<p>Methane (CH<sub>4</sub>) is a powerful greenhouse gas and a central target for near-term climate mitigation. Despite its shorter atmospheric lifetime compared with carbon dioxide (CO<sub>2</sub>), CH<sub>4</sub> exerts a strong warming effect, contributing ~0.5°C of the observed 1.15°C global surface warming since preindustrial periods (IPCC <span>2023</span>). Consequently, rapid reductions in CH<sub>4</sub> emissions are widely recognized as one of the most effective ways to slow warming in the coming decades. This urgency is reflected in global initiatives like the Global Methane Pledge, which aims for substantial emission cuts by 2030. The atmospheric CH<sub>4</sub> budget is controlled by a balance between sources and sinks. While oxidation by hydroxyl radicals dominates global CH<sub>4</sub> removal, aerobic upland soils constitute the second-largest CH<sub>4</sub> sink, accounting for approximately 4% of global CH<sub>4</sub> uptake (Kirschke et al. <span>2013</span>). This sink is unique. Unlike atmospheric chemical sinks, soil CH<sub>4</sub> uptake is embedded within terrestrial ecosystems. This means it can, in principle, respond to land management and stewardship (Song et al. <span>2024</span>). For decades, upland soils have therefore been regarded as an important and manageable ally in mitigating climate change.</p><p>However, the upland soil methane sink is dynamic, especially in a rapidly changing climate. This is because methanotrophic microbes are highly sensitive to multiple factors: temperature, soil moisture, substrate availability, and land-use disturbance. Shifts in temperature and precipitation regimes, together with intensifying human land use, are altering the spatial and temporal patterns of CH<sub>4</sub> uptake in upland ecosystems (Guo et al. <span>2023</span>; Wang et al. <span>2025</span>). Yet the size and direction of these changes remain poorly understood. Observational soil–atmosphere CH<sub>4</sub> exchange remains spatially uneven, and existing models differ substantially in their capacity to represent the nonlinear and interacting controls on CH<sub>4</sub> fluxes.</p><p>To address these knowledge gaps, Li et al. (<span>2025</span>) make a major step forward. It provides the first observation-driven, three-decade (1993–2022) assessment of the changing role and spatiotemporal dynamics of global upland soils as CH<sub>4</sub> sinks and sources. Their study is built on an extensive compilation of in situ CH<sub>4</sub> flux measurements from upland ecosystems worldwide, including croplands, forests, grasslands and tundra. This dataset constitutes the most systematic and comprehensive collection of upland soil CH<sub>4</sub> observations currently available. Based on this rich data foundation, Li et al. (<span>2025</span>) upscaled site-level measurements to global gridded estimates with advanced machine-learning approaches, most notably the XGBoost algorithm. By integrating climatic variables, soil properties
甲烷(CH4)是一种强大的温室气体,也是近期减缓气候变化的中心目标。尽管CH4的大气寿命比二氧化碳(CO2)短,但其增温效应很强,自工业化前以来观测到的1.15°C全球地表增温中,CH4贡献了约0.5°C (IPCC 2023)。因此,迅速减少甲烷排放被广泛认为是未来几十年减缓变暖的最有效方法之一。这种紧迫性反映在全球倡议中,如旨在到2030年大幅减排的全球甲烷承诺。大气CH4收支由源和汇之间的平衡控制。虽然羟基自由基氧化在全球CH4去除中占主导地位,但好氧山地土壤是第二大CH4汇,约占全球CH4吸收量的4% (Kirschke et al. 2013)。这个水槽是独一无二的。与大气化学汇不同,土壤CH4吸收嵌入陆地生态系统中。这意味着它原则上可以响应土地管理和管理(Song et al. 2024)。因此,几十年来,旱地土壤一直被视为减缓气候变化的重要和可管理的盟友。然而,旱地土壤甲烷汇是动态的,特别是在快速变化的气候条件下。这是因为甲烷营养微生物对多种因素高度敏感:温度、土壤湿度、基质有效性和土地利用干扰。温度和降水的变化以及人类土地利用的加剧正在改变高原生态系统中CH4吸收的时空格局(Guo et al. 2023; Wang et al. 2025)。然而,人们对这些变化的规模和方向仍然知之甚少。观测到的土壤-大气CH4交换在空间上仍然是不均匀的,现有模型在表征CH4通量的非线性和相互作用控制方面存在很大差异。为了解决这些知识差距,Li等人(2025)向前迈出了一大步。它提供了第一个观测驱动的三十年(1993-2022)全球高地土壤作为CH4汇和源的变化作用和时空动态评估。他们的研究是建立在对全球高地生态系统(包括农田、森林、草原和冻土带)的原位甲烷通量测量的广泛汇编之上的。该数据集构成了目前可用的最系统和最全面的陆地土壤CH4观测数据集。基于这一丰富的数据基础,Li等人(2025)使用先进的机器学习方法(最著名的是XGBoost算法)将站点级测量升级为全球网格化估计。通过整合气候变量、土壤特性和地理信息,他们的框架生成了跨空间和时间的CH4通量的高分辨率地图。重要的是,作者并没有仅仅依赖于预测性能。他们将机器学习与结构因果建模和可解释性工具相结合,以识别主要的环境驱动因素,并超越简单的相关性,走向因果理解。核心发现是明确的:在过去的30年里,全球陆地土壤对大气中甲烷的吸收能力大幅下降。草地和农田土壤在历史上作为净CH4汇的功能明显减弱。在许多地区,它们已转变为CH4净源。森林土壤也经历了甲烷吸收能力的显著降低,而长期以来被认为是甲烷来源的冻土带高地则表现出更复杂但仍然是相应的变化。至关重要的是,Li等人(2025)证明了这些趋势不是局部异常,而是代表了广泛和全球尺度的变化。气候变量,特别是降水和温度的变化,在很大程度上解释了观测到的时空变异,强调了高原CH4通量对持续气候变化的敏感性。Li等人工作的意义不仅在于记录变化,而且在于从根本上修正陆地土壤在全球CH4收支中的表现。许多先前的评估隐含地认为,随着时间的推移,陆地土壤CH4的吸收相对稳定(Kammann等人,2009;Murguia-Flores等人,2018)。相反,Li等人表明,这个汇是动态的、脆弱的,并且在当代环境压力下已经受到侵蚀。从更广泛的角度来看,这些发现有着严重的影响。观测到的陆地土壤CH4吸收量下降(在某些地区甚至出现逆转)表明陆地生态系统的自然缓冲能力正在逐渐丧失。这使得全球CH4预算对额外排放越来越敏感。随着韧性的降低,不确定性或延迟行动的空间就会减少。减少甲烷排放战略的容错空间越来越小,这加强了能源、农业和废物部门快速减排的紧迫性。 