Pedological features affecting carbon accumulation in submerged-soils sequence assessed with Vis-NIR spectroscopy in a coastal wetland in Albania

IF 5.7 1区 农林科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY
Adri Erebara , Albert Kopali , Seit Shallari , Erika Di Iorio , Alessio Manzo , Elettra Longobardi , Pasquale Napoletano , Anna De Marco , Claudio Colombo
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Abstract

The sequestration of SOC in submerged soils depends on the anaerobic conditions and vegetation types. In this context, soil spectroscopy is an accurate and reproducible method to estimate SOC in the visible and near infrared region. The aim of this research was to quantify the SOC fraction in wetland soils using soil spectroscopy and, subsequently, to try and establish a relation of different carbon fractions with soil pedological features. A transect of 17 pedons was sampled to analyze pedological features that affect carbon accumulation and decarbonation processes in the Kune Vaini lagoon system in Albania. The organic and inorganic C pools were analyzed using dry combustion, with a CNS analyser to determine total organic carbon (TOC), and with a furnace to determine loss on ignition (LOI) at 350 and 450 °C. Vis-NIR spectra were analysed using two regression models (PLSR and SVMR) that were calibrated and validated to obtain a valuable prediction for soil C fractions. Results indicated that the difference of soil organic matter (SOM), estimated with CNS and LOI, can be considered to represent the SOM that is strongly resistant to mineralisation. The SOM from LOI450 was considered to have more resistant forms of organic C, in spite of the more labile and degradable ones (TOC, LOI350). Models derived from PLSR had slightly higher RPD values compared to the results obtained from the SVM regression modelling for all C fractions and for carbonate, EC, BD, and pH. This study showed that the use of visible near infrared spectroscopy coupled with the PLSR model allowed for the accurate prediction of LOI, TOC, CaCO3, BD, EC, and pH of submerged soils. The PLSR model can be applied in estimating different carbon contents under submerged conditions to get a deeper understanding of carbon accumulation in wetland soil ecosystems.

Abstract Image

用可见光-近红外光谱评估阿尔巴尼亚沿海湿地淹没土壤序列中影响碳积累的土壤特征
沉水土壤有机碳的固存取决于厌氧条件和植被类型。在此背景下,土壤光谱学是一种在可见和近红外区域准确、可重复性高的土壤有机碳估算方法。本研究的目的是利用土壤光谱学对湿地土壤的有机碳组分进行量化,并试图建立不同碳组分与土壤土壤学特征的关系。为了分析影响阿尔巴尼亚Kune Vaini泻湖系统碳积累和脱碳过程的土壤学特征,对17个样带进行了取样。采用干燃烧法对有机碳和无机碳池进行分析,用CNS分析仪测定总有机碳(TOC),用炉法测定350°和450°C时的燃失量(LOI)。使用两种回归模型(PLSR和SVMR)对Vis-NIR光谱进行了分析,并对其进行了校准和验证,以获得有价值的土壤C组分预测。结果表明,用CNS和LOI估算的土壤有机质(SOM)差异可以认为代表了土壤有机质对矿化的强烈抵抗。LOI450的SOM被认为具有更强的有机C抗性,尽管更不稳定和可降解的有机C (TOC, LOI350)。与支持向量机回归模型得到的所有C组分、碳酸盐、EC、BD和pH的RPD值相比,PLSR模型得到的RPD值略高。本研究表明,使用可见近红外光谱与PLSR模型相结合,可以准确预测淹没土壤的LOI、TOC、CaCO3、BD、EC和pH。PLSR模型可用于估算淹没条件下不同碳含量,从而更深入地了解湿地土壤生态系统的碳积累情况。
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来源期刊
Catena
Catena 环境科学-地球科学综合
CiteScore
10.50
自引率
9.70%
发文量
816
审稿时长
54 days
期刊介绍: Catena publishes papers describing original field and laboratory investigations and reviews on geoecology and landscape evolution with emphasis on interdisciplinary aspects of soil science, hydrology and geomorphology. It aims to disseminate new knowledge and foster better understanding of the physical environment, of evolutionary sequences that have resulted in past and current landscapes, and of the natural processes that are likely to determine the fate of our terrestrial environment. Papers within any one of the above topics are welcome provided they are of sufficiently wide interest and relevance.
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