Patterns Of Soil Properties Research Articles

A high spatial resolution soil carbon and nitrogen dataset for the northern permafrost region based on circumpolar land cover upscaling

Abstract. Soils in the northern high latitudes are a key component in the global carbon cycle; the northern permafrost region covers 22 % of the Northern Hemisphere land surface area and holds almost twice as much carbon as the atmosphere. Permafrost soil organic matter stocks represent an enormous long-term carbon sink which is in risk of switching to a net source in the future. Detailed knowledge about the quantity and the mechanisms controlling organic carbon storage is of utmost importance for our understanding of potential impacts of and feedbacks on climate change. Here we present a geospatial dataset of physical and chemical soil properties calculated from 651 soil pedons encompassing more than 6500 samples from 16 different study areas across the northern permafrost region. The aim of our dataset is to provide a basis to describe spatial patterns in soil properties, including quantifying carbon and nitrogen stocks. There is a particular need for spatially distributed datasets of soil properties, including vertical and horizontal distribution patterns, for modeling at local, regional, or global scales. This paper presents this dataset, describes in detail soil sampling; laboratory analysis, and derived soil geochemical parameters; calculations; and data clustering. Moreover, we use this dataset to estimate soil organic carbon and total nitrogen storage estimates in soils in the northern circumpolar permafrost region (17.9×106 km2) using the European Space Agency's (ESA's) Climate Change Initiative (CCI) global land cover dataset at 300 m pixel resolution. We estimate organic carbon and total nitrogen stocks on a circumpolar scale (excluding Tibet) for the 0–100 and 0–300 cm soil depth to be 380 and 813 Pg for carbon, and 21 and 55 Pg for nitrogen, respectively. Our organic carbon estimates agree with previous studies, with most recent estimates of 1000 Pg (−170 to +186 Pg) to 300 cm depth. Two separate datasets are freely available on the Bolin Centre Database repository (https://doi.org/10.17043/palmtag-2022-pedon-1, Palmtag et al., 2022a; and https://doi.org/10.17043/palmtag-2022-spatial-1, Palmtag et al., 2002b).

Soil science research priorities in the United States

• Understanding interactions among soil physical and biogeochemical processes that promote soil conservation and sustainability • Quantifying spatiotemporal patterns in soil properties and biogeochemical cycling • Developing resilient and sustainable management systems in response to climate change • Bridging measurement and modeling to better understand soil properties and functions

Changes of Soil Properties along the Altitudinal Gradients in Subarctic Mountain Landscapes of Putorana Plateau, Central Siberia

Changes of soil properties along elevational gradients were studied in a less accessible and explored forest-tundra ecotone in the NW part of Central Siberia. Data on soil physical and chemical properties were collected along three horizontal transects at an elevation of 100–420 m a.s.l., at two localities differing in the slope angle. At each transect, five soil pits were excavated to a depth of 0.3–0.4 m. Soil samples were taken from the depths of 0–0.1 m, 0.1–0.2 m, and 0.2–0.3 m. The results showed a pronounced effect of slope angle on the pattern of soil properties along the elevational gradient. At the locality with a gentle slope, soils exhibited 2.5 times larger thickness of the surface organic layer (SOL), higher pH, and Na+ content, and lower C, N, Ald, and Fed concentration indicating slower pedogenic processes on this site. On the other hand, at the locality with a steeper slope, soil properties were better differentiated between transects situated along elevational gradient especially at the depths of 0.1–0.2 and 0.2–0.3 m. However, a clear positive or negative trend with the altitude was observed only for some soil characteristics, e.g., SOL, C, N, or Ald concentrations on the Lama location.

Effect of land use systems and topographical attributes on the condition of surface soil physicochemical properties in a highland catchment of the Lake Victoria Basin, Uganda

