A NanoSIMS study on the distribution of soil organic matter,iron and manganese in a nodule from a Stagnosol

The development of Stagnosols is the consequence of perched water tables, which induce periodic oxidizing and reducing conditions. These cause the spatial distribution of iron (Fe) and manganese (Mn) between the soil matrix and ferromanganese concretions or nodules. Since oxides of these metals may interact with organic matter, we studied their spatial distribution in bulk material from the Bg horizon of a Stagnosol and in a nodule separated from the horizon. We used wet‐chemical analyses and X‐ray diffractometry together with microscopic techniques and nano‐scale secondary ion mass spectrometry (NanoSIMS), the latter allowing for a submicrometre‐scale spatial resolution. X‐ray diffractometry revealed the presence of quartz, clay minerals, micas and feldspars as the dominant minerals and indicated the presence of lepidocrocite. Relative to the bulk horizon material, the nodule was strongly enriched in organic C (by a factor of 31) and pedogenic (dithionite‐extractable) Fe and Mn (by factors of 2.2 and 62). We selected two regions on a thin section of the nodule for NanoSIMS investigations after studying the element distribution by scanning‐electron microscopy (SEM): one was located in an almost closed pore, the other one along an elongated pore. The NanoSIMS measurements allowed a clearer distinction of Fe‐ and Mn‐accumulation zones than SEM‐EDS. The evaluation of the NanoSIMS measurements by unsupervised classification revealed that zones containing silicates and Mn oxides and the transitional zones between Fe and Mn oxides were particularly enriched in soil organic matter, while, with one exception, the pure Fe‐accumulation zones did not indicate the presence of soil organic matter.     

NanoSIMS as a tool for characterizing soil model compounds and organomineral associations in artificial soils

Purpose  

Secondary ion mass spectrometry at the nanoscale (NanoSIMS) is a new and promising technique in soil science, as it allows us to explore the elemental and isotopic composition of a solid sample with high sensitivity at a submicron scale. In this study, we demonstrate that it is possible to differentiate the major components of soils by this technique.     

微尺度重金属土壤化学研究进展与展望

土壤重金属污染是我国面临的重要生态环境问题,有效管控与修复重金属污染土壤有必要弄清重金属与土壤固相组分的作用机制。土壤组成多样、结构复杂、空间异质,加之土壤团聚体粒径大小不一,形成微观结构和表面性质各异的土壤微域,控制着重金属的形态转化及生物有效性。因此,深入认识微尺度的重金属土壤化学对于预测和管控土壤重金属环境化学行为至关重要。同步辐射X射线微探针(Microprobe)、X射线扫描透射显微术(STXM)及纳米二次离子质谱技术(Nano SIMS)等技术具有微纳米级空间分辨率,为在环境意义尺度上探究微尺度重金属土壤化学提供了独特的支撑平台。本文从环境土壤化学发展历程及当前发展瓶颈、现代微尺度分析技术及其在微尺度重金属土壤化学中的应用进展等方面综述,并对该领域未来的发展进行了展望。     

Spatial heterogeneity of a microbial community in a sandy soil ecosystem

A fieldwork was carried out in Caesarea sand dunes, Israel, to determine the influence of fine-scale landscape-patch abiotic-factor heterogeneity on microbial activity in a Mediterranean region. Soil organisms in terrestrial systems are unevenly distributed in time and space, and are often aggregated. Spatio-temporal patchiness in the soil environment is thought to be crucial for the maintenance of soil biodiversity, providing diverse microhabitats that are tightly interwoven with resource partitioning. Determination of a ‘scale unit’ to help understand ecological processes has become one of the important and most debatable problems in recent years. To better understand the distribution of soil microbial communities at multiple spatial scales, a survey was conducted to examine the spatial organization of the community structure in two sandy soil ecosystems. One-hundred forty-four soil samples were collected from two patches 4000 m apart from each other. Basal respiration (CO₂ evolution without the addition of any external substrate), microbial biomass, functional diversity, and community-level physiological profile (CLPP) in soil were measured with a MicroResp? system. Soil abiotic analysis was performed by soil standard analytical methods. The results demonstrated that bacterial distributions can be highly structured, even within a habitat that appears to be relatively homogeneous at the plot and field scale. Different subsets of the microbial community were distributed differently across the plot. This is due to spatial heterogeneity associated with soil physical, chemical, and biological properties. Although spatial variability in the distribution of soil microorganisms is generally regarded as random, this variability often has a predictable spatial structure. This study provided evidence that a spatially explicit approach to soil ecology can enable the identification of factors that drive the spatial heterogeneity of populations and activities of soil organisms, at scales ranging from meters to hundreds of meters. Furthermore, there is increasing evidence that spatial soil ecology can yield new insights into the factors that maintain and regulate soil biodiversity, as well as on how the spatial distribution of soil organisms influences plant growth and plant community structure.     

