Intact Soil Profiles Research Articles

Evolution of paddy soil fertility in a millennium chronosequence based on imaging spectroscopy

It is essential for future security and soil sustainability to understand how soil fertility evolves under long-term anthropogenic influences. This study investigated the feasibility of laboratory-based imaging spectroscopy (IS) techniques to predict fertility properties (soil organic matter (SOM), total nitrogen (TN), total phosphorus (TP), total potassium (TK), pH) of soil profiles at different ages of rice planting. Three methods, support vector machine (SVM), partial least square regression (PLSR) and back propagation neural network (BPNN), were used to calibrate the models. The prediction performances of full-spectrum multivariate models and variable-selected (i.e., the bootstrapping soft shrinkage (BOSS) algorithm) optimization models were compared. The best models were used to map the fertility properties for every profile and the synthetic index for soil fertility of profiles were computed and used to quantify the soil fertility. And then the evolution of soil fertility was analyzed on a millennium scale. The results showed that the five fertility properties could be predicted and mapped for all profiles, and the BOSS-SVMR models performed better than other models. According to the independent validation results, SOM, TN, and pH were predicted well (R2≥ 0.82, RPIQ ≥ 3.37), and the prediction performance for TP and TK was acceptable (0.50 ≤ R2< 0.66, 2.02 ≤ RPIQ < 2.70). The vertical distribution of soil fertility at different rice-planting ages showed that the soil fertility in the surface layer (0–30 cm) was high and decreased gradually with depth, tending to be stable in the deeper layer (30–100 cm). Rice planting significantly improved surface soil fertility. The linear function fit the changes in soil fertility with planting age better than the power function, indicating that the soil fertility in this area may have a high capacity for improvement. It was concluded that IS technology could be applied to high-resolution mapping of fertility properties in the intact paddy soil profiles. These results can offer new insights on soil fertility evolution and future soil sustainability under long-term anthropogenic influences.

A comparison of machine learning algorithms for mapping soil iron parameters indicative of pedogenic processes by hyperspectral imaging of intact soil profiles

AbstractSoil iron (Fe) performs vital functions in the biogeochemical cycles of soil environments. The amount and profile allocation of various Fe parameters can be used as sensitive indicators of soil development and pedogenic processes. This study aimed to evaluate the potential of ground‐based hyperspectral imaging (HSI: 400–1010 nm) spectroscopy to predict and map six Fe parameters indicative of pedogenic processes: total Fe (Fet), dithionite‐citrate‐bicarbonate (DCB)‐extracted Fe (Fed), oxalate‐extracted Fe (Feo), weathering index (FeW), active ratio (FeA) and crystallinity ratio (FeC). In total, 17 intact soil profiles at a depth of 100 ± 5 cm were collected to acquire HSI images. Four non‐linear machine learning techniques, namely, random forest (RF), XGBoost, CatBoost and support vector machine regression (SVMR), were implemented and compared with linear partial least squares (PLS) to identify the models with the best performance for different soil Fe parameters. Our results indicate that the four non‐linear machine learning models outperformed PLS for most soil Fe parameters, with low root mean square error (RMSE) and high Lin's concordance correlation coefficient (LCCC) values. Based on the testing set, SVMR showed better performance over the other tested models for Fet (RMSEP = 2.645 g kg−1, LCCCP = 0.89), Fed (RMSEP = 0.972 g kg−1, LCCCP = 0.97), Feo (RMSEP = 0.273 g kg−1, LCCCP = 0.97), FeW (RMSEP = 0.035, LCCCP = 0.97), FeA (RMSEP = 0.033, LCCCP = 0.97) and FeC (RMSEP = 0.031, LCCCP = 0.97). According to the LCCCP values, soil Fet was predicted to be in substantial agreement by SVMR, and the other soil Fe predictions were considered to be in near perfect agreement. Moreover, SVMR required lower computational costs. Given these results, the combination of HSI spectroscopy and SVMR is recommended due to its more reliable estimation and profile mapping of the selected soil Fe parameters than that of PLS, RF, XGBoost and CatBoost.Highlights Hyperspectral imaging was used to map six soil Fe parameters of intact profiles. Nonlinear machine learning models were compared to select the most suitable model. Nonlinear techniques outperformed the linear PLS model in most cases. SVMR showed higher comprehensive performance than other models. Hyperspectral imaging combined with SVMR is recommended to map soil Fe in profiles.

