تاثیر نوسانات اقلیمی بر درصد پوشش تاجی گونه های علوفه ای شاخص مراتع استپی قوشه سمنان

نوع مقاله: مقاله پژوهشی

نویسندگان

1 دانش آموخته کارشناسی ارشد، مرتعداری، گروه مهندسی مرتع و آبخیزداری، دانشکده منابع طبیعی، دانشگاه کردستان، سنندج، ایران

2 استادیاردانشکده منابع طبیعی، دانشگاه کردستان، سنندج، ایران،

3 استادیارگروه مهندسی مرتع و آبخیزداری، دانشکده منابع طبیعی، دانشگاه کردستان، سنندج، ایران

چکیده

در این پژوهش، ضمن پایش روند تغییرات درصد پوشش تاجی گونه­های شاخص مراتع استپی منطقه قوشه در استان سمنان طی یک دوره ده‌ساله؛ ارتباط بین دو عامل مهم اقلیمی (بارش و دما) و تغییرات درصد پوشش تاجی نیز بررسی شد. بدین منظور، درصد پوشش تاجی شش گونه گیاهی شاخص (به تفکیک گونه) و گیاهان یک‌ساله بصورت ترکیبی مصــادف بــا رشد کامل گونه­ها، بر روی دو ترانسکت 250 متری و در 30 پلات دو متر مربعی(به فواصل 15 متر از هم) بصورت سالانه و به مدت 10 سال اندازه­گیری شد. نتایج نشان داد که بالاترین مقدار درصد پوشش تاجی، در سال آبی 86-1385 (با بارش بیش از میانگین دوره) و کمترین مقدار آن در سال آبی 92-1391 (با بارش کمتر از میانگین دوره) و به ترتیب معادل 15 و 5/5 درصد بود. مدل­سازی درصد پوشش تاجی براساس روش رگرسیونی خطی و با استفاده از متغیرهای بارش و دما انجام گرفت. نتایج نشان داد که بارش­های یک ماهه فروردین، قادر است 65 درصد تغییرات درصد پوشش تاجی گونه A. sieberiرا در سطح اطمینان 95 درصد توجیه نماید (با 26/0=RRMSE و 49/0 =MAE). بهترین مدل ارائه شده برای برآورد درصد پوشش تاجی گونه­های S. barbata و Z. eurypterum، مربوط به مدل مبتنی بر بارش چهار ماهه اسفند تا خرداد و مدل مبتنی بر بارش یک ماهه اسفند بود که به ترتیب 77 (در سطح اطمینان 99 درصد) و 67 (در سطح اطمینان 95 درصد) درصد تغییرات تاج پوشش این گونه­ها را توجیه می­نمایند. با توجه به نقش قابل توجه گونـه­های A. sieberi، S. barbata و Z. eurypterum در ترکیب پوشش گیاهی مراتع مورد پژوهش، می­توان بیان نمود که بخش عمده تغییـرات پوشش تاجی، براساس تغییـرات بارش دوره رویـش، قابل پیش‌بینی می­باشد.

کلیدواژه‌ها


عنوان مقاله [English]

The effects of climate variability on canopy cover percentage of forage species in Ghosheh steppe Rangelands, Semnan Province

نویسندگان [English]

  • Nahid Azizi 1
  • Hamed Joneidi 2
  • Khaled Osati 3
1 MSc student, Department of Range and Watershed Management, College of Natural Resources, University of Kurdistan,Sanandaj, Iran
2 Assistant professor, Department of Range and Watershed Management, College of Natural Resources,University of Kurdistan,sanangdaj,Iran
3 Assistant professor, Department of Range and Watershed Management, College of Natural Resources, University of Kurdistan,sanangdaj,Iran
چکیده [English]

    This research monitored changes in canopy cover percentage of typical species during a 10-year period in the Ghosheh rangelands to find out the relationship between two important climate variables (precipitation and temperature) and canopy cover changes. Therefore, the canopy cover percentages of six typical species (separately) and annual species (overall) were measured during 10 years at the end of growing season in thirty 2-m2 plots, distributed along two 250–m transect lines. The results demonstrated that the maximum canopy cover percentage for water year 2006-2007 (wet-year) and the minimum value for water year 2012-2013 (drought) were 15% and 5.5%, respectively. The canopy cover percentage modeling was performed based on linear regression method using precipitation and temperature variables. The precipitation of April explained 65% of changes in canopy cover percentage of A. sieberiat 95% confidence level (RRMSE = 0.26 & MAE=0.49). The best simple linear regression model for estimating  canopy cover percentage of S. barbata and Z. eurypterum was introduced by total  precipitation of March-June and precipitation of March, representing 77% (at 99% confidence level) and 67% (at 95% confidence level) of changes in canopy cover, respectively. Considering the dominant role of A. sieberi, S. barbata and Z. eurypterum in vegetation composition of study areas, it can be concluded that most changes in canopy cover of the studied rangeland are predictable by variabilityofprecipitation during growing seasons.

کلیدواژه‌ها [English]

  • Canopy Cover
  • Climatic variability
  • precipitation
  • Linear regression
  • Ghosheh
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