Synergism is not the primary aspect of microbe-earthworm interactions in warm temperate forest soil food webs

Synergism is not the primary aspect of microbe-earthworm interactions in warm temperate forest soil food webs | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Synergism is not the primary aspect of microbe-earthworm interactions in warm temperate forest soil food webs Yuya Yoshikawa, Kazusa Ohi, Keishi Kimoto, Jiro Tsukamoto This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6689570/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background and Aims Understanding carbon dynamics in forest ecosystems—driven primarily by trees, soil microbes, and earthworms— is indispensable in developing ecological strategies to mitigate global warming. A recent systematic review revealed that the effects of tree functional types on earthworms differ between boreal/cool-temperate and warm-temperate forests. The hypothesized driving force of this difference is a phase shift in microbe-earthworm interactions between synergy and competition along the global temperature gradient. This study aims to empirically verify this hypothesis. Methods In a warm temperate region, the six components of decomposer food webs, annual litterfall mass, fine root mass, forest floor turnover rate, soil organic matter content, CO 2 emission rate from the soil, and endogeic earthworm biomass were assessed in each four stands of two forest types—labile litter-producing deciduous and recalcitrant litter-producing evergreen broadleaf forests. Results The two forest types were distinguished without misclassification using a significant linear combination of the six variables of interest. However, regarding the latter three variables (soil, microbes, and earthworms related-variables), the magnitude relationships between the forest types were opposite to those commonly observed in boreal and cool temperate regions. Conclusion The reversal in the relationship between tree functional types and decomposer sub-systems between boreal/cool temperate and warm temperate forests empirically supports the hypothesis that could provide a novel basis for global carbon modelling. Therefore, the dual nature of microbe-earthworm interactions (synergistic versus competitive) and the effects of temperature on the relative importance of the two aspects merit future experimental studies. Biological interaction Temperature dependence Tree functional type CO2 emission rate Endogeic earthworm biomass Warm temperate forests Figures Figure 1 Introduction Understanding the carbon dynamics in terrestrial ecosystems is indispensable for developing ecological strategies to mitigate global warming and sustainable ecosystem management initiatives in a world undergoing climatic change. The decomposition and sequestration of organic matter in the soil, which is the largest carbon pool in terrestrial ecosystems (Amundson 2001 ; Schlesinger and Bernhardt 2013 ), is driven by the interaction between soil microbes and invertebrates, especially earthworms, which are the most powerful ecosystem engineers. Plants, in turn, play a critical role in shaping the microbe-invertebrate interactions via litter quality and quantity, whereas the performance of this tripartite system is mediated by climate (e.g., Deyn et al. 2008 ). In forest ecosystems, which constitute a large fraction of the global terrestrial CO 2 sink (e.g., Keenan and Williams 2018 ), four tree functional types—pioneer, broad-leaved deciduous (mid-to-late-successional species), broad-leaved evergreen, and needle-leaved evergreen—maintain constant differences in economic leaf traits (net photosynthesis, specific leaf area, and leaf nitrogen) across global climate and vegetation type gradients (Reich et al. 1997 ). In a recent systematic review, the four tree functional groups were categorized into two litter types, “labile” and “recalcitrant,” generating significant differences in earthworm biomass between the forests of the two litter types within each of boreal, cool temperate, and warm temperate region (Tsukamoto 2025 ). However, the relationship between litter type (litter quality) and earthworm biomass was reversed along the temperature gradient, with it being positive at lower temperatures and negative at higher temperatures. That is, in boreal to cool temperate regions, earthworm biomass was higher in labile (high-quality) litter-producing forests than in recalcitrant (low-quality) litter-producing forests, and the reverse was true in warm temperate regions. The hypothesized driving force of this reversal is a phase shift in microbe-earthworm interactions from synergy to competition with increasing temperature. The positive relationship between litter quality and earthworm biomass has been well-documented in boreal-to-cool temperate forests in relation to mull versus moder/mor humus formation (Muys, et al. 1992 ; Neirynck et al. 2000 ; Schelfhout, et al. 2017 ). Furthermore, parallel responses of bacteria and earthworms to litter quality have been repeatedly noted (e.g., Bal 1982 ; Frouz 2018 ; Petersen and Luxton 1982 ; Ponge 2003 and 2013 ; Schaefer 1991 ; Swift et al. 1979 ; Wallwork 1970 ), highlighting the synergistic interactions between bacteria and earthworms (Frouz 2018 ; Lavelle et al. 1995 ; Wardle 2002 ). In contrast, information on the negative relationship between litter quality and earthworm biomass and the mechanisms generating it, if any, is lacking. However, in contrast to the litter quality control of soil macro-invertebrate (especially earthworms) biomass prevailing in boreal to cool temperate forests, litter quantity control of soil macro-invertebrate abundance or biomass has been reported in warm temperate (Yoshikawa et al. 2021 ) and tropical (Jochum et al. 2017 ; Kaspari and Yanoviak 2009 ) forests. A similar contrast between climatic zones was detected in a recent meta-analysis on the global distribution of soil fauna (Heděnec et al. 2022 ); namely, a closer association of soil fauna biomass with litter C/N in boreal forests versus that with net primary productivity in tropical forests. These findings imply that the nexus among trees, soil microbes, and soil invertebrates in forest ecosystems changes along the global temperature gradient. This temperature dependence could be one of the driving forces for the biome-dependent contributions of soil invertebrates to litter decomposition (Frouz et al. 2015 ; García-Palacios et al. 2013 ; Makkonen et al. 2012 ; Wall et al. 2008 ) and litter consumption (Heděnec et al. 2022 ). If this is the case, the temperature dependence should be considered in the global carbon modelling and sustainable forest management planning on a local scale. In this study, sympatric assessments of microbial activity, earthworm biomass, and several variables constituting the decomposer food web were conducted in recalcitrant litter-producing broad-leaved evergreen forests and labile litter-producing broad-leaved deciduous forests in a warm temperate region. This study aimed to empirically confirm the temperature tuning of the three-partite system and verify its hypothesized driving force, a temperature-mediated phase shift in microbe-earthworm interactions between synergy and competition. Materials and methods Study sites and stands The study was conducted in eight stands of secondary broad-leaved forest located within an area of 32°44′–33°42′ N and 132°56′–134°12′ E, at an altitude of 108–882 m asl. in Southwestern Japan (Table S1 ). All stands fell within warm temperate moist climate zone [10 ℃ < mean annual temperature 2000 mm]. Four stands each were dominated by broad-leaved evergreen (stand codes E1–4) and broad-leaved deciduous (stand codes D1–4) tree species. The soil type and humus form of the seven stands other than E3 were identical [B D type (moderately moist brown forest soil) (Forest Soil Division 1975 ) and Mull type (Ponge 2003 ), respectively]. The soil and humus forms of E3 were B D (d) [moderately moist brown forest soil (dryer subtype)] and Mull/Modar, respectively, owing to its dryer slope position. Annual litterfall mass Litterfall was trapped during the period of at least two years starting in October (D4), November (E1–4) or December (D1–3) 2013 using 10 circular traps with 0.5 m 2 opening (Fig. S1 ). The traps were arranged in a ladder pattern, with the intervals between two adjacent traps being 2 m or 4 m. The materials trapped, excluding branch litter > 10 cm in girth, were collected once a month, oven dried (80 ℃, 48 h), and weighed by traps. Since some of the litter traps were sometimes disturbed by mammals and/or typhoon, a complete set of ten traps’ data during consecutive twelve month-period was selected by stands so as to overlap as largely as possible among the stands (Sep 2014–Aug 2015 for E4, Oct 2014–Sep 2015 for D4, Nov 2014–Oct 2015 for E1–3 and D3, and Dec 2014–Nov 2015 for D1 and D2, respectively). Monthly measured values were summed by traps, and were taken as the annual litterfall for each trap, yielding ten samples of annual litterfall mass in each stand. Annual mean forest floor mass Leaf fall phenology differs between broad-leaved evergreen and broad-leaved deciduous trees. Most evergreens have their annual leaf fall peak at the time of leaf flushing in spring, which is from April to May in western Japan; the leaf fall of most deciduous species occurs in late autumn to early winter, which is from October to December. Therefore, for comparability, the annual minimum forest floor mass was assessed from late March to early April 2012 in the evergreen stands and from late September to early October 2012 in the deciduous stands, while the annual maximum forest floor mass was assessed from the end of May to June 2012 in the evergreen stands and from December 2012 to January 2013 in the deciduous stands. The mean of the oven-dry weights (80 ℃, 48h) of ten 30 cm × 30 cm quadrat samples of the forest floor was used in each stand on each sampling occasion. The annual mean forest floor mass was estimated as the arithmetic mean of the annual minimum and maximum values, yielding an estimate for each stand. Earthworm biomass Animal sampling was performed in 2010 (E2 and E4) and 2012 (E1, E3, and D1–D4). In both years, the sampling was performed during the annual peak of earthworm biomass in Japan: June to July (Sota 1985 ; Sugi and Tanak, 1978; Uchida and Kaneko 2004 ). Soil macro-invertebrates larger than 2 mm in body length were collected by hand-sorting from six 30 cm × 30 cm quadrat samples of the A 0 -layer and topsoil (0–10 cm) separately. The collected animals were preserved in 75% ethanol, except for earthworms which were preserved in 10% formalin. In the laboratory, the wet weights of the preserved animals were determined individually to 0.1 mg accuracy by using an analytical balance after carefully placing them on filter paper. In this study, we focused on earthworms, the most powerful ecosystem engineers in moist environments that play a dominant role in the regulation of soil processes, including carbon sequestration and decomposition (Lavelle 1997 ). All the of earthworm specimens were classified into two families, i.e., Megascolecidae or Lumbricidae, based on chaetotaxy. Lumbricid worms were further classified into species using an identification key for Lumbricidae in Japan (Nakamura 1972 ), with the result that this family was represented exclusively by one species, Eisenia japonica (Michaelsen, 1892). The functional types of Megascolecidae and Eisenia japonica were identified based on the following