**4.3 The reason for termination of proliferation of old cells**

The cell division cycle (proliferative cycle) is divided into four phases (Sherr, 1994): G1, S, G2, and M (Fig.1).

Cycle of cell reduplication is divided into 4 phases: G1 (gap 1), S (synthesis), G2 (gap 2), and M (mitosis). Fig. 3. Phases of proliferative cell cycle.

In the G1-phase, precursor molecules necessary for DNA reduplication and doubling of all cell structures in the following division are synthesized. In the following S-phase, DNA is reduplicated, and after a short G2-phase, a cell enters M. Numerous studies have showed that all non dividing cells stay in the G1-phase. If a cell has passed through this phase, then it will pass through other phases automatically with almost equal speed. As far as entry of old cells into irreversible proliferative quiescence is concerned, we will be interested only in events occurring in the G1-phase. Control of the cell division rate is performed by endogenous and exogenous (for a cell) regulatory factors that are stimulators and inhibitors of proliferation. As an example of such regulation, the data of one of the first works in this field (Leof, et al., 1982) accurately reflecting the essence of the phenomenon are shown. The effect of different growth factors on mouse fibroblasts was studied. It was shown that, right after mitosis completion, a cell enters a proliferative quiescence state between the M and G1 phases (the G0-phase). To be removed from this state, a cell needed an external proliferative signal from platelet derived growth factor (PDGF). No structural or biochemical changes in a quiescent cell happened without the signal, and it remained insensitive to other proliferative stimuli. This primary stimulus is a competence factor. After a cell has received

Bioenergetics Theory of Aging 75

activity is quite complex (Morgan,1995) but it is enough to know two principal moments to uncover the discussed topic: (1) Cdk is activated when it is conjugated with a specific cyclin (which is evident from its name) and (2) an active Cdk-cyclin complex can be deactivated again if it is conjugated with a specific inhibitor of cyclin-dependent kinases. To date eight types of cyclin-dependent kinases marked with the numbers Cdk1, Cdk2, etc.; ten types of cyclins marked with the Latin letters cyclin A, cyclin B, etc.; and a large group of Cdk inhibitors that have individual number labels and represent several families have been found in mammals. Three Cdks (2, 4, and 6); the cyclins D, E, and A; and the inhibitors of INK4 (p15ink4b, p16ink4a, p18ink4c, and p19ink4d) and CIP/KIP families (p21cip1, p27kip1, and p57kip2) regulate passage through G1 (Sherr & Roberts 1999; Sherr, 2000). INK4 inhibitors specifically interact with Cdk4 and 6 and function in the G1-phase until the restriction point, and CIP/KIP interact with all Cdks. Research on G1-phase events has increased greatly in the past decade. New biochemical participants and ways in which they interact have been found. Information about them can be found in several reviews and original papers (Bockstaele et al., 2009; Larrea et al., 2008; Rahimi & Leoff, 2007; Sherr, 2000). Here only the main events minimally sufficient for understanding of termination of old cells division will be discussed. Leaving out the details, the G1-phase passing scheme discussed in (Sherr, 1996; Sherr & Roberts, 1999) can be shown in the following way (Fig. 4). The level of inhibitor p27 in quiescent cells is high, which prevents the reaction for division preparation. In response to mitogen stimulation, cyclin D is expressed and the active complex cyclin D-Cdk4 is formed, as are phosphorylates Rb. As a result gene-regulating E2F proteins are released and phosphorylated Rb is degraded. Then E2F proteins activate enzyme genes necessary for DNA reduplication in the S-phase and cyclin E, Cdk2, and E2F genes. Released cyclin E and Cdk2 form an active E-Cdk2 complex, which began interacting with p27, phosphorylating Rb, and activating regulatory protein genes. It is important that the cyclin E-Cdk2 complex activates the genes of their components, i.e., it reproduces itself. As a result a positive feedback loop is formed and promotes rapid p27 removal and E2F proteins and S-phase proteins' avalanche-like increase, which allows a cell to pass through a restriction point. With this E2F increased expression induces synthesis of inhibitor p53, which terminates the E2F expression unnecessary in the S-phase. However, this and the following cycle reactions are outside the discussed topic. Two research groups simultaneously and independently drew a considerable specification of the character of interaction of p27 with active cyclin E-Cdk complex (Vlach et al, 1997; Sheaf et al., 1997). Until their works it was considered that p27 and active cyclin E-Cdk2 complex interaction had a single consequence—complex inactivation. They performed a study of the kinetics of the molecular interactions of these compounds and showed that not only does the inhibitor inactivate the complex, but the

complex can also attack an inhibitor phosphorylating it on threonine 187.

complex and was not found in other analogous complexes.

Figuratively speaking, there is a competition for survival between inhibitor p27 and the cyclin E-Cdk2 complex. Its outcome is determined by the reaction energy supply: with a high ATP level, the cyclin E-Cdk2 complex has an advantage. It phosphorylates p27; after that, this inhibitor becomes a target for ubiquitin-dependent proteolytic machinery and is destroyed. If the bioenergetics level becomes lower than a certain value, then even p27 inactivates cyclin E-Cdk2. As a result a positive feedback loop of E2F synthesis and S-phase transition are blocked. An ability to inactivate its inhibitor belongs only to cyclin E-Cdk2

this signal, the biochemical reactions for new division cycle preparation begin, stopping a period of time. For further development of biochemical events, epidermal growth factor (EGF), not PDGF, was necessary. The addition of EGF caused continuation of biochemical and structural changes, but after some time a new halt at the G1/S-transition occurred, which was called the restriction point R. The passage of the last several hours of the G1 phase happened only under somatomedin C stimulation (Sm-C). The last two factors were called the first and the second progression factors. All tissue cells are stimulated by its growth factors. In addition to growth factors, passing through a cell cycle is regulated by a large group of inhibitors (Sherr & Roberts, 1999; Sherr, 2000). Cells can leave a cycle and move to a quiescent state. There are three types of quiescence. (1) Irreversible quiescence, or the terminal differentiation state, in which cells lose growth factors' receptors and become incapable of returning to a proliferative cycle (for example, neural, secretory, and muscular). (2) Temporal quiescence necessary for a cell to function within one or another tissue. This occurs if a cell does not receive the necessary proliferative stimulus from growth factors or there are exogenous inhibitors in the environment that void their proliferative signal. Such cells retain the integrity of their receptor apparatus, and, in appropriate conditions, they are able to come back to a cycle (for example, hepatocytes, fibroblasts, and others). (3) Proliferative quiescence of old cells that spend all their proliferative potential is similar to temporal quiescence. Cells retain their receptor apparatus and the integrity of all structures necessary for proliferation, although division does not occur.

