the temperature dependence of soil organic matter ... - Science Direct

Soil Bid. Biochem. Vol. 27. No. 6, pp. 753-760, 1995

Elsevier Science Ltd. Printed in Great Britain

Pergamon

0038-0717(94)00242-8

THE TEMPERATURE DEPENDENCE OF SOIL ORGANIC MATTER DECOMPOSITION, AND THE EFFECT OF GLOBAL WARMING ON SOIL ORGANIC C STORAGE MIKO U. F. KIRSCHBAUM Division

of Forestry,

CSIRO,

PO Box 4008, Queen Victoria

Terrace,

Canberra,

ACT 2600, Australia

(Accepted 14 October 1994) Sunnnary--One of the key questions in climate change research relates to the future dynamics of the large amount of C that is currently stored in soil organic matter. Will the amount of C in this pool increase or decrease with global warming? The future trend in amounts of soil organic C will depend on the relative temperature sensitivities of net primary productivity and soil organic matter decomposition rate. Equations for the temperature dependence of net primary productivity have been widely used, but the temperature dependence of decomposition rate is less clear. The literature was surveyed to obtain the temperature dependencies of soil respiration and N dynamics reported in different studies. Only laboratory-based measurements were used to avoid confounding effects with differences in litter input rates, litter quality, soil moisture or other environmental factors. A considerable range of values has been reported, with the greatest relative sensitivity of decomposition processes to temperature having been observed at low temperatures. A relationship fitted to the literature data indicated that the rate of decomposition increases with temperature at 0°C with a QM of almost 8. The temperature sensitivity of organic matter decomposition decreases with increasing temperature, indicated by the Q10 decreasing with temperature to be about 4.5 at 10°C and 2.5 at 20°C. At low temperatures, the temperature sensitivity of decomposition was consequently much greater than the temperature sensitivity of net primary productivity, whereas the temperature sensitivities became more similar at higher temperatures. The much higher temperature sensitivity of decomposition than for net primary productivity has important implications for the store of soil organic C in the soil. The data suggest that a 1°C increase in temperature could ultimately lead to a loss of over 10% of soil organic C in regions of th’: world with an annual mean temperature of 5°C whereas the same temperature increase would lead to a loss of only 3% of soil organic C for a soil at 30°C. These differences are even greater in absolute amounts as (cooler soils contain greater amounts of soil organic C. This analysis supports the conclusion of previous r.tudies which indicated that soil organic C contents may decrease greatly with global warming and thereby provide a positive feed-back in the global C cycle.

Hence, it seems likely that soil organic C will decrease with increasing temperature due to climate change (e.g. Shaver et al. 1992). This knowledge has been incorporated by Schimel et al. (1990), Jenkinson et al. (1991) Thornley et al. (1991) and Kirschbaum (1993) who used soil organic matter models to show how a future temperature increase could lead to the release of large quantities of C from the world’s soils. Gifford (1992) on the other hand, conducted a similar analysis, but concluded that there should be no loss of C with increasing temperature. However, the most critical factor in all these analyses is the relativity between the temperature response functions of net primary productivity and soil organic matter decomposition. There is a general expectation that increasing temperature leads to increases in both net primary productivity which provides the input to soil organic C, and the rate of soil organic matter decomposition which determines the loss of soil organic C. The critical question is whether net primary productivity or organic matter decomposition rate is stimulated more by increasing temperature.

INTRODUCTION

Global temperatures have increased by about 0.5”C over the past century (Folland et al., 1990). With the continuing increase in Greenhouse gases in the atmosphere, temperature increases are expected to continue and become even more pronounced. The question arises whether this will lead to a loss or increase in soil otganic C. If it leads to a decrease in soil organic C, tha.t C would have to be oxidized to C02, which would further add to the amount already in the atmosphere, thus providing a positive feed-back effect in climate ch,ange. There are strong correlations between soil C pools and climate. An extensive analysis of soil C storage in different soils was clone by Post et al. (1982) which was followed by a similar analysis of amounts of N stored in soils (Post et al., 1985). In these analyses, amounts of soil organic C and N were found to be positively correlated with precipitation, and negatively correlated with temperature at any particular amount of precipitation. Similarly, Jenny (1980) has shown similar trends along temperature gradients in both American and Indian soils. saa 27,6El