它还强调了保护并在可能的情况下增强土壤CH4汇容量的重要性,而不是假设陆地生态系统将在持续的全球变化下继续提供稳定的调节服务。虽然Li等人(2025)提供了一个强大而全面的分析,但它也强调了未来研究的重要局限性和方向。首先,像大多数大规模模拟工作一样,该模型预测了甲烷氧化和甲烷生成之间抵消的净甲烷通量。因此,它不能直接区分吸收功能减弱是由于氧化减少还是生产增强。尽管作者从现有的知识中得出了机械的推论,但数据本身并没有直接揭示这种关键的联系,这限制了基于过程的洞察力。其次,一些生态系统在全球数据集中的代表性仍然不足。例如,干旱和半干旱地区可能对全球CH4吸收做出不可忽视的贡献,但采样较少(Lee et al. 2023; Song et al. 2024; Wu et al. 2024)。同样,新出现的证据表明,树木木质组织对CH4的吸收可能是森林生态系统中一个额外的、以前被忽视的汇,特别是在热带地区(Gauci et al. 2024)。将这些过程纳入未来的研究可以进一步完善全球CH4预算估算。此外,生物和人为干扰对CH4排放的影响值得重视。最近的研究表明,放牧、啮齿动物活动和土地利用遗产可以强烈地改变土壤结构、水分和微生物群落,从而影响CH4通量(Gan et al. 2025)。干旱、洪水和热浪等极端事件也可能产生不成比例的影响,这些影响难以用长期平均值来衡量。未来的工作应该旨在明确地表示这些因素,并评估它们与气候变化的相互作用。最后,Li等人(2025)开发的框架为探索管理选项提供了一个有价值的平台。确定特定区域的战略来保护或加强陆地土壤CH4汇,无论是通过放牧管理、农田实践还是森林保护,都是具有明确政策相关性的重要下一步。总体而言,Li等人(2025)及时重新评估了全球CH4循环中一个关键但经常被忽视的组成部分。他们的研究结果表明,高地土壤正在失去作为大气CH4稳定汇的能力,这挑战了人们长期以来对其在气候调节中的作用的假设。通过将前所未有的综合观测结果与先进的分析方法相结合,该研究建立了评估陆地甲烷动态的新基准,并强调了作为未来气候减缓战略的一部分,保护并在可能的情况下恢复土壤甲烷汇功能的必要性。杨景瑞:写作——原稿。闫晓媛:写作-审稿和编辑。夏龙龙:构思、撰写-原稿、撰写-审稿、编辑。中国科学院战略重点研究项目(XDB0630302)、杰出青年基金(SBK2024010366)和江苏省科技厅碳峰值与碳中和科技专项基金(BM2022002)资助。作者声明无利益冲突。本文是Li等人的特邀评论,https://doi.org/10.1111/gcb.70248.Data分享不适用于本文,因为本文没有生成或分析数据集。
{"title":"Losing a Hidden Ally: The Shrinking Capacity of Upland Soils to Remove Atmospheric Methane","authors":"Jingrui Yang, Xiaoyuan Yan, Longlong Xia","doi":"10.1111/gcb.70741","DOIUrl":"10.1111/gcb.70741","url":null,"abstract":"<p>Methane (CH<sub>4</sub>) is a powerful greenhouse gas and a central target for near-term climate mitigation. Despite its shorter atmospheric lifetime compared with carbon dioxide (CO<sub>2</sub>), CH<sub>4</sub> exerts a strong warming effect, contributing ~0.5°C of the observed 1.15°C global surface warming since preindustrial periods (IPCC <span>2023</span>). Consequently, rapid reductions in CH<sub>4</sub> emissions are widely recognized as one of the most effective ways to slow warming in the coming decades. This urgency is reflected in global initiatives like the Global Methane Pledge, which aims for substantial emission cuts by 2030. The atmospheric CH<sub>4</sub> budget is controlled by a balance between sources and sinks. While oxidation by hydroxyl radicals dominates global CH<sub>4</sub> removal, aerobic upland soils constitute the second-largest CH<sub>4</sub> sink, accounting for approximately 4% of global CH<sub>4</sub> uptake (Kirschke et al. <span>2013</span>). This sink is unique. Unlike atmospheric chemical sinks, soil CH<sub>4</sub> uptake is embedded within terrestrial ecosystems. This means it can, in principle, respond to land management and stewardship (Song et al. <span>2024</span>). For decades, upland soils have therefore been regarded as an important and manageable ally in mitigating climate change.</p><p>However, the upland soil methane sink is dynamic, especially in a rapidly changing climate. This is because methanotrophic microbes are highly sensitive to multiple factors: temperature, soil moisture, substrate availability, and land-use disturbance. Shifts in temperature and precipitation regimes, together with intensifying human land use, are altering the spatial and temporal patterns of CH<sub>4</sub> uptake in upland ecosystems (Guo et al. <span>2023</span>; Wang et al. <span>2025</span>). Yet the size and direction of these changes remain poorly understood. Observational soil–atmosphere CH<sub>4</sub> exchange remains spatially uneven, and existing models differ substantially in their capacity to represent the nonlinear and interacting controls on CH<sub>4</sub> fluxes.</p><p>To address these knowledge gaps, Li et al. (<span>2025</span>) make a major step forward. It provides the first observation-driven, three-decade (1993–2022) assessment of the changing role and spatiotemporal dynamics of global upland soils as CH<sub>4</sub> sinks and sources. Their study is built on an extensive compilation of in situ CH<sub>4</sub> flux measurements from upland ecosystems worldwide, including croplands, forests, grasslands and tundra. This dataset constitutes the most systematic and comprehensive collection of upland soil CH<sub>4</sub> observations currently available. Based on this rich data foundation, Li et al. (<span>2025</span>) upscaled site-level measurements to global gridded estimates with advanced machine-learning approaches, most notably the XGBoost algorithm. By integrating climatic variables, soil properties","PeriodicalId":175,"journal":{"name":"Global Change Biology","volume":"32 2","pages":""},"PeriodicalIF":12.0,"publicationDate":"2026-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gcb.70741","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146099578","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
