Microcalorimetric study of microbial activity changes of acrisol in subtropical China under three different land management

The microcalorimetric method was applied to analyze the influences of successive reforestations with Eucalyptus granddis × E. uophylla, Pinus massoniana, and continuous sugarcane production on the soil microbial activities. 500 g of each refined representative sample was collected in rainy and dry seasons from four 100 m 2 homogeneously and perfectly defined acrisol quadrats in subtropical China. Two of them were Eucalyptus plantations with 10 (E10) and 20 (E20) year–old stands. The other two were 10–year–old pine tree plantation (P10) and sugarcane land (SL10) correspondingly contiguous to E10 and E20 and used as references for E10 and E20, respectively. Blocks of E10/P10 were 1500 m away from that of E20/SL10. Microcalorimetric experiments were carried out using 1.2 g soil samples and 0.6 ml of solution containing 5.0 mg of glucose and 5.0 mg of ammonium sulphate at 28°C. The effects of land management practice on soil quality were examined by measuring their physicochemical and biological properties. The results showed that: 1) zymogeneous bacteria were the dominated microbes in the land of continuous sugarcane production, but autochthonous floras were the ones for forest; 2) when compared with its control (SL10), land of eucalyptus (E20) had lower soil packing degree and inhibitory effect on microbial activities, but higher seasonal fluctuation in microbe constitution and activities under the same circumstance; 3) compared with its control P10, the land of eucalyptus E10 had alike soil packing degree and higher seasonal fluctuation degree of microbial activities, but lower inhabiting degree of soil microbial metabolism.


