The long-term dynamic evolution and underlying mechanisms of coastal landscape pattern stability,driven by strong anthropogenic interference and consequently climate change,are topics of major interest in national and...The long-term dynamic evolution and underlying mechanisms of coastal landscape pattern stability,driven by strong anthropogenic interference and consequently climate change,are topics of major interest in national and international scientific research.Guangdong Province,located in southeastern China,has been undergoing rapid urbanization over several decades.In this study,we quantitatively determined the scale threshold characteristics of coastal landscape pattern stability in Guangdong Province,from the dual perspective of spatial heterogeneity and spatial autocorrelation.An analysis of the spatiotemporal evolution of the coastal landscape was conducted after the optical scale was determined.Then,we applied the geodetector statistical method to quantitatively explore the mechanisms underlying coastal landscape pattern stability.Based on the inflection point of landscape metrics and the maximum value of the MoranⅠindex,the optimal scale for analyzing coastal landscape pattern stability in Guangdong Province was 240 m×240 m.Within the past several decades,coastal landscape pattern stability increased slightly and then decreased,with a turning point around 2005.The most significant variations in coastal landscape pattern stability were observed in the transition zone of rural-urban expansion.A q-statistics analysis showed that the explanatory power of paired factors was greater than that of a single driving factor;the paired factors with the greatest impact on coastal landscape pattern stability in Guangdong Province were the change in gross industrial output and change in average annual precipitation from 2010 to 2015,based on a q value of 0.604.These results will contribute to future efforts to achieve sustainable coastal development and provide a scientific basis and technical support for the rational planning and utilization of resources in large estuarine areas,including marine disaster prevention and seawall ecological restoration.展开更多
For the sake of exploring how the pattern of Chinese pine （Pinus massoniana Lamb） community changed after the invasion of the pine wood nematode （Bursaphelenchus xylophilus （Steiner ＆ Buhrer） Niclde） in Zhousha...For the sake of exploring how the pattern of Chinese pine （Pinus massoniana Lamb） community changed after the invasion of the pine wood nematode （Bursaphelenchus xylophilus （Steiner ＆ Buhrer） Niclde） in Zhoushan, Zhejiang Province, we established a test area in the local Chinese pine community. Landsat5 TM images from 1991 and 2006 were integrated with auxiliary data from field investigation and spectral data as additional sources of information. A method of expert knowledge classifier was applied to establish the expert knowledge dataset of the main vegetation cover types from which we obtained a forest type distribution map. The spatial patterns and stability of the forest, before and after the invasion of the pine wood nematode, were analyzed in terms of community patterns. The results indicated that the predominant coniferous forest type changed to a mixed forest. As a result, the forest structure became complex and the interaction between coniferous forest patches became weakened over the period from 1991 to 2006. Therefore, the resistance of the forest eco-system to plant diseases and insect pests and the stability of forest eco-system enhanced.展开更多
基金The National Natural Science Foundation of China under contract Nos 42201104 and 42071123the China Postdoctoral Research Foundation under contract No.2023M730758.
文摘The long-term dynamic evolution and underlying mechanisms of coastal landscape pattern stability,driven by strong anthropogenic interference and consequently climate change,are topics of major interest in national and international scientific research.Guangdong Province,located in southeastern China,has been undergoing rapid urbanization over several decades.In this study,we quantitatively determined the scale threshold characteristics of coastal landscape pattern stability in Guangdong Province,from the dual perspective of spatial heterogeneity and spatial autocorrelation.An analysis of the spatiotemporal evolution of the coastal landscape was conducted after the optical scale was determined.Then,we applied the geodetector statistical method to quantitatively explore the mechanisms underlying coastal landscape pattern stability.Based on the inflection point of landscape metrics and the maximum value of the MoranⅠindex,the optimal scale for analyzing coastal landscape pattern stability in Guangdong Province was 240 m×240 m.Within the past several decades,coastal landscape pattern stability increased slightly and then decreased,with a turning point around 2005.The most significant variations in coastal landscape pattern stability were observed in the transition zone of rural-urban expansion.A q-statistics analysis showed that the explanatory power of paired factors was greater than that of a single driving factor;the paired factors with the greatest impact on coastal landscape pattern stability in Guangdong Province were the change in gross industrial output and change in average annual precipitation from 2010 to 2015,based on a q value of 0.604.These results will contribute to future efforts to achieve sustainable coastal development and provide a scientific basis and technical support for the rational planning and utilization of resources in large estuarine areas,including marine disaster prevention and seawall ecological restoration.
文摘For the sake of exploring how the pattern of Chinese pine （Pinus massoniana Lamb） community changed after the invasion of the pine wood nematode （Bursaphelenchus xylophilus （Steiner ＆ Buhrer） Niclde） in Zhoushan, Zhejiang Province, we established a test area in the local Chinese pine community. Landsat5 TM images from 1991 and 2006 were integrated with auxiliary data from field investigation and spectral data as additional sources of information. A method of expert knowledge classifier was applied to establish the expert knowledge dataset of the main vegetation cover types from which we obtained a forest type distribution map. The spatial patterns and stability of the forest, before and after the invasion of the pine wood nematode, were analyzed in terms of community patterns. The results indicated that the predominant coniferous forest type changed to a mixed forest. As a result, the forest structure became complex and the interaction between coniferous forest patches became weakened over the period from 1991 to 2006. Therefore, the resistance of the forest eco-system to plant diseases and insect pests and the stability of forest eco-system enhanced.
