Modeling Hydrologic Alteration and EcosystemResponse to Climate Change in theSoutheastern U.S.

Brian Hughes and Jacob LaFontaine,USGS, Atlanta, GA; Mary Freeman,USGS, Athens, GA; Jim Peterson, USGSCorvallis, OR

NWQMCPortland, ORMay 2, 2012

U.S. Department of the InteriorU.S. Geological Survey

Southeast Regional Assessment Project

SERAP is a pilot study for the USGS NCCWSC and CSC thatintegrates climate change, land-use change, and sea-level riseprojections with habitat and species response models to assessfuture climate effects on terrestrial and aquatic species

• Regional Climate Change Projections

• Coastal Assessment

• Terrestrial Assessment

• Aquatic Assessment

• Optimal Conservation Strategies

Project Team Members

Regionally Downscaled Probabilistic Climate Change Projections—AdamTerando, Murali Haran, Katharine Hayhoe, Klaus Keller

Integrated Coastal Assessment—Nathaniel Plant, Glenn Gutenspergen, VanWilson, Cindy Thatcher, Alexa McKerrow, Adam Terando, Scott Wilson, RobThieler, Peter Howd

Integrated Terrestrial Assessment—Alexa McKerrow, Adam Terando, SteveWilliams, Jamie Callazo, Barry Grand, Jim Nichols, Andrew Royle, John Sauer

Integrated Aquatic Assessment—Jim Peterson, Lauren Hay, Kenneth Odom,Brian Hughes, Robb Jacobson, John Jones, Mary Freeman, Jacob LaFontaine,Carrie Elliot, Steve Markstrom, Jeff Riley

Optimal Conservation Strategies—Barry Grand, Max Post van der Burg, KevinKliner, Allison Moody,

Dissemination of High-Resolution National Climate Change Dataset—JamieCollazo, Lauren Hay, Katharine Hayhoe, Nathaniel Booth, Adam Terando,Jason Hopkins, Roland Viger

Basic Questions Addressed by SERAP

What effects will climate changes have on terrestrial andaquatic ecosystems?• What are the likely impacts of future sea level rise on coastal habitats?

• How will stream flow changes alter habitat conditions necessary forhealthy fish and mussel populations?

• Will changes in vegetation and land use affect terrestrial habitats forbird populations?

What can we do to avoid the worst effects of climate change?• What are the causes and degree of uncertainty in forecasts of climate

change and responses?

• What are the benefits and effectiveness of adaptation strategies?

Probabilistic Global Climate Change Projections

Intermediate ComplexityModel Projections

Statistically Downscaled ClimateProjections

Simulationof ClimateDynamicProcesses

Urban GrowthSea-Level Rise

Projections

WatershedModeling

StreamTemperature

ChannelClassification

LandscapeDynamics

FutureHabitat

Conditions

Simulationof Physical,Social, andEconomicsDynamicProcesses Species-Habitat

Relations

VegetationDynamics

Succession-Disturbance

Models

CoastalHabitatChange

Simulation ofEcologicalDynamicProcesses

Fish and MusselOccupancy Models

Avian RangeDynamics

SERAP COMPONENTS DATA FLOW

Optimal Conservation Strategies

Develop ClimateChange AdaptationStrategies

Probabilistic Global Climate Change Projections

Intermediate ComplexityModel Projections

Statistically Downscaled ClimateProjections

Simulationof ClimateDynamicProcesses

Urban GrowthSea-Level Rise

Projections

WatershedModeling

StreamTemperature

ChannelClassification

LandscapeDynamics

FutureHabitat

Conditions

Simulationof Physical,Social, andEconomicsDynamicProcesses Species-Habitat

Relations

VegetationDynamics

Succession-Disturbance

Models

CoastalHabitatChange

Simulation ofEcologicalDynamicProcesses

Fish and MusselOccupancy Models

Avian RangeDynamics

SERAP COMPONENTS DATA FLOW

Optimal Conservation Strategies

Develop ClimateChange AdaptationStrategies

Climate Scenarios Simulated

Currently using only twoemission scenariosrepresenting worst caseand best case scenarios.

Regional Climate Downscaling

GCM

RCM

Present

GCMs(n = ~8)

EMIC(n = ~200)

DownscaledProbabilisticProjections

Bayesian ModelAveraging

StatisticalDownscaling

Projections

Methods

Output

Regional Climate Change ProjectionsClimate Models

Four-cluster multivariate channelclassification of the Potato Creek streamnetwork using LiDAR for validation

Aquatics Assessment - Stream Classification

Landscape Dynamics - Urban Growth

Urban Growth Model GigalopolisSLEUTH-R (Jantz et al 2009)

Urban Growth Model GigalopolisSLEUTH-R (Jantz et al 2009)

