DOES CLIMATE TRUMP FISH OR FISH
TRUMP CLIMATE? LONG-TERM
ECOLOGICAL DYNAMICS OF SUBALPINE
CASTLE LAKE
Sudeep Chandra, Wendy Trowbridge,
Rene Henery, and Charles R. Goldman
Outline
• Lakes as sentinels of climate change
– Physical and biological alterations linked to local and
regional processes
• Castle Station history: now the America’s oldest,
continuous, mountain lake, ecological dataset
• Long-term dynamics of climate, environmental,
and biological variables
• What is the influence of climate and fish
manipulations on the zooplankton community
composition?
Federal Institute of Aquatic Science and Technology (Eawag), Dübendorf, Switzerland
hLaboratory of Aquatic Photobiology and Plankton Ecology, Institute of Ecology, University of
Innsbruck, Innsbruck, Austria iLimnological Institute, University of Konstanz, Konstanz, Germany
jDepartment
Lakes as
sentinels
of climate
of Aquatic
Food Webs,
Netherlandschange
Institute of Ecology, Centre for Limnology,
k
Nieuwersluis, The Netherlands Department of Aquatic Sciences and Assessment, Swedish
University
of Agricultural
Sciences,
and Department
Ecology and
Evolution,B.Uppsala
a,*, Catherine
b, HoracioofZagarese
c, Stephen
Rita Adrian
M.
O’Reilly
Baines d, Dag O.
l
University,
John Muir
Institute of the
Tahoe Environmental
g,Environment,
h, Dietmar Straile i,
Hessene,Uppsala,
Wendel Sweden
Kellerf, David
M. Livingstone
Ruben Sommaruga
Research Center, jUniversity of California, Davis,
k California
l
Ellen Van Donk , Gesa A. Weyhenmeyer , and Monika Winder
Abstract
aLeibniz-Institute
b
of Freshwater
Inland
Fisheries,
Berlin,
Germany
Biology
While there is a general
sense thatEcology
lakesc canand
act as
sentinels
of climate
change,
their efficacy
has Program,
Bard
Annandale,
New
Laboratorio
de Ecología
y Fotobiología
Acuática,
notCollege,
been thoroughly
analyzed.
WeYork
identified
the key response
variables
within a lake that
act as Instituto
Tecnológico
(INTECH),
Chascomús
Provincia
de Buenos
Aires,
Argentina
indicators ofdetheChascomús
effects of climate
change on
both the lake
and the catchment.
These
variables
dDepartment of Ecology and Evolution, Stony Brook University, Stony Brook, New York
reflect a wide range of physical, chemical, and biological responses to climate. However, the
eDepartment of Biology, University of Oslo, Oslo, Norway fCooperative Freshwater Ecology Unit,
efficacy of the different indicators is affected by regional response to climate change,
Ontario
Ministryof
ofthe
thecatchment,
Environment,
Laurentian
University,
Sudbury,indicators
Ontario,orCanada gSwiss
characteristics
and lake
mixing regimes.
Thus, particular
Federal
Instituteofof
Aquaticare
Science
and Technology
Switzerland
combinations
indicators
more effective
for different(Eawag),
lake types Dübendorf,
and geographic
regions. The
hLaboratory
extraction of
can be further
by the influence
of other
environmental
of climate
Aquaticsignals
Photobiology
andcomplicated
Plankton Ecology,
Institute
of Ecology,
University of
changes, such
as eutrophication
or acidification,Institute,
and the equivalent
reverse
phenomena,
in
Innsbruck,
Innsbruck,
Austria iLimnological
University
of Konstanz,
Konstanz,
Germany
jDepartment
addition to of
other
land-use
influences.
many cases, however,
canfor
beLimnology,
Aquatic
Food
Webs,InNetherlands
Institute confounding
of Ecology,factors
Centre
addressed through
analytical toolskDepartment
such as detrending
or filtering.
Lakes and
are effective
sentinelsSwedish
for
Nieuwersluis,
The Netherlands
of Aquatic
Sciences
Assessment,
climate change
because they
are sensitive
climate, respond
rapidly to
change,
and integrate
University
of Agricultural
Sciences,
and to
Department
of Ecology
and
Evolution,
Uppsala
l
information
about
changes
in
the
catchment.