The first experiments to determine the reasons for termination of proliferation of old cells were performed by Rittling et al. (1986). They studied 11 biochemical reactions happening sequentially in the G1-phase in young and old cells. It was shown that, in old cells, all reactions occur in the same way as in young cells, but old cells stop at the restriction point and deepen in quiescence, not reflecting the proliferative stimulus by the second progression factor. If after some period of time these cells are stimulated by proliferative factors again, they will pass through all the stages of preparation to transfer to the S-phase and will come back to a proliferative quiescence. The authors concluded that, in old cells that have expended all their proliferative potential, the restriction point becomes impassable.

Events happening in the restriction point are studied intensely, mainly by researchers of carcinogenesis. Their interest is due to the fact that malignant cells pass this point without stopping, while a delay of the cycle of dividing normal postembryonic cells here is obligatory and, for old cells, as has already been mentioned, this point becomes an insuperable barrier. To date significant success in studying biochemical events in this point has been achieved.

The main regulators of reactions occurring in the division cycle are cyclin-dependent kinases (Cdks). They are the controllers of all events: the determine the order of reactions, their duration, and their intensity (Sherr, 1996). The function of cyclin-dependent kinases is simple: de novo synthesized gene-regulating proteins of a division cycle E2F leaves a translational conveyor, figuratively speaking, in a package. This package is retinoblastoma protein (Rb). Until these proteins are bound with Rb, they are inactive. Cyclin-dependent kinases phosphorylate Rb protein, and, after that, regulatory proteins are released and activate genes necessary for the division cycle (Sherr, 2000; Frolov & Dyson, 2004). Cdks themselves can be in an active or inactive state. Regulation of cyclin-dependent kinases'

this signal, the biochemical reactions for new division cycle preparation begin, stopping a period of time. For further development of biochemical events, epidermal growth factor (EGF), not PDGF, was necessary. The addition of EGF caused continuation of biochemical and structural changes, but after some time a new halt at the G1/S-transition occurred, which was called the restriction point R. The passage of the last several hours of the G1 phase happened only under somatomedin C stimulation (Sm-C). The last two factors were called the first and the second progression factors. All tissue cells are stimulated by its growth factors. In addition to growth factors, passing through a cell cycle is regulated by a large group of inhibitors (Sherr & Roberts, 1999; Sherr, 2000). Cells can leave a cycle and move to a quiescent state. There are three types of quiescence. (1) Irreversible quiescence, or the terminal differentiation state, in which cells lose growth factors' receptors and become incapable of returning to a proliferative cycle (for example, neural, secretory, and muscular). (2) Temporal quiescence necessary for a cell to function within one or another tissue. This occurs if a cell does not receive the necessary proliferative stimulus from growth factors or there are exogenous inhibitors in the environment that void their proliferative signal. Such cells retain the integrity of their receptor apparatus, and, in appropriate conditions, they are able to come back to a cycle (for example, hepatocytes, fibroblasts, and others). (3) Proliferative quiescence of old cells that spend all their proliferative potential is similar to temporal quiescence. Cells retain their receptor apparatus and the integrity of all structures

The first experiments to determine the reasons for termination of proliferation of old cells were performed by Rittling et al. (1986). They studied 11 biochemical reactions happening sequentially in the G1-phase in young and old cells. It was shown that, in old cells, all reactions occur in the same way as in young cells, but old cells stop at the restriction point and deepen in quiescence, not reflecting the proliferative stimulus by the second progression factor. If after some period of time these cells are stimulated by proliferative factors again, they will pass through all the stages of preparation to transfer to the S-phase and will come back to a proliferative quiescence. The authors concluded that, in old cells that have expended all their proliferative potential, the restriction point becomes

Events happening in the restriction point are studied intensely, mainly by researchers of carcinogenesis. Their interest is due to the fact that malignant cells pass this point without stopping, while a delay of the cycle of dividing normal postembryonic cells here is obligatory and, for old cells, as has already been mentioned, this point becomes an insuperable barrier. To date significant success in studying biochemical events in this point

The main regulators of reactions occurring in the division cycle are cyclin-dependent kinases (Cdks). They are the controllers of all events: the determine the order of reactions, their duration, and their intensity (Sherr, 1996). The function of cyclin-dependent kinases is simple: de novo synthesized gene-regulating proteins of a division cycle E2F leaves a translational conveyor, figuratively speaking, in a package. This package is retinoblastoma protein (Rb). Until these proteins are bound with Rb, they are inactive. Cyclin-dependent kinases phosphorylate Rb protein, and, after that, regulatory proteins are released and activate genes necessary for the division cycle (Sherr, 2000; Frolov & Dyson, 2004). Cdks themselves can be in an active or inactive state. Regulation of cyclin-dependent kinases'

necessary for proliferation, although division does not occur.

impassable.

has been achieved.

