The carbon budget of the managed grasslands of Great Britain constrained by earth observations
The carbon budget of the managed grasslands of Great Britain constrained by earth observations
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DOI：
10.5194/bg-2021-144
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发表时间：
2021
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影响因子：
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通讯作者：
V. Myrgiotis;T. Smallman;M. Williams
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作者：
V. Myrgiotis;T. Smallman;M. Williams
草地覆盖了英国约三分之二的土地面积，是陆地生物碳（C）的重要储存库。在一些监测良好的网站之外，管理草原的C动态的量化是复杂的，结合放牧和切割模式的天气条件的时空变化。地球观测（EO）任务产生高分辨率的经常检索的代理数据的草原冠层的状态，但EO数据和地球化学建模之间的协同作用，以估计草原C动态的探索不足。在这里，我们展示了潜在的5模型-数据融合（ESTA）提供强大的近实时分析GB（英格兰，威尔士和苏格兰）管理的草原。我们结合联合收割机EO数据和基于过程的建模来估计草地C平衡，并检查管理的作用。我们实现了一个可预测的算法来（1）从植被减少数据（Proba-V）中推断草地管理，（2）通过同化叶面积指数（LAI）数据（Sentinel-2）优化模型参数，（3）模拟牲畜放牧，割草和C分配和大气损失。2017年和2018年，在1855个字段（10个来自GB的样本）中应用了该算法。该算法能够有效地同化基于Sentinel-2的LAI时间序列（重叠= 80%，RMSE=1gCm−2，偏差=0.35 gCm−2），并预测与独立的基于人口普查的数据相对应的每个区域的牲畜密度（r=0.68）。所有模拟田地的平均总生物量为6（±1.8）tDM ha− 1 y −1。模拟的草地生态系统在2017年和2018年平均为碳汇; 2017年的GB平均净生态系统交换（NEE）和净生物群落交换（NBE）为-232 94，2018年为-120 103 gCm− 2 y −1。2018年夏季干旱减少了碳汇，与2017年相比，2018年碳源（NBE>0）的数量增加了15 9倍。我们的结论是，管理的草地条件和时间，强度和类型的落叶的形式管理草原的C平衡的关键决定因素。然而，极端天气，如长期干旱，可以转换草地碳汇源。1 https://doi.org/10.5194/bg-2021-144讨论开始日期：2021年6月14日c © Author（s）2021. CC BY 4.0许可证。
Grasslands cover around two thirds of the land area of Great Britain (GB) and are important reservoirs of terrestrial biological carbon (C). Outside a few well-monitored sites the quantification of C dynamics in managed grasslands is made complex by the spatio-temporal variability of weather conditions combined with grazing and cutting patterns. Earth observation (EO) missions produce high-resolution frequently-retrieved proxy data on the state of grassland canopies but synergies between EO data and biogeochemical modelling to estimate grassland C dynamics are under-explored. Here, we show the potential 5 of model-data fusion (MDF) to provide robust near-real time analyses of managed grasslands of GB (England, Wales and Scotland). We combine EO data and process-based modelling to estimate grassland C balance and to examine the role of management. We implement a MDF algorithm to (1) infer grassland management from vegetation reduction data (Proba-V), (2) optimise model parameters by assimilating leaf area index (LAI) data (Sentinel-2) and (3) simulate livestock grazing, grass cutting, and C allocation and loss to the atmosphere. The MDF algorithm was applied for 2017 and 2018 at 1855 fields 10 sampled from across GB. The algorithm was able to effectively assimilate the Sentinel-2 based LAI time series (overlap=80%, RMSE=1gCm−2, bias=0.35 gCm−2) and predict livestock densities per area that correspond with independent census-based data (r=0.68). The mean total removed biomass across all simulated fields was 6 (±1.8) tDM ha−1y−1. The simulated grassland ecosystems were on average C sinks in 2017 and 2018; the GB-average net ecosystem exchange (NEE) and net biome exchange (NBE) for 2017 was -232±94 and for 2018 was -120±103 gCm−2y−1. The 2018 summer drought reduced C sinks, with a 15 9-fold increase in the number fields that were C sources (NBE>0) in 2018 compared to 2017. We conclude that management in the form of sward condition and the timing, intensity and type of defoliation are key determinants of the C balance of managed grasslands. Nevertheless, extreme weather, such as prolonged droughts, can convert grassland C sinks to sources. 1 https://doi.org/10.5194/bg-2021-144 Preprint. Discussion started: 14 June 2021 c © Author(s) 2021. CC BY 4.0 License.