YKL REA Aquatics
Becky
Shaftel
, Leah Kenney,
and
Timm
Nawrocki
Aquatics in the REA
Conservation elements
Distribution mapping methods and results
Conceptual models
Management questions
Aquatic conservation elements
Coarse filters
•
Streams and rivers
•
Connected lakes
•
Disconnected lakes
Fine filters
•
Chinook salmon
•
Chum salmon
•
Sheefish
•
Dolly
Varden
•
Northern pike
Photo: ADF&G
Photo: ADF&G
Streams and rivers
Methods:
flowlines
from the USGS
National Hydrography
Dataset
Results:
Length = 454,000 km
Connected lakes
Methods:
waterbodies
connected to
flowlines
in the
National Hydrography
Dataset
Results:
Count = 31,600 lakes
Area = 25,800 km
2
Photo: USFWS
Disconnected lakes
Methods:
waterbodies
not
connected to
flowlines
in the
National Hydrography
Dataset
Results:
Count = 103,600 lakes
Area = 9,400 km
2
Photo: USFWS
Chinook Salmon
Methods: Clipped
from the
Anadromous
Waters Catalog event
feature class
Results:
Photo: USFWS
AWC Life Stage
Designation
Length
(km)
Spawning Habitat
5,436
Present or Rearing
13,522
Chum Salmon
Photo: USFWS
Methods: Clipped
from the
Anadromous
Waters Catalog event
feature class
Results:
AWC Life Stage
Designation
Length
(
km)
Spawning Habitat
5,902
Present or Rearing
8,640
Sheefish
Photo: USFWS
Methods: Clipped
from
the
Anadromous
Waters Catalog event
feature class
Results:
AWC Life Stage
Designation
Length
(
km)
Spawning Habitat
117
Present
6,036
Fish Distribution Models
Photo: USFWS
Evaluate model
performance
Classification tree
and random forest
models
ADF&G AFFID
species
occurrence data
GIS source data
Predict species
habitat across REA
study area
Fish
distributions
Create stream
network and
landscape predictor
variables in GIS
Process AFFID data
for use in models
Stream Network
Used
TauDEM
to process DEM
1.
Add in additional HUCs on boundary of study area that
flow into the study area
2.
Fill pits
3.
Calculate flow direction (D8 method)
4.
Calculate contributing area
5.
Create stream network based on curvature method and
drop analysis
Predictor Variables
Photo: USFWS
Predictors of Fish Habitat
Elevation
Permafrost
Gradient
Slope over area ratio
Stream order
Watershed area
Average watershed annual
precipitation
Average watershe
d annual
temperature
Average
watershed elevation
Average watershed slope over area
ratio
Average watershed slope
Percent permafrost cover in
watershed
Percent lake cover in watershed
Process AFFID data
-
Select all presences by
fish in AFFID
-
Select absences from
projects in AFFID that
listed fish community
sampling as an objective
-
Resample data in areas of
high intensity to match
densities in other HUCs
-
Shift points along flow
direction grid until they
reached the stream
network
-
Extract all predictor
variables to each data
point for model
development
Classification Trees
Photo: USFWS
Classification Tree Analysis
Steps:
–
Identify the groups
–
Choose the variables
–
Identify the split that
maximizes the
homogeneity of the
resulting groups
–
Determine a stopping
point for the tree
–
Prune the tree using
cross
-
validation
Absent
0.97
(263)
Asterospicularia laurae
Shelf: Inner, Mid
Shelf: Outer
Absent
0.78
(64)
Location: Back, Flank
Location: Front
Depth < 3m
Depth
≥
3m
(De'Ath and Fabricious 2000)
Absent
0.56
(9)
Present
0.81
(37)
Misclassification rates: Null
= 15%, Model = 9%
Random Forests
Creates many classification trees and combines predictions
from all of them:
-
Start with bootstrapped samples of data
-
Observations not included are called out
-
of
-
bag (OOB)
-
Fit a classification tree to each bootstrap sample, for each
node, use a subset of the predictor variables.
-
Determine the predicted class for each observation based
on majority vote of OOB predictions
-
To determine variable importance, compare
misclassification rates for OOB observations using true and
randomly permuted data for each predictor
Run models in R
ct1<
-
mvpart
(
pres.f~.,data
=fish.pred1[s1,],xv="1se")
rf1<
-
randomForest
(
pres.f~.,data
=fish.pred1[s1,],
ntree
=999
)
Photo: USFWS
CT training
CT validation
RF training
RF validation
1
0.271
0.327
0.248
0.264
2
0.273
0.27
0.262
0.226
3
0.265
0.264
0.24
0.245
4
0.271
0.358
0.238
0.233
5
0.271
0.264
0.251
0.252
6
0.283
0.352
0.257
0.239
7
0.292
0.321
0.249
0.258
8
0.214
0.302
0.246
0.226
9
0.244
0.252
0.265
0.214
10
0.297
0.296
0.267
0.245
summary
0.2681
0.3006
0.2523
0.2402
Model Performance
Photo: USFWS
Confusion Matrix
0
1
Error
0
313
96
23.5%
1
98
282
25.8%
Dolly
Varden
Results:
~ 32,000 km of predicted
summer habitat (restricted to
stream reaches > 1 km in
length)
Photo: USFWS
Predictor
1
0
watershed
elevation
541 m
299
m
watershed slope
22%
10%
watershed
annual
precip
.
