Suppr超能文献

揭示中央比利牛斯山亚高山草甸中蚯蚓物种产生的生物成因聚集体的年龄和起源及其近红外指纹图谱。

Unveiling the age and origin of biogenic aggregates produced by earthworm species with their NIRS fingerprint in a subalpine meadow of Central Pyrenees.

机构信息

Universidad del Atlántico, Barranquilla, Colombia.

Universidad Nacional de Colombia, Sede Palmira, Colombia.

出版信息

PLoS One. 2020 Aug 12;15(8):e0237115. doi: 10.1371/journal.pone.0237115. eCollection 2020.

Abstract

In this study the near-infrared reflectance (NIR) spectra signals (750-2,500 nm) of soil samples was compared with the NIR signals of the biogenic aggregates produced in the lab by three earthworm species, i.e., Aporrectodea rosea (Savigny 1826), Lumbricus friendi Cognetti, 1904 and Prosellodrilus pyrenaicus (Cognetti, 1904) from subalpine meadows in the Central Pyrenees. NIR spectral signatures of biogenic aggregates, root-aggregates, and non-aggregated soil were obtained together with soil carbon (C), nitrogen (N), [Formula: see text] and [Formula: see text] determinations. The concentrations of C, N and C:N ratio in the three types of soil aggregates identified were not statistically significant (ANOVA, p>0.05) although non-macroaggregated soil had slightly higher C concentrations (66.3 g kg-1 dry soil) than biogenic aggregates (earthworm- and root-aggregates, 64.9 and 63.5 g kg-1 dry soil, respectively), while concentrations of [Formula: see text] and [Formula: see text] were highest in the root-attached aggregates (3.3 and 0.31 mg kg dry soil-1). Total earthworm density and biomass in the sampled area was 137.6 ind. m-2, and 55.2 g fresh weight m-2, respectively. The biomass of aggregates attached to roots and non-macroaggregated soil was 122.3 and 134.8 g m-2, respectively, while biomass of free (particulate) organic matter and invertebrate biogenic aggregates was 62.9 and 41.7 g m-2, respectively. Multivariate analysis of NIR spectra signals of field aggregates separated root aggregates with high concentrations of [Formula: see text] and [Formula: see text] (41.5% of explained variance, axis I) from those biogenic aggregates, including root aggregates, with large concentrations of C and high C:N ratio (21.6% of total variability, axis II). Partial Least Square (PLS) regressions were used to compare NIR spectral signals of samples (casts and soil) and develop calibration equations relating these spectral data to those data obtained for chemical variables in the lab. After a derivatization process, the NIR spectra of field aggregates were projected onto the PLS factorial plane of the NIR spectra from the lab incubation. The projection of the NIR spectral signals onto the PLSR models for C, N, [Formula: see text] and [Formula: see text] from casts produced and incubated in the lab allowed us to identify the species and the age of the field biogenic aggregates. Our hypothesis was to test whether field aggregates would match or be in the vicinity of the NIR signals that corresponded to a certain species and the age of the depositions produced in the lab. A NIRS biogenic background noise (BBN) is present in the soil as a result of earthworm activity. This study provides insights on how to analyse the role of these organisms in important ecological processes of soil macro-aggregation and associated organic matter dynamics by means of analyzing the BBN in the soil matrix.

摘要

在这项研究中,比较了来自比利牛斯山脉中海拔草地的三种蚯蚓物种(即赤子爱胜蚓(Savigny 1826)、美洲大镰蚓(Cognetti, 1904)和普氏真蚓(Cognetti, 1904)在实验室中产生的生物团聚体的近红外反射(NIR)光谱信号(750-2500nm)与生物团聚体的 NIR 信号。获得了生物团聚体、根团聚体和非团聚体土壤的近红外光谱特征以及土壤碳(C)、氮(N)、[Formula: see text]和[Formula: see text]的测定值。尽管非大团聚体土壤的 C 浓度(66.3gkg-1干土)略高于生物团聚体(蚯蚓和根团聚体,分别为 64.9 和 63.5gkg-1干土),但三种类型的土壤团聚体中 C、N 和 C:N 比值的浓度没有统计学意义(方差分析,p>0.05),而[Formula: see text]和[Formula: see text]的浓度在根附着团聚体中最高(3.3 和 0.31mgkg-1干土)。研究区域内的总蚯蚓密度和生物量分别为 137.6ind.m-2和 55.2g新鲜重量 m-2。附着在根上和非大团聚体土壤中的团聚体的生物量分别为 122.3 和 134.8gm-2,而自由(颗粒)有机物质和无脊椎动物生物团聚体的生物量分别为 62.9 和 41.7gm-2。野外团聚体的近红外光谱信号的多元分析将高[Formula: see text]和[Formula: see text]浓度(解释方差的 41.5%,轴 I)的根团聚体与 C 和高 C:N 比(总变异性的 21.6%,轴 II)的包括根团聚体在内的生物团聚体分开。偏最小二乘(PLS)回归用于比较样本( casts 和土壤)的近红外光谱信号,并建立将这些光谱数据与实验室中获得的化学变量相关联的校准方程。经过衍生化处理后,将野外团聚体的近红外光谱信号投射到实验室孵育的近红外光谱的 PLS 因子平面上。在实验室中产生和孵育的 casts 的 NIR 光谱信号的 PLSR 模型对 C、N、[Formula: see text]和[Formula: see text]的投影使我们能够识别野外生物团聚体的物种和年龄。我们的假设是测试野外团聚体是否与对应于实验室中产生的特定物种和沉积年龄的 NIR 信号相匹配或接近。由于蚯蚓的活动,土壤中存在近红外光谱生物背景噪声(BBN)。本研究通过分析土壤基质中的 BBN,提供了有关如何分析这些生物在土壤大团聚体形成和相关有机质动态等重要生态过程中的作用的见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7d98/7423103/821b082fe31b/pone.0237115.g001.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验