criteria: limited occurrence in the A 0 -layer epigeic, limited occurrence in the topsoil endogeic, extended occurrence across the two layers anecic, or a complex of at least two functional types. Topsoil-related variables A topsoil sample (1–6 cm in depth) was collected from the vicinity of each litter trap from September to October 2015, yielding ten samples from each stand. Cylindrical soil core samplers of 100 cm 3 in volume (20 cm 2 in basal area × 5 cm in height) with known weight to the nearest 10 mg were used. The cylinder samples were sealed with vinyl tape at the upper and lower lids and transported to the laboratory in a cooler box. Root mass After measuring the CO 2 emission from each cylinder sample as described below, the soil material in the cylinder was air dried, sieved, and sorted into three fractions, fine soil, gravel ( ≧ 2 mm in diameter), and root. The root fraction was further separated into fine root (< 1.5 mm in diameter) and coarse root ( ≧ 1.5 mm in diameter) using a digital caliper. The fractions of fine and coarse root were oven dried (105℃, 24 hr.) and weighed to the nearest 10 mg. Soil organic matter content The fractions of fine soil and gravel were oven dried (105℃, 24 hr.) and weighed to the nearest 10 mg. Ignition loss of a small portion of the fine soil fraction (0.78–2.85 g oven dry weight) was determined using a muffle furnace (550℃, 5 hr. + 700℃, 1 hr.). Percentage ignition loss (ignition loss/oven-dry weight of the fine soil tested *100) was taken as the organic matter content of the topsoil. CO 2 emission rate CO 2 emission from the cylinder samples was measured one by one using the dynamic closed chamber method (Hashimoto 2005 ). Within the day of sampling, the cylinder samples were weighed to the nearest 10 mg after removing the vinyl tape, and put in an incubator set at 20℃. After one day incubation at 20°C, each sample, from which the upper lid was removed in advance, was transferred to a plastic chamber which was placed in an incubator set at 20°C. The chamber was connected to a CO 2 analyzer (LI-COR 6252; LI-COR, Lincoln, NE, USA) and an air pump (flow rate: 52.1 ml s − 1 ; MP-2N; Shibata Scientific, Tokyo). The total volume inside the system was 1083.3 ml including the space in the connecting vinyl tubes. For each sample, the CO 2 concentration (µl l − 1 ) in the system was continuously monitored for 7–8 min after starting the air circulation and recorded at intervals of 5 s. The increment in the CO 2 concentration from 1 to 6 min after starting the air circulation was converted to the volume of CO 2 (µl) emitted in 5 min. The rate of CO 2 emission [µl CO 2 (g dry organic matter) −1 h − 1 ] was calculated using oven-dried organic matter mass in each cylinder sample that was calculated as oven-dried fine soil mass multiplied by percentage ignition loss. Data processing The forest floor turnover rate (annual litterfall mass/annual mean forest floor mass) was calculated as an indicator of in situ litter decomposition rate. Regarding earthworms, the biomass of Eisenia japonica was the focus because it was identified as endogeic species (see below) primarily feeding on bacterially processed soil organic matter (Zhong et al., 2025 ). Table 1 presents the processed variables of interest. Statistical analysis The among-stand variations and between-stand differences in the variables of interest, except for the forest floor turnover rate, were analyzed by using one-way ANOVA and Tukey’s HSD test, respectively, using the log 10 transformed raw values of each variable. Other analyses described below were performed using the stand means of each variable, except for the forest floor turnover rate, for which a single representative value from each stand was used. The association between tree functional type and the decomposer food web was investigated using linear discriminant analysis, where the external criterion was broad-leaved evergreen versus broad-leaved deciduous, and the independent variables were “annual litterfall mass + fine root mass” (ALM + FRM), “forest floor turnover rate” (FFTR), “soil organic matter content” (SOM), “CO 2 emission rate” (CO2), and “biomass of Eisenia japonica ” (BEJ) (cf. Table 1). Prior to analysis, a log 10 transformation was performed on the stand mean value of each variable to approximate homoscedasticity. The similarity in cross-stand patterns between each pair of the variables was tested using Spearman’s rank correlation analysis. Multiple regression analysis was performed to test the effects of ALM + FRM (organic matter input) and CO2 (organic matter output) on SOM (organic matter accumulation). Log 10 transformations of stand means were performed to ensure the credibility of this analysis. All analyses were performed with R version 4.3.3 (R Core Team 2024 ) except for linear discriminant analysis, for which SPSS 17.0J (IMB) was used. The significance level was set at α = 0.05. Results Distribution and functional type of earthworms Both Megascolecid and lumbricid worms ( E . japonica ) occurred in all stands (Table 2). Megascolecidae were distributed across the A 0 -layer and topsoil, indicating the multi-functional type composition of this family. In contrast, E. japonica was almost completely confined to the topsoil, indicating that this species was of the endogeic type, exclusively feeding on bacterially processed organic matter in the soil. Among-stand variations and between-stand differences in variables of interest The among-stand variations in the variables of interest were significant (ALM, FRM, SOM, and CO2) or marginally significant (BEJ) (Table 3), except for FFTR, which was beyond the significance test due to its statistical attributes (Table 1). ALM, FRM, SOM, and BEJ tended to be higher in the evergreen forests than in the deciduous forests, with the maximum of each variable being recorded in the evergreen stand and the minimum in the deciduous stand (Fig. 1 , Table 3). The reverse was true for FFTR. CO2 exhibited a different trend in that both maximum and minimum values were recorded within the deciduous-stand group, that is, D2 and D1, respectively. Discrimination of forest type using variables involved in soil organic matter dynamics Broad-leaved evergreen stands and broad-leaved deciduous stands were distinguished without misclassification using a significant linear combination of the tested variables (Table 4). For all variables, a one-unit change in the standardized variable could cause a discriminant score fluctuation of > 10% of its range, with the absolute values of the discriminant function coefficient being 1.304–3.228 versus the range of the discriminant score of 11.394 (− 5.460 to 5.934). Correlations between variables of interest across stands The BEJ was highly positively correlated with SOM (Table 5). The relationships of ALM + FRM with SOM and BEJ tended to be positive. In contrast, the relationships of CO2 with SOM and BEJ tended to be negative. Factors affecting soil organic matter content ALM + FRM and CO2 were tested for their effects on SOM, resulting in a marginally significant multiple regression equation (Table 6). The positive effect of ALM + FRM on SOM was marginally significant. Although the effect of CO2 on SOM was not significant, the partial regression coefficient of CO2 on SOM tended to be negative. Discussion Nexus among trees, microbes, and earthworms in warm temperate forests differs from that in boreal to cool temperate forests The complete discrimination between broad-leaved evergreen stands and broad-leaved deciduous stands using linearly combined variables constituting decomposer food web (Table 3) indicated that the two tree functional types shaped distinct soil organic matter dynamics. The differential shaping of soil organic matter dynamics by different tree functional types per se is common knowledge among boreal to cool temperate forest ecosystems. Specifically, mull humus formation is primarily driven by bacteria and earthworms, facilitated by labile litter, whereas mor humus formation predominantly governed by fungi and meso/micro fauna, constrained by recalcitrant litter (e.g., Bal 1982 ; Frouz 2018 ; Petersen and Luxton 1982 ; Ponge 2003 , 2013 ; Schaefer 1991 ; Swift et al. 1979 ; Wallwork 1970 ). However, this pattern was not observed in the warm temperate forests in this study. In contrast, the relationships between the following pairs of variables tended to be reversed to those commonly observed in boreal and cool-temperate forests. Litter decomposability - earthworm biomass relationship The trend for FFTR to be higher in deciduous stands than in evergreen stands (Fig. 1 , Table 3) was consistent with the results of comparative leaf litter decomposition experiments showing higher decomposability of deciduous broadleaf litter than that of evergreen broadleaf litter (Aponte et al. 2013 ; Cornelissen et al. 1999 ; Cornwell, et al. 2008; Pringle et al. 2011 ; Rahman and Tsukamoto 2013 ; Rawat et al. 2021 ; Wang et al. 2023 ). Accordingly, a higher BEJ is expected in deciduous stands than in evergreen stands, provided that earthworm biomass patterns in relation to litter decomposability do not differ between warm temperate forests and boreal-to-cool temperate forests. However, the reverse trend was observed (Fig. 1 , Table 2). The biomass of Megascolecidae also exhibited a similar trend (Table 2). Microbial activity-earthworm biomass relationship CO 2 emissions from the soil tend to be higher in labile litter-producing forests (broad-leaved deciduous forests) than in recalcitrant litter producing-forests (coniferous forests) in boreal to cool temperate regions (Jevon et al. 2023 ; Raich and Tufekioglu 2000 ; Tewary et al. 1982 ; but Frouz et al. 2013 ). This indicates the parallel responses of microbes and earthworms to tree functional type. This might have led to a somewhat one-sided emphasis on synergistic interactions between bacteria and soil macro-invertebrates, especially earthworms (e.g., Frouz 2018 ; Lavelle et al. 1995 ; Wardle 2002 , but Scheu and Schaefer 1998 ). In the context of this synergism, a positive relationship between CO2 and BEJ was expected; however, the relationship tended to be negative (Table 5). Microbial activity-soil organic matter content relationship The accumulation of organic carbon in the soil tends to be higher in labile litter-producing forests than in recalcitrant litter-producing forests in boreal to cool temperate regions (Cha et al. 2019 ; Frouz et al. 2009 ; Jobbágy and Jackson 2000 ; Nickels and Prescott 2021 ). Thus, despite the apparently opposite flow of carbon, both CO 2 emissions from the soil and the accumulation of organic matter in the soil are positively related to litter decomposability. This supports the “microbial substrate use efficiency” paradigm sensu Cotrufo et al. ( 2013 ), which was developed mainly on the boreal to cool temperate ecosystem background. However, such a corresponding response to the tree functional types was not observed between CO2 and SOM (Fig. 1 ). Instead, the relationship between CO2 and SOM tended to be negative across the study stands (Table 5). Tree species effects on decomposer food web properties within broad-leaved deciduous forests Stands D1 and D2 were dominated by an oak species ( Quercus serrata Thumb.) and a dogwood species ( Swida controversa (Hemsl.) Sojak), respectively (Table S1 ). These species are typical recalcitrant and labile litter producers, respectively (e.g., Takeda et al. 1987 ). This was confirmed in the present study (FFTR in Fig. 1 ). In cool temperate regions, beech