Interactive plant-trait and climate effects on soil organic carbon along the Chilean coastal cordillera

植物性状和气候对智利沿海山脉土壤有机碳的相互作用的影响

• 批准号: 280611154
• 负责人: Professorin Dr. Maaike Bader
• 金额: --
• 依托单位: Helmholtz-Zentrum Potsdam - Deutsches GeoForschungsZentrum (GFZ)
• 依托单位国家: 德国
• 项目类别: Priority Programmes
• 财政年份: 2015
• 资助国家: 德国
• 起止时间: 2014-12-31 至 2019-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/280611154?language=en
• 关键词: Interactive; plant; trait; climate; effects

The input of organic carbon into the soil is one of the major drivers of weathering and erosion. This input, in turn, is primarily controlled by interactive effects of vegetation and climate. Understanding how climate and vegetation together determine soil organic carbon, as an energy source for microorganisms as weathering engines and as a stabilizing factor in erosion, is one of the major scientific goals of the EarthShape program (SPP 1803). With this project we aim to pursue this goal by studying organic carbon fluxes, from plant productivity to litter decomposition and carbon dynamics in soils, disentangling plant and climate effects. Based on our hypothesis that the relative importance of climate and plant traits may be scale dependent we will work at multiple spatial-climatic scales. These scales encompass three biomes along the Chilean coastal cordillera (arid, mediterranean and wet-temperate) and two contrasting study sites within each of these biomes. The investigation of soil organic carbon characteristics below contrasting plant types within these three biomes and six study sites, will allow us to partially decouple vegetation and climate effects. The effect of plant and litter diversity on litter decomposition will also be studied. A further decoupling is achieved by translocating plant litter and soils between the three biomes and sites in a fully-reciprocal experiment over a period of two years. Vegetation will be regarded from a functional point of view, carbon inputs, via primary productivity, litter decomposition, and soil organic carbon transformations being described as functions of plant functional traits (chemical, physical and phenological). To test impacts of vegetation and climate on subsoil organic carbon characterized by a high persistence and a long turnover rate we will translocate subsoil up to the surface where temperature, moisture and organic carbon inputs increase. We will apply innovative lab devices (HPLC, ICM-PS, EA-IRMS, AQUALOG) to describe the chemical composition (C, N, P, 13C, lignin, tannin, trace elements) of leaf, litter and of soil organic carbon (particulate and dissolved) along the soil profile. Simultaneous absorbance-fluorescence measurement technique will advance the analyses of dissolved soil organic carbon compounds including Excitation Emission Matrix (EEM) Fluorescence and Parallel Factor Analysis (PARAFAC) techniques. The joint data analysis is an essential part of this project to connect the plant, litter and soil data following the proposed multi-scale approach. Our results will include a statistical model predicting soil organic carbon contents based on climate and vegetation traits, including the main steps between productivity and final soil carbon contents. This improved process knowledge is important for understanding and modelling carbon cycles and geomorphology-related soil processes.

土壤中有机碳的输入是风化和侵蚀的主要驱动因素之一。反过来，这一投入主要受植被和气候的交互影响所控制。了解气候和植被如何共同决定土壤有机碳，作为微生物的能源，作为风化引擎和侵蚀的稳定因素，是EarthShape计划(SPP 1803)的主要科学目标之一。通过这个项目，我们的目标是通过研究有机碳通量来实现这一目标，从植物生产力到凋落物分解和土壤中的碳动态，解开植物和气候的影响。基于气候和植物特征的相对重要性可能与尺度相关的假设，我们将在多个空间-气候尺度上工作。这些尺度包括智利沿海珊瑚带(干旱、地中海和湿温带)的三个生物群，以及每个生物群中两个截然不同的研究地点。在这三个生物群落和六个研究地点内，对不同植物类型下的土壤有机碳特征进行调查，将使我们能够部分地将植被和气候影响脱钩。还将研究植物和凋落物多样性对凋落物分解的影响。在为期两年的完全互惠实验中，通过在三个生物群落和地点之间转移植物凋落物和土壤，实现了进一步的脱钩。从功能的角度来看，植被通过初级生产力、凋落物分解和土壤有机碳转化的碳输入被描述为植物功能特性(化学、物理和物候)的函数。为了测试植被和气候对具有高持久性和长周转率特征的底土有机碳的影响，我们将底土转移到温度、水分和有机碳输入增加的表层。我们将应用创新的实验室设备(高效液相、ICM-PS、EA-IRMS、AQUALOG)来描述土壤剖面上树叶、凋落物和土壤有机碳(颗粒和溶解)的化学成分(C、N、P、13C、木质素、单宁、微量元素)。吸收-荧光同步测量技术将促进土壤有机碳化合物的分析，包括激发发射矩阵(EEM)、荧光和平行因子分析(PARAFAC)技术。联合数据分析是该项目的重要组成部分，以便按照拟议的多尺度方法将植物、凋落物和土壤数据连接起来。我们的结果将包括一个基于气候和植被特征预测土壤有机碳含量的统计模型，包括生产力和最终土壤碳含量之间的主要步骤。这种改进的过程知识对于理解和模拟碳循环和与地貌有关的土壤过程很重要。