Katie DeGoosh Emily Schilling, Cynthia Loftin, Katherine Webster There’s something fishy about fly...
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Transcript of Katie DeGoosh Emily Schilling, Cynthia Loftin, Katherine Webster There’s something fishy about fly...
Katie DeGoosh
Emily Schilling, Cynthia Loftin, Katherine Webster
There’s something fishy about fly larvae: Chaoborus assemblages as an indicator of fishless lakes
1. Question
2. Background on Fishless Lakes
3. Chaoborus: Ecology and Biology
4. Field and lab methods
5. Results
Species assemblages
Logistic regression model
Evaluating the model
6. Conclusions
Do Chaoborus assemblages
in surface sediment
indicate fishless lakes?
Question
Naturally fishless lakes?
Landscape barriers
Naturally fishless lakes?
Landscape barriers
Hydrologically Isolated
Naturally fishless lakes?
Landscape barriers
Steep outletsHydrologically Isolated
Why study fishless lakes?
Unique communities
Sparse distribution
Unique Communities
Zooplankton
Unique Communities
Insects
Unique Communities
Unique Communities
Chaoborus
5 common species
1. Chaoborus Sayomia
(punctipennis/albatus)2. Chaoborus flavicans3. Chaoborus trivitattus4. Chaoborus americanus
(Uutala, 1990)
MOST CHAOBORUS
Vertically migrate
(von Ende, 1979)
C. americanus
NO vertical migration
(von Ende, 1979)
C. americanus
NO vertical migration
(von Ende, 1979)
Chaoborus Life Cycle
adult
eggs
1st instar
2nd instar
3rd instar4th instar
Head of Chaoborus
Chaoborus mandibles
90 microns
Mandibles can
be found in
lake sediment
Do Chaoborus assemblages
in surface sediment
indicate fishless lakes?
Question
N
Fish-full
Fishless
Selection of Study Lakes
21 Lakes*
10 Fishless 11 Fish-full
Low High Low High Elevation Elevation
7 55 5
*Paired for landscape attributes; verified fishlessness
Core Samples
3 cores at each lake
Sample Analysis
Finding Mandibles
Identification
Slide Mount
Results
1. Species assemblage
2. Determining important variables 3. Logistic regression model
4. Model Accuracy Table
5. Evaluating the model
Species Assemblage
0%
20%
40%
60%
80%
100%
Apple
Cloud
Duck
Kerose
neLoo
n
Mid
day
Mud
North
Unnam
ed 83
85
Unnam
ed 96
33
Fishless Lakes
C. Sayomia C. americanus C. trivitattus
74307 33 82 45 9 97 1 61
Fishless
Lakes
Species Assemblage
Fish
Lakes0%
20%
40%
60%
80%
100%
Lakes with Fish
C. Sayomia C. americanus C. trivittatus
6 6 13 0 0 0 12 73 107 66 1
Stepwise Logistic Regression
Which variables best contribute to a model that indicates a fish lake ?
Chaoborus abundance
% C. americanus
% C. Sayomia
% C. trivitatus
Area (m2)
Elevation (m)
Max. Depth (ft)
pH
Modeling fishless lakesusing stepwise logistic regression
Variables in model Value P-value
Constant -2.297 0.028
Percent C. americanus 0.04 0.021
Modeling fishless lakesusing stepwise logistic regression
Variables in model Value P-value
Constant -2.297 0.028
Percent C. americanus 0.04 0.021
Logistic prob. = B0 + B1x
Modeling fishless lakesusing stepwise logistic regression
Variables in model Value P-value
Constant -2.297 0.028
Percent C. americanus 0.04 0.021
Log(p/(1-p)) = -2.297 + .04 (% am)
Logistic prob. = B0 + B1x
Modeling fishless lakesusing stepwise logistic regression
Log(p/(1-p)) = -2.297 + .04 (% am)
Modeling fishless lakesusing stepwise logistic regression
Log(p/(1-p)) = -2.297 + .04 (% am)
Rearranged:
prob = EXP(-2.297 + .04 (% am))
1+ EXP(-2.297 + .04 (% am))(fishless)
Graphing the model
0 10 20 30 40 50 60 70 80 90 100Percent C. americanus
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
Pro
babi
lity
(fis
hles
s)
Fishless LakesFish Lakes
Lake Status
Lake Status
Fish Lakes
Fishless Lakes
3
4
Observed:
Predicted: FISH FISHLESS
Fish 5 3
Fishless 3 7
Total 8 10