596 mm
521 mm
watershed
annual temp.
-
1.36 C
-
1.41 C
Watershed area
71 km
2
1,665
k
m
2
Invasive
Macrophytes
Climate
Change
Precipitation
Permafrost
Fire
Human Uses
Mining
Change Agents
Drivers
CE
General Effect
Infrastructure
Harvest
Contaminants
Temperature
Permafrost thaw
Reduction in age at maturity and shift in
spawning season
Habitat loss, changes in migration routes, increased
sedimentation
Reduction in juvenile fitness;
bioaccumulation in adults
Direct population decline
Expanded ice
-
free season
Temporary increases in nutrient inputs; increase
sedimentatitation
Reduction in habitat
Increased toxicity
Increased potential for establishment of invasive macrophytes and changing fire dynamics
Increased contaminant sources
Change in
deposition rates
Changes in hydrology
Fish species
Habitat
Increase in ground flow;
increase in sedimentation
Invasive
Macrophytes
Climate
Change
Precipitation
Permafrost
Fire
Human Uses
Mining
Infrastructure
Harvest
Contaminants
Temperature
Permafrost thaw
Reduction in age at maturity and shift in
spawning season
Reduction in juvenile fitness;
bioaccumulation in adults
Expanded ice
-
free season
Temporary increases in nutrient inputs
Elodea
spp
could reduce quality of foraging habitat
Increased toxicity
Increased potential for establishment of invasive macrophytes and changing fire dynamics
Increased contaminant sources
Change in
deposition rates
Increased winter
precipitation may increase
overwintering habitat
Dolly
Varden
Salvelinus
malma
Habitat
Increase groundwater flow
i
mproves overwinter
habitat
Direct destruction of habitat, hindrance of migration routes,
increased downstream turbidity and sedimentation
Change Agents
Drivers
CE
General Effect
CE
-
Specific Effect
Direct population decline
Invasive
Macrophytes
Climate
Change
Precipitation
Permafrost
Fire
Human Uses
Mining
Infrastructure
Harvest
Contaminants
Temperature
Permafrost thaw
Reduction in age at maturity and shift in
spawning season
Bioaccumulation of
mercury in adults
Expanded ice
-
free season
Temporary increases in nutrient inputs
Elodea
ssp
could reduce quality of spawning habitat
In creased toxicity
Increased potential for establishment of invasive macrophytes and changing fire dynamics
Increased contaminant sources
Change in
deposition rates
Northern Pike
Esox
lucius
Habitat
Increase depth of active
layer will increase
lake
drainage area
Subsistence harvest pressures on
overwintering populations
Direct destruction of habitat, hindrance of migration routes,
increased downstream turbidity and sedimentation
Change Agents
Drivers
CE
General Effect
CE
-
Specific Effect
Increased winter
precipitation may increase
overwintering habitat
Invasive
Macrophytes
Climate
Change
Precipitation
Permafrost
Fire
Human Uses
Mining
Infrastructure
Harvest
Contaminants
Temperature
Permafrost thaw
Reduction in age at maturity and shift in
spawning season to later
Reduction in juvenile fitness;
bioaccumulation in adults
Expanded ice
-
free season
Reduction in juvenile feeding habitat
In creased toxicity
Increased potential for establishment of invasive macrophytes and changing fire dynamics
Increased contaminant sources
Change in
deposition rates
High winter flow may affect
spawning habitat
Sheefish
Stenodus
leucichthys
Habitat
Direct population decline and removal
of mature, healthy individuals
Direct destruction of habitat, hindrance of migration routes,
increased downstream turbidity and sedimentation
Change Agents
Drivers
CE
General Effect
CE
-
Specific Effect
Sedimentation of gravel
-
substrate in streams will reduce quality of spawning habitat
Sedimentation of gravel
-
substrate
will
reduce
quality of
spawning
habitat
Invasive
Macrophytes
Climate
Change
Precipitation
Fire
Human Uses
Mining
Infrastructure
Harvest
Temperature
Permafrost thaw
Reduction in age at maturity; earlier spawning
season; increased parasite infection
Habitat loss, changes in migration routes, increased
sedimentation
Expanded ice
-
free season
Reduction in spawning and rearing habitat
Increased potential for establishment of invasive macrophytes and changing fire dynamics
Chinook Salmon
Oncorhynchus
tshawytscha
Habitat
Direct population decline and removal of
mature, healthy individuals
Change Agents
Drivers
CE
General Effect
CE
-
Specific Effect
Contaminants
Increased toxicity
Increased contaminant sources
Change in
deposition rates
Increase in winter habitat
for juveniles
Permafrost
Reduction in juvenile fitness
