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At least 1,567 records · Page 87

Controls and relationships of soil organic carbon abundance and persistence vary across pedo–climatic regions

One of the largest uncertainties in the terrestrial carbon cycle is the timing and magnitude of soil organic carbon (SOC) response to climate and vegetation change. This uncertainty prevents models from adequately capturing SOC dynamics and challenges the assessment of management and climate change effects on soils. Reducing these uncertainties requires simultaneous investigation of factors controlling the amount (SOC abundance) and duration (SOC persistence) of stored C. We present a global synthesis of SOC and radiocarbon profiles (n Profile = 597) to assess the timescales of SOC storage. We use a combination of statistical and depth–resolved compartment models to explore key factors controlling the relationships between SOC abundance and persistence across pedo–climatic regions and with soil depth. This allows us to better understand (i) how SOC abundance and persistence covary across pedo–climatic regions and (ii) how the depth dependence of SOC dynamics relates to climatic and mineralogical controls on SOC abundance and persistence. We show that SOC abundance and persistence are differently related; the controls on these relationships differ substantially between major pedo–climatic regions and soil depth. For example, large amounts of persistent SOC can reflect climatic constraints on soils (e.g., in tundra/polar regions) or mineral absorption, reflected in slower decomposition and vertical transport rates. In contrast, lower SOC abundance can be found with lower SOC persistence (e.g., in highly weathered tropical soils) or higher SOC persistence (e.g., in drier and less productive regions). We relate variable patterns of SOC abundance and persistence to differences in the processes constraining plant C input, microbial decomposition, vertical C transport and mineral SOC stabilization potential. This process–oriented grouping of SOC abundance and persistence provides a valuable benchmark for global C models, highlighting that pedo–climatic boundary conditions are crucial for predicting the effects of climate change and soil management on future C abundance and persistence.

54 ENVIRONMENTAL SCIENCES↗

Observed variation in soil properties can drive large variation in modelled forest functioning and composition during tropical forest secondary succession

Censuses of tropical forest plots reveal large variation in biomass and plant composition. This paper evaluates whether such variation can emerge solely from realistic variation in a set of commonly measured soil chemical and physical properties. Controlled simulations were performed using a mechanistic model that includes forest dynamics, microbe-mediated biogeochemistry, and competition for nitrogen and phosphorus. Observations from 18 forest inventory plots in Guanacaste, Costa Rica were used to determine realistic variation in soil properties. In simulations of secondary succession, the across-plot range in plant biomass reached 30% of the mean and was attributable primarily to nutrient limitation and secondarily to soil texture differences that affected water availability. The contributions of different plant functional types to total biomass varied widely across plots and depended on soil nutrient status. In Central America, soil-induced variation in plant biomass increased with mean annual precipitation because of changes in nutrient limitation. In Central America, large variation in plant biomass and ecosystem composition arises mechanistically from realistic variation in soil properties. Finally, the degree of biomass and compositional variation is climate sensitive. In general, model predictions can be improved through better representation of soil nutrient processes, including their spatial variation.

59 BASIC BIOLOGICAL SCIENCES↗

DNA Viral Diversity, Abundance, and Functional Potential Vary across Grassland Soils with a Range of Historical Moisture Regimes

Soil viruses are abundant, but the influence of the environment and climate on soil viruses remains poorly understood. Here, we addressed this gap by comparing the diversity, abundance, lifestyle, and metabolic potential of DNA viruses in three grassland soils with historical differences in average annual precipitation, low in eastern Washington (WA), high in Iowa (IA), and intermediate in Kansas (KS). Bioinformatics analyses were applied to identify a total of 2,631 viral contigs, including 14 complete viral genomes from three deep metagenomes (1 terabase [Tb] each) that were sequenced from bulk soil DNA. An additional three replicate metagenomes (~0.5 Tb each) were obtained from each location for statistical comparisons. Identified viruses were primarily bacteriophages targeting dominant bacterial taxa. Both viral and host diversity were higher in soil with lower precipitation. Viral abundance was also significantly higher in the arid WA location than in IA and KS. More lysogenic markers and fewer clustered regularly interspaced short palindromic repeats (CRISPR) spacer hits were found in WA, reflecting more lysogeny in historically drier soil. More putative auxiliary metabolic genes (AMGs) were also detected in WA than in the historically wetter locations. The AMGs occurring in 18 pathways could potentially contribute to carbon metabolism and energy acquisition in their hosts. Structural equation modeling (SEM) suggested that historical precipitation influenced viral life cycle and selection of AMGs. The observed and predicted relationships between soil viruses and various biotic and abiotic variables have value for predicting viral responses to environmental change.

