•% \ "■ )Exhaustion Repair '/s - i • .. ... Exhaustion •"-I : "= vi>\ } • •• , • " ./U ) . • ■ X - ■ • 1 : Phase \ Phase 'l :" ' 1 ^Phase
1 , V Removal. / • | ; \
Exhaustion, Death acute damage chronic damage death
Exhaustion, Death acute damage chronic damage death
Strong stress out of an alarm phase more or less rapidly leads into a phase of exhaustion followed by acute damage and death. The stress has negative effects, it is a distress.
Box 3.1 (Continued)
Low stress leads into an alarm phase generating recovery mechanisms. In a recovery phase the system develops out of the conditions in which stress has negative effects, to conditions in which stress has positive effects and stimulates the system; stress is a eustress. The system stabilizes during a hardening phase and attains a resistance phase, in which it may remain, unless the degree of stress is changed or external or internal reserves required for resistance are exhausted. With respect to the latter, it is clear that time, i.e. the duration of stress application may be important. Upon stress removal the system enters a dehardening phase and returns to the normal level.
The system first develops like that of case (2), but then additional stress is applied either by the original stress becoming stronger or by additional different stressor(s). The system now goes into the condition of distress, an exhaustion phase and chronic damage.
4. Strong stress with acute damage followed by repair after stress removal The system first develops like that of case (1), but then a stress-free period follows, and during a repair phase the system is restored and returns to the "normal" level.
(After Beck and Luttge 1990.)
Phenotypes are the receivers and modulators of environmental input and producers of output performance at the community level. The development of phenotypes from genotypes is the real origin of complexity in biology (Schuster 1998; see also West-Eberhard 1986, 1989, 2003; Sultan and Bazzaz 1993; Solbrig 1994; Gehrig et al. 2001). Booth and Grime (2003) tried to test this using microcosms planted with different species, where each species was present in different microcosms at a different degree of genetic diversity. The genetic diversity was generated by planting mixtures of varying numbers of different clones of plants obtained from vegetative propagation. Stress was applied in the form of trampling and artificial grazing. In
Fig. 3.17 Relationship between the diversity of trees and vines in a Malaysian rainforest (ordinate) and combined phosphorus and potassium concentrations in the soil (P + N index on the abscissa). (After Tilman 1982)
Phosphorus / Potassium
Phosphorus / Potassium this way it was attempted to relate genetic diversity to community diversity. Diversity declined in all of the microcosms, and there were no dramatic differences in the first 3 years of the 5 years experiment. However, in the last 2 years the decline of diversity was lower in the microcosms having the largest genetic diversity.
With regard to plasticity it appears that both high stress and low stress do not favour traits, which support such phenotypic variability. High stress favours specialized adaptations to the prevailing specific and strong stressor (e.g. frost near the poles or drought in deserts). Low stress allows the success of few species, which can competitively procure resources for development of their own biomass (e.g. nitrophilous plants in sites rich in nitrate and other nutrients). Only medium stress advances the unfolding of variability. Stress of medium intensity and high variability in time is typical for the environment of the tropical forests, where the important factors are:
None of these factors ever really becomes extreme, but their dynamic spatiotemporal variations and interactions cause stress in tropical forests and determine the struggle for existence between species (Richards 1996). This makes it important to study functional diversity and in this respect the observation of cross diversity by Guehl et al. (2004) is highly interesting. These authors have used the relation between 8 13C-data and leaf conductance for water vapour, gH2O (see Sect. 2.5) to assess water relations of functional types of rain forest trees, i.e. shade tolerant, hemi tolerant and heliophilic species. Differences in 8 13C among species were primarily driven by gH2O, and there was some indication for the expected higher water use efficiency of heliophilic species. However, there was a non-linear pattern in the relations of 8 13C and the gradient of shade tolerance and the results were not in full agreement with a simple concept of functional types, so that cross diversity among main functions or traits may reflect an important aspect in functional diversity.