University, Uppsala, Sweden John Muir Institute of the Environment, Tahoe Environmental
Research Center, University of California, Davis, California
Currently, climate change is considered to be one of the most severe threats to ecosystems
Abstract around the globe (ACIA 2004; Rosenzweig et al. 2007 ). Monitoring and understanding the
effects of climate change pose challenges because of the multitude of responses within an
While there
is a general
sense
thatvariation
lakes canwithin
act asthe
sentinels
of climate
change,
their
ecosystem
and the
spatial
landscape.
A substantial
body
of efficacy
research has
not been demonstrates
thoroughly analyzed.
We identified
key response
variables
withinchemical,
a lake that
the sensitivity
of lakes tothe
climate
and shows
that physical,
andact as
indicatorsbiological
of the effects
of climaterespond
changerapidly
on bothtothe
lake and thechanges
catchment.
These
variables
lake properties
climate-related
( ACIA
2004;
(Limnology
and Oceanography 2009)
Regional climate influences by ocean cycles
influences physical structure, heat content of lakes
“All of the El Niño years and
several others shows that the
depth of the mixed layer and the
mixing of heat into the stratified
thermocline region control the
storage of heat.”
The storage of heat controls the
production in a lake.
(Strub et al., Science, 1985)
Lake Washington case study: influence of thermal structure on primary production
and resulting changes to zooplankton
Changes in the thermal stratification
Shifts in the onset of diatom blooms
Select zooplankton species were influenced by
alterations to the thermal regime
Keratella- no
Daphnia- yes
(Winder and Schindler 2004)
Outline
• Lakes as sentinels of climate change
– Physical and biological alterations linked to local and
regional processes
• Castle Station history: now the America’s oldest,
continuous, mountain lake, ecological dataset
• Long-term dynamics of climate, environmental,
and biological variables
• What is the influence of climate and fish
manipulations on the zooplankton community
composition?
Castle Lake- one of 11 lakes in the
Upper Sacramento region
•
•
•
•
•
•
subalpine cirque lake
mesotrophic
maximum depth- 35 m
~ 54 % littoral habitat
2-4 year HRT
Fish stocking across the
Western mountains if
they survived at Castle.
Castle Lake, small subalpine lake
located in the Klamath mountain
range in California
A test lake by agencies to determine what
hatchery raised species would survive
•
•
•
•
•
•
•
•
•
•
•
Atlantic salmon
Pacific salmon
Arctic grayling
Brown trout
Rainbow trout
Lake trout
Brook trout
Bass
Catfish
Bluegill
Yellowstone cutthroat trout
A young limnologist, arriving from Alaska, Dr. Charles
Goldman recommends an investigation of the factors
contributing to lake production, the program was
initiated in 1958 and continues today
Castle Lake measurements
Climate
Snow ice water content
Snow depth
Air temperatures
Solar radiation
Limnological factors (0-35 m)
Temperature
Dissolved Oxygen
Vertical extinction coefficient
Nitrogen
Phosphorus
Nutrient limitation assays
Pelagic PPr- 14C
Chlorophyll a
Zooplankton composition/ biomass
Fish stocking records
≈ 15 times in Summer, 1 Fall, 1 Winter/ Spring condition
Conditions at Castle Lake can vary greatly
depending on the season.
ice free season, June- November
4000
Current fishes in the lake
Biomass of Catchable fish stocked
No trend
3500
3000
2500
2000
1500
1000
500
0
600 1959
500
1969
1979
1989
1999
2009
1979
1989
1999
2009
Biomass of Fingerling fish stocked
p = 0.28, 16 pound decrease over the 52 years
400
300
200
100
0
1959
1969
• Brook trout (Salvelinus
fontinalis)- naturalized
spawner
• Rainbow trout
(Oncorhynchus mykiss)largely maintained
through stocking with
some limited natural
recruitment
• Golden shiner
(Notemigonus
crysoleuca)- forage fish
with natural recruitment
Late summer pelagic PPr in the mixed layer is
influenced by zooplankton grazing pressure
governed by trout, deep PPr variability results
from changes in climate condition
(Jassby et al. 1990, L&O)
Current working conceptual model for understanding
linkages between climate, fisheries stocking, and
carbon transfer across the landscape
Outline
• Lakes as sentinels of climate change
– Physical and biological alterations linked to local and
regional processes
• Castle Station history: now the America’s oldest,
continuous, mountain lake, ecological dataset
• Long-term dynamics of climate, environmental,
and biological variables
• What is the influence of climate and fish
manipulations on the zooplankton community
composition?