Soil profile connectivity can impact microbial substrate use, affecting how soil CO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; effluxes are controlled by temperature

Abstract. Determining controls on the temperature sensitivity of heterotrophic soil respiration remains critical to incorporating soil–climate feedbacks into climate models. Most information on soil respiratory responses to temperature comes from laboratory incubations of isolated soils and typically subsamples of individual horizons. Inconsistencies between field and laboratory results may be explained by microbial priming supported by cross-horizon exchange of labile C or N. Such exchange is feasible in intact soil profiles but is absent when soils are isolated from surrounding depths. Here we assess the role of soil horizon connectivity, by which we mean the degree to which horizons remain layered and associated with each other as they are in situ, on microbial C and N substrate use and its relationship to the temperature sensitivity of respiration. We accomplished this by exploring changes in C : N, soil organic matter composition (via C : N, amino acid composition and concentration, and nuclear magnetic resonance spectroscopy), and the δ13C of respiratory CO2 during incubations of organic horizons collected across boreal forests in different climate regions where soil C and N compositions differ. The experiments consisted of two treatments: soil incubated (1) with each organic horizon separately and (2) as a whole organic profile, permitting cross-horizon exchange of substrates during the incubation. The soils were incubated at 5 and 15 ∘C for over 430 d. Enhanced microbial use of labile C-rich, but not N-rich, substrates were responsible for enhanced, whole-horizon respiratory responses to temperature relative to individual soil horizons. This impact of a labile C priming mechanism was most emergent in soils from the warmer region, consistent with these soils' lower C bioreactivity relative to soils from the colder region. Specifically, cross-horizon exchange within whole soil profiles prompted increases in mineralization of carbohydrates and more 13C-enriched substrates and increased soil respiratory responses to warming relative to soil horizons incubated in isolation. These findings highlight that soil horizon connectivity can impact microbial substrate use in ways that affect how soil effluxes of CO2 are controlled by temperature. The degree to which this mechanism exerts itself in other soils remains unknown, but these results highlight the importance of understanding mechanisms that operate in intact soil profiles – only rarely studied – in regulating a key soil–climate feedback.

Integrating hyperspectral imaging with machine learning techniques for the high-resolution mapping of soil nitrogen fractions in soil profiles

Soil nitrogen (N) plays a central role in soil quality and biogeochemical cycles. However, little is known about the distribution and spatial variability of the different fractions of soil N within entire soil profiles. This study aimed to investigate the potential of laboratory-based hyperspectral imaging (HSI) spectroscopy to retrieve and map total N (TN), available N (AvailN), ammonium N (NH4-N), nitrate N (NO3-N), and microbial biomass N (MBN) in soil profiles at a high resolution. HSI images of eleven intact soil profiles of 100 ± 5 cm depth from three typical soil types were recorded. A variety of nonlinear machine learning techniques, such as artificial neural networks (ANN), cubist regression tree (Cubist), k-nearest neighbour (KNN), support vector machine regression (SVMR) and extreme gradient boosting (XGBoost), were compared with a partial least squares regression (PLSR) to determine the most suitable model for the prediction of the various soil N fractions. Overall, the results showed that nonlinear techniques performed better than PLSR in most cases, with a high coefficient of determination (R2) and low root mean square error (RMSE). Among the models, SVMR was found to be superior to the other tested models for TN (R2P = 0.94, RMSEP = 0.17 g kg−1), AvailN (R2P = 0.94, RMSEP = 13.35 mg kg−1), NO3-N (R2P = 0.82, RMSEP = 7.31 mg kg−1), and NH4-N (R2P = 0.70, RMSEP = 1.51 mg kg−1) based on independent validation, whereas MBN (R2P = 0.63, RMSEP = 6.62 mg kg−1) was predicted best by KNN. In addition, SVMR required less computational time and was less sensitive to spectral noise. It can therefore be concluded that HSI spectroscopy combined with SVMR is suitable for the high-resolution mapping of various soil N fractions in soil profiles.