Variation of soil respiration at three spatial scales: Components within measurements, intra-site variation and patterns on the landscape

Soil respiration is an important component of terrestrial carbon cycling and can be influenced by many factors that vary spatially. This research aims to determine the extent and causes of spatial variation of soil respiration, and to quantify the importance of scale on measuring and modeling soil respiration within and among common forests of Northern Wisconsin. The potential sources of variation were examined at three scales: [1] variation among the litter, root, and bulk soil respiration components within individual 0.1 m measurement collars, [2] variation between individual soil respiration measurements within a site (<1 m to 10 m), and [3] variation on the landscape caused by topographic influence (100 m to 1000 m). Soil respiration was measured over a two-year period at 12 plots that included four forest types. Root exclusion collars were installed at a subset of the sites, and periodic removal of the litter layer allowed litter and bulk soil contributions to be estimated by subtraction. Soil respiration was also measured at fixed locations in six northern hardwood sites and two aspen sites to examine the stability of variation between individual measurements. These study sites were added to an existing data set where soil respiration was measured in a random, rotating, systematic clustering which allowed the examination of spatial variability from scales of <1 m to 100+ m. The combined data set for this area was also used to examine the influence of topography on soil respiration at scales of over 1000 m by using a temperature and moisture driven soil respiration model and a 4 km² digital elevation model (DEM) to model soil moisture. Results indicate that, although variation of soil respiration and soil moisture is greatest at scales of 100 m or more, variation from locations 1 m or less can be large (standard deviation during summer period of 1.58 and 1.28 μmol CO₂ m⁻² s⁻¹, respectively). At the smallest of scales, the individual contributions of the bulk soil, the roots, and the litter mat changed greatly throughout the season and between forest types, although the data were highly variable within any given site. For scales of 1-10 m, variation between individual measurements could be explained by positive relationships between forest floor mass, root mass, carbon and nitrogen pools, or root nitrogen concentration. Lastly, topography strongly influenced soil moisture and soil properties, and created spatial patterns of soil respiration which changed greatly during a drought event. Integrating soil fluxes over a 4 km² region using an elevation dependent soil respiration model resulted in a drought induced reduction of peak summer flux rates by 37.5%, versus a 31.3% when only plot level data was used. The trends at these important scales may help explain some inter-annual and spatial variability of the net ecosystem exchange of carbon.     

Spatial covariation of Azotobacter abundance and soil properties: A case study using the wavelet transform

The soil microflora is very heterogeneous in its spatial distribution. The origins of this heterogeneity and its significance for soil function are not well understood. A problem for understanding spatial variation better is the assumption of statistical stationarity that is made in most of the statistical methods used to assess it. These assumptions are made explicit in geostatistical methods that have been increasingly used by soil biologists in recent years. Geostatistical methods are powerful, particularly for local prediction, but they require the assumption that the variability of a property of interest is spatially uniform, which is not always plausible given what is known about the complexity of the soil microflora and the soil environment. We have used the wavelet transform, a relatively new innovation in mathematical analysis, to investigate the spatial variation of abundance of Azotobacter in the soil of a typical agricultural landscape. The wavelet transform entails no assumptions of stationarity and is well suited to the analysis of variables that show intermittent or transient features at different spatial scales.In this study, we computed cross-variograms of Azotobacter abundance with the pH, water content and loss on ignition of the soil. These revealed scale-dependent covariation in all cases. The wavelet transform also showed that the correlation of Azotobacter abundance with all three soil properties depended on spatial scale, the correlation generally increased with spatial scale and was only significantly different from zero at some scales. However, the wavelet analysis also allowed us to show how the correlation changed across the landscape. For example, at one scale Azotobacter abundance was strongly correlated with pH in part of the transect, and not with soil water content, but this was reversed elsewhere on the transect.The results show how scale-dependent variation of potentially limiting environmental factors can induce a complex spatial pattern of abundance in a soil organism. The geostatistical methods that we used here make assumptions that are not consistent with the spatial changes in the covariation of these properties that our wavelet analysis has shown. This suggests that the wavelet transform is a powerful tool for future investigation of the spatial structure and function of soil biota.     

