Ectomycorrhizas and tipping points in forest ecosystems.

Ectomycorrhizas and tipping points in forest ecosystems.
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DOI:
10.1111/nph.17547
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发表时间:
2021-06
期刊:
The New phytologist
影响因子:
--
通讯作者:
L. Suz;M. Bidartondo;S. van der Linde;T. Kuyper
L. Suz;M. Bidartondo;S. van der Linde;T. Kuyper
中科院分区:
其他
文献类型:
--
作者:
L. Suz;M. Bidartondo;S. van der Linde;T. Kuyper

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森林的复原力受到人为环境影响的损害,这些影响将森林推向临界点,导致生态系统状态发生重大变化,这些变化可能难以逆转,难以预测和管理,并可能产生巨大的生态、经济和社会后果。关于临界点的文献增长迅速,但几乎完全基于水生和地上系统。到目前为止,几乎没有人努力将其与土壤系统联系起来,土壤系统的变化不那么明显,时间尺度可能不同,恢复可能更慢。预测地下生态系统状态的转变和恢复,以及它们对地上系统的影响,仍然是一个重大的科学、实践和政策挑战。最近观察到的欧洲森林地上树木状况的重大变化可能与地下外生菌根(EM)真菌的变化有因果关系。基于最近在数据收集和分析方面的突破,我们1)将临界点理论应用于森林,包括其地下成分,重点研究EM真菌;2)将EM真菌的环境阈值与森林树木的营养失衡联系起来;3)探索表型可塑性在EM真菌适应环境变化和从环境变化中恢复中的作用;4)提出主要的正反馈机制来理解、解决和预测森林生态系统的临界点。
The resilience of forests is compromised by human-induced environmental influences pushing them towards tipping points resulting in major shifts in ecosystem state that might be difficult to reverse, are difficult to predict and manage, and can have vast ecological, economic and social consequences. The literature on tipping points has grown rapidly, but almost exclusively based on aquatic and aboveground systems. So far little effort has been made to make links to soil systems, where change is not as drastically apparent, timescales may differ, and recovery may be slower. Predicting belowground ecosystem state transitions and recovery, and their impacts on aboveground systems, remains a major scientific, practical and policy challenge. Recently observed major changes in aboveground tree condition across European forests are likely causally-linked with ectomycorrhizal (EM) fungal changes belowground. Based on recent breakthroughs in data collection and analysis, we 1) apply tipping point theory to forests, including their belowground component, focusing on EM fungi, 2) link environmental thresholds for EM fungi with nutrient imbalances in forest trees, 3) explore the role of phenotypic plasticity in EM fungal adaptation to, and recovery from, environmental change, and 4) propose major positive feedback mechanisms to understand, address and predict forest ecosystem tipping points.