aquatic ecosystem vulnerability to fire and climate … · objectives–stakeholder workshops, tool...

AQUATIC ECOSYSTEM VULNERABILITY TO FIRE AND CLIMATE CHANGE IN ALASKAN BOREAL FORESTS

Jeff Falke USGS, AKCFWRU, UAF

Scott Rupp, Peter BieniekInternational Arctic Research Center, UAF

Helene Genet, Stephen Klobucar, Deanna KlobucarInstitute of Arctic Biology, UAF

Elizabeth HinkleCollege of Fisheries and Ocean Sciences, UAF

Project Funding and Collaborators

Fire and Climate Change – Increasing Fire Likelihood

Moritz et al. (2012)

Fire in Alaska – A Changing Landscape

Since 1980’s• Higher frequency• Longer duration• Longer season

Alaska Wildfire Perimeters 1940-Present

Fire in Alaska – A Changing Landscape

Consequences of Climate Change in Boreal Alaska

Vegetation Permafrost

Pastick et al. 2016

• Decreased stream channel stability

• Greater and more variable discharge

• Altered wood dynamics

• Increased nutrient availability

• Higher sediment delivery

• Increased solar radiation

• Altered water temperature regimes

(Dunham et al. 2003; Bixby et al. 2015)

Fire and Aquatic Ecosystems – Conceptual Relationships

(Gresswell 1999)

Fire and Aquatic Ecosystems – Effects on Fish

Elevation (m)

1000 1400 1800

Pro

babili

ty o

f e

xceedin

g 2

0⁰C

0.2

0.4

0.6

0.8

1.0

Dunham et al. 2007Rosenberger et al. 2011; 2015

Unburned

Burned

Burned & Reorganized

Terr

estr

ial I

nve

rteb

rate

s in

Die

t (%

)

Open Canopy (%)

Burned reaches

• Abundance (> Age 0)

• Size-at-age

• Lipid content

• Age at maturationRainbow trout

Fire and Aquatic Ecosystems – Fish Population Vulnerability

Falke et al. 2015

Regional Fire Size

MeanMean + 25%

Habitat Size x Fire Life-stage Pre/Post-Fire

Flitcroft et al. 2016

Fire and Aquatic Ecosystems – Fish Population Vulnerability

Flitcroft et al. 2016

Boreal Fire and Aquatic Ecosystems – Project Overview

GOAL: Assess aquatic ecosystem vulnerability to fire and climate change and identify factors that drive vulnerability

Obj. 1: Characterize physical and biological mechanisms that drive aquatic habitat dynamics and productivity – fieldwork and modeling

Obj. 2: Assess aquatic ecosystem vulnerability via spatially-explicit predictions of fire effects on aquatic habitats under current and future vegetation, permafrost, and climate scenarios – model integration, vulnerability analysis

Obj. 3: Develop decision support tools to translate research results to assist management decision making and meet conservation objectives– stakeholder workshops, tool development

Boreal Fire and Aquatic Ecosystems – Project Flowchart

(1) Sample Aquatic Ecosystems

(2) Integrate Environmental Models

(2) Analyze Vulnerability

(1) Conduct Food Web and Ind. Based Modeling

(3) Develop Fire Management Scenarios

(3) Develop Decision Support Tools

Bixby et al. 2015

Local scale Regional scale

• Interior Alaska boreal forest

• Tributaries to Tanana & Yukon Rivers

• 3,700 km2 burned since 1984

• Important Chinook salmon producers and Arctic grayling fisheries

North Fork Chena River

Boreal Fire and Aquatic Ecosystems – Study Area and Design

Boreal Fire and Aquatic Ecosystems – [1] Fish and Habitat

HabitatChannel and bank topographyCover and substrateVelocity (“2-D” models)

EcohydrologyStream flowWater temperatureWater chemistry/Nutrients

Fish Community structurePrey availability and dietGrowth ratesBody conditionMaturation status

Boreal Fire and Aquatic Ecosystems – [1] Fish and Ecosystem Modeling

Aquatic Trophic Productivity

inSTREAM

Water temperatureNutrients

Channel hydraulicsRiparian structure

DepthVelocity

Water temperatureTurbidity

Primary, secondary,tertiary productivity

Fish growth ratesConsumption

Survival

Population biomass, growth, survival

Physical PhysicalBiological

Climate Climate








Bixby et al. 2015


Boreal Fire and Aquatic Ecosystems – [2] Model Integration

WRF ERA Interim

Downscale

20km grid 0.75° grid

Weather Research and Forecasting Model(WRF; Skamarock et al. 2008)


Fire, Vegetation, and Permafrost Models(ALFRESCO; Rupp et al. 2002; DVM-DOS-TEM; Genet et al. 2013)

Watershed Processes (NetMap)Hydrology (VIC)

Stream Temperature (LST)


Digital Landscape Model(NetMap; Benda et al. 2007)