753

Miko U. F. Kirschbaum

154

Temperature often expressed

responses of biological as a Q10 function Qlo = (~2//#Wz

- rdl

systems

are

(1)

where k2 and k, are the rate constants for a process of interest at two observed temperatures, T2 and T,. A Q,,, of 2, for example, means that the rate of a particular process would occur twice as fast at 15°C as at 5°C. While this relationship is easy to use and provides a ready indication of the temperature sensitivity of any system, it lacks a theoretical justification (Johnson and Thornley, 1985). Other relationships, such as the Arrhenius function, have been used (e.g. Ellert and Bettany, 1992) to provide a better theoretical framework. It is unclear, however, whether it is useful to look for a theoretical basis in a system as complex as a community of soil organisms, where the total activity is determined by the combined activity of a whole range of different organisms that presumably have quite different individual responses to temperature. In the absence of a useful theoretical model, the use of Q10 values is a convenient tool to summarize observed responses. Raich and Schlesinger (1992) estimated the temperature dependence of decomposition rate from measurements of CO, efflux from soils in different regions. They compiled soil respiration measurements from a comprehensive range of ecosystems and expressed observed values as a function of their annual mean temperature. However, measured soil respiration includes both root respiration and COZ efflux from decomposer organisms. Root respiration may have a different temperature sensitivity than organic matter decomposition so that the temperature sensitivity of soil respiration may differ from that of organic matter decomposition. Moreover, for any system in the steady state, soil respiration rate averaged over a year or more must be equal to the rate of C input to the soil over that period, and thereby likely to be proportional to net primary productivity. Consistent with that view, Raich and Schlesinger (1992) showed a good linear correlation between annual soil respiration rate and net primary productivity. Their analysis can therefore not give us the necessary information as to whether the temperature dependence of decomposition is in fact greater or less than the temperature dependence of net primary productivity, and whether, due to global warming, soil respiration might temporarily exceed C input until a new steady state is re-established. Another way of obtaining the temperature dependence of decomposition is by measuring soil respiration throughout a year, and expressing rates as a function of seasonally-fluctuating temperatures (e.g. Anderson, 1973; Schlentner and Van Cleve, 1985; Carlyle and Than, 1988; Naganawa et al., 1989; Lloyd and Taylor, 1994). However, soil respiration is strongly affected by soil moisture and litter quality in addition to temperature. These factors are almost

invariably confounded with temperature so that they bias the estimate of the temperature dependence of decomposition. Ecosystems affected by summer droughts, for example, would have lower values in summer than would be expected on the basis of temperature alone (e.g. see Naganawa et al., 1989). Hence, the apparent temperature sensitivity in such systems would tend to be underestimated. In deciduous forest systems, or grasslands that die off in autumn, the estimation of temperature dependence is confounded with litter quantity and quality, as large amounts of the most readily decomposable litter material become available at a cool time of the year. The high-quality substrate thereby allows higher respiration rates in the cool time of the year than would be expected on the basis of temperature alone. Hence, the temperature dependence of decomposition rates would be underestimated. Analyses of the temperature dependence of decomposition rates that are based on seasonal comparisons of soil respiration must therefore be treated with great caution. To obtain an estimate of the temperature dependence of decomposition rate without the confounding effects discussed above, I therefore restricted myself to using values obtained under controlled conditions where water limitations could be avoided and where samples at all temperatures relied on the same substrate.

DATA MANIPULATION

Literature values were compiled from studies where the temperature dependence of soil or litter respiration, N mineralization or denitrification was obtained under controlled laboratory conditions. For each study, I took the mean temperature at which measurements were taken and either took or calculated the Q10for that temperature range. A letter in Figs 1 and 2 then refers to the reference, the mean temperature between two measurements and the Q,,, calculated from the rates at these temperatures. A summary of literature sources is given in Table 1. The table also notes the type of measurement done in each study and the mean temperatures derived for each study as outlined above. In all cases, I calculated a single mean Q10 for each temperature rather than including all individual data presented in a particular study. This was done to avoid giving greater significance to those studies where a greater number of individual samples were analysed. Further details of the manipulations done to individual data sets were as follows. Data for Bunt and Rovira (19.55) Drobnik (1962), Moureaux (1967) and Waksman and Gerretsen (1931) were taken from Nyhan (1976). They all measured CO? evolution rates from soils at different temperatures. Data were expressed by Nyhan (1976) as Q10values at different temperatures. I obtained Q,,, values and corresponding temperatures from Nyhan’s Fig. 1.

