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Impact of land cover uncertainties on estimates of biospheric carbon fluxes

机译:土地覆盖不确定性对生物圈碳通量估计值的影响

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摘要

Large-scale bottom-up estimates of terrestrial carbon fluxes, whether based on models or inventory, are highly dependent on the assumed land cover. Most current land cover and land cover change maps are based on satellite data and are likely to be so for the foreseeable future. However, these maps show large differences, both at the class level and when transformed into Plant Functional Types (PFTs), and these can lead to large differences in terrestrial CO2 fluxes estimated by Dynamic Vegetation Models. In this study the Sheffield Dynamic Global Vegetation Model is used. We compare PFT maps and the resulting fluxes arising from the use of widely available moderate (1 km) resolution satellite-derived land cover maps (the Global Land Cover 2000 and several MODIS classification schemes), with fluxes calculated using a reference high (25 m) resolution land cover map specific to Great Britain (the Land Cover Map 2000). We demonstrate that uncertainty is introduced into carbon flux calculations by (1) incorrect or uncertain assignment of land cover classes to PFTs; (2) information loss at coarser resolutions; (3) difficulty in discriminating some vegetation types from satellite data. When averaged over Great Britain, modeled CO2 fluxes derived using the different 1 km resolution maps differ from estimates made using the reference map. The ranges of these differences are 254 gC m(-2) a(-1) in Gross Primary Production (GPP); 133 gC m(-2) a(-1) in Net Primary Production (NPP); and 43 gC m(-2) a(-1) in Net Ecosystem Production (NEP). In GPP this accounts for differences of -15.8% to 8.8%. Results for living biomass exhibit a range of 1109 gC m(-2). The types of uncertainties due to land cover confusion are likely to be representative of many parts of the world, especially heterogeneous landscapes such as those found in western Europe.
机译:无论是基于模型还是根据清单,对地面碳通量进行大规模的自下而上的估算都高度依赖于假定的土地覆盖。当前大多数的土地覆盖和土地覆盖变化图都是基于卫星数据的,并且在可预见的将来很可能是这样。但是,这些图在类级别和转换为植物功能类型(PFT)时均显示出较大差异,并且这些差异可能导致动态植被模型估计的陆地二氧化碳通量存在较大差异。在这项研究中,使用了谢菲尔德动态全球植被模型。我们比较了PFT图和使用广泛可用的中度(1 km)分辨率的卫星衍生的土地覆盖图(2000年全球土地覆盖和几种MODIS分类方案)所产生的通量,并使用了参考高(25 m )解析特定于英国的土地覆盖图(2000年土地覆盖图)。我们证明,通过以下方法将不确定性引入碳通量计算中:(1)将土地覆盖类别分配给PFT的不正确或不确定; (2)较粗分辨率下的信息丢失; (3)难以从卫星数据中区分出某些植被类型。当对英国进行平均时,使用不同的1 km分辨率图得出的模拟CO2通量与使用参考图得出的估算值不同。这些差异的范围是初级生产总值(GPP)中的254 gC m(-2)a(-1);净初级生产(NPP)133 gC m(-2)a(-1);净生态系统生产(NEP)中的43 gC m(-2)a(-1)。在GPP中,这占-15.8%至8.8%的差异。活性生物量的结果显示范围为1109 gC m(-2)。土地覆盖混乱造成的不确定性类型可能代表了世界许多地区,尤其是异质景观,例如在西欧发现的景观。

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