Viewing organisms through the lens of their ecological strategies allows us to understand how they function within ecosystems and, thus, conceptualize their interactions with other organisms. Plant ecologists have pioneered this effort, cultivating a historic body of knowledge regarding trade-offs between plant traits across environmental gradients. For example, the leaf economics spectrum defines leaf traits like mass per unit area and leaf tissue nitrogen as indicative of plant investment strategy, varying across environmental conditions (Wright et al., 2004). Such frameworks allow us to predict how plant communities may shift as ecosystems change, for instance following intense environmental disturbance. Soil ecologists have more recently sought to develop similar frameworks, identifying traits like body length and mass as important indicators of ecological trade-offs in nematodes (Zhang et al., 2024a). Still, an integrative understanding of cross-kingdom ecological strategies (i.e. how the ecological strategies of plants and soil organisms interact) is a pressing need since a long-standing body of knowledge supports strong interactions between plant and soil organisms. Without abundant quantitative links between these dynamics and soil carbon cycling parameters, our understanding of how interactions between plants and soil organisms govern soil carbon storage remains limited. The recent publication by Zhang et al. (2024b) is a significant contribution to this knowledge gap because it integrates nematode and plant ecological spectra across a gradient of environmental conditions and links this to microbial carbon use efficiency to explain soil carbon storage.

Among the most compelling results presented by Zhang et al. (2024b) is that integrated plant and nematode ecological spectra explain more variation in soil carbon dynamics together, than either do alone. They further identify that the integrated ecological strategies of plants and nematodes indirectly moderate soil carbon by controlling microbial carbon use efficiency (the amount of carbon incorporated into biomass vs respired to the atmosphere), while also directly contributing to soil carbon through, for example, litterfall. Microbial carbon use efficiency has been experimentally linked to plant traits (e.g. litter chemistry; Ridgeway et al., 2022), and to the interaction between microbial and nematode community composition (Kane et al., 2022). However, because these dynamics are co-occurring in soil environments, influencing soil carbon storage interactively, linking them to overall soil carbon storage remains a complex feat. Observations like those presented by Zhang et al. (2024b) are exciting because they could potentially be integrated into models to represent the influence of interactions between plants and soil organisms. Such data could further improve model predictions that seek to include microbial controls on soil organic matter pools (e.g. Sulman et al., 2014; Wieder et al., 2015). This would be a clear step forward in expanding models to include the influence of soil fauna like nematodes, an area of need that has been conceptually identified (Grandy et al., 2016; Fry et al., 2019). Additionally, the trait-based perspective presented by Zhang et al. (2024b) could be leveraged to facilitate quantitative soil organic carbon (SOC) estimation across scales by utilizing global trait databases (Kattge et al., 2011). Future work that expands these efforts across biomes could further implement the integrated fast–slow plant and nematode economics spectrum, aiding in larger scale predictions of soil carbon storage.

The recent manuscript by Zhang et al. (2024b) aids in filling key knowledge gaps, all while bringing to light exciting areas of future research. While this work eloquently argues that nematode traits like body mass, length, and diameter are strongly associated with plant traits to explain carbon cycling, it is important to note that nematode trophic habits also play a critical role in explaining soil nutrient fluxes and carbon dynamics (Bååth et al., 1981; Kane et al., 2022). For example, nematode trophic groups can influence the sequestration or degradation of SOC by regulating the composition and functionality of mycorrhizal and saprotrophic communities in the rhizosphere (Jiang et al., 2020). Considering the feeding habits of soil animals in the context of soil carbon accumulation poses interesting questions about how trophic interactions in the rhizosphere affect the formation and persistence of labile (particulate organic matter) and stabilized (mineral-associated organic matter) SOC pools. Classifying nematodes and other soil animals according to their trophic habits in similar experimental designs to the recent work by Zhang et al. (2024b) may bring additional explanatory power to soil carbon dynamics, especially when considered alongside plant and microbial traits.