and ash trees are typical moder-humus forming and mull-humus forming tree species, respectively (Muys and Lust 1992 ; Neirynck et al. 2000 ). In general, beech stands exhibit lower litter decomposability (Makkonen, et al. 2012 ; Melillo et al. 1982; Schelfhout, et al. 2017 ; Vesterdal et al. 2008 ; Zuo, et al. 2018 ), lower soil respiration (Vesterdal et al. 2012 ), lower earthworm biomass (Muys and Lust 1992 ; Neirynck et al. 2000 ; Schelfhout et al. 2017 ), and lower soil carbon stocks (Vesterdal et al. 2008 , 2013 ) than ash stands. D1 (oak) and D2 (dogwood) have contrasting litter decomposabilities similar to beech and ash pair. Nevertheless, comparisons of CO2, BEJ, and SOM between D1 and D2 exhibited inverse magnitude relationships with the beech vs. ash comparisons of the relevant soil food web properties. Possible explanation for the biome dependent nexus among trees, microbes, and earthworms As mentioned above, the mode of differential shaping of decomposer food webs or soil organic matter dynamics by different functional tree types differed between boreal/cool-temperate and warm-temperate forests. A hypothesized mechanism for this difference has recently been proposed (Tsukamoto 2025 ). Labile litter promotes earthworms through synergistic interactions with microbes in the regions at lower temperatures but impedes them through competitions with microbes in the regions at higher temperatures. In contrast, recalcitrant litter depresses earthworms with poor synergy benefits from microbes in colder regions but supports earthworms by mitigating microbial competition in warmer regions. The driving force of this hypothetical system is the dual nature of microbe-earthworm interactions (synergistic versus competitive) and the differential momentum of these vectors at different ambient temperatures and, hence, at different levels of microbial activity (e.g., Cruz-Paredes et al. 2021 ; Xiao et al. 2021 ). The following results of this study do not contradict the enhanced microbial activity at warmer temperatures: the highly positive correlation between SOM and BEJ, an indication of food limitation on endogeic earthworms, and the marginally significant positive effect of ALM + FRM on SOM, an indication of litter quantity control of carbon accumulation in the soil. Conclusion The temperature dependence of the nexus among the three major components of forest ecosystems, trees, microbes, and soil invertebrates, and the mechanisms generating it will provide a novel basis for model development to predict changes in global carbon dynamics and for planning sustainable forest management measures at the field scale. Therefore, the sympatric assessments of microbial activity and soil macro-invertebrate biomass along the global temperature gradient and experiments on the effects of temperature on microbe-earthworm interactions merit future studies. Declarations The authors declare that no funds, grants, or other support were received during the preparation of this manuscript. The authors have no relevant financial or non-financial interests to disclose. Acknowledgement We wish to thank Professor Dr. Tomoaki Ichie, Kyoto Prefectural University, for third-party review and valuable advice. References Amundson R (2001) The carbon budget in soils. Annu Rev Earth Planet Sci 29:535–562. Aponte C, Garcia LV, Maranon T (2013) Tree species effects on nutrient cycling and soil biota: A feedback mechanism favouring species coexistence. Forest Ecol Manag 309: 36–46. http://dx.doi.org/10.1016/j.foreco.2013.05.035 Bal L (1982) Zoological Ripening of Soils. Centre for Agricultural Publishing and Documentation, Wageningen. Cha J‐Y, Cha Y, Oh N‐H (2019) The effects of tree species on soil organic carbon content in South Korea. J Geophys Res-Biogeo 124: 708–716. https://doi.org/10. 1029/2018JG004808 Cornelissen JHC, Pérez-Harguindeguy N, Díaz S, Grime J P, Marzano B, Cabido M, Vendramini F, Cerabolini B (1999) Leaf structure and defense control litter decomposition rate across species and life forms in regional floras on two continents. New Phytol 143: 191–200. Cornwell WK et al (2008) Plant species traits are the predominant control on litter decomposition rates within biomes worldwide. Ecol Lett 11: 1065–1071. Cotrufo MF, Wallenstein MD, Boot CM, Denef K, Paul E (2013) The Microbial Efficiency-Matrix Stabilization (MEMS) framework integrates plant litter decomposition with soil organic matter stabilization: do labile plant inputs form stable soil organic matter? Glob Chang Biol 19(4): 988–995. doi: 10.1111/gcb.12113. Cruz-Paredes C, Dániel T, Johannes R (2021) Can moisture affect temperature dependences of microbial growth and respiration? Soil Biol Biochem 156: 103223. https://doi.org/10.1016/j.soilbio.2021.108223. de Deyn GB, Cornelissen JHC, Richard DB (2008) Plant functional traits and soil carbon sequestration in contrasting biomes. Ecol Lett 11: 516–531. Forest Soil Division (1975) Classification of forest soil in Japan. Bulletin of the Government Forest Experiment Station 280: 1–28. (in Japanese with English summary) Frouz J (2018) Effects of soil macro- and mesofauna on litter decomposition and soil organic matter stabilization. Geoderma 332: 161–172. http://dx.doi.org/10.1016/j. geoderma.2017.08.039 Frouz J, Pižl V, Cienciala A, Kalčík J (2009) Carbon storage in post-mining forest soil, the role of tree biomass and soil bioturbation. Biogeochemistry 94: 111–121. Frouz J, Livečková, M, Albrechitová J, Chroňáková A, Cajthaml T, Pižl V, Hánӗl L, Stary J, Baldrian P, Lhotáková Z, Simáčková H, Cepáková S, (2013) Is the effect of trees on soil properties mediated by soil fauna? A case study from post-mining sites. Forest Ecol Manag 309: 87–95. Frouz J, Roubíčková A, Heděnec P, Tajovský K (2015) Do soil fauna really hasten litter decomposition? A meta-analysis of enclosure studies. Eur J Soil Biol 68: 18-24. http://www.elsevier.com/locate/ejsobi García-Palacios P, Maestre FM, Kattge J, Wall DH (2013) Climate and litter quality differently modulate the effects of soil fauna on litter decomposition across biomes. Ecol Lett 16: 1045–1053. Hashimoto S (2005) Temperature sensitivity of soil CO 2 production in a tropical hill evergreen forest in northern Thailand. J For Res 10: 497–503. Heděnec P, Jiménez JJ, Moradi J, Domene X, Hackenberger D, Barot S, Frossard A, Oktaba L, Filser J, Kindlmann P, Frouz J. (2022) Global distribution of soil fauna functional groups and their estimated litter consumption across biomes. Sci. Rep. 12:17362. https://doi.org/10.1038/s41598-022-21563-z IPCC (2006) Guidelines for National Greenhouse Gas Inventories. https://www.ipcc-nggip.iges.or.jp /public/2006gl/vol2.html. Jevon FV, Gewirtzman J, Lang AK, Ayres MP, Matthes JH (2023) Tree species effects on soil CO 2 and CH 4 fluxes in a mixed temperate forest. Ecosystems 26: 1587–1602. https://doi.org/10.1007/s10021-023-00852-2 Jobbágy EG, Jackson RB (2000) The vertical distribution of soil organic carbon and its relation to climate and vegetation. Ecol Appl 10(2): 423–436. Jochum M, Barnes AD, Weigelt P, Ott D, Rembold K, Farajallah A, Brose U (2017) Resource stoichiometry and availability modulate species richness and biomass of tropical litter macro-invertebrates. J Anim Ecol 86: 1114–1123. Kaspari M, Yanoviak SP, (2009) Biogeochemistry and the structure of tropical brown food webs. Ecology 90: 3342–3351. Keenan TF, Williams CA (2018) The terrestrial carbon sink. Annu Rev Env Resour 43: 219–243. https://doi.org/10.1146/annurev-environ-102017-030204 Lavelle P (1997) Faunal activities and soil processes: Adaptive strategies that determine ecosystem function. Adv Ecol Res 27: 93132. Lavelle P, Lattaud C, Trigo D, Barois L (1995). Mutualism and biodiversity in soils. Plant Soil 170: 23–33. Makkonen M, Matty P, Berg I, Handa T, Hättenschwiler S, van Rujiven J, van Bodegom PM, Aerts R (2012) Highly consistent effects of plant litter identity and functional traits on decomposition across a latitudinal gradient. Ecol. Lett. 15: 1033–1041. Melillo JM, Aber JD (1982) Nitrogen and Lignin control of hardwood leaf litter decomposition dynamics. Ecology 63: 621–626. Muys B, Lust N (1992) Inventory of earthworm communities and the state of litter decomposition in the forests of Flanders, Belgium, and its implications for forest management. Soil Biol Biochem 24: 1677–1681. Muys N, Lust N, Granval PH (1992) Effects of grassland afforestation with different tree species on earthworm communities, litter decomposition and nutrient status. Soil Biol Biochem 24: 1459–1466. Nakamura Y (1972) Morphological obsevations of cocoon, larva and adult of Lumbricidae. B Natl Grassl Res Inst 1: 6–16. Neirynck J, Mirtchevaa S, Sioen G, Lust N (2000) Impact of Tilia platyphyllos Scop., Fraxinus excelsior L., Acer pseudoplatanus L., Quercus robur L. and Fagus sylvatica L. on earthworm biomass and physico-chemical properties of a loamy topsoil. Forest Ecol Manag 133: 275–286. Nickels MCL, Prescott CE (2021) Soil carbon stabilization under coniferous, deciduous and grass vegetation in post-mining reclaimed ecosystems. Front For Glob Change 4: 689594. Petersen H, Luxton M (1982) A comparative analysis of soil fauna populations and their role in decomposition processes. Oikos 39, 287–388. Ponge JF (2003) Humus forms in terrestrial ecosystems: a framework to biodiversity. Soil Biol Biochem 35: 935–945. Ponge JF, (2013) Plant–soil feedbacks mediated by humus forms: A review. Soil Biol Biochem 57: 1048–1060. Pringle EG, Adams RI, Broadbent E, Busby PE, Donatti CI, Kurten EL. 1, Renton K, Dirzo R (2011) Distinct leaf-trait syndromes of evergreen and deciduous trees in a seasonally dry tropical forest. Biotropica 43(3): 299–308. Rahman MM, Tsukamoto J (2013) Leaf traits, litter decomposability and forest floor dynamics in an evergreen- and deciduous broadleaved forest in warm temperate Japan. Forestry 86: 441–451. Raich JW, Tufekioglu A (2000) Vegetation and soil respiration: Correlations and controls. Biogeochemistry 48: 71–90. Rawat M, Arunachalam K, Arunachalam A, Alatalo JM, Pandey R (2021) Assessment of leaf morphological, physiological, chemical and stoichiometry functional traits for understanding the functioning of Himalayan temperate forest ecosystem. Sci Rep-UK 11: 23807. https://doi.org/10.1038/s41598-021-03235-6 R Core Team, 2024. R package version 4.3.3 Reich PB, Walters MB, Elsworth DS (1997) From tropics to tundra: Global convergence in plant functioning. Proc Natl Acad Sci USA 94: 13730–13734. Schaefer M (1991) Fauna of the European temperate deciduous forest. In: Röhrig E, Ulrich B (Eds) Ecosystems of the World 7, Temperate deciduous forests. Elsevier, Amsterdam, pp 503–525. Schaefer M, Schauermann J (1990) The soil fauna of beech forests: comparison between mull and a moder soil. Pedobiol 34: 299–314. Schelfhout S, Mertens J, Verheyen K, Vesterdal L, Baeten L, Muys B, de Schrijver A (2017) Tree species identity shapes earthworm communities. Forests 8: 85. Schlesinger WH, Bernhardt ES (2013) Biogeochemistry: An analysis of global change. 