Applied Soil Ecology 145 (2020) 103346
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Short Communication
Time-series analysis of phosphorus-depleted microbial communities in carbon/nitrogen-amended soils
T
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Kazumori Misea,b, , Runa Maruyamac, Yuichi Miyabarad, Takashi Kunitoc, Keishi Senooa,e, Shigeto Otsukaa,e a
Department of Applied Biological Chemistry, Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo 113-8657, Japan b Department of Biological Sciences, Graduate School of Science, The University of Tokyo, 2-11-16 Yayoi, Bunkyo-ku, Tokyo 113-0032, Japan c Department of Environmental Sciences, Faculty of Science, Shinshu University, 3-1-1 Asahi, Matsumoto 390-8621, Japan d Institute of Mountain Science, Shinshu University, 5-2-4 Kogandori, Suwa 392-0027, Japan e Collaborative Research Institute for Innovative Microbiology, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo 113-8657, Japan
A R T I C LE I N FO
A B S T R A C T
Keywords: Phosphatase Phosphorus cycling Resource allocation Stoichiometry Microbial community
The mineralization of organic phosphorus (P) in soil is mainly driven by extracellular phosphatases secreted by soil microbes. Previous studies have suggested that microbial phosphatase production is regulated by soil nutrient stoichiometry and, thus, promoted by carbon and nitrogen (CN) amendment. However, the mechanism leading to increased phosphatase activity after nutrient amendment to soil is unclear, and it is not known how long the effect of the nutrient amendment lasts. To address these questions, we performed a 24-day time-series analysis of full-factorial soil microcosms with CN amendment. Phosphatase activity as well as that expressed per unit of β-D-glucosidase activity, increased sharply and significantly in response to the CN amendment. This suggests that the microbial community shifted their resource allocation after the nutrient amendment and preferentially produced phosphatases rather than β-D-glucosidase. This shifted resource allocation pattern was maintained throughout the 24-day incubation period, and copiotrophic microbes dominated soils that received CN amendment. These results indicate that the effect of the CN amendment on soil microbial resource allocation lasted for > 24 days. Together, our results highlight the importance of high-resolution time-series observations that complement long-term studies for which frequent observation is often difficult.
1. Introduction Phosphorus (P) is an essential macronutrient for all living organisms, including soil microbes and plants. Soil P mainly derives from weathering, and old soils are P-limited owing to chronic biological uptake and leaching loss of P (Hedin et al., 2003; Vitousek et al., 2010). Readily bioavailable forms of P are generally scarce in soil (Cleveland et al., 2002; Hou et al., 2018) and, therefore, chemical transformations of P-containing compounds are crucial for the maintenance of soil ecosystems. Aside from the free ionic phosphate form, P is present in soils as part of organic compounds and metallic salts (metallophosphates), which are enzymatically mineralized and chemically solubilized by organic acid secretion (Shen et al., 2011). The mobilized P is taken up by microbes and plants and converted into biomass P, thereby contributing to primary production and soil microbial functioning.
The production of P-mineralizing enzymes (i.e., extracellular phosphatases) may be positively or negatively regulated depending on microbial demand or the extent to which carbon (C) and nutrients other than P are present in the soil. According to the resource allocation model, soil microbes preferentially produce extracellular enzymes to consume little of the bioavailable nutrients in limited-resource environments (Taillefumier et al., 2017), presumably to maintain their cellular element composition (Sinsabaugh and Moorhead, 1994). Empirical studies have supported this theoretical prediction; the relative activity of phosphatase to C-acquiring enzymes was negatively correlated with bioavailable P concentration (Fujita et al., 2017; Moro et al., 2015). Long-term field studies have also suggested that monthly or yearly nitrogen (N) input enhances soil phosphatase activities (Olander and Vitousek, 2000; Weand et al., 2010; Zheng et al., 2015). In addition to soil microbial community functioning, microbial community
⁎ Corresponding author at: Department of Applied Biological Chemistry, Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo 113-8657, Japan. E-mail address:
[email protected] (K. Mise).
https://doi.org/10.1016/j.apsoil.2019.08.008 Received 14 December 2018; Received in revised form 23 August 2019; Accepted 26 August 2019 Available online 02 September 2019 0929-1393/ © 2019 Elsevier B.V. All rights reserved.
