祁连山天涝池流域亚高山草地土壤呼吸对放牧的响应

发布时间：2018-09-04 06:40

【摘要】：高寒草地生态环境脆弱,是气候变化的敏感区域,且人为干扰严重,超载放牧导致草地不断退化。在全球变暖大背景下,开展高寒草地土壤呼吸研究不仅起到预示作用,还可为管理者在决策时提供科学理论支撑。祁连山区草地资源丰富,其中高寒草地面积达3.56×105 hm2,占草地面积的36.1%,对祁连山的高寒草地土壤呼吸进行研究在一定程度上可反映中国西北地区草地碳循环状况。本研究利用L1-8100土壤碳通量自动测量系统对祁连山天涝池流域的亚高山草地土壤呼吸(Rs)和生态系统呼吸(Re)进行观测,分析土壤呼吸和生态系统呼吸的时间变化动态与环境因子(土壤温度Ta,地表温度Ts、土壤体积含水量VWC、地表相对湿度RH)、光谱指数(NDVI、EVI、CIrededge)、植被生理生态参数(生物量、比叶面积、单叶面积、草高度、叶片含水量、)的关系,并通过3种模拟放牧手段,即添加牦牛粪(0、1000、1500、3000 g·m-2)、割草(割草量占生物量的0%、45—50%、60—75%)和刈割年限(刈割1年、2年、3年)分别研究排泄物、采食和放牧年限对亚高山草地土壤呼吸(Rs)和生态系统呼吸(Re)的影响,主要结论如下:(1)Re和Rs在日变化和月变化上均表现为明显的单峰曲线模式。在日变化动态中,Re和Rs从8:00观测开始逐渐增大,分别于13:00和14:00达到最大值后逐渐下降(Re=18.31±6.26μmol·m-2·s-1,Rs=5.82±1.18μmol·m-2·s-1),Re和Rs在生长季的日均值分别为9.89±0.69μmol·m-2·s-1、3.78±0.21μmol·m-2·s-1。在月变化动态中,呼吸速率在生长季初期最低,随着地表温度和土壤温度的逐渐升高,呼吸速率也逐渐加大,Re在7月底或8月初达到最大值(2014年,Re=21.39±1.43μmol·m-2·s-1;2015年,Re=20.95±2.663μmol·m-2·s-1),Rs在8月初达到最大值(2014年,Rs=8.09±0.28μmol·m-2·s-1;2015年,Rs=6.13±0.58μmol·m-2·s-1)。Re和Rs在生长季的月均值分别为11.06±0.06μmol·m-2·s-1、4.23±0.62μmol·m-2·s-1。在生态系统呼吸测定中,最适测量时间为9—11:00,在土壤呼吸测定中,最适测量时间为9—12:00。(2)呼吸速率与地表温度和土壤温度均呈显著指数相关(P0.05),且与土壤温度的相关性更大;呼吸速率与地表相对湿度呈极显著线性相关(P0.0001),与5、10、20 cm处土壤体积含水量均无相关性。温湿度复合模型显示,Re主要受土壤温度控制,而Rs受土壤温度、水分共同控制。在土壤呼吸组中,R=aebTWc为最佳模型,在生态系统呼吸组中,R=aebT+cW为最佳模型。(3)呼吸速率与光谱指数(VIs)的关系与草地状态有关。在禁牧草地中,Re与CIrededge的相关性最高,R2高达0.72;在放牧草地中,Re与NDVI的相关性最好,NDVI可以解释Re变异的66%;而Rs与光谱指数无显著相关性。(4)地上生物量、草高度、比叶面积、单叶面积和叶片含水量与Re均具有显著相关性(P0.05),它们可以分别解释Re变异的44%、60%、64%、48%和47%。(5)牛粪按梯度0、1000、1500、3000 g·m-2添加到土壤表面后对土壤呼吸有促进作用,且牛粪越多,土壤呼吸越大,并达到显著性差异(P0.05)。4种牛粪添加量下的土壤呼吸日均值分别为4.12、4.32、4.38、5.35μmol·m-2·s-1,月均值分别为4.53、4.70、5.47、6.60μmol·m-2·s-1。(6)割草处理降低了生态系统呼吸速率,但两两之间差异并不显著。未割草、中度割草和重度割草生态系统呼吸速率日均值分别为11.70、10.21、8.14umol·m-2·s-1,月均值分别为11.87、11.36、9.91 umol·m-2·s-1。刈割年限越长,土壤呼吸速率越低,但影响作用并不显著。
[Abstract]:Alpine grassland is a vulnerable ecological environment, which is sensitive to climate change. Grassland degradation is caused by serious human disturbance and overloading grazing. Under the background of global warming, soil respiration research on alpine grassland not only plays a predictive role, but also provides scientific and theoretical support for managers in decision-making. The area of alpine grassland is 3.56 *105 hm2, accounting for 36.1% of the grassland area. The study on soil respiration of Alpine Grassland in Qilian Mountains can reflect grassland carbon cycle in Northwest China to a certain extent. The temporal variation of soil respiration and ecosystem respiration and environmental factors (soil temperature Ta, surface temperature Ts, soil volume water content VWC, surface relative humidity RH), spectral index (NDVI, EVI, CIrededge), vegetation physiological and