755

Soil organic matter decomposition Data source

Table 1. Source details of the data shown in Figs 1 and 2 Measurement

Figure l-CO2 evolution A: Bunt and Rovira (1955) B: Drobnik (1962) C: Flanagan and Veum (1974) D: Koepf (1953) E: Moureaux (1967) F: Nyhan (1976) G: O’Connell (1990) H: Ross and Cairns (1978) I: Schleser (1982) J: Waksman and Gerretsen (1931) K: Wiant (1967)

Soil CO1 e!Xux Soil CO2 efflux Litter CO2 efIIux Soil CO2 efflux Soil CO2 efflux Soil CO> efflux Litter CO2 elllux Soil CO* efflux Soil CO, efflux Soil CO2 efflux Soil CO* efflux

Figure 2-N dynamics L: Addiscott (1983) M: Campbell er al. (1981) N: Ellert and Bettany (1992) 0: Foster (1989) P: Goncalves and Carlyle (1994) Q: Kladivko and Keeney (1987) R: Malhi et al. (1990) S: Stanford et al. (1973) T: Theodorou and Bowen (1983)

N-mineralization N-mineralization N-mineralization N-mineralization N-mineralization N-mineralization Dentrification N-mineralization N-mineralization

Flanagan and Ve urn ( 1974) measured COZ evolution rates from litter at a range of temperatures from - 7 to + 35°C. These data were given in a figure. I read data from the figure, and calculated Q10 values from that over 5°C intervals from 0 to 20°C. Data for higher tempertures were not used for these tundra samples. Koepf (1953) measured CO2 evolution rates from soil at four different temperatures after the soil had been conditioned at three different temperatures for 7 days. I calculated Q10 values from the rate constants that were given and took the average of Q10 values obtained for the three conditioning treatments. Nyhan (1976) mieasured COr evolution rates from plant material incubated in a soil. COZ evolution was measured as %C loss of “C-labelled plant material. Measurements were done at four temperatures and three water stress treatments. I read data from a graph, calculated Qr,, values separately for each water treatment and then averaged them over all water treatments. O’Connell (1990) measured CO, evolution rates from two types of eucalypt litters and fitted equations to the data. I applied his equations at the temperatures at which measurements were taken, calculated Q10 values from the derived data and took the average of QrO values obtained for the two litter types. Ross and Cairns (1978) measured COZ evolution rates from nine different soils in 2 years. Some soils were only used once, and they had a total of 14 independent samples. They took measurements at several different temperatures and calculated Q10 values for each soil separately. I calculated mean Q10 values from their 14 individual data points at temperature range:s S-10, l&20 and 15-25°C and from five data points over the range 20-30°C. Schleser (1982) measured COZ evolution rates from different soils. Q10 values were calculated and expressed as a function of temperature. I read those

Temperatures

(“C)

15, 23, 34 12.5, 23, 33 2.5. 7.5. 12.5. 17.5 15,‘25, 3j 18, 33 6.5, 17.5, 32.5 4, 7, 12, 20, 23, 31, 35 10, 15, 20, 25 4, 4.5, 5, 10, 11, 12, 15, 16, 25 5, 18, 33 25, 33 7.5, 10, 12.5, 20, 22.5 15, 25, 35 10, 20, 27.5 15. 25 7.5, 12.5,‘17.5, 22.5 12.5, 17.5, 22.5, 27.5 0, 7, 15, 30 10, 20, 30 7.5, 12.5, 17.5, 22.5

data from a graph. Only data obtained on samples with multiple replicates were used. Wiant (1967) measured CO* evolution rates from soil under four different tree species. I read values from a graph, calculated Q10 values over the measured temperature ranges and then took the average of values for the soils under the four species. Addiscott (1983) measured N accumulation rates due to N mineralization in three soils at different temperatures. I calculated Q10 values from the rates given at different temperatures. Where data were available for more than one soil type over a given temperature range, I calculated the average of the calculated Q10 values. Campbell et al. (1981) measured N mineralization rates for five different soil types at two different depths. They calculated Q,,, values for three different temperature ranges and presented data as averages for all soil types, but separately for the soil depths. I took the average of data for the two soil depths. Ellert and Bettany (1992) measured N mineralization rates in the forest floor. Q10values were given by the authors for three temperature ranges. Foster (1989) measured N mineralization rates in one soil at different temperatures. Results were expressed after different incubation periods. I used the three highest values that were reported, averaged those, and used them to calculate Q,,, values for different temperature ranges. Goncalves and Carlyle (1994) measured N mineralization rates in a soil collected from a Pinus radiata plantation. The soil was incubated in a factorial experiment at six water contents and five temperatures. I only used data for soils incubated at water contents above 20% of field capacity. I read data for the four remaining water treatments from a graph, calculated Q10values separately for each water treatment between the temperatures at which data were obtained, and then took the mean of the values.

