however, recover again when evolution has had sufficient time to find a new solution to the suddenly changed and emerged life conditions.
The plot illustrates, of course relatively and very roughly, how the ecosphere is moving more and more away from thermodynamic equilibrium by increasing useful knowledge about the ways to utilise the resources and adapt to the currently changing conditions. The amount of biomass has not necessarily changed much over this period of time, except when the terrestrial ecosystems started to be exploited about 400 Ma ago. The amount of inorganic material on Earth available to form complicated and coordinated living matter (this is about 20 elements) has not changed. The changes in the exergy of the biosphere are therefore almost solely due to the increased width and depth of information. The plot in Fig. 11.7 may therefore also be considered as a plot of the relative change in the exergy of the biosphere. The figure should, however, be considered only as a first rough attempt to quantify the evolution.
The following terms are used to cover the various forms of selections (Wilson, 1978):
1. Individual selection. The component of natural selection that operates on the differential fitness of individuals within local and homogeneous populations.
2. Group selection. The component of natural selection that operates on the differential productivity of local populations within the more global population.
3. Egoism. All traits promoted by individual selection d > r in linear selection modelling, where d is the effect on the fitness of the individual itself and r is the effect on every other member of the local population.
4. Weak altruism. All non-egoistic traits selections, where 0 < d < r in linear selection models.
5. Strong altruism. All non-egoistic traits selections, where 0 > d, when r is sufficiently great in linear selection models.
It can be shown that all these types of selections actually take place in nature, and that many observations support the various selection models that are based on these types of selections. Kin selection has been observed with bees, wasps and ants (Wilson, 1978). Prairie dogs endanger themselves (altruism) by conspicuously barking to warn fellow dogs of an approaching enemy (Wilson, 1978), and a parallel behaviour is observed for a number of species.
Co-evolution explains the interactive processes among species. It is difficult to observe co-evolution, but it is easy to understand that it plays a major role in the entire evolution process. The co-evolution of herbivorous animals and plants is a very illustrative example. The plants will develop toward a better spreading of seeds and a better defence towards herbivorous animals. This will in the latter case create a selection of herbivorous animals that are able to cope with the defence. Therefore, the plants and herbivorous animals will co-evolve.
Co-evolution means that the evolution process cannot be described as reductionistic, but that the entire system is evolving. A holistic description of the evolution of the system is needed.
The Darwinian and Neo-Darwinian theories have been criticised from many sides. It has for instance been questioned whether the selection of the fittest can explain the relatively high rate of evolution. Fitness may be measured here by the ability to grow and reproduce under the prevailing conditions. It implies that the question raised according to the Darwinian theories (see the discussion above) is: "which species have the properties that give the highest ability for growth and reproduction?" We shall not go into the discussion in this context, it is another very comprehensive theme, but just mention that the complexity of the evolution processes is often overlooked in this debate. Many interacting processes in evolution may be able to explain the relatively high rate of evolution that is observed.
Seven examples below are used to illustrate that many processes (a) interact, (b) accelerate the rate of evolution and (c) increase the complexity of the evolutionary processes.
1. A mother tiger is an excellent hunter and therefore she is able to feed many offspring and bring her good "hunting genes" further in the evolution. Her tiger kittens have a great probability to survive because they get sufficient food. But in addition she can teach them her hunting strategy and will have more time to care for them in general, because of her successful hunting. So, the kittens not only survive (i.e. the genes survive), but also a better nursing and hunting strategy survives from one tiger generation to the next. we can say in our "computer age" that not only the hardware (the genes) but also the software (the know how) survives.
2. McClintock has observed by working with maize that genes on chromosomes actually move around or transpose themselves; they even appear to change in relation to environmental stress factors. He proposes the idea that the genetic program is not necessarily fixed in each individual. Other geneticists have found what have been dubbed "jumping genes" and to a certain extent confirm this idea. Jumping genes are often named transposons and many workers have labelled them "selfish DNA" (Dawkins, 1989). These discoveries may form the basis for a revolution in biological thinking: the reductionist image of a genetic blueprint may be false.
3. Cairns et al. (1988) showed that when bacteria lacking an enzyme for metabolising lactose were grown in a lactose medium, some of them underwent a mutation that subsequently enabled them to produce the enzyme. This mutation violated the long-held central dogma of molecular biology, which asserts that information flows only one way in the cell—from genes to RNA, to protein and enzyme. Here, the information was obviously going in the reverse direction. An enzyme coded for by a particular gene was feeding back to change that gene itself.
4. A problem of mutations with large effects on development is that they are usually selectively disadvantageous. However, Augros and Stanciu (1987) claim that a subsidiary peak occurs through a different and novel mechanism, which may be explained by a mutation of the D-genes—the genes that control the development of the organism.