<p>The proportion of natural grasslands in Central European landscapes prior to the Neolithic period, which were maintained through grazing by large herbivores or frequent disturbances, remains a subject of debate (Svenning <span>2002</span>). However, most of the grasslands in the current landscape were created by deforestation following the Late Bronze Age (Hejcman et al. <span>2013</span>). Centuries of stable management involving low-intensity mowing or grazing without fertilisation have since created species-rich ecosystems that are considered semi-natural in Central Europe. Wilson et al. (<span>2012</span>) concluded that European temperate grasslands are the richest ecosystems in the world up to 50 m<sup>2</sup>, with a maximum of 43 vascular plant species on 0.1 m<sup>2</sup> (in Romania) and 116 species on 25 m<sup>2</sup> (in the Czech Republic).</p><p>As with many taxonomic groups, the species richness of vascular plants in Central European grasslands, when inventoried in plots, exhibits a hump-shaped pattern in relation to elevation (e.g., Descombes et al. <span>2017</span>). However, the reason for the lower species richness in lowland areas compared to mid-elevations remains unclear. Until now, the hypothesis that grassland diversity decreased in low-lying areas following agricultural intensification after the Second World War has largely been accepted (Descombes et al. <span>2017</span>), despite a lack of available historical data to verify it. This intensification became possible following the production of mineral fertilisers after 1950, which allowed for a higher mowing frequency. Indeed, it is common to apply over 100 kg of nitrogen per hectare per year to meadows, with over three annual cuts (Zechmeister et al. <span>2003</span>).</p><p>As Widmer et al. (<span>2025</span>) explained, there are numerous assessments of species richness evolution in temperate grasslands, with contrasting results. However, they are all based on quite recent baseline data, mostly from after 1970 that is, after the peak of agricultural intensification. Therefore, although a decrease in species richness at the plot level in these grasslands was strongly suspected, it has not yet been possible to quantify it.</p><p>In 2003, during a building renovation, some of the authors discovered boxes containing 580 exhaustive plant inventories of Swiss grasslands, recorded between 1884 and 1931 (Riedel et al. <span>2023</span>). This impressive dataset was completely forgotten. The 0.3 × 0.3-m plots were widely distributed across Switzerland, at elevations ranging from 212 to 2547 m.</p><p>Resurveying such small plots, with only rough location information (mostly the name of the village and the elevation), scattered in landscapes that have completely changed within a century, was challenging. The authors followed a convincing procedure to produce a comparable data set (Widmer et al. <span>2025</span>): definition of a potential area based on available data and
在新石器时代之前,中欧景观中通过大型食草动物的放牧或频繁的干扰来维持的天然草地的比例仍然是一个有争议的话题(Svenning 2002)。然而,目前景观中的大部分草原都是青铜器时代晚期森林砍伐造成的(Hejcman et al. 2013)。几个世纪以来的稳定管理,包括低强度的割草或不施肥的放牧,在中欧创造了物种丰富的生态系统,被认为是半自然的。Wilson et al.(2012)得出结论,欧洲温带草原是世界上最丰富的生态系统,面积达50 m2,在0.1 m2(罗马尼亚)上最多有43种维管植物,在25 m2(捷克共和国)上最多有116种。与许多分类类群一样,中欧草原维管植物的物种丰富度在样地调查时呈现出与海拔相关的驼峰状模式(例如,Descombes等人,2017)。然而,与中海拔地区相比,低地地区物种丰富度较低的原因尚不清楚。到目前为止,尽管缺乏可用的历史数据来验证,但第二次世界大战后农业集约化后低洼地区草地多样性下降的假设已基本被接受(Descombes et al. 2017)。随着1950年后矿物肥料的生产,这种强化成为可能,这使得更高的刈割频率成为可能。事实上,每年每公顷草地施用超过100公斤的氮肥是很常见的,每年减少三次以上(Zechmeister等人,2003年)。正如Widmer等人(2025)所解释的那样,对温带草原的物种丰富度进化进行了大量评估,结果却截然不同。然而,它们都是基于最近的基线数据,大多来自1970年之后,也就是农业集约化高峰之后。因此,虽然强烈怀疑这些草原在样地水平上的物种丰富度下降,但尚未可能量化。2003年,在一次建筑翻修期间,一些作者发现了装有580份详尽的瑞士草原植物清单的盒子,这些清单记录于1884年至1931年之间(Riedel et al. 2023)。这个令人印象深刻的数据集被完全遗忘了。这些0.3 × 0.3 m的地块广泛分布在瑞士各地,海拔从212到2547 m不等。这样的小地块,只有粗略的位置信息(主要是村庄的名称和海拔),分散在一个世纪内完全改变的景观中,重新勘测是具有挑战性的。作者遵循了一个令人信服的程序来产生一个可比较的数据集(Widmer et al. 2025):根据现有数据和地形图定义潜在区域;排除草原以外的地区;在每个潜力区随机选取3-5个地块;对田间选定的新地块进行重新调查。在277个潜力区共查获了1107个新样地,分布在322 ~ 2497 m.a.s.l之间。尽管历史和重新调查的样地并不完全在同一地点,但同一潜在区域内重新调查样地之间的平均布雷-柯蒂斯不相似性平均比历史和最近调查样地之间的布雷-柯蒂斯不相似性平均低0.13。这表明样地位置对物种组成的影响小于时间。研究了植物的α-、β-和γ-分类多样性(物种丰富度)、α-和β-系统发育多样性、α-和β-功能多样性(以株高、种子质量和比叶面积计算)以及功能性状和生态指标值的群落加权平均值的演变。熟悉低地生态系统与农业相关的历史演变的植物生态学家不会对这一结果感到惊讶。然而,它们为中欧草原在20世纪遭受的损失提供了强有力的证据。平均而言,调查的物种数量比历史调查的物种数量减少了26%,这种差异在低地地区尤为明显(在500米左右的地方减少了38%)。β-多样性在各海拔高度均呈下降趋势,γ-多样性在1000 m左右平均下降31%,接近50%。这种物种损失与综合功能α-多样性的普遍下降相对应,系统发育α-多样性下降了17%,其中forbs减少17%,Cyperaceae和Juncaceae减少42%,Poaceae增加47%(图1)。