Instruments and how to program and down-load data from a

PRESENTATIONS

Training Workshop on Marine and Coastal Environmental Monitoring Methods

15-17 February 2009 Zayed University, Dubai, UAE

Geórgenes Cavalcante, UNU‐INWEH, Dubai, UAE Oceanographic Equipment Data processing and management, QA/QC and Preliminary Data Analysis

John Burt, Zayed University, Dubai, UAE UNU‐INWEH EMPs for NMPs in DXB: Overview of Coral Monitoring

Ken Drouillard, GLIER, University of Windsor, Canada Sediment chemistry studies

Paolo Usseglio, UNU‐INWEH, Dubai, UAE Monitoring Fish Communities ‘One Fish Two Fish Red Fish Blue Fish: Fish

Censusing Made Easy'

Setting up a Field Sampling Programme: Staff, Field Instruments & Logistical Requirements for Sampling

Peter Sale, UNU‐INWEH, Canada

Building a Coastal Management Plan

Geórgenes Cavalcante

ContentsTypes of instruments

CharacteristicsApplications

How to install them?Programming a ADCPDownloading data from an ADCP

GPS

Handheld Depth Sounder

Types of instruments

CTD HOBO CT

ADCP

CTD

A profiling Conductivity‐Temperature‐Depth (CTD) probe with internal recording is required for transect sampling.

ConductivityT tTemperatureOxygenpHTurbidityFluorescence

ADCPs use the Doppler effect by transmitting sound at a fixed frequency and listening to echoes returning from sound scatterers in the water.

ADCPs are typically used to create ADCPs are typically used to create profiles of water velocity in everything from open oceans to inland streams, waves, tides and are ideal for time series measurements.

Vc = Vraw ‐ Vb

ADCP ‐ Acoustic Doppler Current Profilers

Deployment

After 30 days

Programming an ADCP

Downloading Data

Geórgenes Cavalcante

ContentsImportanceMetadataData storageDubai case studyyQuality accuracy and Quality controlData analysis

Data inspectionData plottingHarmonic analysisSpectral analysis

ImportanceUtility of physical data in ecological studiesOptimize information and measurements

Selection of parameterspDetermination of sampling rateChoice of duration of measurementsGood design = optimized effort and cost

Define analyses and software

MetadataWhat is metadata?

Structured data which describes the characteristics of a resource

What data are added to a metadata base?ParametersData and timeData and timePosition of the measurementMeasurement of water depthTotal water depth

Why use metadata?Information resources must be made visible in a way that allows people to tell whether the resources are likely to be useful to them.

Metadata

Data storage

Dubai case study

Design and ParametersObjective

Develop a clear understanding of the spatial and temporal variability of parameters, especially the water movement at the variability of parameters, especially the water movement at the various Nakheel Marine Projects (NMPs).

How to obtain informationStationary and additional stationsSpatial and temporal resolution

How to characterize the coastal environment

Movement of water through the system and water budgetAccessing wind and tidal effects Offshore waves characteristicsLongshore sediment transport, accumulation and erosiong p ,Distribution of temperature and salinity

Types of dataTime series from fixed locations

Current speed and directionWind speed and directionTidal elevationSignificant wave height direction frequencySignificant wave height, direction, frequencyHydrographic parameters

Spatial distribution of above parametersTransect measurementsRemote sensing

Quality accuracy and Quality controlQA – ensures that process is defined and appropriate

Methodology and standards development exemplify QAQA review focuses on process elements of a project

QC – ensures activities evaluate a developed work productTesting is one example of a QC activityInspections

Data analysisData inspectionTime seriesVector and scalar dataOrthogonal decompositionOrthogonal decomposition

Data plottingHarmonic analysisSpectral analysis

Data inspectionQuality control

Check suspect or outliers data due:Sensor limitations, biological growth (barnacle, algae), battery power

How to proceed: Electronic spreadsheet through software programValues that lay more than three standard deviations away from the mean of any time (or space) series are suspect

Time seriesVector and scalar data

The wind and current is described as having both a direction and a magnitude (speed), and it is therefore a vector quantity.Scalar ‐ Current speed and tidal elevation

Orthogonal decomposition

)sin(φVuv

=

)cos(φVvv

=

)sin( δαφ ±±= Vuv

)cos( δαφ ±±= Vvv

δαφ Current direction

Magnetic declination

Coastal alignment

Different conventions:

westerly wind westward current

Meteorology Oceanography

)sin(φVuv

−=

)cos(φVvv

−=

Currents Winds

)sin( δαφ ±±= Vuv

)cos( δαφ ±±= Vvv

Data plotting

Palm Jumeirah3D Bathymetry

10 20 30 40 50

30

60300

330

0Current Vectors Time Series for Bin: 2.