Digital Landscape Model(NetMap; Benda et al. 2007)

Middle Fork Chena River – Generalized Erosion Potential


Fire history 20002010 1990 1980 1970 19501960

Fire history data source: BLM


Stream Temperature Model(LST; see Falke et al. 2015 & Flitcroft et al. 2016 for fire applications)

InputsLand surface temperature (NASA Modis)Observed stream temperature (Sensor network)Synthetic stream network (NetMap)

OutputDaily stream temperature

Chena River basinChinook salmon growth


Hydrologic Model(VIC; Liang et al. 1994; Bennett 2014)

InputsPrecipitation

Air temperature

Wind speed

Land cover/vegetation

Frozen ground (permafrost)

Synthetic stream network

Soils

OutputDaily hydrographs

Flow regime metrics

Climate models

ALFRESCO

DVM-DOS-TEM

NetMap

Boreal Fire and Aquatic Ecosystems – [2] Vulnerability Analysis

Low

High

Vulnerability

Low

High

Uncertainty

Falke et al. 2015 Psi(Gradient)

Low (0-0.33)Moderate (0.33-0.66)High(0.66-1.00)

41.844.214.0

0.404 ± 0.25

Gradient (%)

0 to 0.020.02 to 0.040.04 to 0.060.06 to 0.080.08 to 0.10.1 to 0.120.12 to 0.140.14 to 0.160.16 to 0.180.18 to 0.20.2 to 1.5

22.610.69.567.586.334.894.143.553.162.7924.9

0.259 ± 0.39

grad_int grad_slope

Psi(W95)

Low (0.00-0.33)Moderate (0.33-0.66)High (0.66-1.00)

19.415.964.7

0.648 ± 0.28

w95_slope w95_int

Psi(Temp)


51.121.927.0

0.417 ± 0.3

temp_int temp_slope

Maximum Temperature

0 to 1010 to 1111 to 1212 to 1313 to 1414 to 1515 to 1616 to 1717 to 1818 to 2020 to 2222 to 24>= 24

1.292.024.217.199.4310.39.9810.110.117.211.25.111.85

16.7 ± 3.6

Max Temp Input

0 to 1010 to 1111 to 1212 to 1313 to 1414 to 1515 to 1616 to 1717 to 1818 to 2020 to 2222 to 24>= 24

.047

.0340.3010.113.912.36.719.9711.622.110.41.960.50

16.6 ± 2.9

SD

0 to 11 to 22 to 33 to 44 to 5>= 5

4.4279.015.90.64.037.002

1.63 ± 0.55

Reach Habitat Suitability

PoorModerateHigh

33.246.020.8

1.88 ± 0.72

Psi(Summer Flow)


41.157.61.35

0.364 ± 0.2

Mean Summer Flow (cfs)

0 to 7070 to 140140 to 210210 to 280280 to 350350 to 420420 to 490490 to 560560 to 630630 to 1495.56

89.32.381.120.932.340.83.0031.561.54.003

65.9 ± 110

sflow_slope sflow_int sflow_slope_2

Winter High Flow Events (d)

0 to 1.21.2 to 2.42.4 to 3.63.6 to 4.84.8 to 66 to 7.27.2 to 8.48.4 to 9.69.6 to 10.810.8 to 15.45

32.823.310.88.598.755.234.062.052.561.79

3.12 ± 2.9

Bayesian Network ApproachTrack uncertaintyQuantitative + QualitativeAccount for new informationSpatially-explicitMultiple scenarios

Chinook salmonSpecies of concernIntegrate stressorsLife-stage specific

Vulnerability analysis(Falke et al. 2015; Flitcroft et al. 2016)








Bixby et al. 2015


Boreal Fire and Aquatic Ecosystems – [3] Scenario Development

DoD Lands

SERDP RC-2109

Alaska Statewide Fire Management Options

Critical Protection - provide complete protection to identified sites and control the fire at the smallest acreage reasonably possible.

Full Protection - control the fire at the smallest acreage reasonably possible.

Modified Protection - reduce overall suppression costs without compromising protection of higher-valued adjacent resources.

Limited Protection - minimize suppression costs without compromising protection of higher-valued adjacent resources.

New Management

Current Management


Moderately warm / wetter

Very warm / drier

Historical

Current FMPO

Alternative FMPO

Current FMPO

Alternative FMPO

SERDP RC-2109

Are

a b

urn

ed (

km2)

Are

a b

urn

ed (

acre

s)

Year

Fire Management Planning Option (FMPO)


SERDP RC-2109

Jeff Falke, U.S. Geological SurveyAlaska Cooperative Fish and Wildlife Research UnitInstitute of Arctic Biology &College of Fisheries and Ocean SciencesUniversity of Alaska Fairbanks [email protected](907) 474-6044

aquatic ecosystem vulnerability to fire and climate … · objectives–stakeholder workshops, tool...

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