3rd edn. Elsevier, Amsterdam. Scheu S, Schaefer M (1998) Bottom-up control of the soil macrofauna community in a beechwood on limestone: manipulation of food resources. Ecology 79: 1573–1585. Sota T (1985) Activity patterns, diets and interspecific interactions of coexisting spring and autumn breeding carabids: Carabus jaconinus and Leptocarabus kumagaii (Coleoptera, Carabidae). Ecol Entomol 10: 315–324. Sugi Y, Tanaka M (1978) Number and biomass of earthworm populations. In: Kira T, Ono Y, Hosokawa T. (Eds.) Biological Production in a warm-temperate evergreen oak forest of Japan. University of Tokyo Press, Tokyo, pp 171-178. Swift MJ, Heal OW, Anderson JM (1979). Decomposition in Terrestrial Ecosystems. Blackwell, Oxford. Takeda H, Ishida T, Tsutsumi T (1987) Decomposition of leaf litter in relation to litter quality and site conditions. Mem Coll Agric Kyoto Univ 130: 17–38. Tewary CK, Pandey UMA, Singh JS (1982) Soil and litter respiration rates in different microhabitats of a mixed oak-conifer forest and their control by edaphic conditions and substrate quality. Plant Soil 65: 233–228. Tsukamoto J (2025) Pragmatic categorization of moist woodland ecosystems of the world matching the pattern of earthworm biomass. Appl Soil Ecol 212: 106172. Uchida T, Kaneko, N (2004). Life history of Megascolecidae earthworms in forest soils at Kanagawa, Japan. Edaphologia 74: 35-45. (in Japanese with English summary) Vesterdal L, Schmidt IK, Callesen I, Nilsson LO, Gundersen P (2008) Carbon and nitrogen in forest floor and mineral soil under six common European tree species. Forest Ecol Manag 255: 35–48. Vesterdal L, Elberling B, Christiansen JR, Callesen I, Schmidt IK (2012) Soil respiration and rates of soil carbon turnover differ among six common European tree species. Forest Ecol Manag 264: 185–196. Vesterdal L, Clarke N, Sigurdsson BD, Gundersen P (2013) Do tree species influence soil carbon stocks in temperate and boreal forests? Forest Ecol Manag 309: 4–18. Wall DH et al (2008) Global decomposition experiment shows soil animal impacts on decomposition are climate-dependent. Glob Change Biol 14: 2661–2677. Wallwork J A (1970) Ecology of Soil Animals. McGraw-Hill, London. Wang L, He Y, Muhammad U, Guo Y, Tan Q, Kang L, Fang Z, Shen K, Xia T, Wu P, Liu Y, Zang L, Liu Q, Zhao Y, Chen H, Zhao Y (2023) Strategic differentiation of subcommunities composed of evergreen and deciduous woody species associated with leaf functional traits in the subtropical mixed forest. Ecol Indic 150: 110281. https://doi.org/10.1016/j.ecolind.2023.110281 Wardle DA (2002) Communities and Ecosystems. Princeton University Press, Princeton and Oxford. Xiao HB, Shi ZH, Li ZW, Chen J, Huang B, Yue ZJ, Zhan YM (2021) The regulatory effects of biotic and abiotic factors on soil respiration under different land-use types. Ecol. Indic. 127: 107787. https://doi.org/10.1016/j.ecolind. 2021.107787 Yoshikawa Y, Kawano K, Tsukamoto J (2021) Litter quantity controls soil macr-invertebrate biomass in warm temperate broad-leaved forests of Southwestern Japan. Appl. Soil Ecol. 161, 103870. https://doi.org/10.1016/j.apsoil. 2020.103870. Zhong L, Larsen T, Lu J Z, Scheu S, Pollierer M M (2025) High litter quality enhances plant energy channeling by soil macro-detritivores and lowers their trophic position. Ecology 106, e70004. https://doi.org/10.1002/ecy.70004 Zuo J, Hefting MM, Berg M P, van Logtestijn RSP, van HalJ, Goudzwaard L, Liu JC, Sass-Klaassen U, Sterck FJ, Poorter L, Cornelissen J HC (2018) Is there a tree economics spectrum of decomposability? Soil Biol Biochem 119: 135–142. https://doi.org/10.1016/j. soilbio 2018.01.019. Supplementary Files Supplementarymaterials.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6689570","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":467381790,"identity":"09162844-3a48-4784-98ab-b4eaafa15736","order_by":0,"name":"Yuya Yoshikawa","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Yuya","middleName":"","lastName":"Yoshikawa","suffix":""},{"id":467381791,"identity":"f06104e0-89bb-4abb-8c94-07758a5688f3","order_by":1,"name":"Kazusa Ohi","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Kazusa","middleName":"","lastName":"Ohi","suffix":""},{"id":467381792,"identity":"24c83e89-471a-4f0a-b856-682a1d9c4b93","order_by":2,"name":"Keishi Kimoto","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Keishi","middleName":"","lastName":"Kimoto","suffix":""},{"id":467381793,"identity":"35712cb7-ea55-44d0-80b2-dff523d3e1b4","order_by":3,"name":"Jiro Tsukamoto","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5ElEQVRIiWNgGAWjYFACNgjFz8PAwMxgABWUwKOBB6LFgEGyh2QtBmdAWogB9hJpiZ9uVPyRMz5z+ODnggKGxAb2ww8YLHfgsUUi7bB0zhkDY7OzbcnSMwyAWnjSgM48g09LeoN0bptB4rbzPGbMPAb/ExsYchgYJNvwamn+DdKyuR+sBWgL/xtCWtKOgW3ZwNsD1SJByJYzz9Ksc84YG0ucOZYsDdRi3CbxzOAAPr+wt6cZ386pkJPj70k++JnnD4NsP3/yw8eSeEIME4Di6bBkAylaQIDxI8laRsEoGAWjYBgDAOkCRM0ExPBgAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0001-5840-6781","institution":"Kochi University","correspondingAuthor":true,"prefix":"","firstName":"Jiro","middleName":"","lastName":"Tsukamoto","suffix":""}],"badges":[],"createdAt":"2025-05-18 03:28:41","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6689570/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6689570/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":84246835,"identity":"a75f21c4-8598-4587-9c69-bc5e79c4b489","added_by":"auto","created_at":"2025-06-09 16:58:41","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":33181,"visible":true,"origin":"","legend":"\u003cp\u003eStand specific values of variables involved in organic matter dynamics in the top soil\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003e, 1–6cm deep\u003c/p\u003e\n\u003cp\u003eE1－4, Broad-leaved evergreen stands; D1－4, Broad-leaved deciduous stands;\u003c/p\u003e\n\u003cp\u003eALM, Annual litterfall mass (Mg ha\u003csup\u003e-1\u003c/sup\u003e y\u003csup\u003e-1\u003c/sup\u003e); FRM, Fine root mass [Mg (5cm)\u003csup\u003e-1\u003c/sup\u003eha\u003csup\u003e-1\u003c/sup\u003e]; FFTR, Forest floor turnover rate (y\u003csup\u003e-1\u003c/sup\u003e) (Annual litterfall mass/Annual mean forest floor mass); SOM, Soil organic matter content [mg (g dry mass of fine soil)\u003csup\u003e-1\u003c/sup\u003e]; CO2, CO\u003csub\u003e2\u003c/sub\u003e emission rate [ml (g dry mass of organic matter)\u003csup\u003e-1\u003c/sup\u003e h\u003csup\u003e-1\u003c/sup\u003e)]; BEJ, Biomass of \u003cem\u003eE. japonica\u003c/em\u003e (preserved wet weight mg m\u003csup\u003e-2\u003c/sup\u003e);\u003c/p\u003e\n\u003cp\u003eMeans for ALM, FRM, SOM, and CO2 (n = 10) and means for BEJ (n = 6);\u003c/p\u003e\n\u003cp\u003eDifferent lowercase letters indicate significant differences (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, Tukey HSD test following ANOVA).\u003c/p\u003e\n\u003cp\u003eResults of ANOVA for among-stand variations using log 10 transformed data: \u003cem\u003eF\u003c/em\u003e = 17.53, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01 for ALM; \u003cem\u003eF\u003c/em\u003e = 4.19, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01 for FRM; \u003cem\u003eF\u003c/em\u003e = 17.57, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01 for SOM; \u003cem\u003eF\u003c/em\u003e = 5.69, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01 for CO2; \u003cem\u003eF\u003c/em\u003e = 2.22, \u003cem\u003ep\u003c/em\u003e = 0.051 for BEJ\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6689570/v1/c63e3ffc4406ccc7c22922ff.png"},{"id":88217767,"identity":"e03f4903-44c6-4772-b773-cafd62e9b159","added_by":"auto","created_at":"2025-08-04 07:18:05","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":576593,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6689570/v1/20e6d954-f5be-449d-b893-5d84e32e24b0.pdf"},{"id":84246840,"identity":"2684c9c1-a704-465b-952c-ba1c3f298c27","added_by":"auto","created_at":"2025-06-09 16:58:41","extension":"docx","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":365646,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterials.docx","url":"https://assets-eu.researchsquare.com/files/rs-6689570/v1/e088fac7106a3874202963f9.docx"}],"financialInterests":"","formattedTitle":"Synergism is not the primary aspect of microbe-earthworm interactions in warm temperate forest soil food webs","fulltext":[{"header":"Introduction","content":"\u003cp\u003eUnderstanding the carbon dynamics in terrestrial ecosystems is indispensable for developing ecological strategies to mitigate global warming and sustainable ecosystem management initiatives in a world undergoing climatic change. The decomposition and sequestration of organic matter in the soil, which is the largest carbon pool in terrestrial ecosystems (Amundson \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Schlesinger and Bernhardt \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), is driven by the interaction between soil microbes and invertebrates, especially earthworms, which are the most powerful ecosystem engineers. Plants, in turn, play a critical role in shaping the microbe-invertebrate interactions via litter quality and quantity, whereas the performance of this tripartite system is mediated by climate (e.g., Deyn et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2008\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn forest ecosystems, which constitute a large fraction of the global terrestrial CO\u003csub\u003e2\u003c/sub\u003e sink (e.g., Keenan and Williams \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), four tree functional types\u0026mdash;pioneer, broad-leaved deciduous (mid-to-late-successional species), broad-leaved evergreen, and needle-leaved evergreen\u0026mdash;maintain constant differences in economic leaf traits (net photosynthesis, specific leaf area, and leaf nitrogen) across global climate and vegetation type gradients (Reich et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e1997\u003c/span\u003e). In a recent systematic review, the four tree functional groups were categorized into two litter types, \u0026ldquo;labile\u0026rdquo; and \u0026ldquo;recalcitrant,\u0026rdquo; generating significant differences in earthworm biomass between the forests of the two litter types within each of boreal, cool temperate, and warm temperate region (Tsukamoto \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). However, the relationship between litter type (litter quality) and earthworm biomass was reversed along the temperature gradient, with it being positive at lower temperatures and negative at higher temperatures. That is, in boreal to cool temperate regions, earthworm biomass was higher in labile (high-quality) litter-producing forests than in recalcitrant (low-quality) litter-producing forests, and the reverse was true in warm temperate regions. The hypothesized driving force of this reversal is a phase shift in microbe-earthworm interactions from synergy to competition with increasing temperature.