We extend the study of economically optimal carbon storage to a previously unexplored forest type, mixed-species size-structured stands. The ecological model applied in the study is a transition matrix model with growth functions for boreal Norway spruce (Picea abies (L.) Karst.), birch (Betula pendula Roth and B. pubescens Ehrh.), and other broadleaves. The other broadleaved trees are assumed to have no commercial value. We maximize the sum of timber revenues and the value of carbon storage by optimizing the timing and intensity of thinnings and the potentially infinite rotation age. The optimization problem is solved in its general dynamic form using gradient-based interior point methods and a genetic algorithm. We present results for a mixed stand of Norway spruce and birch, and a mixed stand of Norway spruce, birch, and other broadleaves, and compare these to a pure Norway spruce stand. We show that carbon pricing increases stand volume by postponing harvests and limiting them to larger trees, and changes the optimal species composition by increasing the share of Norway spruce relative to birch. Further, carbon pricing incentivizes maintaining other broadleaves in the stand despite their lack of commercial value, thus increasing tree species diversity. We find that sawlog and total yields increase with carbon price. We show that the higher the number of tree species in a stand, the lower the marginal cost of carbon storage.

我们将经济上最佳碳储量的研究扩展到以前未开发的森林类型，混合物种大小结构的林分。该研究中使用的生态模型是具有增长功能的北挪威云杉（Picea abies（L.）Karst。），桦木（Betula pendula Roth和B. pubescens）的过渡矩阵模型。等等）。假定其他阔叶树没有商业价值。通过优化间伐的时间和强度以及可能无限的轮伐年龄，我们可以最大化木材收入和碳储量的总和。使用基于梯度的内点方法和遗传算法以一般动态形式解决了优化问题。我们介绍了挪威云杉和桦树的混交林和挪威云杉，桦树和其他阔叶树的混交林的结果，并将这些结果与纯挪威云杉的林分进行了比较。我们表明，碳定价会通过推迟收获并将其限制在更大的树木上而增加林分数量，并通过增加挪威云杉相对于桦木的份额来改变最佳物种组成。更多，尽管缺乏商业价值，但碳定价激励了其他阔叶林在展位上的维护，从而增加了树种的多样性。我们发现锯木和总产量随着碳价的增加而增加。我们表明，林分中树木的数量越多，碳储存的边际成本越低。