Hyperspectral imaging for high-resolution mapping of soil carbon fractions in intact paddy soil profiles with multivariate techniques and variable selection

Soil organic carbon (SOC) and its labile C fractions play a central role in soil quality and C cycles. This study aimed to investigate the potential of laboratory-based hyperspectral imaging (HSI) spectroscopy to predict and map SOC and its labile C fractions (e.g., dissolved organic C, DOC; readily oxidizable organic C, ROC; and microbial biomass C, MBC) in soil profiles with a high resolution. The HSI images were captured from 16 intact paddy soil profiles to a depth of 100 ± 5 cm from four typical parent materials. The linear (i.e., partial least squares regression, PLSR) and nonlinear (i.e., artificial neural networks, ANN; cubist regression tree, Cubist; Gaussian process regression, GPR; and support vector machine regression, SVMR) multivariate techniques were compared to assess their ability to map the soil C fractions in the profiles. A spectral variable selection technique (i.e., competitive adaptive reweighted sampling, CARS) was applied to these multivariate models (i.e., CARS-PLSR, CARS-ANN, CARS-Cubist, CARS-GPR, and CARS-SVMR). Overall, the results showed that the nonlinear models performed better than the PLSR models in most cases. All optimized multivariate models with CARS achieved prediction performances similar to the full spectrum models, with high Lin's concordance correlation coefficient (LCC) and low root mean square error (RMSE). CARS-SVMR used only 37–70 spectral variables and took less time-consuming on computations (<0.5 min). Considering both the prediction performance and model-run efficiency, the CARS-SVMR models for SOC (LCCP = 0.98, RMSEP = 1.48 g kg−1), DOC (LCCP = 0.93, RMSEP = 100.61 mg kg−1), ROC (LCCP = 0.94, RMSEP = 0.70 g kg−1), and MBC (LCCP = 0.61, RMSEP = 58.12 mg kg−1) were superior to the other optimized models based on the independent validation. It was concluded that HSI spectroscopy coupled with CARS-SVMR is suitable for the high-resolution mapping of SOC and its labile C fractions in the intact paddy soil profiles.

An open-source database for the synthesis of soil radiocarbon data: International Soil Radiocarbon Database (ISRaD) version 1.0

Abstract. Radiocarbon is a critical constraint on our estimates of the timescales of soil carbon cycling that can aid in identifying mechanisms of carbon stabilization and destabilization and improve the forecast of soil carbon response to management or environmental change. Despite the wealth of soil radiocarbon data that have been reported over the past 75 years, the ability to apply these data to global-scale questions is limited by our capacity to synthesize and compare measurements generated using a variety of methods. Here, we present the International Soil Radiocarbon Database (ISRaD; http://soilradiocarbon.org, last access: 16 December 2019), an open-source archive of soil data that include reported measurements from bulk soils, distinct soil carbon pools isolated in the laboratory by a variety of soil fractionation methods, samples of soil gas or water collected interstitially from within an intact soil profile, CO2 gas isolated from laboratory soil incubations, and fluxes collected in situ from a soil profile. The core of ISRaD is a relational database structured around individual datasets (entries) and organized hierarchically to report soil radiocarbon data, measured at different physical and temporal scales as well as other soil or environmental properties that may also be measured and may assist with interpretation and context. Anyone may contribute their own data to the database by entering it into the ISRaD template and subjecting it to quality assurance protocols. ISRaD can be accessed through (1) a web-based interface, (2) an R package (ISRaD), or (3) direct access to code and data through the GitHub repository, which hosts both code and data. The design of ISRaD allows for participants to become directly involved in the management, design, and application of ISRaD data. The synthesized dataset is available in two forms: the original data as reported by the authors of the datasets and an enhanced dataset that includes ancillary geospatial data calculated within the ISRaD framework. ISRaD also provides data management tools in the ISRaD-R package that provide a starting point for data analysis; as an open-source project, the broader soil community is invited and encouraged to add data, tools, and ideas for improvement. As a whole, ISRaD provides resources to aid our evaluation of soil dynamics across a range of spatial and temporal scales. The ISRaD v1.0 dataset is archived and freely available at https://doi.org/10.5281/zenodo.2613911 (Lawrence et al., 2019).

