Effect of land management and soil texture on seasonal variations in soil microbial biomass in dry tropical agroecosystems in Tanzania

Applied Soil Ecology 44 (2010) 80–88

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Effect of land management and soil texture on seasonal variations in soil microbial biomass in dry tropical agroecosystems in Tanzania Soh Sugihara a,*, Shinya Funakawa a, Method Kilasara b, Takashi Kosaki c a

Graduate School of Agriculture, Kyoto University, Kitashirakawaoiwakecho, Sakyoku, Kyoto 606-8502, Japan Faculty of Agriculture, Sokoine University of Agriculture, Tanzania c Graduate School of Urban Environmental Science, Tokyo Metropolitan University, Japan b

A R T I C L E I N F O

A B S T R A C T

Article history: Received 12 April 2009 Received in revised form 8 September 2009 Accepted 9 October 2009

Soil microbes are an essential component of most terrestrial ecosystems; as decomposers they are responsible for regulating nutrient dynamics, and they also serve as a highly labile nutrient pool. Here, we evaluated seasonal variations in microbial biomass carbon (MBC) and nitrogen (MBN) as well as microbial activity (as qCO2) for 16 months with respect to several factors relating to soil moisture and nutrients under different land management practices (plant residue application, fertilizer application) in both clayey (38% clay) and sandy (4% clay) croplands in Tanzania. We observed that MBC and MBN tended to decrease during the rainy season whereas they tended to increase and remain at high levels during the dry season in all treatment plots at both of our test sites, although soil moisture did not correlate with MBC or MBN. qCO2 correlated with soil moisture in all treatment plots at both sites, and hence soil microbes act as decomposers mainly during the rainy season. Although the effect of seasonal variation of soil moisture on the dynamics of MBC, MBN, and qCO2 was certainly greater than that attributable to plant residue application, fertilizer application, or soil texture, plant residue application early in the rainy season clearly increased MBC and MBN in both clayey and sandy soils. This suggests that plant residue application can help to not only counter the N loss caused by leaching but also synchronize crop N uptake and N release from soil microbes by utilizing these microbes as an ephemeral nutrient pool during the early crop growth period. We also found substantially large seasonal variations in MBC and MBN, continuously high qCO2, and rapid turnover of soil microbes in sandy soil compared to clayey soil. Taken together, our results indicate that soil microbes, acting as both a nutrient pool and decomposers, have a more substantial impact on tropical sandy soil than on clayey soil. ß 2009 Elsevier B.V. All rights reserved.

Keywords: Soil microbial biomass Seasonal variation Land management Soil texture Dry tropical agroecosystem

1. Introduction Soil microbes are an essential component of most terrestrial ecosystems. Indeed, as decomposers they regulate nutrient dynamics, and they also act as a highly labile nutrient pool, so that soil microbes are also considered as a sensitive indicator of soil fertility (Wardle et al., 2004; Joergensen and Emmerling, 2006). To assess factors that control seasonal variations in soil microbial biomass and activity (i.e., qCO2) in the dry tropical and temperate ecosystems, numerous studies have evaluated the seasonal dynamics of microbial biomass carbon (MBC) and nitrogen (MBN) (Wardle, 1992, 1998; Hamel et al., 2006; Montano et al., 2007; Murphy et al., 2007). Many studies of dry tropical ecosystems have found that soil moisture primarily affects MBC and MBN; soil microbial biomass is high in the dry season and thus

* Corresponding author. Tel.: +81 75 753 6101; fax: +81 75 753 6102. E-mail address: [email protected] (S. Sugihara). 0929-1393/$ – see front matter ß 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.apsoil.2009.10.003

retains nutrients when plant activity is low. In contrast, during the rainy season soil microbial biomass is low because of accelerated turnover caused by enhanced grazing by soil macro-fauna (Singh et al., 1989; Michelsen et al., 2004) and by microbial cell lysis due to drastic changes in soil moisture (Halverson et al., 2000; Fierer and Schimel, 2003). Ultimately, these changes lead to nutrient release from soil microbes in the rainy season when plant activity is high. Hence, soil microbes act both as a sink and a source of nutrients in tropical ecosystems (Singh et al., 1989; Srivastava, 1992; Tripathi and Singh, 2007). However, most studies that have evaluated seasonal soil microbial dynamics in the dry tropics have been based on forest and savanna ecosystems, and little information has been acquired for cropland (Kushwaha et al., 2000; Sugihara et al., 2009). In addition, most of these studies were conducted with only 3–6 samplings per year, and hence the effect of short-term soil moisture variations on soil microbial dynamics is still unclear in dry tropical agroecosystem. On the other hand, application of plant residue and/or fertilizer in tropical croplands—in an effort to maintain and/or improve soil

