Earthworms Modulate Impacts of Soil Heterogeneity on Plant Growth at Different Spatial Scales

Soil heterogeneity (uneven distribution of soil nutrients and/or other properties) is ubiquitous in nature and can greatly affect plant growth. As earthworm activity can influence nutrient redistribution in the soil, we hypothesize that earthworms may alter the effect of soil heterogeneity on plant growth and this effect may depend on the scale of soil heterogeneity. To test these hypotheses, we grew the clonal grass Leymus chinensis in three soil treatments (heterogeneous large vs. heterogeneous small patch vs. homogeneous soil treatment) with or without earthworms [i.e., Eisenia fetida Savigny (Lumbricidae, epigeic redworm)]. In the heterogeneous treatments, the soil consisted of patches with and without 15N-labeled litter (referred to as high- and low-quality patches, respectively), and in the homogeneous treatment, the soil was an even mixture of the two types of soil patches. Biomass of L. chinensis was significantly higher in the high- than in the low-quality patches, showing the foraging response; this foraging response occurred at both scales and under both earthworm treatments. Compared to the homogeneous treatment, the heterogeneous large patch treatment increased biomass of L. chinensis without earthworms, but decreased it with earthworms. In contrast, biomass of L. chinensis in the heterogeneous small patch treatment did not differ from that in the homogeneous treatment, irrespective of earthworms. Belowground biomass was much greater in the heterogeneous small than in the heterogeneous large patch treatment without earthworms, but it did not differ between these two scale treatments with earthworms. In the heterogeneous treatments, soil 15N was greater in the high- than in the low-quality patches, but this effect became much weaker with than without earthworms, suggesting that earthworm activity homogenized the soil. We conclude that earthworms can change the impact of soil heterogeneity on plant growth via homogenizing the soil, and that this effect of earthworms varies with patch scale. Such scale-dependent interactive effects of soil heterogeneity and earthworms could be a potential mechanism modulating plant community structure and productivity.

Impact of in-field soil heterogeneity on biomass and yield of winter triticale in an intensively cropped hummocky landscape under temperate climate conditions

Crop cultivation provides ecosystem services on increasingly large fields. However, the effects of in-field spatial heterogeneity on crop yields, in particular triticale, have rarely been considered. The study assess the effects of in-field soil heterogeneity and elevation on triticale grown in an intensively cropped hummocky landscape. The field was classified into three soil classes: C1, C2, and C3, based on soil texture and available water capacity (AWC), which had high, moderate, and low yield potential, respectively. Three elevations (downslope (DS), midslope (MS), and upslope (US)) were considered as the second study factor. An unbalanced experimental design was adopted with a factorial analysis of variance for data analysis. Temporal growth analysis showed that soil classes and elevation had significant effects. Generally, better growth was observed in C1 compared to that of C3. DS had a lower yield potential than that of MS and US. In addition, the interactive effect was confirmed, as triticale had poor growth and yield in C3 on the DS, but not on US. Crop physiological parameters also confirmed the differences between soil classes and elevation. Similarly, soil moisture (SM) content in the plow layer measured at different points in time and AWC over the soil profile had a positive association with growth and yield. The results confirmed that spatial differences in AWC and SM can explain spatial variability in growth and yield. The mapping approach combining soil auguring techniques with a digital elevation model could be used to subdivide fields in hummocky landscapes for determining sub-field input intensities to guide precision farming.