210

240

9070

120

150

180

Harmonic AnalysisTidal water level harmonics constituents

Name of partial tide Symbol Period East Entrance

(EE) West Entrance

(WE) Bridge Trunk

(BT) Atlantis Monorail

(AM) Jebel Ali Port

(JAP) (hrs) H (cm) G (º) H (cm) G (º) H (cm) G (º) H (cm) G (º) H (cm) G (º) Long term components Solar semi-annual Ssa 2191.43 - - - - - - - - 4.4 282Lunar monthly Mm 661 30 - - - - - - - - 1 7 169Lunar monthly Mm 661.30 1.7 169 Diurnal components Elliptical lunar Q1 26.87 3.1 83 2.9 83 2.8 79 3.1 80 3.5 77Principal lunar O1 25.82 18.4 101 18.4 99 18.8 99 18.8 100 17.0 101Luni-solar K1 23.93 20.7 157 21.1 157 21.4 156 21.6 157 27.0 153 Semidiurnal components Larger lunar elliptic N2 12.66 9.9 334 9.6 335 9.8 330 9.9 333 9.8 335Principal lunar M2 12.42 44.2 0 43.1 0 45.0 358 44.8 0 44.8 359Principal solar S2 12.00 15.5 44 15.0 42 16.3 43 15.6 44 17.6 47Luni-solar K2 11.97 4.2 48 4.1 49 4.4 47 4.3 48 5.2 30 Shallow-water First M2 over-tide M4 6.21 2.6 0 2.4 358 2.6 354 2.5 1 1.9 359

Spectral AnalysisA procedure that decomposes a time series into a spectrum of cycles of different lengths

Example: Sunspot activity is cyclical, reaching a maximum about every 11 years

3/4/2009

1

UNU-INWEH EMPs for NMPs in DXB

Overview of Coral MonitoringJohn BurtAndrew Bauman

Overview of Coral Monitoring

General Monitoring Methods• Number of sites depends on question• Haphazard placement for ‘general’

picture of community structure• At each site▫ Six 30 m transects▫ Photoquadrat every 1.5 m

Image: P. Jokiel, CRAMP

General Monitoring Methods▫ Photos edited & coded in Photoshop

JR1_21May07_3_07

General Monitoring Methods▫ Corals/Benthos analyzed in CPCe

▫ Download from:▫ http://www nova edu/ocean/cpce/▫ http://www.nova.edu/ocean/cpce/

General Monitoring Methods▫ Results added to Excel file for subsequent analysis

3/4/2009

2

What are the patterns of community development on breakwaters?

1 yr1.5 yr3.5 yr

5.5 yr31 yr

25 yr

Cov

er (%

)

Age

Coral Community Structure

Stress: 4.4

Permanent Vs Haphazard Quadrats

• Permanent quadrats allow understanding of specific temporal changes

• Cover, growth, demographicsg g p▫ 10 permanent quadrats per site▫ Monitored quarterly

3/4/2009

3

Does exposure influence coral community development?

Windward BreakwaterLeeward BreakwaterNatural Reef

Coral Cover

Leeward sites had fewer, smaller colonies

Coral Demographics (mean ± SE colonies m-2)

Recruitment Mortality

Site Summer Fall Winter Spring Summer Fall Winter SpringSite Summer Fall Winter Spring Summer Fall Winter Spring

PJ1 1.7 ± 0.8 0.6 ± 0.6 2.3 ± 0.8

PJ2 0.8 ± 0.8 1.6 ± 0.7

PJ3 2.0 ± 1.5 0.5 ± 0.5 1.0 ± 0.7

PJ4 1.5 ± 0.7 1.0 ± 0.7 1.0 ± 0.8 1.0 ± 0.9

Relative Impacts of Mortality Coral Growth

3/4/2009

4

Summary

• Haphazard quadrats can be used to assess general patterns▫ Replication in space and time depends on needs▫ Replication in space and time depends on needs

• Permanent quadrats useful for detailed understanding of demography and growth▫ Time consuming, but useful for certain questions

Ken DrouillardGreat Lakes Institute for Environmental Research,

University of Windsor, Ontario, Canada

Sediment Chemistry Studies

U e s y o dso , O a o, Ca ada

Sediment Assessment Objectives

• Contrast Sediment Contamination Against Sediment Quality Guidelines

• Detect large or smaller scale spatial gradientsgradients– Near field vs. far field effects

• Establish mass balance that can be used for dredging decisions

• Detect changes in sediment contamination over time

• Assess toxicity, bioavailability of contaminants to organisms

Sediment Quality Objectives (Ontario, Canada)

Sediment Quality Objectives (Ontario, Canada)

Sampling Considerations-Balancing comprehensiveness against cost/effort-Provide data & interpretation to managers in a timely manner-Temporal re-sampling / scale of spatial analysis

Weight of Evidence Approaches-Compile data from variety of different programs-Often hindered by ‘Directed sampling approaches’ i.e. frequent targeting of hot spotsfrequent targeting of hot spots-How compatible are data?

-Timing of sample collections-Spatial boundaries & site selection criteria-Similar sampling design & methodology?-Comparability of analytical methods?

-Can be powerful if different monitoring programs adhere to set of guiding principles & common framework

Sampling Designs•BACI, Upstream/Downstream, Effect-Based Sampling

•Designed to contrast ‘concern area’ with ‘reference site’•Localized, synoptic sampling with low capability for

ti l t l tispatial extrapolation•Sediments Move !!!!•Compilation of many BACI designs leads to poor Weightof-Evidence data base if this is the only information available

Lake Huron Outlet

Roberts LandingPort Lambton

Lake St Clair

Trenton Ch

Fleming Ch

Amherstburg Ch

Whole-Water Sampling Sites

St Clair and Detroit Rivers

2001 & 2002.