\u003c/p\u003e \u003cp\u003eThe positive relationship between litter quality and earthworm biomass has been well-documented in boreal-to-cool temperate forests in relation to mull versus moder/mor humus formation (Muys, et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e1992\u003c/span\u003e; Neirynck et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Schelfhout, et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Furthermore, parallel responses of bacteria and earthworms to litter quality have been repeatedly noted (e.g., Bal \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e1982\u003c/span\u003e; Frouz \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Petersen and Luxton \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e1982\u003c/span\u003e; Ponge \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2003\u003c/span\u003e and \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Schaefer \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e1991\u003c/span\u003e; Swift et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e1979\u003c/span\u003e; Wallwork \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e1970\u003c/span\u003e), highlighting the synergistic interactions between bacteria and earthworms (Frouz \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Lavelle et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e1995\u003c/span\u003e; Wardle \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2002\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn contrast, information on the negative relationship between litter quality and earthworm biomass and the mechanisms generating it, if any, is lacking. However, in contrast to the litter quality control of soil macro-invertebrate (especially earthworms) biomass prevailing in boreal to cool temperate forests, litter quantity control of soil macro-invertebrate abundance or biomass has been reported in warm temperate (Yoshikawa et al. \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and tropical (Jochum et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Kaspari and Yanoviak \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) forests. A similar contrast between climatic zones was detected in a recent meta-analysis on the global distribution of soil fauna (Heděnec et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2022\u003c/span\u003e); namely, a closer association of soil fauna biomass with litter C/N in boreal forests versus that with net primary productivity in tropical forests.\u003c/p\u003e \u003cp\u003eThese findings imply that the nexus among trees, soil microbes, and soil invertebrates in forest ecosystems changes along the global temperature gradient. This temperature dependence could be one of the driving forces for the biome-dependent contributions of soil invertebrates to litter decomposition (Frouz et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Garc\u0026iacute;a-Palacios et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Makkonen et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Wall et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) and litter consumption (Heděnec et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). If this is the case, the temperature dependence should be considered in the global carbon modelling and sustainable forest management planning on a local scale.\u003c/p\u003e \u003cp\u003eIn this study, sympatric assessments of microbial activity, earthworm biomass, and several variables constituting the decomposer food web were conducted in recalcitrant litter-producing broad-leaved evergreen forests and labile litter-producing broad-leaved deciduous forests in a warm temperate region. This study aimed to empirically confirm the temperature tuning of the three-partite system and verify its hypothesized driving force, a temperature-mediated phase shift in microbe-earthworm interactions between synergy and competition.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003eStudy sites and stands\u003c/p\u003e \u003cp\u003eThe study was conducted in eight stands of secondary broad-leaved forest located within an area of 32\u0026deg;44\u0026prime;\u0026ndash;33\u0026deg;42\u0026prime; N and 132\u0026deg;56\u0026prime;\u0026ndash;134\u0026deg;12\u0026prime; E, at an altitude of 108\u0026ndash;882 m asl. in Southwestern Japan (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). All stands fell within warm temperate moist climate zone [10 ℃ \u0026lt; mean annual temperature\u0026thinsp;\u0026lt;\u0026thinsp;18 ℃ (IPCC \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) and mean annual precipitation\u0026thinsp;\u0026gt;\u0026thinsp;2000 mm]. Four stands each were dominated by broad-leaved evergreen (stand codes E1\u0026ndash;4) and broad-leaved deciduous (stand codes D1\u0026ndash;4) tree species. The soil type and humus form of the seven stands other than E3 were identical [B\u003csub\u003eD\u003c/sub\u003e type (moderately moist brown forest soil) (Forest Soil Division \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e1975\u003c/span\u003e) and Mull type (Ponge \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2003\u003c/span\u003e), respectively]. The soil and humus forms of E3 were B\u003csub\u003eD\u003c/sub\u003e(d) [moderately moist brown forest soil (dryer subtype)] and Mull/Modar, respectively, owing to its dryer slope position.\u003c/p\u003e \u003cp\u003eAnnual litterfall mass\u003c/p\u003e \u003cp\u003eLitterfall was trapped during the period of at least two years starting in October (D4), November (E1\u0026ndash;4) or December (D1\u0026ndash;3) 2013 using 10 circular traps with 0.5 m\u003csup\u003e2\u003c/sup\u003e opening (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). The traps were arranged in a ladder pattern, with the intervals between two adjacent traps being 2 m or 4 m. The materials trapped, excluding branch litter\u0026thinsp;\u0026gt;\u0026thinsp;10 cm in girth, were collected once a month, oven dried (80 ℃, 48 h), and weighed by traps. Since some of the litter traps were sometimes disturbed by mammals and/or typhoon, a complete set of ten traps\u0026rsquo; data during consecutive twelve month-period was selected by stands so as to overlap as largely as possible among the stands (Sep 2014\u0026ndash;Aug 2015 for E4, Oct 2014\u0026ndash;Sep 2015 for D4, Nov 2014\u0026ndash;Oct 2015 for E1\u0026ndash;3 and D3, and Dec 2014\u0026ndash;Nov 2015 for D1 and D2, respectively). Monthly measured values were summed by traps, and were taken as the annual litterfall for each trap, yielding ten samples of annual litterfall mass in each stand.\u003c/p\u003e \u003cp\u003eAnnual mean forest floor mass\u003c/p\u003e \u003cp\u003eLeaf fall phenology differs between broad-leaved evergreen and broad-leaved deciduous trees. Most evergreens have their annual leaf fall peak at the time of leaf flushing in spring, which is from April to May in western Japan; the leaf fall of most deciduous species occurs in late autumn to early winter, which is from October to December. Therefore, for comparability, the annual minimum forest floor mass was assessed from late March to early April 2012 in the evergreen stands and from late September to early October 2012 in the deciduous stands, while the annual maximum forest floor mass was assessed from the end of May to June 2012 in the evergreen stands and from December 2012 to January 2013 in the deciduous stands. The mean of the oven-dry weights (80 ℃, 48h) of ten 30 cm \u0026times; 30 cm quadrat samples of the forest floor was used in each stand on each sampling occasion. The annual mean forest floor mass was estimated as the arithmetic mean of the annual minimum and maximum values, yielding an estimate for each stand.\u003c/p\u003e \u003cp\u003eEarthworm biomass\u003c/p\u003e \u003cp\u003eAnimal sampling was performed in 2010 (E2 and E4) and 2012 (E1, E3, and D1\u0026ndash;D4). In both years, the sampling was performed during the annual peak of earthworm biomass in Japan: June to July (Sota \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e1985\u003c/span\u003e; Sugi and Tanak, 1978; Uchida and Kaneko \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Soil macro-invertebrates larger than 2 mm in body length were collected by hand-sorting from six 30 cm \u0026times; 30 cm quadrat samples of the A\u003csub\u003e0\u003c/sub\u003e-layer and topsoil (0\u0026ndash;10 cm) separately. The collected animals were preserved in 75% ethanol, except for earthworms which were preserved in 10% formalin. In the laboratory, the wet weights of the preserved animals were determined individually to 0.1 mg accuracy by using an analytical balance after carefully placing them on filter paper.\u003c/p\u003e \u003cp\u003eIn this study, we focused on earthworms, the most powerful ecosystem engineers in moist environments that play a dominant role in the regulation of soil processes, including carbon sequestration and decomposition (Lavelle \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e1997\u003c/span\u003e). All the of earthworm specimens were classified into two families, i.e., Megascolecidae or Lumbricidae, based on chaetotaxy. Lumbricid worms were further classified into species using an identification key for Lumbricidae in Japan (Nakamura \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e1972\u003c/span\u003e), with the result that this family was represented exclusively by one species, \u003cem\u003eEisenia japonica\u003c/em\u003e (Michaelsen, 1892). The functional types of Megascolecidae and \u003cem\u003eEisenia japonica\u003c/em\u003e were identified based on the following criteria: limited occurrence in the A\u003csub\u003e0\u003c/sub\u003e-layer epigeic, limited occurrence in the topsoil endogeic, extended occurrence across the two layers anecic, or a complex of at least two functional types.\u003c/p\u003e \u003cp\u003eTopsoil-related variables\u003c/p\u003e \u003cp\u003eA topsoil sample (1\u0026ndash;6 cm in depth) was collected from the vicinity of each litter trap from September to October 2015, yielding ten samples from each stand. Cylindrical soil core samplers of 100 cm\u003csup\u003e3\u003c/sup\u003e in volume (20 cm\u003csup\u003e2\u003c/sup\u003e in basal area \u0026times; 5 cm in height) with known weight to the nearest 10 mg were used. The cylinder samples were sealed with vinyl tape at the upper and lower lids and transported to the laboratory in a cooler box.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eRoot mass\u003c/h2\u003e \u003cp\u003eAfter measuring the CO\u003csub\u003e2\u003c/sub\u003e emission from each cylinder sample as described below, the soil material in the cylinder was air dried, sieved, and sorted into three fractions, fine soil, gravel (\u0026thinsp;≧\u0026thinsp;2 mm in diameter), and root. The root fraction was further separated into fine root (\u0026lt;\u0026thinsp;1.5 mm in diameter) and coarse root (\u0026thinsp;≧\u0026thinsp;1.5 mm in diameter) using a digital caliper. The fractions of fine and coarse root were oven dried (105℃, 24 hr.) and weighed to the nearest 10 mg.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSoil organic matter content\u003c/h3\u003e\n\u003cp\u003eThe fractions of fine soil and gravel were oven dried (105℃, 24 hr.) and weighed to the nearest 10 mg. Ignition loss of a small portion of the fine soil fraction (0.78\u0026ndash;2.85 g oven dry weight) was determined using a muffle furnace (550℃, 5 hr. + 700℃, 1 hr.). Percentage ignition loss (ignition loss/oven-dry weight of the fine soil tested *100) was taken as the organic matter content of the topsoil.\u003c/p\u003e\n\u003ch3\u003eCO\u003csub\u003e2\u003c/sub\u003e emission rate\u003c/h3\u003e\n\u003cp\u003eCO\u003csub\u003e2\u003c/sub\u003e emission from the cylinder samples was measured one by one using the dynamic closed chamber method (Hashimoto \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Within the day of sampling, the cylinder samples were weighed to the nearest 10 mg after removing the vinyl tape, and put in an incubator set at 20℃. After one day incubation at 20\u0026deg;C, each sample, from which the upper lid was removed in advance, was transferred to a plastic chamber which was placed in an incubator set at 20\u0026deg;C. The chamber was connected to a CO\u003csub\u003e2\u003c/sub\u003e analyzer (LI-COR 6252; LI-COR, Lincoln, NE, USA) and an air pump (flow rate: 52.1 ml s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e; MP-2N; Shibata Scientific, Tokyo). The total volume inside the system was 1083.3 ml including the space in the connecting vinyl tubes. For each sample, the CO\u003csub\u003e2\u003c/sub\u003e concentration (\u0026micro;l l\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) in the system was continuously monitored for 7\u0026ndash;8 min after starting the air circulation and recorded at intervals of 5 s. The increment in the CO\u003csub\u003e2\u003c/sub\u003e concentration from 1 to 6 min after starting the air circulation was converted to the volume of CO\u003csub\u003e2\u003c/sub\u003e (\u0026micro;l) emitted in 5 min. The rate of CO\u003csub\u003e2\u003c/sub\u003e emission [\u0026micro;l CO\u003csub\u003e2\u003c/sub\u003e (g dry organic matter)\u003csup\u003e\u0026minus;1\u003c/sup\u003e h\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e] was calculated using oven-dried organic matter mass in each cylinder sample that was calculated as oven-dried fine soil mass multiplied by percentage ignition loss.