic Data� Habitat information

� Chemistry� Field parameters, Major Ions, Nutrients, DOC and Pesticides

� Single sample prior ecology sample� Mean monthly average across the year of the ecology sample� Pesticide toxicity index (PTI) information

� Stream flow statistics that encompass timing, magnitude, duration, etc.

� GIS: (GIRAS, NLCDe 1992/1995, NLCDe 2001 )� PRISM-Climatic data precipitation and air temperature

Spatial Distribution of NC-NE Trend Sites

MRB1&3 Focus Sites For PresentationMRB1&3 Focus Sites For Presentation

Clinton River

Little Buck Cr.

Green River

Analysis road mapAnalysis road mapPreparatory phase:

-Data aggregation and QA

Exploratory phase:

-Data and range screening and outlier evaluation

-Data reduction, univariate, and multivariate analyses

-Initial model development

-Identifying subset of ancillary variables

Finalizing analyses phase:

-Final model development

-Evaluating potential effects of natural env. variability

Overview of presentation:Overview of presentation:� Highlight significant temporal changes in assemblage

composition

� Highlight the level of consistency in patterns among assemblage and environmental indicators

� Show example relations for inverts/fish with habitat, QW, and hydrology

� Show an example of response patterns within site type and address the question whether we can group responses by site type

Summary of Significant Assemblage Summary of Significant Assemblage

Trajectories (TRENDS) by Site TypeTrajectories (TRENDS) by Site Type

InvertebratesInvertebrates

URB AG REF INT Total

8/11 5/9 2/7 4/5 19/3219/32

FishFish


6/11 5/9 4/7 0/5 15/3215/32

BothBoth


5/11 3/9 2/7 0/5 10/3210/32

00.10.20.30.40.50.60.70.80.9

** **

****

****

**

****

** **

*

INVT

FISH**- p <0.05* - p<0.10

Urban Sites: Urban Sites: Strength of Strength of Assemblage Trajectories over timeAssemblage Trajectories over time

-0.2-0.1

00.10.20.30.40.50.60.70.8

**

**

** ****INVT

FISH**- p <0.05* - p<0.10

Reference Sites: Reference Sites: Strength of Strength of Assemblage Trajectories over timeAssemblage Trajectories over time

Urban Land Use Change at NCUrban Land Use Change at NC--NE SitesNE Sites

Urban site in suburban Indianapolis

� Changing from AG to URB LU- (1992-2001 NLCDe)

� Little Buck Creek (13%)

Urban Example: Little Buck Creek -45 km2

-headwater stream occasionally goes dry. -GW public supply well located near this site

1992

2000

20092005

Little Buck recent time series

LITTLE BUCK CREEK NEAR INDIANAPOLIS, INTransform: Square root


1993

1994

1995

1997

1998

2002

2003

2004

2D Stress: 0.03LITTLE BUCK CREEK NEAR INDIANAPOLIS, INGroup average

199

3

199

7

199

8

200

4

200

2

200

3

199

4

199

5

Samples

100

80

60

40

20

Sim

ilarity



Ancillary Variables Indicative of change over time:StreamFlow Variables:-Freq. low pulse spells(#events/yr)Habitat:-Wetted X AreaQW:pH

Little Buck Creek continued.

Little Buck examples of trends of select fish, invert, habitat, Little Buck examples of trends of select fish, invert, habitat,

hydrology parametershydrology parameters

GREEN RIVER AT STEWARTVILLE, MATransform: Square root


1993

1994

19952002 2003

20042005

2006

2007

2D Stress: 0.09

conn11cs, GREEN RIVER AT STEWARTVILLE, MAGroup average

2007

1993

1994

1995

2005

2006

2004

2002

2003

Samples

100

80

60

40

20

Sim

ilarity



Ancillary Variables Indicative of change over time:StreamFlow Variables:-Mean Annual Max daily flows (cfs)-Mean Min May flows over POR-Rise Rate (CFS/day)Habitat:Bank Vegetative Cover, Wetted shape, Froude

-107 km2

-Cold water-Gravel/Cobble-Some logging influences

Reference site example: Green River

Green River examples of trends of select fish, invert, habitat, Green River examples of trends of select fish, invert, habitat,

