The Southern African biomes are complex biotic communities, with its distinctive plant and animal species, and are maintained under the suitable climatic conditions of the region. It includes the Fynbos Biome and the ...The Southern African biomes are complex biotic communities, with its distinctive plant and animal species, and are maintained under the suitable climatic conditions of the region. It includes the Fynbos Biome and the Succulent Karoo Biome, which forms the smallest of the world’s six Floristic Kingdoms, and they are of conservation concern. The other six biomes are Albany Thicket, Desert, Grassland, Indian Ocean Coastal belt, Nama-Karoo, Savanna. The biomes are not only threatened by agricultural expansion, overgrazing, and mining;but also by future climate changes and droughts. This study investigates the how to best model the possible vulnerable biome areas, under future climate changes, and how Southern African geology plays a huge role in the restriction of the biome shifts. It provides evidence regarding the importance of the study to understanding the climate change impacts and the geological variables on the Southern African biomes, in terms of possible future biome habitat loss.展开更多
The global rate of fossil fuel combustion continues to rise, but the amount of CO2 accumulating in the atmosphere has not increased accordingly. The causes for this discrepancy are widely debated. Par- ticularly, the ...The global rate of fossil fuel combustion continues to rise, but the amount of CO2 accumulating in the atmosphere has not increased accordingly. The causes for this discrepancy are widely debated. Par- ticularly, the location and drivers for the interannual variability of atmospheric CO2 are highly uncertain. Here we examine links between global atmospheric CO2 growth rate (CGR) and the climate anomalies of biomes based on (1986―1995) global climate data of ten years and accompanying satellite data sets. Our results show that four biomes, the tropical rainforest, tropical savanna, C4 grassland and boreal forest, and their responses to climate anomalies, are the major climate-sensitive CO2 sinks/sources that control the CGR. The nature and magnitude by which these biomes respond to climate anomalies are generally not the same. However, one common influence did emerge from our analysis; the ex- tremely high CGR observed for the one extreme El Nio year was caused by the response of the tropical biomes (rainforest, savanna and C4 grassland) to temperature.展开更多
Considering the legacy of plant functional composition can help assess ecosystem functions and ecosystem services across different spatial scales under land cover changes.Woody plants likely respond to natural and ant...Considering the legacy of plant functional composition can help assess ecosystem functions and ecosystem services across different spatial scales under land cover changes.Woody plants likely respond to natural and anthropogenic perturbations due to historical events(e.g.,agricultural development),thus contemporary plant functional composition may be explained by historical woodland change,a type of land cover change.We propose that historical woodland changes may have legacy effects on contemporary plant functional composition.Here,we used partial least squares regression and linear mixed model analyses to test this assumption by coupling data on community weighted means(CWM)and community weighted variance(CWV)of vegetation plots and calculating the time of woodland existence across different periods from AD 0 to 2017.We found that the legacy effects of historical land cover changes on CWM and CWV during the existence time of woodland,particularly from AD 0 to 900,were drivers of contemporary plant functional composition at large spatial scales.Furthermore,historical woodland changes can affect contemporary plant functional composition,depending on the biome type.Particularly,the CWM of plant height,seed mass,and seed length showed the strongest correlations with woodland changes from AD 1910 to 2010 in tropics with year-round rain,and the CWM of leaf traits correlated with woodland changes from AD 0 to 1700 in tropics with summer rain.Our study provides the effective evidence on the legacy of historical woodland changes and the effects on contemporary plant functional composition,which is crucial with respect to effective management of plant diversity and assessing ecosystem functions and services from local to global scales over time.展开更多
Since the introduction of the concept, studies on valuation of ecosystem services have been overwhelming, in cognizance of its great significance. In this article, the authors took Northeast China as the study area an...Since the introduction of the concept, studies on valuation of ecosystem services have been overwhelming, in cognizance of its great significance. In this article, the authors took Northeast China as the study area and applied the published coefficients for the world by Costanza to calculate the ecosystem services values through a spatial convolution method. The convolution analysis was done with a square processor with 5×5 neighborhood cells. The results showed that the ecosystem services value for the study area in the year 2003 was US$44 990 million which is US$89 million less than the value without operation, and the main contributions for that decrease were from water bodies, wetlands and estuaries. It is expected that this article can attract more interest to explore this field adopting geographic methods.展开更多