activity is quite complex (Morgan,1995) but it is enough to know two principal moments to uncover the discussed topic: (1) Cdk is activated when it is conjugated with a specific cyclin (which is evident from its name) and (2) an active Cdk-cyclin complex can be deactivated again if it is conjugated with a specific inhibitor of cyclin-dependent kinases. To date eight types of cyclin-dependent kinases marked with the numbers Cdk1, Cdk2, etc.; ten types of cyclins marked with the Latin letters cyclin A, cyclin B, etc.; and a large group of Cdk inhibitors that have individual number labels and represent several families have been found in mammals. Three Cdks (2, 4, and 6); the cyclins D, E, and A; and the inhibitors of INK4 (p15ink4b, p16ink4a, p18ink4c, and p19ink4d) and CIP/KIP families (p21cip1, p27kip1, and p57kip2) regulate passage through G1 (Sherr & Roberts 1999; Sherr, 2000). INK4 inhibitors specifically interact with Cdk4 and 6 and function in the G1-phase until the restriction point, and CIP/KIP interact with all Cdks. Research on G1-phase events has increased greatly in the past decade. New biochemical participants and ways in which they interact have been found. Information about them can be found in several reviews and original papers (Bockstaele et al., 2009; Larrea et al., 2008; Rahimi & Leoff, 2007; Sherr, 2000). Here only the main events minimally sufficient for understanding of termination of old cells division will be discussed. Leaving out the details, the G1-phase passing scheme discussed in (Sherr, 1996; Sherr & Roberts, 1999) can be shown in the following way (Fig. 4). The level of inhibitor p27 in quiescent cells is high, which prevents the reaction for division preparation. In response to mitogen stimulation, cyclin D is expressed and the active complex cyclin D-Cdk4 is formed, as are phosphorylates Rb. As a result gene-regulating E2F proteins are released and phosphorylated Rb is degraded. Then E2F proteins activate enzyme genes necessary for DNA reduplication in the S-phase and cyclin E, Cdk2, and E2F genes. Released cyclin E and Cdk2 form an active E-Cdk2 complex, which began interacting with p27, phosphorylating Rb, and activating regulatory protein genes. It is important that the cyclin E-Cdk2 complex activates the genes of their components, i.e., it reproduces itself. As a result a positive feedback loop is formed and promotes rapid p27 removal and E2F proteins and S-phase proteins' avalanche-like increase, which allows a cell to pass through a restriction point. With this E2F increased expression induces synthesis of inhibitor p53, which terminates the E2F expression unnecessary in the S-phase. However, this and the following cycle reactions are outside the discussed topic. Two research groups simultaneously and independently drew a considerable specification of the character of interaction of p27 with active cyclin E-Cdk complex (Vlach et al, 1997; Sheaf et al., 1997). Until their works it was considered that p27 and active cyclin E-Cdk2 complex interaction had a single consequence—complex inactivation. They performed a study of the kinetics of the molecular interactions of these compounds and showed that not only does the inhibitor inactivate the complex, but the complex can also attack an inhibitor phosphorylating it on threonine 187.

Figuratively speaking, there is a competition for survival between inhibitor p27 and the cyclin E-Cdk2 complex. Its outcome is determined by the reaction energy supply: with a high ATP level, the cyclin E-Cdk2 complex has an advantage. It phosphorylates p27; after that, this inhibitor becomes a target for ubiquitin-dependent proteolytic machinery and is destroyed. If the bioenergetics level becomes lower than a certain value, then even p27 inactivates cyclin E-Cdk2. As a result a positive feedback loop of E2F synthesis and S-phase transition are blocked. An ability to inactivate its inhibitor belongs only to cyclin E-Cdk2 complex and was not found in other analogous complexes.

Bioenergetics Theory of Aging 77

reduplication in the S-phase, cyclin E and cyclin-dependent kinase 2 (Cdk2) genes, as well as E2F itself. Combined cyclin E and Cdk2 form an active complex which interacts with inhibitor of cyclin-dependent kinases p27. Two consequences are possible. A. If the bioenergetics level is within the physiological norm, then Cdk2 activated by cyclin E phosphorylates p27. Then the inhibitor becomes a target for degradation. After that cyclin E-Cdk2 phosphorylates Rb and additional gene-regulating proteins are released. As E2F activates cyclin E, Cdk2, and E2F genes, then there is a positive feedback loop promoting rapid p27 removal and an avalanche-like increase of S-phase proteins, which allows a cell to pass through a restriction point. At the same time, increased expression of E2F induces inhibitor p53 synthesis, which inactivates cyclin the E-Cdk2 complex and terminates unnecessary S-phase E2F expression. B. If the bioenergetics level is below a certain critical level, then p27 forms a tight bond with the cyclin E-Cdk2 complex and inactivates it. As a result an increased expression of S-phase proteins does not occur, the p27 level remains

These data can explain the results of the abovementioned research by Rittling et al. The central event of the G1-phase restriction point of the cell cycle is triggering of a self-accelerating cascade of reactions controlled by the cyclin E-Cdk2 complex. This is an essential condition of inhibitor p27 removal and accumulation of all precursors for DNA reduplication and cell division. It is satisfied only with a normal physiological level of bioenergetics. When bioenergetics in old cells decreases until some threshold level, cyclin E-Cdk2 loses its ability to inactivate p27 and itself becomes a target. As a result inhibitor removal stops and S-phase transition becomes impossible. All this information can be summarized in the following way: cyclin-dependent kinase inhibitor p27 prevents passage through the restriction point. There is a special pump for its removal in a cell. Its work efficiency depends on the energy supply. During the programmed decrease of cell bioenergetics, below a certain threshold level, it stops

It should be mentioned that a critical level is achieved after a certain number of divisions. Thus, bioenergetics decrease and the lifespan depend not on the calendar time of an organism's existence, but from the number of past divisions in its critical tissues, i.e., the amount of the past divisions is a biological clock. An organism counts time on proliferative

Several lines of evidence show that genes exert strong controls on longevity and patterns of aging (Carey, 2003; Holzenberger et al., 2003; Kenyon, 2010; Vaupel, 2003). Therefore, the specific genes that program longevity and the selective pressure that would lead the genes to the development during evolution are to exist (Bredesen, 2004; Mitteldorf, 2004; Skulachev, 2001). The most of evolutionists, nevertheless, deny the possibility that longevity is under the control of natural selection (Medawar, 1952; Kirkwood, 2002). In 1952 P.B.Medawar has shown that life expectancy is not under control of individual (Darwinian) natural selection. He has noticed that animals in habitat never live till an old age and perish from the various external reasons at youngish age; therefore the natural selection cannot differentiate them by the longevity sign. Hence the specific genes programming aging

high, and entry into the S-phase becomes impossible.

inhibitor removal and cell division becomes impossible.

**5. Longevity is under control of natural selection** 

cannot exist. This conception dominates till now.

clock.

**5.1 Introduction** 

Fig. 4. Simplified scheme of control of passing through a restriction point.

In response to mitogen stimulation, an active cyclin D-Cdk4 complex is synthesized, which phosphorylates Rb protein. As a result gene-regulating E2F proteins are released and phosphorylated Rb degrades. E2F proteins activate genes of proteins essential for DNA

Fig. 4. Simplified scheme of control of passing through a restriction point.