59 BASIC BIOLOGICAL SCIENCES↗

Regional biogeography versus intra-annual dynamics of the root and soil microbiome

Abstract Background Root and soil microbial communities constitute the below-ground plant microbiome, are drivers of nutrient cycling, and affect plant productivity. However, our understanding of their spatiotemporal patterns is confounded by exogenous factors that covary spatially, such as changes in host plant species, climate, and edaphic factors. These spatiotemporal patterns likely differ across microbiome domains (bacteria and fungi) and niches (root vs. soil). Results To capture spatial patterns at a regional scale, we sampled the below-ground microbiome of switchgrass monocultures of five sites spanning > 3 degrees of latitude within the Great Lakes region. To capture temporal patterns, we sampled the below-ground microbiome across the growing season within a single site. We compared the strength of spatiotemporal factors to nitrogen addition determining the major drivers in our perennial cropping system. All microbial communities were most strongly structured by sampling site, though collection date also had strong effects; in contrast, nitrogen addition had little to no effect on communities. Though all microbial communities were found to have significant spatiotemporal patterns, sampling site and collection date better explained bacterial than fungal community structure, which appeared more defined by stochastic processes. Root communities, especially bacterial, were more temporally structured than soil communities which were more spatially structured, both across and within sampling sites. Finally, we characterized a core set of taxa in the switchgrass microbiome that persists across space and time. These core taxa represented < 6% of total species richness but > 27% of relative abundance, with potential nitrogen fixing bacteria and fungal mutualists dominating the root community and saprotrophs dominating the soil community. Conclusions Our results highlight the dynamic variability of plant microbiome composition and assembly across space and time, even within a single variety of a plant species. Root and soil fungal community compositions appeared spatiotemporally paired, while root and soil bacterial communities showed a temporal lag in compositional similarity suggesting active recruitment of soil bacteria into the root niche throughout the growing season. A better understanding of the drivers of these differential responses to space and time may improve our ability to predict microbial community structure and function under novel conditions.

59 BASIC BIOLOGICAL SCIENCES↗

Effects of Soiling of Photovoltaic Modules and Systems in Brazil’s Climate Zones

This research presents a methodology for quantifying soiling loss in p-Si and CdTe photovoltaic modules through measurements from soiling stations installed in Belo Horizonte (-19.92° S, -43.99° W), Porto Alegre (-30.05° S, -51.17° W), Brotas de Macaúbas (12.0011° S, -42.6303° W), and Macapá (0.0356° N, -51.0705° W), in Brazil. The electrical parameters measured from photovoltaic modules are compared with precipitation data collected in the same location, with the objective of evaluating the behavior of the soiling ratio during the dry periods. Mathematical models determined the SRatio and SRate for each site (in compliance with the IEC-61324-1 monitoring standard [1]). The SRatio for short-circuit current and maximum power data from the modules were evaluated and compared, characterizing the potential effects of uniform and non-uniform soiling. In addition, a method for analyzing energy-production data of PV systems in order to extract the soiling rate was developed and is presented. The gravimetric soiling densities (mg/m2) was determined using the modeling by Coello and Boyle [2] and these are compared to data collected using the Figgis soiling microscope [3].

climate zone↗

Decomposition by ectomycorrhizal fungi alters soil carbon storage in a simulation model

Carbon cycle models often lack explicit belowground organism activity, yet belowground organisms regulate carbon storage and release in soil. Ectomycorrhizal fungi are important players in the carbon cycle because they are a conduit into soil for carbon assimilated by the plant. It is hypothesized that ectomycorrhizal fungi can also be active decomposers when plant carbon allocation to fungi is low. Here, we reviewed the literature on ectomycorrhizal decomposition and we developed a simulation model of the plant-mycorrhizae interaction where a reduction in plant productivity stimulates ectomycorrhizal fungi to decompose soil organic matter. Our review highlights evidence demonstrating the potential for ectomycorrhizal fungi to decompose soil organic matter. Our model output suggests that ectomycorrhizal activity accounts for a portion of carbon decomposed in soil, but this portion varied with plant productivity and the mycorrhizal carbon uptake strategy simulated. Lower organic matter inputs to soil were largely responsible for reduced soil carbon storage. Using mathematical theory, we demonstrated that biotic interactions affect predictions of ecosystem functions. Specifically, we developed a simple function to model the mycorrhizal switch in function from plant symbiont to decomposer. In conclusion, we show that including mycorrhizal fungi with the flexibility of mutualistic and saprotrophic lifestyles alters predictions of ecosystem function.

