首页 | 本学科首页   官方微博 | 高级检索  
文章检索
  按 检索   检索词:      
出版年份:   被引次数:   他引次数: 提示:输入*表示无穷大
  收费全文   3篇
  免费   0篇
畜牧兽医   3篇
  2019年   1篇
  2016年   2篇
排序方式: 共有3条查询结果,搜索用时 421 毫秒
1
1.
In a context of water scarcity, efforts to increase landscape production should focus on improving water productivity. This requires an appreciation of the various components of evapotranspiration (ET), including soil evaporation (Es) because the latter reflects ‘unproductive’ water loss. Both complex and simple algorithms have been developed to determine ET. In data scarce areas, developing and testing parsimonious algorithms is useful. This study sought to improve a simple single layer ET model by incorporating an Es component. Empirical methods were also explored to predict ET from vegetation indices (VIs), leaf area index (LAI) and reference evapotranspiration (ET0). A large aperture scintillometer and an eddy covariance (EC) system were used to validate the proposed algorithm at three sites over Grasslands and Albany Thicket biomes in the Eastern Cape, South Africa. There was good agreement between the observed and predicted ET with RMSE of 0.30–0.58 mm d?1 when average daily observed ET was 0.43–3.24 mm. The VIs had moderate correlations with the observed data due to the significant role played by Es (65%–84%) across the sites and stomatal conductance at the Albany Thicket site. The simple algorithms developed would make determining ET easier in data scarce regions.  相似文献   
2.
Following a field campaign to determine the species composition, canopy cover, aboveground annual production and leaf area index (LAI) of the semi-arid savanna of north-western Namibia, we present a production model that can be used by graziers to determine the livestock carrying capacity. The model predicts the annual aboveground net primary production (ANPP) from regression equations of canopy cover by annual production fraction for plant functional classes. We tested the output of the model against another fully independent net primary production (NPP) model, namely the MODIS NPP product. The mean MODIS NPP for the 29 sites was 343 ± 22?kg dry matter (DM) ha?1 y?1 as opposed to 285 ± 142?kg DM ha?1 y?1 for the fAP model that used the regression method (p < 0.01). As a proof of concept, these landscape-scale ANPP values are used to calculate a recommended livestock carrying capacity for the Ehirovipuka Communal Conservancy, a 1 980 km2 communal area with both wildlife and livestock populations. In addition, we also provide details of a field method for predicting landscape-scale LAI from line transect data. This approach can be used to ground reference the LAI values generated from the MODIS LAI product.  相似文献   
3.
Australian acacias have spread to many parts of the world. In South Africa, species such as A. mearnsii and dealbata are invasive. Consequently, more effort has focused on their clearing. In a context of increasing clearing costs, it is crucial to develop innovative ways of managing invasions. Our aim was to understand the biophysical properties of A. mearnsii in grasslands as they relate to grass production and to explore management implications. Aboveground biomass (AGB) of A. mearnsii was determined using a published allometric equation in invaded grasslands of the northern Eastern Cape, South Africa. The relationships among the A. mearnsii leaf area index (LAI), normalised difference vegetation index (NDVI) and AGB were investigated. The influence of A. mearnsii LAI and terrain slope on grass cover was also investigated. Strong linear relationships between NDVI, LAI and AGB were developed. Acacia mearnsii canopy adversely impacted grass production more than terrain slope (p < 0.05) and when LAI approached 2.1, grass cover dropped to below 10% in infested areas. Reducing A. mearnsii canopy could promote grass production while encouraging carbon sequestration. Given the high AGB and clearing costs, it may be prudent to adopt the ‘novel ecosystems’ approach in managing infested landscapes.  相似文献   
1
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号