In response to mitogen stimulation, an active cyclin D-Cdk4 complex is synthesized, which phosphorylates Rb protein. As a result gene-regulating E2F proteins are released and phosphorylated Rb degrades. E2F proteins activate genes of proteins essential for DNA reduplication in the S-phase, cyclin E and cyclin-dependent kinase 2 (Cdk2) genes, as well as E2F itself. Combined cyclin E and Cdk2 form an active complex which interacts with inhibitor of cyclin-dependent kinases p27. Two consequences are possible. A. If the bioenergetics level is within the physiological norm, then Cdk2 activated by cyclin E phosphorylates p27. Then the inhibitor becomes a target for degradation. After that cyclin E-Cdk2 phosphorylates Rb and additional gene-regulating proteins are released. As E2F activates cyclin E, Cdk2, and E2F genes, then there is a positive feedback loop promoting rapid p27 removal and an avalanche-like increase of S-phase proteins, which allows a cell to pass through a restriction point. At the same time, increased expression of E2F induces inhibitor p53 synthesis, which inactivates cyclin the E-Cdk2 complex and terminates unnecessary S-phase E2F expression. B. If the bioenergetics level is below a certain critical level, then p27 forms a tight bond with the cyclin E-Cdk2 complex and inactivates it. As a result an increased expression of S-phase proteins does not occur, the p27 level remains high, and entry into the S-phase becomes impossible.

These data can explain the results of the abovementioned research by Rittling et al. The central event of the G1-phase restriction point of the cell cycle is triggering of a self-accelerating cascade of reactions controlled by the cyclin E-Cdk2 complex. This is an essential condition of inhibitor p27 removal and accumulation of all precursors for DNA reduplication and cell division. It is satisfied only with a normal physiological level of bioenergetics. When bioenergetics in old cells decreases until some threshold level, cyclin E-Cdk2 loses its ability to inactivate p27 and itself becomes a target. As a result inhibitor removal stops and S-phase transition becomes impossible. All this information can be summarized in the following way: cyclin-dependent kinase inhibitor p27 prevents passage through the restriction point. There is a special pump for its removal in a cell. Its work efficiency depends on the energy supply. During the programmed decrease of cell bioenergetics, below a certain threshold level, it stops inhibitor removal and cell division becomes impossible.

It should be mentioned that a critical level is achieved after a certain number of divisions. Thus, bioenergetics decrease and the lifespan depend not on the calendar time of an organism's existence, but from the number of past divisions in its critical tissues, i.e., the amount of the past divisions is a biological clock. An organism counts time on proliferative clock.

#### **5. Longevity is under control of natural selection**

#### **5.1 Introduction**

Several lines of evidence show that genes exert strong controls on longevity and patterns of aging (Carey, 2003; Holzenberger et al., 2003; Kenyon, 2010; Vaupel, 2003). Therefore, the specific genes that program longevity and the selective pressure that would lead the genes to the development during evolution are to exist (Bredesen, 2004; Mitteldorf, 2004; Skulachev, 2001). The most of evolutionists, nevertheless, deny the possibility that longevity is under the control of natural selection (Medawar, 1952; Kirkwood, 2002). In 1952 P.B.Medawar has shown that life expectancy is not under control of individual (Darwinian) natural selection. He has noticed that animals in habitat never live till an old age and perish from the various external reasons at youngish age; therefore the natural selection cannot differentiate them by the longevity sign. Hence the specific genes programming aging cannot exist. This conception dominates till now.

Bioenergetics Theory of Aging 79

of populations having less *Nmin* is the essence of interpopulation natural selection. Natural selection, as a whole, consists of two stages. During the first stage, the classical Darwin-Wallace individual selection rejects organisms which are less adapted to the given environment. As the members of the population serve as an environmental factor for each individual, attributes can arise that are useful only to their carriers but neutral or harmful for the other individuals. Such attributes become harmful for the community, but they are supported by individual natural selection. Longevity and a number of psychological attributes, for example, are a concern to them (Gadgil, 1975). The interpopulation selection takes such attributes under control as the populations are units of natural selection in the second stage (Levins, 1962; Wilson, 1973). If any attribute decreases *Neq,* or increases the amplitude of oscillations and spreads in the population, then the population perishes as a whole. In contrast, the attributes that increase *Nmin* promote population survival, which is an evolutionary mechanism for developing characteristics that are useless or even harmful for individuals, but beneficial for the community (e.g., altruism, care of posterity, and bravery). To determine the direction of evolution for a specific attribute of a species' populations, it is necessary to assess the dependence of *Nmin* from a quantitative expression of this attribute.

To solve the problem under consideration, we need to consider the dynamics of populations of an abstract species of vertebrates with overlapping generations. In so doing, we shall determine the dependence on *Nmin* from the intrinsic population growth rate (*rin*) at a various

A change in size of population, *dN/dt*, depends on the difference between birth and death

Population size does not influence the birth and death rates directly, but through changes in environmental parameters. When the population size increases, food resources are exhausted, the number of predators and parasites grow, infections are increased, and living space per capita declines. All this raises the level of environmental pressure upon a

where *bin* and *min* are intrinsic are birth and death rates that are realized, provided that *N* is negligible; *a* and *j* are environmental pressures on the birth and death rates respectively. Substituting *b* and *m* from equation (4) in equation (2), and taking into account equation (3),

*r lnR T in* <sup>0</sup> / (1)

/ / – / . *dN dt dN dt dN dt b m* (2)

/ *<sup>b</sup> dN dt bN* and *dN dt mN <sup>m</sup>* / (3)

; *in b b aN m m jN in* (4)

value of environment pressure in the species' ecological niche, remembering thus that

The pressure of group selection is always directed to an increase in *Nmin.*

**5.4 Evolution mechanism of longevity and fertility** 

Accordingly, population size influences birth and death rates:

where *b* and *m* are density-dependent are birth and death rates, respectively.

population. As a result, the birth rate decreases but the death rate increases (Fig. 5):

rates:

it follows that:

The aim of this section was to show the mechanism by which natural selection controls species-specific longevity. The ecological approach was used to solve the problem. As known from ecological laws, the intrinsic population growth rate (*rin*), the length of the generation (*T*), and the net reproductive rate (*R0*) are interconnected by dependence, according to the following formula: *rin= lnR0/T* (MacArthur & Connell, 1966)*.* It is shown here that during evolution the *rin* value is stabilized by interpopulation (group) natural selection (not individual selection) at the level which corresponds to environmental pressure in the ecological niche of the species. This leads to the conclusion that species-specific longevity and fertility are under the control of natural selection and depend inversely on each other.

