combining long-term and high frequency water quality data to understand ecological processes in...
TRANSCRIPT
![Page 1: Combining Long-term And High Frequency Water Quality Data To Understand Ecological Processes In Estuaries Jane Caffrey Center for Environmental Diagnostics](https://reader035.vdocuments.us/reader035/viewer/2022062516/56649d9f5503460f94a8a088/html5/thumbnails/1.jpg)
Combining Long-term And High Frequency Water Quality Data
To Understand Ecological Processes In Estuaries
Jane Caffrey
Center for Environmental Diagnostics and Bioremediation
University of West Florida
![Page 2: Combining Long-term And High Frequency Water Quality Data To Understand Ecological Processes In Estuaries Jane Caffrey Center for Environmental Diagnostics](https://reader035.vdocuments.us/reader035/viewer/2022062516/56649d9f5503460f94a8a088/html5/thumbnails/2.jpg)
J.M. Caffrey, UWF
Acknowledgements
• Data– Thomas Chapin, USGS and Hans Jannasch,
MBARI– Scott Phipps, Weeks Bay NERR and John
Haskins, Elkhorn Slough NERR
• Funding - CICEET and NOAA NERR
![Page 3: Combining Long-term And High Frequency Water Quality Data To Understand Ecological Processes In Estuaries Jane Caffrey Center for Environmental Diagnostics](https://reader035.vdocuments.us/reader035/viewer/2022062516/56649d9f5503460f94a8a088/html5/thumbnails/3.jpg)
J.M. Caffrey, UWF
Outline of talk
• Calculation of metabolic rates (primary production, respiration and net ecosystem metabolism) from DO data – Data sondes deployed at NERR– Salinity, temperature, dissolved oxygen, turbidity, pH
• Understanding short term variability in estuarine processes– Deployment of in-situ NO3
- analyzers (developed by Ken Johnson, MBARI)
• Linking physical, chemical and biological processes
![Page 4: Combining Long-term And High Frequency Water Quality Data To Understand Ecological Processes In Estuaries Jane Caffrey Center for Environmental Diagnostics](https://reader035.vdocuments.us/reader035/viewer/2022062516/56649d9f5503460f94a8a088/html5/thumbnails/4.jpg)
J.M. Caffrey, UWF
National Estuarine Research Reserve System
![Page 5: Combining Long-term And High Frequency Water Quality Data To Understand Ecological Processes In Estuaries Jane Caffrey Center for Environmental Diagnostics](https://reader035.vdocuments.us/reader035/viewer/2022062516/56649d9f5503460f94a8a088/html5/thumbnails/5.jpg)
J.M. Caffrey, UWF
Background
• Dissolved oxygen data collected every half hour between 1995-2001.
• Uses diurnal changes in water column oxygen concentrations to estimate primary production, respiration and net ecosystem metabolism
• Developed by H.T. Odum in 1950s
• Describes the trophic status of the water body
– Autotrophic: P > R
– Heterotrophic: R > P
![Page 6: Combining Long-term And High Frequency Water Quality Data To Understand Ecological Processes In Estuaries Jane Caffrey Center for Environmental Diagnostics](https://reader035.vdocuments.us/reader035/viewer/2022062516/56649d9f5503460f94a8a088/html5/thumbnails/6.jpg)
J.M. Caffrey, UWF
Dissolved Oxygen
Diurnal changes in DO result from photosynthesis and respirationGross production= NAP + respiration Net Ecosystem Metabolism (NEM) = NAP - respiration
0
3
6
9
12
4/19 4/20 4/21 4/22 4/23
mg/
l
Night respirationNet apparent production
![Page 7: Combining Long-term And High Frequency Water Quality Data To Understand Ecological Processes In Estuaries Jane Caffrey Center for Environmental Diagnostics](https://reader035.vdocuments.us/reader035/viewer/2022062516/56649d9f5503460f94a8a088/html5/thumbnails/7.jpg)
J.M. Caffrey, UWF