The recent work by Zhang et al. (2024b) presents a strong study focusing on the ecological strategies of plants and nematodes as they relate to the community-wide carbon cycling of the microbial community and, therefore, soil carbon pools. While their approach was effective in explaining soil carbon dynamics, categorizing this community by their ecological strategies could be of great use as well. Soil microbial communities contain diverse communities of fungi, bacteria, and archaea. One gram of soil is thought to contain thousands of bacterial taxa comprising billions of bacterial cells, only a small fraction of which have been cultivated and studied in the laboratory (Roesch et al., 2007). The microscopic nature of these organisms and their vast phylogenetic and metabolic diversity make measuring and conceptualizing their traits challenging. Several recent frameworks have sought to do this with the goal of feasibly and accurately incorporating microbial carbon cycling into ecosystem models. For example, Malik et al. (2020) classify microbial taxa based on trade-offs between growth yield, nutrient acquisition, and stress tolerance, and Morrissey et al. (2023) categorize taxa based on their carbon source (plant material, dead microbial biomass, dissolved organic carbon, or live microbial biomass). These conceptual frameworks could potentially integrate with those like Zhang et al. (2024b) present in their recent article, together strengthening predictions of global carbon cycling. Connecting the fast–slow plant and nematode trait spectrum with the yield-resource acquisition-stress tolerance (Y-A-S) framework presented in Malik et al. (2020) with the restoration chronosequence presented in Zhang et al.'s (2024b) experiment could aid in resolving a mechanistic understanding SOC dynamics. For example, at the pioneer stage, high-quality litter input could fuel decomposition primarily by fast-growing microbial saprotrophs with high-growth yield traits. This could potentially promote the dominance of r-strategist nematodes (bacterivores and fungivores), which could increase SOC mineralization as CO₂. By contrast, at the climax stage, complex low-quality litter input might favor oligotrophic microbial communities that invest more in resource acquisition traits, leading to the dominance of k-strategist nematodes (e.g. omnivores and predators). This may result in slower SOC mineralization and an increase in SOC stocks.

All told, the new publication by Zhang et al. (2024b) showcases an elegant example of a pressing experimental need in the field of global change ecology – that is, to quantitatively relate interactions between plants and soil organisms to soil carbon storage. In the future, expanding upon this to also integrate bacterial, fungal, and archaeal life strategies may even further advance our understanding of the global carbon cycle and allow for increased accuracy when predicting future environmental scenarios.

通过生物体的生态策略来观察生物体，可以让我们了解它们在生态系统中是如何运作的，从而概念化它们与其他生物体的相互作用。植物生态学家率先开展了这项工作，培养了关于跨环境梯度植物性状之间权衡的历史知识体系。例如，叶片经济学谱定义了每单位面积质量和叶片组织氮等叶片性状，以指示植物投资策略，随环境条件而变化（Wright et al.， 2004）。这样的框架使我们能够预测植物群落如何随着生态系统的变化而变化，例如在强烈的环境干扰之后。土壤生态学家最近试图开发类似的框架，将体长和质量等性状确定为线虫生态权衡的重要指标（Zhang et al.， 2024a）。尽管如此，对跨王国生态策略（即植物和土壤生物的生态策略如何相互作用）的综合理解仍然是一个紧迫的需求，因为长期的知识体系支持植物和土壤生物之间的强烈相互作用。如果这些动态与土壤碳循环参数之间没有丰富的定量联系，我们对植物和土壤生物之间的相互作用如何控制土壤碳储存的理解仍然有限。Zhang 等 人最近发表的文章。（2024b） 是对这一知识差距的重大贡献，因为它整合了线虫和植物生态光谱在环境条件梯度中的光谱，并将其与微生物碳利用效率联系起来，以解释土壤碳储存。

Zhang 等 人提出的最引人注目的结果之一。（2024b） 是综合植物和线虫生态光谱一起解释土壤碳动力学的变化，而不是单独解释。他们进一步确定，植物和线虫的综合生态策略通过控制微生物碳利用效率（生物质中掺入的碳量与呼吸到大气中的碳量）间接调节土壤碳，同时还通过凋落物等方式直接贡献土壤碳。微生物碳利用效率在实验上与植物性状（例如凋落物化学;Ridgeway等人 ，2022 年），以及微生物和线虫群落组成之间的相互作用（Kane等 人，2022 年）。然而，由于这些动态在土壤环境中同时发生，相互作用地影响土壤碳储存，因此将它们与整体土壤碳储存联系起来仍然是一项复杂的壮举。像 Zhang 等 人提供的观察结果。（2024b） 令人兴奋，因为它们有可能被整合到模型中，以表示植物和土壤生物之间相互作用的影响。这些数据可以进一步改进模型预测，这些模型预测旨在包括对土壤有机质库的微生物控制（例如 Sulman 等 人，2014 年;Wieder等 人，2015 年）。这将是扩展模型以包括线虫等土壤动物群的影响的明显一步，这是一个已经从概念上确定的需求领域（Grandy 等 人，2016 年;Fry等 人，2019 年）。 此外，Zhang 等 人提出的基于特征的观点。（2024b） 可以利用全球性状数据库来促进跨尺度的定量土壤有机碳 （SOC） 估计（Kattge et al.， 2011）。将这些工作扩展到生物群落的未来工作可以进一步实施综合的快慢植物和线虫经济学谱，有助于更大规模地预测土壤碳储存。