平均而言,调查中出现的物种对干扰的容忍度更高,竞争能力更强,但对压力的容忍度低于历史调查中的物种。群落生态指标值加权平均值也表明土壤较肥沃,耐刈割性较高。几乎所有这些差异都随着海拔的升高而减小。 气候变化导致各海拔高度温度生态指标值的群落加权平均值增加,但湿度水平保持不变。考虑到它包含的大量分析和长期的框架,这项研究可能是迄今为止发表的对欧洲草原多样性演变的最全面的评估之一。它提供了一个很好的了解瑞士草原在20世纪的演变,这可能与邻国相似。根据这些结果,Widmer等人(2025)首次在地块和景观水平上量化了农业集约化后草原物种丰富度的大幅下降。虽然低地的减少是可疑的,但所有海拔高度的影响程度都令人惊讶,特别是与海拔无关的植物比例的减少。这表明山地农业和亚高山夏季牧场并没有完全免受农业现代化的负面影响。然而,低地物种丰富度的更大减少现在清楚地解释了中欧草原物种丰富度与海拔的驼峰形曲线:低地比中海拔更贫瘠,因为它们失去了物种。Riedel等人(2023)在对历史数据集的初步介绍中已经证明,植物物种丰富度与海拔无关。最丰富的样地在0.09 m2中有47种,甚至超过了罗马尼亚的记录(0.1 m2中有43种;Wilson et al. 2012)。强化的后果不仅限于维管植物的多样性。我们所观察到的forbs的减少,大部分被禾科植物所取代,对应于花蜜产量的减少(见图1),以及专门昆虫饲料多样性的减少。这还不包括现代机械割草对无脊椎动物造成的直接破坏(Humbert et al. 2010)。这两个因素对草原周围的整个食物网都有影响。此外,系统发育多样性的减少可能会削弱草原的总体稳定性和恢复力。尽管农业对损失负有责任,但它不能被指责。第二次世界大战期间,大部分欧洲人营养不良。各国政府鼓励农民使用新的和充足的肥料来增加产量,以提高国家的自给自足程度。在接下来的几十年里,食品成本的下降,部分原因是来自进口农产品的竞争加剧,给农民带来了提高效率的巨大压力。因此,他们要么继续给草原施肥,要么放弃那些难以管理的草原(例如,那些朝南的陡峭地区),重新种植森林。物种丰富的草原,在干燥的,少营养的斜坡上,仍然存在于中欧。然而,尽管从未被施用过化肥,它们却比一个世纪前更加贫瘠(Riedel et al. 2023),而且它们大多被密集开发地区包围,变成了微小的孤立斑块(其历史范围的1%-5%;Lachat et al. 2011; Loos et al. 2021)。因此,残存的小种群受到低繁殖率和近亲繁殖衰退的威胁(Loos et al. 2021)。此外,剩余的物种丰富的草原受到氮沉积的威胁,在中欧,氮沉积大多超过了15公斤公顷−1年−1的临界负荷(Roth et al. 2013)。因此,监测草地,特别是营养贫乏地区,以评估农业集约化对所有营养水平的长期影响是至关重要的。监测方案的设计必须区分小种群近亲繁殖减少、氮沉积和气候变化各自的贡献。补充项目将加强我们对这些草原损失的动态和后果的理解。例如,Widmer等人(2025)比较了相隔一个多世纪的两个时期的物种丰富度。将这些结果与类似的短期研究结果结合起来,我们应该可以绘制出一条精确的曲线,显示物种是如何随时间退化的。与以往的研究(如Descombes et al. 2017)一样,Widmer et al.(2025)将γ-多样性计算为海拔带样地的总物种丰富度。由于样地较小,这可能低估了带内物种的真实丰富度。应该利用历史植物区系或植物标本标本等补充资料来评估γ-多样性在海拔梯度上是否具有类似的驼峰形状,并研究其在2
{"title":"When Clearing Out an Old House Advances Science: The Hump-Shaped Diversity Distribution in Central European Grasslands Better Explained","authors":"Pascal Vittoz","doi":"10.1111/gcb.70731","DOIUrl":"10.1111/gcb.70731","url":null,"abstract":"<p>The proportion of natural grasslands in Central European landscapes prior to the Neolithic period, which were maintained through grazing by large herbivores or frequent disturbances, remains a subject of debate (Svenning <span>2002</span>). However, most of the grasslands in the current landscape were created by deforestation following the Late Bronze Age (Hejcman et al. <span>2013</span>). Centuries of stable management involving low-intensity mowing or grazing without fertilisation have since created species-rich ecosystems that are considered semi-natural in Central Europe. Wilson et al. (<span>2012</span>) concluded that European temperate grasslands are the richest ecosystems in the world up to 50 m<sup>2</sup>, with a maximum of 43 vascular plant species on 0.1 m<sup>2</sup> (in Romania) and 116 species on 25 m<sup>2</sup> (in the Czech Republic).</p><p>As with many taxonomic groups, the species richness of vascular plants in Central European grasslands, when inventoried in plots, exhibits a hump-shaped pattern in relation to elevation (e.g., Descombes et al. <span>2017</span>). However, the reason for the lower species richness in lowland areas compared to mid-elevations remains unclear. Until now, the hypothesis that grassland diversity decreased in low-lying areas following agricultural intensification after the Second World War has largely been accepted (Descombes et al. <span>2017</span>), despite a lack of available historical data to verify it. This intensification became possible following the production of mineral fertilisers after 1950, which allowed for a higher mowing frequency. Indeed, it is common to apply over 100 kg of nitrogen per hectare per year to meadows, with over three annual cuts (Zechmeister et al. <span>2003</span>).</p><p>As Widmer et al. (<span>2025</span>) explained, there are numerous assessments of species richness evolution in temperate grasslands, with contrasting results. However, they are all based on quite recent baseline data, mostly from after 1970 that is, after the peak of agricultural intensification. Therefore, although a decrease in species richness at the plot level in these grasslands was strongly suspected, it has not yet been possible to quantify it.</p><p>In 2003, during a building renovation, some of the authors discovered boxes containing 580 exhaustive plant inventories of Swiss grasslands, recorded between 1884 and 1931 (Riedel et al. <span>2023</span>). This impressive dataset was completely forgotten. The 0.3 × 0.3-m plots were widely distributed across Switzerland, at elevations ranging from 212 to 2547 m.</p><p>Resurveying such small plots, with only rough location information (mostly the name of the village and the elevation), scattered in landscapes that have completely changed within a century, was challenging. The authors followed a convincing procedure to produce a comparable data set (Widmer et al. <span>2025</span>): definition of a potential area based on available data and ","PeriodicalId":175,"journal":{"name":"Global Change Biology","volume":"32 2","pages":""},"PeriodicalIF":12.0,"publicationDate":"2026-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12862448/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146099633","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