59 BASIC BIOLOGICAL SCIENCES↗

Determine metrics and set targets for soil quality on agriculture residue and energy crop pathways

There are three objectives for this project: 1) support OBP in meeting MYPP stated performance goals for the Sustainability Platform, 2) develop integrated feedstock production system designs that increase total productivity of the land, decrease delivered feedstock cost to the conversion facilities, and increase environmental performance of the production system, and 3) deliver to the bioenergy community robust datasets and flexible analysis tools for establishing sustainable and viable use of agricultural residues and dedicated energy crops. The key project outcome to date has been the development and deployment of a sustainable agricultural residue removal decision support framework. The modeling framework has been used to produce a revised national assessment of sustainable residue removal potential. The national assessment datasets are being used to update national resource assessment supply curves using POLYSIS. The residue removal modeling framework has also been enhanced to support high fidelity sub-field scale sustainable removal analyses. The framework has been deployed through a web application and a mobile application. The mobile application is being used extensively in the field with industry, research, and USDA NRCS partners to support and validate sustainable residue removal decisions. The results detailed in this report have set targets for increasing soil sustainability by focusing on primary soil quality indicators (total organic carbon and erosion) in two agricultural residue management pathways and a dedicated energy crop pathway. The two residue pathway targets were set to, 1) increase residue removal by 50% while maintaining soil quality, and 2) increase soil quality by 5% as measured by Soil Management Assessment Framework indicators. The energy crop pathway was set to increase soil quality by 10% using these same indicators. To demonstrate the feasibility and impact of each of these targets, seven case studies spanning the US are presented. The analysis has shown that the feedstock production systems are capable of simultaneously increasing productivity and soil sustainability.

09 BIOMASS FUELS↗

Quantitative, trait-based microbial ecology to accurately model the impacts of nitrogen deposition on soil carbon cycling in the Anthropocene (Final Technical Report)

Atmospheric nitrogen pollution has altered fundamental soil processes, challenging our understanding of the extent to which soils will continue to sequester carbon and slow the pace of future environmental change. While most evidence shows that increases in soil nitrogen have enhanced carbon storage in temperate forests, it remains unclear whether these effects will persist as nitrogen pollution continues to decline. Moreover, there remains uncertainty as to why some forests gain more carbon in response to nitrogen pollution than others. At the heart of this knowledge gap is a failure to link nitrogen–induced shifts in microbial biodiversity with gains or losses in their functional ability to decompose, assimilate, and ultimately stabilize soil carbon. Given that this uncertainty impedes the ability of predictive models to project future soil carbon stocks, there is a critical need to determine how key microbial traits drive soil carbon responses to nitrogen pollution. As such the goals of this project were to: (1) Quantify variation in taxon–specific and community–level microbial traits across gradients in microbial community composition, mycorrhizal symbioses, and nitrogen availability. (2) Integrate empirical data into a novel predictive framework that enhances our ability to project the regional soil carbon consequences of historical nitrogen pollution in temperate forests.

54 ENVIRONMENTAL SCIENCES↗

Leveraging Pre-storm Soil Moisture Estimates for Enhanced Land Surface Model Calibration in Ungauged Hydrologic Basins

