Formulating Hypotheses, Building Models, and Accounting for ...
Why use landscape models? Models allow us to generate and test hypotheses on systems Collect data,...
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Transcript of Why use landscape models? Models allow us to generate and test hypotheses on systems Collect data,...
Why use landscape models? Models allow us to generate and test hypotheses on systems
Collect data, construct model based on assumptions, observe behavior of the model
Identify areas of understanding
Identify range of variability
Identify sensitive parameters
Management applications Test different management scenarios
E.g., alternatives for a National Forest Plan
Landscape ecology poses particular challenges to modeling applications High degree of complexity in ecological systems that we have to account for
nonequilibrium systems
spatial heterogeneity
complex feedbacks through time
relevant processes that operate at a variety of scales
Spatial and temporal constraints on landscape studies
• Experiments on large areas are difficult
• Even more difficult to replicate experiments; or even "sample" and analyze replicates
• Many large-scale processes operate slowly, so landscape change does also
• Even with good data, systems too complex to predict behavior
Operationally, useful to think of three general types of landscape models • Landscape change models
Land cover classes, ecosystem types, or habitats
Influenced by natural or anthropogenic processes
• Landscape process models Simulate a process that depends on landscape states and changes
E.g., hydrological change, or nutrient movement through the soil
• Individual-based models
Individual-Based population models - models of how organisms move through, use, and interact with the landscape
Can be analytical or simulation models
Collections of individuals
• AdvantagesCan be highly mechanistic
Testable
• DisadvantagesComplexity
Poor generality
Landscape change models often include simulation of disturbance and a responselandscape pattern - three basic things, within climatic framework
1) an abiotic or geomorphic template
2) disturbance
3) biotic responses, e.g., succession
Landscape change models a way of simulating pattern change in pattern in a landscape
Most landscape models are different ways of conceptualizing these three general areas
Depending on needs, may need to include in a model processes operating within any of these three areas
Questions, scales, determine processes to include
Modeling approaches - Baker (1989) Distinguished between distributional landscape models and spatial landscape models
Distributional models - model the different values of a variable in a landscape. E.g., the area of a landscape in different land use classes or elements
Spatial models - Model spatial location and configuration of landscape elements or classes
All landscape change models contain basic components of1) initial configuration
2) change processes or dynamics
3) output configuration
Spatial models as defined by Baker, are what we usually think of as landscape models
Include location and configuration of landscape elements
Often use maps or a matrix representation as input and output
Raster or grid cell format most common
Other ways of classifying models E.g., further in Baker 1989
Sklar and Costanza, QMLA
Turner and Dale, same volume
From He and Mladenoff 1999
From Pastor and Johnston
What are problems confronted in developing spatial landscape models?
• Stochastic models (probabilistic) simulate changes in the state of polygons cells based on a matrix of transition probabilities
• Based on observed or inferred rates of change between possible states on a landscape - Markov transition models.
• Assume several things that typically may not be true:Transition rates are constant over time
Rates due to current state
• Must have data to define states and derive transition rates
http://www.env.duke.edu/landscape/classes/env214/le_mod1.html
http://www.env.duke.edu/landscape/classes/env214/le_mod2.html
Cellular automata models: "systems of cells interacting in a simple way but displaying complex overall behavior" (Phipps 1992)
• System of cell networks or grids
• Has specified initial configuration
• Cells interact with neighborhood (transitions)
• Each cell adopts one of m possible states
• Follows discrete time dynamic
• Transition rules for each state can be simple, deterministic or stochastic
Cartographic Models • Binary, Categorical
• Weightings, Quantitative
http://www.env.duke.edu/landscape/classes/env214/le_mod2.html
http://www.env.duke.edu/landscape/classes/env214/le_mod0.html