S. Sugihara et al. / Applied Soil Ecology 44 (2010) 80–88

fertility and crop yields has been the subject of several trials (Bationo and Buerkert, 2001; Palm et al., 2001). Various studies have assessed the effect of such land management practices on the decomposition of applied organic residues (Singh et al., 2007a), nitrogen (N) mineralization (Kushwaha et al., 2000), efficiency of N utilization by crops (Baijukya et al., 2006), and soil sustainability (Powlson et al., 2001; Adeboye et al., 2006) in tropical agroecosystems. However, information on seasonal variations in soil microbial biomass in tropical agroecosystems is scarce (Lulu and Insam, 2000; Agele et al., 2005). In tropical regions, most heavy rainfalls occur within a few hours and cause heavy N leaching (Hartemink et al., 2000; Shahandeh et al., 2004). To minimize N leaching from soil, it is important to utilize soil microbes as a temporal nutrient pool during the rainy season (Herai et al., 2006). Singh et al. (2007b) found that plant residue application in India stimulated N immobilization/mineralization processes of soil microbes, and these researchers suggested that plant residue application can synchronize both crop N uptake and N release from soil microbes due to N mineralization. To investigate this possibility, more detailed information is required about shortterm variations in soil microbes related to plant residue application in dry tropical agroecosystems. Soil texture is also an important factor that controls soil microbial dynamics (Van Veen et al., 1984; Ladd et al., 1992; Mu¨ller and Ho¨per, 2004). Sandy soils are normally characterized by lower amount of soil organic matter, and clayey soil has the structure of high-clay content, protecting soil microbes from predators (Juma, 1993) and dry stress (Van Gestel et al., 1991), so that soil microbial biomass is generally lower in sandy soil as compared to clayey soil (Franzluebbers et al., 1996). On the other hand, many studies have shown a faster turnover rate of soil microbes in sandy soil as compared to clayey soil (Saggar et al., 1999; Mu¨ller and Ho¨per, 2004). Sandy soil in the tropics is one of the most nutrient-poor soil ecosystems in the world (Bationo and Buerkert, 2001), and therefore it is crucial to understand and improve the nutrient dynamics in tropical sandy cropland. Because tropical sandy soil carries a lower soil microbial biomass that turns over more rapidly, it is possible that the effect of seasonal dynamics, e.g., soil moisture/temperature and land management, on seasonal variations in soil microbes could be greater in sandy soil than in clayey soil. In the present study, we tested this possibility by periodically measuring MBC, MBN and microbial activity (as qCO2) in Tanzanian croplands having clayey or sandy soil texture. Our objectives of this study in Tanzania are (1) to evaluate the effect of soil moisture on seasonal variations in soil microbial biomass, (2) to evaluate the effect of land management on the seasonal variations in soil microbial biomass, and (3) to compare the seasonal variations in soil microbial biomass between the clayey and sandy croplands, with regard to nutrient dynamics. 2. Materials and methods 2.1. Description of study sites We conducted the field experiment from March 2007 to June 2008 (16 months total) at two sites with different soil texture, i.e.,

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one clayey (38% clay; Tanzania clayey site = TZc), one sandy (4% clay; Tanzania sandy site = TZs). TZc is located at the agricultural experimental stations of Sokoine University of Agriculture (SUA), at 68,500 S and 378,390 E, at an elevation of 579 m in Morogoro, Tanzania. TZs is located at the Solomon Mahlangu Campus of SUA (at an elevation of 512 m), which is ca. 7 km from TZc. At TZc, the mean annual temperature is 24.5 8C (2000–2005), and the annual rainfall range is 750–1000 mm. Although no climate data are available for TZs, generally annual rainfall is less than that at TZc. In the current study, total rainfall recorded during the 16-month experimental period was 1339 and 1160 mm at TZc and TZs, respectively. Average air temperature in each site was similar during the experimental period (24.8 8C at TZc and 25.2 8C at TZs). In this area, the rainy season is usually bimodal. The long rainy season (mid-February to May) is more reliable and better distributed for cropping, whereas the duration/intensity of the short rainy season (October to December) is less predictable. In the current study, maize was cultivated during the long rainy season in 2007 and 2008 at both sites. At TZc, maize had been planted every year since 2003, whereas the TZs cropland had been fallow from 1998 to 2005, and millet was planted in 2006. The soil at TZc is Kanhaplic Haplustults, and the soil at TZs is Ustic Quartzipsamments (Soil Survey Staff, 2006). Table 1 presents detailed soil characteristics of the plow layer (0–15 cm). Soil organic matter and water holding capacity (WHC) were substantially lower at TZs compared to those at TZc, due to little clay content. 2.2. Experimental design The experimental design included the following four treatments: (1) Control (nothing applied to the soil); Ctrl plot. (2) Chemical fertilizer-treated plot (100 kg N ha1 and 50 kg P ha1); F plot. (3) Plant residue-treated plot; P plot. (4) Plant residue and chemical fertilizer-treated plot; PF plot. Each experimental plot (8 m  8 m) was laid down in a randomized block design using three replicate plots per treatment; an unplanted strip of >1 m separated each block. In the P and PF plots, plant residue was applied in July 2005 (only at TZc), July 2006, March 2007, July 2007, and March 2008, as follows: maize straw and leaves were chopped into 10-cm pieces and incorporated into the soil (15 cm depth) using hand hoes. Table 2 indicates the date and amount of each plant residue treatment. The amount of added plant material C (and N) was determined by measuring the dry weigh and C (and N) content of plant material. The C (and N) content of plant material was measured using a dry combustion method with an NC analyzer (Vario Max CHN, Elementar). Chemical fertilizer in the F and PF plots was applied as follows: urea was broadcasted separately, 35 kg N ha1 at 1 week after planting maize, and 65 kg N ha1 at 5– 6 weeks after planting maize, respectively, and triple super phosphate was broadcast at the time of seeding (50 kg P ha1) (Table 2). Maize was planted on 15 March 2007 and 23 March 2008