INTRODUCTION
As essential components of terrestrial ecosystems, soil microbes play significant roles in decomposing organic materials and nutrient circulation.They are more sensitive to environment stress in their community composition and biomass and dynamic profile than other plants and animals, thus are commonly used as earliest indicators of many ecosystem processes (Dilly and Munch, 1998;Hernot and Robertson, 1994;Nannipieri et al., 1990).Living state of soil microbes are easily influenced by the soil conditions such as soil texture, porosity, pH, C-to-N ratio, salinity, especially the content of water and organic matter (Aanderud et al., 2008;Fierer et al., 2003;Rajaniemi and Allison, 2009), but this does not mean that the soil microbes are conformists against soil conditions.In fact, the soil conditions are energetically transformed by the microbes throug changing their community composition, biomass and metabolism (Nsabimana et al., 2004).However, soil properties are chiefly transformed by land management such as tillage mode, planting vegetation species and fertilization (Zheng et al., 2007;Aanderud et al., 2008).Quite a few researchers have intensively investigated the effects of soil microbial activities on the actual soil quality or ecosystem processes with the purpose of optimizing strategy for land exploitation (Banning et al., 2012;Zhang and Chu, 2011).
Ascribe to a burgeoning demand for wood and wood fiber products in domestic as well as international market; a rapid expansion of eucalyptus plantations has taken place in the Southern China in the last 20 years (Wu and Zhang, 2006).Now, Eucalyptus forest has clothed a large area of barren mountains (about 1.7 million ha, 2012) in the Southern China and the local residents income was greatly increased through selling Eucalyptus timber (Wu and Zhang, 2006).
However, just as the other eucalyptus planted regions in the world, eucalyptus reforestation is still a controversial issue in China as consideration of the understory plant diversity, soil fertility and soil biodiversity (Xue, 2009).Based on analyses of phospholipid fatty acids (PLFA) of soil microbial communities and soil primary physico-chemical parameters in Chronosequence Eucalyptus plantations in south China, Cao et al. (2010) found that PLFA as well as the amount of soil TN and SOC (soil organic carbon) were higher in 13-year-old-Eucalyptus plantations than those in younger ones, and suggested that the soil properties and the community structure of soil microbes were not negatively affected by reforestation of Eucalyptus.But this did not mean that eucalyptus exerting nothing negative on the soil microbial community composition (Cao et al., 2010).
Inconsistently, some research results have shown that Eucalyptus reforestation less ameliorated or even degraded the soil quality in aspect of soil porosity, bulk density, total organic carbon/nitrogen, microbial biomass and microbial metabolic quotient or some essential enzyme activities (Jeddi et al., 2009;Lisardo Nu´n˜ez-Regueira et al., 2006;Behera and Sahani, 2003;Sicardi et al., 2004).It is obvious that discrepancy exists in accounting for relationship of soil quality and Eucalyptus reforestation.Soil quality status was principally characterized by the SOC (soil organic matter content), field water capacity, air-filled porosity, pH and soil bulk density of the top soil, and TN, mean diameter of cumularspharolith (Shukla et al., 2006), but also characterized by the microbial biomass, microbial community composition, soil respiration and enzyme activity (Yakovchenko et al., 1996;Filip et al., 2002).There are agreements on the physical-chemical and biological properties as the soil quality indicators (Klein et al., 1985), but inconsistent opinions also exist as to the biochemical ones, especially the enzyme activity (Trasar-Cepeda, 2008;Sicardi et al., 2004).A large group of soil tests have indicated that the decrease or increase in enzyme activity did not always occur in all enzymes of microbes for a special type of land use, and the absolute values of different enzyme activities did not always show explicit relationship against the reduction or increase in the organic matter content resulted from soil use (Trasar-Cepeda et al., 2008).In fact, effects of decrease of organic matter content on the enzyme activity depend on the type of land use and the type of enzyme (Trasar-Cepeda et al., 2008).
Microcalorimetric method have been applied to study soil and environmental sciences and confirmed to be a valid alternative method in study of soil microbial biomass, metabolism and growth state (Roxg et al., 2007;Lisardo Nu´n˜ez-Regueira et al., 2006;Sigstad et al., 2002).With this alternative method and measurement of physical and chemical properties, Nhiiez-Regueira et al. (2005) successfully established an experimental procedure to assess the productivity and health of soil under two types of land managements.Meanwhile, they also quantified the effect of land use on the soil quality (Nuiiez-Regueira et al., 2005).
The outstanding advantages of the microcalorimetric method are: 1) continuously in situ monitoring the activity of life process for a long-term without disturbing the system; 2) independent of the type of microorganisms and their form of evolution because the method only records the initial and final energy state of the system; and 3) highly sensitive and very simple (Ljungholm et al., 1979a;Zheng et al., 2009).With the expansion of Eucalyptus reforestation in southern China, attention have focused on the plant community composition, soil properties, Eucalyptus growth state and efficient of water utilization in the Eucalyptus forest (Chen et al., 2006;Lu et al., 2005;Cao et al., 2010).But so far, no study was conducted on the activity of soil microbes in the Eucalyptus plantations using microcalorimctric method in China.
As the microcalorimetric technique has corroborated validity of studying microbial activity in soils (Wu et al., 1996;Critter et al., 2002;Zheng et al., 2007), the present study are aimed to analyze the effects of three types of land management practice (consecutive plantation of Eucalyptus, pine, sugarcane) on the microbial activity in soils, to investigate the relationship between dynamic of soil microbe and the specific soil properties that is, soil moisture, soil pH, soil organic carbon content, and to assess which management practice mentioned earlier is more favorable to maintaining soil health and high productive potential in the local climate.