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microcosms to prevent any issues related to repeated sampling and/or reuse (i.e., heterogeneity within and between microcosms).
structure and gene content are also expected to respond adaptively to nutrient stoichiometry shifts (Yao et al., 2018). The studies mentioned above suggest that soil microbes tend to produce P-acquiring enzymes when soil P availability is low (more specifically, P availability relative to the availability of other elements such as C and N). Phosphatase activity, therefore, may be promoted by C and N addition. However, this prediction has the following limitations. First, the addition of CN sources to soils influences not only microbial enzyme production but also microbial community structure (Knelman et al., 2014) and activity (Demoling et al., 2007), which is also a potential cause of enhanced phosphatase activity. The distinction of these two factors, namely, a shift in microbial resource allocation and enhanced microbial abundance or activity, would be useful for understanding changes in phosphatase activity. Second, previous studies have not assessed how long the effects of such stoichiometry shifts persist. Considering the resilient nature of the soil microbial community (Griffiths and Philippot, 2013), one could predict that the influence of any nutritional amendment will attenuate with time. Nevertheless, this has not been quantitatively investigated. To date, there is a lack of highresolution time-series empirical datasets, and most previous long-term field studies have not observed temporal changes in soil enzyme activities or other chemical/biological factors (Olander and Vitousek, 2000; Weand et al., 2010; Zheng et al., 2015). To observe these factors in long-term studies would require costly sampling and is practically difficult. The purpose of the present study was two-fold. First, we aimed to confirm that CN amendment induces P-limited conditions and enhances soil phosphatase activity. Second, we sought to investigate the mechanisms underlying this stimulated phosphatase activity. More specifically, we sought to elucidate [i] whether this enhanced phosphatase activity is the outcome of a microbial shift in resource allocation and [ii] how long phosphatase activity remains stimulated after CN amendment. To this end, we performed soil microcosm incubation experiments with a full factorial design and time-series observations of soil enzyme activities and microbial community structure.
2.2. Soil chemical/biochemical analyses The total C and N content of the pre-incubated soils was measured using a nitrogen and carbon analyzer (Thermo Finnigan Flash EA1112; Thermo Fisher Scientific, Waltham, MA, USA). Soil samples at 0, 3, 10, 17, and 24 days incubation were subjected to enzyme activity measurements and prokaryotic community analyses. We measured alkaline phosphatase (ALP), acid phosphatase (ACP), and β-D-glucosidase (BG) activities using the methods described by Tabatabai (1994). Briefly, ALP and ACP activities were measured in modified universal buffer (MUB) at pH 11.0 and 6.5, respectively, using p-nitrophenyl phosphate as substrate. BG activity was measured in MUB at pH 6.0, using p-nitrophenyl-β-D-glucopyranoside as substrate. 2.3. Amplicon sequencing of the 16S rRNA gene Details on the experimental procedure and bioinformatics analysis are provided in Appendix B. Briefly, we extracted total DNA from each soil sample, used PCR to target the partial 16S rRNA gene, purified the PCR products, and then sequenced via Illumina sequencing-by-synthesis on MiSeq (Illumina, San Diego, CA, USA). The obtained nucleotide sequences were subjected to quality-filtering, operational taxonomic unit (OTU) clustering at the similarity threshold of 97%, taxonomic annotation on RDP classifier, and diversity analysis. Additionally, average rRNA gene copy number per cell was calculated as described by Nemergut et al. (2016) using PICRUSt (Langille et al., 2013). The amplicon sequence data were deposited in DDBJ/ENA/GenBank under the accession number DRA007564 (DRR157393–157518). Accession numbers of each sample are listed in Table A.2. 2.4. Statistical analyses We used a Welch's test to compare phosphatase activity and enzyme activity ratio at day 3 against the null hypotheses that phosphatase activity (or the ratio) were not enhanced by CN amendment. Transitions in soil enzyme activity on day 3 and later were evaluated by Spearman's rank coefficient test between soil enzyme activity (or the ratio) and length of incubation period. The effect of C source on soil enzyme activity ratio was assessed by PERMANOVA, using C source, CN amendment pattern, and incubation period as explanatory variables (1000 times randomization). Overall changes in beta-diversity of CNamended samples referred to control samples, and average rRNA gene copy numbers per cell were compared between incubation days using Games–Howell test. R 3.4.0 (R Core Team, 2017) was used for all the statistical analysis.
