预测抵抗和恢复的时间稳定性和弹性
预测抵抗和恢复的时间稳定性和弹性
作者： 小柯机器人 发布时间：2026/5/7 17:14:14
本期文章：《自然》：Online/在线发表
美国威斯康星大学麦迪逊分校Chad R. Zirbel团队在研究中取得进展。他们揭示了预测抵抗和恢复的时间稳定性和弹性。这一研究成果发表在2026年5月6日出版的国际学术期刊《自然》上。
在这里，该课题组人员开发和测试了时间稳定性和弹性如何取决于它们的抵抗力和恢复成分的新预测。课题组人员发现，即使没有关于系统恢复速度的信息，也可以通过阻力来预测时间稳定性。相比之下，正如早期的理论所述，预测弹性对恢复的依赖程度至少与对抵抗力的依赖程度一样大。利用世界上运行时间最长的生物多样性实验的植物生产力数据，研究团队发现，在生态系统或物种水平上量化超过四分之一世纪的长期时间稳定性，仅从单年的抗性估计中预测出中等的准确性，同时考虑到恢复，只有轻微的改进。在生态系统水平上，通过结合抵抗和恢复来预测恢复力具有中等的准确性。研究组还发现，通过监测干旱前的时间稳定性可以预测生态系统的抗旱性。他们的研究结果表明，长期的时间稳定性和短期的抗性通常可以相互预测，并阐明了如何利用抗性和恢复来增强自然和管理系统的稳定性。
研究人员表示，对于许多自然和社会系统来说，稳定是可取的。时间稳定性，即系统随时间的不变性，可以通过在扰动期间抵抗位移，加速扰动后的恢复，或同时进行来增强。同样，弹性（在扰动后感觉接近于未扰动的水平）也具有承受（阻力）和扰动后恢复的组成部分。
附：英文原文
Title: Predicting temporal stability and resilience from resistance and recovery
Author: Isbell, Forest, Mori, Akira S., Loreau, Michel, Reich, Peter B., Tilman, David, Anderson, Maggie I., Brophy, Caroline, Castillioni, Karen, Chen, Qingqing, Churchill, Amber C., Clark, Adam T., Craven, Dylan, Eisenhauer, Nico, Farah, Hanan C., Gherardi, Lau A., Hautier, Yann, He, Miao, He, Jin-Sheng, Hector, Andy, Hedberg, Sydney, Hobbie, Sarah E., Hong, Pubin, Liang, Guopeng, Liang, Maowei, Luo, Shan, Mohanbabu, Neha, Naeem, Shahid, Niklaus, Pascal A., Pan, Xiaobin, Portales-Reyes, Cristy, Schmid, Bernhard, Shepherd, Harry E. R., Varghese, Steph, Veldhuis, Michiel P., Wang, Shaopeng, Watkins, Carmen R. E., Xu, Qianna, Zheng, Liting, Zirbel, Chad R.
Issue&Volume: 2026-05-06
Abstract: Stability can be desirable for many natural and social systems. Temporal stability, the invariability of a system over time, can be enhanced by resisting displacement during perturbations, accelerating recovery after them, or both1,2,3,4. Likewise, resilience (sensu proximity to unperturbed levels after a perturbation5,6,7,8,9,10) also has components of withstanding (resistance) and recovering after perturbations11,12. Here we develop and test new predictions for how temporal stability and resilience depend on their resistance and recovery components. We find that temporal stability could often be predicted from resistance, even without information about how quickly the system recovers. By contrast, resilience is predicted to depend at least as much on recovery as on resistance, as in earlier theory11,12. Using plant productivity data from the world’s longest-running biodiversity experiment, we find that long-term temporal stability, quantified over a quarter century at the ecosystem or species level, is predicted with moderate accuracy from single-year estimates of resistance alone, with only slight improvement by also considering recovery. Resilience was predicted with moderate accuracy by a combination of resistance and recovery at the ecosystem level. We also find that ecosystem drought resistance can be forecasted by monitoring temporal stability before the drought. Our results reveal that long-term temporal stability and short-term resistance may often be predicted from one another and clarify how resistance and recovery can be leveraged to enhance the stability of both natural and managed systems.
DOI: 10.1038/s41586-026-10498-4
Source: https://www.nature.com/articles/s41586-026-10498-4