<p>Understanding why soil organic carbon (SOC) persists—or is lost—under global change ultimately depends on which biological processes constrain pathways of carbon stabilization. In this issue of <i>Global Change Biology</i>, Du et al. (<span>2025</span>) show that soil food webs, long treated as secondary to decomposition, play an active and context-dependent role in regulating microbial carbon cycling along successional gradients. Predicting SOC persistence has long been central to ecosystem–climate feedback research. Over the past decade, microbial residues have emerged as major precursors of long-lived SOC, particularly mineral-associated organic matter, as formalized in the Microbial Efficiency–Matrix Stabilization (MEMS) framework (Cotrufo et al. <span>2013</span>). Subsequent work has reinforced the importance of microbial anabolism and physicochemical protection in shaping SOC persistence (Liang et al. <span>2017</span>). However, most SOC theory remains largely microbe-centered. Soil fauna are typically subsumed within microbial biomass dynamics rather than treated as regulators in their own right. At the global scale, soil fauna—particularly nematodes—mediate substantial carbon fluxes through grazing and trophic interactions. This influence underscores their potential to shape soil carbon cycling in ways not captured by microbial-centric frameworks (van den Hoogen et al. <span>2019</span>; Neher <span>2010</span>).</p><p>It is against this background that Du et al. (<span>2025</span>) integrated replicated field sampling across two long-term successional chronosequences on the eastern Qinghai–Tibet Plateau. These included a glacier-retreat primary succession and a post-disturbance secondary succession, both examined via complementary molecular, biochemical and food-web approaches. Soils (0–10 cm) from six stages in each sequence (<i>n</i> = 60 composite samples) were analysed for SOC and microbial necromass using amino-sugar biomarkers. Nematode trophic structure was quantified using 18S rDNA metabarcoding, while microbial functional potential was assessed by shotgun metagenomics targeting growth pathways, carbon-degrading CAZymes and carbon-fixation genes. Finally, these data were integrated using partial least-squares path modelling (PLS-PM), redundancy analysis and mixed-effects models. This analytical framework explicitly partitioned trophic versus edaphic controls on microbial carbon processing. Rather than emphasizing variation in decomposition rates, their analysis shifts attention from carbon loss to carbon retention. In doing so, it brings food-web structure into closer alignment with microbial metabolic allocation and necromass formation.</p><p>A central outcome of Du et al. (<span>2025</span>) is that trophic regulation of microbial carbon metabolism depends strongly on successional stage and associated nutrient constraints. In primary successional soils, microbial growth is constrained. These soils are typically characteriz
理解土壤有机碳(SOC)为何在全球变化下持续存在或消失,最终取决于哪些生物过程限制了碳稳定的途径。在本期的《全球变化生物学》(Global Change Biology)中,Du等人(2025)表明,土壤食物网长期以来被视为分解的次级物,在调节微生物碳循环方面发挥了积极的、依赖于环境的作用。长期以来,预测有机碳持久性一直是生态系统-气候反馈研究的核心。在过去的十年中,微生物残留物已经成为长寿命有机碳的主要前体,特别是与矿物质相关的有机物,正如微生物效率-矩阵稳定(MEMS)框架(Cotrufo et al. 2013)所正式确定的那样。随后的工作加强了微生物合成代谢和物理化学保护在形成SOC持久性中的重要性(Liang et al. 2017)。然而,大多数有机碳理论仍然主要以微生物为中心。土壤动物通常被归入微生物生物量动力学中,而不是被视为其自身权利的调节者。在全球范围内,土壤动物,特别是线虫,通过放牧和营养相互作用介导大量的碳通量。这种影响强调了它们以微生物为中心的框架无法捕捉的方式塑造土壤碳循环的潜力(van den Hoogen et al. 2019; Neher 2010)。正是在这种背景下,Du等(2025)在青藏高原东部整合了两个长期连续时间序列的重复野外采样。其中包括冰川退缩的初级演替和扰动后的次级演替,两者都通过互补的分子、生化和食物网方法进行了研究。利用氨基糖生物标志物分析了每个序列中6个阶段(n = 60个复合样品)0-10 cm土壤的有机碳和微生物坏死块。利用18S rDNA元条形码对线虫的营养结构进行量化,同时利用针对生长途径、碳降解酶和碳固定基因的散弹枪元基因组学对微生物功能潜力进行评估。最后,利用偏最小二乘路径模型(PLS-PM)、冗余分析和混合效应模型对这些数据进行整合。该分析框架明确划分了微生物碳处理的营养控制与土壤控制。他们的分析不是强调分解速率的变化,而是将注意力从碳损失转移到碳保留上。在这样做的过程中,它使食物网结构与微生物代谢分配和坏死块形成更接近。Du等人(2025)的一个中心结论是,微生物碳代谢的营养调节在很大程度上取决于演代阶段和相关的营养约束。在原始演替土壤中,微生物的生长受到限制。这些土壤的典型特征是低有机投入、氮限制和弱成土发育,因此食物网结构的变化具有明显的后果。在整个主要时间序列中,SOC遵循s形轨迹(从演替早期的~12 g kg - 1到演替中期的~6 g kg - 1,然后在演替后期恢复到~16 g kg - 1)。同时,氨基糖浓度增加了4倍,从14.8 mg kg - 1增加到61.8 mg kg - 1,这一趋势与SOC密切相关(R2 = 0.56, p < 0.001)。同时,在早期阶段占主导地位的细菌和真菌线虫(占64%)逐渐被捕食者(占57%)所取代。这一转变与微生物生长基因(- 11.5%)和碳固定基因(- 13.5%)的下降同时发生,同时微生物坏死块积累显著增加。总之,这些模式表明,营养复杂性的增加使微生物碳流从快速矿化转向由周转驱动的残留物形成。这一模式与其他地方报道的食物网介导的微生物残留物形成途径一致(Kou et al. 2023)。次级演替系统则呈现出不同的景象。这些系统在有残留有机质和更高级的成土作用的土壤上发育,通常在磷而不是氮的限制下。因此,它们显示出土壤理化性质对微生物功能的更强基线控制。在后期部分恢复之前,SOC范围为~57 ~ ~34 g kg - 1。尽管氨基酸浓度与SOC之间保持着很强的关系,但在各个阶段氨基酸浓度相对稳定(R2 = 0.43, p < 0.001)。微生物生长基因下降14.0%,固碳基因下降9.2%。相比之下,杂食性线虫的变化(从~44%到~9%)与碳固定和CAZyme谱的变化关系更密切,而不是分解本身。因此,动物群效应持续存在,但主要通过调节合成代谢分配而不是通过直接抑制分解来表达。