• Slope,

• Land Cover,

• Exclusion,

• Urbanization,

• Transportation, and

• Hillshade

Earlysuccession

Mid-open Late open

Mid-closed Late closed

Example: Dry longleaf pine

Future landscapeconditions

Input for habitatdistribution models:

priority species

Habitat-specific succession and disturbance models

Habitat types Stage and structure

A2 Weighted Mean

A1b Weighted Mean

B1 Weighted Mean

Hindcast Weighted Mean

Pre

dic

ted

acr

es

bu

rne

d

Landscape Dynamics - Vegetation

Landscape Dynamics – Disturbance

PrecipitationTemperature

Evapotranspiration

Drought

Insect OutbreakDiseaseFire Frequency

Hydrologic Modeling - PRMS

• PRMS is being used to developcoarse- and fine-scale watershedmodels

• Both coarse and fine scale modelswill incorporate probabilisticdownscaled climate changeprojections to predict daily stream-flow through 2100

Simulating Water Quality –PRMS/SNTEMP

• Stream temperature is beingsimulated using a coupledPRMS/SNTemp model

• SNTemp developed by USFWS andUSGS to predict how changes in flowregime affect water temperature

• Uses PRMS output parameters andphysical channel characteristics

• Daily minimum and maximumtemperatures through 2100 will bepredicted

Climate(station data)

WatershedAttributes

Mean and Max DailyWater Temperature, by

stream segment

PRMS

Daily Componentsof Flow, by stream

segment

Daily AirTemperature,

solar radiation, bystream segment

PRMS/SNTemp

ChannelAttributes

SNTemp

SNTemp DailyInput Files:

• Meteorology• Hydrology• Shade• Topology• Geometry

Key:PRMS/SNTemp

Models

User Input

SimulatedOutput

Coupled PRMS/SNTEMP

USGS 02338660 NEW RIVER AT GA 100 NEAR CORINTH, GA

USGS 02334885 SUWANEE CREEK AT SUWANEE, GA

USGS 02337170 CHATTAHOOCHEE RIVER NEAR FAIRBURN, GA

Ecological Modeling - Fish and musseloccupancy

• Empirical multi-state, multi-season occupancy model.

• Models estimate the occupancy (presence) of fish species in astream segment (defined as a section of stream from tributaryjunction to tributary junction).

• The dynamics of the populations (colonization, reproduction,extinction) are modeled as a function of geomorphic channelcharacteristics, stream size, seasonal discharge statistic, andstream temperature.

• Specific species characteristics (preferred habitat, locomotionmode, body size, spawning duration, etc.) are used in models.

Composite estimatesFish species richness 1998 (pre-drought)

Composite estimatesFish species richness 2001 (drought)

Composite estimatesFish species richness 2004 (post- drought)

< 10

>10 - 15

>15 - 20

>20 - 25

>25

Number of species

Integrated Aquatics AssessmentModeling Fish Occupancy

21002001

GAP TerrestrialVertebrate

Models

VegetationDynamics

Urban GrowthOptimal

ConservationStrategies

HabitatAvailability

through Time

Suitable habitat

Cerulean WarblerDendroica cerulea

Integrated Terrestrial AssessmentHabitat models for priority species

Questions?

• What kinds of water quality parameters canbe predicted under future climate scenarioswith any certainty?

• Which of these are the most relevant forecosystem and human health?

SNTEMP

• Developed by USFWSand USGS to predicthow changes in flowregime affect watertemperatures

• Uses output parametersfrom PRMS and physicalchannel characteristics

-20%

-16%

-12%

-8%

-4%

0%

0.5 1.0 2.0 3.0 4.0

Daily water withdrawal (MGD)

Ch

an

ge

ino

cc

up

an

cy

rate

(%)

Moxostoma grammarion

Percina nigrofasciata

Gambusia spp.

Lepomis auritus

Composite species-specific estimates

Climate Adaptation StrategiesFinal Products

• Spatially explicit decision support toolto allow management agencies toprioritize conservation actions basedon a range of predicted future habitatconditions, including:– Portfolio of best conservation actions

– Locations of sites with greatest marginalgain

– Incorporates land-use projections,climate change projections, andvegetation succession

USGS 02330450 CHATTAHOOCHEERIVER AT HELEN,GA

USGS 02334885 SUWANEECREEK AT SUWANEE, GA

USGS 02337170 CHATTAHOOCHEERIVER NEAR FAIRBURN, GA

USGS 02346500 POTATO CREEKNEAR THOMASTON, GA

USGS 02357000 SPRING CREEKNEAR IRON CITY, GA

USGS 02358789 CHIPOLARIVER AT MARIANNA , FL

USGS 02338660 NEW RIVERAT GA 100 NEAR CORINTH, GA

USGS 02355350 ICHAWAYNOCHAWAYCREEK BELOW NEWTON, GA

USGS 02330450 CHATTAHOOCHEERIVER AT HELEN,GA

USGS 02334885 SUWANEECREEK AT SUWANEE, GA

USGS 02337170 CHATTAHOOCHEERIVER NEAR FAIRBURN, GA

USGS 02338660 NEW RIVERAT GA 100 NEAR CORINTH, GA

USGS 02338660 NEW RIVERAT GA 100 NEAR CORINTH, GA

USGS 02346500 POTATO CREEKNEAR THOMASTON, GA

USGS 02357000 SPRING CREEKNEAR IRON CITY, GA

USGS 02358789 CHIPOLARIVER AT MARIANNA , FL

USGS 02355350 ICHAWAYNOCHAWAYCREEK BELOW NEWTON, GA

Integrated Coastal AssessmentCoastal Assessment

Coastal processes such as sea level rise, subsidence, and erosion will bemodeled to support coastal resource management

