The Alaska Gap Analysis Project

Update 2010

Tracey Gotthardt

Alaska Natural Heritage Program

University of Alaska Anchorage

• Keep common species common by

identifying “conservation gaps”

• Provide information about conservation

gaps and biodiversity to inform

resource management decisions

Primary goals:

National Gap Analysis Program (GAP)

• Identify conservation gaps by conducting a “gap

analysis”

• Single species or multiple species

Objective 2 Objective 1 Objective 3

Objective 4

Landcover Mapping Species Distribution Modeling Managed Areas

Protection is currently <6%

of its western range

Protected and

preserved land

Sage Grouse

Gap analysis for Sage Grouse

in Western U.S. Habitat types

Sage grouse

distribution

Protected and

preserved areas

Current status of state GAP Projects

Tracey Gotthardt

Tamara Fields

Kelly Walton

Sanjay Pyare

Julie Nielson

Falk Huettmann

Andy Baltensberger

Grant Humphries

Michael Lindgren

The Alaska Gap Analysis Project Update 2010 “Keeping common species common”

Map completed

October 2009

Map re-evaluation underway

Landcover Mapping Species Distribution Modeling Managed Areas

Completed

October 2006

Underway

2008 - 2011

Objective 2 Objective 1 Objective 3

Objective 4: GAP Analysis 2012

http://landfire.cr.usgs.gov/viewer

30 m resolution

Landsat imagery

Landcover Mapping

Fire Regime Data

•FRCC

•Fire Regime Groups

•Simulated Historical Fire Return

Interval

•Fire Severity Type

•Succession Classes

Vegetation Data

•Ecological Systems

•Biophysical Settings

•Vegetation Dynamics Models

•Environmental Site Potential

•Existing Vegetation Height

•Existing Vegetation Cover

•Field Reference Database

LANDFIRE National Products

FARSITE Data

•13 Fire Behavior Fuel Models

•40 Fire Behavior Fuel Models

•Forest Canopy Bulk Density

•Forest Canopy Base Height

•Forest Vegetation Height

•Forest Canopy Cover

•Elevation

•Aspect

•Slope

Landcover Mapping

We intend to map the RANGE and DISTRIBUTION of select

vertebrate species in Alaska.

Species Distribution Modeling

Solitary Sandpiper Tringa solitaria Global rank: G5 State rank: S2B

Predicted habitat: 25,116,800ha, 16.8% of state

AKGAP Species list

Terrestrial Vertebrates = 432

Birds – 290 (includes 25 subspecies)

Mammals – 137 (includes 61 subspecies)

Amphibians - 6

Coarse scale RANGE

maps for all vertebrate

species are currently

available through

NatureServe http://www.natureserve.org/getData

/animalData.jsp

Range Mapping

Arctic fox

Arctic Fox (Vulpes lagopus)

Range Mapping

Alaska Major Hydrologic Units (HUC) - 8 digit

Range Mapping

Arctic Fox (Vulpes lagopus)

Range Mapping

• Draft HUC range maps

are complete for all

species

•Overlay HUC maps with

occurrence data and

attribute each HUC with

date of latest

occurrence

•10 digit HUCs have

recently become

available – revising HUC

ranges to this more

refined scale

Range Mapping

Species Richness Index

Species Distribution Modeling

Inductive models Deductive models

Temperature

Precipitation

Elevation

Slope

Deductive models

Utilize expert

opinion and

literature review

to produce a

habitat associations

database for

occupied HUCs

Habitat associations

are cross-walked

to landcover classes

Species Distribution Modeling

Species Distribution Modeling

Species Distribution Modeling

Distribution is predicted based on environmental

parameters (e.g., elevation, climatic gradients) at

known points of occurrence.