{"title":"Soil Food Webs Regulate Carbon Persistence Across Succession","authors":"Wenjia Wu, Zhanfeng Liu","doi":"10.1111/gcb.70726","DOIUrl":"10.1111/gcb.70726","url":null,"abstract":"<p>Understanding why soil organic carbon (SOC) persists—or is lost—under global change ultimately depends on which biological processes constrain pathways of carbon stabilization. In this issue of <i>Global Change Biology</i>, Du et al. (<span>2025</span>) show that soil food webs, long treated as secondary to decomposition, play an active and context-dependent role in regulating microbial carbon cycling along successional gradients. Predicting SOC persistence has long been central to ecosystem–climate feedback research. Over the past decade, microbial residues have emerged as major precursors of long-lived SOC, particularly mineral-associated organic matter, as formalized in the Microbial Efficiency–Matrix Stabilization (MEMS) framework (Cotrufo et al. <span>2013</span>). Subsequent work has reinforced the importance of microbial anabolism and physicochemical protection in shaping SOC persistence (Liang et al. <span>2017</span>). However, most SOC theory remains largely microbe-centered. Soil fauna are typically subsumed within microbial biomass dynamics rather than treated as regulators in their own right. At the global scale, soil fauna—particularly nematodes—mediate substantial carbon fluxes through grazing and trophic interactions. This influence underscores their potential to shape soil carbon cycling in ways not captured by microbial-centric frameworks (van den Hoogen et al. <span>2019</span>; Neher <span>2010</span>).</p><p>It is against this background that Du et al. (<span>2025</span>) integrated replicated field sampling across two long-term successional chronosequences on the eastern Qinghai–Tibet Plateau. These included a glacier-retreat primary succession and a post-disturbance secondary succession, both examined via complementary molecular, biochemical and food-web approaches. Soils (0–10 cm) from six stages in each sequence (<i>n</i> = 60 composite samples) were analysed for SOC and microbial necromass using amino-sugar biomarkers. Nematode trophic structure was quantified using 18S rDNA metabarcoding, while microbial functional potential was assessed by shotgun metagenomics targeting growth pathways, carbon-degrading CAZymes and carbon-fixation genes. Finally, these data were integrated using partial least-squares path modelling (PLS-PM), redundancy analysis and mixed-effects models. This analytical framework explicitly partitioned trophic versus edaphic controls on microbial carbon processing. Rather than emphasizing variation in decomposition rates, their analysis shifts attention from carbon loss to carbon retention. In doing so, it brings food-web structure into closer alignment with microbial metabolic allocation and necromass formation.</p><p>A central outcome of Du et al. (<span>2025</span>) is that trophic regulation of microbial carbon metabolism depends strongly on successional stage and associated nutrient constraints. In primary successional soils, microbial growth is constrained. These soils are typically characteriz","PeriodicalId":175,"journal":{"name":"Global Change Biology","volume":"32 2","pages":""},"PeriodicalIF":12.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gcb.70726","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146099644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yue Wang, Yuhao Zhao, Morgan W. Tingley, Xingfeng Si