景观生态学原理在土壤学中的应用

从研究的背景、本质及内容来看 ,现代土壤学有着鲜明的景观生态学内涵 ,研究离不开景观生态学观点的指导。土壤研究的尺度、土壤性质的时空异质性及过程的动态性决定着在大尺度上土壤学研究必须采用景观生态学的观点 ,这也是土壤学发展的一个必然趋势。土壤学汇集了众多学科的前沿研究方法 ,而景观生态学在理论上为土壤学研究拓展了更大的空间。作为学科交叉及研究动态 ,文章给出了景观生态学和土壤学研究相关联的许多热点研究动态 ,同时讨论了土地利用、土壤侵蚀、土壤面源污染等研究的景观生态学本质 ,从理论与实践上指出了景观生态学原理对土壤学研究的意义。     

Establishing a spatial grouping base for surface soil properties along urban–rural gradient—A case study in Nanjing,China

Conventional classification systems based on vegetation and land use are frequently used to characterize or describe urban soils to determine the influence of urbanization on soils. In this study, the sensitivity of different grouping methods in reflecting soil variations along an urban–rural gradient was compared. The objective of this study was to determine the most sensitive grouping system in depicting and explaining variations of soil attributes around an urban area. Grouping methods, including urban–rural division, in situ vegetation type, land use types in different scales and numerical clustering, were compared for both single soil attributes and “soil set” defined by multiple variables. The result shows urbanization has a strong impact on many soil properties, especially that of gravel content, sand content, pH, phosphorus and soil compaction. In terms of the variations of soil attributes, in situ vegetation type is the most sensitive in comparison with local land use types and district-viewed land use types. In other words, soil properties in this study are not sensitive to coarser spatial resolution. Therefore, it's hard to interpret the spatial variation of urban soil by regular methods using natural soil-landscape paradigm. Furthermore, vegetation would best proxy the delineation of single attribute of urban soils. Numerical clusters effectively reflect the land use types and their change during urbanization. All clusters were interpreted as different sets with practical meanings: soil in abandoned greenbelt, soil in ill-managed greenbelt, soil in new vegetable land, extreme urban conditioned soil, soil in well-managed greenbelt, soil in highly mellowed vegetable land, soil in common urban–peri-urban greenbelt and weak-urban-impacted soil. They can be used as bases for soil regionalization in urban and peri-urban environment.     

The millimetre-scale distribution of 2,4-D and its degraders drives the fate of 2,4-D at the soil core scale

The biodegradation of organic compounds in soil is a key process that has major implications for different ecosystem services such as soil fertility, air and water quality, and climate regulation. Due to the complexity of soil, the distributions of organic compounds and microorganisms are heterogeneous on sub-cm scales, and biodegradation is therefore partly controlled by the respective localizations of organic substrates and degraders. If they are not co-localized, transfer processes become crucial for the accessibility and availability of the substrate to degraders. This spatial interaction is still poorly understood, leading to poor predictions of organic compound dynamics in soils. The objectives of this work were to better understand how the mm-scale distribution of a model pesticide, 2,4-dichlorophenoxyacetic acid (2,4-D), and its degraders drives the fate of 2,4-D at the cm soil core scale. We constructed cm-scale soil cores combining sterilized and “natural” soil aggregates in which we controlled the initial distributions of 2,4-D and soil microorganisms with the following spatial distributions: i) a homogeneous distribution of microorganisms and 2,4-D at the core-scale, ii) a co-localized distribution of microorganisms and 2,4-D in a single spot (360 mm³) and iii) a disjoint localization of microorganisms and 2,4-D in 2 soil spots (360 mm³) separated by 2 cm. Two sets of experiments were performed: one used radiolabeled ¹⁴C-2,4-D to study the fate of 2,4-D, and the other used ¹²C-2,4-D to follow the dynamics of degraders. Microcosms were incubated at 20 °C and at field capacity (−31.6 kPa). At the core scale, we followed 2,4-D mineralization over time. On three dates, soil cores with microorganisms and 2,4-D localized in soil spots, were cut out in slices and then in 360 mm³ soil cubes. The individual soil cubes were then independently analysed for extractable and non-extractable ¹⁴C and for degraders (quantitative PCR of tfdA genes). Knowing the initial position of each soil cube allowed us to establish 3D maps of 2,4-D residues and degraders in soil. The results indicated that microorganisms and pesticide localizations in soil are major driving factors of i) pesticide biodegradation, by regulating the accessibility of 2,4-D to degrading microorganisms (by diffusion); and ii) the formation of non-extractable residues (NER). These results also emphasized the dominant role of microorganisms in the formation and localization of biogenic NER at a mm-scale. To conclude, these results demonstrate the importance of considering micro-scale processes to better understand the fate of pesticides and more generally of soil organic substrates at upper scales in soil and suggest that such spatial heterogeneity should not be neglected when predicting the fate of organic compounds in soils.     