Patterns of soil properties in highland environments remain poorly understood and limited knowledge exists on soil quality with respect to land use systems and topographic configurations. In this study, patterns of 12 surface soil physicochemical properties were assessed over a period of three years with respect to land use systems and toposequence positions in the Rwizi catchment of the Lake Victoria Basin. Four land use systems constituting mulched banana, unmulched banana, grassland and tree plantation, and three toposequence positions stratified as footslope, midslope and summit were considered and three replications were applied resulting in a total of 36 sites for soil properties measurements over a three-year period. Topographic attributes (elevation, slope gradient, slope aspect, and location) were collected at each site and correlated with surface soil properties. With the exception of pH and Ca, surface soil physicochemical properties are revealed to be optimal in the catchment. Greater spatial variation was found with soil chemical properties (8–57%) compared to physical properties (7–19%). Land use system registered significant effects (p < 0.05) for all soil chemical properties, as well as bulk density. Toposequence position is shown to have significant (p < 0.05) effects on soil pH, Soil Organic Matter, available P, N and soil texture. The effect of toposequence position revealed better soil quality along the catenary sequence summit > footslope > midslope. Strong and significant regression coefficients (r2 > 0.6, p < 0.05) for topographic attributes were found with soil pH, available P, K, Ca, Mg and sand. Overall, the land use system effect supersedes toposequence position in accounting for variations in surface soil physicochemical properties. Although environments of the Lake Victoria Basin are subject to intense agricultural activity and are usually assumed to be degraded, surface soil physicochemical properties in this part of the catchment reflect relatively healthy soil quality conditions.

Agroecosystem patterns and land management co‐develop through environment, management, and land‐use interactions

AbstractA poor understanding of the interactions between biophysical and social elements within rural mountainous landscapes can lead to suboptimal management and recommendations. The objective of this study was to contribute to more contextualized natural resource management in a rural landscape in the Ecuadorian Andes by (1) identifying biophysical patterns in soil properties, biodiversity, and C stocks that emerge from natural landscape pedogenic processes, resulting from elevation‐induced climate gradients, erosion and soil textural patterns, and (2) assessing farm management and land‐use effects on and their interactions with these biophysical patterns. Our findings revealed that the climate and soil texture gradients within the landscape led to an exponential increase in SOC with elevation moderated by slope gradient, indicating significant erosion processes. Farmers adapted their farm management according to the observed environmental patterns creating three distinct management zones. Differentiated agricultural management in these zones and asymmetrical distribution of land‐uses in turn were observed to significantly influence soil and agroecosystem properties. For example, available P was found to be significantly higher in the upper and middle agricultural management zones (24.0 and 28.7 mg/kg, respectively), where agricultural inputs were higher compared to the lower agricultural management zone (8.9 mg/kg, P &lt; 0.001). Mixed hedgerows, on the other hand, displayed significantly higher Shannon index scores for ground vegetation (1.8) and soil macrofauna (2.0) compared to agricultural land‐uses (1.0 and 1.7). Our results provide important insights into how agroecosystem patterns and land management co‐developed through complex environment, management, and land‐use interactions.

Simulation of spatial variability in crop leaf area index and yield using agroecosystem modeling and geophysics‐based quantitative soil information

AbstractAgroecosystem models that simulate crop growth as a function of weather conditions and soil characteristics are among the most promising tools for improving crop yield and achieving more sustainable agricultural production systems. This study aims at using spatially distributed crop growth simulations to investigate how field‐scale patterns in soil properties obtained using geophysical mapping affect the spatial variability of soil water content dynamics and growth of crops at the square kilometer scale. For this, a geophysics‐based soil map was intersected with land use information. Soil hydraulic parameters were calculated using pedotransfer functions. Simulations of soil water content dynamics performed with the agroecosystem model AgroC were compared with soil water content measured at two locations, resulting in RMSE of 0.032 and of 0.056 cm3 cm−3, respectively. The AgroC model was then used to simulate the growth of sugar beet (Beta vulgaris L.), silage maize (Zea mays L.), potato (Solanum tuberosum L.), winter wheat (Triticum aestivum L.), winter barley (Hordeum vulgare L.), and winter rapeseed (Brassica napus L.) in the 1‐ by 1‐km study area. It was found that the simulated leaf area index (LAI) was affected by the magnitude of simulated water stress, which was a function of both the crop type and soil characteristics. Simulated LAI was generally consistent with the observed LAI calculated from normalized difference vegetation index (LAINDVI) obtained from RapidEye satellite data. Finally, maps of simulated agricultural yield were produced for four crops, and it was found that simulated yield matched well with actual harvest data and literature values. Therefore, it was concluded that the information obtained from geophysics‐based soil mapping was valuable for practical agricultural applications.

