Chemical weathering produces solutes that control groundwater chemistry and supply ecosystems with essential nutrients. Although microbial activity influences silicate weathering rates and associated nutrient fluxes, its relative contribution to silicate weathering in natural settings remains largely unknown. We provide the first quantitative estimates of in situ silicate weathering rates that account for microbially induced dissolution and identify microbial actors associated with weathering. Nanoscale topography measurements showed that fungi colonizing olivine [(Mg,Fe)2SiO4] samples in a Mg-deficient forest soil accounted for up to 16% of the weathering flux after 9 mo of incubation. A local increase in olivine weathering rate was measured and attributed to fungal hyphae of Verticillium sp. Altogether, this approach provides quantitative parameters of bioweathering (i.e., rates and actors) and opens new avenues to improve elemental budgets in natural settings.A next frontier in quantitative modeling of silicate weathering in the critical zone, where “rocks meet life” (Brantley et al., 2011), is the incorporation of microbial activity in reactive transport models (RTMs; Frings and Buss, 2019; Goddéris et al., 2019). Microorganisms contribute to the transformation of rock to regolith (Napieralski et al., 2019), and microbially mediated weathering fluxes of silicates may have been critical for the habitability of Earth (Schwartzman and Volk, 1989). This process could also impact the development of carbon capture and storage strategies based on silicate dissolution, such as enhanced rock weathering (Beerling et al., 2020). However, the contribution of microorganisms to silicate weathering in natural settings remains uncertain (Frings and Buss, 2019).Microorganisms owe their survival to their ability to scavenge elements with low solubility and/or concentration, or trace metals used as enzyme cofactors, for which minerals may be the unique source (Banfield et al., 1999). Echoing the paradigm proposed by Hazen et al. (2008), the coevolution of the geo- and biospheres may favor microbial communities specifically adapted to each mineral surface, possibly harboring microorganisms with efficient weathering ability (Uroz et al., 2015). Microenvironments are generated at the silicate-microbe interface (Benzerara et al., 2005), where locally aggressive conditions can remarkably increase silicate weathering rates (Bonneville et al., 2009; Li et al., 2016), as reported in numerous laboratory experiments involving microbial cultures (Uroz et al., 2015). However, quantitative upscaling of laboratory results to natural settings is not straightforward.On the one hand, laboratory experiments are not designed to be fully representative of natural environments. These experiments generally use synthetic media, which purposely stimulate microbial growth and/or bioweathering, and result in higher microbially mediated mineral dissolution rates than under field conditions. In addition, the commonplace use of axenic strains cannot account for the interplay between distinct populations in a microbial community and its effect on mineral dissolution rates.On the other hand, probing microbial weathering in the field is challenging. Concentrations in soil solution of biomolecules promoting silicate dissolution, such as organic