Soil Sealing: Quantifying Impacts on Soil Functions by a Geospatial Decision Support System

Soil sealing is considered among the most dangerous of land degradation processes on global, European and national scales. Despite important policy documents aiming to mitigate this soil threat, it currently shows no signs of abating, and current efforts often do not result in appropriate implementation of soil sealing mitigation in spatial planning, which represents the subject area governing soil sealing. In this paper, we show a spatial decision support system – based on a Geospatial Cyberinfrastructure – with the aim of applying it as an operational instrument aiming towards soil sealing mitigation. The system has the ambition to impact on those who take decision over soil sealing; typically, these are not agriculture experts but rather spatial planners. This tool, focusing on mitigating such crucial land degradation, allows the users – via the Web – to produce ‘what‐if’ land planning scenarios thanks to the ‘on‐the‐fly’ modelling engines. Therefore, integrated geospatial quantitative data and procedures may be directly and freely used by planners. The tool has been applied to and tested in an area in the South of Italy. Results from two applications are reported: one addressing municipal planning and the other on a more detailed spatial scale. Furthermore, results include quantification of rural fragmentation, loss of soil ecosystem services and an estimate of soil sealing evolution over time. The tool was developed with the help of end users and indirectly explores a change of paradigm where soil science and landscape/urban planning work together to provide operational instruments that may be adopted by local communities in addressing soil sealing issues with a proactive approach. Copyright © 2017 John Wiley & Sons, Ltd.     

The spatial distribution of exoenzyme activities across the soil micro-landscape,as measured in micro- and macro-aggregates,and ecosystem processes

The spatial ecology of soil microbial communities and their functioning is an understudied aspect of soil microbial ecology. Much of our understanding of the spatial organisation of microbial communities has been obtained at scales that are inappropriate for identifying how microbial functioning and spatial patterns are related. In order to reveal the spatial strategies of soil microorganisms, we measured the microscale spatial distribution of 6 exoenzyme activities (EEA) and related them to the catalytic potential of three soils. The relationship between EEA profiles and microbial community structure was also measured in soil aggregates. All the EEA exhibited scale-invariant spatial clustering. The extent of spatial clustering varied significantly among EEA, suggesting that microbial communities employ different spatial strategies when foraging for different elements. The dispersed distribution of alkaline phosphatase suggests that microorganisms invest more heavily in the acquisition of P. The EEA associated with the C and N cycles, but not the P cycle, were significantly affected by management practices in the loamy soil. A significant negative relationship between the extent of spatial clustering of EEA and the overall intensity of the EEA was identified in the two loamy soils, indicating that the microscale spatial ecology of microbial activity may have a significant impact on biogeochemical cycles. No relationship was found between microbial community structure and EEA profiles in aggregates. However, a number of negative relationships between the relative abundance of certain taxa and the most dispersed EEA (alkaline phosphatase and β-glucosidase) were found, suggesting that these taxa make the EEA products available by means other than the production of exoenzymes (e.g. solubilisation of phosphate through the production of organic acids).     

Scale- and location-dependent correlations of soil strength and the yield of wheat