<p>Ecologists have recognized the “problem” of imperfect detection for decades, a pervasive phenomenon in which species frequently go undetected during field surveys, yet predominantly treated it as statistical noise or analytical bias to be corrected. Many methods have been developed to estimate detection probabilities, refine statistical frameworks, and compare modeling approaches (MacKenzie et al. <span>2017</span>). This method-centric perspective is valuable for enriching analytical frameworks, but it overlooks a more fundamental understanding: imperfect detection is not merely a statistical problem but an intrinsic phenomenon that shapes our interpretation of ecological patterns and processes. When ignored, it can distort species-environment relationships, misrepresent community dynamics, or lead to biased inferences about biodiversity change, particularly in ecosystems with numerous rare species or in those responding rapidly to global change. While much previous work has addressed <i>how</i> to correct for detection bias, less attention has been paid to <i>why</i> imperfect detection matters ecologically and <i>how</i> it can affect our conclusions. This conceptual gap has treated imperfect detection as a marginal technical problem, rather than recognizing it as a fundamental component of reliable ecological inference.</p><p>In this context, the study by Miller-ter Kuile et al. (<span>2025</span>) provides a critical advance. It shifts the perspective, framing imperfect detection not merely as a statistical problem to be corrected, but as an ecological variable that can directly alter the observed relationships between biodiversity and global change drivers. Using multi-species occupancy and abundance models to correct detection error for multiple taxa, they examined how ignoring imperfect detection changes the estimates of taxonomic and functional alpha and beta diversity and alters inferred responses to temperature and precipitation. These results demonstrate that ignoring imperfect detection can bias the inferred direction, magnitude, and timescale of the effects of global change drivers on biodiversity. This represents a conceptual shift from purely methodological correction toward a deeper ecological understanding of systems.</p><p>A main strength of the study is its strong empirical generality. By integrating data across multiple taxonomic groups (birds, grasshoppers, and even plants), data structures (occurrence and abundance), and biodiversity dimensions (taxonomic and functional alpha and beta diversity), Miller-ter Kuile et al. (<span>2025</span>) demonstrate that the ecological consequences of imperfect detection are consistent and pervasive. For example, accounting for imperfect detection in bird communities increased estimates of functional alpha diversity and revealed short-term precipitation effects and stronger seasonal temperature influences—patterns that were masked otherwise. In temporal monitoring of plant communities,
几十年来,生态学家已经认识到不完善检测的“问题”,这是一个普遍现象,在实地调查中,物种经常未被发现,但主要是将其视为需要纠正的统计噪声或分析偏差。已经开发了许多方法来估计检测概率、改进统计框架和比较建模方法(MacKenzie et al. 2017)。这种以方法为中心的观点对于丰富分析框架是有价值的,但它忽略了一个更基本的理解:不完美的检测不仅仅是一个统计问题,而且是一种内在现象,它塑造了我们对生态模式和过程的解释。如果被忽视,它可能扭曲物种与环境的关系,歪曲群落动态,或导致对生物多样性变化的偏见推断,特别是在拥有众多稀有物种的生态系统或对全球变化反应迅速的生态系统中。虽然以前的很多工作都解决了如何纠正检测偏差,但很少有人关注为什么不完美的检测在生态上很重要,以及它如何影响我们的结论。这种概念上的差距将不完美检测视为一个边缘技术问题,而不是将其视为可靠生态推断的基本组成部分。在此背景下,Miller-ter Kuile等人(2025)的研究提供了一个关键的进步。它改变了视角,将不完善的检测不仅作为一个需要纠正的统计问题,而且作为一个生态变量,可以直接改变观察到的生物多样性与全球变化驱动因素之间的关系。他们利用多物种占用和丰度模型来修正多分类群的检测误差,研究了忽略不完善的检测如何改变分类和功能α和β多样性的估计,以及改变对温度和降水的推断响应。这些结果表明,忽略不完善的检测会使推断出的全球变化驱动因素对生物多样性影响的方向、幅度和时间尺度产生偏差。这代表了一种概念上的转变,从纯粹的方法修正到对系统的更深层次的生态理解。这项研究的一个主要优点是它具有很强的经验普遍性。Miller-ter Kuile等人(2025)通过整合多个分类类群(鸟类、蚱蜢甚至植物)、数据结构(发生率和丰度)和生物多样性维度(分类和功能α和β多样性)的数据,证明了不完善检测的生态后果是一致的和普遍的。例如,考虑到鸟类群落中不完善的探测,增加了对功能性α多样性的估计,并揭示了短期降水效应和更强的季节性温度影响——这些模式被掩盖了。在植物群落的时间监测中,考虑物种可探测性揭示了更大的物种损失,并确定降水和蒸汽压赤字是关键驱动因素,具有强烈的季节信号和多季节“记忆”效应,这些效应以前未被发现。相反,考虑到蚱蜢群落的检测误差,减少了基于丰度的群落变化的估计,从而削弱了气候驱动因素和气候塑造群落动态的季节性途径的明显影响。综上所述,这些发现传达了一个明确的信息:不完善的检测问题可以从根本上改变对生物多样性如何响应全球变化驱动因素的生态学解释。Miller-ter Kuile等人(2025)的这项工作进一步强调了稀有物种在揭示气候变化下不完善检测的生态后果方面的重要性。稀有物种往往功能独特,对全球变化高度敏感,也是最常未被发现的物种。重要的是,即使在长期的、多季节的数据集中,不完美的探测仍然存在,并且可以显著地改变推断的气候响应。Miller-ter Kuile等人(2025)通过明确考虑鸟类、植物和昆虫中稀有物种的检测误差,证明忽略不完善的检测不仅会低估甚至有时会逆转温度和降水对群落动态的影响。稀有物种,虽然只占群落的一小部分,但作为一个特别说明的例子,说明检测错误如何不成比例地影响推断的气候响应、群落结构和生物多样性模式。这一见解对生态推理和应用保护科学都有直接的影响。虽然以前的研究已经认识到检测误差会影响生态推断,但大部分工作仅限于单一分类群或单一指标(Tingley和Beissinger 2013; Wang et al. 2025)。Miller-ter Kuile等人提供的广泛的跨系统合成。 (2025)超越了这些有价值但更有限的贡献。作者提供了明确的证据,不完善的检测是生态推断和结论的关键决定因素,而不是外围的方法论问题。这项研究的实际意义同样重要。结合检测误差可以通过优化重复调查的次数、采样时间和地点选择,直接改善长期监测方案,从而提高效率和代表性(ksamry and Royle 2008)。对于以机制为中心的生态学研究,它可以揭示物种对环境变化的真实反应,而不是被误导的信号所偏见的推断。在保护中,人们可以更可靠地评估保护区内的物种丰富度和种群趋势,为稀有或功能重要物种的优先级提供信息,并改进对恢复成功的评估,从而降低基于扭曲数据的决策风险(Bennett et al. 2024)。通过这种方式,Miller-ter Kuile等人(2025)将概念洞察力与生态应用联系起来,表明考虑不完美检测对于理解真实的生态动态和指导有效的生物多样性保护至关重要。尽管有其优势,该研究仍为未来的工作留下了很大的空间,特别是与方法进步的结合。目前的框架侧重于与环境变量的关系,并假设物种之间的相互作用是弱的或随机的。