acids (OAs), are frequently argued to be too low in natural settings to increase the dissolution rate beyond the microbe-mineral contact (Drever and Stillings, 1997). While most estimates of microbially mediated silicate weathering rates so far have been derived from laboratory experiments (Wild et al., 2018), a few pioneering studies have provided environmental estimates for naturally altered minerals in surface aquifers (Rogers and Bennett, 2004) or soil profiles (e.g., van Schöll et al., 2008, and references therein) based on scanning electron microscopy (SEM) analysis. However, current approaches are not suited to quantify the actual mineral volume dissolved by microorganisms such as fungi and fail to provide a simultaneous measurement of the fungal-free contribution to the overall dissolution rate in situ. As a result, clear imprints of bioweathering often remain subtle and controversial (Knowles et al., 2012), while models predicting mineral dissolution and associated carbon and nutrient budgets overlook the contribution of microbial actors, which remains essentially unknown.We developed an approach to directly quantify in situ mineral weathering rates in natural environments, providing a joint evaluation of the fungal contribution to the overall weathering flux and the associated fungal diversity. Our approach relies on the in situ incubation of well-characterized mineral samples, which circumvents the aforementioned limitations by ensuring a representative biogeochemical environment while providing quantitative rate estimates. It combines an interpretation of the nanoscale topography of mineral surfaces resulting from weathering (Kirtzel et al., 2017; Fischer and Luttge, 2018) with an analysis of associated microbial taxa using DNA–based high-throughput sequencing (Jones and Bennett, 2014). Olivine samples were incubated for 9 mo in the A horizon of a Mg-deficient forest soil to probe its weathering potential. The incubation of basaltic minerals in base-poor soils has been recently acknowledged as a promising strategy to stimulate enhanced rock weathering for carbon dioxide removal (Beerling et al., 2020). However, the biotic and abiotic contributions to the overall weathering rate have not yet been experimentally teased apart in natural settings, partly due to the complexity in obtaining an abiotic reference point that does not exist on Earth today (Frings and Buss, 2019). Cross-correlations of optical microscopy images with vertical scanning interferometry (VSI) topography data provided the first in situ quantification of mineral dissolution rates together with estimates of the fungal contribution to the overall weathering rate. These results were coupled with fungal diversity data to identify potential fungal taxa associated with bioweathering. Altogether, this approach provides a long sought-after framework for benchmarking quantitative reaction models while incorporating microbially driven weathering.Olivine samples were prepared both as crushed powders (160–315 μm) and polished monoliths (∼5 mm on a side), packed into nylon bags, and sterilized in ethanol. The nylon bags were buried for 9 mo into the A horizon of a Mg-deficient forest soil (beech plot) developed on a Hercynian base-poor granite located in the Strengbach catchment, Aubure, France (48°12′41.04″N, 7°11′45.66″E) (Pierret