Table 1 Soil characteristics in the plow layer (0–15 cm) at the TZc and TZs sites at February 2007. Site

Total C (gC kg1 soil)

Total N (gN kg1 soil)

pH (1:5 water)

TZc TZs

12.4 3.8

1.1 0.4

6.0 6.5

a b

Bulk density was measured by core methods. WHC means maximum water holding capacity.

Soil texture (%) Sand

Silt

Clay

56.0 91.7

10.9 3.3

33.1 4.9

Bulk densitya (g cm3)

WHCb (%)

1.2 1.6

58.3 26.1

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Table 2 Description of the crop cultivation and land management schedule. TZc Date

TZs Crop cultivation

30-July-05 29-July-06 5-March-07 15-March-07 21-March-07 25-April-07 5-July-07 15-July-07

Seeding

Date –

Harvest

5-March-08 23-March-08 30-March-08 27-April-08 3-July-08

Land managements Plant residue application (2.5 t C ha1, 35 kg N ha1) Plant residue application (5 t C ha1, 70 kg N ha1) Plant residue application (2.5 t C ha1, 35 kg N ha1) P fertilizer application (50 kg P ha1) N fertilizer application (35 kg N ha1) N fertilizer application (65 kg N ha1)

Seeding

Plant residue application (5 t C ha1, 70 kg N ha1) Plant residue application (2.5 t C ha1, 35 kg N ha1) P fertilizer application (50 kg P ha1) N fertilizer application (35 kg N ha1) N fertilizer application (65 kg N ha1)

Harvest

at TZc, and on 14 March 2007 and 22 March 2008 at TZs. The crop was harvested on 5 July 2007 and 3 July 2008 at TZc, and on 20 June 2007 and 28 June 2008 at TZs (Table 2). 2.3. Soil environmental monitoring At both TZc and TZs, air temperature and soil temperatures at a depth of 5 cm were measured. The monitoring was done hourly in two replicates for both the Ctrl and PF plots. The volumetric moisture content in the surface soil (0–15 cm) was also monitored hourly for the Ctrl plot using a data logger system (107 thermistor probes for temperature and CS616 for soil volumetric moisture were connected to a CR-10X data logger; Campbell Scientific, Inc.). Rainfall was also monitored hourly at both sites using the same CR10X data logger system and a TE525MM device (Campbell Scientific, Inc.). 2.4. Soil sampling and analyses Soil samples were collected 25 times at TZc and 24 times at TZs during the experimental period (from March 2007 to June 2008; 16 months). We conducted soil sampling especially focused on the crop growth season, i.e., March to June. In addition, we also collected soil samples before and after plant residue treatment. For each sample, six soil cores (2 cm diameter  15 cm depth) were taken inside the plot (7 m  6 m; avoiding the plot edge), and the six soil samples were combined and mixed per each replicate. Soil samples were immediately transported to the lab in a 4 8C cooler, sieved through a 4-mm mesh screen after removing visible plant debris, and stored under field-moist conditions at 4 8C until analysis. Samples were taken for determination of gravimetric soil moisture, inorganic N (NH4+ and NO3), MBC, and MBN. All measurements, except for soil moisture, were conducted after transport to Japan within 3 months of sampling. After sieving, 10.0 g of each soil sample was weighed in an aluminum dish and placed in a 105 8C oven for 48 h, and the dry weight was recorded. Gravimetric soil moisture was the difference in soil weight before and after oven drying. Inorganic N was extracted from 10.0 g soil (dry base) with 30.0 ml of 1 M KCl for 30 min on an orbital shaker, and the suspension was centrifuged and filtered through filter paper (Advantec No. 5C). NH4+ in the extract was determined using the modified indophenol blue method (Rhine et al., 1998), and NO3 in the extract was determined using the modified Greisess Ilovay method (Mulvaney, 1996). MBC and MBN were measured