\u003c/p\u003e \u003cp\u003eData processing\u003c/p\u003e \u003cp\u003eThe forest floor turnover rate (annual litterfall mass/annual mean forest floor mass) was calculated as an indicator of \u003cem\u003ein situ\u003c/em\u003e litter decomposition rate. Regarding earthworms, the biomass of \u003cem\u003eEisenia japonica\u003c/em\u003e was the focus because it was identified as endogeic species (see below) primarily feeding on bacterially processed soil organic matter (Zhong et al., \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Table\u0026nbsp;1 presents the processed variables of interest.\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eThe among-stand variations and between-stand differences in the variables of interest, except for the forest floor turnover rate, were analyzed by using one-way ANOVA and Tukey\u0026rsquo;s HSD test, respectively, using the log 10 transformed raw values of each variable. Other analyses described below were performed using the stand means of each variable, except for the forest floor turnover rate, for which a single representative value from each stand was used.\u003c/p\u003e \u003cp\u003eThe association between tree functional type and the decomposer food web was investigated using linear discriminant analysis, where the external criterion was broad-leaved evergreen versus broad-leaved deciduous, and the independent variables were \u0026ldquo;annual litterfall mass\u0026thinsp;+\u0026thinsp;fine root mass\u0026rdquo; (ALM\u0026thinsp;+\u0026thinsp;FRM), \u0026ldquo;forest floor turnover rate\u0026rdquo; (FFTR), \u0026ldquo;soil organic matter content\u0026rdquo; (SOM), \u0026ldquo;CO\u003csub\u003e2\u003c/sub\u003e emission rate\u0026rdquo; (CO2), and \u0026ldquo;biomass of \u003cem\u003eEisenia japonica\u003c/em\u003e\u0026rdquo; (BEJ) (cf. Table\u0026nbsp;1). Prior to analysis, a log 10 transformation was performed on the stand mean value of each variable to approximate homoscedasticity.\u003c/p\u003e \u003cp\u003eThe similarity in cross-stand patterns between each pair of the variables was tested using Spearman\u0026rsquo;s rank correlation analysis. Multiple regression analysis was performed to test the effects of ALM\u0026thinsp;+\u0026thinsp;FRM (organic matter input) and CO2 (organic matter output) on SOM (organic matter accumulation). Log 10 transformations of stand means were performed to ensure the credibility of this analysis.\u003c/p\u003e \u003cp\u003eAll analyses were performed with R version 4.3.3 (R Core Team \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) except for linear discriminant analysis, for which SPSS 17.0J (IMB) was used. The significance level was set at α\u0026thinsp;=\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eDistribution and functional type of earthworms\u003c/p\u003e \u003cp\u003eBoth Megascolecid and lumbricid worms (\u003cem\u003eE\u003c/em\u003e. \u003cem\u003ejaponica\u003c/em\u003e) occurred in all stands (Table\u0026nbsp;2). Megascolecidae were distributed across the A\u003csub\u003e0\u003c/sub\u003e-layer and topsoil, indicating the multi-functional type composition of this family. In contrast, \u003cem\u003eE. japonica\u003c/em\u003e was almost completely confined to the topsoil, indicating that this species was of the endogeic type, exclusively feeding on bacterially processed organic matter in the soil.\u003c/p\u003e \u003cp\u003eAmong-stand variations and between-stand differences in variables of interest\u003c/p\u003e \u003cp\u003eThe among-stand variations in the variables of interest were significant (ALM, FRM, SOM, and CO2) or marginally significant (BEJ) (Table\u0026nbsp;3), except for FFTR, which was beyond the significance test due to its statistical attributes (Table\u0026nbsp;1).\u003c/p\u003e \u003cp\u003eALM, FRM, SOM, and BEJ tended to be higher in the evergreen forests than in the deciduous forests, with the maximum of each variable being recorded in the evergreen stand and the minimum in the deciduous stand (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Table\u0026nbsp;3). The reverse was true for FFTR. CO2 exhibited a different trend in that both maximum and minimum values were recorded within the deciduous-stand group, that is, D2 and D1, respectively.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eDiscrimination of forest type using variables involved in soil organic matter dynamics\u003c/p\u003e \u003cp\u003eBroad-leaved evergreen stands and broad-leaved deciduous stands were distinguished without misclassification using a significant linear combination of the tested variables (Table\u0026nbsp;4). For all variables, a one-unit change in the standardized variable could cause a discriminant score fluctuation of \u0026gt;\u0026thinsp;10% of its range, with the absolute values of the discriminant function coefficient being 1.304\u0026ndash;3.228 versus the range of the discriminant score of 11.394 (\u0026minus;\u0026thinsp;5.460 to 5.934).\u003c/p\u003e \u003cp\u003eCorrelations between variables of interest across stands\u003c/p\u003e \u003cp\u003eThe BEJ was highly positively correlated with SOM (Table\u0026nbsp;5). The relationships of ALM\u0026thinsp;+\u0026thinsp;FRM with SOM and BEJ tended to be positive. In contrast, the relationships of CO2 with SOM and BEJ tended to be negative.\u003c/p\u003e \u003cp\u003eFactors affecting soil organic matter content\u003c/p\u003e \u003cp\u003eALM\u0026thinsp;+\u0026thinsp;FRM and CO2 were tested for their effects on SOM, resulting in a marginally significant multiple regression equation (Table\u0026nbsp;6). The positive effect of ALM\u0026thinsp;+\u0026thinsp;FRM on SOM was marginally significant. Although the effect of CO2 on SOM was not significant, the partial regression coefficient of CO2 on SOM tended to be negative.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eNexus among trees, microbes, and earthworms in warm temperate forests differs from that in boreal to cool temperate forests\u003c/p\u003e \u003cp\u003eThe complete discrimination between broad-leaved evergreen stands and broad-leaved deciduous stands using linearly combined variables constituting decomposer food web (Table\u0026nbsp;3) indicated that the two tree functional types shaped distinct soil organic matter dynamics. The differential shaping of soil organic matter dynamics by different tree functional types \u003cem\u003eper se\u003c/em\u003e is common knowledge among boreal to cool temperate forest ecosystems. Specifically, mull humus formation is primarily driven by bacteria and earthworms, facilitated by labile litter, whereas mor humus formation predominantly governed by fungi and meso/micro fauna, constrained by recalcitrant litter (e.g., Bal \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e1982\u003c/span\u003e; Frouz \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Petersen and Luxton \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e1982\u003c/span\u003e; Ponge \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2003\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Schaefer \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e1991\u003c/span\u003e; Swift et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e1979\u003c/span\u003e; Wallwork \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e1970\u003c/span\u003e). However, this pattern was not observed in the warm temperate forests in this study. In contrast, the relationships between the following pairs of variables tended to be reversed to those commonly observed in boreal and cool-temperate forests.\u003c/p\u003e\n\u003ch3\u003eLitter decomposability - earthworm biomass relationship\u003c/h3\u003e\n\u003cp\u003eThe trend for FFTR to be higher in deciduous stands than in evergreen stands (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Table\u0026nbsp;3) was consistent with the results of comparative leaf litter decomposition experiments showing higher decomposability of deciduous broadleaf litter than that of evergreen broadleaf litter (Aponte et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Cornelissen et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e1999\u003c/span\u003e; Cornwell, et al. 2008; Pringle et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Rahman and Tsukamoto \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Rawat et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Wang et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Accordingly, a higher BEJ is expected in deciduous stands than in evergreen stands, provided that earthworm biomass patterns in relation to litter decomposability do not differ between warm temperate forests and boreal-to-cool temperate forests. However, the reverse trend was observed (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Table\u0026nbsp;2). The biomass of Megascolecidae also exhibited a similar trend (Table\u0026nbsp;2).\u003c/p\u003e\n\u003ch3\u003eMicrobial activity-earthworm biomass relationship\u003c/h3\u003e\n\u003cp\u003eCO\u003csub\u003e2\u003c/sub\u003e emissions from the soil tend to be higher in labile litter-producing forests (broad-leaved deciduous forests) than in recalcitrant litter producing-forests (coniferous forests) in boreal to cool temperate regions (Jevon et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Raich and Tufekioglu \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Tewary et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e1982\u003c/span\u003e; but Frouz et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). This indicates the parallel responses of microbes and earthworms to tree functional type. This might have led to a somewhat one-sided emphasis on synergistic interactions between bacteria and soil macro-invertebrates, especially earthworms (e.g., Frouz \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Lavelle et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e1995\u003c/span\u003e; Wardle \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2002\u003c/span\u003e, but Scheu and Schaefer \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). In the context of this synergism, a positive relationship between CO2 and BEJ was expected; however, the relationship tended to be negative (Table\u0026nbsp;5).