Phenotypic plasticity must be considered in relation to co-occurrence of different genotypes within a population which are each adapted to a slightly different environment. Genetic variation is reflected in phenotypic plasticity (Booy et al. 2000). Plasticity itself can be considered as a trait, which is subject to selection (WestEberhard 1986, 1989, 2003). However, plasticity per se is not adaptive. This much depends on the physiological costs of plasticity (van Kleunen and Fischer 2005). In any case, phenotypic plasticity offers material for selection, since selection is acting on the phenotypes. This is particularly important in systems, which are not strictly homeostatic (see Sect. 3.3.3), and where radiative movement of phenotypes followed by separation may be one of the bases for the development of genetic diversity (West-Eberhard 1986, 1989, 2003). Thus, the promotion of phenotypic plasticity by variable and medium stress may be one of the reasons for the extraordinarily high biodiversity of tropical forests (Lüttge 1995, 2005, 2007).
3.3.3 Diversity and the Chaos of Oscillating Mosaics
After assessing diversity and plasticity, this then leads us to the question: Is there homeostasis? The tropical rainforest is frequently considered to be a climax association. Ideally, climax associations are steady-states for vegetation, representing stable or homeostatic ecological equilibria, determined by the natural environmental factors in a given climatic zone. According to the climax theory (Clements 1936) independent of the starting conditions at a given location, progressive successions should always lead to the same final equilibrium or climax association. Only when there is an effect of external influences, such as natural or man-made catastrophes, are regressive successions elicited, which cause a deviation from the climax association. Of course, the latter involves changes of environmental conditions.
The question arises, however, as to whether the final steady state is really independent of the starting conditions. Can predictions be made? Is there only one possible final equilibrium? Or are there several different possible ecological states? Is it then possible that small initial deviations from the mean climatic conditions (e.g. mean annual precipitation and temperatures) might divert the development of succession towards very different end points?
In fact, the straightforward application of the climax theory to large ecosystems has been challenged by Remmert (1985, 1991), using the very example of the tropical rainforest. He strongly underlines the dynamic nature of rainforests (see also Whitmore 1990) and in his view the tropical rainforest is subject to a continuous cycle of series of successional states. It represents a diverse cyclically changing mosaic pattern (see also Watt 1947). This can be illustrated by considering the dynamics of gaps or chablis in the tropical rainforest (Orians 1982; van der Meer and Bongers 1996). In the original French meaning chablis are clearings in forests due to storms. In wet tropical forests tall falling trees with their large crowns cause two adjacent gaps, one beneath the original location of the crown and the other one at the site of impact on the ground (Fig. 3.18).
When this is set in the context of floristic diversity, destruction such as the formation of chablis, as well as the introduction of roads may increase diversity because j-diversity is introduced (Sect. 3.3.1). Gaps and chablis are reinvaded by vegetation, and with various successional stages the forest is restored (Fig. 3.19). Thus, such chablis are sites of destruction and renewal, which at any given time may comprise 3 -10% of the total forest area (Jacobs 1988). Larger clearings also result from shifting agriculture (Fig. 3.20) and other human activities.
In the renewal of forest in natural clearings resulting from falling trees, hurricanes, earthquakes, volcanic eruptions, fires and landslides, or in farms abandoned due to exhaustion of nutrients or the take-over of weeds and pests there is no predetermined pattern. As Jacobs (1988) comments "... the selection is one of unpredictable irregularity". There is a plethora of environmental factors affecting regeneration and to which the unpredictability of proximal species regeneration will be related to. It depends among others on the extent of diversity in adjacent vegetation and the age of the surrounding communities, the light climate (Torquebiau 1988), the availability and viability of propagules, seed and seedling bank compo-
sition (Dalling et al. 1998; Massey et al. 2006), dispersal limitation and dormancy parameters (Dalling et al. 1998), differences in growth and mortality rates among species with different carbon allocation patterns (Newell et al. 1993; Dalling et al. 1998), edaphic specialization and soil resources (Phillips et al. 2003; Palmiotto et al. 2004; Valencia et al. 2004). With such unpredictability we are not naturally facing a stochastic development of diversity. This would be an a priori unjustified simplification. However, we are right back in the realm of non-linear dynamics and deterministic chaos (Sect. 2.6; Solé et al. 1994; Solé and Manrubia 1995a,b; Man-rubia and Solé 1996; Levin and Muller-Landau 2001), where we may recall one of the most characteristic implications of the chaos theory, namely that even the slightest differences in the starting conditions - or the many factors affecting gap dynamics - may lead to the most dramatic differences in subsequent development (see also Fig. 2.15C).
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