Alpine treeline, as a prominent ecological boundary between forested mountain slopes and alpine meadow/shrub, is highly complex in altitudinal distribution and sensitive to warming climate. Great efforts have been mad...Alpine treeline, as a prominent ecological boundary between forested mountain slopes and alpine meadow/shrub, is highly complex in altitudinal distribution and sensitive to warming climate. Great efforts have been made to explore their distribution patterns and ecological mechanisms that determine these patterns for more than 100 years, and quite a number of geographical and ecophysiological models have been developed to correlate treeline altitude with latitude or a latitude related temperature. However,on a global scale, all of these models have great difficulties to accurately predict treeline elevation due to the extreme diversity of treeline site conditions.One of the major reasons is that "mass elevation effect"(MEE) has not been quantified globally and related with global treeline elevations although it has been observed and its effect on treeline elevations in the Eurasian continent and Northern Hemisphere recognized. In this study, we collected and compiled a total of 594 treeline sites all over the world from literatures, and explored how MEE affects globaltreeline elevation by developing a ternary linear regression model with intra-mountain base elevation(IMBE, as a proxy of MEE), latitude and continentality as independent variables. The results indicated that IMBE, latitude and continentality together could explain 92% of global treeline elevation variability, and that IMBE contributes the most(52.2%), latitude the second(40%) and continentality the least(7.8%) to the altitudinal distribution of global treelines. In the Northern Hemisphere, the three factors' contributions amount to 50.4%, 45.9% and 3.7% respectively; in the south hemisphere, their contributions are 38.3%, 53%, and 8.7%, respectively. This indicates that MEE, virtually the heating effect of macro-landforms, is actually the most significant factor for the altitudinal distribution of treelines across the globe, and that latitude is relatively more significant for treeline elevation in the Southern Hemisphere probably due to fewer macro-landforms there.展开更多
An unusually warm East Asia in spring 2018,when exceptionally high surface air temperatures were recorded in large areas of Asia,such as northern China,southern China,and Japan,was investigated based on the ERA-Interi...An unusually warm East Asia in spring 2018,when exceptionally high surface air temperatures were recorded in large areas of Asia,such as northern China,southern China,and Japan,was investigated based on the ERA-Interim reanalysis.The East Asian warming anomalies were primarily attributed to a tripole mode of North Atlantic SST anomalies,which could have triggered anomalous Rossby wave trains over the North Atlantic and Eurasia through modulating the North Atlantic baroclinic instability.Atlantic-forced Rossby waves tend to propagate eastward and induce anomalously high pressure and anticyclonic activity over East Asia,leading to a northward displacement of the Pacific subtropical high.As a result,descending motion,reduced precipitation,and increased surface solar radiation due to less cloud cover appear over East Asia,accompanied by remarkably warm advection from the ocean to southern China,northern China,and Japan.The transportation of anomalously warm advection and the feedbacks between soil moisture and surface temperature were both favorable for the recordbreaking warmth in East Asia during spring 2018.The seasonal‘memory’of the North Atlantic tripole SST mode from the previous winter to the following spring may provide useful implications for the seasonal prediction of East Asian weather and climate.展开更多
Soil erosion poses a great threat to the sustainability of the ecological environment and the harmonious development of human well-being.The revised universal soil loss equation(RUSLE)was used to quantify soil erosion...Soil erosion poses a great threat to the sustainability of the ecological environment and the harmonious development of human well-being.The revised universal soil loss equation(RUSLE)was used to quantify soil erosion in the Three-River Headwaters region(TRH),Qinghai,China from 2000 to 2015.The possible effects of an ecosystem restoration project on soil erosion were explored against the background of climatic changes in the study area.The model was validated with on-ground observations and showed a satisfactory performance,with a multiple correlation coefficient of 0.62 from the linear regression between the estimations and observations.The soil erosion modulus in 2010–2015 increased 6.2%,but decreased 1.2%compared with those in the periods of 2000–2005 and 2005–2010,respectively.Based on the method of overlay analysis,the interannual change of the estimated soil erosion was dominated by climate(about 64%),specifically by precipitation,rather than by vegetation coverage(about 34%).Despite some uncertainties in the model and data,this study quantified the relative contribution of ecological restoration under global climatic change;meanwhile the complexity,labor-intensiveness and long-range character of ecological restoration projects have to be recognized.On-ground observations over the long-term,further parameterization,and data inputs with higher quality are necessary and essential for decreasing the uncertainties in the estimations.展开更多
Ecological regime shift is the rapid transition from one stable community structure to another, often ecologically infe- rior, stable community. Such regime shifts are especially common in shallow marine communities, ...Ecological regime shift is the rapid transition from one stable community structure to another, often ecologically infe- rior, stable community. Such regime shifts are especially common in shallow marine communities, such as the transition of kelp forests to algal turfs that harbour far lower biodiversity. Stable regimes in communities are a result of balanced interactions be- tween species, and predicting new regimes therefore requires an evaluation of new species interactions, as well as the resilience of the ＇stable＇ position. While computational optimisation techniques can predict new potential regimes, predicting the most likely community state of the various options produced is currently educated guess work. In this study we integrate a stable regime op- timisation approach with a Bayesian network used to infer prior knowledge of the likely stress of climate change （or, in practice, any other disturbance） on each component species of a representative rocky shore community model. Combining the results, by calculating the product of the match between resilient computational predictions and the posterior probabilities of the Bayesian network, gives a refined set of model predictors, and demonstrates the use of the process in determining community changes, as might occur through processes such as climate change. To inform Bayesian priors, we conduct a review of molecular approaches applied to the analysis of the transcriptome of rocky shore organisms, and show how such an approach could be linked to meas- ureable stress variables in the field. Hence species-specific microarrays could be designed as biomarkers of in situ stress, and used to inform predictive modelling approaches such as those described here.展开更多