Mesoscale Soil Moisture Patterns Revealed Using a Sparse In Situ Network and Regression Kriging

AbstractSoil moisture spatial patterns with length scales of 1‐100 km influence hydrological, ecological, and agricultural processes, but the footprint or support volume of existing monitoring systems, for example, satellite‐based radiometers and sparse in situ monitoring networks, is often either too large or too small to effectively observe these mesoscale patterns. This measurement scale gap hinders our understanding of soil water processes and complicates calibration and validation of hydrologic models and soil moisture satellites. One possible solution is to utilize geostatistical techniques that have proven effective for mapping static patterns in soil properties. The objective of this study was to determine how effectively dynamic, mesoscale soil moisture patterns can be mapped by applying regression kriging to the data from a sparse, large‐scale in situ network. The fully automated system developed here uses several data sets: daily soil moisture measurements from the Oklahoma Mesonet, sand content estimates from the Natural Resource Conservation Service Soil Survey Geographic Database, and an antecedent precipitation index computed from National Weather Service multisensor precipitation estimates. A multiple linear regression model is fitted daily to the observed data, and the residuals of that model are used in a semivariogram estimation and kriging routine to produce daily statewide maps of soil moisture at 5‐, 25‐, and 60‐cm depths at 800‐m resolution. During over 3 years of operation, this mapping system has revealed complex, dynamic, and depth‐specific mesoscale patterns, reflecting the shifting influences of both soil texture and precipitation, with a mean absolute error of ≤0.0576 cm3/cm3 across all three depths.

Estimating the field capacity and permanent wilting point at the regional scale for the Hexi Corridor in China using a state-space modeling approach

The field capacity (FC) and permanent wilting point (PWP) are important soil hydraulic properties that determine the maximum available water for plants, and they are crucial parameters for biophysical models and irrigation management. However, previous estimates of the FC and PWP failed to consider their spatial correlations at the regional scale. Therefore, we estimated the FC and PWP using the state-space equation by considering the spatial correlations between soil properties. We estimated the FC and PWP using a first order autoregressive state-space equation based on the elevation (Elev), bulk density (BD), soil texture (Clay, Silt, Sand), soil organic carbon (SOC), and land use (LU) with a data set obtained from 104 in situ sampling sites across the entire Hexi Corridor. The results indicated that the distributions of the FC and PWP exhibited moderate variations in the Hexi Corridor, with values of 0.127 ± 0.060 and 0.075 ± 0.034 g/g (mean ± 1 standard deviation (SD)), respectively. According to t tests, the autocorrelation coefficients for FC, PWP, Elev, LU, Silt, Sand, and SOC as well as the cross-correlation coefficients between FC, PWP, and pertinent variables were significant with one lag distance (approximately 40 km) (p ˂ 0.05). Calculations of the coefficient of determination (R2) and root mean square error (RMSE) showed that the state-space models performed better at estimating FC and PWP than multiple linear stepwise regression models (SMLRs). Bivariate state-space equations based on Silt and LU were the optimal models for estimating FC (R2 = 0.999, RMSE = 0.002 g/g) and PWP (R2 = 0.997, RMSE = 0.002 g/g). According to the coefficients in the optimal state-space models, soil texture and LU were the dominant factors that affected the spatial variability in FC and PWP. After neglecting the spatial correlations between variables, the SMLRs showed that BD and soil texture were the best variables for estimating FC and PWP. The state-space approach is recommended as a useful tool for quantifying larger-scale spatial patterns in soil properties.