Increase stream flow overwinter
reduce egg survival
Sedimentation of gravel
-
substrate will reduce quality of spawning
habitat;
Temporary increases in nutrient
inputs could increase juvenile foraging
Invasive
Macrophytes
Climate
Change
Precipitation
Permafrost
Fire
Human Uses
Mining
Infrastructure
Harvest
Temperature
Permafrost thaw
Reduction in age at maturity; earlier spawning
season; increased egg incubation time
Habitat loss, changes in migration routes,
increased sedimentation
Expanded ice
-
free season
Increased potential for establishment of invasive macrophytes and changing fire dynamics
Chum Salmon
Oncorhynchus
keta
Habitat
Increased stream discharge
could increase
sedimentation and scour
eggs
Direct population decline and removal of
mature, healthy individuals
Change Agents
Drivers
CE
General Effect
CE
-
Specific Effect
Increase stream flow
overwintr
reduce quality of
spawning habitat and egg survival
Reduction in spawning habitat
Sedimentation of gravel
-
substrate in streams will reduce quality of spawning habitat
Invasive
Macrophytes
Connected
Lakes
Change
Agents
Drivers
CE
Permafrost
Human Uses
Mining
Infrastructure
Decrease in lake area; lake
drainage;
increase in methane emissions
Outcompete native aquatic and emergent vegetation
Increased potential for establishment of invasive macrophytes and changing fire dynamics
Lake drying
in summer decreasing connectivity; expanded
ice
-
free season
allow for early
wildlife use (birds and fish);
changes in thermal regimes
Fire
Temporary increases in
nutrient inputs ;
postfire
landslides and debris
flows
Permafrost
thaw
Climate
Change
Precipitation
Temperature
Direct destruction of
lake habitat
Lake area increase through increased precipitation; increased winter
habitat
for aquatic species
Invasive
Macrophytes
Disconnected
Lakes
Change
Agents
Drivers
CE
Permafrost
Human Uses
Mining
Infrastructure
Outcompete native aquatic and emergent vegetation; faster growing vegetation
overtaking lake area
Increased potential for establishment of invasive macrophytes and changing fire dynamics
Direct destruction of
lake habitat
Fire
Temporary increases in nutrient
inputs;
postfire
landslides and debris
flows
Lake area increase through increased
precipitation;
increased winter
habitat for aquatic species
Permafrost thaw
Lake drying in summer decreasing
lake area;
expanded ice
-
free season allow for early wildlife use (birds and fish);
changes in thermal regimes
Climate
Change
Precipitation
Temperature
Decrease in lake area; lake drainage;
increase in methane emissions
Invasive
Macrophytes
Streams
Change
Agents
Drivers
CE
Permafrost
Human Uses
Mining
Infrastructure
Permafrost thaw
Altered
hydrologies
; increased channel disturbance from
flooding; increased discharge and sediment transport; increase in
winter precipitation will increase wildlife overwinter habitat
Outcompete native aquatic and emergent vegetation
Increased potential for establishment of invasive macrophytes and changing fire dynamics
Warming
could
increase extent
of available
habitats; l
ethal
temperature limits for fish and other aquatic organisms
;
change in thermal regimes
Direct destruction of stream habitat, change in conductivity, reduced
flow
Fire
Temporary increases in nutrient inputs;
post fire
landslides and debris flows; increased
channel
disturbance;
altered riparian vegetation and stream shade,
temperature change
regimes
Climate
Change
Precipitation
Temperature
Increased sedimentation rates
Management Questions
How
, where, and when could Essential Fish
Habitat (EFH) be affected by predicted changes in
climate
?
-
Primarily a literature review. SNAP does not
currently have models predicting changes in
aquatic habitats, such as stream temperature or
hydrologic regime
Photo: USFWS
Management Questions
Where and how might
mineral resource
development affect
fishery habitat?
-
From BSWI RMP: field
validated information on
historic and current
mining sites and high,
medium, and low
mineral potential by
sections
-
Other options include
ARDF and permit data
Photo: USFWS
Review
Please review and provide comments:
-
Distribution models for fish and habitats
-
Conceptual models and text descriptions for fish
Not yet final:
-
Northern pike distribution model
-
Conceptual models and text descriptions for habitats
Contact: Rebecca
Shaftel
rsshaftel@uaa.alaska.edu
, 907
-
786
-
4965
Photo: USFWS
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