\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eMicrobial activity-soil organic matter content relationship\u003c/h2\u003e \u003cp\u003eThe accumulation of organic carbon in the soil tends to be higher in labile litter-producing forests than in recalcitrant litter-producing forests in boreal to cool temperate regions (Cha et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Frouz et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Jobb\u0026aacute;gy and Jackson \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Nickels and Prescott \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Thus, despite the apparently opposite flow of carbon, both CO\u003csub\u003e2\u003c/sub\u003e emissions from the soil and the accumulation of organic matter in the soil are positively related to litter decomposability. This supports the \u0026ldquo;microbial substrate use efficiency\u0026rdquo; paradigm \u003cem\u003esensu\u003c/em\u003e Cotrufo et al. (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), which was developed mainly on the boreal to cool temperate ecosystem background. However, such a corresponding response to the tree functional types was not observed between CO2 and SOM (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Instead, the relationship between CO2 and SOM tended to be negative across the study stands (Table\u0026nbsp;5).\u003c/p\u003e \u003cp\u003eTree species effects on decomposer food web properties within broad-leaved deciduous forests\u003c/p\u003e \u003cp\u003eStands D1 and D2 were dominated by an oak species (\u003cem\u003eQuercus serrata\u003c/em\u003e Thumb.) and a dogwood species (\u003cem\u003eSwida controversa\u003c/em\u003e (Hemsl.) Sojak), respectively (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). These species are typical recalcitrant and labile litter producers, respectively (e.g., Takeda et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e1987\u003c/span\u003e). This was confirmed in the present study (FFTR in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). In cool temperate regions, beech and ash trees are typical moder-humus forming and mull-humus forming tree species, respectively (Muys and Lust \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e1992\u003c/span\u003e; Neirynck et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). In general, beech stands exhibit lower litter decomposability (Makkonen, et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Melillo et al. 1982; Schelfhout, et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Vesterdal et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Zuo, et al. \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), lower soil respiration (Vesterdal et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), lower earthworm biomass (Muys and Lust \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e1992\u003c/span\u003e; Neirynck et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Schelfhout et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), and lower soil carbon stocks (Vesterdal et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2008\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) than ash stands. D1 (oak) and D2 (dogwood) have contrasting litter decomposabilities similar to beech and ash pair. Nevertheless, comparisons of CO2, BEJ, and SOM between D1 and D2 exhibited inverse magnitude relationships with the beech vs. ash comparisons of the relevant soil food web properties.\u003c/p\u003e \u003cp\u003ePossible explanation for the biome dependent nexus among trees, microbes, and earthworms\u003c/p\u003e \u003cp\u003eAs mentioned above, the mode of differential shaping of decomposer food webs or soil organic matter dynamics by different functional tree types differed between boreal/cool-temperate and warm-temperate forests. A hypothesized mechanism for this difference has recently been proposed (Tsukamoto \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Labile litter promotes earthworms through synergistic interactions with microbes in the regions at lower temperatures but impedes them through competitions with microbes in the regions at higher temperatures. In contrast, recalcitrant litter depresses earthworms with poor synergy benefits from microbes in colder regions but supports earthworms by mitigating microbial competition in warmer regions. The driving force of this hypothetical system is the dual nature of microbe-earthworm interactions (synergistic versus competitive) and the differential momentum of these vectors at different ambient temperatures and, hence, at different levels of microbial activity (e.g., Cruz-Paredes et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Xiao et al. \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The following results of this study do not contradict the enhanced microbial activity at warmer temperatures: the highly positive correlation between SOM and BEJ, an indication of food limitation on endogeic earthworms, and the marginally significant positive effect of ALM\u0026thinsp;+\u0026thinsp;FRM on SOM, an indication of litter quantity control of carbon accumulation in the soil.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe temperature dependence of the nexus among the three major components of forest ecosystems, trees, microbes, and soil invertebrates, and the mechanisms generating it will provide a novel basis for model development to predict changes in global carbon dynamics and for planning sustainable forest management measures at the field scale. Therefore, the sympatric assessments of microbial activity and soil macro-invertebrate biomass along the global temperature gradient and experiments on the effects of temperature on microbe-earthworm interactions merit future studies.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eThe authors declare that no funds, grants, or other support were received during the preparation of this manuscript.\u003c/p\u003e\n\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\u003ch2\u003eAcknowledgement\u003c/h2\u003e \u003cp\u003eWe wish to thank Professor Dr. Tomoaki Ichie, Kyoto Prefectural University, for third-party review and valuable advice.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAmundson R (2001) The carbon budget in soils. Annu Rev Earth Planet Sci 29:535\u0026ndash;562.\u003c/li\u003e\n \u003cli\u003eAponte C, Garcia LV, Maranon T (2013) Tree species effects on nutrient cycling and soil biota: A feedback mechanism favouring species coexistence. Forest Ecol Manag 309: 36\u0026ndash;46. http://dx.doi.org/10.1016/j.foreco.2013.05.035\u003c/li\u003e\n \u003cli\u003eBal L (1982) Zoological Ripening of Soils. Centre for Agricultural Publishing and Documentation, Wageningen.\u003c/li\u003e\n \u003cli\u003eCha J‐Y, Cha Y, Oh N‐H (2019) The effects of tree species on soil organic carbon content in South Korea. J Geophys Res-Biogeo 124: 708\u0026ndash;716. https://doi.org/10. 1029/2018JG004808\u003c/li\u003e\n \u003cli\u003eCornelissen JHC, P\u0026eacute;rez-Harguindeguy N, D\u0026iacute;az S, Grime J P, Marzano B, Cabido M, Vendramini F, Cerabolini B (1999) Leaf structure and defense control litter decomposition rate across species and life forms in regional floras on two continents. New Phytol 143: 191\u0026ndash;200.\u003c/li\u003e\n \u003cli\u003eCornwell WK et al (2008) Plant species traits are the predominant control on litter decomposition rates within biomes worldwide. Ecol Lett 11: 1065\u0026ndash;1071.\u003c/li\u003e\n \u003cli\u003eCotrufo MF, Wallenstein MD, Boot CM, Denef K, Paul E (2013) The Microbial Efficiency-Matrix Stabilization (MEMS) framework integrates plant litter decomposition with soil organic matter stabilization: do labile plant inputs form stable soil organic matter? Glob Chang Biol 19(4): 988\u0026ndash;995. doi: 10.1111/gcb.12113.\u003c/li\u003e\n \u003cli\u003eCruz-Paredes C, D\u0026aacute;niel T, Johannes R (2021) Can moisture affect temperature dependences of microbial growth and respiration? Soil Biol Biochem 156: 103223. https://doi.org/10.1016/j.soilbio.2021.108223.\u003c/li\u003e\n \u003cli\u003ede Deyn GB, Cornelissen JHC, Richard DB (2008) Plant functional traits and soil carbon sequestration in contrasting biomes. Ecol Lett 11: 516\u0026ndash;531.\u003c/li\u003e\n \u003cli\u003eForest Soil Division (1975) Classification of forest soil in Japan. Bulletin of the Government Forest Experiment Station 280: 1\u0026ndash;28. (in Japanese with English summary)\u003c/li\u003e\n \u003cli\u003eFrouz J (2018) Effects of soil macro- and mesofauna on litter decomposition and soil organic matter stabilization. Geoderma 332: 161\u0026ndash;172. http://dx.doi.org/10.1016/j. geoderma.2017.08.039\u003c/li\u003e\n \u003cli\u003eFrouz J, Pižl V, Cienciala A, Kalč\u0026iacute;k J (2009) Carbon storage in post-mining forest soil, the role of tree biomass and soil bioturbation. Biogeochemistry 94: 111\u0026ndash;121.\u003c/li\u003e\n \u003cli\u003eFrouz J, Livečkov\u0026aacute;, M, Albrechitov\u0026aacute; J, Chroň\u0026aacute;kov\u0026aacute; A, Cajthaml T, Pižl V, H\u0026aacute;nӗl L, Stary J, Baldrian P, Lhot\u0026aacute;kov\u0026aacute; Z, Sim\u0026aacute;čkov\u0026aacute; H, Cep\u0026aacute;kov\u0026aacute; S, (2013) Is the effect of trees on soil properties mediated by soil fauna? A case study from post-mining sites. Forest Ecol Manag 309: 87\u0026ndash;95.\u003c/li\u003e\n \u003cli\u003eFrouz J, Roub\u0026iacute;čkov\u0026aacute; A, Heděnec P, Tajovsk\u0026yacute; K (2015) Do soil fauna really hasten litter decomposition? A meta-analysis of enclosure studies. Eur J Soil Biol 68: 18-24. http://www.elsevier.com/locate/ejsobi\u003c/li\u003e\n \u003cli\u003eGarc\u0026iacute;a-Palacios P, Maestre FM, Kattge J, Wall DH (2013) Climate and litter quality differently modulate the effects of soil fauna on litter decomposition across biomes. Ecol Lett 16: 1045\u0026ndash;1053.\u003c/li\u003e\n \u003cli\u003eHashimoto S (2005) Temperature sensitivity of soil CO\u003csub\u003e2\u003c/sub\u003e production in a tropical hill evergreen forest in northern Thailand. J For Res 10: 497\u0026ndash;503.\u003c/li\u003e\n \u003cli\u003eHeděnec P, Jim\u0026eacute;nez JJ, Moradi J, Domene X, Hackenberger D, Barot S, Frossard A, Oktaba L, Filser J, Kindlmann P, Frouz J. (2022) Global distribution of soil fauna functional groups and their estimated litter consumption across biomes. Sci. Rep. 12:17362. https://doi.org/10.1038/s41598-022-21563-z\u003c/li\u003e\n \u003cli\u003eIPCC (2006) Guidelines for National Greenhouse Gas Inventories. https://www.ipcc-nggip.iges.or.jp /public/2006gl/vol2.html.\u003c/li\u003e\n \u003cli\u003eJevon FV, Gewirtzman J, Lang AK, Ayres MP, Matthes JH (2023) Tree species effects on soil CO\u003csub\u003e2\u003c/sub\u003e and CH\u003csub\u003e4\u003c/sub\u003e fluxes in a mixed temperate forest. Ecosystems 26: 1587\u0026ndash;1602. https://doi.org/10.1007/s10021-023-00852-2\u003c/li\u003e\n \u003cli\u003eJobb\u0026aacute;gy EG, Jackson RB (2000) The vertical distribution of soil organic carbon and its relation to climate and vegetation. Ecol Appl 10(2): 423\u0026ndash;436.\u003c/li\u003e\n \u003cli\u003eJochum M, Barnes AD, Weigelt P, Ott D, Rembold K, Farajallah A, Brose U (2017) Resource stoichiometry and availability modulate species richness and biomass of tropical litter macro-invertebrates. J Anim Ecol 86: 1114\u0026ndash;1123.\u003c/li\u003e\n \u003cli\u003eKaspari M, Yanoviak SP, (2009) Biogeochemistry and the structure of tropical brown food webs. Ecology 90: 3342\u0026ndash;3351.\u003c/li\u003e\n \u003cli\u003eKeenan TF, Williams CA (2018) The terrestrial carbon sink. Annu Rev Env Resour 43: 219\u0026ndash;243. https://doi.org/10.1146/annurev-environ-102017-030204\u003c/li\u003e\n \u003cli\u003eLavelle P (1997) Faunal activities and soil processes: Adaptive strategies that determine ecosystem function. Adv Ecol Res 27: 93132.\u003c/li\u003e\n \u003cli\u003eLavelle P, Lattaud C, Trigo D, Barois L (1995). Mutualism and biodiversity in soils. Plant Soil 170: 23\u0026ndash;33.