Quantifying relations between surface runoff and aridity after wildfire

AbstractPost‐wildfire runoff and erosion are major concerns in fire‐prone landscapes around the world, but these hydro‐geomorphic responses have been found to be highly variable and difficult to predict. Some variations have been observed to be associated with landscape aridity, which in turn can influence soil hydraulic properties. However, to date there has been no attempt to systematically evaluate the apparent relations between aridity and post‐wildfire runoff. In this study, five sites in a wildfire burnt area were instrumented with rainfall‐runoff plots across an aridity index (AI) gradient. Surface runoff and effective rainfall were measured over 10 months to allow investigation of short‐ (peak runoff) and longer‐term (runoff ratio) runoff characteristics over the recovery period. The results show a systematic and strong relation between aridity and post‐wildfire runoff. The average runoff ratio at the driest AI site (33.6%) was two orders of magnitude higher than at the wettest AI site (0.3%). Peak runoff also increased with AI, with up to a thousand‐fold difference observed during one event between the driest and wettest sites. The relation between AI, peak 15‐min runoff (Q15) and peak 15‐min rainfall intensity (I15) (both in mm h‐1) could be quantified by the equation: Q15 = 0.1086I15 × AI 2.691 (0.65&lt;AI&lt;1.80, 0&lt;I15&lt;45) (adjusted r2 = 0.84). The runoff ratios remained higher at drier AI sites (AI 1.24 and 1.80) throughout the monitoring period, suggesting higher AI also lengthens the window of disturbance after wildfire. The strong quantifiable link which this study has determined between AI and post‐wildfire surface runoff could greatly improve our capacity to predict the magnitude and location of hydro‐geomorphic processes such as flash floods and debris flows following wildfire, and may help explain aridity‐related patterns of soil properties in complex upland landscapes. Copyright © 2018 John Wiley &amp; Sons, Ltd.

Topographic and Geologic Controls on Soil Variability in California's Sierra Nevada Foothill Region

Author(s): Beaudette, DE; O'Geen, AT | Abstract: We evaluated the feasibility of quantitative soil mapping in two catenas established on different lithologies (metavolcanic and granitic) in the Sierra Foothill Region of California. Indices of landform and microclimate were extracted from a 1-m elevation model. Variation in soil character (clay content, pH, color, cation-exchange capacity [CEC], and Feo/Fed) was partitioned across variables associated with terrain shape and microclimate, lithologic variability, and sampling depth. The potential for using digital elevation models (DEM)-derived indices of terrain shape to predict spatial patterns in soil properties varied greatly between our two experimental catenas. Terrain shape accounted for 4% (metavolcanic site) to 30% (granitic site) of variance in soil properties, while lithology accounted for 14% (metavolcanic site) to 22% (granitic site) of variance in soil properties. Sample depth accounted for 3% (metavolcanic site) to 12% (granitic site) of variance in soil properties. At the metavolcanic site, variability in lithology contributed more to soil variation than terrain shape, which makes digital soil modeling efforts a challenge in these regions. Up to 66% of the variance in soil properties was explained at the granitic site when considering terrain, lithology, sample depth, and associated interactions of these variables. Variance proportions can provide insight into the relative importance of soil-forming factors and is a useful tool when evaluating the efficacy of digital soil mapping projects.

Solar radiation as a global driver of hillslope asymmetry: Insights from an ecogeomorphic landscape evolution model

AbstractObservations at the field, catchment, and continental scales across a range of arid and semiarid climates and latitudes reveal aspect‐controlled patterns in soil properties, vegetation types, ecohydrologic fluxes, and hillslope morphology. Although the global distribution of solar radiation on earth's surface and its implications on vegetation dynamics are well documented, we know little about how variation of solar radiation across latitudes influence landscape evolution and resulting geomorphic difference. Here, we used a landscape evolution model that couples the continuity equations for water, sediment, and aboveground vegetation biomass at each model element in order to explore the controls of latitude and mean annual precipitation (MAP) on the development of hillslope asymmetry (HA). In our model, asymmetric hillslopes emerged from the competition between soil creep and vegetation‐modulated fluvial transport, driven by spatial distribution of solar radiation. Latitude was a primary driver of HA because of its effects on the global distribution of solar radiation. In the Northern Hemisphere, north‐facing slopes (NFS), which support more vegetation cover and have lower transport efficiency, get steeper toward the North Pole while south‐facing slopes (SFS) get gentler. In the Southern Hemisphere, the patterns are reversed and SFS get steeper toward the South Pole. For any given latitude, MAP is found to have minor control on HA. Our results underscore the potential influence of solar radiation as a global control on the development of asymmetric hillslopes in fluvial landscapes.