The relationship between soil strength and crop yield may be summarized by a linear correlation coefficient (usually negative). It is likely, however, that this over-simplifies a complex situation in which the relationship between these variables depends on spatial scale and location. We used the wavelet transform to assess this scale- and location-dependence. We established a transect on an arable field in Eastern England, and studied the correlations of soil strength (top- and subsoil) with crop yield. The transect comprised 267 contiguous 0.72 m × 0.72 m plots. Measurements were taken during two consecutive growing seasons of winter wheat (harvest dates of August 2004 and 2005). Soil strength was measured with a penetrometer in the spring of each growing season. As expected, the overall correlation of soil strength with yield was negative but weak. Wavelet analysis revealed that, at fine spatial scales, topsoil and subsoil strength were correlated more or less equally with yield; however, at coarse spatial scales, topsoil strength had a stronger correlation with yield than did subsoil strength. The correlation of topsoil strength with yield at fine spatial scales (corresponding to about 1 m on the ground) was negative. A likely source of this fine-scale variation was the soil compaction associated with tractor wheelings. The correlation of topsoil strength with yield at the coarsest spatial scale (corresponding to about 50 m on the ground) was positive. This correlation was temporally stable, and might have reflected how soil strength can act as a proxy for other soil attributes. In the 2005 growing season, we found evidence that, at intermediate spatial scales, the correlation of soil strength with yield changed depending on the position on the transect. This was probably due to an interaction between the compaction associated with tractor wheelings and the local soil conditions. There was no evidence of such location-dependence in the correlation of soil strength with yield in the 2004 growing season. In summary, the effect of soil strength on crop yield was not expressed in a constant negative correlation across all spatial scales and locations: the negative correlation occurred mainly at fine spatial scales, and the correlation changed according to the position in the landscape and the prevailing local soil conditions.     

对土壤侵蚀研究的几点思考

土壤侵蚀是现代地理环境条件下改变地貌景观的主要过程,也是引起土壤质量退化、沙漠化与石漠化的核心因素,与土壤、生态、水文等多个地表过程密切相关。虽然土壤侵蚀研究需要气候、地质、地貌、土壤、水文、生态等相关学科的基本知识,分析土壤侵蚀发生、发展过程的动力机制,但需要明确界定土壤侵蚀研究的时空尺度。土壤侵蚀与水土保持之间相互联系、相互促进。土壤侵蚀研究的时间尺度以次降雨、月、年为主,研究主题为次降雨侵蚀过程、土壤侵蚀季节变化与年际变化,时间尺度不宜超过100年。土壤侵蚀研究的空间尺度以小流域为主,基于土壤侵蚀垂直分带性,可以进一步分为样点、坡面、沟坡与小流域。在不同空间尺度上,研究内容与研究方法差异明显。土壤侵蚀过程包括土壤分离、泥沙输移和泥沙沉积,各个过程的主控因素存在差异,研究成果积累差异明显,研究重点会随着时空尺度的变化而有所不同。在土壤侵蚀过程研究中,应充分理解分离控制和输移控制及其时空转换阈值。虽然土壤侵蚀研究已经取得了大量成果,但在细沟网络结构及其时空变化、泥沙沉积过程、沟蚀形成与演变动力机制、重力侵蚀发育过程动力学机理、小流域土壤侵蚀过程模型等诸多方面,亟待加强研究。     

基于WebGIS的中国土壤参比查询系统研究

土壤分类是土壤科学综合研究水平的反映。本研究采用B/S系统架构,利用WebGIS以及相关的计算机技术,在中国1∶100万土壤数据库基础上,以ArcIMS作为土壤地图数据发布平台,使用ArcSDE作为空间数据库引擎,采用关系数据库SQL Server2000统一管理土壤空间数据和属性数据,建立了一个基于WebGIS的中国土壤参比查询系统,实现了GSCC到CST的“傻瓜式”参比。该系统按照参比出发点的不同,即基于单个剖面数据信息,或基于二个系统分类单元的空间分布特征,分三个子模块,分别为基于全国尺度、区域尺度(省级)和单个土体尺度,这样研究人员可以通过友好的交互性界面便捷地查询到尽可能精确的土壤分类参比数据。     

区域土壤有机碳空间分布特征与尺度效应

结合当前土壤属性空间分布特征及其尺度效应研究进展和不足,综合采用变异函数理论、空间自相关理论、多重分形理论等方法从土壤有机碳(soil organic carbon,SOC)空间变异性、相关性和结构性等不同层面深入揭示不同尺度下SOC空间分布特征及其尺度效应。研究结果表明:除了15 km尺度外,基于变异函数分析的其他尺度块基比均小于50%,结构性因素占主导,结构性因素主要包括土壤亚类、土地质地、土地类型等,随机部分带来的空间变异性随着尺度的增加呈现减少趋势;不同尺度下的莫兰指数随着分离距离的增加由完全正值逐渐变小,过渡到正负交替出现的格局,最后完全变为负值,标准化统计量均大于1.96,每个尺度均具有良好的空间结构;不论是瑞利谱图,还是多重分形谱,随着尺度的增加,图谱越来越接近,研究区不同尺度下的SOC在空间上的分布是典型的分维数体;无论何种尺度,基于多重分形克里格法的实测值与预测值特异值空间吻合程度较高,特异值覆盖比率均在85%以上。联合了变异函数、空间自相关、多重分形和多重分形克里格等方法能够从空间变异性、空间相关性、空间结构性等更加深入全面地揭示研究区SOC空间分布特征。研究成果可为相对平坦农业区域土壤有机碳空间分布特征研究提供方法支撑。     