\u003c/li\u003e\n \u003cli\u003eMakkonen M, Matty P, Berg I, Handa T, H\u0026auml;ttenschwiler S, van Rujiven J, van Bodegom PM, Aerts R (2012) Highly consistent effects of plant litter identity and functional traits on decomposition across a latitudinal gradient. Ecol. Lett. 15: 1033\u0026ndash;1041.\u003c/li\u003e\n \u003cli\u003eMelillo JM, Aber JD (1982) Nitrogen and Lignin control of hardwood leaf litter decomposition dynamics. Ecology 63: 621\u0026ndash;626.\u003c/li\u003e\n \u003cli\u003eMuys B, Lust N (1992) Inventory of earthworm communities and the state of litter decomposition in the forests of Flanders, Belgium, and its implications for forest management. Soil Biol Biochem 24: 1677\u0026ndash;1681.\u003c/li\u003e\n \u003cli\u003eMuys N, Lust N, Granval PH (1992) Effects of grassland afforestation with different tree species on earthworm communities, litter decomposition and nutrient status. Soil Biol Biochem 24: 1459\u0026ndash;1466.\u003c/li\u003e\n \u003cli\u003eNakamura Y (1972) Morphological obsevations of cocoon, larva and adult of Lumbricidae. B Natl Grassl Res Inst 1: 6\u0026ndash;16.\u003c/li\u003e\n \u003cli\u003eNeirynck J, Mirtchevaa S, Sioen G, Lust N (2000) Impact of Tilia platyphyllos Scop., Fraxinus excelsior L., Acer pseudoplatanus L., Quercus robur L. and Fagus sylvatica L. on earthworm biomass and physico-chemical properties of a loamy topsoil. Forest Ecol Manag 133: 275\u0026ndash;286.\u003c/li\u003e\n \u003cli\u003eNickels MCL, Prescott CE (2021) Soil carbon stabilization under coniferous, deciduous and grass vegetation in post-mining reclaimed ecosystems. Front For Glob Change 4: 689594.\u003c/li\u003e\n \u003cli\u003ePetersen H, Luxton M (1982) A comparative analysis of soil fauna populations and their role in decomposition processes. Oikos 39, 287\u0026ndash;388.\u003c/li\u003e\n \u003cli\u003ePonge JF (2003) Humus forms in terrestrial ecosystems: a framework to biodiversity. Soil Biol Biochem 35: 935\u0026ndash;945.\u003c/li\u003e\n \u003cli\u003ePonge JF, (2013) Plant\u0026ndash;soil feedbacks mediated by humus forms: A review. Soil Biol Biochem 57: 1048\u0026ndash;1060.\u003c/li\u003e\n \u003cli\u003ePringle EG, Adams RI, Broadbent E, Busby PE, Donatti CI, Kurten EL. 1, Renton K, Dirzo R (2011) Distinct leaf-trait syndromes of evergreen and deciduous trees in a seasonally dry tropical forest. Biotropica 43(3): 299\u0026ndash;308.\u003c/li\u003e\n \u003cli\u003eRahman MM, Tsukamoto J (2013) Leaf traits, litter decomposability and forest floor dynamics in an evergreen- and deciduous broadleaved forest in warm temperate Japan. Forestry 86: 441\u0026ndash;451.\u003c/li\u003e\n \u003cli\u003eRaich JW, Tufekioglu A (2000) Vegetation and soil respiration: Correlations and controls. Biogeochemistry 48: 71\u0026ndash;90.\u003c/li\u003e\n \u003cli\u003eRawat M, Arunachalam K, Arunachalam A, Alatalo JM, Pandey R (2021) Assessment of leaf morphological, physiological, chemical and stoichiometry functional traits for understanding the functioning of Himalayan temperate forest ecosystem. Sci Rep-UK 11: 23807. https://doi.org/10.1038/s41598-021-03235-6\u003c/li\u003e\n \u003cli\u003eR Core Team, 2024. R package version 4.3.3\u003c/li\u003e\n \u003cli\u003eReich PB, Walters MB, Elsworth DS (1997) From tropics to tundra: Global convergence in plant functioning. Proc Natl Acad Sci USA 94: 13730\u0026ndash;13734.\u003c/li\u003e\n \u003cli\u003eSchaefer M (1991) Fauna of the European temperate deciduous forest. In: R\u0026ouml;hrig E, Ulrich B (Eds) Ecosystems of the World 7, Temperate deciduous forests. Elsevier, Amsterdam, pp 503\u0026ndash;525.\u003c/li\u003e\n \u003cli\u003eSchaefer M, Schauermann J (1990) The soil fauna of beech forests: comparison between mull and a moder soil. Pedobiol 34: 299\u0026ndash;314.\u003c/li\u003e\n \u003cli\u003eSchelfhout S, Mertens J, Verheyen K, Vesterdal L, Baeten L, Muys B, de Schrijver A (2017) Tree species identity shapes earthworm communities. Forests 8: 85.\u003c/li\u003e\n \u003cli\u003eSchlesinger WH, Bernhardt ES (2013) Biogeochemistry: An analysis of global change. 3rd edn. Elsevier, Amsterdam.\u003c/li\u003e\n \u003cli\u003eScheu S, Schaefer M (1998) Bottom-up control of the soil macrofauna community in a beechwood on limestone: manipulation of food resources. Ecology 79: 1573\u0026ndash;1585.\u003c/li\u003e\n \u003cli\u003eSota T (1985) Activity patterns, diets and interspecific interactions of coexisting spring and autumn breeding carabids: \u003cem\u003eCarabus jaconinus\u003c/em\u003e and \u003cem\u003eLeptocarabus kumagaii\u003c/em\u003e (Coleoptera, Carabidae). Ecol Entomol 10: 315\u0026ndash;324.\u003c/li\u003e\n \u003cli\u003eSugi Y, Tanaka M (1978) Number and biomass of earthworm populations. In: Kira T, Ono Y, Hosokawa T. (Eds.) Biological Production in a warm-temperate evergreen oak forest of Japan. University of Tokyo Press, Tokyo, pp 171-178.\u003c/li\u003e\n \u003cli\u003eSwift MJ, Heal OW, Anderson JM (1979). Decomposition in Terrestrial Ecosystems. Blackwell, Oxford.\u003c/li\u003e\n \u003cli\u003eTakeda H, Ishida T, Tsutsumi T (1987) Decomposition of leaf litter in relation to litter quality and site conditions. Mem Coll Agric Kyoto Univ 130: 17\u0026ndash;38.\u003c/li\u003e\n \u003cli\u003eTewary CK, Pandey UMA, Singh JS (1982) Soil and litter respiration rates in different microhabitats of a mixed oak-conifer forest and their control by edaphic conditions and substrate quality. Plant Soil 65: 233\u0026ndash;228.\u003c/li\u003e\n \u003cli\u003eTsukamoto J (2025) Pragmatic categorization of moist woodland ecosystems of the world matching the pattern of earthworm biomass. Appl Soil Ecol 212: 106172.\u003c/li\u003e\n \u003cli\u003eUchida T, Kaneko, N (2004). Life history of Megascolecidae earthworms in forest soils at Kanagawa, Japan. Edaphologia 74: 35-45. (in Japanese with English summary)\u003c/li\u003e\n \u003cli\u003eVesterdal L, Schmidt IK, Callesen I, Nilsson LO, Gundersen P (2008) Carbon and nitrogen in forest floor and mineral soil under six common European tree species. Forest Ecol Manag 255: 35\u0026ndash;48.\u003c/li\u003e\n \u003cli\u003eVesterdal L, Elberling B, Christiansen JR, Callesen I, Schmidt IK (2012) Soil respiration and rates of soil carbon turnover differ among six common European tree species. Forest Ecol Manag 264: 185\u0026ndash;196.\u003c/li\u003e\n \u003cli\u003eVesterdal L, Clarke N, Sigurdsson BD, Gundersen P (2013) Do tree species influence soil carbon stocks in temperate and boreal forests? Forest Ecol Manag 309: 4\u0026ndash;18.\u003c/li\u003e\n \u003cli\u003eWall DH et al (2008) Global decomposition experiment shows soil animal impacts on decomposition are climate-dependent. Glob Change Biol 14: 2661\u0026ndash;2677.\u003c/li\u003e\n \u003cli\u003eWallwork J A (1970) Ecology of Soil Animals. McGraw-Hill, London.\u003c/li\u003e\n \u003cli\u003eWang L, He Y, Muhammad U, Guo Y, Tan Q, Kang L, Fang Z, Shen K, Xia T, Wu P, Liu Y, Zang L, Liu Q, Zhao Y, Chen H, Zhao Y (2023) Strategic differentiation of subcommunities composed of evergreen and deciduous woody species associated with leaf functional traits in the subtropical mixed forest. Ecol Indic 150: 110281. https://doi.org/10.1016/j.ecolind.2023.110281\u003c/li\u003e\n \u003cli\u003eWardle DA (2002) Communities and Ecosystems. Princeton University Press, Princeton and Oxford.\u003c/li\u003e\n \u003cli\u003eXiao HB, Shi ZH, Li ZW, Chen J, Huang B, Yue ZJ, Zhan YM (2021) The regulatory effects of biotic and abiotic factors on soil respiration under different land-use types. Ecol. Indic. 127: 107787. https://doi.org/10.1016/j.ecolind. 2021.107787\u003c/li\u003e\n \u003cli\u003eYoshikawa Y, Kawano K, Tsukamoto J (2021) Litter quantity controls soil macr-invertebrate biomass in warm temperate broad-leaved forests of Southwestern Japan. Appl. Soil Ecol. 161, 103870. https://doi.org/10.1016/j.apsoil. 2020.103870.\u003c/li\u003e\n \u003cli\u003eZhong L, Larsen T, Lu J Z, Scheu S, Pollierer M M (2025) High litter quality enhances plant energy channeling by soil macro-detritivores and lowers their trophic position. Ecology 106, e70004. https://doi.org/10.1002/ecy.70004\u003c/li\u003e\n \u003cli\u003eZuo J, Hefting MM, Berg M P, van Logtestijn RSP, van HalJ, Goudzwaard L, Liu JC, Sass-Klaassen U, Sterck FJ, Poorter L, Cornelissen J HC (2018) Is there a tree economics spectrum of decomposability? Soil Biol Biochem 119: 135\u0026ndash;142. https://doi.org/10.1016/j. soilbio 2018.01.019.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Biological interaction, Temperature dependence, Tree functional type, CO2 emission rate, Endogeic earthworm biomass, Warm temperate forests","lastPublishedDoi":"10.21203/rs.3.rs-6689570/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6689570/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground and Aims\u003c/b\u003e\u003c/p\u003e \u003cp\u003eUnderstanding carbon dynamics in forest ecosystems\u0026mdash;driven primarily by trees, soil microbes, and earthworms\u0026mdash; is indispensable in developing ecological strategies to mitigate global warming. A recent systematic review revealed that the effects of tree functional types on earthworms differ between boreal/cool-temperate and warm-temperate forests. The hypothesized driving force of this difference is a phase shift in microbe-earthworm interactions between synergy and competition along the global temperature gradient. This study aims to empirically verify this hypothesis.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e \u003cp\u003eIn a warm temperate region, the six components of decomposer food webs, annual litterfall mass, fine root mass, forest floor turnover rate, soil organic matter content, CO\u003csub\u003e2\u003c/sub\u003e emission rate from the soil, and endogeic earthworm biomass were assessed in each four stands of two forest types\u0026mdash;labile litter-producing deciduous and recalcitrant litter-producing evergreen broadleaf forests.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe two forest types were distinguished without misclassification using a significant linear combination of the six variables of interest. However, regarding the latter three variables (soil, microbes, and earthworms related-variables), the magnitude relationships between the forest types were opposite to those commonly observed in boreal and cool temperate regions.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusion\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe reversal in the relationship between tree functional types and decomposer sub-systems between boreal/cool temperate and warm temperate forests empirically supports the hypothesis that could provide a novel basis for global carbon modelling. Therefore, the dual nature of microbe-earthworm interactions (synergistic versus competitive) and the effects of temperature on the relative importance of the two aspects merit future experimental studies.\u003c/p\u003e","manuscriptTitle":"Synergism is not the primary aspect of microbe-earthworm interactions in warm temperate forest soil food webs","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-09 16:58:36","doi":"10.21203/rs.3.rs-6689570/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"17a34ec6-6af2-4adb-937e-c490071f3334","owner":[],"postedDate":"June 9th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-08-04T07:09:59+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-09 16:58:36","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6689570","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6689570","identity":"rs-6689570","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}