Crop cultivation

30-July-06 3-March-07 14-March-07 21-March-07 18-April-07 20-June-07 28-June-07

Seeding

Plant residue application (2.5 t C ha1, 35 kg N ha1) Plant residue application (2.5 t C ha1, 35 kg N ha1) P fertilizer application (50 kg P ha1) N fertilizer application (35 kg N ha1) N fertilizer application (65 kg N ha1)

Harvest

3-March-08 22-March-08 29-March-08 26-April-08 28-June-08

Land managements

Seeding

Plant residue application (5 t C ha1, 70 kg N ha1) Plant residue application (2.5 t C ha1, 35 kg N ha1) P fertilizer application (50 kg P ha1) N fertilizer application (35 kg N ha1) N fertilizer application (65 kg N ha1)

Harvest

using the fumigation-extraction method (Brookes et al., 1985; Vance et al., 1987). Briefly, soil samples (8.0 g dry base) were fumigated with ethanol-free CHCl3 for 24 h at 25 8C. If the soil moisture content was under 40% water holding capacity, the soils were rewetted to ca. 40% water holding capacity before fumigation (Sparling and West, 1989; Mueller et al., 1998). After removal of the CHCl3, soluble C and N were extracted from the fumigated and non-fumigated samples with 32.0 ml of 0.5 M K2SO4 for 30 min on an orbital shaker. Total organic C and extractable N in the filtered extract were determined using a TOC-N Auto-analyzer (TOC-V carbon analyzer with an IN unit, Shimadzu). Microbial C flush (difference between extractable C from fumigated and nonfumigated samples) was converted to MBC using a KEC factor of 0.45 (Vance et al., 1987). Microbial N flush was also converted to MBN using a KEN factor of 0.54 (Brookes et al., 1985). All measurements were done in duplicate. The K2SO4-extractable C from non-fumigated soil samples was used as a measure of extractable C (Ext-C), which indicates the amount of labile C (Beck et al., 1997; Hamel et al., 2006). In addition, we calculated the ratio of MBC to total C (MBC/TC) and the ratio of MBN to total N (MBN/TN), to evaluate the effect of land managements and soil texture on the labile fraction of soil organic matter. 2.5. In situ microbial activity as qCO2 We evaluated the microbial activity as qCO2 in view of the efficiency of soil organic matter decomposition, although qCO2 is commonly termed as metabolic quotient (Anderson and Domsch, 1993). We measured the CO2 efflux rate as soil respiration in situ using a closed-chamber system (Funakawa et al., 2006). The CO2 efflux rate was always measured in the morning (between 8:00 and 11:00), which was the same day of soil sampling. We divided the measured CO2 efflux rate by the MBC to yield the qCO2 value. In the calculation, both the CO2 efflux rate and MBC were expressed on an area basis (g m2 h1 and g m2, respectively). As soil respiration consists of plant-root respiration and microbial respiration, we excluded the plant-root respiration using the trenching method according to Shinjo et al. (2006). Polyvinyl chloride cylinders (diameter 13 cm, height 30 cm) were inserted into the soil to a depth of 15 cm, and the enclosed soil was later covered with a fine plastic mesh to support the soil in the core sample. These were conducted at the end of February 2007. At each measurement, the cylinder was removed once together with the

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soil inside them to cover the bottom with a plastic sheet and thus to suppress root respiration. We sampled the gases in the headspace of the polyvinyl chloride cylinder at 0 and 40 min after the top of the cylinder was covered with a plastic sheet. After each measurement, we removed the plastic sheet and returned the cylinder to the soil body, allowing free percolation of water. The CO2 efflux rate was calculated based on the increase of CO2 concentration in the cylinder after 40 min. Gas samples were analyzed with an infrared CO2 controller (ZFP9AA11; Fuji Electric). Five replicate measurements were made for each plot. 2.6. Statistical analyses To assess the factors that control the seasonal variations in soil microbial biomass, Pearson’s correlation coefficient was used to estimate overall correlations for measured variables in all the plots. The effects of treatment and sampling time (seasonal effect) were assessed using repeated-measures analysis of variance. The Tukey’s test was used to detect statistically significant differences between treatments (p < 0.05). All variables were tested for normality of the distribution and transformed when necessary to minimize deviance. All statistical analyses were performed with SYSTAT v.11 (SYSTAT Software, Inc.). All data are expressed on a dry-weight basis.