et al., 2018). The plot chosen for this study was part of an instrumented site of the Observatoire Hydro-Géochimique de l'Environnement (OHGE) critical zone observatory, which enabled us to retrieve environmental parameters monitored on site during sample incubation. Olivine was purposely selected because it has recently been proposed as an additive to promote enhanced weathering in Mg-deficient soils. The average pH of soil solution was 4.2 ± 0.2, and concentrations of the most common low-molecular-weight OAs (acetate, formate, malonate, oxa-late, citrate) measured by ion chromatography (ICS 3000 DIONEX) were below the detection limit (<5 mmol/L). The temperature of the soil varied between 25 °C and −9 °C, and the average precipitation was ∼125 mm/mo over the incubation period.Monolith samples were visualized with reflected light microscopy and SEM (Tescan® VEGA II). Materials adhering to the surface were then mechanically and chemically removed using cotton swabs, ethanol, and acetone. The difference in nanotopography between weathered and unweathered regions of the olivine surface masked with a room-temperature vulcanizing (RTV) glue spot was measured using VSI (Zygo NewView 7300), from which rate maps were extracted as described in Fischer and Luttge (2018). Subsequent transformation of rate data from the spatial domain to the frequency domain was used to generate rate spectra (Fischer and Luttge, 2018), from which rate contributors were identified.After 9 mo, total DNA was extracted with a PowerSoil® DNA Isolation Kit (MO BIO, Carlsbad, California, USA) both from the olivine powder samples and the surrounding soil. DNA was quantified with a Qubit 2.0 spectrofluorometer (Life Technologies, Grand Island, New York, USA). Fungal diversity was evaluated for each sample by targeting the internal transcribed spacer 2 (ITS2) region of the 18S ribosomal ribonucleic acid (rRNA) gene, amplified using a standardized 18S amplicon library protocol as previously described by, e.g., Al-Bulushi et al. (2017). Gene sequences were analyzed by Geno-screen Laboratory (Lille, France) using a standard analysis pipeline (Al-Bulushi et al., 2017). Sequencing data obtained after treatment and classification were used to examine the fungal community composition. Fungal enrichment at the genus level was estimated based on the ratio of the relative abundance of the fungal genus associated with the olivine sample (nolivine) to the relative abundance of the fungal genus in soil (nsoil).DNA sequences were deposited in the National Center for Biotechnology Information (NCBI) BioProject database and are freely accessible through the NCBI website (https://www.ncbi.nlm.nih.gov/bioproject/638437).Optical microscopy and SEM analyses showed abundant filaments on the olivine samples (Fig. 1A), typical of colonization by fungal hyphae (e.g., van Schöll et al., 2008).SEM and VSI analyses evidenced depressions located underneath the hyphae after their removal, such as those shown in Figures 1B and 2A (green arrows). These features were absent from the initial minerals and contrasted with crystallographically controlled etch pits (Fig. 1B, black arrows) typical of abiotic weathering of olivine (Velbel, 2009). They were thus interpreted as the result of local bioweathering.VSI measurements of the surface topography indicated that the