Stabilisation of pyrogenic carbon in tropical grasslands (SPECTRAL)

每年，火灾烧毁地球上超过5亿公顷的土地。这些火灾留下部分燃烧的生物质残余物，作为“热解碳”沉积在土壤表面。据估计，每年有多达114至379 Tg的PyC被添加到土壤中，全球模型预测，许多地区的火灾频率和强度将增加。这些热解碳中的大部分沉积在土壤表面，随后进入更深层，因此在一些易发生火灾的生态系统（如热带稀树草原）中，热解碳可以占土壤中储存的碳总量的50%。土壤中热解碳的储存对自然和管理的生态系统与全球气候系统的相互作用至关重要。PyC一旦进入土壤，就会有一个固有的缓慢周转，这意味着它将比沉积在未暴露于火的土壤上或土壤中的有机物质持续更长时间。然而，值得注意的是，我们在很大程度上忽视了PyC对全球碳循环的命运和总体贡献。这是因为科学界到目前为止对决定PyC在土壤中分布和周转的因素只有初步的了解。在理解作为农业实践添加到土壤中的烧焦生物质的作用方面取得了重大进展，我们对这些系统以及它如何与土壤生物和物理因素相互作用有了合理的理解。然而，我们需要更好地了解PyC颗粒变化的过程，以及火灾后引入土壤的碳的稳定性，以便模拟当前的PyC动态，并能够在未来气候下预测这些。特别是生物过程，如无脊椎土壤动物和不同土壤微生物类群的作用，迄今尚未得到足够的重视。我们提出了一项研究计划，旨在创建一个新的土壤PyC模型，该模型可以与区域和全球碳气候模型相关联，到目前为止，这些模型忽略了PyC。我们将通过在加蓬热带萨凡纳系统进行的一些实验来实现这一目标。这提供了一个理想的实验设置，因为这些火灾易发系统在土壤剖面中含有大量的PyC，我们将能够在Lopé国家公园进行长期的火灾操纵现场实验。使用有针对性的土壤取芯对比火灾返回间隔，结合确定整个剖面的PyC年龄（使用天然14C丰度），我们将能够得出这个稳定的土壤碳库的停留时间。通过使用同位素标记的PyC（基于在13C富集下生长的植物，13C是一种无害的稳定碳同位素），我们的目标是更好地了解土壤PyC动态的机理和定量。这种方法与土壤动物存在的操纵有关，因为这些被假设对土壤中PyC的分布和营业额有显着影响。从同位素示踪剂研究的见解将被用来开发一种新的土壤有机质模型，将PyC动力学首次，我们将能够参数化这个新的模型与我们的实验数据和验证模拟营业额对我们独立评估的营业额时间PyC池。

Every year, fires burn more than 500 million ha of the land surface on Earth. These fires leave residues of partially burned biomass which are deposited on the soil surface as "pyrogenic carbon" (PyC). It is estimated that as much as 114 to 379 Tg of PyC are added to soils each year, and global models predict that fire frequency and intensity will increase in many areas. Much of this PyC is deposited on to the soil surface and subsequently incorporated into deeper layers, so that it can account for as much as 50% of total carbon stored in soils in some fire prone ecosystems such as tropical savannahs.Storage of pyrogenic carbon in soils matters a lot to the way in which natural and managed ecosystems interact with the global climate system. PyC has an inherently slow turnover once it is in the soil, meaning that it will persist much longer than organic matter deposited on or in soils that have not been exposed to fire. Remarkably, however, we largely ignore the fate and overall contribution of PyC to global carbon cycling. This is due to the fact that the scientific community so far only has a rudimentary understanding of what determines PyC distribution and turnover in soils. There have been significant advances in understanding the role of charred biomass added to soil as an agricultural practice, and we have a reasonable understanding of these systems and how it interacts with soil organisms and physical factors. However, we require a much better understanding of processes underlying the changes of PyC particles, and stabilisation of carbon introduced to the soil after fire, in order to model current PyC dynamics, and be able to forecast these under future climates. Particularly biological processes, such as the role of invertebrate soil animals and different groups of soil microbial organisms have so far not received sufficient attention. We propose a programme of research directed at creating a novel soil-PyC model that can be linked to regional and global carbon-climate models, which so far ignore PyC. We will achieve this through a number of experiments based in a tropical savannah system in Gabon. This provides an ideal experimental set-up, as these fire prone systems have a significant abundance of PyC in the soil profile, and we will be able to link to a long-term fire manipulation field experiments in the Lopé National Park. Using targeted soil coring for contrasting fire return intervals, combined with the determination of the age of PyC (usingnatural 14C abundance) across the profile, we will be able to derive residence times of this stable soil carbon reservoir. By using isotopically labelled PyC (based on plants grown under enrichment with 13C, a non-harmful, stable isotope of carbon), we aim to gain a better mechanistic and quantitative understanding of soil PyC dynamics. This approach is linked to manipulations of soil animal presence, as these are hypothesised to have a significant influence over the distribution and turnover of PyC in the soil. Insights from the isotopic tracer study will be used to develop a novel soilorganic matter model to incorporate PyC dynamics for the first time, We will be able to parameterise this new model with our experimental data and validate simulated turnover against our independently assessed turnover time of PyC pools.