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运用上海市宝山区海岸带遥感数据、DEM数据和气象数据,基于研究区域生态系统服务功能具体情况建立了海岸带生态资产评估的指标体系.利用改进的月总太阳辐射模型和基于遥感的生态资产计算方法,对宝山区海岸带的生态资产进行了评估.结果表明:1998年、2005年和2008年上海市宝山区海岸带生态资产总量折合人民币分别为3.226×... 相似文献
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Simulation study of China’s net primary production 总被引:1,自引:0,他引:1
Spatial and temporal distribution of vegetation net primary production (NPP) in China was studied using three light-use efficiency models (CASA, GLOPEM and GEOLUE) and two mechanistic ecological process models (CEVSA, GEOPRO). Based on spatial and temporal analysis (e.g. monthly, seasonally and annually) of simulated results from ecological process mechanism models of CASA, GLOPEM and CEVSA, the following conclusions could be made: (1) during the last 20 years, NPP change in China followed closely the seasonal change of climate affected by monsoon with an overall trend of increasing; (2) simulated average seasonal NPP was: 0.571±0.2 GtC in spring, 1.573±0.4 GtC in summer, 0.6±0.2 GtC in autumn, and 0.12±0.1 GtC in winter. Average annual NPP in China was 2.864±1 GtC. All the five models were able to simulate seasonal and spatial features of biomass for different ecological types in China. This paper provides a baseline for China's total biomass production. It also offers a means of estimating the NPP change due to afforestation, reforestation, conservation and other human activities and could aid people in using for-mentioned carbon sinks to fulfill China's commitment of reducing greenhouse gases. 相似文献
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《科学通报(英文版)》2008,(3)
Spatial and temporal distribution of vegetation net primary production(NPP)in China was studied us-ing three light-use efficiency models(CASA,GLOPEM and GEOLUE)and two mechanistic ecological process models(CEVSA,GEOPRO).Based on spatial and temporal analysis(e.g.monthly,seasonally and annually)of simulated results from ecological process mechanism models of CASA,GLOPEM and CEVSA,the following conclusions could be made:(1)during the last 20 years,NPP change in China followed closely the seasonal change of climate affected by monsoon with an overall trend of increas-ing;(2)simulated average seasonal NPP was:0.571±0.2 GtC in spring,1.573±0.4 GtC in summer,0.6±0.2 GtC in autumn,and 0.12±0.1 GtC in winter.Average annual NPP in China was 2.864±1 GtC.All the five models were able to simulate seasonal and spatial features of biomass for different ecological types in China.This paper provides a baseline for China's total biomass production.It also offers a means of estimating the NPP change due to afforestation,reforestation,conservation and other human activities and could aid people in using for-mentioned carbon sinks to fulfill China's commitment of reducing greenhouse gases. 相似文献
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长白山阔叶红松林净初级生产力对气候变化的响应: 基于BIOME-BGC模型的分析 总被引:2,自引:0,他引:2
为了分析气候变化和大气CO2浓度增加对长白山阔叶红松林净初级生产力(NPP)的影响, 运用本地参数化后的BIOME-BGC模型进行模拟, 并以实测NPP和增强型植被指数(EVI)进行验证。模拟结果表明, 长白山阔叶红松林NPP均值为611.71 gC/(m2•a), 1960-2011年年际间的波动范围是473.28~703.44 gC/(m2•a)。模拟结果与基于样地实测的NPP (均值为594.66 gC/(m2•a))相似; 同时, BIOME-BGC模型模拟的NPP年际间变化趋势与EVI的波动趋势相似, 二者间存在显著的相关关系, 表明模型能较好地模拟生产力的时间动态。模拟表明, 红松的NPP与降水关系更为密切, 而阔叶树NPP与温度、降水都呈显著的正相关。模型预测, 在未来CO2浓度加倍和温度、降水同时增加的场景下, 长白山阔叶红松林NPP将显著增加, 其中阔叶树和红松的NPP将分别增加27.87%和23.96%。单独增加温度(2℃)或单独增加降水(12%)都能促进阔叶树和红松NPP的增加, 其中降水的作用弱于温度的作用, 而单独CO2浓度的倍增对阔叶树和红松的NPP没有明显的影响。 相似文献
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以陕北榆阳区气候及土地利用方面的资料为依据,根据研究区特定的自然环境,结合相关研究成果和实地调查结果选择测算模型,对该区1988~2003年间的植被生态系统净第一性生产力动态变化情况进行估算和分析。研究表明:1988~2003年期间,榆阳区植被生态系统净第一性生产力总体上呈上升态势,总量在1988年的基础上增加了7.75%,年度递增率为0.50%;其中林地和园地净第一性生产力总量增加,增幅分别为11.35%和1054.99%,而草地的净第一性生产力总量呈明显下降趋势,降幅为6.15%;林地、园地和草地分别贡献了整个增量的95.56%、31.82%和-27.38%。榆阳区在研究时段内土地利用类型结构调整提升了区内植被生态系统净第一性生产力总量,改善了生态环境,为经济、环境和社会的和谐发展奠定了基础。图1,表4,参13。 相似文献
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【目的】基于江西省2011年和2016年的森林资源清查数据,分别估算不同森林类型的净生产力,为森林资源科学经营提供依据。【方法】以江西省2011年和2016年两期森林资源清查数据为样本,采用生物量回归模型法,在样木水平上计算单木生物量、累计样地水平生物量并扩大到总体水平,测算乔木层生物量的生长量和枯损量,结合乔木层生物量结果估测灌木层和草本层,并估算不同森林类型的净生产力。【结果】综合考虑森林乔木层生长与枯损、林下灌木层、草本层生物量,基于复位样木,由单木生物量模型得到样地生物量,进而计算江西省主要森林类型的净生产力,得出阔叶混交林的净生产力最高,针阔混交林次之,而针叶林和阔叶纯林的净生产力较低。2011—2016年,江西省森林平均净生产力为7.28 t/(hm2·a),阔叶混交林净生产力最高为11.26 t/(hm2·a)。【结论】在国家标准框架下的森林净生产力估算模式,可为更大范围内、统一标准下客观准确评估森林净生产力提供参考。 相似文献