| Surface albedo is a key element of hydrological cycle and plays an important role in energy distribution of terrestrial and atmospheric systems.It plays a key role in the steady-state formation of regional and even global climate.Understanding the dynamics in surface albedo is very important to the energy cycle of ecosystem and its relationship with environmental change.This study measured surface albedo of urban greed-land ecosystem in Beijing Olympic Forest Park by in situ continuous monitoring from 2013 to 2017.Our objective was to study dynamic eharacterize about surface albedo at different time scales and examine its effect on gross primary productivity(GPP).The main results were as follows:(1)Surface albedo of Beijing Olympic Forest Park had obvious variation character:istics in different time scales.Diurnal variation of surface albedo in the growing season was characterized by a gradual decrease from 8:30 to 12:00 in the morning and relatively constant values from 12:00 at noon to 17:00 in the afternoon.The main controlling factor of the diurmal variation of surface albedo was the dew on the surface of morning plant leaves.The variation of surface albedo were the largest in winter and the smallest in suumer.The surface albedo in spring was larger than that in autumn.Seasonal variation of surface albedo was affected by multiple factors.(2)Surface albedo showed an exponential and negative relationship with air temperature in the growing season.The response threshold of surface albedo to air temperature was 20℃ in years of 2013-2016,and that in 2017 was 15℃.In different phenological stages,the correlation between surface albedo and air temperature was differed.During leaf-expanding period,surface albedo was linear and negative correlation with air temperature.During leaf-expanded and lead-falling periods,surface albedo was exponential and negative relationship with air temperature.(3)Surface albedo showed an exponential and negative relationship with soil water content in the growing season,with different threshold of soil water content in different years.And the response thresholds from 2013 to 2017 were 12%,18%,12%,15%and 20%,respectively.During the leaf-expanding stage,there was no significant correlation between surface albedo and soil water content.During the leaf-expanded and leaf-falling periods,surface albedo was exponential and negative relationship with soil water content.(4)Surface albedo showed a liner and negative correlation with relative humidity in the growing season,and relative humidity from 2013 to 2017 could account for 63%,23%,19%,52%,38%of change in surface albedo.There was a inter-annual difference in surface albedo sensitivity to relative humidity.(5)Surface albedo showed an exponential and negative correlation with soil temperature in the growing season,with different threshold of soil temperature in different years.Soil temperature from 2013 to 2017 could account for 71%,65%,61%,73%,and 58%of the change in surface albedo in the growing season.(6)The correlation coefficient between surface albedo and vegetation cover index was different in different years.There was a seasonal difference in correlation coefficient in the same year,with a correlation coefficient being negative firstly,then becoming positive,and getting finally negative(7)Surface albedo showed a linear and negative correlation with GPP in the growing season from 2013 to 2017.There were inter-annual differences in the linear regression model parameters of GPP and surfaee albedo.And there was a certain difference in the sensitivity of GPP to surface albedo.In conclusion,the albedo of urban forest was affected by vegetation and environmental factors.The albedo thresholds of air temperature,soil water content and soil temperatiure were 83℃,15.4%,17.5℃This study reveals the dynamic characteristics of surface albedo in Beijing Olympic Forest Park and its impact on gross primary productivity.The research results have important significance for understanding the dynamic changes of surface albedo in urban green space ecosystem and its ecosystem carbon cycle. |