Study area and sampling
The experimental sites are located in Dongmen town (22°51' to 22°55' N and 113°44' to 113°53' E), Fusui county, Guangxi Zhuang Autonomous Region, southern China.This area is a region with topographic features of karst-localized low hilly tablelands.Half of its total tillable soil is used for reforestation of eucalyptus and pine trees (98% of which is for eucalyptus) and the other half is for vegetation of sugarcane.It has a subtropical monsoon climate with an average annual temperature of 20 ~ 25°C, and the highest and lowest average monthly temperatures of 28.2°C (July) and 13.4°C (January).The average annual rainfall is 1000 ~ 1200 mm with 80% of it falling in April to September.So the climate is clearly divided into rainy season (April to September) and dry one (October to March).The soil is Acrisol developed from granite.Textures of the surface soils vary from sandy loams to clay loams while subsoils are clays to heavy clays (Xiang et al., 2006).The sampling plots for this study were Eucalyptus (Eucalyptus granddis × E. uophylla) plantations of two stand-growth-ages, the 20-year-old (E20) (reforestation 20 years ago for demonstration) and 10-year-old (E10) (reforestation for timber production 10 years ago, the present stands are result of sprout regeneration, the first generation was fallen 5 years ago), pine (Pinus massoniana) plantation with stands of 10 years (P10) and sugarcane land (SL10).
The sugarcane land plantation has been subjected to the local conventional tillage type for more than 10 years, namely that sugarcanes are harvested during December and February and the residues were left to cover the surface soil until the March to April when soil-incorporation and first fertilization was conducted using moldboard-plow.The second fertilization was conducted in June to July.The intensity of fertilization usually was about 750 kg/ha and the sugarcane stubbles were replaced every three years.All the works were done in farming way.Compound fertilizer with the content of N being about 10.0, P2O5 about 7.4 and K2O about 12.0 g per 100 kg was usually applied.The mean yield of sugarcane generally was 90 to 120 tons/ha.Planting density was 625 stands/ha for E10 and P10 and 400 stands/ha for E20.Management practice for the Eucalyptus and pine plantations usually was weeds-bush-hoed for reforestation in the period of March to May followed by weed control with hand work and fertilization of the tree-lets with a model of pot-like-hole digging in the first three years.The forest land was fertilized with Eucalyptus-special fertilizer at half intensity for the sugarcane land.The mean yield of merchantable timber under such a practices generally was 90 to 120 m 3 /ha for Eucalyptus in each rotation period (average 6 years).Pine plantations were initially reforested as control for scientific research on the Eucalyptus timber production and have not fallen yet till now.The understory of P10 forest is a tall shrub layer dominated by litsea glutinosa and Evodia lepta, a shrub layer dominated by Rhodomyrtus tomentosa, Miscanthus sinensis, Ficus simplicissima Lour.[F.hirta Vahl var.Palmatiloba (Merr.)Chun], Ligustrum quihoui Carr, Trema angustifolia (Planch.),Lygodium japonicum (Thunb.)Sw. species and a ground layer of Dicranopteris linearis, Arthraxon lanceolatus (Roxb.)Hochst.
The understory of the E10 forest is a tall shrub layer comprised of l. glutinosa, E. lepta, Mallotus paniculatus and Rhus chinensis, a shrub layer dominated by T. angustifolia (Planch.),Ficus simplicissima Lour.[F.hirta Vahl var.Palmatiloba (Merr.)Chun] and L. quihoui Carr.and a ground layer dominated by D. linearis and A. lanceolatus (Roxb.)Hochst.However, no figuration understory was found in the E20 forest except the sporadic distribution of D. linearis.The average height of trees is about 20, 30 and 18 m in E10, E20 and P10 forest, respectively.The slope gradient of all the study plots is no more than 5%, and the canopy density of the E10, E20 and P10 is about 70, 90 and 70%, respectively.The E10 was contiguous to P10 and E20 was contiguous to SL10.E10 had opposite slope orientation to P10, E20 had opposite slope orientation to SL10.Block of E10/P10 was 1500 m away from that of E20/SL10.Such a distribution pattern of vegetation offers a rare opportunity to compare how reforestation of Eucalyptus affects soil microbial community composition and their activity against reforestation of native tree species of P. massoniana and sugarcane cropping in the texture-alike soil under the same climatic condition.For sample collection, 100 m 2 of land was delimited as the plot and divided into 1 m 2 ones.Five noncontiguous plots were randomly chosen.After removal of the fallen foliage and litter, 1 kg of soil was taken at the depth of 5 to 20 cm and processed through coning and quartering procedure (Petersen et al., 1995).A total of 500 g of each highly homogenized soil samples was placed in a polyethylene bag tabbed with requisite information (date and time of sampling, orientation of slope, topography of the zone, characteristics of understory vegetation, soil colour, etc) to avoid contamination and loss of moisture.These bags were sent back to the laboratory in less than 10 h and stored at 4°C to keep field conditions as steady as possible until indoor work started in no more than 24 h.Sampling was conducted twice a year at rainy season (26-05-2012) and dry season (26-12-2012).Each sample was divided into two fractions, one fraction (E10-1, P10-1, E20-1 and SL10-1) was used for microcalorimetric experiments and the other fraction (E10-2, P10-2, E20-2, and SL10-2) was used for measurement of physical, chemical and biological properties.

