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Study On Resilience Thresholds Of Subtropical Forest Ecosystem Under Ice-Snow Frozen Disaster

Posted on:2019-07-29Degree:MasterType:Thesis
Country:ChinaCandidate:W LiFull Text:PDF
GTID:2370330545971194Subject:Surveying and mapping engineering
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Recently,the globally climate change and the unbalance between human demands and natural resources result in the high frequency of extreme weathers.It not only brings out the heavy cost of human life and production,but also destroys the forest ecosystem which results in the vicious circle between the reduction of the forest coverage rate and aggravation of climate problem.How to reduce the cost of forests damaged by climate change and prevent regime shift of forests become the hot topic.Researches of forest resilience threshold determination provides a new ideal for this.Therefore,this thesis does the research on the threshold determination of subtropical forest resilience in Dao County and Jianghua Yao Autonomous County areas under the south snow disaster in 2008.The main research is shown below:(1)The regime shift area of the forest was extracted under the snow disaster in2008 and study on its distribution before the disaster to ensure the range of area which is high likely to occur regime shift.(2)The most representative and widely distributed cedar forests,broad-leaved forests,and masson pine forests in the study area were selected as research objects,and detailed statistics were made on the distribution of system resilience in the study area and in the study area.(3)Analyze the relationship between the probability of regime shift and the system resilience of the cedar forest,broad-leaved forest,and masson pine forest in the statistical sense,and compare the differences among the three.(4)Explore whether there is a link between the probability of regime shift in the forests of pine,broad-leaved forest,and masson pine and the altitude under the influence of snow disasters;and explore the performance of relationship between the probability of forest regime shift and the resilience within each elevation range.The analysis results show that the relationship between the probability of regime shift in forests of different tree species and the system resilience is different under the influence of ice and snow disasters: the basic regime shift probability of Chinese fir forests decreases with the increase of forest ecosystem resilience.Broad-leaved forests show that the shift probability is higher in the range of low resilience,and then become basically a normal distribution with increase of ecosystem resilience.And the forest ecosystem has the highest regime shift when resilience in the range of 0.38 to 0.39;The masson pine regime shift fluctuation is small.The forest ecosystem has lowest regime shift when the resilience is between 0.32~0.33 and 0.39~0.40.In addition,the regime shift probability of fir,broad-leaved forest and masson pine forest is related to altitude.When the altitude is less than 800 meters,the probability of regime shift occurs for the same altitude: masson pine forest>cedar forest>broad-leaved forest.When the altitude exceeds 800 meters,the probability of regime shift of the forest for the same altitude is: cedar forest>broad-leaved forest>masson pine forest.Under the disturbance of ice and snow,the probability of regime shift between the sunny and semi-sunny forests is higher than that of the shady and semi-shady slopes.Through the study on the threshold determination of the restoration force of the ecosystems of the cedar forest,broad-leaved forest,and masson pine forest in Dao County and Jianghua County in 2008,the resilience interval and altitude threshold point with high regime shift probability were determined.it provides scientific basis and data reference for similar disaster events in the future and it is great significance for timely determination of severely affected areas and reducing the probability of steady state transition.
Keywords/Search Tags:Resilience, Regime shift, Thresholds, Remote sensing interpretation, Ice-Snow frozen disaster, Subtropical forest
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