2. Materials and methods 2.1. Construction of soil microcosms We used two different kinds of soil (Table A.1), both of which were sampled in Nagano Prefecture, Japan. The first was an arable Andisol (hereafter referred to as "soil X"), and the second was a brown forest soil (referred to as "soil Y"). For each soil, we constructed 63 microcosms consisting of approximately 15 g of soil placed in Petri dishes. After five days of pre-incubation at 23 °C without light, three microcosms of each soil type were destructively sampled for time point "day 0." To 48 microcosms (of the remaining 60), we added a C source (glucose or cellobiose solution) and N source (ammonium chloride solution). We created two treatment groups: half of the microcosms (n = 24) were amended with 8.4 mg-C and 420 μg-N per gram of wet soil on day 0 (hereafter referred to as "high-CN group"), while the other half (n = 24) was amended with a quarter of those CN amounts at the beginning of the incubation period, with additional amendments every seven days ("accumulative CN group"). The total amount of amended C and N were the same in all samples after 24 days of incubation. Four types of treatments were prepared (besides the negative controls), representing two C sources (glucose vs. cellobiose) and two patterns of CN amendment (total CN dose added at the beginning of the incubation in the high-CN group vs. a quarter of that amount added at the beginning of the incubation and the rest added weekly in the accumulative CN group). The amendments and treatments are summarized in Table A.2. All microcosms were incubated at 23 °C and soil moisture was maintained by a daily supply of distilled water. Three microcosms per treatment type were destructively sampled on days 3, 10, 17, and 24. We designed this destructive sampling experiment using small
3. Results 3.1. Soil enzyme activities In the high-CN groups, ACP and ALP activities were significantly elevated after CN amendment in both soils (Welch's test, P < 0.05, Fig. 1A, Fig. A.2(A)(C)). The ratios of ACP/BG and ALP/BG activity also increased between day 0 and day 3 in both soils (Welch's test, P < 0.05, Fig. A.2(B)(D)), with the exception of ACP/BG in the cellobiose-amended soil X (although nearly significant: P = 0.051). The C source amendment significantly affected enzyme activity ratios: glucose-amended samples presented higher ratios than did cellobioseamended ones (PERMANOVA, P < 0.05; Fig. 1A, Fig. A.2). Although the normality of enzyme activities was not checked owing to the small sample size (n = 3), the rejection of the null hypothesis is reliable because the power of the parametric Welch test is weak (i.e., it tends to mistakenly accept null hypothesis) when the data is not normally 2
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Fig. 1. Temporal change in ACP activity (upper panel) and ACP/BG ratio (lower panel) of high-CN groups (A) and accumulative CN groups (B), throughout the 24day incubation period. Error bars represent standard errors.
Table 1 Transition of soil biochemical/microbial profiles (soil enzyme activities and soil enzyme activity ratios) from day 3 onward, evaluated using Spearman's rank coefficient with the length of incubation period. Treatment
High-CN group
Soil
Soil X Soil Y
Accumulative CN group
Soil X Soil Y
Amendment
Objective variables
Glucose + NH4Cl Cellobiose + NH4Cl Glucose + NH4Cl Cellobiose + NH4Cl Glucose + NH4Cl Cellobiose + NH4Cl Glucose + NH4Cl Cellobiose + NH4Cl
ACP
ACP/BG
ALP
ALP/BG
−0.842⁎⁎⁎ −0.842⁎⁎⁎ 0.876⁎⁎⁎ 0.691⁎ 0.972⁎⁎⁎ 0.950⁎⁎⁎ 0.928⁎⁎⁎ 0.734⁎⁎⁎
−0.518 0.367 0.065 −0.108 0.928⁎⁎⁎ 0.518 0.691⁎ 0.777⁎⁎
−0.453 −0.669⁎ 0.368 −0.271 0.928⁎⁎ 0.799⁎⁎ 0.820⁎⁎ 0.757⁎⁎
0.108 0.022 −0.238 −0.453 0.864⁎⁎⁎ 0.540 0.345 0.691⁎
Abbreviations: ACP, acid phosphatase; BG, β-D-glucosidase; ALP, alkaline phosphatase. ⁎⁎⁎ P < 0.001; ⁎⁎P < 0.01; ⁎P < 0.05
distributed (Rasch et al., 2011). Following the above-mentioned initial sharp increase, phosphatase activities varied temporally, depending on the treatment group and soil type. Beyond day 3, phosphatase activity for soil X was significantly diminished in the high-CN group, while they remained stable or slightly increased in soil Y (Spearman's correlation test, P < 0.05 for soil X and P > 0.05 for soil Y, Table 1). Conversely, ACP/BG and ALP/BG ratios did not consistently vary during the subsequent three weeks (P > 0.05, Table 1). For the accumulative CN groups, ACP and ALP activities in both soils significantly increased after the initial amendment of CN (Fig. 1B, Fig. A.2). In contrast to the high-CN group, soil X showed a gradual and linear increase in phosphatase activity throughout the incubation period. Soil Y, on the other hand, showed little difference between the amendment groups (Fig. 1, Table 1).