#### **5.2 Population size oscillations and extinction risk**

The state of a population's size over the long-term is a measure of population welfare. Stability or an increase in size testifies to the well-being of the community, but a decrease indicates that the population is under risk of extinction. A practical determination of this criterion represents a difficult problem because biological systems are dynamic. Successive changes in biological systems are termed "disturbance" (White & Pickett, 1985). Disturbances are inherent in all biological communities and occur on a wide range of quantitative, spatial, and temporal scales (Pickett & White, 1985). The size of any population determined by observation is in fact its value at an instantaneous time cut-off (Southwood, 1981). Population number can change in time by hundreds, thousands, and in some species, even by millions (Nicholson, 1954). Population size oscillations are forced by varying environmental factors, such as the infections, the availability of food, the number of predators and parasites, etc. The mean population size, population number averaged over some period of observation, is a much more informative characteristic. Based on theoretical averaging over a prolonged time interval, this parameter is considered to be the dynamically equilibrium size *(Neq).* However, the fate of a population depends on its minimal size (*Nmin*), i.e., the lowest value which a population reaches in the process of oscillations. *Nmin* depends on both *Neq* and swings in the population size. The minimal population size is a genetic bottleneck that is an evolutionary event in which the population is often reduced by several orders of magnitude (Leberg, 1992; Richards & Leberg, 1996). Populations are potentially immortal, but each of them is always subject to the risk of extinction due to minimum viable population size (Green, 2003; Tracy & George, 1992). The last is the smallest population size that will persist over some specified length of time with a specified probability (Hedrick & Gilpin, 1996). If a population size is reduced below this value, even if for a moment in time, then the population becomes doomed to extinction during future generations due to genetic drift (Cherry & Wakeley, 2003; Gilpin & Soule, 1986). Therefore, the extinction risk is maximal in the *Nmin* state because a significant part of a population is prevented from reproducing. This increases genetic drift, as the rate of the drift is inversely proportional to the population size (Frankham, 1996; Lande, 1993; Shaffer, 1981).

#### **5.3 The interpopulation natural selection**

The mechanism of interpopulation natural selection is simple: "Small populations can fluctuate out of existence quite rapidly" (Leigh, 1975). In other words, preferred extinction

The aim of this section was to show the mechanism by which natural selection controls species-specific longevity. The ecological approach was used to solve the problem. As known from ecological laws, the intrinsic population growth rate (*rin*), the length of the generation (*T*), and the net reproductive rate (*R0*) are interconnected by dependence, according to the following formula: *rin= lnR0/T* (MacArthur & Connell, 1966)*.* It is shown here that during evolution the *rin* value is stabilized by interpopulation (group) natural selection (not individual selection) at the level which corresponds to environmental pressure in the ecological niche of the species. This leads to the conclusion that species-specific longevity and fertility are under the control of natural selection and depend inversely on

The state of a population's size over the long-term is a measure of population welfare. Stability or an increase in size testifies to the well-being of the community, but a decrease indicates that the population is under risk of extinction. A practical determination of this criterion represents a difficult problem because biological systems are dynamic. Successive changes in biological systems are termed "disturbance" (White & Pickett, 1985). Disturbances are inherent in all biological communities and occur on a wide range of quantitative, spatial, and temporal scales (Pickett & White, 1985). The size of any population determined by observation is in fact its value at an instantaneous time cut-off (Southwood, 1981). Population number can change in time by hundreds, thousands, and in some species, even by millions (Nicholson, 1954). Population size oscillations are forced by varying environmental factors, such as the infections, the availability of food, the number of predators and parasites, etc. The mean population size, population number averaged over some period of observation, is a much more informative characteristic. Based on theoretical averaging over a prolonged time interval, this parameter is considered to be the dynamically equilibrium size *(Neq).* However, the fate of a population depends on its minimal size (*Nmin*), i.e., the lowest value which a population reaches in the process of oscillations. *Nmin* depends on both *Neq* and swings in the population size. The minimal population size is a genetic bottleneck that is an evolutionary event in which the population is often reduced by several orders of magnitude (Leberg, 1992; Richards & Leberg, 1996). Populations are potentially immortal, but each of them is always subject to the risk of extinction due to minimum viable population size (Green, 2003; Tracy & George, 1992). The last is the smallest population size that will persist over some specified length of time with a specified probability (Hedrick & Gilpin, 1996). If a population size is reduced below this value, even if for a moment in time, then the population becomes doomed to extinction during future generations due to genetic drift (Cherry & Wakeley, 2003; Gilpin & Soule, 1986). Therefore, the extinction risk is maximal in the *Nmin* state because a significant part of a population is prevented from reproducing. This increases genetic drift, as the rate of the drift is inversely proportional to the population size (Frankham, 1996; Lande, 1993; Shaffer,

The mechanism of interpopulation natural selection is simple: "Small populations can fluctuate out of existence quite rapidly" (Leigh, 1975). In other words, preferred extinction

each other.

1981).

**5.3 The interpopulation natural selection** 

**5.2 Population size oscillations and extinction risk** 

of populations having less *Nmin* is the essence of interpopulation natural selection. Natural selection, as a whole, consists of two stages. During the first stage, the classical Darwin-Wallace individual selection rejects organisms which are less adapted to the given environment. As the members of the population serve as an environmental factor for each individual, attributes can arise that are useful only to their carriers but neutral or harmful for the other individuals. Such attributes become harmful for the community, but they are supported by individual natural selection. Longevity and a number of psychological attributes, for example, are a concern to them (Gadgil, 1975). The interpopulation selection takes such attributes under control as the populations are units of natural selection in the second stage (Levins, 1962; Wilson, 1973). If any attribute decreases *Neq,* or increases the amplitude of oscillations and spreads in the population, then the population perishes as a whole. In contrast, the attributes that increase *Nmin* promote population survival, which is an evolutionary mechanism for developing characteristics that are useless or even harmful for individuals, but beneficial for the community (e.g., altruism, care of posterity, and bravery). To determine the direction of evolution for a specific attribute of a species' populations, it is necessary to assess the dependence of *Nmin* from a quantitative expression of this attribute. The pressure of group selection is always directed to an increase in *Nmin.*

#### **5.4 Evolution mechanism of longevity and fertility**

To solve the problem under consideration, we need to consider the dynamics of populations of an abstract species of vertebrates with overlapping generations. In so doing, we shall determine the dependence on *Nmin* from the intrinsic population growth rate (*rin*) at a various value of environment pressure in the species' ecological niche, remembering thus that

$$r\_{\rm int} = \ln R\_0 \, / \, T \tag{1}$$

A change in size of population, *dN/dt*, depends on the difference between birth and death rates:

$$dN \;/\, dt \; = \; d\mathcal{N}\_b \;/\, dt \; - \; d\mathcal{N}\_m \;/\, dt. \tag{2}$$

Accordingly, population size influences birth and death rates:

$$\left|dN\_b \right\rangle \left|dt\right\rangle = bN \quad \text{and} \; dN\_m \;/\, dt \; = \text{mN} \tag{3}$$

where *b* and *m* are density-dependent are birth and death rates, respectively.

