Visible near infra-red (VisNIR) spectroscopy for predicting soil organic carbon in Ethiopia

Over the past few decades, the advantages of the visible-near infra-red (VisNIR) diffuse reflectance spectrometer (DRS) method have enabled prediction of soil organic carbon (SOC). In this study, SOC was predicted using regression models for samples taken from three sites (Gununo, Maybar and Anjeni) in Ethiopia. SOC was characterized in laboratory using conventional wet chemistry and VisNIR-DRS methods. Principal component analysis (PCA), principal component regression (PCR) and partial least square regression (PLS) models were developed using Unscrambler X 10.2. PCA results show that the first two components accounted for a minimum of 96% variation which increased for individual sites and with data treatments. Correlation (r), coefficient of determination (R2) and residual prediction deviation (RPD) were used to rate four models built. PLS model (r, R2, RPD) values for Anjeni were 0.9, 0.9 and 3.6; for Gununo values 0.6, 0.3 and 1.2; for Maybar values 0.6, 0.3 and 0.9, and for the three sites values 0.7, 0.6 and 1.5, respectively. PCR model values (r, R2, RPD) for Anjeni were 0.9, 0.8 and 2.7; for Gununo values 0.5, 0.3 and 1; for Maybar values 0.5, 0.1 and 0.7, and for the three sites values 0.7, 0.5 and 1.2, respectively. Comparison and testing of models shows superior performance of PLS to PCR. Models were rated as very poor (Maybar), poor (Gununo and three sites) and excellent (Anjeni). A robust model, Anjeni, is recommended for prediction of SOC in Ethiopia.

Pedogeomorphology, geochronology and paleobotany of soil profiles obtained in the Nagqu area, central Tibet

Vast areas on the Tibetan Plateau are covered by alpine sedge mats consisting of different species of the genus Kobresia. These mats have topsoil horizons rich in rhizogenic organic matter which creates turfs. As the turfs have recently been affected by a complex destruction process, knowledge concerning their soil properties, age and pedogenesis are needed. In the core area of Kobresia pygmaea mats around Nagqu (central Tibetan Plateau, ca. 4500 m a.s.l.), four profiles were subjected to pedological, paleobotanical and geochronological analyses concentrating on soil properties, phytogenic composition and dating of the turf. The turf of both dry K. pygmaea sites and wet Kobresia schoenoides sites is characterised by an enrichment of living (dominant portion) and dead root biomass. In terms of humus forms, K. pygmaea turfs can be classified as Rhizomulls mainly developed from Cambisols. Wet-site K. schoenoides turfs, however, can be classified as Rhizo-Hydromors developed from Histic Gleysols. At the dry sites studied, the turnover of soil organic matter is controlled by a non-permafrost cold thermal regime. Below-ground remains from sedges are the most frequent macroremains in the turf. Only a few pollen types of vascular plants occur, predominantly originating from sedges and grasses. Large amounts of microscopic charcoal (indeterminate) are present. Macroremains and pollen extracted from the turfs predominantly have negative AMS 14C ages, giving evidence of a modern turf genesis. Bulk-soil datings from the lowermost part of the turfs have a Late Holocene age comprising the last ca. 2000 years. The development of K. pygmaea turfs was most probably caused by an anthropo(zoo)-genetically initiated growth of sedge mats replacing former grass-dominated vegetation ('steppe'). Thus the turfs result from the transformation of pre-existing topsoils comprising a secondary penetration and accumulation of roots. K. schoenoides turfs, however, are characterised by a combined process of peat formation and penetration/accumulation of roots probably representing a (quasi) natural wetland vegetation.

Soil organic carbon storage and soil properties for 50 soil profiles in the Lena River Delta including land form description and map

To project the future development of the soil organic carbon (SOC) storage in permafrost environments, the spatial and vertical distribution of key soil properties and their landscape controls needs to be understood. This article reports findings from the Arctic Lena River Delta where we sampled 50 soil pedons. These were classified according to the U.S.D.A. Soil Taxonomy and fall mostly into the Gelisol soil order used for permafrost-affected soils. Soil profiles have been sampled for the active layer (mean depth 58±10 cm) and the upper permafrost to one meter depth. We analyze SOC stocks and key soil properties, i.e. C%, N%, C/N, bulk density, visible ice and water content. These are compared for different landscape groupings of pedons according to geomorphology, soil and land cover and for different vertical depth increments. High vertical resolution plots are used to understand soil development. These show that SOC storage can be highly variable with depth. We recommend the treatment of permafrost-affected soils according to subdivisions into: the surface organic layer, mineral subsoil in the active layer, organic enriched cryoturbated or buried horizons and the mineral subsoil in the permafrost. The major geomorphological units of a subregion of the Lena River Delta were mapped with a land form classification using a data-fusion approach of optical satellite imagery and digital elevation data to upscale SOC storage. Landscape mean SOC storage is estimated to 19.2±2.0 kg C/m**2. Our results show that the geomorphological setting explains more soil variability than soil taxonomy classes or vegetation cover. The soils from the oldest, Pleistocene aged, unit of the delta store the highest amount of SOC per m**2 followed by the Holocene river terrace. The Pleistocene terrace affected by thermal-degradation, the recent floodplain and bare alluvial sediments store considerably less SOC in descending order.