Objectives and methods for this analysis
1) Evaluate the interactions between two human driven influences, climate and fish manipulations
2) How important is climate and lake phenological characteristics in understanding lake primary
production?
3) How much does climate explain a shift in planktonic, primary consumers (zooplankton) during a
period of experimental fish manipulation and drought period?
3) What drives zooplankton community structure before and after this period and do lakes recovery
from these perturbations?
Long-term trend analysis using regression corrected for autocorrelation, some of the environmental
data is inherently nonlinear
Created a hypothesized model to determine the influence of climate and fish manipulation on
zooplankton structure. Divided data into 3 periods and used structural equation modeling (SEM),
multivariate approach to look at a network of variables including latent variable, to understand the
drivers of planktonic biomass.
1958-1987 Pre major fish manipulation, climate driven period
1987-1994 “Experimental” fish manipulation and extended drought conditions
1995-2011 Climate driven manipulation with intermittent fish stocking and non stocking periods
4
1
0
1959
-1
1969
1979
1989
1999
2009
-2
-3
-4
-5
180
140
120
80
60
40
20
140
1979
1989
1999
Snow Water Content
p = 0.54, 8.1 cm increase over the 52 years
100
80
60
40
20
0
1959
1969
1979
1989
1999
140
120
100
80
1959
2009
1969
1979
1989
1999
2009
Minimum air temperature in August
p = 0.0002, 4 degree increase over the 52
13
12
11
10
9
8
7
6
5
4
1959
2009
Winter condition
120
1969
160
34
1969
1979
1989
1999
2009
Maximum Air Temperature in August
p = 0.02, 2.2 degree increase over 52 years
32
30
28
26
24
22
20
1959
1969
1979
1989
1999
2009
Summer condition
100
0
1959
180
14
Precipitation in late winter (Jan - March)
p = 0.44, 6.6 cm increase over the 52 years
Winter condition
160
200
Winter condition
2
Winter condition
3
Ice out date
p = 0.003, 48 days later over the 52
220
Minimum Air Temperature in April
p = 0.02, 2.1 degree increase over 52 years
12
Minimum Temperature
10
(All months are significantly different)
1959 - 1987
1995 - 2011
Temperature °C
8
6
4
2
0
-2
-4
-6
Jan
35
Feb
Mar
Apr
May
June
July
Aug
Sept
Oct
Nov
Dec
Maximum Temperature
*
(* indicate significant change)
*
Temperature °C
30
25
*
20
15
10
5
0
Jan
Feb
Mar
Apr
May
45
July
Aug
Sept
Oct
Nov
Dec
Oct
Nov
Dec
Precipitation
40
Centimeters of Precipitation
June
(* indicate significant change)
35
30
25
20
15
*
10
*
5
*
0
Jan
Feb
Mar
Apr
May
June
July
Aug
Sept
Water temp August 0-5 meters
p = 0.19, 0.33 degree increase over the 52 years
22
21
20
19
18
17
1959
5
4.5
1969
1979
1989
1999
Lake Temperature
23
2009
Shallow Primary productivity (0-12 m)
p = 0.18, .74 increase over the 52 years
4
3.5
3
2.5
1
0.5
0
1959
1969
2.5
1979
1989
1999
2009
Deep Primary Productivity (13-32 m)
p = 0.18, 0.4 decrease over the 52 years
2
1.5
1
0.5
0
1959
1969
1979
1989
1999
2009
Primary production
2
1.5
5
Carbon grams/square meter
Shallow pooled mixed layerp = 0.0003
b
pelagic PPr increases during the
a
drought and fish manipulation
“experiment”, returning to
a
previous condition after the
p = 0.045
experiment.
Primary Productivity
p = 0.0001
b
p = 0.0045
4
3
a
b
a
a
a
a
2
How much does climate
a,bthe bamount of
influence
productivity during this
experimental period?