Zhang 等 人最近的手稿。（2024b） 有助于填补关键知识空白，同时揭示未来研究的令人兴奋的领域。虽然这项工作雄辩地论证了体重、长度和直径等线虫性状与植物性状密切相关，以解释碳循环，但重要的是要注意，线虫营养习性在解释土壤养分通量和碳动力学方面也起着关键作用（Bååth 等 人，1981 年;Kane等 人，2022 年）。例如，线虫营养群可以通过调节根际菌根和腐生群落的组成和功能来影响 SOC 的隔离或降解（江等 人，2020 年）。在土壤碳积累的背景下考虑土壤动物的摄食习惯，提出了关于根际营养相互作用如何影响不稳定（颗粒有机物）和稳定（矿物相关有机物）SOC 库的形成和持久性的有趣问题。根据线虫和其他土壤动物的营养习性对线虫和其他土壤动物进行分类，实验设计与 Zhang 等人 最近的工作类似。（2024b） 可能会为土壤碳动力学带来额外的解释力，尤其是与植物和微生物特性一起考虑时。

Zhang 等 人最近的工作。（2024b） 提出了一项强有力的研究，重点关注植物和线虫的生态策略，因为它们与微生物群落的群落范围碳循环有关，因此与土壤碳库有关。虽然他们的方法在解释土壤碳动力学方面很有效，但根据他们的生态策略对这个群落进行分类也可能非常有用。土壤微生物群落包含真菌、细菌和古细菌的不同群落。一克土壤被认为含有数千个细菌类群，包括数十亿个细菌细胞，其中只有一小部分是在实验室中培养和研究的（Roesch 等 人，2007 年）。这些生物体的微观性质及其巨大的系统发育和代谢多样性使得测量和概念化它们的特征具有挑战性。最近的几个框架试图做到这一点，目标是将微生物碳循环可行且准确地纳入生态系统模型。例如，Malik 等 人。（2020 年）根据生长产量、养分获取和抗逆性之间的权衡对微生物分类群进行分类，Morrissey 等 人。（2023） 根据碳源（植物材料、死亡微生物生物量、溶解有机碳或活微生物生物量）对分类群进行分类。这些概念框架可能会与 Zhang 等 人整合。（2024b） 发表在他们最近的文章中，共同加强对全球碳循环的预测。 将快-慢植物和线虫性状谱与 Malik 等 人提出的产量-资源获取-胁迫耐受性 （YAS） 框架联系起来。（2020 年）与 Zhang 等 人提出的恢复时间序列。s （2024b） 实验可能有助于解决对 SOC 动力学的机理理解。例如，在先锋阶段，高质量的凋落物输入主要可以通过具有高生长产量特性的快速生长的微生物腐生菌来促进分解。这可能会促进 r 策略线虫（噬菌动物和食真菌动物）的优势，这可能会增加 SOC 矿化为 CO₂。相比之下，在顶峰阶段，复杂的低质量凋落物输入可能有利于寡营养微生物群落，这些微生物群落在资源获取性状上投入更多，导致 k 战略线虫（例如杂食动物和捕食者）占据主导地位。这可能导致土壤有机碳矿化速度变慢，土壤有机碳储量增加。

总而言之，Zhang 等 人的新出版物。（2024b） 展示了全球变化生态学领域迫切实验需求的一个优雅例子——即定量地将植物和土壤生物之间的相互作用与土壤碳储存联系起来。未来，在此基础上进行扩展，整合细菌、真菌和古细菌生命策略，可能会进一步促进我们对全球碳循环的理解，并在预测未来环境情景时提高准确性。