Seeing Central African forests through their largest trees.
Seeing Central African forests through their largest trees.
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DOI：
10.1038/srep13156
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发表时间：
2015-08-17
影响因子：
4.6
通讯作者：
Bogaert J
中科院分区：
文献类型：
--
作者：
Bastin JF;Barbier N;Réjou-Méchain M;Fayolle A;Gourlet-Fleury S;Maniatis D;de Haulleville T;Baya F;Beeckman H;Beina D;Couteron P;Chuyong G;Dauby G;Doucet JL;Droissart V;Dufrêne M;Ewango C;Gillet JF;Gonmadje CH;Hart T;Kavali T;Kenfack D;Libalah M;Malhi Y;Makana JR;Pélissier R;Ploton P;Serckx A;Sonké B;Stevart T;Thomas DW;De Cannière C;Bogaert J
最近，大型热带树木和一些优势物种被确定为热带森林的主要结构要素。然而，这样的结果尚未转化为定量方法，而定量方法对于理解、预测和监测大片、往往交通不便的地区的森林功能和组成至关重要。在这里，我们表明，整个森林的地上生物量 (AGB) 可以通过几棵大树来预测，并且在跨越中部非洲 8 个地点调查的 175 个 1 公顷地块中，这种关系被证明非常稳定。我们设计了一个通用模型，当仅基于 5% 的茎时，预测 AGB 的误差为 14%，这表明森林结构特性的普遍性。我们首次在非洲发现了一些对森林 AGB 贡献不成比例的优势物种，其中 1.5% 的记录物种占 AGB 储量的 50% 以上。因此，关注大树和优势物种可以提供整个林分的精确信息。这为理解热带森林的功能提供了新的视角，并为制定创新监测策略打开了新的大门。
Large tropical trees and a few dominant species were recently identified as the main structuring elements of tropical forests. However, such result did not translate yet into quantitative approaches which are essential to understand, predict and monitor forest functions and composition over large, often poorly accessible territories. Here we show that the above-ground biomass (AGB) of the whole forest can be predicted from a few large trees and that the relationship is proved strikingly stable in 175 1-ha plots investigated across 8 sites spanning Central Africa. We designed a generic model predicting AGB with an error of 14% when based on only 5% of the stems, which points to universality in forest structural properties. For the first time in Africa, we identified some dominant species that disproportionally contribute to forest AGB with 1.5% of recorded species accounting for over 50% of the stock of AGB. Consequently, focusing on large trees and dominant species provides precise information on the whole forest stand. This offers new perspectives for understanding the functioning of tropical forests and opens new doors for the development of innovative monitoring strategies.