Ontario Canada

Geostatistical Designs•Grid and Transect Sampling Designs

•Often used to document change in distribution with time. E.g. trends at fixed sampling stations

•Assumes smooth spatial distribution of measured parameters

Can miss hot spots and/or deposition areas•Can miss hot spots and/or deposition areas•In consistent with mass balance & statistical test assumptions•Useful for GIS mapping•Locations of deposition areas can periodically change due to stochastic events

Lake Huron Outlet

Roberts LandingPort Lambton

Whole-Water Sampling Sites

St Clair and Detroit Rivers

2001 & 2002.

. .. . . .

Lake St Clair

Trenton Ch

Fleming Ch

Amherstburg Ch

Ontario Canada

. . . . . . .. . . . . . .. . . . . . .

Geostatistical Designs•Randomization designs

•Equal probability of sampling all areas within geographic boundary

•Complete randomization may lead to poor sample dispersion

E i t l h t it it t t•Environmental heterogeneity necessitates greater sampling intensity

•Process:-Grid generated over study area

(Size of grid = dispersion criteria)-Each grid square given unique identifier number-Use random number generator to pick sampling stations

Stratified random design-Compromise between Grid and Randomization-Samples randomly allocated within pre-selected strata-Station is the unit of replication-Allows statistical testing for differences between strata-Ensures sample dispersion, conserves sampling costs

Geostatistical Designs (Cont.)

-Can compensate for environmental heterogeneity if strata selected based on underlying factors controllingvariability (e.g. water flow, bathymetry etc)

-Strata mean±SD provides localized reference point forhigh resolution sampling programs

-Well suited to deducing regional-scale temporal trends if design is implemented over multiple years

Lake St. Clair StationsUpper Canadian

-7 Analyzed Stations-6 Alternate Unanalyzed Stations

Lower Canadian-11 Analyzed Stations-5 Alternate Unanalyzed Stations

Upper U.S.Upper U.S.-7 Analyzed Stations-5 Alternate Unanalyzed Stations

Lower U.S.-8 Analyzed Stations-10 Alternate Unanalyzed Stations

Sample Collection & Processing

•Grab samplers; Corers

•Issues: Efficiency of grab sampler varies by sediment type

Grab samplers best for soft siltsGrab samplers – best for soft, silts - inefficient on

sands/cobbles

Cores – preservestemporal structure

Diversity of Sediment Types…. Sample Collection & ProcessingField Processing -Multiple Grabs Taken to Achieve 1 L “Organics” and 1.5 L “Trace Elements + Mercury + Grain size” Samples-Homogenization on-vessel of multiple grabs, collection of sediments into pre-cleaned polyethylene bags or solvent rinsed 500 mL mason jarsrinsed 500 mL mason jars

Laboratory Processing-Trace element, Hg and organic contaminants analysis conducted on pre-sieved (2mm mesh) samples

Auxiliary Variables-Grain size analysis conducted on whole sediments-TOC Content, AVS (metals bioavailability)

Case Study: Huron-Erie Corridor Sediment Quality Studies

– On a Corridor-Scale Basis:• Evaluate Sediment Contamination for Conventional

Pollutants (Geostatistical Approach)

Project Objectives:

– Provide Regional Database of Sediment Quality:• Better Interpretation of Localized, High Res. Studies

– (i.e. mass balance studies within RAPs)• Baseline Study for Monitoring Temporal Recovery on

a System-Wide Scale• Compare with 1999 Detroit River Survey

•Entire Corridor-Mixing Waters St. Clair River-L. Huron to Mixing Waters of Detroit River – L. Erie

2004 Sediment Quality Studies in the Huron-Erie Corridor

Scope of Project

•Stratified Random Sampling Design (100 Stations + 59 Alternates)

•Equal Sampling Intensity in U.S./Canadian Waters•Emphasis on near-shore (< 5.5 m depth)•Sample dispersion: 100 m (St. Clair River & Delta), 1000 m (Lake St. Clair)

Geostatistical Design/Site Selection

Localization of sampling sites

Huron Corridor 2004

St. Clair River (SCR)

St. Clair Delta (SCD)

St. Clair Lake (SCL)Detroit River (DR)

HCB in Sediments of the Corridor(Marker for HOC-Dispersion)

1

10

100

mg/

g O

C w

eigh

t)

LEL = 0.9 μg/g OC weight

B

SCRUSA

SCDUSA

SCLUSA

DRUSA

SCRCA

SCDCA

SCLCA

DRCA

HCB Displays Pattern Consistent with Can. LSR – Source with Downstream Dispersion

mean value

25, 75 percentile

min-max range1E-3

0.01

0.1

HC

B C

once

ntra

tion

(m

LEL 0.9 μg/g OC weight

(mean TOC = 2.13%)A A A A

B

AA

1999 Detroit River Sediment Assessment

-150 stations stratified random design-6 Strata: Upper, Middle, Lower Can/US-grain size distribution determined-chemical analysis on <2 mm size fraction