An open source database for the synthesis of soil radiocarbon data: ISRaD version 1.0

Abstract. Radiocarbon is a critical constraint on our estimates of the timescales of soil carbon cycling that can aid in identifying mechanisms of carbon stabilization and destabilization, and improve forecast of soil carbon response to management or environmental change. Despite the wealth of soil radiocarbon data that has been reported over the past 75 years, the ability to apply these data to global scale questions is limited by our capacity to synthesis and compare measurements generated using a variety of methods. Here we describe the International Soil Radiocarbon Database (ISRaD, soilradiocarbon.org ), an open-source archive of soils data that include data from bulk soils, or whole-soils ; distinct soil carbon pools isolated in the laboratory by a variety of soil fractionation methods; samples of soil gas or water collected interstitially from within an intact soil profile; CO2 gas isolated from laboratory soil incubations; and fluxes collected in situ from a soil surface. The core of ISRaD is a relational database structured around individual datasets (entries) and organized hierarchically to report soil radiocarbon data, measured at different physical and temporal scales, as well as other soil or environmental properties that may also be measured at one or more levels of the hierarchy that may assist with interpretation and context. Anyone may contribute their own data to the database by entering it into the ISRaD template and subjecting it to quality assurance protocols. ISRaD can be accessed through: (1) a web-based interface, (2) an R package (ISRaD), or (3) direct access to code and data through the GitHub repository, which hosts both code and data. The design of ISRaD allows for participants to become directly involved in the management, design, and application of ISRaD data. The synthesized dataset is available in two forms: the original data as reported by the authors of the datasets; and an enhanced dataset that includes ancillary geospatial data calculated within the ISRaD framework. ISRaD also provides data management tools in the ISRaD-R package that provide a starting point for data analysis. This community-based dataset and platform for soil radiocarbon and a wide array of additional soils data information in soils where data are easy to contribute and the community is invited to add tools and ideas for improvement. As a whole, ISRaD provides resources that can aid our evaluation of soil dynamics and improve our understanding of controls on soil carbon dynamics across a range of spatial and temporal scales. The ISRaD v1.0 dataset (Lawrence et al., 2019) is archived and freely available at https://doi.org/10.5281/zenodo.2613911 .

Evaluating the ability of standardised leaching tests to predict metal(loid) leaching from intact soil columns using size-based elemental fractionation

Laboratory-based leaching tests are frequently used for in situ risk assessments of contaminant leaching to groundwater and surface waters. This study evaluated the ability of three standardised leaching tests to assess leaching of lead (Pb), zinc (Zn), arsenic (As) and antimony (Sb) from four intact soil profiles, by considering particulate (0.45–8 μm; percolation test), colloidal (10 kDa–0.45 μm) and truly dissolved (<10 kDa) fractions of these elements. Deionised water was used as the percolation test leachant, while either deionised water or 1 mM CaCl2 was used in batch tests. Data from an irrigation experiment were used as reference. The results indicated that in percolation tests, leachate should be collected at a liquid:solid ratio (L/S) range of 2–10, instead of 0–0.5 or 0.5–2. Even at L/S = 2–10, the percolation test overestimated total Pb concentration, mainly because of greater mobilisation of particle-bound Pb, but appeared suitable for categorising soils into high/low risk with respect to mobilisation of particulate and colloidal contaminants. The batch test performed better with CaCl2 than with deionised water when standard membrane filtration (0.45 μm) was used, as the high Ca2+ concentration reduced colloidal mobilisation, avoiding overestimation of concentrations of elements such as Pb. However, the higher Ca2+ concentration and lower pH could result in overestimated concentrations of weakly sorbed elements, e.g. Zn.