基金supported by the National Natural Science Foundation of China (Grant Nos. 41030528 and No. 40971064)
文摘Alpine treeline, as a prominent ecological boundary between forested mountain slopes and alpine meadow/shrub, is highly complex in altitudinal distribution and sensitive to warming climate. Great efforts have been made to explore their distribution patterns and ecological mechanisms that determine these patterns for more than 100 years, and quite a number of geographical and ecophysiological models have been developed to correlate treeline altitude with latitude or a latitude related temperature. However,on a global scale, all of these models have great difficulties to accurately predict treeline elevation due to the extreme diversity of treeline site conditions.One of the major reasons is that "mass elevation effect"(MEE) has not been quantified globally and related with global treeline elevations although it has been observed and its effect on treeline elevations in the Eurasian continent and Northern Hemisphere recognized. In this study, we collected and compiled a total of 594 treeline sites all over the world from literatures, and explored how MEE affects globaltreeline elevation by developing a ternary linear regression model with intra-mountain base elevation(IMBE, as a proxy of MEE), latitude and continentality as independent variables. The results indicated that IMBE, latitude and continentality together could explain 92% of global treeline elevation variability, and that IMBE contributes the most(52.2%), latitude the second(40%) and continentality the least(7.8%) to the altitudinal distribution of global treelines. In the Northern Hemisphere, the three factors' contributions amount to 50.4%, 45.9% and 3.7% respectively; in the south hemisphere, their contributions are 38.3%, 53%, and 8.7%, respectively. This indicates that MEE, virtually the heating effect of macro-landforms, is actually the most significant factor for the altitudinal distribution of treelines across the globe, and that latitude is relatively more significant for treeline elevation in the Southern Hemisphere probably due to fewer macro-landforms there.
基金supported by the National Key Research and Development Program of China [grant number2016YFA0602703]the National Natural Science Foundation of China [grant numbers 41661144019,41690123,41690120,and91637208]+1 种基金the CMA Guangzhou Joint Research Center for Atmospheric Sciencesthe Jiangsu Collaborative Innovation Center for Climate Change
文摘An unusually warm East Asia in spring 2018,when exceptionally high surface air temperatures were recorded in large areas of Asia,such as northern China,southern China,and Japan,was investigated based on the ERA-Interim reanalysis.The East Asian warming anomalies were primarily attributed to a tripole mode of North Atlantic SST anomalies,which could have triggered anomalous Rossby wave trains over the North Atlantic and Eurasia through modulating the North Atlantic baroclinic instability.Atlantic-forced Rossby waves tend to propagate eastward and induce anomalously high pressure and anticyclonic activity over East Asia,leading to a northward displacement of the Pacific subtropical high.As a result,descending motion,reduced precipitation,and increased surface solar radiation due to less cloud cover appear over East Asia,accompanied by remarkably warm advection from the ocean to southern China,northern China,and Japan.The transportation of anomalously warm advection and the feedbacks between soil moisture and surface temperature were both favorable for the recordbreaking warmth in East Asia during spring 2018.The seasonal‘memory’of the North Atlantic tripole SST mode from the previous winter to the following spring may provide useful implications for the seasonal prediction of East Asian weather and climate.
基金National Key Research and Development Program of China(2016YFC0500203)Science and Technology Program of Qinghai Province(2018-ZJ-T09,2017-SF-A6)
文摘Soil erosion poses a great threat to the sustainability of the ecological environment and the harmonious development of human well-being.The revised universal soil loss equation(RUSLE)was used to quantify soil erosion in the Three-River Headwaters region(TRH),Qinghai,China from 2000 to 2015.The possible effects of an ecosystem restoration project on soil erosion were explored against the background of climatic changes in the study area.The model was validated with on-ground observations and showed a satisfactory performance,with a multiple correlation coefficient of 0.62 from the linear regression between the estimations and observations.The soil erosion modulus in 2010–2015 increased 6.2%,but decreased 1.2%compared with those in the periods of 2000–2005 and 2005–2010,respectively.Based on the method of overlay analysis,the interannual change of the estimated soil erosion was dominated by climate(about 64%),specifically by precipitation,rather than by vegetation coverage(about 34%).Despite some uncertainties in the model and data,this study quantified the relative contribution of ecological restoration under global climatic change;meanwhile the complexity,labor-intensiveness and long-range character of ecological restoration projects have to be recognized.On-ground observations over the long-term,further parameterization,and data inputs with higher quality are necessary and essential for decreasing the uncertainties in the estimations.
文摘Ecological regime shift is the rapid transition from one stable community structure to another, often ecologically infe- rior, stable community. Such regime shifts are especially common in shallow marine communities, such as the transition of kelp forests to algal turfs that harbour far lower biodiversity. Stable regimes in communities are a result of balanced interactions be- tween species, and predicting new regimes therefore requires an evaluation of new species interactions, as well as the resilience of the ＇stable＇ position. While computational optimisation techniques can predict new potential regimes, predicting the most likely community state of the various options produced is currently educated guess work. In this study we integrate a stable regime op- timisation approach with a Bayesian network used to infer prior knowledge of the likely stress of climate change （or, in practice, any other disturbance） on each component species of a representative rocky shore community model. Combining the results, by calculating the product of the match between resilient computational predictions and the posterior probabilities of the Bayesian network, gives a refined set of model predictors, and demonstrates the use of the process in determining community changes, as might occur through processes such as climate change. To inform Bayesian priors, we conduct a review of molecular approaches applied to the analysis of the transcriptome of rocky shore organisms, and show how such an approach could be linked to meas- ureable stress variables in the field. Hence species-specific microarrays could be designed as biomarkers of in situ stress, and used to inform predictive modelling approaches such as those described here.