Zone 1-CDN (10%)%Area=6.4%

Zone 1-US (10%)%Area=9.3%

Zone 2-CDN (10%)%Area=3.2%

Zone 2-US (10%)%Area=3.1%

-Sediment Chemistry-Benthic Community Identification

%Area 3.2%

Zone 3-US (30%)%Area=45.3% Zone 3-CDN

30%)%Area=32.7%

PCBs in Detroit River Sediments (1999)

Upper

Middle0.01

0.1

1

10

100

B C

once

ntra

tion

(µg·

g-1 O

C w

eigh

t) Can.

ON LEL

ON PEL 530 ug/g

0 2

Kilometers

4

#

•44 (38 U.S.; 6 Canadian) Sites Exceeded MOE LEL for PCBs (70 ng/g dry wt.); 0 SEL’s

•Csed Elevated Mainly On U.S. Side of River

Upper Middle Lower Upper Middle Lower

Lower

1E-3

tota

l PC

B

U.S

1

10

100

5

6

28

31

33

35

4445

47

48

6063

5859

6567

68

69 7071

72

73

7481

8384

85

86

88

9092

93

9496

104

105108

109

121122125

126

127

129

130131

132

133

Detroit River Sediment PCBs 1999-2001

0 5 10 15 20 25 30 35 40 450.01

0.11

7

8

16

21

22

23

26

32

36

37

4159

64

66

82

89

91

108123124

131

Downstream Distance (km) Downstream Distance (km)

Sampling Stations outside of 99% confidence intervals representdistinct sediment hotspots.

Octachlorostyrene as a Tracerof PCB Point Sources

100

1000

9

55

113

118

119

120

135

143

658

71

8688

95% ConfidenceInterval

ng/g

OC

wt.)

US Sites

CDN Sites •Main OCS source from St. Clair

•No differences in sediment OCS

0 5 10 15 20 25 30 35 40 45 50

1010

11

12

13

14

17

19

24

30

29

39

42

43

49

50

51

52

5776

79

95

99

100

101

102103

107

110

111

113

115

120

128

134

136139 140

142

149

1

6

78 16

22

23

26

32

35

37 44

4547

4859

64

66

676870

72

73

7481

83

84

85

87

89

91

92

93

94

97

104105

108

109

121

123124

125126

127

130131

133

OC

S C

once

ntra

tion

(

Distance Downstream

Geometric MeanAll Sites

concentrations between CND and US Sites

•Enrichment of OCS likely reflects sediment focusing

•Depletion of OCS represents dilution (shoreline erosion or tributary inputs)

13

24

5

7 6 1000

10000

100000

015 030

029

042

049

050

054052

114 144

034

076079

103

099 150147146

031

ratio

n R

atio

Possible Loadings Sources ofContaminated Particles

PCB/OCS ratio as a Tracer of Loading Sources

9

7

8

1011

6

0 10 20 30 40 500.1

1

10

100

003024

011

014

027

043

038

055

051

075

098

114

118

117

009

004

025010013017

019 039

053

057

080078077

100102095101

103

113111

110120

116115119

106

107

148135142134

128

139149141145

143136138140

137

026

022021

018

037

036

035

032

033

041

047

048

063060

058

073

071

068

088

093090094

083

124125123

001008

007006005

023016028

045044

059

072074069

065064067070066

081

097

096092091

084

087

089

085086

082

104

109

108

105133

130129131132

122

127126

12195% ConfidenceInterval of CDN PCB/OCS Ratio

Sum

PC

B/O

CS

Con

cent

r

Distance Downstream of River (km)

Geometric MeanCDN PCB/OCS Ratio

13

24

5

7 6

Contaminated Particle and Biomonitoring PCB Hotspots

0 2

Kilometers

4

#

9

7

8

1011

6

0 2

Kilometers

4

#

Sediment PCB Sources (Tracers) Biomonitoring PCB Hotspots

13

24

5

7 6

Zone Area Depth PCB mass % PCB % Area(m2) (m) (kg) mass

1 5.4x106 0.10 1.1 0.25 4.802 3.4x106 0.10 0.4 0.09 3.023 3 7x106 0 10 2 4 0 52 3 29

PCB Mass Balance in Detroit River Sediments

0 2

Kilometers

4

#

9 8

1011

3 3.7x10 0.10 2.4 0.52 3.294 7.0x106 0.10 5.9 1.31 6.235 7.1x106 0.10 7.2 1.60 6.326 8.5x106 0.10 20.5 4.55 7.567 14.3x106 0.10 27.4 6.09 12.728 7.6x106 0.10 10.8 2.40 6.76 9 4.8x106 0.10 39.8 8.84 4.2710 31.9x106 0.10 55.8 12.41 28.3811 18.7x106 0.10 278.7 61.95 16.64

112.4x106 0.10 449.9 Total:

**70% Surficial sediment PCBs in TT & downstream TT

PCBs in Detroit River Sediments 1999 – 2004 Comparison

Upper

Middle 100

1000

wt)