ecological parameters (biomass, specific leaf area, single leaf area, grass height, leaf height) were analyzed. The effects of excreta, feeding and grazing years on soil respiration (Rs) and ecosystem respiration (Re) in subalpine grassland were studied by three simulated grazing methods, i.e. adding yak manure (0,1000,1500,3000 g m-2), mowing (0%, 45-50%, 60-75% of biomass) and cutting years (1, 2, 3 years of mowing). The main conclusions are as follows: (1) Re and Rs show obvious unimodal curve patterns in both diurnal and monthly variations. Re and Rs increase gradually from 8:00 to 13:00 and decrease gradually after reaching their maximum values at 14:00 and 13:00 respectively (Re = 18.31 6.26_ m ol M 2 s 1, Rs = 5.82 1.18_ m ol M 2 Respiration rate was the lowest at the beginning of the growing season. Respiration rate increased gradually with the increase of surface temperature and soil temperature. Re reached its maximum at the end of July or the beginning of August (in 2014, Re = 21.39 + 1.43 micromol. m - 2. s - 1; in 2015, Re = 20.95 + 2.663 Re and Rs reached their maximum values in early August (in 2014, Rs = 8.09.28 m-2 65 (2) Respiration rate had a significant exponential correlation with surface temperature and soil temperature (P 0.05), and had a greater correlation with soil temperature; Respiration rate had a very significant linear correlation with surface relative humidity (P 0.0001), and had no correlation with soil bulk water content at 5,10,20 cm. In the soil respiration group, R = aebTWc was the best model, and in the ecosystem respiration group, R = aebT + cW was the best model. (3) The relationship between respiration rate and spectral index (VIs) was related to grassland status. In grazing grassland, Re and NDVI had the best correlation, NDVI could explain 66% of Re variation, while Rs had no significant correlation with spectral index. (4) Above ground biomass, grass height, specific leaf area, single leaf area and leaf water content had significant correlation with Re (P 0.05), which could explain 44%, 60%, 64%, 48% and 47% of Re variation respectively. The daily mean values of soil respiration were 4.12, 4.32, 4.38, 5.35 micromol M 2 s 1, and the monthly mean values were 4.53, 4.70, 5.47, 6.60 micromol M 2 s 1, respectively. The daily average respiration rates of the ecosystems without mowing, moderate mowing and severe mowing were 11.70, 10.21, 8.14 umol M 2 s 1 and 11.87, 11.36, 9.91 umol M 2 s 1, respectively. The longer the mowing years, the lower the soil respiration rates, but the effect was not obvious. It is.
【学位授予单位】：兰州大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：S812.2

【相似文献】