The multi-scale spatial variance of soil moisture in the semi-arid Loess Plateau of China

Purpose  

An understanding of soil moisture heterogeneity across spatial scales has been considered to be critical to eco-hydrological research and particularly important for vegetation restoration in semi-arid areas. This study aimed to investigate the spatial variance of deep soil moisture at multiple scales in the semi-arid Loess Plateau of China. The relative importance of the related factors and the dominant driver of soil desiccation were especially discussed.     

Spatial analysis reveals differences in soil microbial community interactions between adjacent coniferous forest and clearcut ecosystems

Knowledge of how forest management influences soil microbial community interactions is necessary for complete understanding of forest ecology. In this study, soil microbial communities, vegetation characteristics and soil physical and chemical properties were examined across a rectangular 4.57 × 36.58 m sample grid spanning adjacent coniferous forest and clearcut areas. Based on analysis of soil extracted phospholipid fatty acids, total microbial biomass, fungi and Gram-negative bacteria were found to be significantly reduced in soil of the clearcut area relative to the forest. Concurrent with changes in microbial communities, soil macroaggregate stability was reduced in the clearcut area, while no significant differences in soil pH and organic matter content were found. Variography indicated that the range at which spatial autocorrelation between samples was evident (patch size) was greater for all microbial groups analyzed in the clearcut area. Overall, less spatial structure could be resolved in the forest. Variance decomposition using principal coordinates of neighbor matrices spatial variables indicated that soil aggregate stability and vegetation characteristics accounted for significant microbial community spatial variation in analyses that included the entire plot. When clearcut and forest areas were analyzed separately, different environmental variables (pH in the forest area and soil organic matter in the clearcut) were found to account for variation in soil microbial communities, but little of this variation could be ascribed to spatial interactions. Most microbial variation explained by different components of microbial communities occurred at spatial scales other than those analyzed. Fungi accounted for over 50% of the variation in bacteria of the forest area but less than 11% in the clearcut. Conversely, AMF accounted for significant variation in clearcut area, but not forest, bacteria. These results indicate broadly disparate controls on soil microbial community composition in the two systems. We present multiple lines of evidence pointing toward shifts in fungi functional groups as a salient mechanism responsible for qualitative, quantitative and spatial distribution differences in soil microbial communities.     

Combining ground penetrating radar methodologies enables large-scale mapping of soil horizon thickness and bulk density in boreal forests

Forest soil properties must be observed with the appropriate resolution by depth and landscape area to understand biogeomorphological controls on soil carbon (C). These observations, particularly in boreal forests, have been limited because of the poor resolution and unavailability of physical soil sampling results, especially for soil bulk density measurements. Ground penetrating radar (GPR) has been demonstrated to non-destructively and continuously estimate forest soil properties required in Cstock estimates, such as soil horizon thickness and soil bulk density, across small spatial scales and shallow depths. Yet, successful small-scale forest GPR approaches represent a potential opportunity to obtain soil property estimates at relevant resolution and depth across forest landscapes, enabling improvement to much needed soil mapping and stock estimates. This review discusses the existing soil property studies that utilize ground penetrating radar (GPR) and explores how the adaptation of GPR methodology can contribute to investigating soils in forest landscapes. We have identified common GPR surveying practices, data processing steps and interpretation methods employed in multiple studies. These approaches have proven effective in obtaining higher-resolution estimates of important soil properties, such as bulk density and horizon thickness, within small-scale forest plots. By applying relevant findings in this review to our own boreal forest investigation across an 80 m hillslope transect, we provide recommendations on how to tailor GPR methodology for landscape-scale estimates of soil horizon thickness and bulk density to examine forest soil property distribution. These findings should enable the future collection of soil datasets informing the distribution of soil C stocks and their relationship to landscape features, and thus their controls and responses to climate and environmental change.