然而,物种之间的相互作用(例如竞争和捕食)可以改变物种的分布、活动周期或行为模式,所有这些都可能直接影响物种的可探测性。将物种相互作用纳入多物种模型——要么直接通过明确的相互作用条款(Rota等人,2016),要么间接通过共享的潜在结构或相关框架(Dorazio等人,2025)——可以更机械地理解全球变化下不完美检测与群落组装和时间动态之间的关系。此外,虽然作者通过使用beta回归的后续分析有效地证明了传播后验群落结构不确定性的重要性,但这里使用的方法可能会扩展到适用于不同随机多样性指数的其他分布(例如,物种丰富度的负二项分布或Shannon多样性的伽马分布)。当将校正后的生物多样性估计值与环境驱动因素联系起来时,这些扩展将增强推理的稳健性。然而,对鸟类、植物和蚱蜢群落提供的经验证据强调了检测偏差对测量生物多样性变化的广泛影响。未来的研究可以研究检测异质性的生态机制,包括物种特征,如体型、发声频率、生态位和/或系统发育影响(例如Si et al. 2018),从而将框架扩展到其他生物或非生物驱动因素。该框架是灵活的,也可以适应由环境DNA (eDNA)采样的新兴生态数据。未来的发展可以超越假阴性,也可以解释假阳性,这在自动传感器或公民科学的数据中很常见(Guillera-Arroita et al. 2017)。总的来说,这项工作擅长于展示一个明确的概念信息:不完美的检测应该被视为生态过程的固有组成部分,而不是作为“讨厌的”技术细节。Miller-ter Kuile等人(2025)通过展示多分类群、多度量、跨系统的证据,展示了在全球变化时代,检测偏差如何从根本上改变我们对群落动态和生物多样性变化的理解。因此,将缺陷检测整合到研究设计、生态机制推断和保护规划中,不仅是一个方法论问题,而且是一个基本的生态需求。这项研究强调了一个基本的观念转变:不完善的检测不仅仅是统计噪声——它是生态信号的一部分,对生态研究和保护实践都具有持久的价值。王岳:写作——原稿,构思。赵宇浩:写作——审编、构思。摩根·廷利:写作——评论和编辑,概念化。兴风司:构思、撰写、审编、监督。作者声明无利益冲突。本文是Miller-ter Kuile等人的特邀评论,https://doi.org/10.1111/gcb.70362.The支持本研究结果的数据可从通讯作者处索取。由于隐私或道德限制,这些数据不会公开。
{"title":"Reconceptualizing Imperfect Detection From Statistical Noise to a Lens for Ecological Signal","authors":"Yue Wang, Yuhao Zhao, Morgan W. Tingley, Xingfeng Si","doi":"10.1111/gcb.70732","DOIUrl":"10.1111/gcb.70732","url":null,"abstract":"<p>Ecologists have recognized the “problem” of imperfect detection for decades, a pervasive phenomenon in which species frequently go undetected during field surveys, yet predominantly treated it as statistical noise or analytical bias to be corrected. Many methods have been developed to estimate detection probabilities, refine statistical frameworks, and compare modeling approaches (MacKenzie et al. <span>2017</span>). This method-centric perspective is valuable for enriching analytical frameworks, but it overlooks a more fundamental understanding: imperfect detection is not merely a statistical problem but an intrinsic phenomenon that shapes our interpretation of ecological patterns and processes. When ignored, it can distort species-environment relationships, misrepresent community dynamics, or lead to biased inferences about biodiversity change, particularly in ecosystems with numerous rare species or in those responding rapidly to global change. While much previous work has addressed <i>how</i> to correct for detection bias, less attention has been paid to <i>why</i> imperfect detection matters ecologically and <i>how</i> it can affect our conclusions. This conceptual gap has treated imperfect detection as a marginal technical problem, rather than recognizing it as a fundamental component of reliable ecological inference.</p><p>In this context, the study by Miller-ter Kuile et al. (<span>2025</span>) provides a critical advance. It shifts the perspective, framing imperfect detection not merely as a statistical problem to be corrected, but as an ecological variable that can directly alter the observed relationships between biodiversity and global change drivers. Using multi-species occupancy and abundance models to correct detection error for multiple taxa, they examined how ignoring imperfect detection changes the estimates of taxonomic and functional alpha and beta diversity and alters inferred responses to temperature and precipitation. These results demonstrate that ignoring imperfect detection can bias the inferred direction, magnitude, and timescale of the effects of global change drivers on biodiversity. This represents a conceptual shift from purely methodological correction toward a deeper ecological understanding of systems.</p><p>A main strength of the study is its strong empirical generality. By integrating data across multiple taxonomic groups (birds, grasshoppers, and even plants), data structures (occurrence and abundance), and biodiversity dimensions (taxonomic and functional alpha and beta diversity), Miller-ter Kuile et al. (<span>2025</span>) demonstrate that the ecological consequences of imperfect detection are consistent and pervasive. For example, accounting for imperfect detection in bird communities increased estimates of functional alpha diversity and revealed short-term precipitation effects and stronger seasonal temperature influences—patterns that were masked otherwise. In temporal monitoring of plant communities,","PeriodicalId":175,"journal":{"name":"Global Change Biology","volume":"32 2","pages":""},"PeriodicalIF":12.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gcb.70732","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146099659","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}