TESTING THE EFFECT OF LIFE ON EARTH’S FUNCTIONING:
HOW GAIAN IS THE EARTH SYSTEM?
AXEL KLEIDON
Department of Geography, 2181 Lefrak Hall, University of Maryland, College Park,
MD 20742, U.S.A.
E-mail: [email protected]
Abstract. The Gaia hypothesis of Lovelock states that life regulates Earth’s functioning for its own
benefit, maintaining habitable, or even optimum conditions for life. But what is beneficial? What
is good for one species, may be bad for another. Problems associated with this important, but illdefined hypothesis make it difficult to test. In order to address these problems and make the concept
of Gaia testable, I give a precise definition of terms. Based on these definitions, I put forward four
null hypotheses, describing increasing beneficial effects of life on the conditions of Earth, ranging
from an ‘Antigaian’ to an ‘optimising Gaian’ null hypothesis. I list some indications for rejection of
all but one hypothesis, and conclude that life has indeed a strong tendency to affect Earth in a way
which enhances the overall benefit (that is, carbon uptake). However, this does not imply that the
biota regulates Earth’s environment for its own benefit.
1. Defining Gaia
The notion that life affects its environment, and hence Earth functioning, is long
known (see e.g., Kirchner, 1989, and references therein). There is plenty of evidence from various disciplines for this notion. An obvious example for biotic
effects on Earth are land surface properties. For instance, the reflectivity or albedo
of a land surface is generally lower when it is vegetated. In simple terms, a surface
covered by rainforest is darker than a desert. The reflectivity determines net absorbed solar radiation, thus affecting the surface energy balance with consequences
for the physical functioning of the atmosphere. Also, the chemical composition of
the atmosphere clearly reflects biotic activity, as for instance noted by Lovelock
and Margulis (1974). But are these effects beneficial for life?
About 30 years ago, Lovelock formulated the original version of the Gaia hypothesis (Lovelock and Margulis, 1974) in which he states that the biotic Earth can
be seen as an active adaptive control system, exhibiting atmospheric homeostasis
by and for the biosphere. Since then, this hypothesis has received much attention
(see e.g., Schneider and Boston, 1991; Lenton, 1998, and references therein) and
has been revised a couple of times (see e.g., Lovelock 1989). However, one of the
main obstacles is that this hypothesis is difficult to test (Schneider, 1987; Kirchner, 1989). In order to make Gaia testable by scientific methods, a precise and
unambiguous definition of terms is necessary. Gaia states that life regulates the enClimatic Change 52: 383–389, 2002.
© 2002 Kluwer Academic Publishers. Printed in the Netherlands.
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vironment for its own benefit. But what is this benefit and how can it be measured?
All these definitions are crucial for putting forward Gaian null hypotheses which
can then be tested and rejected. The aim of this paper is to provide such definitions
and to set up testable null hypotheses.
I start by defining a measure for how beneficial environmental conditions are
for life. Since carbon is the basic building block of life on Earth, it makes sense to
base this definition on carbon fluxes (see also Volk, 1998). I therefore define the
benefit of environmental conditions for life by their effect on the long-term mean
global gross uptake of carbon by the biota (global gross primary productivity, or
GPP). This definition is not based on what is ‘good’ for one particular species,
but rather on what is ‘good’ for the whole global biota, or ‘life’. The choice of
this globally integrated flux reflects the attempt of Gaia to describe planetaryscale effects of life. With this definition, environmental conditions which are more
favorable to life or enhance life are those that lead to a higher value of GPP. Optimum living conditions then translate into environmental conditions which lead to
a maximum value of GPP. Note that alternative definitions of ‘benefit’ would also
seem appropriate, e.g., biomass, diversity (see e.g., Schneider, 1987) or entropy
(Schrödinger, 1944). However, most biospheric attributes are generally linked to
the environment in similar ways. For instance, the ‘beneficial’ climate of a tropical
rainforest yields high values of local carbon uptake, but is generally also associated
with high biomass and diversity. It would therefore seem that the overall outcome
would not substantially be affected by the particular choice of ‘benefit’ (this would,
however, require further investigation).
Based on these definitions, I propose the following null hypotheses, which reflect an increasing importance of biotic effects for life in the Earth system, that
is, an increasing biotic effect on environmental conditions which constrain GPP.
I put these hypotheses into precise equations, using the notations EA for the environment of Earth without biotic effects (an ‘abiotic’ environment), EB for the
actual, biotic, environment on Earth and EO for the environment optimal to life.