2004

U.S. Stations Canadian Stations

1:1 Relationship

0 2

Kilometers

4

#

Lower

0.1 1 10 100 10000.1

1

10

tota

l PC

Bs (n

g/g

dry

w

total PCBs (ng/g dry wt) 1999

**No significant differences (paired t-test; p<0.05) in PCBs at replicated stations


with exceeded LEL for total PCB

In the Huron-Erie Corridor

PCBs in Sediments of Huron-Erie Corridor

mean value

LEL = 3.3 μg/g OC weight

(mean TOC = 2.13%)

10

on (u

g/g

OC

wt)

U.S. Can.

mean value

25, 75 percentile

min-max range

***PCBs localized in U.S. Detroit River (Downstream Reach)

Elevated, but below LEL, PCBs observed in Canadian St. Clair River

0.1

1

tota

l PC

B c

once

ntra

ti o

SCR SCD LSC-N LSC-S DR DR99 SCR SCD LSC-N LSC-S DR DR99

PAHs in Detroit River Sediments (1999)

10

100

1000

10000

PAH

s (u

g/g

OC

wei

ght)

LEL

Upper

Middle

1

10

tota

l P


0 2

Kilometers

4

#

Lower53 (42 U.S.; 11 Canadian) Sites Exceeded MOE LEL for PAHs (4 ug/g dry wt.)

•Csed Elevated Mainly on U.S. Side of River

PAHs in Sediments of Huron-Erie Corridor

10

100

1000

OC

wt)

0.01

0.1

1

tota

l PAH

s (u

g/g

SCR SCD LS-N LS-S DR SCR SCD LS-N LS-S DR

***PAHs localized in U.S. Detroit River (Downstream Reach)


with exceeded LEL for total PAH


1999 Detroit River Sediments: total Hg

Upper

Middle 0.1

1

3

Con

cent

ratio

n (µ

g·g-1

dry

wt)

MOE LEL

MOE SEL

0 2

Kilometers

4

#

Lower


•Related BUI – Fish Consumption AdvisoriesRestrictions on Dredging

•69 (39 U.S.; 30 Canadian) Sites Exceeded MOE LEL; 1 U.S. Exceeds OMOE SEL

SEL

0.01Hg

C


with exceeded LEL for Hg


Distribution of Hg in Corridor

1

10

g/g

dry

wei

ght)

AA

B

BA

SEL = 2 μg/g dry weight

mean value

25, 75 percentile

min-max range0.01

0.1

Hg

conc

entra

tion

(μ

SCRUSA

SCDUSA

SCLUSA

DRUSA

SCRCA

SCDCA

SCLCA

DRCA

Total Hg in sediments – Regional Issue – Canada – SCR/LSC; U.S. – Upper DR

LEL = 0.2 μg/g dry weight

A

A

A A

Conclusions: PCBs & PAHs• PCBs and PAHs are a localized issue to Detroit River• PCBs - high sediment concentrations (70% mass)

restricted to Trenton Channel and Downstream T.T.

– PCBs in this Region Are Major Driver of Observed Fish Advisories– PCBs in this Region At Risk for Re-suspension to Lake Erie

• PAHs distributed throughout nearshore & downstream U.S. areas of Detroit River– PAHs in this Region Are Major Driver of Sediment Genotoxicity

• Local Remediation of Sediments & Point Source Control of PCBs in Detroit River Could be Effective for Beneficial Use Impairments due to these Chemicals

Conclusions for total Hg in Sediments

• Hg is a corridor issue, with high sediment concentrations distributed throughout – Canadian St. Clair River, Lake St. Clair, Lower Detroit River– U.S. Upper, Middle, Lower Detroit River

-Local sediment remediation will not address Hg in contaminated sediments

-Understanding Hg bioavailability critical to linking sediment/water contamination with fish advisories

Discussion Comments

• Geostatistical design provides unbiased evaluation of corridor contamination trends

• Places localized, high resolution studies in systems contextsystems context

• Permits mass balance• Study should be repeated in time (e.g.

every 5 years) to provide temporal trend

Paolo Usseglio

One fish two fishred fish blue fish:

fish censusing made easy

United Nations University-International Network on Water and Environmental

Health

Paolo Usseglio

Fish censusing

Why census fish?Types of questions to be answered:

– AbundanceDiversity– Diversity

– Distribution– Biomass

Fish censusing

Types of data obtained:– Species abundance

30

0

5

10

15

20

25

30

PA2 PA4 PJ2 PJ3 TW1 TW2 UNU1 UNU2

Fish censusing

Types of data obtained:– Species richness

50

60

0

10

20

30

40

fort

isla

nd

al h

edla

juss

a w

est

turtl

e be

ach

dibb

a ro

ck

dibb

a si

te 1

al-ja

zeer

a

qant

ab re

ef

al-g

hatta

n

juss

a po

int

Ras

hid

isla

nd w

est

Cor

al g

arde

n

juss

a is

land

sadi

yat i

slan

d

Ras

Gan

adah

Fish censusing

Types of data obtained:– Biomass

100120140160

020406080

100

al h

edla

dibb

a si

te 1

Ras

hid

isla

nd w

est

dibb

a ro

ck

Cor

al g

arde

n

fort

isla

nd

sadi

yat i

slan

d

al-g

hatta

n

turtl

e be

ach

juss

a w

est

al-ja

zeer

a

qant

ab re

ef

juss

a po

int

juss

a is

land

Ras

Gan

adah

80%90%

100%

Fish censusing

Types of data obtained:– Size class distributions

0%10%20%30%40%50%60%70%80%

al-

ghat

tan

al-

jaze

era

fort

isla

nd

qant

abre

ef

>3121_3011_20<10

Fish censusing

Types of data obtained:– Species list

abudefduf vaigensis Chaetodon gardineri

acanthurus mata chaetodon melapterus

henionchus acuminatus pomacentrus leptus

labroides dimidiatus pseudochromis aldabraensis

acanthurus sohal chaetodon nigropunctatus

acanthurus sp2 Cheilinus lunulatus

Amphiprion clarkii cheilodipterus novemstriatus

apogon aureus chromis xanthopterygia

apogon holotaenia coris frerei

bodianus macrognathos Dascyllus trimaculatus

caesio lunaris Diagramma pictum

caesio varilineata diodon hystrix

cephalopolis hemistiktos ecsenius pulcher

chaetodon collare gymnothorax favagineus

lutjanus russellii Pterois antennata

myripristis murdjan rastrelliger kanagurta

odonus niger rhinecanthus assasi

ostracion cyanurus Scarus fuscopurpureus

Parupeneus macronemus scarus persicus

Parupeneus margaritatus scolopsis ghanam

plectorhinchus gaterinus siderea grisea

plotosus lineatus siganus javus

pomacanthus imperator Stethojulis interrupta

pomacanthus maculosus sufflamen chrysopterum

Fish censusing

Methods– Belt transects

Fish censusing

Methods– GPS transects

Fish censusing

Methods– Timed swim

Fish censusing

Methods– Roving diver

Fish censusing

Methods– Cylinder

Fish censusing

Methods– Rotenone stations

Fish censusing

Methods– Fishing methods

Fish censusing

Which method?– Will depend on question.Will depend on question.

Fish censusing

“What is the size class distribution of Hamour along the breakwaters of the major developments in Dubai?”

Fish censusing“What is the size class distribution of Hamour along the

breakwaters of the major developments in Dubai?”

- Site fidelity- Low density- Cover large areas- 150m long by 1m wide

Fish censusing“What is the size class distribution of Hamour along the

breakwaters of the major developments in Dubai?”

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Fish censusing

One observer vs. several– Observer bias

• Ability to correctly identify a fish• Precision and accuracy of size estimates

P i i d f t• Precision and accuracy of counts– Inter observer calibration exercises

• Aimed at reducing the uncertainty in estimates carried by several observers

Fish censusing

– Size class estimation• Models• Juveniles capture-measure

Inter observer bias and calibration

Fish censusing

– Analysis– Linear regression analysis. Observed vs. estimated

length. – r^2= precision, slope= accuracy

Inter observer bias and calibration

25

y = 1.2042xR2 = 0.9438

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Fish censusingInter observer bias and calibration

• Inter observer calibration exercises• Abundance and diversity

– Side by side transects– Several runs of the same transect

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Fish censusingEMP census methods

EMP fish census methods– 8 belt transects 30x1m wide– Counting every individual observed– Estimating size

•Why 8?

Fish censusingPower analysis

Power analysis• How large a sample is needed to enable

statistical judgments that are accurate and reliablereliable

• How likely your statistical test will be to detect effects of a given size in a particular situation

Fish censusingPower analysis

Power analysis• Pilot study data. Variance, population mean

– 1340 transects over a year at 6 sites• 95% confidence in detecting a 5% change in

abundance of fishabundance of fish species tran. SitePLSOR 13LUFUL 9LUEHR 2POAQU 4SCGHA 2POMAC 3PAMAR 1CHNIG 10POTRIC 10POLEP 4ABVAI 3CHNOV 1SICAN 5AMALB 4

Fish censusingTaxonomy

Taxonomy• Tips to help identify an USO (Unidentified

Swimming Object)– Obtain proper reference material (Randall)– www.fishbase.org


Taxonomy• Types of tail

Miller and Lea, 1972 "Guide to the Coastal Marine Fishes of California"


Taxonomy• Dorsal fin


Taxonomy• Bars, lines, ocelles, spots


Taxonomy• Tentative family


–Point and shoot camera–Still vs. video


Taxonomy• Ontogenic changes


Taxonomy• Ontogenic changes

Fish censusing

• Questions• Methods• Observer bias and calibration

Summary

• Fish ID resources

Setting up a field sampling programme: staff, field instruments and logistical requirements for sampling in the field

Paolo Usseglio

United Nations University- International Network on Water and Environmental Health

g

Setting up a field sampling programme

Field sampling programme provides data that will be used to guide decisions

within an Environmental Management Program.