average depth of fungi-associated depression was 235 ± 125 nm; after conversion to a local dissolution rate, this corresponds to 2.2 ± 1.2 × 10−10 moles of olivine per square meter per second (mol/m2/s). This value does not consider the potential contribution of solid-state leaching through an amorphous silica-rich layer, as suggested, for instance, for biotite-fungi interactions by Bonneville et al. (2011). Arguably, such amorphous layers are very thin (≤5 nm) on olivine weathered at ambient temperature (Hellmann et al., 2012) and might even be absent at the fungus-olivine interface (Gerrits et al., 2021). This contribution can therefore be neglected.In contrast, the average value of surface retreat for the whole sample was 23 ± 2 nm (dissolution rate of 2.2 ± 0.2 × 10−11 mol/m2/s), reflecting olivine weathering resulting from the interaction between the bulk soil solution and olivine, without direct fungal contribution. Taken together, the magnitude of enhanced dissolution under the fungal hyphae (∼10-fold factor) is very similar to the estimation by Bonneville et al. (2011) from laboratory experiments with biotite.Rate spectra analysis (Fig. 2B) helped to tease apart biotic and abiotic contributions to the overall dissolution rate. Two clusters of peaks can be distinguished from the reference surface (yellow in Fig. 2B). They correspond to rate contributions of the fungal-free portion of the surface impacted by fluid-mineral interactions (blue in Fig. 2B), and to fungus-related weathering (green in Fig. 2B). The latter cluster exhibited faster average rates with smaller integral (due to smaller surface area) and included several rate contributors likely related to the evolution of the spatial extent of fungal weathering. Interestingly, the overall dissolution rate was lower than rates estimated with RTMs based on environmental parameters (fluid composition, soil temperature) recorded at this location during sample incubation (∼10–20 times lower depending on the model chosen; for more discussion on this discrepancy, see Wild et al. [2019]). Those simulations were based on state-of-the-art kinetic parameters and did not include any bioweathering component. This emphasizes the observation that microbial weathering is insignificant in areas devoid of hyphae, which would otherwise tend to increase rates compared to abiotic estimates.Fungal-mediated fluxes accounted for up to 16% of the dissolution flux over 9 mo, as estimated from a portion of the olivine surface area colonized by fungi. This estimation falls within the range of values previously reported using indirect methods (0.5%–50%; see van Schöll et al., 2008). It probably represents a lower bound, since fungal colonization of olivine likely did not reach a steady state. Our results show that possible fungal contribution to the dissolution process is spatially limited to the close vicinity of hyphae in contact with the mineral surface, consistent with the importance of surface attachment in microbial weathering processes highlighted in previous studies (Bonneville et al., 2011; Ahmed and Holmstrom, 2015; Gerrits et al., 2021). Moving forward, evaluation of the spatial heterogeneity related to, for example, mineral surface coverage by microorganisms and assessments of its temporal evolution will constitute key steps in the formulation, parameterization, and