individual plants. Biomass growth in LUCIA follows the WOFOST concept, as
implemented in the Crop Growth Monitoring System (Supit 2003). Potential
growth rates are thereby calculated first, as determined by photo-synthetically
active solar radiation and plant-specific assimilation capacity. Actual growth rates
are then derived by successively introducing water and nutrient constraints, which
are determined by the actual soil water and nutrient contents, and the rooting depth.
Having accounted for respiration, net assimilates are converted into biomass.
Morphological characteristics of the plant stand are then mainly driven by air
temperature. Within a species-specific range, temperature sums are accumulated,
which then determine the phenological development stages, from germination
through flowering to maturity. Thus, for annual plants, higher temperatures
throughout a growing season lead to accelerated maturation and shorter vegetation
periods. Phenological development steers important physiological functions in the
plant organism, such as the partitioning of assimilates between plant parts (leaves,
stems, fruits and roots), the N, P and K demand of these same parts, the maximum
assimilation capacity and the specific leaf area (SLA; a measure of leaf thickness).
Values for these factors vary throughout the development stages of the plant and are
thus indirectly temperature driven.
Once leaf biomass has been formed according to the above-mentioned
partitioning rules, it is converted into leaf area index (LAI) by multiplication with
SLA. LAI expresses leaf area relative to ground area and thus determines the
capacity of the plant to absorb sunlight.
LUCIA can simulate both annual and perennial plants. The biomass and LAI of
perennial plants, which are present before the start of a simulation, such as old
growth forest, can be initialized using allometric or other empiric equations.
Plant litter in the form of leaves is shed once a plant ages, experiences severe
drought stress or shades itself out once the canopy becomes too dense (i.e., above a
threshold of LAI). In addition, plant necromass can remain in the field after harvest
or slashing and burning; this includes above-ground as well as root litter. While the
latter remains in the respective horizons, the former can be incorporated into the
soil when plowing takes place.
10.2.3.4 Soil Organic Matter
Carbon and macro-nutrients circulate between plant and soil, and turnover rates are
determined by soil organic matter dynamics (Fig. 10.5). Above ground and root
litter are subdivided into a metabolic and a structural fraction, which differ in their
lignin: N and C:N ratios, and decompose at different rates. When these pools are
initialized in the model, they are associated with the present vegetation, not genetic
soil units.
Litter fractions are converted into soil organic matter (SOM) over time. As an
analogy for litter, SOM fractions are characterized by distinct C:N ratios and
decomposition rates, representing the role of substrate degradability in microbial
decomposition processes. The entire system is carbon and thus energy-driven and
10 Integrated Modeling of Agricultural Systems in Mountainous Areas
377
implemented in the Crop Growth Monitoring System (Supit 2003). Potential
growth rates are thereby calculated first, as determined by photo-synthetically
active solar radiation and plant-specific assimilation capacity. Actual growth rates
are then derived by successively introducing water and nutrient constraints, which
are determined by the actual soil water and nutrient contents, and the rooting depth.
Having accounted for respiration, net assimilates are converted into biomass.
Morphological characteristics of the plant stand are then mainly driven by air
temperature. Within a species-specific range, temperature sums are accumulated,
which then determine the phenological development stages, from germination
through flowering to maturity. Thus, for annual plants, higher temperatures
throughout a growing season lead to accelerated maturation and shorter vegetation
periods. Phenological development steers important physiological functions in the
plant organism, such as the partitioning of assimilates between plant parts (leaves,
stems, fruits and roots), the N, P and K demand of these same parts, the maximum
assimilation capacity and the specific leaf area (SLA; a measure of leaf thickness).
Values for these factors vary throughout the development stages of the plant and are
thus indirectly temperature driven.
Once leaf biomass has been formed according to the above-mentioned
partitioning rules, it is converted into leaf area index (LAI) by multiplication with
SLA. LAI expresses leaf area relative to ground area and thus determines the
capacity of the plant to absorb sunlight.
LUCIA can simulate both annual and perennial plants. The biomass and LAI of
perennial plants, which are present before the start of a simulation, such as old
growth forest, can be initialized using allometric or other empiric equations.
Plant litter in the form of leaves is shed once a plant ages, experiences severe
drought stress or shades itself out once the canopy becomes too dense (i.e., above a
threshold of LAI). In addition, plant necromass can remain in the field after harvest
or slashing and burning; this includes above-ground as well as root litter. While the
latter remains in the respective horizons, the former can be incorporated into the
soil when plowing takes place.
10.2.3.4 Soil Organic Matter
Carbon and macro-nutrients circulate between plant and soil, and turnover rates are
determined by soil organic matter dynamics (Fig. 10.5). Above ground and root
litter are subdivided into a metabolic and a structural fraction, which differ in their
lignin: N and C:N ratios, and decompose at different rates. When these pools are
initialized in the model, they are associated with the present vegetation, not genetic
soil units.
Litter fractions are converted into soil organic matter (SOM) over time. As an
analogy for litter, SOM fractions are characterized by distinct C:N ratios and
decomposition rates, representing the role of substrate degradability in microbial
decomposition processes. The entire system is carbon and thus energy-driven and
10 Integrated Modeling of Agricultural Systems in Mountainous Areas
377