5. Symbiosis is generally very well developed in nature. Poly-cellular organisms are a result of symbiotic relationships among many unicellular organisms according to Lynn Margulis, as can be recognised from the endo-symbiosis in all organisms. It may explain the jumps in the evolution: two or more "properties" are suddenly united and create a symbiotic effect (see Mann, 1991).
6. Fischer and Hinde (1949) describe how the habit of opening milk bottles has spread among blue and great tits. Milk bottles were left on the doorsteps of households and were raided by these songbirds, which open them by tearing off their foil caps. The birds then drink the cream frOm the tOp Of the bOttles. The habit has prObably spread thrOugh sOme type Of sOcial learning Or sOcial enhancement. A nOvel and learned behaviOur appears tO have mOdified these birds' envirOnments in ways that have subsequently changed the selection pressures that act back on the bird themselves (Sherry and Galef, 1984). None has shOwn any genetic respOnse tO these altered selectiOn pressures.
This example illustrates what Odling-Smee and Patten (1992) call "ecological inheritance", which they assert wOrks parallel tO the genetic inheritance. The ecOlOgical inheritance is a result Of the species' ability tO change their envirOnment and thereby tO a certain extent mOdify the selectiOn pressure On themselves.
NObOdy dealing with evOlutiOn wOuld deny these pOssibilities Of the species tO mOdify their Own envirOnment, but the influence Of this ability On the evOlutiOn prOcess has mOst prObably been underestimated. Odling-Smee and Patten attempt tO emphasise the impOrtance by intrOductiOn Of the cOncept Of "envirOtype" as a supplement tO genOtype and phenOtype.
A tOtal image Of the evOlutiOn will require a hOlistic apprOach tO accOunt fOr many simultaneOusly interacting prOcesses. EvOlutiOn is a result Of many simultaneOus prOcesses that are interacting in a very cOmplex way. This may enable us tO explain the relatively high rate Of evOlutiOn.
7. A further cOmplicatiOn is the sO-called mOrphO-genes Or D-genes. The develOpmental prOcesses, as mentiOned in the fOurth example abOve, are ObviOusly extremely impOrtant fOr the evOlutiOn prOcesses, but it wOuld nOt be pOssible tO gO intO mOre detail in this cOntext. Further infOrmatiOn can be fOund in Dawkins (1982, 1989) and AugrOs and Stanciu (1987).
The cOncept Of sustainable develOpment is frOm a thermOdynamical pOint Of view unrealistic, if we cOnsider the entire ecOsphere and technOsphere. Only lOcally is sustainable develOpment pOssible and Only as a result Of an entrOpy dump elsewhere.
It is pOssible tO set up an exergy balance fOr the entire biOsphere and On a glObal scale.
Figs. 11.3 and 11.4 give a clear global image of the exergy balance. The exergy map indicates the upwelling areas in the Oceans very clearly. The trOpical fOrest areas OppOsite the deserts have a high utilisatiOn Of the exergy in the sOlar radiatiOn. The net primary prOductiOn is almOst mOnOtOnOusly declining frOm the equatOr tO the pOles—sO the exergy pattern and vegetatiOn pattern fOllOw, nOt surprisingly, the radiatiOn pattern very clOsely.
The exergy Of the biOsphere has been calculated based upOn the difference in chemical composition between biota and the crust. The crust represents the thermodynamic equilibrium and the cOmpOsitiOn Of the biOsphere represents the free energy Of the biOsphere—the chemical energy needed tO prOvide the characteristic cOmpOsitiOn Of the biosphere. An expression can also easily be found for specific exergy: see Eq. (7.2); r, the ratiO Of living matter tO the tOtal weight Of the biOsphere, is fOund tO be 2.5 X 1024. When this value is applied, the specific exergy is found to be 520 kJ/g, which can be compared with the expected value, namely 30 X 18.4 kJ/g = 550 kJ/g, where 30 is the
B value of average plants/vegetation; see Table 5.1. The two values are very close, which may be considered as a support for the weighting factors based on the genetic information.
The external factors steadily change the species composition. The introduction of exergy calculations in ecological models makes it possible to describe this shift in the species composition, as will be presented later. Exergy is, so to say, a measure of the survival, as it accounts for biomass and information. Which properties give the best survival can be determined by testing which properties (parameters in the models) give the highest exergy.
The exergy weighting factors have also been used in an attempt to express the evolution quantitatively by multiplication of the number of families and the weighting factors of the most developed species. The number of families expresses the possibilities the ecosphere offers to utilise the available resources and the ecological niches—we could call it the width of the biological information—and the weighting factor expresses the amount of feedbacks and regulation mechanisms the most advanced species have—we could call it the depth of the biological information. The multiplication of the two would, therefore, be a relative measure of the overall increase of the biological information. Fig. 11.7 shows this quantification of the evolution.
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