Despite long-standing efforts, hydrologists still lack robust tools for calibrating land surface model (LSM) streamflow estimates within ungauged basins. Using surface soil moisture estimates from the Soil Moisture Active Passive Level 4 Soil Moisture (L4_SM) product, precipitation observations, and streamflow gauge measurements for 617 medium-scale (200-10,000 km2) basins in the contiguous United States, we measure the temporal (Spearman) rank correlation between antecedent (i.e., pre-storm) surface soil moisture (ASM) and the storm-scale runoff coefficient (RC; the fraction of storm-scale precipitation accumulation converted into streamflow). In humid and semi-humid basins, this rank correlation is shown to be sufficiently strong to allow for the substitution of storm-scale RC observations (available only in basins that are both lightly regulated and gauged) with high-quality ASM values (available quasi-globally from L4_SM) in streamflow calibration procedures. Using this principle, we define a new, basin-wise LSM streamflow calibration approach based on L4_SM alone and successfully apply it to identify LSM configurations that produce a high rank correlation with observed RC. However, since the approach cannot detect RC bias, it is less successful in identifying LSM configurations with low mean-absolute error. Plain Text Summary Accurately forecasting the fraction of rainfall that runs off into streams, as opposed to infiltrates into the soil, is critical for flash-flood prediction, water-resource monitoring, and tracking the transport of nutrients from agricultural fields into local waterways. Such forecasting is typically performed by hydrologic models that attempt to represent the physical processes responsible for surface runoff generation. However, to provide accurate streamflow forecasts, these models typically need to be calibrated against actual streamflow observations. This is problematic given the relatively poor, and declining, global availability of stream gauges. This paper presents a novel model calibration strategy that uses soil moisture from remote sensing and numerical modeling in place of streamflow observations during calibration. This transition has significant practical advantages because, unlike streamflow observations, the soil moisture data are continuously available across space. Our results demonstrate that this new approach can significantly improve hydrologic models within humid and semi-humid basins lacking sufficient ground-based instrumentation for traditional streamflow calibration.

hydrologic models↗

Development and validation of a citrate synthase directed quantitative PCR marker for soil bacterial communities

Molecular innovations in microbial ecology are allowing scientists to correlate microbial community characteristics to a variety of ecosystem functions. However, to date the majority of soil microbial ecology studies target phylogenetic rRNA markers, while a smaller number target functional markers linked to soil processes. We validated a new primer set targeting citrate synthase (gtlA), a central enzyme in the citric acid cycle linked to aerobic respiration. Primers for a 225 bp fragment suitable for qPCR were tested for specificity and assay performance verified on multiple soils. Clone libraries of the PCR-amplified gtlA gene exhibited high diversity and recovered most major groups identified in a previous 16S rRNA gene study. Comparisons among bacterial communities based on gtlA sequencing using UniFrac revealed differences among the experimental soils studied. Conditions for gtlA qPCR were optimized and calibration curves were highly linear (R2 > 0.99) over six orders of magnitude (4.56 10^5 to 4.56 10^11 copies), with high amplification efficiencies (>1.7). We examined the performance of the gtlA qPCR across a variety of soils and ecosystems, spanning forests, old fields and agricultural areas. We were able to amplify gtlA genes in all tested soils, and detected differences in gtlA abundance within and among environments. These results indicate that a fully developed gtlA-targeted qPCR approach may have potential to link microbial community characteristics with changes in soil respiration.

54 ENVIRONMENTAL SCIENCES↗

Evaluating the Accuracy of Various Irradiance Models in Detecting Soiling of Irradiance Sensors: Preprint

We evaluate the feasibility of using various clear-sky models or purchased satellite data for estimating the soiling of a reference cell irradiance sensor. We find results to be more accurate for models that consider local meteorological conditions. We conclude that given the data sets considered, and depending on the requirements of the data analyst, choosing to use purchased satellite irradiance data from Solargis to estimate the soiling of a reference cell sensor tends to yield more accurate results, although there are instances where a clear-sky model performs better. The SOLIS clear-sky model in PVLIB with variable Pwat provided useful soiling results, implying that the general method of using a clear-sky model with local meteorological data may provide a low-cost tool for detecting soiling of irradiance sensors. irradiance data from Solargis to estimate the soiling of a reference cell sensor tends to yield more accurate results, although there are instances where a clear-sky model performs better. The SOLIS clear-sky model in PVLIB with variable Pwat provided useful soiling results, implying that the general method of using a clear-sky model with local meteorological data may provide a low-cost tool for detecting soiling of irradiance sensors.