Small-scale spatial heterogeneity of soil properties in undisturbed and reclaimed sagebrush steppe

The sagebrush (Artemisia tridentata) steppe is inherently heterogeneous, both above- and belowground disturbances that manipulate vegetation and soil may result in homogenization of soil properties. Our objective was to examine the spatial distributions of soil properties in a sagebrush steppe of south-central Wyoming following disturbance and reclamation. We predicted that soil properties in undisturbed sagebrush steppe would display patchiness, while reclaimed soils would be more uniform. At the experimental scale (<10m2), we examined the spatial correlation structure and patterns of soil properties in a recently disturbed and reclaimed pipeline scar and adjacent undisturbed sagebrush steppe in 2009. In each treatment, we sampled soil (0–0.05m depth, calcareous fine sand Regosol) using a spatially explicit design, and used geostatistics to quantify, interpolate, and visualize spatial patterns of soil chemical and biological properties. Soil nitrogen and organic carbon in the undisturbed plot showed spatial associations with the vegetation, which were not apparent in the reclaimed plot. Our predictions about homogenization were true for soil properties that are known to have strong spatial associations with shrubs. Soil organic carbon concentration, total nitrogen concentration, and microbial abundance experienced homogenization, while soil salinity and alkalinity became patchier after disturbance. In addition to changes in spatial patterns, most soil properties were elevated in the reclaimed soil, compared with the undisturbed soil. This case study illustrates that the degree of soil heterogeneity in this patchy system may change with disturbance. Belowground spatial patterns should be considered when restoring characteristically heterogeneous shrub lands.

Derivation of terrain covariates for digital soil mapping in Australia

Digital soil mapping is founded on the availability of covariates that are used as surrogates for the spatial patterns in soil properties. One important subset of covariates represents the patterns due to terrain, and these are typically derived from a digital elevation model at a suitable resolution. When each digital soil mapping exercise requires the calculation of terrain covariates, there is a clear potential for inconsistent methods and for choosing the covariates that are easiest to derive rather than those that are most relevant. The creation of open repositories of relevant terrain covariates that are correctly derived avoids these problems and fosters the application of digital soil mapping and other modelling activities that benefit from landscape properties. This paper describes the creation of a suite of commonly used terrain covariates from the 1-arcsecond (~30 m) resolution digital elevation models for Australia that were released through CSIRO’s Data Access Portal and the TERN Data Discovery Portal. The methods used to derive the terrain covariates are described and their characteristics are identified.

Denitrifier community size, structure and activity along a gradient of pasture to riparian soils

Forested riparian zones may protect waterways from receiving excess N from adjacent agricultural lands by immobilizing N in plants or microbes, or through denitrification. If denitrified, excess N is emitted either as harmful nitrous oxide or benign N2 gas. Therefore the size, structure and activity of the denitrifying community may play important roles in determining the net effect of riparian zones on the overall environmental impact of excess agricultural N. We assessed the size and structure of prokaryotic denitrifying communities, measured soil physiochemical characteristics and estimated denitrification along a gradient of grazed dairy pasture to forested riparian zone buffering the Manawatu River in New Zealand. We assessed denitrifier community structure by T-RFLP of the nirS and nosZ genes. We assessed denitrifier community size by quantitative PCR (qPCR) of these genes and total bacterial numbers by qPCR of the ribosomal polymerase (rpoB) gene. Strong gradients in microbial biomass, gene abundances and potential denitrification were primarily driven by differences in soil texture between pasture and riparian zones, with smaller scale patterns in soil properties emerging among slope positions with each zone. We found that nirS and nosZ communities responded strongly, though sometimes independently, to these gradients. nosZ abundance and community structure were significantly correlated to large scale patterns edaphic characters that distinguished pasture and riparian zone soils, but were not significantly correlated to denitrifier activity. By contrast, nirS abundance responded in a unimodal fashion to soil texture, leading to strong patterns of abundance and community structure associated with the different slope positions. Furthermore, nirS community structure was significantly correlated to denitrification rates and end-products. Finally, we found that the evenness of denitrifying communities was uncorrelated denitrification parameters and was negatively correlated to the proportional abundance of denitrifiers. Taken together, our data suggest that small numbers of genotypes become dominant and drive higher rates of denitrification in favourable ‘hotspots’ in the toe-slopes of pastures. Conversely, the low overall community evenness and low proportional abundance of complete denitrifiers in the riparian zone soils suggested a limited capacity for riparian buffers to remove excess N through denitrification and a propensity for incomplete denitrification to lead to N2O emissions. These results contribute to our understanding of the role of riparian zones determining the fate of excess agricultural N and highlight the importance of careful N management especially in pastures that occur on coarse textured soils.

