کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5761229 | 1624435 | 2017 | 11 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Modelling productivity and resource use efficiency for grassland ecosystems in the UK
ترجمه فارسی عنوان
بهره وری مدل سازی و بهره وری منابع برای اکوسیستم های علفزار در انگلستان
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کلمات کلیدی
مزرعه بهبود یافته، نیمه طبیعی مدل تعامل سینک منبع، مقیاس بالا تعادل آب
موضوعات مرتبط
علوم زیستی و بیوفناوری
علوم کشاورزی و بیولوژیک
علوم زراعت و اصلاح نباتات
چکیده انگلیسی
Estimating spatially resolved grassland productivity is essential for benchmarking the total UK productive potential to assess food, feed and fuel trade-offs in the context of whole systems analyses. Our objectives were to adapt and evaluate a well-known process-based model (PBM) and estimate productivity of improved (permanent, temporary) and semi-natural grassland systems using meta-models (MM) trained by extensive PBM scenario simulations. Observed dry matter (DM) yields in multi-site nitrogen (N) response (0, 150 and 300 kg N haâ1) experiments were well emulated describing the average productivity of rough grazing, permanent and temporary grassland (3.1, 7.4 and 9.8 t DM haâ1, respectively). Cross-validated with independent and long-term data (Park Grass Experiment), the PBM explained more variation when considering all systems combined (81%) than across all improved grasslands (61%) but little for rough grazing (26%). The PBM-trained MMs explained 48, 72 and 70% of the simulated yield variation in the grasslands of increasing management intensity, and 43 and 75% of observed variation in the combined improved and all three grassland systems, respectively. Considering the assessment of ecosystem services, like drainage and water productivity, PBM scenario simulations are essential. Compared to improved grassland rough grazing will result in 40% more groundwater recharge due to its lower simulated water use and water productivity (12 versus 25 and 43 kg haâ1 mmâ1 for permanent and temporary grassland, respectively).
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: European Journal of Agronomy - Volume 89, September 2017, Pages 148-158
Journal: European Journal of Agronomy - Volume 89, September 2017, Pages 148-158
نویسندگان
Aiming Qi, Philip J. Murray, Goetz M. Richter,