以全球变暖为背景，以中国南部区域18．000-27．50°N，108．50°～112．50°E样带为研究对象，以纬度为梯度，应用CRU（Climate Research Unit殓球观测数据集和CO2体积分数倍增后的2050年模拟气候状况作为平衡态陆地生物...以全球变暖为背景，以中国南部区域18．000-27．50°N，108．50°～112．50°E样带为研究对象，以纬度为梯度，应用CRU（Climate Research Unit殓球观测数据集和CO2体积分数倍增后的2050年模拟气候状况作为平衡态陆地生物圈模型BIOME4的气候驱动，对中国南部样带历史100a和未来50a间的潜在植被净初级生产力（netprimary production，NPP）和叶面积指数（leaf area index，LAI）变化进行模拟和统计分析。结果显示样带内影响NPP的主要因素为年最低温度和年均降雨量，影响LAI的主要因素为年均温度和年均降雨量。植被类型变化与气候变化所造成的NPP、LAI变化略有不同。样带较高纬度地区，植被类型变化与气候变化造成的NPP均值差异较小而LAI则差异较大。未来气候状况下NPP、LAI都有大幅度的增加，但不同纬度增幅不同。展开更多
Birch(Betula tortuosa)is one of the treeline forming species within the Siberian Mountains.We analysed the area dynamics of birch stands and the upslope climb of birch treeline based on the Landsat time series scenes ...Birch(Betula tortuosa)is one of the treeline forming species within the Siberian Mountains.We analysed the area dynamics of birch stands and the upslope climb of birch treeline based on the Landsat time series scenes and on-ground data.We found that since the warming onset(1970th)birch area increased by 10%,birch stands and treeline boundary were moving upslope with a rate of 1.4 m/yr and 4.0 m/yr.Birch upslope shift correlated with air temperatures at the beginning(May-June)and the end(August-October)of the growth period.Meanwhile,no correlation was found between birch upslope migration and precipitation.Winds negatively influenced both birch area growth and birch upslope climb during spring,fall,and wintertime.In the windy habitats,birch,together with larch and Siberian pine,formed clusters(hedges)which mitigated the influence of adverse winds.These clusters are the adaptive pattern for trees’upslope climb within windward slopes.The other adaptation to the harsh alpine ecotone habitat is non-leaf(bark)photosynthesis which supports tree survival.Thereby,Betula tortuosa upslope climb depends on the wind impact and warming in spring and fall that extended growth period.With ongoing warming and observed wind speed decrease on the background of sufficient precipitation,it is expected to further birch advance into alpine tundra in the Siberian Mountains.展开更多
以全球变暖为背景,以中国南部区域18.00°—27.50°N、108.50°—112.50°E样带为研究对象,以纬度为梯度,应用CRU(Climate Research Unit)全球观测数据集和CO2浓度倍增后的2050年模拟气候状况作为平衡态陆地生物圈模型B...以全球变暖为背景,以中国南部区域18.00°—27.50°N、108.50°—112.50°E样带为研究对象,以纬度为梯度,应用CRU(Climate Research Unit)全球观测数据集和CO2浓度倍增后的2050年模拟气候状况作为平衡态陆地生物圈模型BIOME4的气候驱动,对中国南部样带历史100 a和未来50 a间的潜在植被变化进行模拟和统计分析。结果表明,随时间推移与全球变暖加剧,植被类型变化呈加剧趋势;温度作为植被变化的主要因素导致热带与温带植被的交错带成为气候变化的敏感地带。历史气候条件下,北回归线以北边缘地带的24.5°N的植被变化率最大,其次为以南边缘地带的22.5°N。在CO2浓度倍增导致温度、降雨量、最低温都显著增加后,研究区域植被变化率最大地带由北回归线边缘带北移到25.5°N。展开更多
Turkey,containing three of the world’s biodiversity hotspots,is a hub for genetic biodiversity.However,the vegetation cover has drastically changed in recent decades as a result of substantial transformations in land...Turkey,containing three of the world’s biodiversity hotspots,is a hub for genetic biodiversity.However,the vegetation cover has drastically changed in recent decades as a result of substantial transformations in landuse practices.A map of the potential natural vegetation can be used to represent the biodiversity of a country,and therefore a reference to effectively develop conservation strategies.The multinomial logistic regression is used to simulate the probability of different biomes occurring in the country using elevation,climatological data and natural vegetation data.A correlation test was applied to the climatological data to determine which predictors influence vegetation the most.These were temperature,precipitation,relative humidity and cloudiness.The Ordinary Kriging method was employed to transform the data into the format for the multinomial logistic regression model.The model showed that temperature was the most influencing factor with respect to Turkey’s vegetation and distribution follows a similar distribution as the various macroclimates.Broadleaf forests are mostly found in the Black Sea region,which is also the wettest region of the country.The Marmara region is the only other region where there are broadleaf forests.Mixed forests and shrublands are mostly located in Central Anatolia due to the region’s low humidity which favours herbaceous flora.Coniferous forests were dominant in the Aegean and Mediterranean regions,attributed to high temperatures.展开更多
文摘The Southern African biomes are complex biotic communities, with its distinctive plant and animal species, and are maintained under the suitable climatic conditions of the region. It includes the Fynbos Biome and the Succulent Karoo Biome, which forms the smallest of the world’s six Floristic Kingdoms, and they are of conservation concern. The other six biomes are Albany Thicket, Desert, Grassland, Indian Ocean Coastal belt, Nama-Karoo, Savanna. The biomes are not only threatened by agricultural expansion, overgrazing, and mining;but also by future climate changes and droughts. This study investigates the how to best model the possible vulnerable biome areas, under future climate changes, and how Southern African geology plays a huge role in the restriction of the biome shifts. It provides evidence regarding the importance of the study to understanding the climate change impacts and the geological variables on the Southern African biomes, in terms of possible future biome habitat loss.
