Key message In this exploratory study, we show how combining the strength of tree diversity experiment with the long-term perspective offered by forest gap models allows testing the mixture yielding behavior across a full rotation period. Our results on a SW France example illustrate how mixing maritime pine with birch may produce an overyielding (i.e., a positive net biodiversity effect). Context Understanding the link between tree diversity and stand productivity is a key issue at a time when new forest management methods are investigated to improve carbon sequestration and climate change mitigation. Well-controlled tree diversity experiments have been set up over the last decades, but they are still too young to yield relevant results from a long-term perspective. Alternatively, forest gap models appear as appropriate tools to study the link between diversity and productivity as they can simulate mixed forest growth over an entire forestry cycle. Aims We aimed at testing whether a forest gap model could first reproduce the results from a tree diversity experiment, using its plantation design as input, and then predict the species mixing effect on productivity and biomass in the long term. Methods Here, we used data from different forest experimental networks to calibrate the gap model F or CEEPS for young pine ( Pinus pinaster ) and birch ( Betula pendula ) stands. Then, we used the refined model to compare the productivity of pure and mixed pine and birch stands over a 50-year cycle. The mixing effect was tested for two plantation designs, i.e., species substitution and species addition, and at two tree densities. Results Regarding the comparison with the experiment ORPHEE (thus on the short term), the model well reproduced the species interactions observed in the mixed stands. Simulations showed an overyielding (i.e., a positive net biodiversity effect) in pine-birch mixtures in all cases and during the full rotation period. A transgressive overyielding was detected in mixtures resulting from birch addition to pine stands at low density. These results were mainly due to a positive mixing effect on pine growth being larger than the negative effect on birch growth. Conclusion Although this study remains explorative, calibrating gap models with data from monospecific stands and validating with data from the manipulative tree diversity experiment (ORPHEE) offers a powerful tool for further investigation of the productivity of forest mixtures. Improving our understanding of how abiotic and biotic factors, including diversity, influence the functioning of forest ecosystems should help to reconsider new forest managements optimizing ecosystem services.

中文翻译：

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利用林隙模型和实验数据探索树木多样性对混交林生产力的长期影响

关键信息 在这项探索性研究中，我们展示了如何将树木多样性实验的强度与森林间隙模型提供的长期视角相结合，可以测试整个轮作周期内的混合物产量行为。我们在法国西南部的一个例子中的结果说明了海松与桦木的混合可能会产生过度的产量（即积极的净生物多样性效应）。背景 在研究新的森林管理方法以改善碳固存和减缓气候变化时，了解树木多样性与林分生产力之间的联系是一个关键问题。在过去的几十年里，已经建立了控制良好的树木多样性实验，但它们还太年轻，无法从长期的角度产生相关结果。或者，森林差距模型似乎是研究多样性和生产力之间联系的合适工具，因为它们可以模拟整个林业周期内的混合森林生长。目的 我们旨在测试森林间隙模型是否可以首先重现树木多样性实验的结果，使用其人工林设计作为输入，然后预测物种混合对生产力和生物量的长期影响。方法 在这里，我们使用来自不同森林实验网络的数据来校准幼松 (Pinus pinaster) 和桦木 (Betula pendula) 林分的间隙模型 F 或 CEEPS。然后，我们使用改进后的模型来比较 50 年周期内纯和混合松桦林的生产力。对两种种植园设计（即物种替代和物种添加）以及两种树木密度测试了混合效应。结果 关于与实验 ORPHEE 的比较（因此在短期内），该模型很好地再现了在混交林中观察到的物种相互作用。模拟显示在所有情况下和在整个轮作期间，松桦混合物的产量过高（即正的净生物多样性效应）。在将桦木以低密度添加到松林中所产生的混合物中检测到海侵超产。这些结果主要是由于对松树生长的积极混合效应大于对桦树生长的负面影响。结论 尽管这项研究仍然是探索性的，但使用来自单种林的数据校准间隙模型并使用来自操纵树木多样性实验 (ORPHEE) 的数据进行验证，为进一步研究森林混合物的生产力提供了一个强大的工具。