Atributos químicos e biológicos de solos sob diferentes ecossistemas e adicionados de material vegetal de soja

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Factors driving the carbon mineralization priming effect in a sandy loam soil amended with different types of biochar

The effect of biochar on the soil carbon mineral- ization priming effect depends on the characteristics of the raw materials, production method and pyrolysis conditions. The goal of the present study is to evaluate the impact of three different types of biochar on physicochemical properties and CO2 emissions of a sandy loam soil. For this purpose, soil was amended with three different biochars (BI, BII and BIII) at a rate of 8 wt % and soil CO2 emissions were measured for 45 days. BI is produced from a mixed wood sieving from wood chip production, BII from a mixture of paper sludge and wheat husks and BIII from sewage sludge. Cumulative CO2 emissions of biochars, soil and amended soil were well fit to a simple first-order kinetic model with correlation coef- ficients (r 2 ) greater than 0.97. Results show a negative prim- ing effect in the soil after addition of BI and a positive prim- ing effect in the case of soil amended with BII and BIII. These results can be related to different biochar properties such as carbon content, carbon aromaticity, volatile matter, fixed carbon, easily oxidized organic carbon or metal and phenolic substance content in addition to surface biochar properties. Three biochars increased the values of soil field capacity and wilting point, while effects over pH and cation exchange capacity were not observed.

How can soil monitoring networks be used to improve predictions of organic carbon pool dynamics and CO2 fluxes in agricultural soils?

Abstract As regional and continental carbon balances of terrestrial ecosystems become available, it becomes clear that the soils are the largest source of uncertainty. Repeated inventories of soil organic carbon (SOC) organized in soil monitoring networks (SMN) are being implemented in a number of countries. This paper reviews the concepts and design of SMNs in ten countries, and discusses the contribution of such networks to reducing the uncertainty of soil carbon balances. Some SMNs are designed to estimate country-specific land use or management effects on SOC stocks, while others collect soil carbon and ancillary data to provide a nationally consistent assessment of soil carbon condition across the major land-use/soil type combinations. The former use a single sampling campaign of paired sites, while for the latter both systematic (usually grid based) and stratified repeated sampling campaigns (5–10 years interval) are used with densities of one site per 10–1,040 km². For paired sites, multiple samples at each site are taken in order to allow statistical analysis, while for the single sites, composite samples are taken. In both cases, fixed depth increments together with samples for bulk density and stone content are recommended. Samples should be archived to allow for re-measurement purposes using updated techniques. Information on land management, and where possible, land use history should be systematically recorded for each site. A case study of the agricultural frontier in Brazil is presented in which land use effect factors are calculated in order to quantify the CO2 fluxes from national land use/management conversion matrices. Process-based SOC models can be run for the individual points of the SMN, provided detailed land management records are available. These studies are still rare, as most SMNs have been implemented recently or are in progress. Examples from the USA and Belgium show that uncertainties in SOC change range from 1.6–6.5 Mg C ha−1 for the prediction of SOC stock changes on individual sites to 11.72 Mg C ha−1 or 34% of the median SOC change for soil/land use/climate units. For national SOC monitoring, stratified sampling sites appears to be the most straightforward attribution of SOC values to units with similar soil/land use/climate conditions (i.e. a spatially implicit upscaling approach). Keywords Soil monitoring networks - Soil organic carbon - Modeling - Sampling design

What determines soil organic carbon stocks in the grazing lands of north-eastern Australia?

This study aimed to unravel the effects of climate, topography, soil, and grazing management on soil organic carbon (SOC) stocks in the grazing lands of north-eastern Australia. We sampled for SOC stocks at 98 sites from 18 grazing properties across Queensland, Australia. These samples covered four nominal grazing management classes (Continuous, Rotational, Cell, and Exclosure), eight broad soil types, and a strong tropical to subtropical climatic gradient. Temperature and vapour-pressure deficit explained >80% of the variability of SOC stocks at cumulative equivalent mineral masses nominally representing 0-0.1 and 0-0.3m depths. Once detrended of climatic effects, SOC stocks were strongly influenced by total standing dry matter, soil type, and the dominant grass species. At 0-0.3m depth only, there was a weak negative association between stocking rate and climate-detrended SOC stocks, and Cell grazing was associated with smaller SOC stocks than Continuous grazing and Exclosure. In future, collection of quantitative information on stocking intensity, frequency, and duration may help to improve understanding of the effect of grazing management on SOC stocks. Further exploration of the links between grazing management and above- and below-ground biomass, perhaps inferred through remote sensing and/or simulation modelling, may assist large-area mapping of SOC stocks in northern Australia. © CSIRO 2013.