Assumptions
• Respiration rate is constant in light and dark
• System is well mixed vertically
• No advection of water masses with different DO concentrations is occurring – or biology dominates over physics
![Page 8: Combining Long-term And High Frequency Water Quality Data To Understand Ecological Processes In Estuaries Jane Caffrey Center for Environmental Diagnostics](https://reader035.vdocuments.us/reader035/viewer/2022062516/56649d9f5503460f94a8a088/html5/thumbnails/8.jpg)
J.M. Caffrey, UWF
Primary ProductionWeeks Bay
0
5
10
15
20
25
30
1996 1997 1998 1999 2000 2001 2002 2003 2004 2005
Gro
ss p
rod
uct
ion
gO
2/m
2/d
0
5
10
15
20
25
30
35
1996 1997 1998 1999 2000 2001 2002 2003 2004 2005
Tem
pera
ture
°C
Gro
ss p
rodu
ctio
n m
g O
2/m
2/d
![Page 9: Combining Long-term And High Frequency Water Quality Data To Understand Ecological Processes In Estuaries Jane Caffrey Center for Environmental Diagnostics](https://reader035.vdocuments.us/reader035/viewer/2022062516/56649d9f5503460f94a8a088/html5/thumbnails/9.jpg)
J.M. Caffrey, UWF
Temperature effectsNorth Inlet-Winyah Bay, SC - Oyster
Landing
r = 0.71
0
4
8
12
16
0 5 10 15 20 25 30 35
Temperature °C
Tot
al r
espi
ratio
n gO
2/m
3/d
Temperature versus metabolic rate correlations• Gross production – 23 sites• Total Respiration – 26 sites• Net ecosystem metabolism – 19 sites
![Page 10: Combining Long-term And High Frequency Water Quality Data To Understand Ecological Processes In Estuaries Jane Caffrey Center for Environmental Diagnostics](https://reader035.vdocuments.us/reader035/viewer/2022062516/56649d9f5503460f94a8a088/html5/thumbnails/10.jpg)
J.M. Caffrey, UWF
Salinity effectsElkhorn Slough, CA – Azevedo Pond
r = 0.39
0
10
20
30
40
50
60
0 5 10 15 20 25 30 35 40Salinity
Gro
ss p
rodu
ctio
n,g
O2/
m3/
d
Salinity versus metabolic rate correlations• Gross Production – 16 sites• Total Respiration –12 sites• Net ecosystem metabolism – 13 sites
![Page 11: Combining Long-term And High Frequency Water Quality Data To Understand Ecological Processes In Estuaries Jane Caffrey Center for Environmental Diagnostics](https://reader035.vdocuments.us/reader035/viewer/2022062516/56649d9f5503460f94a8a088/html5/thumbnails/11.jpg)
J.M. Caffrey, UWF
Net ecosystem by habitat
-8
-7
-6
-5
-4
-3
-2
-1
0
1C
BV
Go
od
win
Isl
an
d
PA
D B
ay
Vie
w
WQ
B C
en
tra
l Ba
sin
AP
A E
ast
Ba
y
GR
B G
rea
t B
ay
GR
B S
qu
am
sco
tt R
ive
r
NA
R P
ott
ers
Co
ve
NA
R T
-wh
arf
WK
B F
ish
Riv
er
WK
B W
ee
ks B
ay
JOB
Sta
tion
9
JOB
Sta
tion
10
RK
B B
lack
wa
ter
Riv
er
RK
B U
pp
er
He
nd
ers
on
CB
M J
ug
Ba
y
CB
M P
atu
xen
t P
ark
HU
D T
ivo
li S
ou
th
CB
V T
ask
ina
s C
ree
k
AC
E B
ig B
asi
n
AC
E S
t P
ierr
e
EL
K S
ou
th M
ars
h
NIW
Oys
ter
La
nd
ing
NIW
Th
ou
san
d A
cre
EL
K A
zeve
do
Po
nd
PA
D J
oe
Le
ary
Slo
ug
hH
UD
Sa
wki
ll
g O
2 m
-2 d
-1
SAV open water mangrove marsh creeks upland
![Page 12: Combining Long-term And High Frequency Water Quality Data To Understand Ecological Processes In Estuaries Jane Caffrey Center for Environmental Diagnostics](https://reader035.vdocuments.us/reader035/viewer/2022062516/56649d9f5503460f94a8a088/html5/thumbnails/12.jpg)
J.M. Caffrey, UWF
Conclusions
• Water quality monitoring data is useful for estimating metabolic rates
• within site variability– temperature – salinity – nutrient concentration – chlorophyll concentration
• Among site variability– habitat (organic matter loading)– nutrient loading – residence time