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sites remained high (23–28% at TZc and 15–18% at TZs) during the rainy seasons but was quite low (10–15% at TZc and 2–5% at TZs) during the dry seasons, i.e., June–October 2007, December 2007– January 2008, and May–June 2008 (Fig. 1a and c). Soil moisture content at TZs was continuously lower than that at TZc throughout the experimental period, due to low WHC of sandy soil. Average daily soil temperature during the experimental period was 28.8 and 27.3 8C in the C and PF plots at TZc, and 29.1 and 28.2 8C in the Ctrl and PF plots at TZs, respectively (Fig. 1b and d). Soil and air temperatures at the two sites fluctuated similarly throughout the experimental period. Soil temperature in the PF plot was continuously lower by ca. 1–2 8C compared with the Ctrl plot at both sites. The difference was presumably caused by plant residue application, as observed by Tilander and Bonzi (1997). NO3 and NH4+ in the TZc Ctrl plot fluctuated substantially from 3.3 to 35.4 mg N kg1 soil (coefficient of variation (CV) 63.6%) and from 2.4 to 18.4 mg N kg1 soil (CV 60.1%). In the TZs Ctrl plot, NO3 and NH4+ also fluctuated substantially from 0.3 to 16.2 mg N kg1 soil (CV 44.5%) and from 1.5 to 15.5 mg N1 kg soil soil (CV 67.3%). Ext-C in the TZc Ctrl plot fluctuated a little from 80.7 to 125.1 mg C1 kg soil (CV 9.9%), whereas that in the TZs Ctrl plot fluctuated to a greater degree from 18.7 to 45.8 mg C1 kg soil (CV 19.8%). 3.2. Seasonal variations in soil microbial biomass

3. Results and discussion 3.1. Seasonal variations of soil environments and nutrients The rain fell primarily during the rainy seasons (ca. 80% of total rain at both sites), i.e., March–May 2007, November–December 2007, and March–April 2008, so that soil moisture content in both

MBC and MBN in the TZc Ctrl plot fluctuated substantially from 111 to 262 mg C kg1 soil (CV 22.8%) and from 10.0 to 23.2 mg N kg1 soil (CV 21.2%), respectively (Fig. 2A). In the TZs Ctrl plot, MBC and MBN also fluctuated substantially from 32.1 to 119 mg C kg1 soil (CV 36.4%) and from 3.4 to 15.9 mg N kg1 soil (CV 41.5%), respectively (Fig. 2B). According to a review by Wardle

Fig. 1. Fluctuation in volumetric moisture content (VMC) at the Ctrl plot as a function of daily rainfall at the TZc (a) and TZs sites (c), and daily averaged air and soil (5 cm) temperatures at the Ctrl and PF plots at TZc (b) and TZs (d). VMC and soil temperature data from middle March to May 2008 at TZc and from December 2007 to February 2008 at TZs could not be obtained because of technical problems with the sensors.

Fig. 2. (A) Temporal variations in microbial biomass C (a) and N (b) and in qCO2 (c) at the TZc plots. The three downward-pointing arrows indicate plant residue application, and the four upward-pointing arrows indicate N application. Bars indicate the standard error. (B) Temporal variations in microbial biomass C (a) and N (b) and in qCO2 (c) at the TZs plots. The three downward-pointing arrows indicate plant residue application, and the four upward-pointing arrows indicate N application. Bars indicate the standard error.

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S. Sugihara et al. / Applied Soil Ecology 44 (2010) 80–88

(1998), these CVs of MBC and MBN are comparable with those reported in similar studies. In 2007 and 2008, MBC and MBN in all treatment plots at both sites tended to decrease and remain low during the rainy season and tended to increase and remain high during the dry season (Fig. 2A and B). Many explanations have been given for such seasonal variations in MBC and MBN in dry tropical ecosystems: (1) increased soil fauna during the rainy season increases grazing on soil microbes, thereby reducing their population (Singh et al., 1989; Michelsen et al., 2004), and (2) soil microbes accumulate intracellular solutes during the dry season; as a result, the drastic changes in soil moisture content after the first rainfalls of the rainy season lead to microbe lysis and a dramatic drop in their population (Halverson et al., 2000; Fierer and Schimel, 2003). Because MBC and MBN gradually decreased during the rainy season in our study, the increased soil fauna seems to be a more reasonable explanation for the observed decrease in soil microbes in the rainy season because the effect of soil moisture change would be to trigger rapid depletion of soil microbes (Fierer and Schimel, 2003). With regard to crop growth stage, MBN in both Ctrl plots appeared to remain low during the crop maturation stage, i.e., the middle to late crop growth period and the early dry season. As indicated by Singh et al. (2007b), crop N uptake during the maturation stage gave rise to the severe N competition between crop and soil microbes, thereby remaining low MBN at this period. These results suggest that soil microbes act as a nutrient pool for crop growth both in clayey and sandy croplands in Tanzania. To date, many studies evaluating the seasonal dynamics of MBC and MBN in the dry tropics have reported that MBC and/or MBN correlate negatively with soil moisture (Singh et al., 1989; Raghubanshi, 1995; Kushwaha et al., 2000; Tripathi and Singh, 2007); however, these conclusions were based on the analysis of samples taken only 1–3 times during the rainy and dry seasons. In the current study, we found no significant relationship between soil moisture and MBC and MBN (Table 3). We measured MBC and MBN 5–7 times during the rainy season (in total, 25 and 24 times at TZc and TZs, respectively), and soil microbes gradually decreased throughout the rainy season both in 2007 and 2008. Thus, there was no clear correlation between soil moisture and MBC or MBN, though we observed the clear effect of soil moisture on MBC and MBN. Based on above results and discussion, we concluded that soil moisture strongly affected the seasonal variations in MBC and MBN, so that soil microbes acted as a nutrient source during the rainy season and as a sink in the dry season in both agroecosystems.

