scholarly journals Contrasting Responses of Protistan Plant Parasites and Phagotrophs to Ecosystems, Land Management and Soil Properties

2020 ◽  
Vol 11 ◽  
Author(s):  
Anna Maria Fiore-Donno ◽  
Tim Richter-Heitmann ◽  
Michael Bonkowski
Proceedings ◽  
2019 ◽  
Vol 30 (1) ◽  
pp. 35 ◽  
Author(s):  
Telak ◽  
Bogunovic ◽  
Rodrigo-Comino

Humans are the driving factor of soil erosion and degradation. Therefore, sustainable land management practices should be developed and applied. The aim of this study was to determine land management impacts on soil properties, soil loss and nutrient loss in 3 different treatments; grass-covered vineyard (GCV), tilled vineyard (TV), and tilled hazelnut orchard (HO). The study area is located in Orahovica, Croatia (45°31′ N, 17°51′ E; elevation 230 m) on ~7° slope. The soil under the study area was classified as a Stagnosol. 8 rainfall simulations (58 mm h−1, during 30 min, over 0.785 m2 plots) were performed at each treatment where the next data were noted: ponding time, runoff time, and collection of overland flow. Soil samples were taken for determination of mean weight diameter (MWD), water stable aggregates (WSA), P2O5 content, and organic matter content. Analyses of sediment revealed concentrations of P2O5 and N. All three treatments had significantly different values of MWD (GCV 3.30 mm; TV 2.94 mm; HO 2.16 mm), while WSA and organic matter significantly differs between GCV and HO. The infiltration rate showed no significant difference between treatments. Sediment yield was significantly the highest at the TV (21.01 g kg−1 runoff), while no significant difference was noted between GCV (2.91) and HO (6.59). Sediments of GCV treatment showed higher concentrations of P2O5 and N, compared to TV and HO. Nutrients loss was highest in the TV (450.3 g P2O5 ha−1; 1891.7 g N ha−1) as a result of highest sediment yield, despite the fact GCV had the highest nutrients concentrations. Results indicate that land management (and/or tillage) affects soil properties and their stability. Even tough HO was tilled and had the lowest values of organic matter, WSA, and MWD, measurements were performed immediately after tillage where the plant residues reduced potential erodibility of the soil. Such results reveal that tillage should be avoided in vineyard and hazelnut production in order to prevent soil and nutrient losses.


2020 ◽  
Author(s):  
Leigh Winowiecki ◽  
Tor-Gunnar Vågen

<p>Maintaining soil organic carbon (SOC) content is recognized as an important strategy for a well-functioning soil ecosystem. The UN Convention to Combat Desertification (UNCCD) recognizes that reduced SOC content can lead to land degradation, and ultimately low land and agricultural productivity. SOC is almost universally proposed as the most important indicator of soil health, not only because SOC positively influences multiple soil properties that affect productivity, including cation exchange capacity and water holding capacity, but also because SOC content reflects aboveground activities, including especially agricultural land management. To be useful as an indicator, it is crucial to assess the importance of both inherent soil properties as well as external factors (climate, vegetation cover, land management, etc.) on SOC dynamics across space and time. This requires large, reliable and up-to-date soil health data sets across diverse land cover classes. The Land Degradation Surveillance Framework (LDSF), a well-established method for assessing multiple biophysical indicators at georeferenced locations, was employed in nine countries across the tropics (Burkina Faso, Cameron, Honduras, India, Indonesia, Kenya, Nicaragua, Peru, and South Africa) to assess the influence of land use, tree cover and inherent soil properties on soil organic carbon dynamics. The LDSF was designed to provide a biophysical baseline at landscape level, and monitoring and evaluation framework for assessing processes of land degradation and the effectiveness of rehabilitation measures over time. Each LDSF site has 160 – 1000 m<sup>2</sup> plots that were randomly stratified among 16 - 1 km<sup>2</sup> sampling clusters. A total of 6918 soil samples were collected (3478 topsoil (0-20 cm) and 3435 subsoil (20-50 cm)) within this study. All samples were analyzed using mid-infrared spectroscopy and 10% of the samples were analyzed using traditional wet chemistry to develop calibration prediction models.  Validation results for soil properties (soil organic carbon (SOC), sand, and total nitrogen) showed good accuracy with R<sup>2</sup> values ranging between 0.88 and 0.96. Mean organic carbon content was 21.9 g kg<sup>-1</sup> in topsoil and 15.2 g kg<sup>-1</sup> in subsoil (median was 18.3 g kg<sup>-1</sup>  for topsoil and 10.8 g kg<sup>-1</sup> in subsoil). Forest and grassland had the highest and similar carbon content while bushland/shrubland had the lowest. Sand content played an important role in determining the SOC content across the land cover types. Further analysis will be conducted and shared on the role of trees, land cover and texture on the dynamics of soil organic carbon and the implications for LDN reporting, land restoration initiatives as well as sustainable land management recommendations.</p>


2009 ◽  
Vol 6 (4) ◽  
pp. 5565-5601 ◽  
Author(s):  
W. Korres ◽  
C. N. Koyama ◽  
P. Fiener ◽  
K. Schneider

Abstract. Soil moisture is one of the fundamental variables in hydrology, meteorology and agriculture. Nevertheless, its spatio-temporal patterns in agriculturally used landscapes affected by multiple natural (rainfall, soil, topography etc.) and agronomic (fertilisation, soil management etc.) factors are often not well known. The aim of this study is to determine the dominant factors governing the spatio-temporal patterns of surface soil moisture in a grassland and an arable land test site within the Rur catchment in Western Germany. Surface soil moisture (0–6 cm) has been measured in an approx. 50×50 m grid at 14 and 17 dates (May 2007 to November 2008) in both test sites. To analyse spatio-temporal patterns of surface soil moisture, an Empirical Orthogonal Function (EOF) analysis was applied and the results were correlated with parameters derived from topography, soil, vegetation and land management to connect the pattern to related factors and processes. For the grassland test site, the analysis results in one significant spatial structure (first EOF), which explains about 57.5% of the spatial variability connected to soil properties and topography. The weight of the first spatial EOF is stronger on wet days. The highest temporal variability can be found in locations with a high percentage of soil organic carbon (SOC). For the arable land test site, the analysis yields two significant spatial structures, the first EOF, explaining 38.4% of the spatial variability, shows a highly significant correlation to soil properties, namely soil texture. The second EOF, explaining 28.3% of the spatial variability, is connected to differences in land management. The soil moisture in the arable land test site varies more during dry and wet periods on locations with low porosity.


1995 ◽  
Vol 37 (1-3) ◽  
pp. 333-345 ◽  
Author(s):  
Andrew G. Williams ◽  
J. Les Ternan ◽  
Andy Elmes ◽  
Marta Gonzalez del Tanago ◽  
Raoul Blanco

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