Due to the Tibetan Plateau's unique high altitude and low temperature climate conditions,the region's alpine steppe ecosystem is highly fragile and is suffering from severe degradation under the stress of increasing population,overgrazing,and climate change.The soil stoichiometry,a crucial part of ecological stoichiometry,provides a fundamental approach for understanding ecosystem processes by examining the relative proportions and balance of the three elements.Understanding the impact of degradation on the soil stoichiometry is vital for conservation and management in the alpine steppe on the Tibetan Plateau.This study aims to examine the response of soil stoichiometry to degradation and explore the underlying biotic and abiotic mechanisms in the alpine steppe.We conducted a field survey in a sequent degraded alpine steppe with seven levels inNorthern Tibet.The plant species,aboveground biomass,and physical and chemical soil properties such as the moisture content,temperature,pH,compactness,total carbon(C),total nitrogen(N),and total phosphorus(P)were measured and recorded.The results showed that the contents of soil C/N,C/P,and N/P consistently decreased along intensifying degradation gradients.Using regression analysis and a structural equation model(SEM),we found that the C/N,C/P,and N/P ratios were positively affected by the soil compactness,soil moisture content and species richness of graminoids but negatively affected by soil pH and the proportion of aboveground biomass of forbs.The soil temperature had a negative effect on the C/N ratio but showed positive effect on the C/P and N/P ratios.The current study shows that degradation-induced changes in abiotic and biotic conditions such as soil warming and drying,which accelerated the soil organic carbon mineralization,as well as the increase in the proportion of forbs,whichwere difficult to decompose and input less organic carbon into soil,resulted in the decreases in soil C/N,C/P,and N/P contents to a great extent.Our results provide a sound basis for sustainable conservation and management of the alpine steppe. 相似文献
高分六号卫星具有覆盖广、多种分辨率、波段多的优势,能为遥感解译提供更丰富的信息。为探究高分六号卫星新增波段在森林树种识别上的应用,本文以覆盖根河市阿龙山林业局的一期高分六号宽幅影像为数据源,基于特征优化空间算法(Feature Space Optimization,FSO)和最大似然分类法,分别利用高分六号的前4个波段和所有波段(8波段)的光谱、纹理等特征进行了森林树种分类,并逐一添加新增波段特征确定了各波段的贡献率排名。结果表明:在加入了优选出的均匀性纹理、均值纹理和角二阶矩纹理3种纹理特征后,前4波段和8波段的分类精度比只基于光谱特征时的精度分别高出13.23%和24.63%;利用8波段信息比只利用前4波段在基于光谱特征上的精度高11.88%,在基于光谱+纹理特征上则高23.24%;基于8波段光谱+纹理特征的树种分类精度最高,达到68.74%,新增4波段的贡献率排名为B6>B5>B8>B7,说明新增红边波段对于本次树种分类试验的贡献率最高,能为北方树种识别提供有效帮助。 相似文献
In many arid ecosystems, vegetation frequently occurs in high-cover patches interspersed in a matrix of low plant cover. However, theoretical explanations for shrub patch pattern dynamics along climate gradients remain unclear on a large scale. This context aimed to assess the variance of the Reaumuria soongorica patch structure along the precipitation gradient and the factors that affect patch structure formation in the middle and lower Heihe River Basin (HRB). Field investigations on vegetation patterns and heterogeneity in soil properties were conducted during 2014 and 2015. The results showed that patch height, size and plant-to-patch distance were smaller in high precipitation habitats than in low precipitation sites. Climate, soil and vegetation explained 82.5% of the variance in patch structure. Spatially, R. soongorica shifted from a clumped to a random pattern on the landscape towards the MAP gradient, and heterogeneity in the surface soil properties (the ratio of biological soil crust (BSC) to bare gravels (BG)) determined the R. soongorica population distribution pattern in the middle and lower HRB. A conceptual model, which integrated water availability and plant facilitation and competition effects, was revealed that R. soongorica changed from a flexible water use strategy in high precipitation regions to a consistent water use strategy in low precipitation areas. Our study provides a comprehensive quantification of the variance in shrub patch structure along a precipitation gradient and may improve our understanding of vegetation pattern dynamics in the Gobi Desert under future climate change.