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Kladivko and Keeney (1987) measured N mineralization rates in two different soils, with different water potentials and at five different temperatures. They analysed their data with reference to Arrhenius functions, and reported that activation energies were constant from 10 to 30°C and the same for all water treatments. So, I calculated Qlo values based on their given activation energies for the periods over which they had conducted measurements. Malhi er al. (1990) measured denitrification rates in three different soils at six temperatures from -4 to 60°C. I calculated Q10values for each range and then calculated average Q10values from the different values for the three soils. Stanford et al. (1973) calculated N mineralization rates for 11 different soils and gave rates for each soil at four different temperatures. I calculated Q10values separately for each soil and then took the mean of values for the different soils. Theodorou and Bowen (1983) measured N mineralization rates in a soil collected from a Pinus radiata plantation. The soil was incubated at five temperatures and six water potentials. Only the four moister treatments were used. I read mineralization rates from a graph, calculated Q,,, values independently for each water treatment and then took the mean of the four values. O’Connell (1990) presented a useful equation to describe the temperature dependence of biological processes like soil respiration or mineralization rates. It is of the general form: k = exp[a + flT(l - 0.5T/T,,,],

(2)

where k is the rate constant of the process to be described, Tis temperature in “C, tl and Bare constants and To,, is the optimum temperature for the process. In this equation, c(determines the absolute rate of the process and p in conjunction with To,, its temperature dependence. By combining equations (1) and (2) one can obtain an expression for the Q10in terms of the parameters in equation (2):

Qlo=

exp[ W(l- 2)],

(3)

with the same parameters as in equation (2). I fitted that equation to the data shown in Figs 1 and 2. As the data only describe the temperature dependence of soils processes, they could give no guidance as to the value of c(, which was therefore chosen in such a way to give relative rate processes that reach a maximum of 1 at the optimal temperature. The parameters fitted to the data are given in equations (4) and (5). RESULTS

A summary of values for the temperature dependence of organic matter decomposition (CO2 evolution) rate obtained from the literature is shown

0

‘I

0

I

I

I

5

10

16

I

20

Temperature

I

I

26

30

1

I

36

(“C)

Fig. 1.The Q~oof CO2 efflux from soil or litter as a function of temperature and a relationship fitted to the data. Shown are experimental data, indicated by different letters. Each letter refers to data from a different literature source as shown in Table 1. Some of the data were slightly offset from their true position to allow identification of individual letters. All data are shown in their correct position in Fig. 3. One data point at 4°C had a QMof 12.9, referred to by an arrow in the figure. Equation (3) was fitted to the data, with parameters given in equation (4) (n = 43; r2 = 0.500).

data for N dynamics are shown in Fig 2. Figure 1 shows that Q,,, values for soil COZ efflux are not constant, but much greater values are reported at lower than higher temperatures. Rate constants for soil or litter COZ efflux are, of course, highest at high temperatures, but the relative rate of increase of the rate constants with temperatures is greatest at low temperatures. The figure indicates that Q10values are generally around 2 for temperatures above 20°C but increase at lower temperatures to some very high values. Equation (3) was fitted to the data in Fig. 1, and the fitted parameters gave the following rate equation: in Fig 1. The corresponding

k = exp[ - 3.764 + 0.204T(l - OST/36.9)].

(4)

There is considerable scatter in the data, part of which may be due to measurement error. Researchers who have compared the temperature responses in different systems, such as different soil types, different soil horizons or different litter types, also generally report differences in the temperature sensitivities of different systems. Ross and Cairns (1978), for example, collected 14 different samples for their measurements at 5 and 15°C. The mean Q10for those was 5.15, but individual values ranged from 2.9 to 9.3. This may reflect different inherent temperature sensitivities in their different soils. Measurement error may have further contributed as samples from the same sites also gave different values when measured in different years. Figure 2 shows the temperature dependence of N dynamics (mineralization rates and one data set of denitrification rates; see Table 1). The data for N

Soil organic matter decomposition dynamics appeared to have overall lower temperature sensitivities and h.ad less increase in temperature sensitivity at low temperature than the data for COZ efflux. However, the degree of scatter in the data means that one cannot say with confidence that the two processes have different inherent temperature sensitivities. When equation (3) was fitted to all data for both CO2 evolution and N dynamics, it lead to a choice of parameters with which the rate equation for all data became:

10

(5)

0

, Jmkhon

1

t 0

a’

-

0

6

10

16

20

Temperature

26

30

36

(T)

Fig. 2. The QMof net N mineralization or denitrification rates as a function of temperature. Shown are experimental data, indicated by different letters. Each letter refers to data from a different literature source as shown in Table 1. Some of the data were slightly offset from their true position to allow identification of indrvidual letters. All data are shown in their correct position in Fig. 3. The curve is the same as the curve fitted to the data in Fig. 1.

oL[

:

0

a’