Note that while GPP depends on a multitude of variables, such as temperature,
moisture availability, radiation, and nutrients, I represent ‘the environment’ by one
lumped variable E for simplicity. The actual magnitude of GPP also depends on
the efficiency of carbon uptake, which in turn depends on evolution. However, the
following hypotheses are not based on the actual value of GPP, but on the difference between GPP(EB ) and GPP(EA ) at a given time, therefore being independent
of the efficiency of carbon uptake and evolution.
The null hypotheses are:
I. ‘Antigaia’: Biotic effects worsen environmental conditions, thus leading
to lower GPP. In mathematical terms, this is equivalent to GPP(EB ) <
GPP(EA ).
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Figure 1. Schematic illustrations of the null hypotheses proposed to test Gaia. The benefit of Earth’s
environment on life is measured by the global gross carbon uptake GPP. Diagram (I) represents an
‘Antigaian’ null hypothesis: life worsens environmental conditions. Diagram (II) represents a ‘No
Gaian’ null hypothesis: there may be biotic effects, but their sum does not make environmental conditions consistently better or worse. Diagram (III) represents an ‘Enhancing Gaian’ null hypothesis:
the net of all biotic effects enhance environmental conditions, leading to higher GPP, but not to
the maximum possible GPP. Diagram (IV) represents an ‘Optimising Gaian’ null hypothesis: biotic
effects lead to optimum environmental conditions for life, leading to a maximum possible GPP.
II. ‘No Gaia’: There may be biotic effects on environmental conditions, but
their total effect does not decrease or increase GPP. In mathematical terms,
this is equivalent to GPP(EB ) = GPP(EA ).
III. ‘Enhancing Gaia’: Biotic effects enhance environmental conditions, thus
leading to higher GPP, but not to maximum GPP. In mathematical terms,
this is equivalent to GPP(EB ) > GPP(EA ) and GPP(EB ) < GPP(EO ).
IV. ‘Optimising Gaia’: Biotic effects enhance environmental conditions to
such an extent that they are optimal for life, resulting in maximum GPP.
In mathematical terms, this is equivalent to GPP(EB ) > GPP(EA ) and
GPP(EB ) = GPP(EO ).
These null hypotheses are illustrated schematically in Figure 1. With these four
precise definitions of the null hypotheses, I continue by listing some indications for
rejection of all but one of these hypotheses.
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2. Testing Gaian Null Hypotheses
As mentioned above, life has noticable effects on the environment, e.g., on the
atmospheric composition and land surface characteristics. But do these effects
necessarily affect the environment in a consistent way, that is, do biotic effects
decrease or increase GPP?
I first discuss the biogeophysical effects of vegetation using the results from
climate model simulations which provide means for rejection of null hypotheses (I)
and (II). In this discussion I will focus on terrestrial vegetation because marine life
does not have a strong effect on the biogeophysical conditions of its environment.
With vegetation, there is a general trend towards higher absorption of solar radiation and enhanced evapotranspiration, leading to enhanced moisture recycling over
land. There are two studies which have quantified the total biogeophysical effect of
vegetation on climate using atmospheric General Circulation Models (Betts, 1999;
Fraedrich et al., 1999; Kleidon et al., 2000). In these studies, the authors conducted
a simulation of an abiotic, ‘Desert World’, in which the effects of present-day vegetation were removed. As a response to vegetation removal, the climate of a ‘Desert
World’ is drier with less continental moisture recycling (Figure 2), enhancing the
spatial and temporal extent of water limitation for the productivity of vegetation.
This means that the biogeophysical effect of vegetation on climate acts to reduce
water stress and enlarge the spatial extent where vegetation can exist, therefore
leading to a higher GPP. I estimated this increase in GPP from the sum of absorbed
solar radiation at the surface, reduced by the simulated water stress factor which is
used for the calculation of evapotranspiration in the model. With more than 250%
of the ‘Desert World’s’ value, GPP is substantially increased for the present-day
climate, that is, for a climate with the effect of life. Of course, this approximate
calculation of actual GPP only considers the biogeophysical limitations of light
and water, and only terrestrial vegetation.
Additional indications for rejection of null hypotheses (I) and (II) comes from
the rate at which essential nutrients are cycled within the accessible part of the
biota, or ‘cycling ratios’ (Volk, 1998). Volk showed that life generally enhances the
cycling of nutrients, thus reducing limitations of productivity by nutrients, leading
to a generally higher GPP. For example, phosphorus is an often limiting nutrient
for land plants for which rock weathering is the only abiotic source. With the effect
of the biota, the cycling rate of phosphorus through the biosphere is 46 times the
rate of rock weathering (Volk, 1998), thus substantially reducing the limiting effect
of this essential nutrient. Put into other words, the effect of life on phosphorus
cycling roughly increases GPP by an equivalent magnitude. This enhancement of
‘cycling ratios’ is closely connected with the enhancement of GPP and can be seen
for both, terrestrial and marine biota.
