Above-ground forest productivity can be reliably estimated from tree-ring width measurements. In doing so, annual growth is linked to the tree’s basal area increment (BAI), which is the change in cross-sectional area associated with each annual ring. When BAI is estimated from ring-width series, a value for the diameter of the tree is required. This diameter is ideally measured in the field, but can also be estimated as the sum of the annual ring widths. Tree biomass can also be estimated directly from the diameter estimates derived from tree-rings. Summing the ring widths, however, typically underestimates the tree’s true diameter. To evaluate this potential bias in diameter, we compared field-measured diameter and diameter estimated from the sum of the ring widths using tree-ring chronologies for seven common species in the eastern United States. We then evaluated the impacts of using the biased diameter estimates on derived BAI and biomass values. To simulate field-sampling error (i.e., failure to reach the pith when obtaining a core sample), we re-calculated BAI and biomass after removing a portion of the innermost rings from each tree. Comparisons of these various methods quantify the substantial and consistent underestimations in forest productivity estimates. To reduce the bias in diameter when using ring widths, we developed a regression model to adjust the diameter using core samples. This model is predicated on having some field-measured diameter values available at a site to calibrate and validate the model, but it can then be used to produce estimates at similar sites with similar species where no field-measured diameter values are available. Values of BAI and biomass derived from model-estimated diameter were more accurate at representing absolute growth than values produced by using the sum of the ring widths. Assessing the interannual variations in tree-growth is dependent on having metrics that accurately reflect the area and mass of wood produced. Our results suggest that published estimates of BAI and biomass using the sum of the ring widths to estimate diameter have substantially underestimated these productivity metrics. Our new procedure allows for more reliable estimates of productivity metrics that use diameter-at-breast height derived from tree rings.

可以从树轮宽度测量结果可靠地估算地上森林的生产力。在这种情况下，年生长量与树的基础面积增加量（BAI）相关，BAI是与每个年轮相关的横截面积的变化。从环宽序列估计BAI时，需要树的直径值。理想情况下，可以在现场测量该直径，但也可以将其估算为年轮宽度的总和。树木生物量也可以直接从树木年轮的直径估算中估算。但是，求和环的宽度通常会低估树的真实直径。为了评估这种潜在的直径偏差，我们比较了美国东部7种常见树种的实地测量直径和使用树年轮年表从年轮宽度总和估算出的直径。然后，我们评估了使用偏差直径估计值对得出的BAI和生物量值的影响。为了模拟野外采样误差（即，在获取岩心样品时未能达到髓），我们在从每棵树中去除了一部分最里面的环后重新计算了BAI和生物量。这些不同方法的比较量化了森林生产力估算中的实质性和一致的低估。为了减少使用环宽度时直径的偏差，我们开发了一个回归模型以使用岩心样品调整直径。该模型的基础是在站点上可以使用一些实地测量的直径值来校准和验证模型，但随后可以在没有可用实地测量的直径值的情况下，使用该模型在具有相似物种的相似站点上产生估计值。从模型估计的直径得出的BAI和生物量的值比通过使用环宽的总和产生的值更准确地表示绝对生长。评估树木生长的年际变化取决于是否具有能够准确反映出所生产木材的面积和质量的指标。我们的结果表明，已公开的BAI和生物量估计值（使用环宽度之和来估计直径）大大低估了这些生产率指标。我们的新程序可使用从年轮得出的胸径直径来更可靠地估算生产率指标。评估树木生长的年际变化取决于是否具有能够准确反映出所生产木材的面积和质量的指标。我们的结果表明，已公开的BAI和生物量估计值（使用环宽度之和来估计直径）大大低估了这些生产率指标。我们的新程序可使用从年轮得出的胸径直径来更可靠地估算生产率指标。评估树木生长的年际变化取决于是否具有能够准确反映出所生产木材的面积和质量的指标。我们的结果表明，已公开的BAI和生物量估计值（使用环宽度之和来估计直径）大大低估了这些生产率指标。我们的新程序可使用从年轮得出的胸径直径来更可靠地估算生产率指标。