Short-Term Medieval Settlement Activities Irreversibly Changed Forest Soils and Vegetation in Central Europe

In Europe, many contemporary forests are not continuous, but were established on former agricultural land in territories of deserted villages. We aimed to explore whether medieval settlement activities of only 60 years irreversibly changed soil properties and whether these changes were reflected by contemporary forest vegetation. The research was performed in the deserted village of Kři, which existed from 1357 to ca 1420 AD in a current oak forest on sandy soils in the Czech Republic. We identified four former land-use types (building sites, courtyards, the village square, and gardens), where we analyzed soil properties and plant species composition of the forest understory. Higher concentrations of plant-available P, K, Ca, and Mg as well as the total concentrations of organic C and trace elements (As, Cd, Cu, and Zn) were recorded at former building sites with neutral soils, compared to the other former land-use types with acidic soils. The four-times higher species richness at former building sites compared to the former gardens indicate the strong effect of soil pH and nutrient availability on plant species composition, even on the spatial scale of several square metres. Understanding recent patterns in soil properties and biodiversity in Central European forests requires detailed knowledge of former land use over centuries. Analysis of contemporary soil properties together with analysis of vegetation can help to identify former land-use types in deserted villages.

Hierarchical analysis of vegetation dynamics over 71 years: soil–rainfall interactions in a Chihuahuan Desert ecosystem

Proliferation of woody plants in grasslands and savannas is a persistent problem globally. This widely observed shift from grass to shrub dominance in rangelands worldwide has been heterogeneous in space and time largely due to cross-scale interactions among soils, climate, and land-use history. Our objective was to use a hierarchical framework to evaluate the relationship between spatial patterns in soil properties and long-term shrub dynamics in the northern Chihuahuan Desert of New Mexico, USA. To meet this objective, shrub patch dynamics from 1937 to 2008 were characterized at patch and landscape scales using historical imagery and a recent digital soils map. Effects of annual precipitation on patch dynamics on two soils revealed strong correlations between shrub growth on deep sandy soils and above-average rainfall years (r = 0.671, P = 0.034) and shrub colonization and below-average rainfall years on shallow sandy soils (r = 0.705, P = 0.023). Patch-level analysis of demographic patterns revealed significant differences between shrub patches on deep and shallow sandy soils during periods of above- and below-average rainfall. Both deep and shallow sandy soils exhibited low shrub cover in 1937 (1.0% +/- 2.3% and 0.3% +/- 1.3%, respectively [mean +/- SD]) and were characterized by colonization or appearance of new patches until 1960. However, different demographic responses to the cessation of severe drought on the two soils and increased frequency of wet years after 1960 have resulted in very different endpoints. In 2008 a shrubland occupied the deep sandy soils with cover at 19.8% +/- 9.1%, while a shrub-dominated grassland occurred on the shallow sandy soils with cover at 9.3% +/- 7.2%. Present-day shrub vegetation constitutes a shifting mosaic marked by the coexistence of patches at different stages of development. Management implications of this long-term multi-scale assessment of vegetation dynamics support the notion that soil properties may constrain grassland remediation. Such efforts on sandy soils should be focused on sites characterized by near-surface water-holding capacity, as those lacking available water-holding capacity in the shallow root zone pose challenges to grass recovery and survival.

Gradient analysis reveals a copper paradox on floodplain soils under long-term pollution by mining waste

Arable alluvial soils are a globally important resource under increasing pressure from both industrial pollution and intensified agricultural land use. Quality of agricultural soils is ultimately defined by crop yields; it is however seldom feasible to study the consequences of complex soil pollution on crops under field conditions. This work analyses the long term effects of two gradients: spatial (relative distance from the water channel) and land use intensity (cropping frequency) on soil properties and model crop (barley) response. On an exceptional model locality in Eastern Serbia, degraded by fluvial deposition of sulphidic copper tailings during 50years, multivariate analysis shows that land use accelerates the substitution of high plant available Cu by nutrient deficiency (primarily P and microelements) and excessive exchangeable Al. Though agronomic soil quality might not differ along the land use gradient, the environmental consequences do drastically change. The observed apparent “paradoxes” (e.g. soil Cu decreases towards the pollution source; higher yields might coincide with higher soil and leaf Cu concentrations; and leaching of Cu does not restore soils agronomic quality) can be explained by a) the Cu retention patterns along the transects, b) importance of higher SOM and nutrient availability for modifications of Cu toxicity, and c) the existence of plant adaptation mechanisms which can considerably counteract the adverse soil conditions. Land use-induced nutrient deficiency can counteract the positive effects of decreased Cu levels. In a long run, accelerated Cu mobilisation is likely to increase vulnerability of these soils to further environmental hazards. This study demonstrates the clear and consistent patterns in soil properties and plant response along the gradients and points out the probable long-term environmental trends in a “would be” scenario for agricultural use of similar polluted soils.