Both examples, the ‘Desert World’ climate simulations and the ‘cycling ratios’,
demonstrate that biotic effects strongly enhance the biogeophysical and biogeochemical conditions for life, leading to a substantially higher GPP. Therefore, these
two examples suggest the rejection of null hypotheses (I) and (II).
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Figure 2. Magnitude of the biogeophysical effects of vegetation on the terrestrial water cycle as a
means to reject null hypotheses I and II. Shown is the simulated mean terrestrial water cycle of three
climate model simulations: an abiotic, ‘Desert World’ (left), in which land surface characteristics are
set to ones representative of a desert, a ‘Present-Day’ situation (middle), and a ‘Green Planet’, where
all land areas are represented by forest characteristics. Arrows denote precipitation (downward) and
evapotranspiration (upward) and values are given in 1012 m3 /yr. Top boxes denote mean precipitable
water (or total atmospheric water vapor content) in kg/m2 . Taken from Fraedich et al. (1999), Kleidon
et al. (2000) and Roeckner et al. (1996).
At the same time, both examples support null hypothesis (III), so that (III)
cannot easily be rejected. However, there is some indication for rejection of null hypothesis (IV) from the study of Fraedrich et al. (1999) and Kleidon et al. (2000). A
climate model simulation of a ‘Green Planet’ quantified the maximum biogeophysical effect that vegetation can have on climate. This climate is considerably wetter
with land precipitation roughly 30% higher than for the ‘Present-Day’ simulation
(Figure 2). This climate can be seen as closer to optimum conditions with respect
to climate since it is the one with the least amount and spatial extent of water limitation. However, while GPP is only enhanced by 5%, this climate is quite different
from the present-day. Note that this increase in GPP may not lead to the maximum
possible value of GPP because imposing forest-like land surface parameters in
semiarid and arid regions in the ‘Green Planet’ simulation substantially reduced
the growing period length by enhancing the efficiency of evapotranspiration. The
variation of some land surface parameters may lead to higher values of GPP. This
was for instance reported for sensitivity simulations in respect to rooting depth
(Kleidon and Heimann, 1998). Nevertheless, while vegetation enhances water recycling over land, as noted above, it does not seem to achieve the maximum effect
on climate, suggesting that the biotic effects on the environment do not produce
optimum conditions. Therefore, the example of a ‘Green Planet’ seems to provide
means for rejection of null hypothesis (IV), but further investigations would be
needed to support this rejection.
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3. Conclusion
This straightforward definition and compilation of evidence suggests the rejection
of all null hypotheses except (III). With (I) and (II) easily being dismissed, the real
Earth should act according to (III), but it remains to be determined how close to
either (II) or (IV). The fact that the simulated present-day value of GPP is close to
the value of the ‘Green Planet’ and the profound effects on biogeochemical cycles
suggest that real Earth operates closer to (IV). In other words, life has a strong
tendency to affect its environment in a way which enhances the overall benefit (i.e.,
GPP(EB ) > GPP(EA )) at fixed external forcing. Life-enhancing effects outweigh
the life-destructing ones, leading to a net benefit of increasing carbon uptake. This
life enhancing tendency seems plausible and can be understood as an emergent
property of evolution since life-enhancing effects would be favoured by natural
selection (Lenton, 1998). However, no temporal effects are considered in the definitions of terms and null hyptheses given here. The rejection of null hypotheses
proposed here only suggests that environmental conditions with biotic effects lead
to a higher GPP than without biotic effects at fixed external forcing. In respect to
life’s response to changes in external forcing, it would seem that during periods of
change, e.g., glacial cycles, life will adjust and tend again to enhance environmental
conditions (i.e., biotic feedbacks will enhance environmental conditions for GPP),
reaching a new steady state with the abiotic components of Earth. Note that this
notion does not imply homeostatic behaviour.
Hopefully, this work will stimulate further research and discussions in which
explicit definitions of what is beneficial to life are given and null hypotheses are
tested to yield a consistent picture about the effect, and the importance of life’s role
in Earth system functioning.
Acknowledgements
The ideas for this paper were stimulated by the second AGU Chapman conference
on the Gaia hypothesis, held in Valencia, Spain, from June 19 to June 23, 2000.
The author would like to acknowledge the financial support from the American
Geophysical Union (AGU) for attending the conference and the Alexander-vonHumboldt Foundation for a Feodor Lynen Fellowship. The author thanks Stephen
Schneider for his encouragement and James Kirchner, Tim Lenton, and Tyler Volk
for their stimulating and constructive criticisms.
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(Received 12 October 2000; in revised form 25 July 2001)