Population size does not influence the birth and death rates directly, but through changes in environmental parameters. When the population size increases, food resources are exhausted, the number of predators and parasites grow, infections are increased, and living space per capita declines. All this raises the level of environmental pressure upon a population. As a result, the birth rate decreases but the death rate increases (Fig. 5):

$$b = b\_{in} - aN; \ m = m\_{in} + jN \tag{4}$$

where *bin* and *min* are intrinsic are birth and death rates that are realized, provided that *N* is negligible; *a* and *j* are environmental pressures on the birth and death rates respectively. Substituting *b* and *m* from equation (4) in equation (2), and taking into account equation (3), it follows that:

Bioenergetics Theory of Aging 81

*<sup>t</sup>* / ( – ) *t in t*( ) *dN dt N r pN*

Exes: abscissa is time and the ordinate is the currant population number divided by the equilibrium at time t0 (Nr = Nt/Neq). The consequences of two situations in the environment are modulated (two curves): (1) a favorable coincidence that raises the outbreak of the population number (N0 > Neq= 1.5) and (2) coincidence of severe conditions that causes population depression (N0 < Neq= 0.5). (a)

Populations having small values of rin are reduced to the minimal value after outbreaks of numbers (red curve): coincidences of favorable circumstances in the environment threaten the existence of such populations to a greater extent. (b) Populations having large values of rin reach the lowest number after a state of decay (red curve): coincidences of unfavorable circumstances threaten the existence of such populations to a greater extent. (c) There is an optimal rin value under the present environmental pressure when favorable and unfavorable environment cataclysms are followed by an equal aftereffect. The value of Nmin is maximal under this rin; this rin value is maintained by interpopulation selection. Fig. 6. The influence of the intrinsic population growth rate on parameters of population size

It can be seen that the dynamics of the population are determined by three parameters: *τ* and *р*, are factors of the habitat, but *rin* is an intrinsic characteristic of the population. Each of the factors influences oscillation characteristics. Parameter *τ* is the regeneration time of density-dependent environmental factors. As the environmental pressure is a complex value, then *τ* is also a multifactorial distributed characteristic of the environment (Schley &

(7)

With the delay effect, equation (6) becomes:

oscillations.

$$dN \;/\, dt \; = \; \left( b \; - \; m \right) \\ N \; = \; \left( b\_{in} - m\_{in} \right) \\ N \; - \; \left( a \; + j \right) \\ N^2 \tag{5}$$

Having designated *bin - min = rin* and *a + j = p,* equation (5) can be rewritten as

$$dN \,/\, dt \,\,=\, N\{r\_{in} - pN\}\tag{6}$$

where *rin* is the intrinsic population growth rate (*time -1*), and *р* is the environmental pressure (*time -1N -1*).

The dynamics of any population is complicated by feedback among population size and the environmental pressure. The environmental conditions vary after changes in population size with some time delay. Let, for example, population size grow from *Nmin* at time *t0* to *Neq* at time *t.* At once, as the population size reaches *Neq,* the environmental pressure remains at the level that existed at the moment, *t-.* The time delay,, is the time necessary for the breeding of parasites and predators and a reduction of food resources and vital space per capita. As a result, the population size proceeds to increase to the equilibrium point *Neq*, and reaches the point, *Nmax*> *Neq*. As this state is unstable, the population size is reduced and, for the same reason, passes the *Neq* point and falls to *Nmin*< *Neq*; this is the nature of autooscillations about *Neq* (Macfadien, 1963; May, 1973). Being forced out of the equilibrium condition, a population enters an auto-oscillation regimen and the amplitude of the oscillations can serve as a criterion of population responsiveness to environmental variability.

The increase in the population number leads to a decrease in b and an increase in both m and r relative to their intrinsic values, bin, min, and rin. The slopes of the line depend on the environmental pressure on the birthrate (a) and mortality (j).

Fig. 5. Dependence of birth (b) and death (m) rates and the population growth rate (r) from the population number (N).

where *rin* is the intrinsic population growth rate (*time -1*), and *р* is the environmental pressure

The dynamics of any population is complicated by feedback among population size and the environmental pressure. The environmental conditions vary after changes in population size with some time delay. Let, for example, population size grow from *Nmin* at time *t0* to *Neq* at time *t.* At once, as the population size reaches *Neq,* the environmental pressure remains at

breeding of parasites and predators and a reduction of food resources and vital space per capita. As a result, the population size proceeds to increase to the equilibrium point *Neq*, and reaches the point, *Nmax*> *Neq*. As this state is unstable, the population size is reduced and, for the same reason, passes the *Neq* point and falls to *Nmin*< *Neq*; this is the nature of autooscillations about *Neq* (Macfadien, 1963; May, 1973). Being forced out of the equilibrium condition, a population enters an auto-oscillation regimen and the amplitude of the oscillations

The increase in the population number leads to a decrease in b and an increase in both m and r relative to their intrinsic values, bin, min, and rin. The slopes of the line depend on the environmental pressure on

Fig. 5. Dependence of birth (b) and death (m) rates and the population growth rate (r) from

*.* The time delay,

can serve as a criterion of population responsiveness to environmental variability.

Having designated *bin - min = rin* and *a + j = p,* equation (5) can be rewritten as

(*time -1N -1*).

the level that existed at the moment, *t-*

the birthrate (a) and mortality (j).

the population number (N).

<sup>2</sup> / – – *in in dN dt b m N b m N a j N* (5)

*dN dt N r* / – *in pN* (6)

, is the time necessary for the

With the delay effect, equation (6) becomes:

$$dN\_t \slash dt \ = N\_t (r\_{in} - pN\_{(t-\tau)}) \tag{7}$$

Exes: abscissa is time and the ordinate is the currant population number divided by the equilibrium at time t0 (Nr = Nt/Neq). The consequences of two situations in the environment are modulated (two curves): (1) a favorable coincidence that raises the outbreak of the population number (N0 > Neq= 1.5) and (2) coincidence of severe conditions that causes population depression (N0 < Neq= 0.5). (a) Populations having small values of rin are reduced to the minimal value after outbreaks of numbers (red curve): coincidences of favorable circumstances in the environment threaten the existence of such populations to a greater extent. (b) Populations having large values of rin reach the lowest number after a state of decay (red curve): coincidences of unfavorable circumstances threaten the existence of such populations to a greater extent. (c) There is an optimal rin value under the present environmental pressure when favorable and unfavorable environment cataclysms are followed by an equal aftereffect. The value of Nmin is maximal under this rin; this rin value is maintained by interpopulation selection.