Determination of the physical properties
Soil moisture was determined by incubating samples in an oven at 105°C to a constant weight.Soil pH was measured through soil water suspension (1:2.5 v:v) with a digital pH meter (Thomas, 1996).Bulk density was determined by the cylinder method.In brief, soil samples were carefully introduced into a 6.5 cm diameter and 7.5 cm high cylinder to avoid generating compaction.After being sent to the laboratory, the cylinder was placed in an oven and incubated at 105 to 110°C to constant weight.Bulk density was then calculated from the dry weight and occupied volume values of the sample.Values of moisture and actual density of sample were calculated at the same time.Total porosity, aeration porosity and water porosity were determined as previously reported (Liu et al., 1996).Values of physical properties are shown as the mean of that of samples colleting in rainy and dry season.

Determination of the chemical properties
Soil organic materials (OM) were valuated using dichromate oxidation method and total N (TN) was determined using an ultraviolet spectrophotometer after Kjeldahl digestion (Liu et al., 1996).Soil total P was determined by molybdenum-blue colorimetry after digested with HF-HClO4 (Jackson, 1958).Values of chemical properties are shown as the mean of that of samples colleting in rainy and dry season.

Determination of biological properties
The number of living microorganisms was estimated by viable count on serial spread plates as reported previously (Zheng et., 2007).In a nutshell, 10 g of each soil sample was suspended in 90 ml of sterilized phosphate buffered saline and continuously diluted by 10fold for 6 times.Then, 0.1 ml of the diluted sample suspension was spread over an agar plate with Martin's medium for fungi, a plate with beef extract peptone medium for bacteria and a plate with Gause's No. 1 synthetic medium for actinomycetes.The plates were incubated at 28°C until colonies appeared (2 days for bacteria and 5 days for fungi and actinomycetes).The experiment was performed in triplicates and colony forming units (CFU) were counted independently for three times.

Microcalorimetric measurements
The microcalorimetric test was conducted on a 3114/3236 thermal active monitor (TAM TM ) air eight-channel isothermal calorimeter manufactured by Thermometric AB, Stochholm, Sweden.The structure and work principle of this instrument was detailed in other literatures (Ren et al., 2012) or web site of the manufacturer.The measurement was conducted as previously reported (Zheng et al., 2007).In brief, the 5 ml glass ampoules were cleaned and sterilized in an oven at 100°C before use.All soil samples were preheated at 28°C for one day and then measured microcalorimetrically.1.2 g of soil sample was placed in a sterilized glass ampoule and then 0.6 ml of a solution containing 5.0 mg of glucose and 5.0 mg of ammonium sulphate was added.To control evaporation and energy loss, the ampoules were hermetically closed using Teflon sealing discs.The temperature of the calorimeter system and the isothermal box was controlled at 28°C.The heat flow rate of microbial growth was continuously monitored with a thermal activity monitor and recorded with a computer to plot time-power curve.Three repeats of measurement for each sample were done and only one power-time curve from these measurements was analyzed since high repeatability was seen with the three parallel records (Zheng et al., 2007).
The thermodynamic parameters including growth rate constant (k), the maximum thermal power (Pmax), the time of reaching the maximum peak (tmax) and total heat dissipation (Qt) were obtained directly or by integrating the power-time curves.Among them, the k obeys the following thermokinetic equation (Yao et al., 2008): Where t is time, Pt is the power output at time t, P0 is the power at time t = 0 and k is the growth rate constant calculated from the slope of semi-logarithm of the exponential phases.The Qt is the sum of thermal power during organic material consumption and reflects the activities of soil microbes (Yao et al., 2008).

Statistical analyses
The results of microbial numbers and that of soil physical and chemical properties were given as the arithmetic mean of three independent measurements.Pearson correlation analysis was performed with SPSS 11.5 software (SPSS Inc., 2002).