FSP should be:• Comprehensive• Homogeneous • Sensitive• Sensible• Consistent • Cost effective


Question drivenDifferent questions will require different methods,

degrees of repetition, accuracy and precision

Identify the question

Develop conceptual

Evaluatesampling/analysis optionsquestion

Evaluate available data

conceptual model

options

Assemble datacollection options(methods)

Train personnel

Develop datacollection manuals

Begin datacollection

Setting up a field sampling programmeSetting a monitoring program

Staff considerations

Different activities require different skills

Postgraduate educationlevel (M Sc Ph D)

Undergraduate education level

High schoolEducationlevel (M.Sc., Ph.D)

PlanningTraining staffDevelop conceptual modelDevelopment of manualsData analysisScientific writingProgram management

education level (B.Sc.)

Field data collectionData entryEquipment maintenancePreliminary data analysis

Education

Data collection (basic)Data entry (basic)Equipment maintenanceField logistics


Equipment considerations

“If the only tool you only have is a hammer, you will see every problem as a nail” Abraham Maslow

• Plethora of field equipmentb d i i l• brands, sizes, price, colour

• Accuracy, sensitivity, operational parameters

•How to choose the most appropriate field equipment?

•Let the question drive your choice


Equipment

• Example:– What are the water movement patterns of the

island of Krakatoa?

• Parameters: current speed, direction.

Setting up a field sampling programmeWhat are the water movement patterns of the island of Krakatoa?

Water direction: compassWater speed: Surface drogueOnce a day at one site

Daily surface water movement patterns. Average monthlycurrent pattern

Setting up a field sampling programmeWhat are the water movement patterns of the island of Krakatoa?

• Analysis- Relationship between hydrodynamic patterns

and fish eggs dispersal in Krakatoa


Relationship between hydrodynamic patterns and fish eggs dispersal in Krakatoa?

Current metersSample every hour Sample every meter3 locations


Relationship between hydrodynamic patterns and fish eggs dispersal in Krakatoa?


Question driven

Different questions will require different methodsrequire different methods, repetition, accuracy and

precision

• Example:– Assessment of the physical characteristics of

the shallow waters surrounding the island of S P d it l t d th t i l t


San Pedrito located on the tropical eastern Antarctic.

• Parameters: Temperature, salinity.

Setting up a field sampling programmeExample: San Pedrito

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C TemperatureC SalinityD TemperatureD Salinity


A)WQM Wet labs.

Materials:

B) Sea-bird CTD.

C) HOBO D)Thermometerrefractometer


WQM CTD HOBO HandheldMeassurements Salinity,

TemperatureSalinity, Temperature

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Temperature, Depth, DO, Turbidity, Chl

Temperature, Depth, DO, ORP, PAR, Chl

Salinity, Temperature

Salinity, Temperature

Boat Days 2 30 2 30Divers 2 0 0 0Personnel days 2 30 2 30Personnel training High High Little LittleEquipment cost 35,000 USD 27,224 USD 120 USD 80 USDPersonnel cost $$$$ $$$ $ $$


Monitoring parameters

BiologicalBiotic (living) elements of

Physico-chemicalAbiotic (non living) conditions.

the environment of interest

Abundance, diversity, biomass.

Determine the ability of organisms to live and reproduce.

Temperature, salinity, oxygen,Nutrients.

Monitoring parameters

Biological parameters

Plankton

Physico-chemical parametersTemperatureSalinity

Benthic invertebratesCoral communitiesFish

CurrentsTurbidityTidesMeteorological parametersNutrients

Monitoring parameters: instruments

Plankton: drifting organisms found in the pelagic zone of the ocean.Method: Plankton towsEquipment: Plankton nets, Niskin/Van Dorn bottles, dissecting scope, microscope, flowcam.


PlanktonStaff: Postgraduate coordinator, field assistant, lab techLogistics:

• Boat schedules• Sample storage• Gear maintenanceGear maintenance


Benthic invertebrates: individuals who inhabit sedimentsMethod: sediment coresEquipment: Core sampler, coffee can sampler, sieve, dissecting scope.


Benthic invertebratesStaff: Postgraduate coordinator, field assistant (diver), lab tech.Logistics:

• Boat and dive schedules• Sample storageSample storage• Gear maintenance, field and dive equipment


Coral communities: abundance and distribution of corals in a given areaEquipment: dive gear, dive boat, still image camera, video camera, brass chain, slate and underwater paper.


Coral communitiesStaff: Postgraduate coordinator, field assistant (diver)Logistics:

• Boat and dive schedules• Image storage and backup• Gear maintenance, field and dive equipmentGear maintenance, field and dive equipment


Fish communities: abundance and distribution of fish in a given areaEquipment: dive gear, dive boat, still image camera, slate and underwater paper, tape measures.


Fish communitiesStaff: Postgraduate coordinator, field researcher, field assistant (diver)Logistics:

• Boat and dive schedules• Data entry storage and backupData entry storage and backup• Gear maintenance, field and dive equipment


Water quality: Physico-chemical characteristics of the water columnEquipment: dive gear, dive boat, current meters, water quality monitors, CTD, underwater loggers, tide gauge.