0

I

I

I

6

10

16

Temperature where k,,, is the cclmbined rate constant for all soils processes. The goodness of fit was only very marginally affected by the choice of Tort.Therefore, the same value (36.9) that was obtained from the fit to the soil respiration data [equation (4)] was retained for the fit to all the data. Figure 3 compares the temperature dependence of net primary productivity according to Lieth (1973) with the temperature dependence of soil decomposition as fitted to the data summarized in the present work [fit to the CO2 efflux data, equation (4)] and as used in the CENTURY model (Parton et al., 1987) and Rothamsted model (Jenkinson et al., 1991). The function used by Jenkinson et al. (1991), and especially the one used by Parton et al. (1987), give a good description of the data, but the equation used by Jenkinson et al. (1991) increases to some very high Q10 values at temperatures approaching 0°C. At low temperatures, net primary production, according to the equation developed by Lieth (1973) has much weaker temperature dependence than

at

i, \

k,,, = exp[ - 3.432 + O.l86T(l - OST/36.9)], (n = 76; r2=0.353)

;

\ \

8

757

I

20

I

26

I

I

30

36

(“C)

Fig. 3. Observed QIOvalues of soils processes as a function of temperature together with the theoretical relationship fitted to the CO2 evolution data in the present work [-I and the relationships used by Parton et al. (1987) [- -_I and Jenkinson et al. (1991) [- - - -1as well as the relationship used by Lieth (1973) [---I to describe the temperature dependence of net primary productivity. Symbols refer to the same data as shown in Figs 1 and 2, with open circles referring to data of N dynamics and solid circles to data of CO2 evolution.

decomposition rates (Fig. 3). A comparison of the temperature dependencies of decomposition rate and net primary production therefore suggests that with increasing temperature, soil organic matter decomposition should be stimulated much more than net primary productivity. The respective temperature dependencies of these two processes become more similar at higher temperatures. This is illustrated further in Fig. 4 where the equilibrium soil organic C contents were calculated over the range of temperatures from 5 to 30°C. The modelling was as described by Kirschbaum (1993) except that the temperature dependence of CO2 evolution from soil or litter as fitted to the present data [equation (4)] was used for calculating the equilibrium values for Fig. 4. The model that was used combined a simple biochemically-based growth model in response to CO2 and temperature with a soil organic matter model (Parton et a/., 1987). The model includes nitrogen limitation to productivity and a change in biological nitrogen fixation with changing net primary productivity. The temperature response function of primary productivity (and biological nitrogen fixation) was based on Lieth (1973). Water limitations were not included as a limitation in the model. Soil organic C was divided into seven different pools, consisting of four. litter pools, active (microbial) organic matter, slow organic matter and recalcitrant organic matter. A more detailed description can be found in Kirschbaum (1993). The absolute amounts of organic C in the model are strongly determined by the N input rate, by the fraction of N that is volatilized and lost during N mineralization and by soil texture. As neither of these

758


factors are likely to be constant across different sites or temperature regions, no significance should be attached to the absolute values shown here. However, if these factors are independent of temperature, then the relative response to temperature would be dependent only on the relative temperature sensitivities of net primary productivity and soils processes (as shown in Fig. 3). The relative changes with temperature as shown in Fig. 4(c), are thus the relevant outputs of this model. The model runs suggest that equilibrium C contents should be highest at lowest temperature, and decrease greatly with increasing temperature [Fig. 4(a)]. The loss of C per degree warming decreases with increasing temperature. This is very pronounced if expressed in absolute terms [Fig. 4(b)], with a loss of 4 kg m - 2per degree warming (for the particular model parameters) for a soil at 5°C which reduced to a loss of only about 200 g m-* per degree warming at 35°C. The greater effect in cooler soils is still apparent even in relative terms [Fig. 4(c)], with C loss decreasing from over 10% per degree warming at 5°C to about 3% at 30°C.

-5

10

15

20

Temperature

26

30

(“C)

Fig. 4. Model runs of equilibrium soil organic C contents as a function of temperature (a), the absolute loss of C per degree warming (b) and the loss expressed as a percentage of equilibrium contents (c). The modelling used a simple biochemically-based productivity model coupled to a version of the CENTURY model (Parton er al., 1987) with modifications and parameters described by Kirschbaum (1993) except that the temperature dependence as determined in the present analysis [equation (4)] was used.