Fig. 6. The influence of the intrinsic population growth rate on parameters of population size oscillations.

It can be seen that the dynamics of the population are determined by three parameters: *τ* and *р*, are factors of the habitat, but *rin* is an intrinsic characteristic of the population. Each of the factors influences oscillation characteristics. Parameter *τ* is the regeneration time of density-dependent environmental factors. As the environmental pressure is a complex value, then *τ* is also a multifactorial distributed characteristic of the environment (Schley &

Bioenergetics Theory of Aging 83

if the environmental pressure is constant, then any population of a species deviating from this value will have a greater extinction risk. As *rin = lnR0/T,* then the length of the generation and the net reproduction rate are stabilized by interpopulation natural selection.

However, in the course of evolution, it can gradually vary during a change of parameters of an ecological niche under influence, for example, changes of climate. The calculated dependence of the stabilized *ŕin* value from *р* shows that variation in environmental pressure causes a change of the stabilized intrinsic population growth rate: the greater the *p* value,

An increase in environmental press in the ecological niche of a species in the course of evolution causes

Thus, the value of the intrinsic rate of population growth is under natural selection control and it is predetermined by environmental pressure within the ecological niche of the species. The conclusion that the intrinsic rate of population growth is stabilized by interpopulation natural selection can be made logically without resorting to mathematical calculations. Population size oscillations are inevitable because of stochastic variations in the environment and are harmful as they increase the extinction risk. The intrinsic rate of the population growth influences population responsiveness to environmental fluctuations. When a population is in a state of size reduction, the maximal *rin* is preferably for oscillation damping. Under these conditions, a decrease in population size in any given half cycle of the oscillation will be minimal as the high rate of breeding serves as a brake for the decrease.

Fig. 8. The dependence of a stabilized intrinsic population growth rate (ŕin) from

growth of the intrinsic population growth rate and vice versa.

environmental pressure (p).

On a long-term temporal scale, the environmental pressure becomes constant.

the greater the *ŕin.*

Gourley, 2000). However, it can be accepted as a discrete characteristic at solving many tasks analogous to our problem (May, 1981; Schley & Gourley, 2000). The numerical solution of equation (7) shows that *τ* influences the amplitude of the population size oscillations: the greater the *τ*, the greater the amplitude of oscillations. Species that are under *τ* < 0.3 have the least variability; perturbed size of its populations monotonously return to the equilibrium state. In the range 0.3 < *τ* < 1.6, an oscillatory return to an equilibrium number occurs. The further *τ* increases cause continuous oscillations. If *τ* > 2.2, then populations become nonviable; the smallest external disturbance provokes increasing oscillations that decrease *Nmin* to nil. It is apparent that within an ecological niche, in the overwhelming majority of vertebrate species the *τ* value is limited by 0.4-1.5. Therefore, we shall accept in further calculations that this parameter of the ecological niche of the abstract species under consideration is equal to 1.

The numerical solution of equation (7) shows that the variation of *rin* influences both the *Neq* value and the amplitude of oscillations that predetermines changes in *Nmin* (Fig. 6). The dependence of *Nmin* from *rin*, calculated with other parameters unchanged (*р = 1; τ = 1),* is shown in Fig. 7. The curve of dependence *Nmin*(*rin*) has a maximum under certain *ŕin*. As mentioned above, the selective pressure is always directed to an increase in *Nmin.* In the case in point, the directions of selective pressure are opposite from larger and smaller *rin* values. Hence, it appears that the intrinsic rate of population growth is stabilized by group selection on the level which corresponds to the maximal *Nmin* value:

Under constant environmental parameters (p = 1; τ = 1) the curve of dependence Nmin(rin) has a maximum under a certain ŕin. As the extinction risk is inversely proportional to Nmin, then selective pressure pushes rin of populations of species to this value.

Fig. 7. Scheme of stabilization of the intrinsic population growth rate by interpopulation selection.

Gourley, 2000). However, it can be accepted as a discrete characteristic at solving many tasks analogous to our problem (May, 1981; Schley & Gourley, 2000). The numerical solution of equation (7) shows that *τ* influences the amplitude of the population size oscillations: the greater the *τ*, the greater the amplitude of oscillations. Species that are under *τ* < 0.3 have the least variability; perturbed size of its populations monotonously return to the equilibrium state. In the range 0.3 < *τ* < 1.6, an oscillatory return to an equilibrium number occurs. The further *τ* increases cause continuous oscillations. If *τ* > 2.2, then populations become nonviable; the smallest external disturbance provokes increasing oscillations that decrease *Nmin* to nil. It is apparent that within an ecological niche, in the overwhelming majority of vertebrate species the *τ* value is limited by 0.4-1.5. Therefore, we shall accept in further calculations that this parameter of the ecological niche of the abstract species under

The numerical solution of equation (7) shows that the variation of *rin* influences both the *Neq* value and the amplitude of oscillations that predetermines changes in *Nmin* (Fig. 6). The dependence of *Nmin* from *rin*, calculated with other parameters unchanged (*р = 1; τ = 1),* is shown in Fig. 7. The curve of dependence *Nmin*(*rin*) has a maximum under certain *ŕin*. As mentioned above, the selective pressure is always directed to an increase in *Nmin.* In the case in point, the directions of selective pressure are opposite from larger and smaller *rin* values. Hence, it appears that the intrinsic rate of population growth is stabilized by group selection

Under constant environmental parameters (p = 1; τ = 1) the curve of dependence Nmin(rin) has a maximum under a certain ŕin. As the extinction risk is inversely proportional to Nmin, then selective

Fig. 7. Scheme of stabilization of the intrinsic population growth rate by interpopulation

pressure pushes rin of populations of species to this value.

selection.

consideration is equal to 1.

on the level which corresponds to the maximal *Nmin* value:

if the environmental pressure is constant, then any population of a species deviating from this value will have a greater extinction risk. As *rin = lnR0/T,* then the length of the generation and the net reproduction rate are stabilized by interpopulation natural selection. On a long-term temporal scale, the environmental pressure becomes constant.