community structure was observed in all experimental groups (but not in the control group). Compared to day 3, the proportion of bacteria belonging to the phylum Firmicutes decreased at day 10 in soil X, while the proportion of bacteria of the phylum Proteobacteria did not change in soil Y. Prokaryotic community beta-diversity, estimated as weighted UniFrac distances between CN-amended samples and control samples, was significantly reduced in soil X but not in soil Y (Fig. 2(A), Fig. A.5(A)). An increase in the average rRNA gene copy number during the first three days of incubation was observed in both soils. In soil X, the average copy numbers peaked at day 3 and subsequently decreased, while in soil Y these values remained stable (Fig. 2(B), Fig. A.5(B)).
3.2. Soil prokaryotic community structure
The sharp increase in phosphatase activity after high-CN amendment (Fig. 1A, Fig. A.2) indicates that CN addition accelerated the release of P from recalcitrant organic P, in agreement with our prediction. Two underlying factors may have contributed to this result. One potential mechanism involves changes in microbial activity or microbial abundance: C presumably served as a microbial energy source, while N was used by microbes as the component of proteins. Accordingly, previous studies have shown that soil bacterial growth rate is enhanced by C input (Demoling et al., 2007) and microbial geochemical function is
4. Discussion
A total of 2,514,047 high-quality sequences and 7968 non-chimeric OTUs were obtained. The rarefaction curves suggest that most prokaryotic classes were detected, whereas some rare biosphere OTUs remained undetected (Fig. A.3). A sharp rise in the proportion of Firmicutes (soil X) and Proteobacteria (soil Y) members was detected after the initial soil perturbation (Fig. A.4). Even when subsequent transitions were less pronounced, a gradual change in the prokaryotic 3
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Fig. 2. Temporal change in beta-diversity (weighted UniFrac distance) between CN-amended samples and control samples (A) and average rRNA gene copy number per cell within the prokaryotic community of high-CN group samples (B). Error bars represent standard errors. Letter(s) above each bar indicate significant differences between incubation periods (P < 0.05) based on Games–Howell test.
high-CN groups of both soil types beyond day 3 (Table 1), suggesting that microbial resource allocation was sustained throughout the 24-day incubation period. Therefore, phosphatase activity reductions in soil X may be the consequence of decreased soil microbial activities, rather than changes in microbial resource allocation. In addition, neither prokaryotic community structures nor rRNA gene copy number per cell exhibited significant recovery to the control state after day 10 (Fig. 2, Fig. A.5). Given that fast-growing microorganisms favored by copiotrophic environments tend to harbor multiple rRNA genes (Roller et al., 2016), a high average rRNA copy number is an indication of a copiotrophic environment that filters fast-growing microbes (Nemergut et al., 2016). Thus, the temporal stability we observed may indicate that the effect of CN amendment persisted throughout these incubation experiments. This highlights the effectiveness of our high-resolution timeseries observation, which was lacking in previous long-term experiments. Nevertheless, it remains unclear how long the effect of CN amendment actually persists. This may require elaborate time-series observations, spanning longer periods, which would certainly provide useful information on soil nutrient managements. In the accumulative CN groups, trends in enzyme activities were partly coincident with those observed for the high-CN groups: enzyme activities in soil Y, but not in soil X, strongly correlated with those found in high-CN groups (Fig. A.2). Additionally, in the high-CN groups, the transitions in ACP activity was opposite between two soils (Table 1). These discrepancies could be explained by the differences in soil elemental stoichiometry. Soil Y had higher bioavailable C:P and N:P ratios than those of soil X (Table A.1), indicating that C and N limitation was rather subtle. The amount of C and N required to induce P-limitation (and thereby to accelerate P turnover processes) was probably smaller in soil Y than in soil X. This is consistent with the results of previous field studies in which the effect of N amendment on microbial and enzymatic activities is more positive in N-deficient soils than in Nrich soils (Castle et al., 2017; Olander and Vitousek, 2000). Nevertheless, additional factors such as vegetation or other undocumented physicochemical properties may also have affected our results (Weand et al., 2010). Overall, our results confirm that soil CN amendment enhances phosphatase activity. It is likely that this was not only the result of an increase in microbial abundance or total activity but also due to a shift in microbial resource allocation. We have shown that the shifted resource allocation was maintained throughout the whole 24-day incubation period, reflecting the copiotrophic state of our soils. Phosphatase activity, on the other hand, was not maintained. Finally, we found that the transitions in phosphatase activity were notoriously asynchronous between the two soils and may be explained differences in soil elemental stoichiometry. Here we highlight two possible implications for resource deposition
