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
Polar Bear
Tamarisk
Red
Squirrel
Arctic Tern
Blue
Whale
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
Experiments
And
Observations
Statistical Model
Environmental
Layers
Parameters and
Results
Processing
Distribution Map
Model Validation
Equations
Correlations
• Correlations between environmental variables
and species requirements
Responce to Height at Elevation
Height (meters)
12
10
8
6
4
y = -0.0035x + 23.133
2
R2 = 0.9215
0
0
2000
4000
Elevation (meters)
6000
8000
Tamarix – Invasive Species
Tamarix and Precipitation
Proportion of Occurances in Precipitation Categories
1.2
Propotion of Occurances
1
0.8
GODM Tamarix
0.6
Continental US
DiGIR Tamarix
0.4
0.2
0
7
28
49
71
92
113
134
156
177
198
Percipitation (cm per year)
219
240
262
283
Tamarix and Temperature
Proportion of Occurances in Temperature Categories
1.2
Proportion of Occurances
1
0.8
GODM Tamarix
Continental US
0.6
DiGIR Tamarix
0.4
0.2
0
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)
Precipitation (cm/year)
Box Model
50
30
5.6
Temperature (degrees C)
Tamarix Potential Habitat
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.
1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
Forest
Shrub
Grassland
Alpine
Ranges
• Create mask rasters for area below and
above (0 for unsuitable, 1 for suitable)
1.0
0.0
Mask (0.0)
1.0
Mask (0.0)
Gradients
1.0
0.0
Mask
Gradient
1.0
Envelopes
1.0
0.0
Mask
Gradient
1.0
Gradient
Mask
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