14 SOLAR ENERGY↗

Mycorrhiza better predict soil fungal community composition and function than aboveground traits in temperate forest ecosystems

We sampled soil in the organic and mineral horizons beneath two AM-associated (Fraxinus americana, Thuja occidentalis) and two ECM-associated tree species (Betula alleghaniensis, and Tsuga canadensis), with an evergreen and deciduous species in each mycorrhizal group. To characterize fungal communities and organic matter decomposition beneath each tree species, we sequenced the ITS1 region of fungal DNA and measured the potential activity of carbon and nitrogen-targeting extracellular enzymes. Each tree species harbored distinct fungal communities, supporting the need to consider both mycorrhizal type and leaf habit. However, between tree characteristics, mycorrhizal type better predicted fungal communities. Across fungal guilds, saprotrophic fungi were the most important group in shaping fungal community differences in soils beneath all tree species. The effect of leaf habit on carbon and nitrogen-targeting hydrolytic enzymes depended on tree mycorrhizal association in the organic horizon, while oxidative enzyme activities were higher beneath EcM-associated trees across both soil horizons and leaf habits. These data include extracellular hydrolytic and oxidative enzyme activities, ITS sequencing fungal community data, soil carbon to nitrogen, and soil pH. Site level data include climate (mean annual temperature, precipitation), elevation, and soil series and order information.

54 ENVIRONMENTAL SCIENCES↗

NGEE Arctic Plant Traits: Soil Cores, Kougarok Road Mile Marker 64, Seward Peninsula, Alaska, 2016

Soil cores were collected from twelve vegetation biomass plots at the Kougarok hillslope in late July of 2016. The sampled plots were located across six ecotypes present at this site (n=2 replicates per ecotype). Soil cores were separated into depth intervals in the field and frozen for transport to Oak Ridge National Laboratory. Laboratory sample processing of these soils generated data on soil texture, pH, gravimetric water content, bulk density, bulk soil %C and %N. Water extracts were performed on subsamples for determination of extractable total nitrogen, inorganic nitrogen, organic nitrogen, phosphorus, and dissolved organic carbon. This dataset contains 1 csv, and 1 pdf.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Forest soil carbon oxidation state and oxidative ratio responses to elevated CO 2

The oxidative ratio (OR) of the biosphere is the stoichiometric ratio (O 2 /CO 2 ) of gas exchange by photosynthesis and respiration a key parameter in budgeting calculations of the land and ocean carbon sinks. Carbon cycle-climate feedbacks could alter the OR of the biosphere by affecting the quantity and quality of organic matter in plant biomass and soil carbon pools. Here, this study considers the effect of elevated atmospheric carbon dioxide concentrations ([CO 2 ]) on the OR of a hardwood forest after nine growing seasons of Free-Air CO 2 Enrichment. We measured changes in the carbon oxidation state (C ox ) of biomass and soil carbon pools as a proxy for the ecosystem OR. The OR of net primary production, 1.039, was not affected by elevated [CO 2 ]. However, the C ox of the soil carbon pool was 40% higher at elevated [CO 2 ], and the estimated OR values for soil respiration increased from 1.006 at ambient [CO 2 ] to 1.054 at elevated [CO 2 ]. A biochemical inventory of the soil organic matter ascribed the increases in C ox and OR to faster turnover of reduced substrates, lignin and lipids, at elevated [CO 2 ]. This implicates the heterotrophic soil community response to elevated [CO 2 ] as a driver of disequilibrium in the ecosystem OR. The oxidation of soil carbon pool constitutes an unexpected terrestrial O 2 sink. Carbon budgets constructed under the assumption of OR equilibrium would equate such a terrestrial O 2 sink to CO 2 uptake by the ocean. We find that the potential for climate-driven disequilibriua in the cycling of O 2 and CO 2 warrants further investigation.

54 ENVIRONMENTAL SCIENCES↗

Lignin lags, leads, or limits the decomposition of litter and soil organic carbon

Lignin’s role in litter and soil organic carbon (SOC) decomposition remains contentious. Lignin decomposition was traditionally thought to increase during midstage litter decomposition, when cellulose occlusion by lignin began to limit mass loss. Alternatively, lignin decomposition could be greatest in fresh litter as a consequence of co-metabolism, and lignin might decompose faster than bulk SOC. To test these competing hypotheses, we incubated 10 forest soils with C 4 grass litter (amended with 13 C-labeled or unlabeled lignin) over 2 yr and measured soil respiration and its isotope composition. Early lignin decomposition was greatest in 5 of 10 soils, consistent with the co-metabolism hypothesis. However, lignin decomposition peaked 6–24 months later in the other five soils, consistent with the substrate-limitation hypothesis; these soils were highly acidic. Rates of lignin, litter, and SOC decomposition tended to converge over time. Cumulative lignin decomposition was never greater than SOC decomposition; lignin decomposition was significantly lower than SOC decomposition in six soils. Net nitrogen mineralization predicted lignin decomposition ratios relative to litter and SOC. Although the onset of lignin decomposition can indeed be rapid, lignin still presents a likely bottleneck in litter and SOC decomposition, meriting a reconsideration of lignin’s role in modern decomposition paradigms.

