García-Ontiyuelo Mario, Acuña-Alonso Carolina, Valero Enrique, Álvarez Xana
University of Vigo, Agroforestry Group, School of Forestry Engineering, 36005, Pontevedra, Spain.
University of Vigo, Agroforestry Group, School of Forestry Engineering, 36005, Pontevedra, Spain; Centre for the Research and Technology of Agro-Environmental and Biological Sciences - CITAB, University of Trás-os-Montes and Alto Douro (UTAD), Ap. 1013, 5001-801 Vila Real, Portugal.
Sci Total Environ. 2024 Apr 20;922:171297. doi: 10.1016/j.scitotenv.2024.171297. Epub 2024 Feb 27.
CO emissions have increased exponentially in recent years, so measuring and quantifying carbon sequestration is a step towards sustainable forest management and combating climate change. The overall goal of this study is to develop an accurate model for estimating carbon storage and sequestration for forest areas of the Atlantic Biogeographic Region. Specifically, the modelling and field sampling are carried out in the municipality of Baiona (Galicia, NW Spain), which was selected as a representative biome of this region. The methodology consists of carrying out two object-based image analysis (OBIA) classifications in spring and autumn to observe possible stocks of seasonal differences. Two carbon storage and sequestration models are built up (model 1 and model 2): model 1 for forest areas only and model 2 including all other land cover in the study area. Sentinel-2 geospatial data for 2021, Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) tools and geographic information systems (GIS) are used. A Kappa index of 0.92 is obtained for both classifications, thus ruling out any notable seasonal differences in the images used. The results from both models indicate that it is land covers associated with forest uses which store the most carbon in the study area, accounting for >50 % more than the other land covers. It is concluded that the methodology and data used are very useful for quantifying ecosystem services, which will help the governance of the region by implementing measures to mitigate some of the effects of climate change and help to create silvicultural models for the sustainable management of the Atlantic Biogeographic Region.
近年来，一氧化碳排放量呈指数级增长，因此测量和量化碳固存是迈向可持续森林管理和应对气候变化的重要一步。本研究的总体目标是开发一个准确的模型，用于估算大西洋生物地理区域森林面积的碳储存和固存。具体而言，建模和实地采样在巴约纳市（西班牙西北部加利西亚）进行，该市被选为该区域具有代表性的生物群落。该方法包括在春季和秋季进行两次基于对象的图像分析（OBIA）分类，以观察季节性差异的可能存量。建立了两个碳储存和固存模型（模型1和模型2）：模型1仅适用于森林区域，模型2包括研究区域内的所有其他土地覆盖类型。使用了2021年的哨兵-2地理空间数据、生态系统服务综合价值评估（InVEST）工具和地理信息系统（GIS）。两种分类的卡帕指数均为0.92，因此排除了所用图像中存在任何明显季节性差异的可能性。两个模型的结果均表明，在研究区域内，与森林用途相关的土地覆盖类型储存的碳最多，比其他土地覆盖类型多50%以上。得出的结论是，所使用的方法和数据对于量化生态系统服务非常有用，这将有助于该地区通过实施措施减轻气候变化的一些影响来进行治理，并有助于创建大西洋生物地理区域可持续管理的造林模型。