A Pedogenic View of Ecosystem Restoration

Ecosystem response to site restoration depends in part on the physical, chemical, and biological properties of soils. Soil properties are influenced by the factors and processes of soil formation that determine soil profile characteristics and pedogenic pathways for soils. Loss of integrity of the original soil profiles or disruption of a past pedogenic pathway from site disturbance may limit the success of restoration if assessment is based on comparisons to previous ecosystems or mature reference systems. New profile characteristics and a pedogenic pathway will emerge over time if materials are used to construct soil profiles or if topsoil or organic matter amendments are added to enhance ecosystem development during site restoration. Ecosystem restoration should include the following pedogenic evaluation of soils: 1) the integrity of existing soil profiles of a degraded site; 2) the soil types (based on soil orders) and past pedogenic pathways for sites of intact soil profiles or sites that require only surface horizon modification; 3) the relative contributions of soil forming factors and processes on future pedogenesis; 4) the conditions that promote or hinder horizon development; and 5) predictions of pedogenic pathways and potential soil types after site restoration. Understanding pedogenesis as a component of ecosystem restoration will improve our understanding of how soils influence ecosystem development, as well as our ability to predict potential success of ecosystem restoration.

Pre-and post-Missoula flood geomorphology of the Pre-Holocene ancestral Columbia River Valley in the Portland forearc basin, Oregon and Washington, USA

Geomorphic landscape development in the pre-Holocene ancestral Columbia River Valley (1–5km width) in the Portland forearc basin (~50km length) is established from depositional sequences, which pre-date and post-date the glacial Lake Missoula floods. The sequences are observed from selected borehole logs (150 in number) and intact terrace soil profiles (56 in number) in backhoe trenches. Four sequences are widespread, including (1) a vertically aggraded Pleistocene alluvial plain, (2) a steep sided valley that is incised (125–150m) into the Pleistocene gravel plain, (3) Missoula flood terraces (19–13ka) abandoned on the sides of the ancestral valley, and (4) Holocene flooding surfaces (11–8ka) buried at 70–30m depth in the axial Columbia River Valley. Weathering rims and cementation are used for relative dating of incised Pleistocene gravel units. Soil development on the abandoned Missoula flood terraces is directly related to terrace deposit lithology, including thin Bw horizons in gravel, irregular podzols in sand, and multiple Bw horizons in thicker loess-capping layers. Radiocarbon dating of sand and mud alluvium in the submerged axial valley ties Holocene flooding surfaces to a local sea level curve and establishes Holocene sedimentation rates of 1.5cmyear−1 during 11–9ka and 0.3cmyear−1 during 9–0ka. The sequences of Pleistocene gravel aggradation, river valley incision, cataclysmic Missoula flooding, and Holocene submergence yield complex geomorphic landscapes in the ancestral lower Columbia River Valley.

A method for experimental heating of intact soil profiles for application to climate change experiments

AbstractA new system for simulating future belowground temperature increases was conceived, simulated, constructed and tested in a temperate deciduous forest in Oak Ridge, TN, USA. The new system uses low‐wattage, 3 m deep heaters installed around the circumference of a defined soil volume. The heaters add the necessary energy to achieve a set soil temperature differential within the treatment area and add exterior energy inputs equal to those, which might be lost from lateral heat conduction. The method, which was designed to work in conjunction with aboveground heated chambers, requires only two control sensor positions one for aboveground air temperatures at 1 m and another for belowground temperatures at 0.8 m. The method is capable of achieving temperature differentials of at least +4.0±0.5 °C for soils to a measured depth of −2 m. These +4 °C differential soil temperatures were sustained in situ throughout 2009, and both diurnal and seasonal cycles at all soil depths were retained using this simple heating approach. Measured mean energy inputs required to sustain the target heating level of +4 °C over the 7.1 m2 target area were substantial for aboveground heating (21.1 kW h day−1 m−2), but 16 times lower for belowground heaters (1.3 kW h day−1 m−2). Observations of soil CO2 efflux from the surface of the target soil volumes showed CO2 losses throughout 2009 that were elevated above the temperature response curve that have been reported in previous near‐surface soil warming studies. Stimulation of biological activity within previously undisturbed deep‐soil carbon stocks is the hypothesized source. Long‐term research programs may be able to apply this new heating method that captures expected future warming and temperature dynamics throughout the soil profile to address uncertainties in process‐level responses of microbial, plant and animal communities in whole, intact ecosystems.