![Page 13: Combining Long-term And High Frequency Water Quality Data To Understand Ecological Processes In Estuaries Jane Caffrey Center for Environmental Diagnostics](https://reader035.vdocuments.us/reader035/viewer/2022062516/56649d9f5503460f94a8a088/html5/thumbnails/13.jpg)
J.M. Caffrey, UWF
Understanding Temporal Patterns
Continuous measurements give greater temporal resolution than discrete measurements
Salinity
0
5
10
15
20
25
J F M A M J J A S O N D
PS
U
![Page 14: Combining Long-term And High Frequency Water Quality Data To Understand Ecological Processes In Estuaries Jane Caffrey Center for Environmental Diagnostics](https://reader035.vdocuments.us/reader035/viewer/2022062516/56649d9f5503460f94a8a088/html5/thumbnails/14.jpg)
J.M. Caffrey, UWF
Relating Runoff to Estuarine Processes
Rainfall in the Weeks Bay watershed leads to reduced salinity at the head of the estuary
0
5
10
15
20
25
J F M A M J J A S O N D
Sal
init
y P
SU
0
40
80
120
160
Rai
nfa
ll m
m
![Page 15: Combining Long-term And High Frequency Water Quality Data To Understand Ecological Processes In Estuaries Jane Caffrey Center for Environmental Diagnostics](https://reader035.vdocuments.us/reader035/viewer/2022062516/56649d9f5503460f94a8a088/html5/thumbnails/15.jpg)
J.M. Caffrey, UWF
In-situ nutrient analysis
![Page 16: Combining Long-term And High Frequency Water Quality Data To Understand Ecological Processes In Estuaries Jane Caffrey Center for Environmental Diagnostics](https://reader035.vdocuments.us/reader035/viewer/2022062516/56649d9f5503460f94a8a088/html5/thumbnails/16.jpg)
J.M. Caffrey, UWF
Seasonal patterns in rainfall, temperature, salinity and nitrate concentrations in Elkhorn
Slough, CA
![Page 17: Combining Long-term And High Frequency Water Quality Data To Understand Ecological Processes In Estuaries Jane Caffrey Center for Environmental Diagnostics](https://reader035.vdocuments.us/reader035/viewer/2022062516/56649d9f5503460f94a8a088/html5/thumbnails/17.jpg)
J.M. Caffrey, UWF
Winter rains lead to extended periods of high NO3
- concentrations in Elkhorn Slough, CA
15
20
25
30
2/8 2/13 2/18 2/23 2/28 3/5 3/10 3/15
Sa
linity
0
1
2
3
4
rain
, cm
0
40
80
120
2/8 2/13 2/18 2/23 2/28 3/5 3/10 3/15
NO
3-
µM
0
1
rain
, cm
15
20
25
30
2/8 2/13 2/18 2/23 2/28 3/5 3/10 3/15
Sa
linity
0
1
2
3
4
rain
, cm
0
40
80
120
2/8 2/13 2/18 2/23 2/28 3/5 3/10 3/15
NO
3-
µM
0
1
rain
, cm
![Page 18: Combining Long-term And High Frequency Water Quality Data To Understand Ecological Processes In Estuaries Jane Caffrey Center for Environmental Diagnostics](https://reader035.vdocuments.us/reader035/viewer/2022062516/56649d9f5503460f94a8a088/html5/thumbnails/18.jpg)
J.M. Caffrey, UWF
Relating Runoff to Nutrient Loading
High NO3- concentrations associated with runoff events in
Weeks Bay, AL during winter rains
0
20
40
60
80
1/3 1/17 1/31 2/14 2/28
NO
3- con
cent
ratio
n, µ
M
0
10
20
30
Sal
inity
, R
ainf
all,
mm
![Page 19: Combining Long-term And High Frequency Water Quality Data To Understand Ecological Processes In Estuaries Jane Caffrey Center for Environmental Diagnostics](https://reader035.vdocuments.us/reader035/viewer/2022062516/56649d9f5503460f94a8a088/html5/thumbnails/19.jpg)
J.M. Caffrey, UWF
Seasonal differences in NO3-
concentrations following runoff events
0
20
40
60
80
0 5 10 15 20 25
Salinity
NO
3-
µM
Jan
Aug
![Page 20: Combining Long-term And High Frequency Water Quality Data To Understand Ecological Processes In Estuaries Jane Caffrey Center for Environmental Diagnostics](https://reader035.vdocuments.us/reader035/viewer/2022062516/56649d9f5503460f94a8a088/html5/thumbnails/20.jpg)
J.M. Caffrey, UWF
What factors contribute to variability?