Water qualityStaff: Postgraduate coordinator (math genius), field researcher, field assistant (diver), technician (maintenance)Logistics:

• Boat and dive schedules• Instrument deployment and maintenance schedulesInstrument deployment and maintenance schedules• Data download, storage and backup• Equipment maintenance, field and dive equipment

•Specialized equipment must be serviced by trained professionals


Setting a monitoring program

Identify the question

Develop conceptual

Evaluatesampling/analysis

tiquestion

Evaluate available data

conceptual model

options

Assemble datacollection options(methods)

Train personnel

Develop datacollection manuals

Begin datacollection


Develop data collection manuals

Begin data collection

Identify the questionEvaluate available data

Develop conceptual model

Assemble methods

Train personnel

Building a Coastal Building a Coastal Management PlanManagement Plan

UNUUNU--INWEH Monitoring WorkshopINWEH Monitoring WorkshopZayed University, February 2009Zayed University, February 2009

Peter F. SalePeter F. SaleUnited Nations UniversityUnited Nations University

International Network on Water, Environment and International Network on Water, Environment and HealthHealth

Hamilton, CanadaHamilton, Canada

Environmental Management Environmental Management ApproachesApproaches•• No management No management

at allat all



at allat all•• ReactiveReactive


•• Reactive Reactive managementmanagement


at allat all•• ReactiveReactive

•• Monitoring data are Monitoring data are necessary for reactive necessary for reactive or proactiveor proactive


•• Reactive Reactive managementmanagement

•• Proactive Proactive managementmanagement

or proactive or proactive managementmanagement

•• Data requirements are Data requirements are fewer for reactive fewer for reactive managementmanagement

A Simple Example A Simple Example –– Mussel WatchMussel Watch

•• Uses mussels as biomonitorsUses mussels as biomonitors•• Samples any of 11 species around Samples any of 11 species around

shores of North Americashores of North America•• Flesh analysed for a wide range ofFlesh analysed for a wide range of


•• Flesh analysed for a wide range of Flesh analysed for a wide range of chemical contaminantschemical contaminants

•• Longest running monitoring program Longest running monitoring program anywhere >20yranywhere >20yr

•• Regular reports on state of the Regular reports on state of the coastscoasts


•• Collecting methods are simpleCollecting methods are simple•• Analytical methods are Analytical methods are

standardizedstandardized


•• Data are pooled across Data are pooled across jurisdictionsjurisdictions

•• Data have been used in Data have been used in reactive and in proactive reactive and in proactive management planningmanagement planning


•• Here is an example of Here is an example of what can be extracted what can be extracted from the datafrom the dataF it i Mi iF it i Mi i


•• For sites in Miami For sites in Miami harbourharbour

•• Examining Lead, Zinc, Examining Lead, Zinc, total PAHs, and total total PAHs, and total PCBsPCBs

•• Usual approach is to establish environmental Usual approach is to establish environmental quality objectivesquality objectives

•• Then set action criteria for specified parametersThen set action criteria for specified parameters

Conventional Reactive ManagementConventional Reactive Management


–– Action criterion is the value of parameter that Action criterion is the value of parameter that indicates need for ‘attention’ (engineer approach)indicates need for ‘attention’ (engineer approach)

–– Management action may be a simple as closing a Management action may be a simple as closing a beach to swimmingbeach to swimming

•• Can work well when ecosystem processes are Can work well when ecosystem processes are well understoodwell understood

Proactive ManagementProactive Management

•• Requires a more detailed understanding of Requires a more detailed understanding of the system dynamicsthe system dynamics

•• Based on a deeper analysis of the Based on a deeper analysis of the i i di i d


monitoring datamonitoring data•• Prognostic models to permit view of likely Prognostic models to permit view of likely

future given current trendsfuture given current trends•• Informed management action in order to Informed management action in order to

change anticipated futurechange anticipated future


•• There is no fundamental difference in the There is no fundamental difference in the monitoring program to support reactive or monitoring program to support reactive or proactive managementproactive management


•• There is a different mindThere is a different mind--set held by the set held by the managersmanagers

•• Reactive = Compliance with RegulationsReactive = Compliance with Regulations•• Proactive = Understand and InvestigateProactive = Understand and Investigate

Proactive ManagementProactive Management•• Proactive managers Proactive managers

visualize scenarios visualize scenarios and use monitoring and use monitoring data to build these data to build these i f th lik li f th lik l


images of the likely images of the likely futurefuture

•• They seek to They seek to understand the understand the system they managesystem they manage


•• Scenarios are more accurate, and solutions to Scenarios are more accurate, and solutions to problems more reliable, when the manager problems more reliable, when the manager understands the behavior of the systemunderstands the behavior of the system


understands the behavior of the systemunderstands the behavior of the system•• Better monitoring data, and better evaluation, in Better monitoring data, and better evaluation, in

a climate of ‘what if’ questions build this a climate of ‘what if’ questions build this understandingunderstanding

•• Building a research focus into the management Building a research focus into the management agency is a likely precursor to proactive agency is a likely precursor to proactive management management

Documents

Instruments and how to program and down-load data from a