研究水热波动和土地覆盖变化对植被净初级生产力(Net Primary Productivity,NPP)的影响对于估算陆地碳循环及其驱动机制具有重要意义。利用MODIS遥感影像获得的时间序列NPP和土地覆盖产品,结合气象观测数据(气温和降水),采用相关分析、...研究水热波动和土地覆盖变化对植被净初级生产力(Net Primary Productivity,NPP)的影响对于估算陆地碳循环及其驱动机制具有重要意义。利用MODIS遥感影像获得的时间序列NPP和土地覆盖产品,结合气象观测数据(气温和降水),采用相关分析、回归分析和空间分析相结合的方法,研究2000—2015年东北地区植被NPP的时空变化特征,并定量评估水热波动和土地覆盖变化对该地区植被NPP的相对影响。研究结果表明,2000—2015年东北地区植被NPP呈波动上升趋势,从2000年的369.24 g C m^-2 a^-1增加到2015年的453.84 g C m^-2 a^-1,平均值是412.10 g C m^-2 a^-1,年际增加速率为4.54 g C m^-2 a^-1。近16年来东北地区年均植被NPP空间上呈现南高北低、东高西低的分布格局,整体变化趋势以增加为主,其中轻微增加面积占该地区总面积的45.9%。不同土地覆盖类型的年均NPP差异明显,其中灌木最高为400.34 g C m^-2 a^-1,草地最低为300.49 g C m^-2 a^-1。东北地区植被NPP与气温的相关性不明显,而与降水量主要表现为正效应。水热波动对该地区不同土地覆盖类型NPP总量变化的贡献大于土地覆盖变化的贡献,其中对森林和农田的贡献最大,均达到70%以上。展开更多
土地覆盖变化是影响植被净初级生产力(NPP)的关键因素之一.本研究基于MOD17A3 NPP数据和MCD12Q1土地覆盖数据,利用经典统计和空间分析相结合的方法,对2000—2014年山东省植被NPP空间分布格局及其时空变异特征进行定量分析,探讨NPP的时...土地覆盖变化是影响植被净初级生产力(NPP)的关键因素之一.本研究基于MOD17A3 NPP数据和MCD12Q1土地覆盖数据,利用经典统计和空间分析相结合的方法,对2000—2014年山东省植被NPP空间分布格局及其时空变异特征进行定量分析,探讨NPP的时空动态对土地覆盖变化的响应特征,以及土地覆盖变化在植被NPP变化中的贡献率.结果表明,山东省内主要土地覆盖类型为耕地,森林、灌木和草地分布相对较少,其分布状况具有明显的区域性特征;山东省多年平均NPP为368.94 g C·m^(-2)·yr^(-1),空间分布总体上呈现为东南高于西北,沿海高于内陆;2000-2014年山东省四种土地覆盖类型的年平均NPP呈现耕地>森林>灌木>草地的趋势;大部分区域NPP呈上升趋势,但不显著,主要分布在山东中部、西部和西北部,NPP减少显著的区域主要集中在烟台市和青岛市附近;不同土地覆盖类型间存在差异,但整体上土地覆盖变化增加了NPP;草地的贡献率(66.31%)最高,森林次之,再次为灌木,耕地(5.95%)最低.展开更多
In this study,using Moderate Resolution Imaging Spectroradiometer(MODIS)satellite images and environmental satellite CCD images,the spatio-temporal distribution of Ulva prolifera in the southern Yellow Sea during the ...In this study,using Moderate Resolution Imaging Spectroradiometer(MODIS)satellite images and environmental satellite CCD images,the spatio-temporal distribution of Ulva prolifera in the southern Yellow Sea during the period of 2011–2018 was extracted and combined with MODIS Level3 Photosynthetically Active Radiation(PAR)product data and Earth System Research Laboratory(ESRL)Sea Surface Temperature(SST)data to analyze their influences on the growth and outbreak of Ulva prolifera.The following conclusions were drawn:1)comprehensive analysis of Ulva prolifera distribution during the eight-year period revealed that the coverage area of Ulva prolifera typically exhibited a gradually increasing trend.The coverage area of Ulva prolifera reached a maximum of approximately 1714.21 km^2 during the eight-year period in late June 2015.The area affected by Ulva prolifera fluctuated.In mid-July 2014,the area affected by Ulva prolifera reached a maximum of approximately 39020.63 km^2.2)The average growth rate of Ulva prolifera was positive in May and June but negative in July.During the outbreak of Ulva prolifera,the SST in the southern Yellow Sea tended to increase each month.The SST anomaly and average growth rate of Ulva prolifera were positively correlated in May(R^2=0.62),but not significantly correlated in June or July.3)The variation trends of PAR and SST were approximately the same,and the PAR during this time period maintained a range of 40–50 mol/(m^2·d),providing sufficient illumination for the growth and outbreak of Ulva prolifera.In addition,the abundant nutrients and suitable temperature in the sea area near northern Jiangsu shoal resulted in a high growth rate of Ulva prolifera in May.In summary,the outbreak of Ulva prolifera was closely related to the environmental factors including SST,nutrients,and PAR.Sufficient nutrients and suitable temperatures resulted in a fast growth rate of Ulva prolifera.However,under poor nutrient conditions,even more suitable temperatures were not sufficient to trigger an outbreak of Ulva prolifera.展开更多