DISCUSSION

Observed trends in amounts of soil organic C or N generally show the amounts to decrease with increasing temperature (e.g. Harradine and Jenny, 1958; Jenny, 1980; Post etal., 1982,1985). This implies that the relative temperature sensitivity of decomposition processes must be greater than the temperature sensitivity of net primary productivity (Shaver et al., 1992). The curve fitted to the literature values compiled in this analysis is consistent with that (see Fig. 3), and thereby leads to patterns of soil organic C with temperature (Fig. 4) like those observed by Harradine and Jenny (1958) Jenny (1980) Post et al. (1982, 1985) and others. Significantly, the temperature sensitivity, as expressed by the QlO,was not constant across the range of temperatures, but was far greater at low (< 10°C) than at moderate to high (2&3o”C and above) temperatures. This pattern has been noted before (e.g. Kononova, 1966; Schleser, 1982; Lloyd and Taylor, 1994) and is also embodied in equations like those used by Parton et al. (1987) O’Connell (1990) and Jenkinson et al. (1991), yet was not considered by other workers who calculated the temperature dependence of soil processes with reference to a constant Q10 function (e.g. Townsend et al., 1992; Gifford, 1992). The temperature sensitivity of soil processes obtained in the present work is greater than that obtained by Raich and Schlesinger (1992) from a comprehensive survey of soil respiration rates observed in situ. As discussed above, this is not unexpected as actual soil respiration rates at steady state are determined by the rate at which C is added to the soil which, in turn, is likely to be proportional to net primary productivity. Deriving the temperature sensitivity of soils processes from measuring rates during seasonally varying temperatures (Anderson, 1973; Schlentner and Van Cleve, 1985; Carlyle and Than, 1988; Naganawa et al., 1989; Lloyd and Taylor, 1994) also has problems due to the confounding effects of water availability, litter quality and root respiration as mentioned above. The present work established the temperature sensitivity of decomposition at non-limiting soil water contents. Under most field situations, soil water contents and temperature are both varying seasonally, with water contents often being the lowest when temperatures are the highest (e.g. Goncalves and Carlyle, 1994). Actual decomposition rates may therefore not be the highest at the time of highest temperatures. To give actual predictions of decomposition rates at specific sites, it is necessary to know soil water contents throughout the year, and the dependence of decomposition rates on soil water contents, in addition to its dependence on temperature that was the subject of the present work. There are some experimental problems with measuring COZ evolution or N mineralization in

759

Soil organic matter decomposition laboratory studies. The difficulties with such studies are well illustrated by Ross and Cairns (1978) who showed time courses for their incubations. When soils were set up for experimental measurements, CO;1 evolution rates were at first high due to microbial stimulation by d:sturbance. In most case, rates decreased to lower values after one to several weeks, and those rates were maintained for up to several months in some samples or they continued to decrease in others. In soils where rates continued to decrease, that may indicate the exhaustion of readily-decomposable material or build-up of waste products. As these effects are likely to develop more quickly at warmer temperature (Koepf, 1953) this would depress rates at higher temperatures (unless determinations are made very early after the start of incubation), and underestimate the temperature sensitivity of decomposition. The temperature sensitivity of decomposition rates could therefore be even higher than shown in the present study. IMPLICATIONS

FOR THE GLOBAL C CYCLE

The calculation of the temperature dependence of soil organic matter decomposition based on literature values of decomposition is consistent with the predictions of loss in soil organic matter with increasing temperature that were made in earlier modelling studier, (e.g. Jenkinson et al., 1991; Thornley et al., 1991; Kirschbaum, 1993). Divergent results in a similar study that did suggest that soil organic C contents should be little affected by temperature (Gifford, 1992) was due to the use of a different temperature sensitivity for decomposition rate in that study. My study confirms that there is a strong potential positive feed-back inherent in the massive amounts of C that are currently tied up in organic matter in the soil. The danger is that this could be released by global warming and greatly add to the CO2 already in the atmosphere. This has also been observed in experiments wherse soil temperature has artificially been increased in :ritu (e.g. Van Cleve et al., 1990). It is worrying in this context that temperatures at high latitudes are expected to increase significantly more than temperatures in regions that are already warmer. However, an analysis of soil organic C dynamics with the full version of the CENTURY model (Parton et al., 1987) has shown that the change in soil organic C contents is likely to be very slow and take many centuries (Kirschbaum, 1993). While at equilibrium, soils, especially in cooler regions, are likely to lose large amounts of C (Fig. 4) this may only translate into a relatively small annual loss rate, and, while continuously adding to the CO2 load of the atmosphere, does not seem likely to be of greater importance than CO2 additions from the burning of fossil fuels or deforestation. Furthermore, increasing CO, concentration is likely to stimulate net primary production and provide

