کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8487642 | 1552040 | 2015 | 7 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Simulating effects of grazing on soil organic carbon stocks in Mongolian grasslands
ترجمه فارسی عنوان
شبیه سازی اثرات چرا بر روی ذخایر کربن آلی خاک در مراتع مغولستان
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کلمات کلیدی
بیش از حد ریشگی، تجمع کربن، مدل سازی، مغولستان،
موضوعات مرتبط
علوم زیستی و بیوفناوری
علوم کشاورزی و بیولوژیک
علوم زراعت و اصلاح نباتات
چکیده انگلیسی
Grassland degradation is a major issue in many parts of the world. Rehabilitation of areas that have been degraded by overgrazing can potentially accumulate soil carbon, but there have been few studies in the vast grasslands of Mongolia. Here, we calibrated and validated Century model with 618 measurements from a soil inventory covering four grassland types in a forest steppe region of Mongolia. Soil organic carbon (SOC) simulated by Century largely agreed with the observational dataset and the sign of SOC response to intensive grazing. We employed the calibrated model to assess SOC accumulation under reduced grazing intensity scenarios, and the projected accumulation rates were 22.0-36.9 g C mâ2 yrâ1 in the near term (2012-2035). These results imply that reducing the intensity of grazing may be an effective strategy for restoration of degraded grasslands, which can be implemented by reducing livestock numbers and/or by changing the timing and duration of grazing events. Moreover, the simulated SOC accumulation was mainly determined by a conceptual slow pool, which was not supported by experimental observations in similar soils. Therefore, evaluating the long-term climate mitigation through soil carbon accumulation in degraded grasslands still warrants further attention.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Agriculture, Ecosystems & Environment - Volume 212, 20 December 2015, Pages 278-284
Journal: Agriculture, Ecosystems & Environment - Volume 212, 20 December 2015, Pages 278-284
نویسندگان
Xiaofeng Chang, Xiaoying Bao, Shiping Wang, Andreas Wilkes, Baasandai Erdenetsetseg, Batkhishig Baival, Danzan-osor Avaadorj, Temuujin Maisaikhan, Bolormaa Damdinsuren,