基金the National Natural Science Foundation of China (Grant Nos. 40401028, 40671173, 40425008, and 30590384)the Visiting-Professor Funding from the Institute of Geographical Sciences and Natural Resources (IGSNRR), Chinese Academy of Sciences
文摘The global rate of fossil fuel combustion continues to rise, but the amount of CO2 accumulating in the atmosphere has not increased accordingly. The causes for this discrepancy are widely debated. Par- ticularly, the location and drivers for the interannual variability of atmospheric CO2 are highly uncertain. Here we examine links between global atmospheric CO2 growth rate (CGR) and the climate anomalies of biomes based on (1986―1995) global climate data of ten years and accompanying satellite data sets. Our results show that four biomes, the tropical rainforest, tropical savanna, C4 grassland and boreal forest, and their responses to climate anomalies, are the major climate-sensitive CO2 sinks/sources that control the CGR. The nature and magnitude by which these biomes respond to climate anomalies are generally not the same. However, one common influence did emerge from our analysis; the ex- tremely high CGR observed for the one extreme El Nio year was caused by the response of the tropical biomes (rainforest, savanna and C4 grassland) to temperature.
基金We acknowledge support from the National Natural Science Foundation of China(NSFC,32060385 and 31860668)the Project of Qinghai Science&Technology Department(2020-ZJ-733).
文摘Considering the legacy of plant functional composition can help assess ecosystem functions and ecosystem services across different spatial scales under land cover changes.Woody plants likely respond to natural and anthropogenic perturbations due to historical events(e.g.,agricultural development),thus contemporary plant functional composition may be explained by historical woodland change,a type of land cover change.We propose that historical woodland changes may have legacy effects on contemporary plant functional composition.Here,we used partial least squares regression and linear mixed model analyses to test this assumption by coupling data on community weighted means(CWM)and community weighted variance(CWV)of vegetation plots and calculating the time of woodland existence across different periods from AD 0 to 2017.We found that the legacy effects of historical land cover changes on CWM and CWV during the existence time of woodland,particularly from AD 0 to 900,were drivers of contemporary plant functional composition at large spatial scales.Furthermore,historical woodland changes can affect contemporary plant functional composition,depending on the biome type.Particularly,the CWM of plant height,seed mass,and seed length showed the strongest correlations with woodland changes from AD 1910 to 2010 in tropics with year-round rain,and the CWM of leaf traits correlated with woodland changes from AD 0 to 1700 in tropics with summer rain.Our study provides the effective evidence on the legacy of historical woodland changes and the effects on contemporary plant functional composition,which is crucial with respect to effective management of plant diversity and assessing ecosystem functions and services from local to global scales over time.
基金funded by the Major Program of National Natural Science Foundation of China (40930101)National Technology Introduction Program of China (948 Program,2009-Z31)the Key Project of the Commonweal Foundation of China's National Academy (2010-02)~~
文摘Since the introduction of the concept, studies on valuation of ecosystem services have been overwhelming, in cognizance of its great significance. In this article, the authors took Northeast China as the study area and applied the published coefficients for the world by Costanza to calculate the ecosystem services values through a spatial convolution method. The convolution analysis was done with a square processor with 5×5 neighborhood cells. The results showed that the ecosystem services value for the study area in the year 2003 was US$44 990 million which is US$89 million less than the value without operation, and the main contributions for that decrease were from water bodies, wetlands and estuaries. It is expected that this article can attract more interest to explore this field adopting geographic methods.
