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Temporal heterogeneity in climatic responses of four tree species in the Altai Mountains, northwest China
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作者 Hanxue Liang leibo Che +7 位作者 Wenyang Si Na Liu Zhitao Wu Ziqiang Du Jianwei Shi tianjie lei Bin Sun Shaowei Jiang 《Journal of Forestry Research》 SCIE EI CAS CSCD 2024年第6期230-241,共12页
In the context of ongoing climate change,rela-tionships between tree growth and climate present uncertain-ties,which limits the predictions of future forest dynamics.Northwest China is a region undergoing notable warm... In the context of ongoing climate change,rela-tionships between tree growth and climate present uncertain-ties,which limits the predictions of future forest dynamics.Northwest China is a region undergoing notable warming and increased precipitation;how forests in this region will respond to climate change has not been fully understood.We used dendrochronological methods to examine the rela-tionship between climate and the radial growth of four tree species in a riparian forest habitat in Altai region:European aspen(Populus tremula),bitter poplar(Populus laurifolia),Swedish birch(Betula pendula),and Siberian spruce(Picea obovata).The results reveal that European aspen was insen-sitive to climate changes.In contrast,bitter poplar showed a positive response to elevated temperatures and negative to increased moisture during the growing season.Swedish birch and Siberian spruce were adversely affected by higher temperatures but benefited from increased precipitation.A moving correlation analysis suggested that,against a back-drop of continuous warming,growth patterns of these spe-cies will diverge:European aspen will require close moni-toring,bitter poplar may likely to show accelerated growth,and the growth of Swedish birch and Siberian spruce may be inhibited,leading to a decline.These findings offer insight into the future dynamics of riparian forests under changing climate. 展开更多
关键词 Broadleaf species Coniferous species Warming and increased precipitation SPEI Riparian forests
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Review of drought impacts on carbon cycling in grassland ecosystems 被引量:6
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作者 tianjie lei Jie FENG +8 位作者 Cuiying ZHENG Shuguang LI Yang WANG Zhitao WU Jingxuan LU Guangyuan KAN Changliang SHAO Jinsheng JIA Hui CHENG 《Frontiers of Earth Science》 SCIE CAS CSCD 2020年第2期462-478,共17页
Grasslands play a key role in both carbon and water cycles.In semi-arid and arid grassland areas,the frequency and intensity of droughts are increasing.However,the influence of a drought on grassland carbon cycling is... Grasslands play a key role in both carbon and water cycles.In semi-arid and arid grassland areas,the frequency and intensity of droughts are increasing.However,the influence of a drought on grassland carbon cycling is still unclear.In this paper,the relationship between drought and grassland carbon cycling is described from the perspective of drought intensity,frequency,duration,and timing.Based on a large amount of literature,we determined that drought is one of the most prominent threats to grassland carbon cycling,although the impacts of different drought conditions are uncertain.The effects of a drought on grassland carbon cycling are more or less altered by drought-induced disturbances,whether individually or in combination.Additionally,a new conceptual model is proposed to better explain the mechanism of droughts on grassland carbon cycling.At present,evaluations of the effects of droughts on grassland carbon cycling are mainly qualitative.A data fusion model is indispensable for evaluating the fate of carbon cycling in a sustainable grassland system facing global change.In the future,multi-source data and models,based on the development of single and multiple disturbance experiments at the ecosystem level,can be utilized to systematically evaluate drought impacts on grassland carbon cycling at different timescales.Furthermore,more advanced models should be developed to address extreme drought events and their consequences on energy,water,and carbon cycling. 展开更多
关键词 DROUGHT carbon cycling grasslands conceptual model interactive mechanisms data fusion
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