Models of forest growth and yield (G&Y) are a key component in long-term strategic forest management plans. Models leveraging the industry-standard “empirical” approach to G&Y are frequently underpinned by an assumption of historical consistency in climatic growing conditions. This assumption is problematic as forest managers look to obtain reliable growth predictions under the changing climate of the 21st century. Consequently, there is a pressing need for G&Y modelling approaches that can be more robustly applied under the influence of climate change. In this study we utilized an established forest gap model (JABOWA-3) to simulate G&Y between 2020 and 2100 under Representative Concentration Pathways (RCP) 2.6, 4.5, and 8.5 in the Canadian province of Newfoundland and Labrador (NL). Simulations were completed using the province’s permanent sample plot data and surface-fitted climatic datasets. Through model validation, we found simulated basal area (BA) aligned with observed BA for the major conifer species components of NL’s forests, including black spruce [Picea mariana (Mill.) Britton et al.] and balsam fir [Abies balsamea (L.) Mill]. Model validation was not as robust for the less abundant species components of NL (e.g., Acer rubrum L. 1753, Populus tremuloides Michx., and Picea glauca (Moench) Voss). Our simulations generally indicate that projected climatic changes may modestly increase black spruce and balsam fir productivity in the more northerly growing environments within NL. In contrast, we found productivity of these same species to only be maintained, and in some instances even decline, toward NL’s southerly extents. These generalizations are moderated by species, RCP, and geographic parameters. Growth modifiers were also prepared to render empirical G&Y projections more robust for use under periods of climate change.

中文翻译：

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加拿大东北北方森林在21世纪气候预测下针叶树生产力的混合区域变化

森林生长和产量（G＆Y）模型是长期森林战略管理计划的关键组成部分。利用行业标准的G＆Y“经验”方法进行建模的模型通常以气候增长条件下的历史一致性为基础。由于森林管理者希望在21世纪不断变化的气候下获得可靠的增长预测，因此这一假设存在问题。因此，迫切需要可以在气候变化的影响下更可靠地应用G＆Y建模方法。在这项研究中，我们利用建立的森林缺口模型（JABOWA-3）模拟了加拿大纽芬兰和拉布拉多省（NL）的2020年和2100年之间的G＆Y（典型代表浓度路径（RCP）2.6、4.5和8.5）。使用该省的永久性样地数据和表面拟合的气候数据集完成了模拟。通过模型验证，我们发现了NL森林的主要针叶树种成分（包括黑云杉[Picea mariana（密西根州）Britton等]和香脂冷杉[ Abies balsamea（L.）Mill]。模型验证对于NL数量较少的物种成分（例如Acer rubrum L. 1753，Populus tremuloides Michx。和Picea glauca）不那么健壮。（Moench）Voss）。我们的模拟通常表明，在NL地区向北生长的环境中，预计的气候变化可能会适度提高黑云杉和香脂的生产率。相比之下，我们发现这些相同物种的生产力只能维持到NL的南方范围，在某些情况下甚至会下降。这些概括受物种，RCP和地理参数的控制。还准备了增长修正剂，以使经验性G＆Y预测在气候变化时期更可靠。