As the primary producers of biomass, plants determine the physiognomy and character of large ecological units and provide the basis for all other life. This has contributed greatly to the practice of using patterns of vegetation for a coarse global division of the geo-biosphere in ecological terms. On the other hand, Walter and Breckle (1983) argue that the large naturally occurring communities of flora and fauna, or "biomes", are best delineated on the basis of the climatic conditions under which they occur, since in global terms a coarse division of geographical regions is given by the large climatic zones, from which Walter and Breckle (1983) then derived their term zono-biomes. Thus, we also obtain the large zones of vegetation in a three-dimensional climatic gradation (Ehrendorfer 1991):
• from the equator to the poles (temperature gradient);
• from the oceans to the continents (oceanity or continentality according to the degree of annual balance of temperature);
• in the altitudinal zones in high mountains.
This possibility of separating large-scale vegetation units according to the climate leads to the practical question of whether one can make predictions on plant distribution in extended areas based on simple models.
One simple technique, which has proven extraordinarily successful, is the Klimadiagramm of Walter (1973). In his autobiography Walter (1982) describes vividly how the idea developed when he was first confronted with the problem of a large-scale interpretation of vegetation in Anatolia (Turkey) in 1954. The Klimadiagramm (Box 2.1) essentially uses simple data which are readily available from all weather
1 "Der Ausdruck Klima bezeichnet in seinem allgemeinsten Sinne alle Veränderungen in der Atmosphäre, die unsere Organe merklich afficiren: die Temperatur, die Feuchtigkeit, die Verändrun-gen des barometrischen Druckes, den ruhigen Luftzustand oder die Wirkungen ungleichnamiger Winde, die Größe der electrischen Spannung, die Reinheit der Atmosphäre oder die Vermengung mit mehr oder minder schädlichen gasförmigen Exhalationen, endlich den Grad habitueller Durchsichtigkeit und Heiterkeit des Himmels; welcher nicht bloß wichtig ist für die vermehrte Wärmestrahlung des Bodens, die organische Entwicklung der Gewächse und die Reifung der Früchte, sondern auch für die Gefühle und ganze Seelenstimmung des Menschen."
stations, i.e. mean monthly temperatures and precipitation. They are plotted according to a precise scheme of scaling on the ordinate vs months on the abscissa: humid periods are indicated by areas on the graph, where the temperature curve is below the curve of precipitation; arid periods are delineated by the precipitation curve being lower than that of temperature. According to a precisely defined scheme, additional information can be built into the Klimadiagramm, so that depending on data availability each diagram may give a complete description of the climate at a given station.
Box 2.1 Klimadiagramm after Walter (1973)
• The months of the year are plotted on the abscissa.
• The mean monthly temperatures and precipitation are plotted on the ordinate, so that
- at mean monthly precipitation between 0 and 100 mm one unit of scale corresponding to 10 0C gives 20 mm precipitation or the ratio of scalation is 1 0C:2 mm precipitation;
- at mean monthly precipitation above 100 mm the precipitation scale is reduced to 1/10, and the ratio is 1 0C:20 mm precipitation.
• Humid periods are indicated by precipitation curves above temperature curves; they are marked by vertical hatching up to 100 mm and by black colour above 100 mm precipitation.
• Arid periods are indicated by precipitation curves below temperature curves, they are marked by dotting.
• According to a well-defined scheme, other details may be added to the Klimadiagramm as indicated in the examples given below.
Examples presented are for tropical stations in Africa with an arid, a perhumid and a seasonal climate: Mogamedes at the Atlantic coast of Angola (15° ÖS7 S, 12° 09' E), Djolu, Congo (ÖÖ° 38' N, 22° 377 E) and Mpika, Muchinga Mountains, Rhodesia (11° 52' S, 31° 26' E). For further details see Walter and Lieth (1967) and Walter (1973).
For a large-scale evaluation of a certain area, or even an entire continent, one requires the diagrams of many stations covering the respective area. One can integrate them in a geographic information system, e.g. in the simplest way paste them on a map to obtain a good survey of the climatic structure of the area. Areas with humid, arid or seasonal climates are readily separated. An example is shown for the predominantly tropical continent of Africa in Fig. 2.1. The humid belt along the equator is clearly separated from the more semi-arid and arid regions. The power of the approach can be seen by comparing the distribution of rainforest and savanna on the African continent (Fig. 1.3) with the more humid and more seasonal regions, respectively (Fig. 2.1).
Although we will have to draw attention to certain limitations of the Klimadiagramm technique later (Sect. 3.1), since arid and humid climates are strictly defined by precipitation and evaporation and not by precipitation and temperature as in the Klimadiagramm, we will make repeated use of the Klimadiagramm in this book.
2.2.2 Vegetation Modeling Based on Irradiance and Water Budgets
Climatic conditions like irradiance and temperature affect the water-vapour pressure deficit of the atmosphere, and thus determine evapotranspiration or the loss of water vapour of the vegetation to the atmosphere. Irradiance and water
availability in turn are modulated by other climatic factors. Thus, it is possible to make model calculations of evapotranspiration from climatic data using basic plant-physiological principles of transpiratory water loss from leaves driven by the leaf/air water-vapour pressure-difference. Furthermore, there are close links between evapotranspiration and leaf area index (LAI), which is the total leaf area related to a unit of ground surface (see Sect. 3.4.1). The LAI is characteristically related to the physiognomy of plants and vegetation. Therefore, from LAI one may then obtain ecophysiological models of vegetation as dominated respectively by broad-leaved trees, shrubs and herbs (Woodward 1987). Large-scale presentations of the models' results may then be compared with real observations (Fig. 2.2).
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