dynamics of the mediterranean vegetation mosaic: modeling across spatial scales from simple to...

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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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.