54 ENVIRONMENTAL SCIENCES↗

Impact of biochar amendments on soil water and plant uptake dynamics under different cropping systems

Abstract Application of biochar amendments in agricultural systems has received much attention in recent years. In this study, we assess the 5‐year impacts of biochar application on soil water and plant interactions for an irrigated fresh market tomato ( Solanum lycopersicum ) and a rainfed pasture ( Poaceae ) cropping system. In particular, we focus on three varieties of locally produced biochar from agricultural waste materials—almond shell, walnut shell, and almond pruning residues that are pyrolyzed using a mobile pyrolysis unit. We used the soil hydrological model HYDRUS‐1D to explicitly track seasonal and annual soil water fluxes through changes in water retention, drainage, evaporation, and plant water uptake under biochar application. Modeling results show that the application of biochar at 5% increased soil water availability within the top 20 cm for a rainfed system, irrespective of biochar amendment type. This is clearly indicative of higher plant water uptake and greater water use efficiency (WUE) under biochar application. In contrast, a similar biochar amendment for the irrigated system did not affect WUE, instead reducing seasonal soil evaporation loss and thereby reducing irrigation demand. In both cropping systems, year‐to‐year variability in precipitation significantly impacted the total amount of water saved under biochar application with certain amendments retaining more water than others. Given that biochar application increased water retention irrespective of cropping systems, we further used a simple approach to determine yield trade‐off, if any, between control and biochar treatments. Our economic balance clearly demonstrates that the water saved by amending soil with biochar does not offset the yield disparity if compensated with carbon credits and therefore, application of biochar should be actively considered for both its direct and indirect benefits to potential greenhouse gas mitigation (e.g., diverting orchard waste from open burning), water savings, and soil health.

54 ENVIRONMENTAL SCIENCES↗

Influence of Al{sub 2}O{sub 3} Nanoparticles on the Soil Elements

The behavior of nanoparticles released to the soil has been extensively studied in recent years; however, the effects of nanoparticles on the distribution of soil elements and on sowing are still unknown. To this end, to examine the distribution of selected elements in soil, soil samples were treated weekly with 1.0 mg and 20.0 mg of Al{sub 2}O{sub 3} nanoparticles for 3 weeks. Additionally, different types of plants (including taproot, fibrous root and ornamental bulbous plants) were sowed in the soil samples. After each treatment, surface soil samples were collected and digested with acid digestion. The concentrations of selected elements (Ca, Mg, Fe, Al, Cu, Co, Ni) were determined using a microwave plasma atomic emission spectrometer. Al{sub 2}O{sub 3} treatment for 3 weeks, both low and high doses, had no effect on the Al content in soil samples when compared to the controls. Additionally, Al{sub 2}O{sub 3} showed desorption properties on the analyte elements.

54 ENVIRONMENTAL SCIENCES↗

Long-Term Effects of Crude Oil Spillage on Selected Physicochemical Properties Including Heavy Metal Contents of Sandy Tropical Soil

Crude oil spillage effects on the environment often wane with time, making late remediation of affected soils look irrelevant. Physicochemical quality of a sandy soil under 9-year-old spillage was compared with that of adjacent unaffected site in southern Nigeria. Soil bulk density and equilibrated water content were higher in affected than unaffected site, but permeability did not change. The spillage increased soil pH, organic carbon, total nitrogen and available phosphorus by about 7%, 1700%, 133% and − 16%, respectively. It lowered divalent exchangeable bases/acidity but raised base saturation. It increased total petroleum hydrocarbon (PHC{sub t}) and micronutrients/heavy metals (Fe, Mn, Zn, Cd and Pb), all of which were below their critical limits in soils by regulatory bodies. Soil pH, organic carbon and PHC{sub t} correlated positively with all five micronutrients/heavy metals; total nitrogen did so with Zn and Pb. Nine-year period may be insufficient for spillage effects in sandy soils to cease to be evident. Such effects for PHC{sub t} and heavy metals, however, are deemed tolerable for ecological safety.

54 ENVIRONMENTAL SCIENCES↗