Soil physical and chemical property
Table 1 lists the main physical and chemical properties of soil samples.It is obvious that: 1) E20/SL10 plots had higher organic matter content than E10/P10 plots; 2) E10 plot had the lowest total nitrogen content, while the other three plots had similar total nitrogen content; 3) P10 plot had the lowest total phosphorus content; 4) C/N ratio of the four plots was out of the range of 10 to 15, which was not sustainable for microbe growth in soils.Plots P10, E20 and SL10 were more favorable to microbe growth because they had more abundant nitrogen.All forest soil samples were acidic except the sugarcane one was neutral.The two Eucalyptus plantations E10 and E20 were more acidic than their control P10 and SL10 accordingly.No significant difference was observed in soil actual density among the four plots although the SL10 had the highest bulk density.Among the four samples, E20 had the lowest water porosity, while SL10 had the lowest air porosity.

Microbial numbers and their relationship with type of land use and season alternation
Table 1 shows the mean values of microbial numbers for all soil samples.It is demonstrated that varies in type of land use and season alternation greatly affected soil microbial numbers and their composition.In both rainy and dry seasons, SL10 collected from sugarcane land was influenced most by human activities, showing the highest bacterium number.By contrary, soil samples of E20, E10 and P10 collected from regeneration forest were lest influenced by human activities, containing lower bacterium numbers.Fluctuation in number of soil microbes with seasonal change was particularly notable for the samples collected from forest land, which wasmuch higher in E10 and E20 from Eucalyptus plantation than that in their control P10 and SL10, respectively.These data indicated that number and constitution of microorganisms in Eucalyptus plantation were more unstable than the one originated from sugarcane or the indigenous varieties of pine tree.

Microbial activity measured by microcalorimetric method
Table 2, Figures 1 and 2 display the results of calorimetric tests for all soil samples collected in rainy and dry seasons.Traces of microbial activity from different biotope were recorded as distinguishable power-time curves.They all presented a typical process of microbial metabolic activity.Just as the typical growth curve of microbes, after a lag phase, the heat flow increased exponentially which was followed by a stationary phase and a decline phase.Comparison of the power-time curves of the four samples collected in rainy season with those in dry season showed that samples collected in rainy season had second peaks and the segments in the curves containing the second peak were nearly parallel, which were not seen in samples collected in dry season.According to Yao et al., (2008), the second peaks may be caused by: 1) the growth of different microbial communities; 2) same microorganisms utilize different carbon sources besides glucose added at the beginning of the experiment; and 3) adaptation of soil anaerobes to anaerobic conditions.In our experiment, the volume of the measuring cell in the glass ampoule was 5.0 ml, and 3.0 ml air was left after adding the soil sample and the aqua.At the beginning of the test, oxygen in the room above the soil sample in the airtight glass ampoule was available for soil microbes, which was initially in favor of aerobes.When the oxygen was consumed, the condition was more favorable to anaerobes.This may explain why there were two typical peaks.It was worth the whistle that segments in the curves containing the second peak were nearly parallel as mentioned earlier; this may be interpreted as that alike microbial communities in these four soil samples were undergoing metabolism using the alike substrates of similar content.
Considering that the nutritional elements in a soil would not completely vanish in a short time of six months, it was most likely that the second peak disappeared in the thermal activity curves of the samples collected in dry season was caused by lacking the corresponding anaerobic microbial communities in samples collected in the rainy season.Contrasting the power-time curves of samples collected in rainy and dry seasons from the same plot, the amplitude of variation (AV) for a specific parameter was obtained by the following equation:

Rx -Dx Avx = × 100 Rx
Where AVx was the amplitude of variation for a specific parameter x; Rx and Dx were the amplitude of variation for a specific parameter (x) of samples collected in the rainy season and dry season, respectively.
AV of K (AVk) was 6.41% higher in E10 than that of its control P10, and was 6.84% higher in E20 than that of its control SL10.AV of P max  (AVP max ) and Q t (AVQ t ) were 26.482 and 11.75% higher in E10 than those of its control P10, respectively, and 58.813 and 8.623% higher in E20 than those of its control SL10, respectively.AV of T max (AVT max ) was 25.3% higher in E10 than that of its control P10, and 4.45% higher in E20 than that of its control SL10.These data indicated that season alternation had higher influence on microbe activities in soil of Eucalyptus plantation than in soil used for vegetation of sugarcane and pine under the local climate condition.This was in consistence with the ratiocination in the soil analysis.Both the power-time curves of samples collected in rainy and dry seasons can be divided into two groups based on microbial growth process.Samples collected in rainy season from SL10 and E20, which were the land of sugarcane and 20year-old Eucalyptus stand and contiguous to each other, lacked a lag phase and showed rapid microbial growth at the beginning (Figure 1), while samples collected in rainy season from E10 and P10, which were the land of 10yesar-old Eucalyptus and 10-year-old pine tree and contiguous to each other, presented a longer lag phase (Figure 1).Differently, only samples collected in the dry season from SL10 showed rapid microbial growth at the beginning, and all the other samples collected from E20, E10 and P10 showed longer lag phase (Figure 2).Obviously, power-time curves were consistent with their bacterial numbers (Table 1).Taken together, the bacterial quantity data and microbial activity curves indicated that zymogenous bacteria were the main community for soil sample SL10 in both rainy and dry seasons and for soil sample E20 in the rainy season, while the autochthonous floras were the dominant microbial communities in soil sample E20 in the dry season and in soil samples E10 and P10 in both rainy and dry seasons.
For parameters of all the power-time curves, K (the microbial growth rate constant during the log phase or the exponential phase of microbial activity curves), T max (h) (the time to reach the peak) and P max (µw) (the peak of heat evolution) also presented the same trend as mentioned earlier ( Figures 1, 2 and Table 2).
The K value was positively correlated with bacterial number with Pearson's correlation coefficient value of 0.681 and 0.842 for samples collected in the rainy and dry seasons, respectively (Figure 3).T max was negatively correlated with bacterial number with Pearson's correlation coefficient of -0.902 and -0.683 for samples collected in rainy and dry seasons, respectively (Figure 4).P max was positively correlated with bacterial number with Pearson's correlation coefficient of 0.793 and 0.914 for samples collected in rainy and dry seasons, respectively.
The heat evolution of samples E10 and P10 had longer stationary phase (Figures 1, 2, 5 and 6).By contrast, the Q t (the value of total heat released by soil microorganisms) had weak correlation with the total number of culturable soil microorganisms, showing Pearson's correlation coefficient of 0.465 and 0.329 for samples collected in the rainy and dry seasons, respectively (Figures 7 and 8).

Relationship between land use type and soil physical/chemical properties
Actual density (kg.m -3 ) of all the samples from land under three management types was not significantly different, indicating that all the tested lands were developed from the same mother rock.Sample from SL10 had the highest bulk density (kg.m -3 ), but the lower total porosity among the samples, suggesting that the packing degree of soil from SL10 was higher than those of the other three samples.The higher packing degree of soil from SL10  Tmax presented as two groups, the group of E10 and P10 showed higher Tmax value but lower bacterial numbers than the group of E20 and SL10.
may be correlated with frequent human activities such as harvest, fertilization, but most of all, long-term, intense use of chemical fertilizers.However, the packing degree of soil from SL10 was not high enough to restrict microbial activities, it only influences soil aeration by directly affecting total porosity.In some cases, due to the formation of surface and subsurface compact layers, its resulted drainage restriction, flooding and anoxia can adversely affect microbial growth and activities (Lisardo Nu´n˜ez-Regueira et al., 2006).Higher total porosity and lower bulk density for samples from E10 and P10 usually originate faster water vertical motion and subsequently result in lower field capacity (Table 1).However, because organic matters could absorb enough water to maintain a significant biological activity, this dose not adversely affect soil microbial growth and activities (Lisardo Nu´n˜ez-Regueira et al., 2006).
The results that soil from E10 and P10 had almost the same total, air, water porosity and field capacity indicated that the packing degree of them was alike.
The total porosity of soil from E20 and SL10 is not significant different, however the former has higher air but lower water porosity than its control SL10, these suggest that the packing degree of sugarcane land is higher than that of the E20 land.