• Develop Bayesianstatistical frameworkfor predicting coastalerosion and inundation

• Assess affects of sealevel rise on coastalecosystems andwildlife

• Direct observations

• Develop visualizationtools for resourcemanagers

Climate Change&

Sea LevelRise

GroundwaterImpact

Wetland Loss

Coastal Erosion

InundationSafety

Habitat Loss

Physical& BiologicalProcesses

PotentialImpacts Management

Decisions

DrivingForces

InitialConditions

Integrated Coastal AssessmentBayesian Sea Level Rise Model

Geomorphology

Geo 1Geo 2Geo 3Geo 4Geo 5

10.710.718.612.947.0

3.75 ± 1.4

Shoreline Change (m/yr)

-10 to -5-5 to -2-2 to -1-1 to 11 to 5

14.215.720.335.714.1

-1.49 ± 3.2

Coastal Slope (%)

0 to 0.020.02 to 0.040.04 to 0.060.06 to 0.080.08 to 0.12

25.652.815.75.350.56

0.0306 ± 0.018

Tidal Range (m)

0 to 0.20.2 to 0.40.4 to 0.60.6 to 0.80.8 to 2

5.1040.936.511.65.91

0.474 ± 0.29

Mean Wave Height (m)

0 to 0.250.25 to 0.50.5 to 0.750.75 to 11 to 1.5

0 +25.345.128.41.24

0.641 ± 0.21

Relative Sea-Level Rise Rate (mm/yr)

0 to 33 to 66 to 99 to 12

42.818.014.624.6

5.13 ± 3.8

Dune Height (m)

0 to 11 to 2.52.5 to 55 to 10

17.537.928.616.0

3.02 ± 2.4

Social,Ecological,

andEconomicResponses

DrivingForces

GeologicConstraints

ErosionResponse

Topography

Developed 606 terrestrial vertebrate speciesmodels for the Southeastern U.S.

Relationships

ProductsMaps and summaries potential habitat

loss by species under a variety ofSLR projections.

ShorelineErosion

Inundation

GapTerrestrialVertebrate

Distributions

PotentialHabitat LossDue to SeaLevel Rise

Integrated Coastal AssessmentModeling Habitat Loss

Integrated Coastal AssessmentSea Level Rise Viewer

• Developing GoogleTM

Thematic Mapper based mapview that depicts inundationas sea level rises

• User friendly environment forresource managers andpublic to visualize impacts ofsea-level rise

• Interactive map displayselevations of 1, 3, and 6 feetabove Mean Higher HighWater datum

Integrated Terrestrial AssessmentLinking landscape, climate, and urbanization models

A decision making process that accounts for theuncertainty associated with predictingenvironmental dynamics and populationresponses, and the uncertainty associated withconservation policies and whether they will beeffective.

UrbanGrowthModels

GlobalClimateModels

ExistingLandscapeConditions

Succession &Disturbance

Models

Range of FutureLandscapeConditions

Avian OccupancySpecies Distribution

• Basic objective: Test hypotheses aboutavian range dynamics as function ofclimate change and other relevantfactors.

• Probabilities of local extinction andcolonization predicted as function of:

o Climate change

o Land-use change

o Location within overall speciesrange

o Neighbor effects (occupancy ofnearby locations)

• Ranges are likely to shift or contractand can be modeled by varying rates ofextinction/colonization

Integrated Terrestrial AssessmentModeling North American land bird range dynamics

0

0.2

0.4

0.6

0.8

1

1.2

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1Loggerhead Shrike(Lanius ludovicianus)

BBS data for 1996-2006 % of occupied neighbors site

colonization

extinction

Integrated Terrestrial AssessmentModeling occupancy dynamics

Pro

babili

tyofocc

urr

ence

Determine optimal conservationStrategies through:

• Implementation of StrategicHabitat Conservation usingAdaptive Management

• Incorporation of potential effectsof climate change on fish andwildlife population

• Development of strategy at anecoregional scale.

Climate Adaptation StrategiesOptimal Conservation Strategies

SiteUtility

Species 1Utility

Species 2Site

Utility

1 0.5 0.3 0.8

2 0.2 0.6 0.8

3 0.2 0.8 1.0

4 1.0 0.3 1.3

Compare among sites

Incorporate species value

Weighted

SiteUtility

Species 1

UtilitySpecies 2

(2x)

SiteUtilit

y

1 0.5 0.6 1.1

2 0.2 1.2 1.4

3 0.2 1.6 1.8

4 1.0 0.6 1.6

Site Utility

SiteNo

Management Management CostMarginal

Gain

1 1.1 1.8 20 0.035

2 1.4 1.6 20 0.01

3 1.8 1.9 5 0.02

4 1.6 1.8 5 0.04

Climate Adaptation StrategiesSimple model example

Cost

ManagementNoManagementgainMarginal

Compare alternatives

Questions?