remote sensing tools for assessing large scale habitat quality for ungulates brad griffith usgs,...
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Remote Sensing Tools for AssessingLarge Scale Habitat Quality for
Ungulates
Brad GriffithUSGS, Alsaska Cooperative Fish and Wildlife Research UnitInstitute of Arctic Biology, University of Alaska Fairbanks
Ungulates don’t respect boundariesAnnual cycles encompass several jurisdictionsMonitoring of annual ranges necessary to understand performanceRemote sensing provides tools for large scale habitat monitoring
Purposes today
• List some available tools for habitat assessment
• Give two examples of research results with monitoring applications– One migratory species– One non-migratory species
Tools• AVHRR –
– 1, 4, 8km resolution– High frequency of overpasses– Greenness, snow cover, surface temperature
• TM, MSS, SPOT– 10-100m resolution– Low frequency overpasses– Greenness, land-cover classification and change
• Passive Microwave– 25km resolution– Intermediate frequency overpasses– Snow water equivalent
Changes in lake levels between 1986 and 1998 - Old Crow Flats
Green = No change
Blue = Increased Water levels
Yellow = Decreased Water levels
Courtesy of Jim Hawking and Elizabeth Malta, Canadian Wildlife Service
Net Climate Effects+ Earlier green-up
• Increased calf survival
– Reduced forage quality in fall– Delayed age of first reproduction? (Cook et al. 2001, 2004)
– Reduced body condition entering winter? (Cook et al. 2001, 2004)
– Reduced winter survival? (Cook et al. 2001, 2004)
– Increased icing on spring ranges– Reduced access to forage?– Increased travel costs?– Increased predation risk?
= Warming induced population decline for Porcupine herd?
Substantial spatial and temporal heterogeneity in climate effects on caribou ranges and on population dynamics.
Do no expect same scenario for Western Arctic
Habitat Suitability for Dall’s Sheep (Ovis dalli) in
Wrangell - St. Elias National Park & Preserve
Miranda Terwilliger
a.k.a. What constitutes Natural and Healthy?
Objectives• Estimate population
characteristics of sheep in Wrangell-St. Elias
• Inventory survey units for habitat characteristics
• Estimate relationships between population and habitat characteristics (JR Manes)
(WRST NP/P)
0
2
4
6
8
10
12
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16
1 2 3 4e 4w 5e 5w 7e 7w 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23e 23w 24 25 26 27 28 29 30 31 32
Survey Unit
Nu
mb
er
of
fixe
d-w
ing
su
rve
ys 1
94
9-2
00
2
Habitat Characteristics - Inventory
• “Escape” Terrain– >60% slope with 150m buffer
>40% (McKinney et al. 2004)
• Terrain Ruggedness– Surface to planar area ratio
(Hobson 1972)
• Aspect– % south & west
• Relative Greenness– NDVI (Tucker et al. 1984)– Relative amount of plant biomass
Summary• 56% of density was explained by:56% of density was explained by:
– (+) relative greenness (forage quantity)(+) relative greenness (forage quantity)– (+) terrain ruggedness(+) terrain ruggedness
• 64% of harvest was explained by:64% of harvest was explained by:– (+) proportion of south facing slopes(+) proportion of south facing slopes– (+) mean adult density(+) mean adult density
• 42% of horn length was explained by:42% of horn length was explained by:– (+) trends in adult density (+) trends in adult density – (+) perimeter to area ratio of escape terrain(+) perimeter to area ratio of escape terrain
• Test predictive power in other areasTest predictive power in other areas
• Consider additional sources of Consider additional sources of variationvariation
• Snow coverSnow cover• Wind scouringWind scouring• Climate Climate • PredationPredation
Future DirectionsFuture Directions
What have we learned?
• Temporal resolution more important than spatial resolution for seasonally breeding ungulates (except for those damned sheep)
• Capture the seasonal dynamics– Static views may not be relevant to life history
stages of interest
• Forget forested areas– Nothing eats the tops of trees
Monitoring Considerations
• Large scale problem for ungulates– Don’t look at your feet
• Document the background trends– Climate, physical environment, habitats
• Only way to understand system performance
– Don’t assume “global” trends apply everywhere
• Match the scale of questions and data– Smaller grain increases variance
• Match the resolution of data and animal performance• Don’t over-analyze
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