scholarly journals Microscale Heterogeneity of the Spatial Distribution of Organic Matter Can Promote Bacterial Biodiversity in Soils: Insights From Computer Simulations

2018 ◽  
Vol 9 ◽  
Author(s):  
Xavier Portell ◽  
Valérie Pot ◽  
Patricia Garnier ◽  
Wilfred Otten ◽  
Philippe C. Baveye
Keyword(s):  
Organic Matter ◽  
Spatial Distribution ◽  
Computer Simulations ◽  
Bacterial Biodiversity ◽  
Microscale Heterogeneity

scholarly journals Drivers, mechanisms and long-term variability of seasonal hypoxia on the Black Sea northwestern shelf – is there any recovery after eutrophication?

2013 ◽  
Vol 10 (6) ◽  
pp. 3943-3962 ◽  
Author(s):  
A. Capet ◽  
J.-M. Beckers ◽  
M. Grégoire
Keyword(s):  
Organic Matter ◽  
Spatial Distribution ◽  
Interannual Variability ◽  
Black Sea ◽  
Sea Surface ◽  
The Black Sea ◽  
Northwestern Shelf ◽  
Bottom Waters ◽  
Seasonal Hypoxia ◽  
Bottom Hypoxia

Abstract. The Black Sea northwestern shelf (NWS) is a shallow eutrophic area in which the seasonal stratification of the water column isolates the bottom waters from the atmosphere. This prevents ventilation from counterbalancing the large consumption of oxygen due to respiration in the bottom waters and in the sediments, and sets the stage for the development of seasonal hypoxia. A three-dimensional (3-D) coupled physical–biogeochemical model is used to investigate the dynamics of bottom hypoxia in the Black Sea NWS, first at seasonal and then at interannual scales (1981–2009), and to differentiate its driving factors (climatic versus eutrophication). Model skills are evaluated by a quantitative comparison of the model results to 14 123 in situ oxygen measurements available in the NOAA World Ocean and the Black Sea Commission databases, using different error metrics. This validation exercise shows that the model is able to represent the seasonal and interannual variability of the oxygen concentration and of the occurrence of hypoxia, as well as the spatial distribution of oxygen-depleted waters. During the period 1981–2009, each year exhibits seasonal bottom hypoxia at the end of summer. This phenomenon essentially covers the northern part of the NWS – which receives large inputs of nutrients from the Danube, Dniester and Dnieper rivers – and extends, during the years of severe hypoxia, towards the Romanian bay of Constanta. An index H which merges the aspects of the spatial and temporal extension of the hypoxic event is proposed to quantify, for each year, the intensity of hypoxia as an environmental stressor. In order to explain the interannual variability of H and to disentangle its drivers, we analyze the long time series of model results by means of a stepwise multiple linear regression. This statistical model gives a general relationship that links the intensity of hypoxia to eutrophication and climate-related variables. A total of 82% of the interannual variability of H is explained by the combination of four predictors: the annual riverine nitrate load (N), the sea surface temperature in the month preceding stratification (Ts), the amount of semi-labile organic matter accumulated in the sediments (C) and the sea surface temperature during late summer (Tf). Partial regression indicates that the climatic impact on hypoxia is almost as important as that of eutrophication. Accumulation of organic matter in the sediments introduces an important inertia in the recovery process after eutrophication, with a typical timescale of 9.3 yr. Seasonal fluctuations and the heterogeneous spatial distribution complicate the monitoring of bottom hypoxia, leading to contradictory conclusions when the interpretation is done from different sets of data. In particular, it appears that the recovery reported in the literature after 1995 was overestimated due to the use of observations concentrated in areas and months not typically affected by hypoxia. This stresses the urgent need for a dedicated monitoring effort in the Black Sea NWS focused on the areas and months concerned by recurrent hypoxic events.

scholarly journals Spatial control of carbon dynamics in soil by microbial decomposer communities

2020 ◽  
Author(s):  
Holger Pagel ◽  
Björn Kriesche ◽  
Marie Uksa ◽  
Christian Poll ◽  
Ellen Kandeler ◽  
...  
Keyword(s):  
Organic Matter ◽  
Spatial Distribution ◽  
Soil Organic Matter ◽  
Distribution Patterns ◽  
Microbial Succession ◽  
Thin Sections ◽  
Spatial Control ◽  
Soil Organic Matter Turnover ◽  
Microbial Decomposer ◽  
Modelling Approach

