Biosphere Modeling

Vegetation is a major factor affecting land surface processes (Figure 6.3), and a good measure of ambient climate and change in this. Therefore, a central part of understanding climate change impact is to understand the correspondence between climate and the distribution of vegetation, both in terms of major vegetation formations, or biomes, and individual plants or species. Modeling the biosphere is not a new field of research. Initial attempts were carried out by Kostitzin (1935). Working on ideas about the interdependence between vegetation and climate he created the first mathematical model for the co-evolution of atmosphere and biota. Individual-based models describe vegetation dynamics in terms of interactions between individual plants with little emphasis on ecophysiology and climate (Farquhar, 1997). A compromise between these schools is the popular forest gap models (Tongeren and Prentice, 1986) that describe species-specific establishment, growth, death of trees, and interactions between them resulting in successional patterns. Species-based approaches create bioclimatic envelopes delimited by a combination of climate variables based on the correlation between spatial distribution of individual species and climatic parameters. The bioclimatic envelopes can then be used to model potential species responses to climate change. Genetic algorithms are used to create the envelopes because of their ability to take into account a large number of climate variables (McClean et al., 2005).

Atmospheric Disturbance Classifications
Figure 6.2. Indication of the amount of incoming and outgoing radiation, and the percentage absorbed and reflected by the various atmospheric components.

The best-known approach for predicting the equilibrium response of broad-scale potential vegetation types to climate change is the climate-vegetation classification approach (Holdridge, 1947)—using this approach Holdridge recognizes some 37 "life zones". The disadvantage of such an approach is that the climatic variables may not be the factor to which vegetation responds (Peng, 2000). Vegetation responds to a range of climatic influences, geomorphic substrates, ecological disturbances (natural and human-induced) with an incredible array of different species, growth and competition habits, and basic life forms (Figure 6.4). For example, simulations of vegetation patterns with and without fire show that large areas of C4 grasslands in Africa and South America have the climate potential to support forests (Bond et al., 2004). Functional groups work well—for example, the FORMIND model was applied to lowland forest data from Indonesia. The analysis used 22 functional groups, comprising 436 species, based on diameter growth and light demand, with an additional criterion being based on height (Kohler and Huth, 1998). Plant-functional types that group plant species by their physiognomic and morphological traits and responses to climate (e.g., tropical evergreen broad-leaf rainforest tree) are a very useful classification tool, particularly when dealing with the complexity of a tropical flora (Figure 6.4).

By including climate dependencies, biosphere models can account for climatic, immigration, and competitional influences, thus providing a forecast of ecosystem impacts under various climate scenarios (Figure 6.5). In earlier studies, climate input

Decrease " soil moisture

Rainforest Ecosystem Tropical Rainforest Impacts

Figure 6.3. Impact on the biogeochemical components of the modeled ecosystem following a change in below-ground (a) and above-ground (b) biomass.

Figure 6.3. Impact on the biogeochemical components of the modeled ecosystem following a change in below-ground (a) and above-ground (b) biomass.

Aboveground And Belowground Interaction
Figure 6.4. Schematic division to determine plant-functional types based on a series of divisions, in this case on growth form, tolerance to seasonal temperature, and physiology of the parent plant.
Factors Determining Climate Scenarios

climatic change

+disturbance nutrient cycling

Global Change

+fragmentation atmospheric C02


S nutrient disturbance ^ cycling regime

Ecosystem Impacts atmospheric hydrology composition '

s. decomposition

Dispersal Rates

Figure 6.5. The impacts of migration and dispersal that are increasingly being incorporated within dynamic vegetation models as feedbacks, in conjunction with other ecosystem impacts— such as disturbance type.

data and timing of species appearance were inferred from the pollen records to which the simulation results were compared. Such circular reasoning between cause and effects limits insights gleaned about factors controlling vegetation response, and has been easily broken by using climatic input from independent data sources. Additionally, there has been an increasing interest in parameterizing the role of dispersal (Figure 6.5), in part driven by the development of more appropriate (realistic) models and partly due to the increasing understanding of the dynamic nature of populations. These approaches are currently confined to the temperate realm, but have interesting applications to tropical areas (Paradis et al., 2002). This complexity has resulted in a number of approaches for studying biosphere responses to climate change that incorporate migration and adaptation (Kirilenko et al., 2000), dispersal factors (seed production, fecundity, dispersal vector interaction), additional environmental factors (such as climate seasonality, edaphic factors, aspect), and ecological factors (such as association, parasite/disease, inertia) (Figure 6.5). In addition to changing areal extent and composition of the vegetation, changes in vertical structure are an important part of vegetation change (Cowling, 2004).

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