Correct 62% 70%
Model Accuracy Table
Observed:
Predicted: FISH FISHLESS
Fish 5 3
Fishless 3 7
Total 8 10
Correct 62% 70%
Model Accuracy Table
Observed:
Predicted: FISH FISHLESS
Fish 5 3
Fishless 3 7
Total 8 10
Correct 62% 70%
Model Accuracy Table
Observed:
Predicted: FISH FISHLESS
Fish 5 3
Fishless 3 7
Total 8 10
Correct 62% 70%
Model Accuracy Table
Observed:
Predicted: FISH FISHLESS
Fish 5 3
Fishless 3 7
Total 8 10
Correct 62% 70%
Model Accuracy Table
Observed:
Predicted: FISH FISHLESS
Fish 5 3
Fishless 3 7
Total 8 10
Correct 62% 70%
Model Accuracy Table
Using the model
Using the model
Using the model
History in Sediment Core
Recentsediment
Old sediment
History in Sediment Core
Recentsediment
Old sediment
Current Conditions
History in Sediment Core
Recentsediment
Old sediment
Current Conditions
Historical
History in Sediment Core
Evaluating the model
3 Historically fishless lakes
Evaluating the model
3 Historically fishless lakes
Speck
Stocked in 1962
Evaluating the model
3 Historically fishless lakes
Tumbledown
Stocked in 1966
Speck
Stocked in 1962
Evaluating the model
3 Historically fishless lakes
Tumbledown
Stocked in 1966
Speck
Stocked in 1962
Ledge
Stocked in 1968
Evaluating the model
3 Historically fishless lakes
TumbledownSpeck Ledge
Evaluating the model
3 Historically fishless lakes
TumbledownSpeck Ledge
Pb-Dated Sediment CoresSteve Norton, Ron Davis (Davis, 1994)
Evaluating the model
3 Historically fishless lakes
TumbledownSpeck Ledge
19571956
1952
r = 3 r = 1 r = 2
Species Assemblage
0%
20%
40%
60%
80%
100%
Tumbledown(1956)
Speck (1957) Ledge (1953)
Historically Fishless Samples
C. americanus C. Sayomia C.flavicans
41 2327
Species Assemblage
0%
20%
40%
60%
80%
100%
Tumbledown(1956)
Speck (1957) Ledge (1953)
Historically Fishless Samples
C. americanus C. Sayomia C.flavicans
41 2327
90%
57%70%
Applying the model
0 10 20 30 40 50 60 70 80 90 100Percent C. americanus
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
Pro
babi
lity
(fis
hles
s)
Fishless LakesFish Lakes
Lake Status
Lake Status
Fish Lakes
Fishless Lakes
0 10 20 30 40 50 60 70 80 90 100Percent C. americanus
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
Pro
babi
lity
(fis
hles
s)
Fishless LakesFish Lakes
Lake Status
Speck Pond
70%
C.americanus
62% probability (fishless)
Applying the model
0 10 20 30 40 50 60 70 80 90 100Percent C. americanus
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
Pro
babi
lity
(fis
hles
s)
Fishless LakesFish Lakes
Lake Status
Ledge Pond
90%
C. americanus
78% probability (fishless)
Applying the model
0 10 20 30 40 50 60 70 80 90 100Percent C. americanus
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
Pro
babi
lity
(fis
hles
s)
Fishless LakesFish Lakes
Lake Status
Tumbledown
57%
C. americanus
49% probability (fishless)
Applying the model
Conclusions• Chaoborus mandible assemblages in surface sediments
DO indicate fishless lakes
• The dominant species in fishless lakes is Chaoborus americanus
• Logistic regression can be used to find the probability that a given sample reflects fishless conditions
Log(prob) = 2.297 + 0.04 (% C. americanus)
• The model accurately classifies fishless lakes 70% of the time
• Historically fishless ponds can be identified by applying the model to sediment core samples
Committee Members: Dennis Anderson
Cynthia Loftin Michael Kinnison
Katherine Webster Ann Dieffenbacher-Krall
Diadem Strout
Kim Gibbs
Jason Houle
Paul Kusnierz
Christine Guerette
Field and Lab Assistants
Dawn Bavaro
Anne Fleischman
Matthew Day
Rebecca Clark
Additional Funding
Penobscot County Conservation AssociationUM Association of Graduate Students
Keith McCullough
Benjamin Reining
Erin Wilkinson
Jennifer Wilcox
Catherine Gannoe