strongly affected by microbial abundance (Graham et al., 2014). This mechanism is consistent with the observed increase in BG activity after CN amendment in our study. The second possible mechanism involves changes in microbial resource allocation. Soil microbes are known to invest resources (energy and cellular components) into the production of extracellular enzymes for acquiring an element that limits their growth (Fujita et al., 2017; Sinsabaugh and Moorhead, 1994). In our experiment, CN input may have put soil microbes into P-limited condition, thereby prompting phosphatase secretion. To examine whether the observed changes were the outcome of shifts in microbial resource allocation, we calculated enzyme activity ratios (Fujita et al., 2017; Sinsabaugh and Moorhead, 1994). The increase in ACP/BG and ALP/BG suggests that CN amendment preferentially induced microbial production of phosphatases. These enzymatic ratios were higher in the glucose-amended microcosms than in their cellobiose-amended counterparts (Fig. 1, Fig. A.2). Compared to glucose, cellobiose requires enzymatic decomposition before it can be incorporated into cells (Steinweg et al., 2008) and may, therefore, be considered a more recalcitrant C source. Thus, microbial communities in cellobiose-amended treatments may have been at a disadvantage for phosphatase production, which is in line with the resource allocation hypothesis. Collectively, the present study indicates that CN amendments induced the preferential production of P-acquiring enzymes (phosphatases) to C-acquiring enzymes (glucosidase). This potentially led to stimulated mineralization of organic P; this could be confirmed by tracking the transitions of soil P concentrations. The shift in resource allocation also coincides with the molecular machinery of bacterial extracellular phosphatase production, where extracellular phosphate scarcity activates the inducer protein of phosphatase-production-related operons, prompting the production and secretion of extracellular phosphatases (Vershinina and Znamenskaya, 2002). Previous field studies have investigated the effect of long-term (months or years) N input on soil phosphatase activity. In these studies, the changes in soil phosphatase activity were less sharp than those in our experiments (Olander and Vitousek, 2000; Weand et al., 2010; Zheng et al., 2015). In our experiment, we added labile C with N, meaning that the soil received more intense perturbation than that in previous studies. This may explain why soil phosphatase activity increased sharply in response to CN amendment. CN input in our experiment acting as strong perturbation to the soil ecosystem is also supported by the sharp transitions in prokaryotic community structure that we observed between days 0 and 3 (Fig. A.4). Soil microbial ecosystems often recover to their initial state after receiving pulse perturbations (Shade et al., 2012) and, according to this, soil microbial resource allocation (represented by enzyme activity ratios) and community structure may rapidly return to the initial state. However, we found that ACP/BG and ALP/BG ratios remained stable in
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studies, both of which are obtained from high-resolution time-series observation. First, the evaluation of the soil microbial response to resource amendment can be measured by enzyme activity itself or by microbial resource allocation (enzyme activity ratio; Olander and Vitousek, 2000; Sinsabaugh and Moorhead, 1994). These two measurements presented quite different trends in our experiment: the effect on microbial resource allocation (or microbial community) may be more persistent than the effect on enzyme activity. Second, the effect of soil type (soil elemental stoichiometry, in particular). In our experiment, the transitions of phosphatase activity (or enzyme activity ratios) were variable between the two soils, although the initial increases were similar. This suggests that soil elemental stoichiometry may affect how long the effect of resource input lasts. Together, these two implications highlight the importance of high-resolution time-series observations as a complement to long-term studies where frequent observation is difficult. Supplementary data to this article can be found online at https:// doi.org/10.1016/j.apsoil.2019.08.008.
