Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
8845050 | Ecological Indicators | 2018 | 10 Pages |
Abstract
Climate change is known to have an impact on the vegetation and on the well-being of ecosystems. Whereas there is a limited number of studies which have assessed historical vegetation changes in the Mongolian Plateau (MP), there are even fewer considering future changes. This paper therefore fills a gap in the literature, by investigating such changes in temporal and spatial scales, and by assessing their effects (1982-2100). The methods used in the study mainly included Pearson correlation and Mann-Kendall test. Results showed that climate extremes in MP, significantly influence vegetation growth. In addition, vegetation trends in MP, vary according to different scenarios. Potentially vulnerable areas of grassland and forest in the future are pointed out. Among the adaptation options available, better management of farmland and water resources should be pursued, and planting of vegetation types should be considered separately. Improvement of the barren area in MP requires international cooperation between Mongolia and China and it is necessary to integrate adaptation options into relevant policies. For mitigation, the projection indicates the emission under Scenario A1B is better for grass growth in MP and great attention should be paid to the greenhouse gas (GHG) emissions from grassland systems in detail, apart from the high quality and low GHG emission animal species, the types of intake grass also need to be seriously considered. In addition, management of sheepfolds in MP is also an important way to reduce GHG emissions. The results from this study will provide useful information about appropriate adaptation and mitigation strategies which may influence vegetation growth in MP.
Related Topics
Life Sciences
Agricultural and Biological Sciences
Ecology, Evolution, Behavior and Systematics
Authors
Chunlan Li, Walter Leal Filho, Jun Wang, Jie Yin, Mariia Fedoruk, Gang Bao, Yuhai Bao, Shan Yin, Shan Yu, Richa Hu,