QW parametersQW parameters

CLINTON RIVER AT STERLING HEIGHTS, MITransform: Square root


1996

1997

1998

2002

2003

2004

20052006

2007

2D Stress: 0.03

Urban Example: Clinton RiverUrban Example: Clinton River

Ancillary Variables Indicative of change over time:StreamFlow Variables:-Mean Min May flows over PORHabitat:%Riffles, CV of Open Canopy, %Embedd, FroudeQW: Ave P, Ave_pH

Urban site in suburban Detroit

CLINTON RIVER AT STERLING HEIGHTS, MIGroup average

1996

1997

1998

2005

2006

2004

2002

2003

2007

Samples

100

80

60

40

20

Sim

ilarity



-803 km2

~80% flow from GW-Sewage treatment plant ~1km US-Highly permeable soils

Clinton River Invert. Clinton River Invert.

Richness BasedRichness Based--TraitsTraits

Number Generations per year

Quick Adult lifespan Collector-Filters

Dispersal Ability

Clinton River examples of trends of select fish, invert, Clinton River examples of trends of select fish, invert,

habitat, QW parametershabitat, QW parameters

Habitat

Fish

*Single QW

Inverts

Can we generalized site type response Can we generalized site type response

patterns?patterns?

� We can see some similarity in responses to ancillary variables across sites within a site type (e.g., URB or AG)

� But size, climate, and biogeographical differences represent a significant influence

� Our real power for understanding trends is best evaluated on a individual site basis

Urban InvertebratesUrban Invertebrates

AG InvertebratesAG InvertebratesHYDRO HABITAT QW

Important Variables Important Variables Important Variables

DH1, DH21, DH5, MA20, ML13 Riff%, BKVegCov, Frd, BO%, OTH% P, pH

DH21, FL3, ML5 HydRad, Depth SC, pH

FH9, FL3 W_cv, BFD, BKER, Emb SC

FL3, MA20, ML15 BKVegCov, Emb, Wetshap, Hydrad,SA% NH4

ML13, MH7 Riff%,RUN%, BFW, BKER, SA% NO2NO3

DH21, FL3, ML5 Pool%, D, BKER, SA%, OTH% NO2NO3

FH9, MA15, ML5 BFD, BKvegCov, HydRad, Si% pH

DH21, DL5, FH9, MA15, MA20 W_cv, BKvegCov, BKER,OC, Si% P, pH

ML5 W_cv, OC, WetArea, SI%, OTH% NH4

HYDRO HABITAT QW

Important Variables Important Variables Important Variables

DH1, DH21, DL5, TA2 BKER, Frd P, pH

MA20 Depth_ave NH4, P

RA1, RA3, TA2 Riff%, BFD, WetShape NH4, SC

MA15, MA20, ML5, MH7Riff%, Embed%, OC_Cv, WetSh, Frd

P, pH

DL5, DH21 Pool/riff, D, BKER, WetShape, BO% P, pH

DH1, RA1W/D, BKvegCov, BKER, CO%, OTH% NO2NO3, SC, pH

FL3, MA15, ML13, RA3 D_cv, WetArea, pH

DH21, MA20, ML15 W-cv, BFD, OC, CO_PCT NO2NO3, pH

DL, FH9, FL3, MA20 D,W/D, BKER, WP, BO_p NO2NO3, pH

DL5, MH6, ML13, ML3 Depth_cv NH4, pH

DH1, DH21, DL5, MA15, MA20Pool/riff, Si%, SA%, OTH% P

Summary of findingsSummary of findings--

NC/NE trend sitesNC/NE trend sites

� Established significant patterns of change in fish and invertebrate assemblages at 15 and 19 sites, respectively

� Ten of which are sites significant for both

� We delineated some of the potential mechanisms influencing these assemblages (i.e. habitat, QW, hydrology parameters accounting change)

� Noted some consistency of indicators over time

� Although we can see some similarities for sites within particular site type (AG or URB), the real strength of our analyses is to look at individual site patterns over time

Take home points Take home points

from these trends studies so farfrom these trends studies so far� Change in assemblage composition was evident, but response

differed relative to assemblage type.

� Hydrologic variability appears to be a major factor most of our analyses

� Difficulties with attributing the change in community patterns to ancillary variables.

� Accounting for climatic variability is very important

� Sample size is important-the more data more likely ability to detect change over time.

temporal response patterns in fish and benthic ... · null hypothesis testing ho1: aquatic...

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