additional inputs of C to soil organic matter which would to some extent balance the loss of C from global warming. As the CO, sensitivity of photosynthesis is greater at higher temperature (Kirschbaum, 1994) one would, however, still have to expect losses of C in cool regions of the world, whereas in warmer regions the effect of increasing CO* concentration may be of greater significance than the effect of increasing temperature (Kirschbaum, 1993). Since there is about twice as much C in the world’s soils as in the atmosphere (Melillo er al., 1990) changes in this pool can have considerable feed-back effects on the amount of CO? in the atmosphere and thereby on global warming. The relative loss or accretion rates of C in the soil are determined by the interplay of physical, chemical and biological factors. We must further improve our understanding of these processes to gain a better understanding of the likely future interaction between the global C cycle and climate change to be able to adequately anticipate the nature of the feed-back effects that link soil and atmospheric C reservoirs. Acknowledgements-This work was supported by the Australian National Greenhouse Advisory Committee Dedicated Research Grants Scheme. I thank P. K. Khanna and J. C. Carlyle for helpful comments on the manuscript. REFERENCES

Addiscott T. M. (1983) Kinetics and temperature relationships of mineralization and nitrification in Rothamsted soils with differing histories. Journal of Soil Science 34, 343-353. Anderson J. M. (1973) Carbon dioxide evolution from two temperate, deciduous woodland soils. Journal of Applied Ecology 10, 361-378. Bunt J. S. and Rovira A. D. (1955) The effect of temperature and heat treatment on soil metabolism. Journal of Soil Science 6, 129-136. Campbell C. A., Myers R. J. K. and Weier K. L. (1981) Potentially mineralizable nitrogen, decomposition rates and their relationship to temperature for five Queensland soils. Australian Journal of Soil Research 19, 3233332. Carlvle J. C. and Than U. B. (1988) . , Abiotic controls of soil respiration beneath an eighteen-year-old Pinus radiata stand in south-eastern Australia. Journal of Ecology 76, 654662. Drobnik J. (1962) The effect of temperature on soil respiration. Folia Microbiologica 7, 132-140. Ellert B. H. and Bettany J. R. (1992) Temperature dependence of net nitrogen and sulfur mineralization. Soil Science Society of America Journal 56, 1133-l 141. Flanagan P. W. and Veum A. K. (1974) Relationship between respiration, weight loss temperature and moisture in organic residues in tundra. In Soil Organisms and Decomposition in Tundra (A. J. Holding, 0. W. Heal, S. F. MacLean and P. W. Flanagan, Eds), pp. 2499277. Tundra Biome Steering Committee, Stockholm. Folland C. K., Karl T. R. and Vinnikov K. Y. A. (1990) Observed climate variations and change. In Climate Change: the IPCC Scienttfic Assessment (J. T. Houghton, G. J. Jenkins and J. J. Ephraums, Eds), pp. 195-238. University Press, Cambridge. Foster N. W. (1989) Influences of seasonal temperature on nitrogen and sulfur mineralization/immobilization in a maple-birch forest floor in central Ontario. Canadian Journal of Soil Science 69, 501-514.

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Gifford R. M. (1992) Implications of the globally increasing atmospheric CO1 concentration and temperature for the Australian terrestrial carbon budget: integration using a simple model. Ausfralian Journal of Botany 40, 527-543. Goncalves J. L. M. and Carlyle J. C. (1994) Modelling the influence of moisture and temperature on net nitrogen mineralisation in a forested sandy soil. Soil Biology and Biochemistry 26, 1557-1564. Harradine F. and Jenny H. (1958) Influence of parent material and climate on texture and nitrogen and carbon contents of virgin California soils. I. Texture and nitrogen contents of soils. Soil Science 85, 235-243. Jenkinson D. S., Adams D. E. and Wild A. (1991) Model estimates of CO? emissions from soil in response to global warming. Nafure 351, 304306. Jenny H. (1980) The Soil Resource: Origin and Behavior, Ecological Studies No. 37. Springer, New York. Johnson I. R. and Thornley J. H. M. (1985) Temperature dependence of plant and crop processes. Annals of Botany 55, l-24. Kirschbaum M. U. F. (1993) A modelling study of the effects of changes in atmospheric CO2 concentration, temperature and atmospheric nitrogen input on soil organic carbon storage. Tellus 45B, 321-334. Kirschbaum M. U. F. (1994) The sensitivity of C1 photosynthesis to increasing CO2 concentration. A theoretical analysis of its dependence on temperature and background GO2 concentration. Plant, Cell and Environment 17, 7477754. Kladivko E. J. and Keeney D. R. (1987) Soil nitrogen mineralization as affected by water and temperature interactions. Biology and Fertility of Soils 5, 248-252. Koepf H. (1953) Die Temperatur/Zeit-Abhangigkeit der Bodenatmung. Zeitschriffiir Pfanzenernahrung, Diingung und Bodenkunde 61, 2948. Kononova M. M. (1966) Soil Organic Matter: Its Nature, ifs Role in Soil Formation and in Soil Fertility, 2nd edn. Pergamon Press, Oxford. Lieth H. (1973) Primary production: terrestrial ecosystems. Human Ecology 1, 3033332. Lloyd J. and Taylor J. A. (1994) On the temperature dependence of soil respiration. Functional Ecology 8, 315-323. Malhi S. S., McGill W. B. and Nyborg M. (1990) Nitrate loss in soils: effect of temperature, moisture and substrate concentration. Soil Biology and Biochemistry 22, 7333737. Melillo J. M., Callaghan T. V., Woodward F. I., Salati E. and Sinha S. K. (1990) Effects on ecosystems. In Climare Change: the IPCC Scientific Assessmenr (J. T. Houghton, G. J. Jenkins and J. J. Ephraums, Eds), pp. 283-310. University Press, Cambridge. Moureaux C. (1967) Influence de la temperature et de I’humidite sur les activites biologiques de quelques sols ouest-africains. Cahiers Pedologie Orstom 5, 393420. Naganawa T., Kyuma K., Yamamoto H., Yamamoto Y., Yokoi H. and Tatsuyama K. (1989) Measurement of soil respiration in the field: influence of temperature, moisture level, and application of sewage sludge compost and agro-chemicals. Soil Science and Plant Nuirition 35, 509-516.