180166. https://doi.org/10.1038/sdata.2018.166. Knelman, J.E., Schmidt, S.K., Lynch, R.C., Darcy, J.L., Castle, S.C., Cleveland, C.C., Nemergut, D.R., 2014. Nutrient addition dramatically accelerates microbial community succession. PLoS One 9. https://doi.org/10.1371/journal.pone.0102609. Langille, M.G.I., Zaneveld, J., Caporaso, J.G., McDonald, D., Knights, D., Reyes, J.A., Clemente, J.C., Burkepile, D.E., Vega Thurber, R.L., Knight, R., Beiko, R.G., Huttenhower, C., 2013. Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences. Nat. Biotechnol. 31, 814–821. https://doi. org/10.1038/nbt.2676. Moro, H., Kunito, T., Sato, T., 2015. Assessment of phosphorus bioavailability in cultivated Andisols from a long-term fertilization field experiment using chemical extractions and soil enzyme activities. Arch. Agron. Soil Sci. 61, 1107–1123. https:// doi.org/10.1080/03650340.2014.984697. Nemergut, D.R., Knelman, J.E., Ferrenberg, S., Bilinski, T., Melbourne, B., Jiang, L., Violle, C., Darcy, J.L., Prest, T., Schmidt, S.K., Townsend, A.R., 2016. Decreases in average bacterial community rRNA operon copy number during succession. ISME J. 10, 1147–1156. https://doi.org/10.1038/ismej.2015.191. Olander, L.P., Vitousek, P.M., 2000. Regulation of soil phosphatase and chitinase activity by N and P availability. Biogeochemistry 49, 175–190. https://doi.org/10.1023/ A:1006316117817. R Core Team, 2017. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/. Rasch, D., Kubinger, K.D., Moder, K., 2011. The two-sample t test: pre-testing its assumptions does not pay off. Stat. Pap. 52, 219–231. https://doi.org/10.1007/s00362009-0224-x. Roller, B.R.K., Stoddard, S.F., Schmidt, T.M., 2016. Exploiting rRNA operon copy number to investigate bacterial reproductive strategies. Nat. Microbiol. 1, 16160. https://doi. org/10.1038/nmicrobiol.2016.160. Shade, A., Peter, H., Allison, S.D., Baho, D.L., Berga, M., Bürgmann, H., Huber, D.H., Langenheder, S., Lennon, J.T., Martiny, J.B.H., Matulich, K.L., Schmidt, T.M., Handelsman, J., 2012. Fundamentals of microbial community resistance and resilience. Front. Microbiol. 3, 417. https://doi.org/10.3389/fmicb.2012.00417. Shen, J., Yuan, L., Zhang, J., Li, H., Bai, Z., Chen, X., Zhang, W., Zhang, F., 2011. Phosphorus dynamics: from soil to plant. Plant Physiol. 156, 997–1005. https://doi. org/10.1104/pp.111.175232. Sinsabaugh, R.L., Moorhead, D.L., 1994. Resource allocation to extracellular enzyme production: a model for nitrogen and phosphorus control of litter decomposition. Soil Biol. Biochem. 26, 1305–1311. https://doi.org/10.1016/0038-0717(94)90211-9. Steinweg, J.M., Plante, A.F., Conant, R.T., Paul, E.A., Tanaka, D.L., 2008. Patterns of substrate utilization during long-term incubations at different temperatures. Soil Biol. Biochem. 40, 2722–2728. https://doi.org/10.1016/j.soilbio.2008.07.002. Tabatabai, M.A., 1994. Soil enzymes. In: Weaver, R., Angle, S., Bottomley, P., Bezdicek, D., Smith, S., Tabatabai, M.A., Wollum, A. (Eds.), Methods of Soil Analysis, Part 2, Microbiological and Biochemical Properties. Soil Sci. Soc. Am.pp. 775–833 Madison, Madison, Wisconsin. Taillefumier, T., Posfai, A., Meir, Y., Wingreen, N.S., 2017. Microbial consortia at steady supply. eLife 6, e22644. https://doi.org/10.7554/eLife.22644. Vershinina, O.A., Znamenskaya, L.V., 2002. The Pho regulons of bacteria. Microbiology 71, 497–511. https://doi.org/10.1023/A:1020547616096. Vitousek, P.M., Porder, S., Houlton, B.Z., Chadwick, O.A., 2010. Terrestrial phosphorus limitation: mechanisms, implications, and nitrogen – phosphorus interactions. Ecol. Appl. 20, 5–15. https://doi.org/10.1890/08-0127.1. Weand, M.P., Arthur, M.A., Lovett, G.M., McCulley, R.L., Weathers, K.C., 2010. Effects of tree species and N additions on forest floor microbial communities and extracellular enzyme activities. Soil Biol. Biochem. 