validation of “microbially informed” RTMs (Meile and Scheibe, 2019). This can be achieved by extending approaches combining surface imaging with surface topography analysis, such as developed in the present study, to larger sets of samples including time series. Moreover, the extent of local silicate weathering was related to potential fungal actors. Relating reaction rates, microbial community composition, and, ultimately, their functional traits is another prerequisite to further develop RTMs that explicitly represent microorganisms (Meile and Scheibe, 2019). The fungal diversity associated with the olivine samples differed from that of the bulk soil, with the specific enrichment in a limited number of genera compared to the surrounding soil (Fig. 3). This echoes previous studies suggesting that single minerals represent a specific ecological niche for bacteria (Mitchell et al., 2013; Jones and Bennett, 2014; Uroz et al., 2015) and fungi (Gleeson et al., 2005). The main fungal genera, most likely corresponding to the hyphae observed by optical microscopy, were Hydnotrya (14.3%), Mortierella (12.0%), and Verticillium (4.4%) (Fig. 1A). In particular, some members of the most enriched genus at the olivine surface, i.e., Verticillium (cf. Fig. 3), are capable of synthesizing OAs and siderophores and can weather Mg-silicates (Daghino et al., 2009). Chemotaxis might be a major mechanism that promoted olivine colonization and subsequent dissolution by fungal hyphae, since olivine samples were incubated in a Mg-deficient soil compartment (Wild et al., 2019).Species belonging to the Verticillium genus (Fig. 3) may thus be associated with high-dissolution-rate features (Fig. 2B) and may be involved in silicate weathering and CO2 draw-down when stimulated with the appropriate silicate substrates. The triggering of bioweathering mechanisms, namely, the upregulation of genes involved in carbonate ion production from CO2 in the presence of silicate minerals, was reported for another Ascomycete fungus (Aspergillus fumigatus; Xiao et al., 2012). This study and others (e.g., Olsson-Francis et al., 2010; Kirtzel et al., 2017) further support the conclusion that microbial weathering processes play a role in the determination of accurate fluxes of carbon and bioavailable nutrients in the critical zone.Overall, our study demonstrates that local weathering rates can be determined in situ while identifying the actors involved in microbially mediated dissolution and quantifying their effect on weathering fluxes. The proposed approach can be extended to probe the bioweathering potential of a virtually unlimited range of natural environments as well as in sensitive industrial contexts, for which knowledge of the microbial contribution to corrosion and silicate weathering is not only fundamental but also urgently needed (Trias et al., 2017). The incubation of mineral probes in situ provides the reference kinetic parameters and microbial data required to set up a next generation of RTMs accounting for microbially mediated mineral dissolution. Gradual inclusion of microbial dynamics in RTMs constitutes an important milestone in modeling the biosphere and its impact on regolith (Goddéris et al., 2019). Beyond providing a quantitative assessment of bioweathering rates, the proposed approach is also well suited to