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3.3. Seasonal variations in microbial activity as qCO2 qCO2 in the TZc Ctrl plot fluctuated substantially from 0.02 to 5.84 (CV 120.9%; 25.1% after normalization), and qCO2 in the TZs Ctrl plot also fluctuated substantially from 0.43 to 8.25 (CV 83.9%; 44.5% after normalization) (Fig. 2A and B). qCO2 was clearly high during the rainy season at both sites, whereas it was low during the dry season, and qCO2 levels strongly correlated with soil moisture in all plots (Table 3). These results suggest that soil organic matter decomposition mainly occurred in the rainy season, and this is consistent with other studies done in dry tropical ecosystems (Chen et al., 2002; Garcı´a-Oliva et al., 2003; Cookson et al., 2006). In addition, high qCO2 and low MBC in the rainy season also suggest the fast turnover rate of soil microbes, leading to faster nutrients supply through soil microbes in this period (Joergensen and Emmerling, 2006). Based on these results, we concluded that soil microbes acted as decomposers mainly in the rainy season. 3.4. Effect of plant residue and fertilizer application on soil microbial dynamics Table 4 presents the average amounts of soil microbial and nutrients variables during the experimental period at the TZc and TZs sites of each treatment. We found that plant residue and fertilizer application did not affect these variables clearly, except for MBN and MBN/TN of soil in the TZc P and PF plots. In addition, plant residue and fertilizer application had less effect on the variations of MBC, MBN, and qCO2 at both sites as compared to the effect of sampling date (Table 5). Spedding et al. (2004) also found that the seasonal effect on soil microbial dynamics was larger than the effect of land management, i.e., tillage and residue application in Canada. On the other hand, they also found a distinct effect of land management on temporal variations in MBC and MBN. In our study, we observed an effect of plant residue application on seasonal variations in MBN at both sites (Table 5), and also found the increased MBC and MBN in both sites after the addition of plant residue at the beginning of March in 2007 and 2008, i.e., the early rainy season. Furthermore, the increased MBN were maintained relatively high in the P and PF plots at both sites as compared with the Ctrl and F plots until the end of the crop growth period. These results indicate that seasonal variations in MBC and MBN can be controlled, at least short-term, by plant residue application early in the rainy season. Singh et al. (2007b) also reported a rapid increase in MBC and MBN just after

Table 3 Correlation coefficient between soil microbial factors and soil nutrient and environment factors in each treatment plot and all treatment plots at the TZc and TZs sites. TZc

Ctrl plot (n = 25)

P plot (n = 25)

F plot (n = 25)

PF plot (n = 25)

All treatment plots (n = 100)

MBC

MBN

qCO2

MBC

MBN

qCO2

MBC

MBN

qCO2

MBC

MBN

qCO2

MBC

MBN

qCO2

NH4+ N03 Inorg-N Ext-C Soil moist.

NSa NS NS NS NS

NS NS NS NS NS

NS NS NS NS 0.79**

NS NS NS NS NS

NS NS NS NS NS

NS NS 0.40* NS 0.66**

NS NS NS NS NS

NS NS NS NS NS

0.39* 0.40* 0.45* NS 0.69**

NS NS NS NS NS

NS NS NS NS NS

0.38* 0.44* 0.55** NS 0.69**

NS NS NS NS NS

0.29** NS 0.23* NS NS

0.36** 0.31** 0.39** NS 0.71**

TZs

Ctrl plot (n = 24)

NH4+ NO3 Inorg-N Ext-C Soil moist. a * **

P plot (n = 24)

F plot (n = 24)

PF plot (n = 24)

All treatment plots (n = 96)

MBC

MBN

qCO2

MBC

MBN

qCO2

MBC

MBN

qCO2

MBC

MBN

qCO2

MBC

MBN

qCO2

NS NS NS NS NS

0.66** NS 0.45* NS NS

0.41* NS 0.41* NS 0.60**

NS NS NS NS NS

NS 0.49* NS NS NS

0.54** NS 0.64** NS 0.61**

NS NS NS NS NS

0.52** NS NS NS NS

NS NS NS NS 0.57**

NS NS NS NS NS

0.47* NS NS NS NS

0.41* NS 0.46* NS 0.70**

NS NS NS 0.28** NS

0.49** NS NS 0.23* NS

0.38** NS 0.32** NS 0.52**

NS means not significant. p < 0.05. p < 0.01.