1
0
pre
exp
pos t
pre
PPr 0 - 32
3500
pos t
PPr 0 - 12
p = 0.0001
Fish Stocking
b
2500
2000
p = 0.366
1500
a
1000
500
0
pre
exp
pos t
Fi ngerl i ng
pre
exp
Ca tcha bl e
pre
exp
pos t
PPr 13 - 32
b
3000
Pounds of fish stocked
exp
pos t
pre
exp
PPr 0 - 5
pos t
Outline
• Lakes as sentinels of climate change
– Physical and biological alterations linked to local and
regional processes
• Castle Station history: now the America’s oldest,
continuous, mountain lake, ecological dataset
• Long-term dynamics of climate, environmental,
and biological variables
• What is the influence of climate and fish
manipulations on the zooplankton community
composition?
Primary Productivity 0 - 5 meters
5
Fish Experiment / drought period
4
3
2
1
1987
1988
1989
1990
1991
1992
1993
1994
1995
Carbon grams/square meter
p = 0.0003
Primary Productivity
5
Shallow pooled mixed layer (0-5 m) pelagic
b
PPr increases during the drought andafish
manipulation “experiment”, returning to
a
previous
condition
after
the
experiment.
p = 0.045
p = 0.0001
b
p = 0.0045
4
3
b
a
a
a
a
a
Total zooplankton biomass remains the
a,bthere
b is change in the functional
same but
players.
2
1
0
pre
e xp
pos t
pre
PPr 0 - 32
80
e xp
pos t
pre
PPr 0 - 12
e xp
pos t
pre
PPr 13 - 32
PPr 0 - 5
Zooplankton
70
p = 0.047
µg/liter
60
50
40
30
a
p <0.0001
a
b
20
10
b
a,b
b
p <0.0001
p = 0.145
b
p = 0.0002
b
a
a
p = 0.1538
b b
0
pre exp pos t
Di a ptomus
pre exp pos t
pre exp pos t
pre exp pos t
Cycl opoi d
Da phni a
Bos mi na
pre exp pos t
Hol opedi um
e xp
pre exp pos t
Total
pos t
Zooplankton trends from an interannual viewpoint, not aggregated over period
35
Cyclopoid biomass
p = 0.8, 7 increase over the 52 years
30
55
50
45
25
Daphnia biomass
p = 0.06, 13 increase over the 52 years
40
35
20
30
25
15
20
10
15
10
5
5
0
1959
35
30
1969
1979
1989
1999
2009
0
1959
35
Diaptomus biomass
p = 0.11, 12 decrease over the 52 years
30
25
20
20
15
15
10
10
5
5
0
1959
0
1959
1979
1989
1999
2009
1979
1989
1999
2009
1999
2009
Holopedium biomass
p = 0.04, 8 decrease over the 52 years
25
1969
1969
1969
1979
1989
1959 - 1987
1995 - 2011
Summary of findings and future directions
Long-term trends do not suggest changes in ice out, snow water content however, summer
(min & max) and winter (min) air temperature is increasing.
Shallow PPr is increasing but there are distinct periods of change; deep water PPr is
decreasing.
Climate does explain the change during the drought period as expected but the manipulation
of fishes may cause an increase in PPr. Two decades are needed for the primary production
to recover. Is this mediated through the zooplankton or nutrient excretion?
Total zooplankton biomass has not changed over time. Functional players of zooplankton
have shifted in the last 2 decades particularly in the copepod community which is dominated
by cyclopoids.
Fish are implicated in changing zooplankton community structure in recent times compared
to the historical period likely due to the amount of stocking which seems to change the
influence of lake variables on select taxa composition.
Fish and climate (drought condition) together trump planktonic production and consumer
composition, how long does it take to recover? Life history must matter? What about the
influence of prior years on subsequent years? Ice out does not change but is something
going on with nutrient cycling in the winter?
Back to our conceptual model… now, we are focusing on maintaining
our pelagic monitoring program but expanding to the collection of
benthic production and invertebrate emergence, watershed inflow
measurements for nutrients, winter sampling, fish analysis, linkages to
terrestrial consumers (e.g. bats)
Thanks for listening, come
collaborate with us!