identify biosignatures on material surfaces, which is a prerequisite to confirm the biotic contribution to dissolution and unravel underlying bioweathering mechanisms.We acknowledge the Strengbach Catchment Critical Zone Observatory, OHGE (Observatoire Hydro-Géochimique de l'Environnement) and the French critical zone observatories network (OZCAR). We thank two anonymous reviewers and Mats Åström, who helped to improve the manuscript. This work was funded by the project ANR-20-ERC8–0006–01_t erc mobidic, awarded to D. Daval, and by the MicXtreme project (LABEX ANR-11-LABX-0050_G-EAU-THERMIE-PROFONDE), awarded to G. Imfeld.

中文翻译：

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直接测量真菌对土壤硅酸盐风化率的贡献

化学风化产生的溶质控制地下水化学并为生态系统提供必需的养分。尽管微生物活动影响硅酸盐风化速率和相关的养分通量，但其对自然环境中硅酸盐风化的相对贡献仍然很大程度上未知。我们提供了原位硅酸盐风化速率的首次定量估计，该速率解释了微生物诱导的溶解，并确定了与风化相关的微生物因素。纳米级地形测量表明，在 9 个月的孵化后，在缺镁的森林土壤中定植橄榄石 [(Mg,Fe)2SiO4] 样品的真菌占风化通量的 16%。测量了橄榄石风化率的局部增加，并将其归因于轮枝菌属的真菌菌丝。共，这种方法提供了生物风化的定量参数（即速率和参与者），并开辟了改善自然环境中元素预算的新途径。 临界区硅酸盐风化定量建模的下一个前沿，在那里“岩石与生命相遇”（Brantley et al ., 2011)，是将微生物活动纳入反应性运输模型（RTM；Frings 和 Buss，2019；Goddéris 等，2019）。微生物有助于岩石向风化层的转化（Napieralski 等，2019），微生物介导的硅酸盐风化通量可能对地球的宜居性至关重要（Schwartzman 和 Volk，1989）。该过程还可能影响基于硅酸盐溶解的碳捕获和储存策略的发展，例如增强的岩石风化（Beerling 等，2020）。然而，微生物对自然环境中硅酸盐风化的贡献仍然不确定（Frings 和 Buss，2019 年）。微生物的生存归功于它们清除溶解度和/或浓度低的元素或用作酶辅助因子的微量金属的能力，其中矿物质可能是唯一的来源（Banfield 等，1999）。呼应 Hazen 等人提出的范式。(2008)，地球和生物圈的共同进化可能有利于微生物群落特别适应每个矿物表面，可能含有具有有效风化能力的微生物（Uroz 等，2015）。微环境产生于硅酸盐-微生物界面（Benzerara 等人，2005 年），其中局部侵蚀性条件可以显着增加硅酸盐风化率（Bonneville 等人，2009 年；Li 等人，2016 年），正如许多涉及微生物培养的实验室实验所报道的那样（Uroz 等，2015）。然而，将实验室结果定量升级到自然环境并不是一件容易的事。一方面，实验室实验并非旨在完全代表自然环境。这些实验通常使用合成介质，其有意刺激微生物生长和/或生物风化，并导致比现场条件下更高的微生物介导的矿物溶解速率。此外，普遍使用无菌菌株无法解释微生物群落中不同种群之间的相互作用及其对矿物溶解速率的影响。另一方面，在该领域探索微生物风化具有挑战性。促进硅酸盐溶解的生物分子在土壤溶液中的浓度，例如有机酸 (OAs)，通常被认为在自然环境中浓度太低，无法在微生物-矿物质接触后增加溶解速率 (Drever and Stillings, 1997)。虽然迄今为止对微生物介导的硅酸盐风化率的大多数估计都来自实验室实验（Wild 等人，2018 年），但一些开创性研究提供了对地表含水层中自然改变的矿物（Rogers 和 Bennett，2004 年）或土壤中的环境估计值配置文件（例如，van Schöll 等人，2008 年，以及其中的参考文献）基于扫描电子显微镜 (SEM) 分析。然而，目前的方法不适合量化由微生物（例如真菌）溶解的实际矿物质体积，并且无法同时测量无真菌对原位整体溶解速率的贡献。其结果，生物风化的清晰印记通常仍然是微妙和有争议的（Knowles 等，2012），而预测矿物溶解和相关碳和营养预算的模型忽略了微生物参与者的贡献，这在本质上仍然是未知的。我们开发了一种直接量化原位的方法自然环境中的矿物风化率，提供了真菌对整体风化通量和相关真菌多样性的贡献的联合评估。我们的方法依赖于特征良好的矿物样品的原位孵化，通过确保具有代表性的生物地球化学环境同时提供定量速率估计来规避上述限制。它结合了对风化导致的矿物表面纳米级地形的解释（Kirtzel 等人，2017 年；Fischer 和 Luttge，2018）使用基于 DNA 的高通量测序分析相关微生物分类群（Jones 和 Bennett，2014）。橄榄石样品在缺镁森林土壤的 A 层中培养 9 个月，以探测其风化潜力。最近，在贫瘠土壤中培育玄武岩矿物被认为是一种有前景的策略，可以刺激增强岩石风化以去除二氧化碳（Beerling 等，2020）。然而，生物和非生物对整体风化率的贡献尚未在自然环境中通过实验来区分，部分原因是获得当今地球上不存在的非生物参考点的复杂性（Frings 和 Buss，2019）。光学显微镜图像与垂直扫描干涉测量 (VSI) 地形数据的互相关提供了矿物溶解速率的第一个原位量化以及真菌对整体风化速率的贡献的估计。这些结果与真菌多样性数据相结合，以确定与生物风化相关的潜在真菌类群。总而言之，这种方法提供了一个长期追捧的框架，用于在结合微生物驱动的风化作用的同时对定量反应模型进行基准测试。橄榄石样品制备为粉碎粉末（160-315 μm）和抛光整料（一边约 5 mm），装入尼龙袋，乙醇消毒。将尼龙袋埋入 A 层中缺镁森林土壤（山毛榉地块）的 A 层中，该层位于法国 Aubure Strengbach 集水区（48°12′41.04″N, 7 °11′45.66″E)（Pierret 等人，2018 年）。本研究选择的地块是 Observatoire Hydro-Géochimique de l'Environnement (OHGE) 临界区天文台仪器站点的一部分，这使我们能够检索样品孵化期间现场监测的环境参数。橄榄石是特意选择的，因为它最近被提议作为一种添加剂，以促进缺镁土壤中的风化作用。土壤溶液的平均 pH 值为 4.2 ± 0.2，最常见的低分子量 OA（醋酸盐、甲酸盐、丙二酸盐、草酸盐、通过离子色谱法 (ICS 3000 DIONEX) 测量的柠檬酸盐) 低于检测限 (<5 mmol/L)。土壤温度在 25 °C 和 -9 °C 之间变化，在孵化期间平均降水量为 125 毫米/月。使用反射光显微镜和 SEM (Tescan® VEGA II) 观察整体样品。然后使用棉签、乙醇和丙酮以机械和化学方式去除粘附在表面上的材料。使用 VSI (Zygo NewView 7300) 测量被室温硫化 (RTV) 胶点掩盖的橄榄石表面的风化和未风化区域之间纳米形貌的差异，如 Fischer 和 Luttge (2018) 所述从中提取速率图. 