<p>Trait-based models have improved the understanding and prediction of soil organic matter dynamics in terrestrial ecosystems. Microscopic observations and pore scale models are now increasingly used to quantify and elucidate the effects of soil heterogeneity on microbial processes. Combining both approaches provides a promising way to accurately capture spatial microbial-physicochemical interactions and to predict overall system behavior. The present study aims to quantify controls on carbon (C) turnover in soil due to the mm-scale spatial distribution of microbial decomposer communities in soil. A new spatially explicit trait-based model (SpatC) has been developed that captures the combined dynamics of microbes and soil organic matter (SOM) by taking into account microbial life-history traits and SOM accessibility. Samples of spatial distributions of microbes at µm-scale resolution were generated using a spatial statistical model based on Log Gaussian Cox Processes which was originally used to analyze distributions of bacterial cells in soil thin sections. These µm-scale distribution patterns were then aggregated to derive distributions of microorganisms at mm-scale. We performed Monte-Carlo simulations with microbial distributions that differ in mm-scale spatial heterogeneity and functional community composition (oligotrophs, copiotrophs and copiotrophic cheaters). Our modelling approach revealed that the spatial distribution of soil microorganisms triggers spatiotemporal patterns of C utilization and microbial succession. Only strong spatial clustering of decomposer communities induces a diffusion limitation of the substrate supply on the microhabitat scale, which significantly reduces the total decomposition of C compounds and the overall microbial growth. However, decomposer communities act as functionally redundant microbial guilds with only slight changes in C utilization. The combined statistical and process-based modelling approach derives distribution patterns of microorganisms at the mm-scale from microbial biogeography at microhabitat scale (µm) and quantifies the emergent macroscopic (cm) microbial and C dynamics. Thus, it effectively links observable process dynamics to the spatial control by microbial communities. Our study highlights a powerful approach that can provide further insights into the biological control of soil organic matter turnover.</p>

Guild distribution of some termites from cerrado vegetation in south-east Brazil

1991 ◽  
Vol 7 (4) ◽  
pp. 523-529 ◽  
Author(s):  
Terezinha Abreu Gontijo ◽  
Denize Junqueira Domingos
Keyword(s):  
Organic Matter ◽  
Spatial Distribution ◽  
Resource Partitioning ◽  
Random Distribution ◽  
Food Preferences ◽  
General Distribution ◽  
Nearest Neighbour ◽  
Termite Species ◽  
Cerrado Vegetation ◽  
Distributional Patterns

ABSTRACTThe distributional patterns and food preferences of some cerrado vegetation termites were studied in an area of 2500 m2 in south-east Brazil. All the termitaria were mapped and opened for identification of the species present. Their spatial distribution was studied using the nearest neighbour method (Clark & Evans 1954). We found 46 termite species in 450 nests. The majority of them were wood feeders. The general distribution of termitaria was regular. The distributional patterns of grass and litter feeders were not significantly different from a random distribution. Soil and organic matter feeders were contagiously distributed. The distribution of wood feeders was also contagious. Their spatial distribution was largely influenced by the distribution of the species Nasutitermes sp. 1 and Armitermes euamignathus. These two species occurred in two distinct patches, suggesting resource partitioning.

The spatial distribution of positron-emitting nuclei generated by relativistic light ion beams in organic matter

1992 ◽  
Vol 37 (11) ◽  
pp. 2127-2131 ◽  
Author(s):  
W Enghardt ◽  
W D Fromm ◽  
H Geissel ◽  
H Heller ◽  
G Kraft ◽  
...  
Keyword(s):  
Organic Matter ◽  
Spatial Distribution ◽  
Ion Beams

Soil Sediment Loading and Related Environmental Impacts from Farms

2017 ◽  
Author(s):  
Vito Ferro
Keyword(s):  
Organic Matter ◽  
Spatial Distribution ◽  
Soil Erosion ◽  
Sediment Yield ◽  
Water Storage ◽  
Sediment Deposition ◽  
Delivery Ratio ◽  
Sediment Delivery Ratio ◽  
Sediment Delivery ◽  
Soil Particles

