dynamics of the mediterranean vegetation mosaic: modeling across spatial scales from simple to...
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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
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.
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.
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
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:
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
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
Intermediate model: patch + site scales
This stage increases model complexity by:
1. Adding states.
2. Introducing non-constant transitions.
3. Adding a hierarchical level.
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.
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
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
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.
•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
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
ov
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Field data
Simulation
Site scale model – undisturbed
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?
Landscape level initial simulations:Disturbance effects on landscape structure
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.
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.