DEM

Aspect

Euclidean Distance

Precipitation

Temperature

Inductive models

Species Distribution Modeling

Total # Occurrences = 1,527,983

Birds = 1,423,156

Mammals = 101,756

Amphibians = 3,071

0

200000

400000

600000

800000

1000000

1200000

1400000

Blank < 1970 1970-1990 1990-2010

Nu

mb

er

of

Re

cord

s

Year

Occurrence Records Temporal Assessment

Species Distribution Modeling

Deductive models Inductive models

Species Distribution Modeling

Project Timeline

YEAR 1 - 2009

• Finalize preliminary range maps

• Occurrence data gathering

YEAR 2 - 2010

• Continue occurrence data gathering and synthesis

• Begin inductive modeling

YEAR 3 - 2011

• Finalize inductive models

• Build deductive models

• Build hybrid models

• Expert review

YEAR 4 - 2012

• Conduct GAP Analysis

• Automate all data products

• Managed Areas Database (TNC)

• Wildlife Occurrence Database

• Habitat Associations Database

• Species Range Maps, modified

by occurrence data and expert

review

• Species Distribution Atlas

containing predicted

distributions derived from

deductive an inductive models

• Species Richness Maps for

combined taxa

AKGAP Data Products

AKGAP Data Products

Ancillary Data

Surficial Geology

Soils

Lotic Waters (distance to flowing water)

Lentic Waters

Aquatic System

Salinity

December Sea Ice Extent 2003-2007

June Sea Ice Extent 2003-2007

Glacial Extent

Permafrost

Water Table

Elevation

Slope

Aspect

Terrain Roughness

Coastline

Vegetation (Landfire, NLCD)

Wetland Vegetation (distance to)

Alpine (distance to)

Infrastructure (low, medium, high)

Infrastructure (distance to)

Insect History (year of damage)

Fire History

Fire Location (distance to fire)

Precipitation

Temperature

First Day of Thaw

First Day of Freeze

Length of Growing Season

Insolation

Wind (exposure 1-5)

Edge Density

Patch Size

Connectivity

AKGAP Data - Uses in Conservation Planning

• Species predictive distribution models will help guide

inventory, monitoring, and research efforts

• Identify areas that support the persistence of key species

and to prioritize areas for conservation (e.g: migration,

dispersal corridors, biodiversity hotspots)

• Creates a baseline of information that can be used in future

climate change and human impact modeling scenarios

AKGAP Partners/Data Providers

ABO 1997 ABR 2005 ADF&G 2005 ADF&G 2009 ADFG 1993 ADFG 1995 ADFG 2008 Adler and Savage 1999 Adler et al. 1973 Ajmi 2009a Ajmi 2009b Ajmi 2009c Alaska Bat Monintoring Project 2009 Alaska

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Browne 1997 Andres and Browne 1998 Andres et al. 1999 Andres et al. 1999 Anonymous 1973 Anonymous 1974a Anonymous 1974b Anonymous 1983b Anonymous 1984 Anonymous 1985 Anonymous 1988 Anonymous

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1973 Bailey 1974 Bailey 1976 Bailey 1977 Bailey and Faust 1981 Bailey and Faust 1984 Baird and Moe 1978 Baker and Findley 1954 Ball 1988 Baltensperger 2009 Baluss 2005 Barrett et al. 2005 Bee 1958 Bee and Hall

1956 Belson 1961 Bennett 1992 Bennett 1993 Bennett 1994 Bennett 1995a Bennett 1995b Bennett 1996 Benoit 2009a Benoit 2009b Benson 2000 Bent 1927 Bent 1929 Beringer and Nishimoto 1988 Beringia Birders

Database 2008 Bertram 2005 Bevins 1987 Beymer 1988 Blatt 1995 BLM 2000 BLM 2002 Bodkin et al. 2008 Boland 2006 Bollinger and Eldridge 2008 Bollinger et al. 2007 Booms 2009 Booz 2005 Boyd 1997 Brackney et al.

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and Climo 1988 Byrd and Day 1986 Byrd and Mendenhall 1986 Byrd and Norvell Byrd and Williams 1999 Byrd and Williams 2004 Byrd and Williams 2005 Byrd et al. 1974 Byrd et al. 1985 Byrd et al. 2001 Cady 2005

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Gibson 1981 Gibson 1983 Gibson and Kessel 1983 Gibson and Kessel 1989 Gilbert 1976 Gill 1988 Gill and Amaral 1984 Gill and Handel 1981 Gill and Handel 1987 Gill and Handel 1990 Gill and Sarvis 1999 Gill and Tibbitts

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1999 Zador and Piatt 2002 Zeilemaker 1987 Zweifelhofer 2002 Zwiefelhofer and Forsell 1989

AKGAP Data Providers

www.akgap.info

The Alaska Gap Analysis Project “Keeping common species common”