Grassland community composition drives small-scale spatial patterns in soil properties and processes

The presence and activity of individual plants can affect soil resource availability and microbial processes, and can influence the spatial scale over which soil properties vary. While soils have been found to differ under plants of differing growth form (i.e. grasses vs. trees), few studies have focused on small-scale soil differences under comparably-sized species. Here we investigate how two types of C-3 grasses influence patterns in soil properties and processes at scales of less than one meter in a California grassland. To understand how native perennial grasses differ from invasive annual grasses in their effects on soils, we used cross-semivariogram analysis to quantify the degree and scale of spatial heterogeneity in soil properties and processes in experimentally-seeded grasslands. We then used mapping techniques to correlate spatial patterns of soil properties and processes with the cover of annual and perennial grasses aboveground. We found that many soil properties and processes belowground were spatially-correlated with the aboveground presence of annuals or perennials. Soil moisture became more heterogeneous with increasing amounts of perennial cover, suggesting that perennial bunchgrass individuals take up more water and produce zones of resource depletion in comparison with soils directly under annual grasses. The association of belowground resources and activity with the two types of grass suggests that the historical shift from perennial to annual dominance in California grasslands led to changes in the small-scale spatial structure of soil properties and processes in these systems. These changes may alter ecosystem function and could potentially perpetuate invasive annual grass dominance.

Apparent Electrical Conductivity in Correspondence to Soil Chemical Properties and Plant Nutrients in Soil

Spatial variability and relationship between soil apparent electrical conductivity (ECa), soil chemical properties, and plant nutrients in soil have not been well documented in Malaysian paddy fields. For this reason precision farming has been used for assessing field conditions. ECa technique for describing soil spatial variability is used for soil data acquisition. Soil sampling provides the data used to make maps of the spatial patterns in soil properties. Maps are then used to make recommendations on the variation of application rates. The main purpose of the authors in this study was to generate variability map of soil ECa within a Malaysian rice cultivation area using VerisEC sensor. The ECa values were compared to some soil properties after delineation. Measured parameters were mapped using kriging technique and their correlation with soil ECa was determined. Through this study the authors showed that the EC sensor can determine soil spatial variability, where it can acquire the soil information quickly.

Litterfall and associated nutrient pools extend beyond the canopy of scattered eucalypt trees in temperate pastures

Scattered paddock trees are a keystone feature of temperate grazing landscapes of Australia. However, our understanding of their influence on their immediate environment, and specifically the spatial distribution and characteristics of litter, is still limited. Here, we quantified the spatial pattern of litter around 4 Eucalyptus species (Eucalyptus melliodora A. Cunn. Ex Schauer, E. viminalis Labill., E. blakelyi Maiden and E. michaeliana Blakely) in grazing landscapes on the Northern Tablelands of NSW, Australia. We examined the effect of species and soil parent material (basalt, granite and meta-sediments) on litter chemistry and chemical pools. Between 54–145 kg of litter was found around individual trees and litter density consistently declined with distance from the tree (330 g.m−2 in the inner canopy to 4 g.m−2 in the open paddock). However, an equivalent quantity of litter was found beneath and beyond the canopy indicating that a large quantity of the litter and nutrients fell beyond the edge of the canopy. Overall, leaf litter accounted for 23 to 34% of litterfall and had larger nutrient concentrations and pools than bark or stick litter. Most litter nutrients concentrations were independent of tree species or parent material but our results suggest that P, K and S were removed in foliage prior to abscission whilst Ca and Fe concentrations increased. The spatial patterns of litter distribution around scattered trees coincide with spatial patterns in soil properties that are frequently observed in these environments, and provide strong evidence of a significant link between these factors. Our results suggest that the removal of scattered trees from pastoral landscapes in this region of Australia will result in the loss of a significant litter input to the soil surface and will diminish this potentially important source of soil nutrients.