German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Deutscher Platz 5e, 04103 Leipzig, Germany.
Department of Economics, University of Leipzig, Grimmaische Straße 12, 04109 Leipzig, Germany.
Science. 2020 Apr 10;368(6487):165-168. doi: 10.1126/science.aaz4797.
Understanding tropical forest dynamics and planning for their sustainable management require efficient, yet accurate, predictions of the joint dynamics of hundreds of tree species. With increasing information on tropical tree life histories, our predictive understanding is no longer limited by species data but by the ability of existing models to make use of it. Using a demographic forest model, we show that the basal area and compositional changes during forest succession in a neotropical forest can be accurately predicted by representing tropical tree diversity (hundreds of species) with only five functional groups spanning two essential trade-offs-the growth-survival and stature-recruitment trade-offs. This data-driven modeling framework substantially improves our ability to predict consequences of anthropogenic impacts on tropical forests.
了解热带森林动态并规划其可持续管理需要高效且准确地预测数百种树木物种的联合动态。随着有关热带树木生活史信息的增加，我们的预测能力不再受限于物种数据，而是受限于现有模型利用这些数据的能力。我们使用一个基于个体的森林模型表明，通过仅用五个功能组（涵盖两个基本权衡关系——生长-存活权衡和树高-繁殖权衡）来代表热带树木多样性（数百个物种），就可以准确预测新热带森林演替过程中的林分断面积和组成变化。这种基于数据的建模框架极大地提高了我们预测人为因素对热带森林影响的后果的能力。