Relationship between organic matter (OM) and microbial quantity and activity
It was generally believed that OM is positively correlated with the number, biomass and activity of microbes in soil Positive relationship among organic matter (OM), log of total colony forming units and the value of total heat released by soil microorganisms (Qt) for samples collected in dry season.The Pearson's correlation coefficient was 0.887 between OM and log of total colony forming units, 0.409 between OM and Qt, and 0.329 between Qt and log of total colony forming units, respectively.(Barros et al., 1997).In agreement with that, our results also indicated that OM is positively correlated with the total number of culturable microbes, with Pearson correlation coefficient as high as 0.821 and 0.887 for samples collected in rainy and dry season, respectively (Figures 7 and 8).Although, Q t is positively correlated with OM and the total number of culturable microbes, their Pearson's correlation coefficient is relatively low (Figures 7 and 8), suggesting that metabolism of soil microbial communities is inhibited by some ill-defined elements while experiments were conducted, even in the original circumstances.Meanwhile, the heat flow generated by per CFU was much higher for samples from E10 and E20 than that of their control samples from P10 and SL10, regardless of rainy or dry seasons (Figures 9 and 10).Taking together, the results indicate that inhibiting degree of microbe's metabolism for soil samples from P10 and SL10 was much stronger than that from E10 and E20.Unfortunately, we were unable to determine whether this differentiation is caused by

Conclusions
In this study, we analyzed the effects of three types of land management practice (consecutive plantation of Eucalyptus, pine, sugarcane) on soil microbial activity, investigated the relationship between soil microbial activities measured by using microcalorimetric method and specific soil properties (soil moisture, soil pH, soil organic carbon content) and assessed the effect of management practice on maintaining soil health and high productive potential.Taking together, we concluded as follows: 1) Zymogenous bacteria were the dominant microbes in the land of continuous sugarcane production but autochthonous floras were the one in the land of forest.2) Compared with its control (land of continuous sugarcane, SL10), the land of eucalyptus E20 had lower soil packing degree and inhibition against soil microbe activities, but higher seasonal fluctuation degree of soil microbial activities and constitution under the same circumstance.
3) Compared with its control P10, the land of eucalyptus E10 had similar soil packing degree and higher seasonal fluctuation degree of microbial activities, but lower inhabiting degree of soil microbial metabolism.

Figure 1 .
Figure 1.Power-time curves recorded microcalorimetrically by supplementing glucose and ammonium sulphate into the four soil samples collected in rainy season.In these curves, thermal power (µw) is plotted against time (h).Integration of these curves provides values of the total heat evolved in the process.The evolution of peak height (Pmax) is the power at the maximum of the peak, and peak time (Tmax) is the time to reach the maximum of the peak.

Figure 2 .
Figure 2. Power-time curves recorded microcalorimetrically by supplementing glucose and ammonium sulphate into the four soil samples collected in dry season.In these curves, thermal power (µw) is plotted against time (h).Integration of these curves provides values of the total heat evolved in the process.The evolution of peak height (Pmax) is the power at the maximum of the peak, and peak time (Tmax) is the time to reach the maximum of the peak.

Figure 3 .
Figure3.Growth rate constant (k) and log colony forming units of bacteria of soil samples collected both in rainy and dry season.The value of k increased with bacterial quantity increasing and positively correlated with bacterial quantity with Pearson's correlation coefficient of 0.681 and 0.842 for rainy and dry seasons, respectively.

Figure 4 .
Figure 4.The peak time (the time to reach the peak, Tmax) inversely related to the log colony forming units of bacteria of samples collected in rainy season (RS) (Pearson's correlation coefficient of -0.902) and dry season (DS) (Pearson's correlation coefficient of -0.683).Tmax presented as two groups, the group of E10 and P10 showed higher Tmax value but lower bacterial numbers than the group of E20 and SL10.

Figure 5 .Figure 6 .
Figure 5. Positive correlation with Pearson's correlation coefficient of 0.793 was found between the maximum thermal power (Pmax) and the log of bacterial number of samples collected in rainy season.

Figure 7 .
Figure7.Positive relationship among organic matter (OM), log of total colony forming units and the value of total heat released by soil microorganisms (Qt) for samples collected in rainy season.The Pearson's correlation coefficient was 0.821 between the OM and log of total colony forming units, 0.620 between OM and Qt, and 0.465 between Qt and log of total colony forming units, respectively.

Figure 9 .Figure 10 .
Figure 9.The heat flow generated by per CFU (J/CFU) of samples collected in rainy season.

Table 2 .
Results from power-time curve measured by microcalorimetric method.