Improved method of making soil monoliths using an acrylic bonding agent and proline auger

This soil monolith production method, initially developed in the late 1990s, has now been successfully applied to over 100 soil profiles, dealing with the majority of Australian soils ranging from clays to sands, from uniform to texture contrast profiles, and from alkaline soils to even acid sulphate soils. The method outlined utilises intact soil profiles (150 mm diameter undisturbed soil cores collected with a Proline hollow flight auger). This technique is rapid and minimises site disturbance. A modern acrylic bonding compound (Bondcryl 737 ®) was selected as the bonding agent because it is strong, durable, UV resistant, and non-toxic. The bonding agent is applied to the soil profile as a series of fine misty sprays using a hand pump action spray bottle. After several applications the solution permeates through the outer 5 mm or more of the soil, bonding the whole profile together. The finished soil monolith has a moist soil colour, but with a natural non-glossy appearance. A decade has now passed since the first monoliths were made using this method, and those monoliths are still being transported and displayed regularly. They remain in good condition, giving us some confidence in the reliability of this method.

Measurement of soil carbon oxidation state and oxidative ratio by 13C nuclear magnetic resonance

The oxidative ratio (OR) of the net ecosystem carbon balance is the ratio of net O2 and CO2 fluxes resulting from photosynthesis, respiration, decomposition, and other lateral and vertical carbon flows. The OR of the terrestrial biosphere must be well characterized to accurately estimate the terrestrial CO2 sink using atmospheric measurements of changing O2 and CO2 levels. To estimate the OR of the terrestrial biosphere, measurements are needed of changes in the OR of aboveground and belowground carbon pools associated with decadal timescale disturbances (e.g., land use change and fire). The OR of aboveground pools can be measured using conventional approaches including elemental analysis. However, measuring the OR of soil carbon pools is technically challenging, and few soil OR data are available. In this paper we test three solid‐state nuclear magnetic resonance (NMR) techniques for measuring soil OR, all based on measurements of the closely related parameter, organic carbon oxidation state (Cox). Two of the three techniques make use of a molecular mixing model which converts NMR spectra into concentrations of a standard suite of biological molecules of known Cox. The third technique assigns Cox values to each peak in the NMR spectrum. We assess error associated with each technique using pure chemical compounds and plant biomass standards whose Cox and OR values can be directly measured by elemental analyses. The most accurate technique, direct polarization solid‐state 13C NMR with the molecular mixing model, agrees with elemental analyses to ±0.036 Cox units (±0.009 OR units). Using this technique, we show a large natural variability in soil Cox and OR values. Soil Cox values have a mean of −0.26 and a range from −0.45 to 0.30, corresponding to OR values of 1.08 ± 0.06 and a range from 0.96 to 1.22. We also estimate the OR of the carbon flux from a boreal forest fire. Analysis of soils from nearby intact soil profiles imply that soil carbon losses associated with the fire had an OR of 1.091 (±0.003). Fire appears to be a major factor driving the soil C pool to higher oxidation states and lower OR values. Episodic fluxes caused by disturbances like fire may have substantially different ORs from ecosystem respiration fluxes and therefore should be better quantified to reduce uncertainties associated with our understanding of the global atmospheric carbon budget.

Enhanced nitrogen mineralization in mowed or glyphosate treated cover crops compared to direct incorporation