Optimum size and shape of plots based on data from a uniformity trial on Indian Mustard in Haryana

The most obvious use of uniformity trial data is to provide information on the most suitable size and shape of plots, in which the field was planted to a single variety and harvested as small plots. Indian mustard (Brassica juncea L.) cultivar RH-749 was grown using uniform crop improvement practices during rabi season of 2013-14 at Research Farm of Oilseed section, Department of Genetics and Plant Breeding, CCSHAU, Hisar, Haryana state, India, to estimate optimum plot size and shape using yield data of the 48 m × 48 m (2304 basic units) recorded separately from each basic unit of 1 m × 1 m. The variability among plots of different sizes and shapes was determined by calculating coefficient of variation. It was observed that the coefficient of variation decreases as the plot size increases in case of both the directions i.e., when plots were elongated in N-S direction (88 per cent decrease) or elongated in E-W direction (93 per cent decrease). Further it was observed that long and narrow plots elongated in E-W direction were more useful than the compact and square plots in controlling the soil heterogeneity. Based on the maximum curvature method the optimum plot size for yield trial was estimated to be 5 m2 with rectangular shape.

2D Geotechnical site-response analysis including soil heterogeneity and wave scattering

This study describes an approach for modeling wave scattering and the spatial variability of ground motion in geotechnical site-response analysis by modeling soil heterogeneity through 2D correlated random fields. Importantly, the required site-specific inputs to apply the proposed approach in a practical setting are the same as those associated with conventional 1D site-response analysis. The results, which are affected by wave scattering attenuation, are compared to those from conventional laterally homogeneous 1D site-response analyses and 1D analyses with randomized velocity profiles extracted from heterogeneous 2D velocity model realizations. A sensitivity study, involving 5400 2D model realizations, investigates the influence of random field input parameters on wave scattering and site response. The computed ground surface acceleration waveforms and transfer functions show that this method is capable of scattering seismic waves. Multiple ground-motion intensity measures are analyzed to quantify this influence and distinguish between the effects of 1D vertical heterogeneities and averaging across many nodes and realizations, from the effects of wave scattering and 2D ground-motion phenomena. The redistribution of ground-motion energy across wider frequency bands and scattering attenuation of high-frequency waves in the 2D analyses resemble features observed in empirical transfer functions computed in other studies. While analyses with 1D randomized velocity profiles are able to replicate median results from 2D analyses for some low-frequency intensity measures (e.g. transfer functions at [Formula: see text] Hz, and spectral acceleration at the fundamental period), medians and standard deviations of high-frequency intensity measures (e.g. transfer function at [Formula: see text] Hz, [Formula: see text], and Arias intensity), which are influenced by wave scattering, are not appropriately captured. Given the equivalent input information requirements as conventional 1D analysis, and the availability of large computational resources, we advocate that the proposed 2D (and eventually 3D) approach is a fruitful path forward to improve the modeling of site-response physics and realize improved predictive capabilities.

Root-associated fungal community reflects host spatial co-occurrence patterns in a subtropical forest

Plant roots harbor and interact with diverse fungal species. By changing these belowground fungal communities, focal plants can affect the performance of surrounding individuals and the outcome of coexistence. Although highly host related, the roles of these root-associated fungal communities per se in host plant spatial co-occurrence is largely unknown. Here, we evaluated the host dependency of root-associated communities for 39-plant species spatially mapped throughout a 50-ha subtropical forest plot with relevant environmental properties. In addition, we explored whether the differentiation in root fungal associations among plant species can reflect their observed co-occurrence patterns. We demonstrated a strong host-dependency by discriminating the differentiation of root-associated fungal communities regardless of background soil heterogeneity. Furthermore, Random Forest modeling indicated that these nonrandom root fungal associations significantly increased our ability to explain spatial co-occurrence patterns, and to a greater degree than the relative abundance, phylogenetic relatedness, and functional traits of the host plants. Our results further suggested that plants harbor more abundant shared, “generalist” pathogens are likely segregated, while hosting more abundant unique, “specialist” ectomycorrhizal fungi might be an important strategy for promoting spatial aggregation, particularly between early established trees and the heterospecific adults. Together, we provide a conceptual and testable approach to integrate this host-dependent root fungal “fingerprinting” into the plant diversity patterns. We highlight that this approach is complementary to the classic cultivation-based scheme and can deepen our understanding of the community-level effect from overall fungi and its contribution to the pairwise plant dynamics in local species-rich communities.