Beyond damage to rainfed agricultural and forestry ecosystems, soil erosion due to water affects surrounding environments. Large amounts of eroded soil are deposited in streams, lakes, and other ecosystems. The most costly off-site damages occur when eroded particles, transported along the hillslopes of a basin, arrive at the river network or are deposited in lakes. The negative effects of soil erosion include water pollution and siltation, organic matter loss, nutrient loss, and reduction in water storage capacity. Sediment deposition raises the bottom of waterways, making them more prone to overflowing and flooding. Sediments contaminate water ecosystems with soil particles and the fertilizer and pesticide chemicals they contain. Siltation of reservoirs and dams reduces water storage, increases the maintenance cost of dams, and shortens the lifetime of reservoirs. Sediment yield is the quantity of transported sediments, in a given time interval, from eroding sources through the hillslopes and river network to a basin outlet. Chemicals can also be transported together with the eroded sediments. Sediment deposition inside a reservoir reduces the water storage of a dam. The prediction of sediment yield can be carried out by coupling an erosion model with a mathematical operator which expresses the sediment transport efficiency of the hillslopes and the channel network. The sediment lag between sediment yield and erosion can be simply represented by the sediment delivery ratio, which can be calculated at the outlet of the considered basin, or by using a distributed approach. The former procedure couples the evaluation of basin soil loss with an estimate of the sediment delivery ratio SDRW for the whole watershed. The latter procedure requires that the watershed be discretized into morphological units, areas having a constant steepness and a clearly defined length, for which the corresponding sediment delivery ratio is calculated. When rainfall reaches the surface horizon of the soil, some pollutants are desorbed and go into solution while others remain adsorbed and move with soil particles. The spatial distribution of the loading of nitrogen, phosphorous, and total organic carbon can be deduced using the spatial distribution of sediment yield and the pollutant content measured on soil samples. The enrichment concept is applied to clay, organic matter, and all pollutants adsorbed by soil particles, such as nitrogen and phosphorous. Knowledge of both the rate and pattern of sediment deposition in a reservoir is required to establish the remedial strategies which may be practicable. Repeated reservoir capacity surveys are used to determine the total volume occupied by sediment, the sedimentation pattern, and the shift in the stage-area and stage-storage curves. By converting the sedimentation volume to sediment mass, on the basis of estimated or measured bulk density, and correcting for trap efficiency, the sediment yield from the basin can be computed.

Spatial Distribution of Organic Matter and Nitrogen in the Entic Podzols of the Prioksko-Terrasnyi Reserve and Its Relationship with the Structure of Forest Phytocenoses

2020 ◽  
Vol 53 (8) ◽  
pp. 1021-1032
Author(s):  
I. V. Priputina ◽  
G. G. Frolova ◽  
V. N. Shanin ◽  
T. N. Myakshina ◽  
P. Ya. Grabarnik
Keyword(s):  
Organic Matter ◽  
Spatial Distribution ◽  
Forest Phytocenoses

scholarly journals Spatial Distribution and Health Risk Assessment of Potentially Toxic Elements in Surface Soils of Bosten Lake Basin, Central Asia

2019 ◽  
Vol 16 (19) ◽  
pp. 3741 ◽  
Author(s):  
Long Ma ◽  
Jilili Abuduwaili ◽  
Wen Liu
Keyword(s):  
Organic Matter ◽  
Spatial Distribution ◽  
Linear Model ◽  
Geographically Weighted Regression ◽  
Toxic Elements ◽  
Potentially Toxic Elements ◽  
Weighted Regression ◽  
Lake Basin ◽  
Total Organic Matter ◽  
Bosten Lake

A geographically weighted regression and classical linear model were applied to quantitatively reveal the factors influencing the spatial distribution of potentially toxic elements of forty-eight surface soils from Bosten Lake basin in Central Asia. At the basin scale, the spatial distribution of the majority of potentially toxic elements, including: cobalt (Co), chromium (Cr), copper (Cu), nickel (Ni), lead (Pb), thallium (Tl), vanadium (V), and zinc (Zn), had been significantly influenced by the geochemical characteristics of the soil parent material. However, the arsenic (As), cadmium (Cd), antimony (Sb), and mercury (Hg) have been influenced by the total organic matter in soils. Compared with the results of the classical linear model, the geographically weighted regression can significantly increase the level of simulation at the basin spatial scale. The fitting coefficients of the predicted values and the actual measured values significantly increased from the classical linear model (Hg: r2 = 0.31; Sb: r2 = 0.64; Cd: r2 = 0.81; and As: r2 = 0.68) to the geographically weighted regression (Hg: r2 = 0.56; Sb: r2 = 0.74; Cd: r2 = 0.89; and As: r2 = 0.85). Based on the results of the geographically weighted regression, the average values of the total organic matter for As (28.7%), Cd (39.2%), Hg (46.5%), and Sb (26.6%) were higher than those for the other potentially toxic elements: Cr (0.1%), Co (4.0%), Ni (5.3%), V (0.7%), Cu (18.0%), Pb (7.8%), Tl (14.4%), and Zn (21.4%). There were no significant non-carcinogenic risks to human health, however, the results suggested that the spatial distribution of potentially toxic elements had significant differences.

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