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Table 4 Average soil microbial and nutrients variables during the experimental period (n = 25 in TZc, n = 24 in TZs). Site

Treatment

MBC (mg C kg1 soil)

MBN (mg N kg1 soil)

MB C/Na

MBC/TCb (%)

MBN/TNb (%)

qCO2 (CO2-C MBC1 h1)

NO3 (mg N kg1 soil)

NH4+ (mg N kg1 soil)

Inorg-N (mg N kg1 soil)

Ext-C (mg C kg1 soil)

TZc

Ctrl P F PF

163.1 189.9 161.0 191.3

a a a a

16.8 21.6 17.2 22.3

b a b a

9.9 9.1 9.8 9.1

a a a a

1.3 1.5 1.3 1.5

a a a a

1.5 2.0 1.6 2.0

b a b a

1.2 1.8 1.5 1.8

a a a a

14.3 16.6 22.6 27.8

b b ab a

6.9 9.8 9.0 11.6

b ab ab a

21.2 26.3 31.6 39.4

c bc ab a

100.5 113.1 113.2 103.0

b a a b

TZs

Ctrl P F PF

68.1 75.5 65.7 70.2

A A A A

8.3 10.2 8.2 9.6

A A A A

9.1 8.0 9.5 8.1

A A A A

1.8 2.0 1.7 1.8

A A A A

2.1 2.6 2.1 2.4

A A A A

2.8 4.5 3.7 4.9

A A A A

9.1 9.2 15.9 11.4

B B A AB

6.1 7.1 7.1 8.5

A A A A

15.2 16.4 23.0 19.8

B B A AB

30.1 31.8 31.9 31.0

A A A A

Different letters indicate significant differences between treatments at each of the study site (Tukey’s test, p < 0.05). a MB C/N means the ratio of MBC to MBN. b MBC/TC and MBN/TN mean the ratio of MBC to total C of soil and the ratio of MBN to total N of soil, respectively.

Table 5 Summary of effects according to repeated-measures analysis of variance. Source

Plant residue application (P) Sampling date (season) Season  P Fertilizer application (F) Season Season  F PF Season Season  PF a

MBC

MBN

qCO2

TZc

TZs

TZc

TZs

TZc

TZs

NSa <0.0001 NS NS <0.0001 NS 0.02 <0.0001 NS

NS <0.0001 NS NS <0.0001 NS NS <0.0001 NS

0.05 <0.0001 NS NS <0.0001 NS 0.03 <0.0001 <0.0001

0.02 <0.0001 0.02 NS <0.0001 NS 0.05 <0.0001 NS

0.002 <0.0001 <0.0001 0.04 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001

0.01 <0.0001 <0.0001 NS <0.0001 <0.0001 0.03 <0.0001 <0.0001

NS means not significant.

residue application (within a month) during the early rainy season in India. It is important to synchronize crop N uptake and N release from soil microbes in the rainy season in dry tropical agroecosystems to minimize N loss from soil (Singh et al., 2007a). In particular, N leaching during the early rainy season (seeding and tillering stage for crop growth stage) leads to critical N loss, because plants are still small and take up little N at this period (Shahandeh et al., 2004). In the current study, temporally increased MBN by plant residue application suggest that it may contribute to reduce N leaching in the early rainy season (Herai et al., 2006), and to synchronize the crop N uptake and N release from soil microbes in the late crop growth period (i.e., maturation stage), though further studies are needed to verify these possibilities. The effect of plant residue application during the dry season (i.e., the end of June) on MBC and MBN levels was unclear at both sites, except for MBN in the TZc PF plot (Fig. 2A and B). Zaman et al. (1999) showed that both sufficient C substrate and favorable soil moisture conditions are necessary to increase MBC and MBN. Hence, we presume that, due to reduced soil moisture during the dry season, soil microbial biomass did not expand in the P and PF plots after application of plant residue. The effect of plant residue application on seasonal variation in qCO2 was substantial and was maintained for the entire experimental period, whereas the effect of N fertilizer application on qCO2 disappeared within a month (Fig. 2A and B). Even in the dry season, addition of plant residue increased qCO2 at both sites, although it did not increase MBC and MBN. These results suggest that the effect of plant residue application on qCO2 was greater than that of fertilizer application. N fertilizer application sometimes increased MBN just after application, but this increase was only transient (Fig. 2A and B). A previous study in Costa Rica also showed that N fertilizer application increased the MBN, but that MBN then declined rapidly within 20–40

