Developing high-resolution above- and below-ground 3-D carbon maps for farm and land-D carbon maps

Stelina已成功获得2019年9月/ 10月开始的CENTA2博士培训计划的名额。博士学位的目的是开发和评估开发可应用于农场和景观规模的地下和地上碳的高分辨率3D地图/模型的程序。预计该模型将有助于对自然资本进行高分辨率评估，评估不同农业实践对碳储存的影响，并有助于为未来的农业环境法规提供信息。英国正在寻求通过在农业和森林土地上储存更高水平的碳来减少温室气体（GHG）净排放，从而最大限度地减少气候变化。温室气体排放是英国农村土地利用对环境的最大负面影响，碳储存是自然资本的一种形式，已经为英国制作了1公里分辨率的土壤和地上碳储存地图（CEH 2018）。虽然存在国家地图，但大多数土地管理决策都是在农场或景观层面进行的，1公里分辨率不足以检查植树、树篱扩展和保护性耕作等管理方案的效果（Upson等人，2016；Axe等人，2017；Giannitsopoulos等人，2019）。因此，该博士学位的目的是开发和评估开发地下和地上碳的高分辨率3D地图/模型的程序，这些地图/模型使用数字技术和最新研究成果的创新，并且可以应用于农场和景观规模（图1）。预期的模型将建立在垂直分辨率为10厘米的土壤C模型的基础上（如Veronesi等人2014年使用的），但增加水平分辨率，以便检查田间管理和景观特征（如树篱）变化的影响。这种地图/模型将有助于对自然资本进行高分辨率评估，评估不同农业实践对碳储存的影响，并有助于为未来的农业环境法规提供信息。

Stelina has successfully secured a place on the CENTA2 Doctoral Training Programme starting in September/October 2019. The aim of the PhD is to develop and evaluate procedures for developing high resolution 3D map/models of below- and above ground carbon that can be applied at farm- and landscape scale. It is anticipated that the model will be useful in high-resolution assessments of natural capital, assessments of the effect of different farm practices on carbon storage, and could help inform future agri-environment regulations.The UK is seeking to minimise climate change by reducing net greenhouse gas (GHG) emissions by storing higher levels of carbon on agricultural and forest land. GHG emissions are the greatest negative environmental effect of rural land use in the UK, carbon storage is a form of natural capital, and maps of soil and above-ground carbon storage have been produced for England at 1 km resolution (CEH 2018). Whilst national maps exist, most land management decisions are taken at a farm- or landscape-level, and a 1 km resolution is insufficient to examine the effect ofmanagement options such as tree planting, hedgerow expansion, and conservation tillage (Upson et al. 2016; Axe et al., 2017; Giannitsopoulos et al. 2019). Hence the aim of this PhD is to develop and evaluate procedures for developing high resolution 3D map/models of below- and above ground carbon that uses innovations in digital technology and recent research results, and which can be applied at farm- and landscape scale (Fig 1). The anticipated model will build on a vertical resolution for soil C model of 10 cm (as used by Veronesi et al. 2014), but increase the horizontal resolution to allow the examination of the effect of changes in field management and landscape features such as hedgerows. Such a map/model will be useful in high-resolution assessments of natural capital, assessments of the effect of different farm practices on carbon storage, and could help inform future agri-environment regulations.