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Dynamics of the Mediterranean vegetation mosaic: modeling across spatial scales from simple to complex
Avi Bar MassadaAvi Bar Massada11, Gili Koniak, Gili Koniak22, Yohay Carmel, Yohay Carmel11, Imanuel Noy Meir, Imanuel Noy Meir22
11Technion – Israel Institute of TechnologyTechnion – Israel Institute of Technology22The Faculty of Agriculture, The Hebrew University of Jerusalem The Faculty of Agriculture, The Hebrew University of Jerusalem
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Background
• Thousands of years of human agro-pastoral activities converted the
Mediterranean landscapes into spatially heterogeneous “Mosaics”
• Land use changes in the recent decades transformed these landscapes into
closed scrublands and woodlands, with lower biodiversity, lower scenic
diversity, and increased fire risk.
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How can we preserve mosaic landscapes?
• Mainly through grazing, clearing, and burning, the traditional disturbances that
created and maintained these landscapes.
• How to manage for heterogeneity? Woody vegetation recovery is quick, thus a
complex set of management practices is needed.
• Long-term interactions between disturbance and vegetation dynamics are not
fully understood, especially in complex systems as the Mediterranean region.
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The modeling approach
In order to understand and predict the spatiotemporal dynamics of
Mediterranean vegetation under multiple disturbances, we are
developing mathematical models across three spatial scales: patch, site
and landscape. The models are constructed by successive
approximations, from simple to complex, registering the changes in
model behavior and realism at each stage
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Hierarchical levels
Landscape: a contiguous set of sites (>>100m2) that may differ in environment and disturbance history.
Site: a group of neighboring patches (100m2) of uniform environment and disturbance history.
Patch (cell): a unit area of 1m2, the size of an adult dwarf shrub.
The models are being developed on three hierarchically nested spatial scales,
incorporated into model structure with rising complexity:
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Underlying mechanism: states and transitions theory (Westoby, Walker, and Noy-Meir 1989)
Spontaneous transitions
via colonization or
expansion
Disturbance related
transitions (fire, clearing),
or natural death
Grazing
effects
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The basic model – Patch scale
A state-and transition process between vegetation states at the patch level,
described by a simple Markov model with constant transition probabilities.
Nstates
AxtxxBtB VpV ,1,
Frequency of patches in vegetation state B at time t+1
Transition probability between state x and state B
Frequency of patches in state x at time t
x=A,B,…,N
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Intermediate model: patch + site scales
This stage increases model complexity by:
1. Adding states.
2. Introducing non-constant transitions.
3. Adding a hierarchical level.
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1. Increasing model complexity: states
The simple Markov model had one state variable – the vegetation
state. Increasing complexity starts by adding variables. Now, each
patch is characterized by 5 state variables:
1. The dominant vegetation state.
2. Height of the dominant.
3. Age of the dominant.
4. Identity of the colonizer vegetation state.
5. Age of the colonizer.
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2. Increasing model complexity: transitions
In reality, transition probabilities aren’t constant, but depend on:
• Residence time of a patch in a specific vegetation state, and of a colonizer growing below it.
• Vegetation states of neighboring patches
• Fire, clearing, and grazing events.
),,,,,(0
GCFVpfp neighborsAABAB The transition probabilities are turned into continuous The transition probabilities are turned into continuous transition functionstransition functions
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3. Adding the site hierarchical level
The probability of colonization from seeds depends on the percentage cover of all dominants in the site, plus a constant contribution from patches outside the site.
Pcolonization = Psite + Plong
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3. Adding the site hierarchical level
The probability of expansion has two forms:
1. Non-spatial explicit, depending on percentage cover
2. Spatial explicit: only one of its 8 nearest neighbors can expand into a patch.
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•Different sites may have different disturbance histories.
•The probability of colonization from seeds has now three components:
Pcolonization = Pshort + Pmedium + Plong
Top model: patch + site + landscape scales
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Validation at the site scale
Model performance tested for a 10 years period – no disturbance.
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Herbaceous Dwarf shrubs Mediumshrubs
Tall shrubs Trees
Vegetation type
% C
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Field data
Simulation
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Site scale model – undisturbed
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Site scale model – intensive goat grazing
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Goat grazing excluded after 30 years
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Site scale model – intermediate goat and cattle grazing
Possible equilibrium?
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Landscape level initial simulations:Disturbance effects on landscape structure
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Future research
• Large scale simulations on actual landscapes.
• Landscape structure studies: effects of disturbances, initial structure.
• Management practices: which are better for mosaic conservation.
• Addition of vegetation types: model generalization to other Mediterranean landscapes.
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Thank you!
Many thanks to:
Prof. Avi Perevolotsky, Dr. Liat Hadar, and Sagie Sagiv of the Ramat Hanadiv Nature Park staff.
The research is generously supported by the ISF.