文摘研究水热波动和土地覆盖变化对植被净初级生产力(Net Primary Productivity,NPP)的影响对于估算陆地碳循环及其驱动机制具有重要意义。利用MODIS遥感影像获得的时间序列NPP和土地覆盖产品,结合气象观测数据(气温和降水),采用相关分析、回归分析和空间分析相结合的方法,研究2000—2015年东北地区植被NPP的时空变化特征,并定量评估水热波动和土地覆盖变化对该地区植被NPP的相对影响。研究结果表明,2000—2015年东北地区植被NPP呈波动上升趋势,从2000年的369.24 g C m^-2 a^-1增加到2015年的453.84 g C m^-2 a^-1,平均值是412.10 g C m^-2 a^-1,年际增加速率为4.54 g C m^-2 a^-1。近16年来东北地区年均植被NPP空间上呈现南高北低、东高西低的分布格局,整体变化趋势以增加为主,其中轻微增加面积占该地区总面积的45.9%。不同土地覆盖类型的年均NPP差异明显,其中灌木最高为400.34 g C m^-2 a^-1,草地最低为300.49 g C m^-2 a^-1。东北地区植被NPP与气温的相关性不明显,而与降水量主要表现为正效应。水热波动对该地区不同土地覆盖类型NPP总量变化的贡献大于土地覆盖变化的贡献,其中对森林和农田的贡献最大,均达到70%以上。
文摘土地覆盖变化是影响植被净初级生产力(NPP)的关键因素之一.本研究基于MOD17A3 NPP数据和MCD12Q1土地覆盖数据,利用经典统计和空间分析相结合的方法,对2000—2014年山东省植被NPP空间分布格局及其时空变异特征进行定量分析,探讨NPP的时空动态对土地覆盖变化的响应特征,以及土地覆盖变化在植被NPP变化中的贡献率.结果表明,山东省内主要土地覆盖类型为耕地,森林、灌木和草地分布相对较少,其分布状况具有明显的区域性特征;山东省多年平均NPP为368.94 g C·m^(-2)·yr^(-1),空间分布总体上呈现为东南高于西北,沿海高于内陆;2000-2014年山东省四种土地覆盖类型的年平均NPP呈现耕地>森林>灌木>草地的趋势;大部分区域NPP呈上升趋势,但不显著,主要分布在山东中部、西部和西北部,NPP减少显著的区域主要集中在烟台市和青岛市附近;不同土地覆盖类型间存在差异,但整体上土地覆盖变化增加了NPP;草地的贡献率(66.31%)最高,森林次之,再次为灌木,耕地(5.95%)最低.
基金Under the auspices of Natural Science Foundation of Shandong(No.ZR2019MD041)National Natural Science Foundation of China(No.41676171)+2 种基金Qingdao National Laboratory for Marine Science and Technology of China(No.2016ASKJ02)Natural Science Foundation of Shandong(No.ZR2015DM015)Development and Construction Funds Project of National Independent Innovation Demonstration Zone in Shandong Peninsula(No.ZCQ17117)。
文摘In this study,using Moderate Resolution Imaging Spectroradiometer(MODIS)satellite images and environmental satellite CCD images,the spatio-temporal distribution of Ulva prolifera in the southern Yellow Sea during the period of 2011–2018 was extracted and combined with MODIS Level3 Photosynthetically Active Radiation(PAR)product data and Earth System Research Laboratory(ESRL)Sea Surface Temperature(SST)data to analyze their influences on the growth and outbreak of Ulva prolifera.The following conclusions were drawn:1)comprehensive analysis of Ulva prolifera distribution during the eight-year period revealed that the coverage area of Ulva prolifera typically exhibited a gradually increasing trend.The coverage area of Ulva prolifera reached a maximum of approximately 1714.21 km^2 during the eight-year period in late June 2015.The area affected by Ulva prolifera fluctuated.In mid-July 2014,the area affected by Ulva prolifera reached a maximum of approximately 39020.63 km^2.2)The average growth rate of Ulva prolifera was positive in May and June but negative in July.During the outbreak of Ulva prolifera,the SST in the southern Yellow Sea tended to increase each month.The SST anomaly and average growth rate of Ulva prolifera were positively correlated in May(R^2=0.62),but not significantly correlated in June or July.3)The variation trends of PAR and SST were approximately the same,and the PAR during this time period maintained a range of 40–50 mol/(m^2·d),providing sufficient illumination for the growth and outbreak of Ulva prolifera.In addition,the abundant nutrients and suitable temperature in the sea area near northern Jiangsu shoal resulted in a high growth rate of Ulva prolifera in May.In summary,the outbreak of Ulva prolifera was closely related to the environmental factors including SST,nutrients,and PAR.Sufficient nutrients and suitable temperatures resulted in a fast growth rate of Ulva prolifera.However,under poor nutrient conditions,even more suitable temperatures were not sufficient to trigger an outbreak of Ulva prolifera.
