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The contribution of quality assessment of eroded agricultural soil on hilly-undulating landscapes to sustainable community development

  • Benediktas Jankauskas
  • Genovaite Jankauskiene
  • Algimantas Tiknius
Part of the NATO Science for Peace and Security Series C: Environmental Security book series (NAPSC)

Sustainable community development depends on different circumstances and conditions and soil is one of the most important natural resources influencing community development. Some soil quality indicators are exceptionally sensitive on hilly undulating relief. The results from 18 years of field experiments at the Kaltinenai Research Station of the Lithuanian Institute of Agriculture indicate that soil erosion processes under the field crop rotation (containing 17% tillage crops, 33% grasses, and 50% cereal grains), disrupt the top layer of unprotected soil, decrease soil organic matter content, impoverish soil physical–chemical properties and instigate landscape leveling. The mean annual erosion rates under the field crop rotation were 9.9, 23.4, and 32.2 Mg ha-1 year-1, respectively, from slopes of 2–5°, 5–10°, and 10–14°. Erosionpreventive grass-grain crop rotations (containing 67% grasses and 33% cereal grains), as well as the sod-forming perennial grasses for long-term use, decreased mean annual erosion rates by 75–80% compared with the field crop rotation. Both land use systems ensure increasing soil organic matter content, decreasing soil erodibility and increasing soil carbon sequestration, helping to decrease atmospheric CO2 concentrations and thus positively influencing global climate changes. These land use systems can be considered as soil conserving, sustainable systems ensuring environmental security on the vulnerable hilly undulating agricultural landscape.

Keywords: Soil erosion; soil conservation strategy; land use systems; soil organic matter; energy accumulated; sustainable development

Keywords

Soil Erosion Crop Rotation Soil Loss Perennial Grass Spring Barley 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer 2008

Authors and Affiliations

  • Benediktas Jankauskas
    • 1
  • Genovaite Jankauskiene
    • 1
  • Algimantas Tiknius
    • 2
  1. 1.Kaltinenai Research Station of Lithuanian Agriculture InstituteLithuania
  2. 2.Department of Geophysical SciencesKlaipeda UniversityLithuania

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