nr 422- habitat suitability models jim graham spring 2009
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NR 422- Habitat Suitability Models
Jim Graham
Spring 2009
Habitat Suitability• Predict the potential distribution of a
species based on finding suitable habitat• Also known as:
– Niche modeling– Predicting distributions
Terminology• Realized Niche – current distribution
– Established species– Late succession (minimal disturbance)
• Potential Niche – future distribution?– Invasive species– Theatened and endangered species
Approaches• Mechanistic/Experimental
– Based on understanding of a species requirements and experiments
– Can miss the complexity of environmental conditions and genetic plasticity
• Statistical– Based on the existing distribution of a
species– Can miss the “realized niche”
• Observational / Anecdotal– Hard to validate
Basic Idea• Basic idea is to find a correlation
between a species and a variable we can measure– Temperature– Precipitation– Surface type: Water, Rock, Soil Type– Distance to human activity– Other species!
Process
Occurrence Data
Parameters and
EquationsResults
Statistical Model
Distribution Map
Environmental Layers
Processing
Model Validation
Experiments
And Observations
Correlations• Correlations between environmental variables
and species requirements
Responce to Height at Elevation
y = -0.0035x + 23.133
R2 = 0.92150
2
4
6
8
10
12
0 2000 4000 6000 8000
Elevation (meters)
Hei
gh
t (m
eter
s)
Tamarix and Precipitation
Proportion of Occurances in Precipitation Categories
0
0.2
0.4
0.6
0.8
1
1.2
7 28 49 71 92 113 134 156 177 198 219 240 262 283
Percipitation (cm per year)
Pro
po
tio
n o
f O
cc
ura
nc
es
GODM Tamarix
Continental US
DiGIR Tamarix
Tamarix and Temperature
Proportion of Occurances in Temperature Categories
0
0.2
0.4
0.6
0.8
1
1.2
0.2 2.2 4.1 6.0 7.9 9.8 11.8 13.7 15.6 17.5 19.4 21.4 23.3
Temperature (degrees C)
Pro
po
rtio
n o
f O
cc
ura
nc
es
GODM Tamarix
Continental US
DiGIR Tamarix
Box Model
Temperature (degrees C)
Pre
cip
itat
ion
(cm
/yea
r) 50
30
5.6
Tamarix Potential Habitat
Legend
Tamarix Occurrence
Tamarix Ecoregions
US States
Legend
Tamarix Occurrence
Tamarix Ecoregions
US States
Vegetation Layers• Minimum temperatures at certain times of
the year• Amount of sun• Precipitation• Soil type• Elevation• Slope• Aspect
www.geography.hunter.cuny.edu
Herbivore Layers• Vegetation layers• Proximity to cover• Distance to water
www.ministryofpropaganda.co.uk media-2.web.britannica.com
Carnivore Layers• Herbivore layers• Proximity to cover• Distance to water
www.juneauempire.com
Proxy Layers• Remotely sensed:
– MODIS– LandSat– Aerial
• Human disturbance• DEMs: Elevation, slope, aspect
White Tailed Deer• Habitat Suitability Index (HSI) =
Forage * Cover• Log(Deer Density) = a + b (HSI)
Roseberry, J. L., Woolf, A. 1998. Habitat-Population Density Relationships for White-Tailed Deer in Illinois, Wildlife Society Bulletin, Vol. 26, No. 2 (Summer, 1998), pp. 252-258
Black Bears in Rocky
Baldwin, R.A., L. C. Bender. 2007. Den-Site Characteristics of Black Bears in Rocky Mountain National Park, Colorado, JOURNAL OF WILDLIFE MANAGEMENT 72(8):1717–1724
Habitat Suitability Index• HIS =
– 0 for least suitable– 1 for most suitable
• HIS = V1 * V2 * V3– Where each VX is a raster scaled from 0 to
1– 0 = unsuitable factor– 1 = suitable factor– In between values for intermediate suitability
Categories• Assign each category a value from 0 to 1
based on how suitable it is.
Forest Shrub Grassland Alpine0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Ranges• Create mask rasters for area below and
above (0 for unsuitable, 1 for suitable)1.0
0.0
Mask (0.0) Mask (0.0)1.0
Gradients
1.0
0.0
Mask 1.0Gradient
Envelopes1.0
0.0
Mask Mask1.0Gradient Gradient
Statistical Approaches• Linear Regression (continuous variables)• Logistic Regression (presence data)• Genetic Algorithm for Rule-set Production
: GARP• Classification and Regression Trees:
CART• MaxEnt (presence)
Integrating Climate Change
Japanese Honeysuckle
Where to go from here• Spatial modeling
– Robin’s class• OpenModeler
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