days (Mazzarino et al., 1993). In our study, because of N leaching and crop N uptake, inorganic N in soils decreased to a similar level in all treatment plots 1 month after the second N fertilizer application (data not shown), and therefore N fertilizer application did not have a long-term effect on soil microbial dynamics. Because heavy N leaching generally occurs during the rainy season in croplands in similar climates (Shahandeh et al., 2004; Singh et al., 2007a), it is important to improve N use efficiency of crops in tropical agroecosystems. In the present study, MBN in the TZc PF plot clearly increased compared with MBN in the P and F plots after the first N fertilizer application in 2007 (Fig. 2A-b). This suggests that application of plant residue along with N fertilizer is an effective option to increase N use efficiency as suggested by Herai et al. (2006). Based on above results and discussion, we concluded that the application of soil microbes as an ephemeral nutrient pool (e.g., by plant residue application) is an important concept/option in this agroecosystem to synchronize the crop N uptake and N release from soil microbes to minimize the N loss. 3.5. Effect of soil texture on soil microbial dynamics MBC and MBN in the TZs Ctrl plot were substantially low compared to those in the TZc Ctrl plot, due to low soil organic matter (Table 4). In contrast, MBC/TC and MBN/TN were relatively higher in the TZs Ctrl plot compared to those in the TZc Ctrl plot. These results suggest that soil microbes both in sandy and clayey soil have an important role as a labile nutrient pool, though the amount of MBN was small in sandy soil. In addition, we found that inorganic N factors in the TZs Ctrl plot correlated with MBN and qCO2, whereas inorganic N factors did not correlate with soil microbes in the TZc Ctrl plot (Table 3). Ext-C correlated with MBC and MBN only in the all TZs treatment plots, but this was not the case at the other treatment plots. Because Matlou and Haynes (2006) indicated that water-extractable C give more realistic value

S. Sugihara et al. / Applied Soil Ecology 44 (2010) 80–88

as labile substrate than K2SO4-extractable C, we may miss the clear effect of C substrate variations on soil microbial dynamics in the current study. These results suggest that the seasonal variations in available soil N (and possibly C) also influenced the seasonal variations in MBC, MBN and qCO2 as substrate for soil microbes in the nutrient-poor tropical sandy soil (Tu et al., 2006). Seasonal variations in MBC, MBN, and qCO2 were similarly fluctuated in clayey and sandy soils during the experimental period, but the CVs of MBC and MBN during the experimental period were higher at TZs than at TZc. It suggests that seasonal variations in MBC and MBN were greater at TZs than at TZc. This is because soil microbes in clayey soil are protected from macro-fauna (i.e., predators), by clay (Juma, 1993) and from dry stress by soil aggregates (Van Gestel et al., 1991), and hence soil microbial biomass is relatively steady in clayey soil compared with sandy soil. Similarly, qCO2 was substantially higher and fluctuated to a greater degree at TZs than at TZc. Many laboratory studies have shown that qCO2 in sandy soil is higher than that in clayey soil (Hassink, 1994; Thomsen et al., 2003), and our field results are consistent with those results. Large variations in both MBC and MBN and a high qCO2 imply rapid turnover of soil microbes (McGill et al., 1986; Joergensen and Emmerling, 2006), resulting in an increased nutrient supply through the soil microbes. Using the method outlined by McGill et al. (1986) and Friedel et al. (2001), we calculated the turnover rate of soil microbes in the Ctrl plot of TZc and TZs and found it to be 1.37 per year at TZc and 4.90 per year at TZs. It means that soil microbes should supply 41.4 and 91.5 kg N ha1 in a year, in the TZc Ctrl plot and the TZs Ctrl plot, respectively. Sakamoto and Hodono (2000) also showed that the turnover rate of soil microbes in sandy soil (4.38 per year; 7% clay) was more than twice that in clayey soil (1.69 per year; 39% clay). Based on these results and discussion, the nutrient dynamics in tropical agroecosystems appeared to be more substantially affected by soil microbes at TZs than at TZc. 4. Conclusion We found that seasonal variations in soil moisture control the observed seasonal variations in MBC, MBN, and qCO2 both in clayey and sandy soils of a tropical agroecosystem. Plant residue and fertilizer application also affect soil microbial dynamics, at least short-term, although these effects are relatively small compared with seasonal effects. Short-term increase of MBN by plant residue application suggests the applicability of soil microbes as an ephemeral nutrient pool to potentiate crop growth (e.g., the decrease of N leaching or synchronization of the crop N uptake and N release from soil microbes), though further studies are needed to verify this possibility. Finally, with regard to nutrient dynamics, the positive effects of soil microbes seem to be more important for sandy soil than clayey soil because of the large variations in MBN and fast turnover rate of soil microbes in sandy soil. Acknowledgments We thank Prof. J. J. T. Msaky and the staff of the Sokoine University of Agriculture for their kind technical support in the field and laboratory experiments in Tanzania. Our work was financially supported by the Kyoto University Foundation and Research Fellowship of the Japan Society for the Promotion of Science of Young Scientists. References Adeboye, M.K.A., Iwuafor, E.N.O., Agbenin, J.O., 2006. The effect of crop rotation and nitrogen fertilization on soil chemical and microbial properties in a Guinea Savanna Alfisol of Nigeria. Plant Soil 281, 97–107. Agele, S.O., Ewulo, B.S., Oyewusi, I.K., 2005. Effect of some soil management systems on soil physical properties, microbial biomass and nutrient distribution under

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