Nyhan J. W. (1976) Influence of soil temperature and water tension on the decomposition rate of carbon-14 labelled herbage. Soil Science 121, 288-293. O’Connell A. M. (1990) Microbial decomposition (respiration) of litter in eucalypt forests of south-western Australia: an empirical model based on laboratory incubations. Soil Biology and Biochemistry 22, 153-160. Parton W. J., Schimel D. S., Cole C. V. and Ojima D. S. (1987) Analysis of factors controlling soil organic matter levels in Great Plains grasslands. Soil Science Society of America Journal 51, 1173-I 179. Post W. M., Emanuel W. R., Zinke P. J. and Stangenberger A. G. (1982) Soil carbon pools and world life zones. Nature 298, 156159 Post W. M., Pastor J., Zinke P. J. and Stangenberger A. G. (1985) Global patterns of soil nitrogen storage. Natlrre317, 613-616. Raich J. W. and Schlesinger W. H. (1992) The global carbon dioxide flux in soil respiration and its relationship to vegetation and climate. ?ellus 44B, 81-99. Ross D. J. and Cairns A. (1978) Influence of temperature on biochemical processes in some soils from tussock grasslands. New Zealand Journal of Science 21, 581-589. Schimel D. S., Parton W. J., Kittel T. G. F., Ojima D. S. and Cole C. V. (1990) Grassland biogeochemistry: links to atmospheric processes. Climatic Change 17, 13-25. Schlentner R. E. and Van Cleve K. (1985) Relationshios between CO2 evolution from soil, substrate temperatuie and substrate moisture in four mature forest types in interior Alaska. Canadian Journal of Foresr Research 15, 97-106. Schleser G. H. (1982) The response of CO* evolution from soils to global temperature changes. Zeitschrift fur Naturforschung 37a, 287-29 1. Shaver G. R., Billings W. D., Chapin F. S. III, Giblin A. E., Nadelhoffer K. J.. Oechel W. C. and Rastetter E. B. (1992) Global change and the carbon balance of arctic ecosystems. Bioscience 42, 4333441. Stanford G., Frere M. H. and Schwaninger D. H. (1973) Temperature coefficient of soil nitrogen mineralization. Soil Science 115, 321-323. Theodorou C. and Bowen G. D. (1983) Effects of temperature, moisture and litter on nitrogen mineralization in Pinus radiata forest soils. Australian Forest Research 13, 113-I 19. Thornley J. H. M., Fowler D. and Cannell M. G. R. (1991) Terrestrial carbon storage resulting from CO> and nitrogen fertilization in temperate grasslands. Plant, Cell and Environment 14, 1007-1011. Townsend A. R., Vitousek P. M. and Holland E. A. (1992) Tropical soils could dominate the short-term carbon Climatic cycle feedbacks to increased global temperatures. Change 22, 293-303. Van Cleve K., Oechel W. C. and Horn J. L. (1990) Response of black spruce (Picea mariana) ecosystems to soil temperature modification in interior Alaska. Canadian Journal of Forest Research 20, 1530-l 535. Waksman S. A. and Gerretsen F. C. (1931) Influence of temperature and moisture upon the nature and extent of decomposition of plant residues by microorganisms. Ecology 12, 33-60. Wiant H. V. (1967) Influence of temperature on the rate of soil respiration. Journal of Forestry 65, 489-490.