Millington Research Overview | EED Seminar Sept 2013

http://www.landscapemodelling.net
Landscape Ecology
Modelling & Simulation
Dr. James Millington
Lecturer in Physical and Quantitative Geography

Research Background

Research Interests
Landscape Ecology Modelling & Simulation
Succession-
Disturbance
Resource
Management
Agent-Based
Epistemology

Landscape Change
 Land Use/Cover Change
Millington et al. (2007)

Landscape Change
 Agricultural decision-making Agent-Based
Model (ABM)

Landscape Change
 Agricultural decision-making ABM
 Landscape succession-disturbance (LFSM)

Succession-Disturbance

Succession-Disturbance
Movie

Ongoing Modelling
 Model assessment
 Sensitivity and uncertainty analyses
 Pattern-oriented modelling
 Updating model to
better represent
climate and soil
moisture

Ongoing Modelling
Carrion et al. 2010

Resource Management
 Wildlife and timber management
Timber Deer
© L.S. Johnson
Birds

Selection Timber Harvest
Shade-tolerant species
regenerate in understory
Intends to mimic gap-
phase dynamics

Variation in Gap Regeneration

Simulation Model
USFS Forest
Vegetation Simulator
MSU Regeneration Model
7.0m
TreeHeight
Deer
Herbivory
Landscape Forest Structure
Forest Valuation
Timber
Harvest
(light & seed
availability)
Site Quality
(soil resources, competition)

Deer Distribution

Winter Deer Habitat
Juxtaposition of
northern
hardwood and
lowland conifer
stands
Provides winter
food and
thermal cover in
close proximity
Lowland
Conifer
Aspen
Northern
Hardwood
Other
0 1km

Deer Distribution Regression
Deer Density = f(DLC, DBH)
Bayesian Model Averaging to select this ‘best’ model

Deer Distribution Example
Deer Density – Original
Low
High
deer/km2
Lowland
Conifer
0 1km

Deer Distribution Example
Deer Density – Conifer Removal
Lowland
Conifer
0 1km
Low
High
deer/km2

Gap Regeneration Scenarios
100% Regeneration
100 years
10-year timestep
Year

Gap Regeneration Scenarios
0% Regeneration
100 years
10-year timestep
Year

Combined effects?
What are the combined effects of
variable regeneration and timber
management on songbirds and
timber production?

Bird Occupancy Probability
 Occupancy Models (after MacKenzie et al.)
 logit(p) = b0 + b1x1 + … bixi
0.0
0.2
0.4
0.8
1.0
0.6
OccupancyProbability
Least Flycatcher
Black Throated
Green Warbler
0.0 12.5 25.0 37.5 50.0
Canopy Openness (%)

Bird Occupancy Probability
BTNW EAWP
LEFL RBGR
Canopy Openness (-ve)
SumDiam15m (+ve)
Canopy Height (+ve)
Canopy Height (+ve)
Canopy Openness (+ve)
Basal Area (+ve)
SumDiam20m (+ve)

Birds vs. Timber vs. Regeneration

Birds vs. Timber vs. Regeneration
Black-Throated Green Warbler

Integrated Simulation
 Integrated forest management
 Integrated simulation model: regeneration,
timber and deer

Ongoing Modelling
 Spatial-temporal co-ordination of timber and
wildlife management
 Impact of variable snow at regional scale

Transferable Methods!
 Statistical models
 Logistic regression modelling
 Categorical or probabilistic dependent variable
 Land cover, species abundance
 Risk models, Forecast models
 Multi-model inference
 Evaluating evidence for different combinations of
variables

Transferable Methods!
 Simulation approaches
 For dispersal, diffusion, random walk processes
 Cellular Automata & GIS modelling
 Grid models with specified rules of change
 Risk mapping and change
 Individual- or Agent-based modelling
 For representing discrete entities
 Human activity, animal distribution, plant migration

Millington Research Overview | EED Seminar Sept 2013

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