ModMED
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Vegetation comprises many interacting individuals of many plant species. The competitive balance between species, and hence the successional development of vegetation, is largely determined by patterns of grazing and fire frequency. The maquis and garrigue vegetation has evolved over thousands of years in an environment of heavy grazing and frequent cutting and burning but agricultural land use in the Mediterranean has changed considerably in the last 20 - 30 years. Records show that grazing of semi-natural Mediterranean vegetation by sheep and goats has virtually ceased in several European countries where marginal land has been abandoned. This has lead to the rapid succession to woodland and accumulation of biomass. This in turn then affects the frequency and intensity of fires. Abandonment of traditional land management will result in dramatic changes to the landscape.
Vegetation plays a vital role in the protection of soil structure through its effects on hydrology and therefore in preventing desertification. ModMED will provide a tool to predict changes in the structure and function of vegetation in response to changes in fire and grazing regimes.
The Approach
The primary objective of the ModMED project is to predict the development of vegetation patterns in the landscape in response to changes in land use. It is an underlying assumption that successful prediction of changes in the landscape will come from an understanding of the processes of succession and vegetation change in response to disturbance. Similarly, prediction of community development will come from an understanding of the behaviour of individual plants. Research is therefore being conducted on factors relevant to vegetation dynamics at a wide range of spatial and temporal scales. Data and information on ecological processes are being collected from the literature and through field survey and experiments in Italy, Greece and Portugal.
At the community level, research is concerned with post-fire succession and the influence of grazing on vegetation. Regular monitoring of permanent plots provides estimates of rates of change in vegetation of different ages. Measures of fuel quantity and quality permit the prediction of fire behaviour, while the behaviour of grazing animals is related to the distribution of fodder. Litter production and its role in soil development provides a link between vegetation and hydrology. Studies of seedling demography following fire complement manipulative experiments on factors affecting seedling establishment.
At the individual level, measurements of the water balance and photosynthesis of several species growing in their natural environment show the physiological tolerances and responses of individual plants to their immediate microenvironment. This information relates to the phenology and growth of plants and their response to damage by grazing animals.
The Landscape-level Model comprises a raster representation of the landscape using topographic and soil data from a GIS. Processes modelled at this level include long-range seed dispersal, the distribution of grazing animals and the spread of fire (Table 1). The user controls fire initiation and stocking rates during the simulation and can monitor model predictions through maps and tabular output of data.
Each 'cell' or spatial unit within the Landscape model contains a community-level model of vegetation (Figure 1). This could be a simple Markov model of transitions in the state of the vegetation. Alternatively, more complex models of vegetation dynamics may be based on qualitative rules, compartment flows or population dynamics. The most complex model being developed by ModMED includes a spatially-explicit representation of individual plants. This, the Individual-based Community-level Model, includes the processes of soil development and hydrology, fire intensity and seedling establishment. Light interception by vegetation and offtake by grazing animals are also calculated. The individual plants within the community respond to their immediate environment of light intensity and soil moisture potential with a physiologically-based model, and respond to the effects of grazing and burning through the allocation to root and shoot growth and the development of a canopy shape. The behaviour of each individual depends on the ecological attributes of the species.
Each spatial unit in the landscape level holds a community-level module which is represented as existing in one of a number of states (a or b). The community-level transitions between states may be modelled, for example, as a simple transition-matrix model, or as a complex spatially-explicit individual-based model. Each individual plant is modelled at the physiological level.
Model outputs at the landscape level can be in the form of proportions of the landscape that are occupied by different vegetation types, or as maps in the form of a GIS. At the community and individual levels the model produces graphs of changing micro-environment and physiological status of individual plants as the vegetation develops in a range of burning and grazing management regimes.
These types of management will have important consequences for soil and water conservation. The model will predict water usage of vegetation given different weather conditions. The accumulation of litter and soil organic matter also controls the water-holding properties of the soil. A hydrological module is being developed as part of the ERMES Project which will provide a link between vegetation dynamics and other related research on hydrology, climate change and desertification.
Validation is an important part of any modelling exercise and much of the data collection is for testing the model predictions at the community and landscape levels. The process of constructing, parameterising and testing a model is fundamental to the scientific method. The ModMED model will provide a valuable tool for future research as more of the ecological processes are investigated and parameterised.
The model also has valuable educational potential and a simplified version has been produced which is linked to a hypertext display for use in schools, and other educational establishments.
Donatelli, M. 1995. CSYMBA (Cropping Systems Model Building Assistant) Program Documentation and User Manual. Version 1.0 Beta. Istituto Sperimentale Agronomico - Sezione de Modena. Italian Ministry of Agriculture, Food and Forestry Resources.
McCown, R. L., Hammer, G. L., Hargreaves, J. N. G., Holzworth, D. P. & Freebairn, D. M. 1996. APSIM: a novel software system for model development, model testing and simulation in agricultural systems research. Agricultural Systems 50: 255 - 271.
Laval, P. 1995. Hierarchical object-oriented design of a concurrent, individual-based model of a pelagic tunicate bloom. Ecological Modelling 82: 265-276.
Muetzelfeldt, R. I., Taylor, J., Wiggins, G. & Sharp, L. 1996. Modular approaches to agroforestry modelling. In Agroforestry Modelling and Research Coordination: Annual Report on ODA FRP R5652. Chapter 11. Institute of Terrestrial Ecology.