• Harmonic regression analysis – choose periods of interest: tidal 12.5h, diurnal 24h, and
lunar 29.5d
– Fit data to linear regression– Run full models with all periods and reduced models to
look at contributions of different components
t
kperiod
bt
kperiod
aaNO t x2
sinx2
cos3 110
![Page 21: Combining Long-term And High Frequency Water Quality Data To Understand Ecological Processes In Estuaries Jane Caffrey Center for Environmental Diagnostics](https://reader035.vdocuments.us/reader035/viewer/2022062516/56649d9f5503460f94a8a088/html5/thumbnails/21.jpg)
J.M. Caffrey, UWF
Elkhorn Slough
•Lunar signal most important during winter, capturing runoff events. •Spring-neap forcing of deep Monterey Bay water into Slough (Chapin et al. 2004)•Diurnal signal dominates during summer when biological processes dominate.
0%
25%
50%
75%
100% Lunar
Diurnal
Tidal
![Page 22: Combining Long-term And High Frequency Water Quality Data To Understand Ecological Processes In Estuaries Jane Caffrey Center for Environmental Diagnostics](https://reader035.vdocuments.us/reader035/viewer/2022062516/56649d9f5503460f94a8a088/html5/thumbnails/22.jpg)
J.M. Caffrey, UWF
Weeks Bay
0%
20%
40%
60%
80%4
Ja
n -
25
Ja
n
25
Ja
n -
20
Fe
b
20
Fe
b -
8 M
ar
28
Ju
n -
19
Ju
l
19
Ju
l -9
Au
g
9 A
ug
-7
Se
p
1 N
ov
-2
7 N
ov
Lunar
Diurnal
Tidal
Lunar and diurnal signals also important in Weeks Bay.Not surprising that tidal signal is weak because tides arediurnal rather than semidiurnal.
![Page 23: Combining Long-term And High Frequency Water Quality Data To Understand Ecological Processes In Estuaries Jane Caffrey Center for Environmental Diagnostics](https://reader035.vdocuments.us/reader035/viewer/2022062516/56649d9f5503460f94a8a088/html5/thumbnails/23.jpg)
J.M. Caffrey, UWF
NO3- inputs enhance gross
production in Weeks Bay
0
10
20
30
40
8/9 8/14 8/19 8/24 8/29
NO
3-
µM
, ra
in m
m
0
4
8
12
16
Gro
ss p
rod
uct
ion
g O
2 m
-2 d
-1
![Page 24: Combining Long-term And High Frequency Water Quality Data To Understand Ecological Processes In Estuaries Jane Caffrey Center for Environmental Diagnostics](https://reader035.vdocuments.us/reader035/viewer/2022062516/56649d9f5503460f94a8a088/html5/thumbnails/24.jpg)
J.M. Caffrey, UWF
And Elkhorn Slough
0
10
20
30
40
4/1 4/8 4/15 4/22 4/29 5/6 5/13 5/20 5/27
NO
3 µ
M
0
10
20
30
40
Gro
ss P
rod
uct
ion
gO
2/m
2/d
![Page 25: Combining Long-term And High Frequency Water Quality Data To Understand Ecological Processes In Estuaries Jane Caffrey Center for Environmental Diagnostics](https://reader035.vdocuments.us/reader035/viewer/2022062516/56649d9f5503460f94a8a088/html5/thumbnails/25.jpg)
J.M. Caffrey, UWF
Conclusions and Challenges
• In situ instruments allow you to examine short term temporal variations, e.g. runoff events
• Water quality monitoring data (DO) can be used to estimate metabolic rates.
• How to link these time series together to examine how events at different time scales affect ecological processes
![Page 26: Combining Long-term And High Frequency Water Quality Data To Understand Ecological Processes In Estuaries Jane Caffrey Center for Environmental Diagnostics](https://reader035.vdocuments.us/reader035/viewer/2022062516/56649d9f5503460f94a8a088/html5/thumbnails/26.jpg)
J.M. Caffrey, UWF
Nitrogen Loading
N
MiI
eE
c
C
B
R2 = 0.30
-7
-6
-5
-4
-3
-2
-1
0
1
0 5 10 15 20 25
Nitrogen loading mmol m-2 d-1
Net
eco
syst
em m
etab
olis
m,
g O
2 m
-2 d
-1