Information on how management by mowing and herbicide alter residue quality and nitrogen (N) inputs would be valuable to improve prediction of N availability. Mowing and glyphosate application are widely used by growers to limit cover crop growth and facilitate incorporation. A mixture of cover crops, hairy vetch (Vicia villosa L.), oriental mustard (Brassica junceaL.) and cereal rye (Secale cerealeL.), was investigated as a means to improve soil quality and optimize N availability. There is limited information on how mowing or glyphosate application influence cover crop decomposition and N mineralization from these heterogeneous residues. A rye cover crop was grown in the field over the winter and transferred to containers as an intact soil profile to conduct a greenhouse study. Management treatments (mowing and glyphosate) were imposed eight days before incorporation. Plant and soil N dynamics were monitored. The experiment was repeated with the addition of a tri-mixture cover crop. Inorganic NO3− in bare soil ranged from 6 to 10 μg N g soil−1 over 39 days. Similar or lower levels of soil NO3− were observed after rye residue incorporation, from 2 to 6 μg N g−1; consistent with N-immobilization. Application of untreated, mixed cover crop residues generally was associated with higher levels of soil inorganic NO3−, from 3 to 11 μg N g−1. For both rye and mixed residues, management by mowing or glyphosate enhanced N mineralization by 10 to 100%, compared to untreated residues. At the same time, application of mowing or glyphosate 8 days before cover crop incorporation seemed to reduce the amount of residues by about half compared to untreated controls. Belowground biomass was reduced more than aboveground, although recovery of senescent roots may have been incomplete. Management by glyphosate or mowing enhanced soil inorganic N availability in the short-term while simultaneously reducing carbon and N inputs.

Contents of Cu, Ni and Zn in smelter-polluted soil–plant systems

Intact soil profiles including litter layer and ground vegetation were taken at five distances (0.5, 2, 4, 8 and 60 km) from a Cu–Ni smelter in Harjavalta, SW Finland. The soil cores were placed in 10 l pots and a 4 year-old, bare-rooted pine seedling ( Pinus sylvestris L.) was planted in each. The containers were incubated for17 months in controlled greenhouse conditions. At the end of the experiment the seedlings were harvested and soil samples were taken from each pot and analysed for Cu, Ni and Zn. The absence of atmospheric metal deposition had no reducing effect on the exchangeable heavy-metal contents of the soil pots. Metal uptake by the plant seedlings during the experiment had a negligible effect on the exchangeable heavy-metal content of the soil cores from the most polluted sites. The increase in both the exchangeable and the total humus Cu, Ni and Zn concentrations in the 0.5 km soil cores during the experiment suggested that there were pools of accumulated metals in the thick litter layer on top of the humus.

Assessing groundwater vulnerability using travel time and specific surface area as indicators

A method for general assessment of groundwater vulnerability was developed using the concept of hydrogeological settings by which a small-scale landscape can be represented by larger units on the map. For accidental spills, the time available for remedial actions is crucial. Travel times to the saturated zone or to a depth of 5 m are classified in four intervals, ranging from 1 yr. Total particle surface available for retention of pollutants in the unsaturated zone is used as a semi-quantitative indicator of vulnerability in a long-term perspective. This indicator is classified into four intervals, ranging from 25×106 m2/m2. The quality of the surfaces is not assessed. However, the absence of an intact soil profile is estimated to result in an increase in vulnerability by one class. Application of the methodology was demonstrated in an area south of Stockholm, Sweden. The digital geological map was processed using GIS to delineate four defined hydrogeological settings and vulnerability classes. Compared with an existing vulnerability map based on stratigraphic zoning, the hydrogeological settings allow a site to be interpreted in its hydrogeological context, and the use of quantitative vulnerability indicators increase the usefulness in practical planning and management.

The relevance of the Rio-Convention on biodiversity to conserving the biodiversity of soils

Nowhere in nature are species so densely packed as in soil communities. A large number of animal phyla and a diverse microflora are represented and these comprise a considerable part of any country's biodiversity. There are three main reasons for protecting soil biodiversity, (i) Ecological reasons: Decomposition and soil formation are key processes in nature and represent `ecological services' for the rest of the ecosystem. Soil organisms also represent the base for several above-ground food chains and the majority of terrestrial insects are soil dwellers for at least some stage in their life cycle, (ii) Utilitarian reasons: Soil biodiversity form the basis of agriculture, some medicines, and research in ecology and other disciplines and (iii) Ethical reasons: All life forms can be said to have an inherent value. Many groups of soil organisms are very old in evolutionary terms. Soil biodiversity must be included in the national strategies for long-term preservation of biodiversity to be developed following the Rio-Convention on Biodiversity. This implies both pure conservation measures and sustainable use of soils. Conservation measures must include identification and protection of sites with unique, endemic or threatened soil communities. Other targets could be rare soil types or intact soil profiles. Soil biodiversity is generally high in forests which may represent `hot spots' in agricultural landscapes. Measures for sustainable use must aim at keeping the biodiversity of agricultural and forest soils as high as possible. Chemicals and other treatments, which reduce soil biodiversity, should preferably be avoided. Conservation of soil biodiversity is a new and challenging field, for soil biologists, conservation biology, and local, national and international authorities. There is a great need for strengthening both basic and applied soil biology, including taxonomy and soil biologists should start the process by publicising the role, great complexity and threats to soil communities.