Effects of soil heterogeneity on susceptibility of shallow landslides

Uncertainties in parameters of landslide susceptibility models often hinder them from providing accurate spatial and temporal predictions of landslide occurrences. Substantial contribution to the uncertainties in landslide assessment originates from spatially variable geotechnical and hydrological parameters. These input parameters may often vary significantly through space, even within the same geological deposit, and there is a need to quantify the effects of the uncertainties in these parameters. This study addresses this issue with a new three-dimensional probabilistic landslide susceptibility model. The spatial variability of the model parameters is modeled with the random field approach and coupled with the Monte Carlo method to propagate uncertainties from the model parameters to landslide predictions (i.e., factor of safety). The resulting uncertainties in landslide predictions allow the effects of spatial variability in the input parameters to be quantified. The performance of the proposed model in capturing the effect of spatial variability and predicting landslide occurrence has been compared with a conventional physical-based landslide susceptibility model that does not account for three-dimensional effects on slope stability. The results indicate that the proposed model has better performance in landslide prediction with higher accuracy and precision than the conventional model. The novelty of this study is illustrating the effects of the soil heterogeneity on the susceptibility of shallow landslides, which was made possible by the development of a three-dimensional slope stability model that was coupled with random field model and the Monte Carlo method.

District-scale numerical analysis of settlements related to ground water lowering in variable soil conditions

This study presents a novel framework in which numerical modelling contributes to the performance of district-scale subsidence-induced damage assessment in cities where ground settlements affect entire quarters. Therein, the implementation of expeditious procedures offers geotechnical engineers the possibility of contributing beyond the typical site scale. For this purpose, several “typified” hydro-geomechanical-loading (HGL) models, which represent (simplified) scenarios of masonry buildings undergoing settlements, were set up to account for different predisposing/triggering factors (i.e. soil heterogeneity, loading conditions, and groundwater variations) of settlement occurrence in built-up areas. These models exploit multi-source wide-area input datasets encompassing the hydro-mechanical properties of geomaterials, in situ investigations and measurements (e.g. groundwater levels in wells), and innovative remote sensing data (i.e. DInSAR techniques). With reference to a district in Rotterdam City (the Netherlands), which was built on “soft soils”, the numerical simulations of different scenarios i) provide an overview of the comparative role of predisposing/triggering factors on settlement occurrence and ii) allow assessments of the expected induced damage to masonry buildings over thirty years with the exploitation of fragility curves. Considering the widespread diffusion of such geohazards, the proposed approach could help prioritise (rather expensive) maintenance work to the built heritage within sustainable strategies for subsidence risk mitigation.

Redox Heterogeneity Entangles Soil and Climate Interactions

Interactions between soils and climate impact wider environmental sustainability. Soil heterogeneity intricately regulates these interactions over short spatiotemporal scales and therefore needs to be more finely examined. This paper examines how redox heterogeneity at the level of minerals, microbial cells, organic matter, and the rhizosphere entangles biogeochemical cycles in soil with climate change. Redox heterogeneity is used to develop a conceptual framework that encompasses soil microsites (anaerobic and aerobic) and cryptic biogeochemical cycling, helping to explain poorly understood processes such as methanogenesis in oxygenated soils. This framework is further shown to disentangle global carbon (C) and nitrogen (N) pathways that include CO2, CH4, and N2O. Climate-driven redox perturbations are discussed using wetlands and tropical forests as model systems. Powerful analytical methods are proposed to be combined and used more extensively to study coupled abiotic and biotic reactions that are affected by redox heterogeneity. A core view is that emerging and future research will benefit substantially from developing multifaceted analyses of redox heterogeneity over short spatiotemporal scales in soil. Taking a leap in our understanding of soil and climate interactions and their evolving influence on environmental sustainability then depends on greater collaborative efforts to comprehensively investigate redox heterogeneity spanning the domain of microscopic soil interfaces.