42, 2161–2173. https://doi.org/10.1016/j. soilbio.2010.08.012. Yao, Q., Li, Z., Song, Y., Wright, S.J., Guo, X., Tringe, S.G., Tfaily, M.M., Paša-Tolić, L., Hazen, T.C., Turner, B.L., Mayes, M.A., Pan, C., 2018. Community proteogenomics reveals the systemic impact of phosphorus availability on microbial functions in tropical soil. Nat. Ecol. Evol. 2, 499–509. https://doi.org/10.1038/s41559-0170463-5. Zheng, M., Huang, J., Chen, H., Wang, H., Mo, J., 2015. Responses of soil acid phosphatase and beta-glucosidase to nitrogen and phosphorus addition in two subtropical forests in southern China. Eur. J. Soil Biol. 68, 77–84. https://doi.org/10.1016/j. ejsobi.2015.03.010.
Acknowledgements This work was supported by JSPS KAKENHI [Grant Number 26292035]. The authors thank Kazuo Isobe (The University of Tokyo) and Hitoshi Moro (Shinshu University) for helpful discussions and Kazunari Nagaoka (National Agriculture and Food Research Organization) for funding acquisition. References Castle, S.C., Sullivan, B.W., Knelman, J., Hood, E., Nemergut, D.R., Schmidt, S.K., Cleveland, C.C., 2017. Nutrient limitation of soil microbial activity during the earliest stages of ecosystem development. Oecologia 185, 513–524. https://doi.org/10.1007/ s00442-017-3965-6. Cleveland, C.C., Townsend, A.R., Schmidt, S.K., 2002. Phosphorus limitation of microbial processes in moist tropical forests: evidence from short-term laboratory incubations and field studies. Ecosystems 5, 680–691. https://doi.org/10.1007/s10021-0020202-9. Demoling, F., Figueroa, D., Bååth, E., 2007. Comparison of factors limiting bacterial growth in different soils. Soil Biol. Biochem. 39, 2485–2495. https://doi.org/10. 1016/j.soilbio.2007.05.002. Fujita, K., Kunito, T., Moro, H., Toda, H., Otsuka, S., Nagaoka, K., 2017. Microbial resource allocation for phosphatase synthesis reflects the availability of inorganic phosphorus across various soils. Biogeochemistry 136, 325–339. https://doi.org/10. 1007/s10533-017-0398-6. Graham, E.B., Wieder, W.R., Leff, J.W., Weintraub, S.R., Townsend, A.R., Cleveland, C.C., Philippot, L., Nemergut, D.R., 2014. Do we need to understand microbial communities to predict ecosystem function? A comparison of statistical models of nitrogen cycling processes. Soil Biol. Biochem. 68, 279–282. https://doi.org/10.1016/j. soilbio.2013.08.023. Griffiths, B.S., Philippot, L., 2013. Insights into the resistance and resilience of the soil microbial community. FEMS Microbiol. Rev. 37, 112–129. https://doi.org/10.1111/ j.1574-6976.2012.00343.x. Hedin, L.O., Vitousek, P.M., Matson, P.A., 2003. Nutrient losses over four million years of tropical forest development. Ecology 84, 2231–2255. Hou, E., Tan, X., Heenan, M., Wen, D., 2018. A global dataset of plant available and unavailable phosphorus in natural soils derived by Hedley method. Sci. Data 5,
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