The topsoil as the major store of the propagules of vesicular-arbuscular mycorrhizal fungi in southeast Australian sandstone soils

The formation of vesicular-arbuscular mycorrhizae (VAM) in intact soil profiles from two sites in southeastern Australia were measured at two depths using a bioassay grown in intact soil cores. Intact soil cores were taken from (1) topsoil (0–15 cm) and (2) subsoil (15–30 cm) four times during 1990. Seeds of Acacialinifolia (Vent.) Willd. (Mimosaceae) were sown into the cores and plants harvested 8 and 12 weeks after sowing. For 1990, at both sites and in all seasons, VAM most readily developed in the roots of seedlings of A. linifolia grown in topsoil. Limited VAM occurred in roots grown in subsoil cores. Most colonisation of roots by VAM occurred from cores collected during spring and summer. Spore numbers were quantified for each site and depth by wet-sieving 100-g samples of air-dried soil and counting turgid spores containing oil droplets. Three types of spores were found in the soils. Few spores were extracted from all soils sampled, and for the most abundant of the spore types at least twice as many spores occurred in the topsoil than in the subsoil for all seasons examined. As most of the propagules that initiate VAM infection were observed in the topsoil, disturbances which involve the removal and storage of the top 15 cm will adversely affected these fungi.

The use of earthworms in environmental management

During the past 25 yr, research by the authors at Rothamsted Experimental Station investigated many aspects of the utilization of earthworms in land improvement and environmental management. Results of some of these investigations are summarized in this paper with the aim of illustrating the general principles of how earthworm populations can be manipulated and managed for environmental improvement. The use of earthworms in land improvement and reclamation: we investigated the effects of inoculating earthworms of the species Lumbricus terrestris L., Aporrectodea longa (Ude), Aporrectodea caliginosa (Sav.) and Allolobophora chlorotica (Sav.) into intact soil profiles in the laboratory, plots on direct-drilled, arable land in the field and newly-capped waste disposal sites that had few or no earthworms. In all these studies the earthworms increased significantly in number and rate of growth and yield of plants growing on the inoculated sites. Earthworms for inoculation were obtained by field collection after watering soil with dilute formaldehyde solution. The use of earthworms in organic waste management: the life cycles and productivity of Eisenia fetida (Sav.), Eudrilus eugeniae (Kinberg), Perionyx excavatus (Michaelsen) and Dendrobaena veneta (Rosa), and their potential in processing animal and plant wastes, from sewage, agricultural, domestic, urban and industrial sources are summarized. The preprocessing of wastes, their population ecology, optimum stocking rates, the mechanization of processing and utilization of the product are discussed. Results of experiments on the effects of temperatures of 10, 15, 20 and 25°C and a range of soil moisture contents of 70, 75, 80, 85 and 90% on the growth, cocoon production and cocoon hatching of the four species are summarized. The use of earthworms in assessment of the environmental effects of chemicals: earthworms can be used as key indicators to predict the effects of chemicals on other soil invertebrates. Methods of testing chemicals against earthworms in field and laboratory are reviewed. Two standardized laboratory test methods, one exposing earthworms to chemicals on filter paper and one to chemicals in artificial soils are described, and the median lethal concentration (LC 50) for chloracetamide, pentachlorophenol, chlordane, carbaryl, potassium bromide, copper sulfate and trichloracetic acid calculated, based on assays done in 34 laboratories. The relevancy of the two tests in environmental toxicity testing is reviewed.