文摘以全球变暖为背景，以中国南部区域18．000-27．50°N，108．50°～112．50°E样带为研究对象，以纬度为梯度，应用CRU（Climate Research Unit殓球观测数据集和CO2体积分数倍增后的2050年模拟气候状况作为平衡态陆地生物圈模型BIOME4的气候驱动，对中国南部样带历史100a和未来50a间的潜在植被净初级生产力（netprimary production，NPP）和叶面积指数（leaf area index，LAI）变化进行模拟和统计分析。结果显示样带内影响NPP的主要因素为年最低温度和年均降雨量，影响LAI的主要因素为年均温度和年均降雨量。植被类型变化与气候变化所造成的NPP、LAI变化略有不同。样带较高纬度地区，植被类型变化与气候变化造成的NPP均值差异较小而LAI则差异较大。未来气候状况下NPP、LAI都有大幅度的增加，但不同纬度增幅不同。
基金The research was funded by Russian Foundation for Basic Research,Krasnoyarsk Territory and Krasnoyarsk Regional Fund of Science,project number 20-44-240007.
文摘Birch(Betula tortuosa)is one of the treeline forming species within the Siberian Mountains.We analysed the area dynamics of birch stands and the upslope climb of birch treeline based on the Landsat time series scenes and on-ground data.We found that since the warming onset(1970th)birch area increased by 10%,birch stands and treeline boundary were moving upslope with a rate of 1.4 m/yr and 4.0 m/yr.Birch upslope shift correlated with air temperatures at the beginning(May-June)and the end(August-October)of the growth period.Meanwhile,no correlation was found between birch upslope migration and precipitation.Winds negatively influenced both birch area growth and birch upslope climb during spring,fall,and wintertime.In the windy habitats,birch,together with larch and Siberian pine,formed clusters(hedges)which mitigated the influence of adverse winds.These clusters are the adaptive pattern for trees’upslope climb within windward slopes.The other adaptation to the harsh alpine ecotone habitat is non-leaf(bark)photosynthesis which supports tree survival.Thereby,Betula tortuosa upslope climb depends on the wind impact and warming in spring and fall that extended growth period.With ongoing warming and observed wind speed decrease on the background of sufficient precipitation,it is expected to further birch advance into alpine tundra in the Siberian Mountains.
文摘以全球变暖为背景,以中国南部区域18.00°—27.50°N、108.50°—112.50°E样带为研究对象,以纬度为梯度,应用CRU(Climate Research Unit)全球观测数据集和CO2浓度倍增后的2050年模拟气候状况作为平衡态陆地生物圈模型BIOME4的气候驱动,对中国南部样带历史100 a和未来50 a间的潜在植被变化进行模拟和统计分析。结果表明,随时间推移与全球变暖加剧,植被类型变化呈加剧趋势;温度作为植被变化的主要因素导致热带与温带植被的交错带成为气候变化的敏感地带。历史气候条件下,北回归线以北边缘地带的24.5°N的植被变化率最大,其次为以南边缘地带的22.5°N。在CO2浓度倍增导致温度、降雨量、最低温都显著增加后,研究区域植被变化率最大地带由北回归线边缘带北移到25.5°N。
文摘Turkey,containing three of the world’s biodiversity hotspots,is a hub for genetic biodiversity.However,the vegetation cover has drastically changed in recent decades as a result of substantial transformations in landuse practices.A map of the potential natural vegetation can be used to represent the biodiversity of a country,and therefore a reference to effectively develop conservation strategies.The multinomial logistic regression is used to simulate the probability of different biomes occurring in the country using elevation,climatological data and natural vegetation data.A correlation test was applied to the climatological data to determine which predictors influence vegetation the most.These were temperature,precipitation,relative humidity and cloudiness.The Ordinary Kriging method was employed to transform the data into the format for the multinomial logistic regression model.The model showed that temperature was the most influencing factor with respect to Turkey’s vegetation and distribution follows a similar distribution as the various macroclimates.Broadleaf forests are mostly found in the Black Sea region,which is also the wettest region of the country.The Marmara region is the only other region where there are broadleaf forests.Mixed forests and shrublands are mostly located in Central Anatolia due to the region’s low humidity which favours herbaceous flora.Coniferous forests were dominant in the Aegean and Mediterranean regions,attributed to high temperatures.