However, in the course of evolution, it can gradually vary during a change of parameters of an ecological niche under influence, for example, changes of climate. The calculated dependence of the stabilized *ŕin* value from *р* shows that variation in environmental pressure causes a change of the stabilized intrinsic population growth rate: the greater the *p* value, the greater the *ŕin.*

An increase in environmental press in the ecological niche of a species in the course of evolution causes growth of the intrinsic population growth rate and vice versa.

Fig. 8. The dependence of a stabilized intrinsic population growth rate (ŕin) from environmental pressure (p).

Thus, the value of the intrinsic rate of population growth is under natural selection control and it is predetermined by environmental pressure within the ecological niche of the species. The conclusion that the intrinsic rate of population growth is stabilized by interpopulation natural selection can be made logically without resorting to mathematical calculations. Population size oscillations are inevitable because of stochastic variations in the environment and are harmful as they increase the extinction risk. The intrinsic rate of the population growth influences population responsiveness to environmental fluctuations. When a population is in a state of size reduction, the maximal *rin* is preferably for oscillation damping. Under these conditions, a decrease in population size in any given half cycle of the oscillation will be minimal as the high rate of breeding serves as a brake for the decrease.

Bioenergetics Theory of Aging 85

initial population size and *NT* is the population size one generation later. It is apparent that

Thus, longevity and fertility are actually under the control of interpopulation natural selection. The selective pressure acts on both components of *rin* simultaneously, but the distribution of forces are unequal for different species because of environmental factor specificity. As a result, only a correlation between longevity and fertility exist in nature. This evolution mechanism of longevity is apparently applicable only for vertebrata. Invertebrates, by virtue of their huge variety, can have others, and various, evolution

According to the above considerations, the mechanism of programmed aging is represented as follows (Fig. 10): the genetic program controls the only function – bioenergetics decline. The latter causes the increase in the ROS level, a lowering of the protein synthesis rate, the cessation of cells dividing and some other processes; every one of them in turn spawns a number of secondary harmful processes. As the number of cells dividing (proliferative time) increases, these destructive phenomena in an organism's tissues augment progressively,

The genetic program decreases the bioenergetics level as the number of cell divisions augments. This results in the increase in the ROS level, the lowering of the protein synthesis rate, the cessation of cells dividing and some other injurious processes. In turn, each one of them spawns a number of secondary harmful processes which leads to a decrease in all of the physiological functions of an organism, i.e. aging.

Fig. 10. Scheme of the bioenergetics mechanism of aging.

if *R0* is increasing in evolution, the fertility is growing, and vice versa.

mechanisms determine species specific longevity.

which gradually leads to the organism's destruction.

**6. The mechanism of aging** 

But, such *rin* values will become threatening when the opposite phase begins as it intensifies the increase in population size. According to the theory of risk spread, the greater the extension of a population on top, the deeper it falls in foot. The same intensification of amplitudes is provoked by an inverse extreme value of the intrinsic population growth rate. A natural population cannot have such an extreme or any arbitrary of rin value. There is an optimal value of the intrinsic rate of population growth which ensures minimal possible population oscillation (Fig. 6). That value is sustained by interpopulation natural selection because deflection of the rin to any side from the value increases the population extinction risk; the above-stated mathematical calculations alone have demonstrated this.

Let's look now what in fact is hidden behind the intrinsic population growth rate. According to equation (1), these are two population characteristics: 1) the net reproduction rate and 2) the length of the generation, neither of which can be programmed by the genome directly. In a general sense, the length of the generation is the time from which the individuals are born to the time most offspring, on average, are produced for a population. The concept of "postreproductive age" is applicable to the full only to post-industrial man and his/her pets. Animals of post-reproductive age are rare in natural habitats (Medawar, 1952). Analyses of cohort life tables of natural populations show that the length of the generation is actually equal to the mean survival of the population age-groups. Thus the average longevity in the habitat is under natural selection control.

Fig. 9. Dependence of longevity (T) on environmental pressure in the ecological niche of a species.

The variation in the net reproduction rate corresponds to the variation in fertility of the population members. To understand it, we should recollect that *R0= NT/N0,* where *N0* is the

But, such *rin* values will become threatening when the opposite phase begins as it intensifies the increase in population size. According to the theory of risk spread, the greater the extension of a population on top, the deeper it falls in foot. The same intensification of amplitudes is provoked by an inverse extreme value of the intrinsic population growth rate. A natural population cannot have such an extreme or any arbitrary of rin value. There is an optimal value of the intrinsic rate of population growth which ensures minimal possible population oscillation (Fig. 6). That value is sustained by interpopulation natural selection because deflection of the rin to any side from the value increases the population extinction

Let's look now what in fact is hidden behind the intrinsic population growth rate. According to equation (1), these are two population characteristics: 1) the net reproduction rate and 2) the length of the generation, neither of which can be programmed by the genome directly. In a general sense, the length of the generation is the time from which the individuals are born to the time most offspring, on average, are produced for a population. The concept of "postreproductive age" is applicable to the full only to post-industrial man and his/her pets. Animals of post-reproductive age are rare in natural habitats (Medawar, 1952). Analyses of cohort life tables of natural populations show that the length of the generation is actually equal to the mean survival of the population age-groups. Thus the average longevity in the

The increase in environmental pressure in a species ecological niche results in a longevity decrease. Fig. 9. Dependence of longevity (T) on environmental pressure in the ecological niche of a

The variation in the net reproduction rate corresponds to the variation in fertility of the population members. To understand it, we should recollect that *R0= NT/N0,* where *N0* is the

risk; the above-stated mathematical calculations alone have demonstrated this.

habitat is under natural selection control.

species.

initial population size and *NT* is the population size one generation later. It is apparent that if *R0* is increasing in evolution, the fertility is growing, and vice versa.

Thus, longevity and fertility are actually under the control of interpopulation natural selection. The selective pressure acts on both components of *rin* simultaneously, but the distribution of forces are unequal for different species because of environmental factor specificity. As a result, only a correlation between longevity and fertility exist in nature. This evolution mechanism of longevity is apparently applicable only for vertebrata. Invertebrates, by virtue of their huge variety, can have others, and various, evolution mechanisms determine species specific longevity.