随后将速率数据从空间域转换为频域用于生成速率谱（Fischer 和 Luttge，2018），从中确定速率贡献者。 9 个月后，使用 PowerSoil® DNA 分离试剂盒提取总 DNA（ MO BIO，卡尔斯巴德，加利福尼亚州，美国）来自橄榄石粉末样品和周围土壤。使用 Qubit 2.0 分光荧光计（Life Technologies，Grand Island，New York，USA）对 DNA 进行定量。通过靶向 18S 核糖体核糖核酸 (rRNA) 基因的内部转录间隔区 2 (ITS2) 区域来评估每个样品的真菌多样性，使用标准化的 18S 扩增子文库方案进行扩增，如之前由 Al-Bulushi 等人所述。(2017)。基因序列由 Geno-screen Laboratory (Lille, France）使用标准分析管道（Al-Bulushi 等人，2017 年）。处理和分类后获得的测序数据用于检查真菌群落组成。根据与橄榄石样品（nolivine）相关的真菌属的相对丰度与土壤中真菌属的相对丰度（nsoil）的比值估计属水平的真菌富集。DNA序列存放在国家中心用于生物技术信息 (NCBI) BioProject 数据库，可通过 NCBI 网站 (https://www.ncbi.nlm.nih.gov/bioproject/638437) 免费访问。光学显微镜和 SEM 分析显示橄榄石样品上有丰富的细丝（图. 1A)，典型的真菌菌丝定植（例如，van Schöll 等，2008）。SEM 和 VSI 分析表明，去除后位于菌丝下方的凹陷，如图 1B 和 2A（绿色箭头）所示。这些特征在最初的矿物中是不存在的，并且与橄榄石非生物风化典型的晶体学控制的蚀刻坑（图 1B，黑色箭头）形成对比（Velbel，2009）。因此，它们被解释为局部生物风化的结果。表面形貌的 VSI 测量表明，真菌相关凹陷的平均深度为 235 ± 125 nm；转换为局部溶解速率后，这相当于每秒每平方米 2.2 ± 1.2 × 10−10 摩尔橄榄石 (mol/m2/s)。该值不考虑固态浸出通过无定形富含二氧化硅的层的潜在贡献，例如，Bonneville 等人的黑云母-真菌相互作用。(2011)。可以说，这种无定形层在环境温度下风化的橄榄石上非常薄（≤5 nm）（Hellmann 等人，2012 年），甚至可能在真菌-橄榄石界面处不存在（Gerrits 等人，2021 年）。因此，这种贡献可以忽略不计。 相反，整个样品的表面后退平均值为 23 ± 2 nm（溶解速率为 2.2 ± 0.2 × 10−11 mol/m2/s），反映了相互作用导致的橄榄石风化土壤溶液和橄榄石之间，没有直接的真菌贡献。总之，真菌菌丝下溶解增强的程度（~10 倍因子）与 Bonneville 等人的估计非常相似。(2011) 来自黑云母的实验室实验。速率光谱分析（图。2B) 有助于区分生物和非生物对整体溶解速率的贡献。可以从参考表面（图 2B 中的黄色）区分出两个峰簇。它们对应于受流体-矿物相互作用影响的表面无真菌部分的速率贡献（图 2B 中的蓝色），以及与真菌相关的风化作用（图 2B 中的绿色）。后一个集群表现出更快的平均速率和较小的积分（由于较小的表面积），并且包括几个可能与真菌风化空间范围演变有关的速率贡献者。有趣的是，整体溶解速率低于基于环境参数（流体成分、土壤温度）在样品孵育期间在该位置记录的 RTM 估计的速率（约 10-20 倍，取决于所选模型；有关这种差异的更多讨论，请参阅 Wild 等人。[2019]）。这些模拟基于最先进的动力学参数，不包括任何生物风化成分。这强调了观察结果，即在没有菌丝的区域微生物风化是微不足道的，否则与非生物估计值相比，这往往会增加速率。 根据一部分估计，真菌介导的通量在 9 个月内占溶解通量的 16%被真菌定殖的橄榄石表面积。该估计值属于先前使用间接方法报告的值范围（0.5%–50%；参见 van Schöll 等人，2008 年）。它可能代表一个下限，因为橄榄石的真菌定植可能没有达到稳定状态。我们的结果表明，真菌对溶解过程的可能贡献在空间上仅限于与矿物表面接触的菌丝附近，这与先前研究中强调的微生物风化过程中表面附着的重要性一致（Bonneville 等，2011； Ahmed 和 Holmstrom，2015 年；Gerrits 等人，2021 年）。展望未来，与微生物矿物表面覆盖率等相关的空间异质性评估及其时间演变将构成“微生物知情”RTM 的制定、参数化和验证的关键步骤（Meile 和 Scheibe，2019 年） . 这可以通过将表面成像与表面形貌分析相结合的方法（例如本研究中开发的）扩展到包括时间序列在内的更大样本集来实现。此外，局部硅酸盐风化的程度与潜在的真菌行为者有关。将反应速率、微生物群落组成以及最终的功能特征相关联是进一步开发明确代表微生物的 RTM 的另一个先决条件（Meile 和 Scheibe，2019）。与橄榄石样品相关的真菌多样性与大块土壤不同，与周围土壤相比，在有限数量的属中进行了特定的富集（图 3）。这与之前的研究相呼应，表明单一矿物质代表细菌（Mitchell 等人，2013 年；Jones 和 Bennett，2014 年；Uroz 等人，2015 年）和真菌（Gleeson 等人，2005 年）的特定生态位。最有可能与光学显微镜观察到的菌丝相对应的主要真菌属是 Hydnotrya (14.3%)、Mortierella (12.0%)、和轮枝菌 (4.4%)（图 1A）。特别是，橄榄石表面最丰富的属的一些成员，即轮枝菌（参见图 3），能够合成 OA 和铁载体，并且可以风化镁硅酸盐（Daghino 等，2009）。趋化性可能是促进橄榄石定植和随后被真菌菌丝溶解的主要机制，因为橄榄石样品是在缺镁的土壤隔间中培养的（Wild 等，2019）。属于轮枝菌属的物种（图 3）可能因此与高溶解速率特征相关（图 2B），并且当用适当的硅酸盐基质刺激时，可能参与硅酸盐风化和 CO2 下降。生物风化机制的触发，即，据报道，另一种子囊菌属真菌（Aspergillus fumigatus；Xiao et al., 2012）在硅酸盐矿物存在下参与从二氧化碳产生碳酸根离子的基因上调。这项研究和其他研究（例如 Olsson-Francis 等人，2010 年；Kirtzel 等人，2017 年）进一步支持了微生物风化过程在确定关键区域碳和生物可利用养分的准确通量方面发挥作用的结论。总体而言，我们的研究表明，可以原位确定局部风化速率，同时确定参与微生物介导的溶解的参与者并量化它们对风化通量的影响。提议的方法可以扩展到探索几乎无限范围的自然环境以及敏感的工业环境中的生物风化潜力，为此，微生物对腐蚀和硅酸盐风化的贡献的知识不仅是基本的，而且是迫切需要的（Trias 等人，2017 年）。矿物探针的原位孵育提供了建立下一代 RTM 所需的参考动力学参数和微生物数据，这些 RTM 解释了微生物介导的矿物溶解。在 RTM 中逐步包含微生物动力学是模拟生物圈及其对风化层影响的重要里程碑（Goddéris 等，2019）。除了提供生物风化率的定量评估外，所提出的方法还非常适合识别材料表面的生物特征，这是确认生物对溶解和揭示潜在生物风化机制的贡献的先决条件。我们感谢 Strengbach 流域临界区天文台、OHGE（Observatoire Hydro-Géochimique de l'Environnement）和法国临界区天文台网络 (OZCAR)。我们感谢两位匿名审稿人和 Mats Åström，他们帮助改进了手稿。这项工作由授予 D. Daval 的 ANR-20-ERC8-0006-01_t erc mobidic 项目和授予 G 的 MicXtreme 项目 (LABEX ANR-11-LABX-0050_G-EAU-THERMIE-PROFONDE) 资助. 伊姆费尔德。