美国新型异速生长模型在森林碳估算、建模与制图方面带来阶跃式变革
New allometric models for the USA create a step-change in forest carbon estimation, modeling, and mapping
AI总结：
针对美国FIA以NSVB取代CRM导致既有AGB模型与地图兼容性问题，研究用相同方法对比新旧参考数据制图，发现被动卫星影像可估算时点碳储量但难测成熟林生长，需更新方法与产品。
摘要：
美国国家森林资源清查（NFI）是全国森林地上生物量（AGB）和碳核算的基础。这些数据不仅能够在州和区域层面基于设计估算森林碳储量及储量变化，还可作为基于模型方法的输入，用于在更精细分辨率上表征森林碳储量及储量变化。尽管NFI的单木和样地数据在这些模型中常被视为真值，但实际上它们是基于统称为组分比率法（CRM）的区域物种组模型所得的估算值。2023年底，森林清查与分析（FIA）项目推出了新的国家尺度材积与生物量估算器（NSVB）系统，以在全国范围内取代CRM，并更精确、准确地表征森林AGB和碳。鉴于依赖FIA的基于模型的AGB研究十分普遍，人们担心相关方法从CRM向NSVB模型的可迁移性，以及现有CRM AGB产品（例如地图）与新的及即将推出的NSVB AGB产品之间的可比性。为着手解决这些问题，我们将此前发表的CRM AGB地图与采用相同方法、但使用NSVB AGB参考数据制作的新地图进行了比较。结果表明，依赖被动卫星影像（如Landsat）的模型能够对某一时点的NSVB AGB和碳储量提供可接受的估算，但无法准确量化成熟郁闭林分的生长。我们强调，现有基于FIA参考数据的估算、模型和地图已不再与NSVB兼容，并建议采用新方法以及更新模型和地图，以适应这一阶跃式变化。我们在建模和制图工作流程中采用NSVB的共同能力，将有助于提供尽可能准确的森林碳空间数据，从而更好地为地方管理和决策提供信息。
英文摘要：
The United States national forest inventory (NFI) serves as the foundation for forest aboveground biomass (AGB) and carbon accounting across the nation. These data enable design-based estimates of forest carbon stocks and stock-changes at state and regional levels, but also serve as inputs to model-based approaches for characterizing forest carbon stocks and stock-changes at finer resolutions. Although NFI tree and plot-level data are often treated as truth in these models, they are in fact estimates based on regional species-group models known collectively as the Component Ratio Method (CRM). In late 2023 the Forest Inventory and Analysis (FIA) program introduced a new National Scale Volume and Biomass Estimators (NSVB) system to replace CRM nationwide and offer more precise and accurate representations of forest AGB and carbon. Given the prevalence of model-based AGB studies relying on FIA, there is concern about the transferability of methods from CRM to NSVB models, as well as the comparability of existing CRM AGB products (e.g. maps) to new and forthcoming NSVB AGB products. To begin addressing these concerns we compared previously published CRM AGB maps to new maps produced using identical methods with NSVB AGB reference data. Our results suggest that models relying on passive satellite imagery (e.g. Landsat) provide acceptable estimates of point-in-time NSVB AGB and carbon stocks, but fail to accurately quantify growth in mature closed-canopy forests. We highlight that existing estimates, models, and maps based on FIA reference data are no longer compatible with NSVB, and recommend new methods as well as updated models and maps for accommodating this step-change. Our collective ability to adopt NSVB in our modeling and mapping workflows will help us provide the most accurate spatial forest carbon data possible in order to better inform local management and decision making.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
