近58 a川西北高原的气候变化及其生态效应

川西北高原位于我国一、二级阶梯的过渡地带,是长江、黄河上游的集水区,也是我国五大牧区之一,高寒草甸是其高原面上的典型植被.近年来,草地沙化问题突出,已经威胁到区域生态安全和畜牧业的可持续发展.以过度放牧为主的人为因素和以气候变化为主的自然因素被认为是导致川西北高寒草地沙化的驱动力.着眼于气候因素,研究1961—2018年与草地沙化密切相关的温度、降水、风速、潜在蒸散和气候干燥度的变化特征,在此基础上讨论气候变化的地表覆被效应,结果表明:川西北高原的温度呈显著上升趋势,气候倾向率为0.25℃/Da,受其影响潜在蒸散(potential evapotranspiration,ET_(o))也呈上升趋势,倾向率为4.4 mm/Da.降水量变化表现为平均增加但线性趋势不显著,总体倾向率大于ET_(o),为8.3 mm/Da.因此,气候干燥度呈多年平均变湿润特征,但线性趋势不明显.把各气候因子与地表覆被NDVI进行相关分析发现,单气候因子与NDVI的相关性均不强,说明气候变化对植被影响的复杂性,也证明人类扰动在土地沙化中的作用不可忽略.

川西农牧交错带“三生”空间冲突演变特征分析及模拟预测——以阿坝州四县为例

川西农牧交错带处于我国第一、第二阶梯的交替地带,是西部生态脆弱典型区,地势起伏显著,地形及生态环境复杂,积极开展川西农牧交错带“三生”空间冲突(生活、生产、生态)研究,将有助于川西农牧交错带生态安全保障与社会经济协调良性发展。研究区域为阿坝藏族羌族自治州四县(马尔康、理县、黑水、松潘),以2005—2020年土地利用数据为基础,通过CLUE-S软件模拟了未来的土地利用模式;将研究区域“三生”空间分为生活生产空间、生态生产空间、生产生态空间、生态空间4种类型,并建立空间冲突测算模型,对研究区域2005—2025年四期空间冲突水平进行了测算。结果表明:(1)2005—2025年四县域面积所占比重最大的是生态生产空间,之后依次为生态空间、生产生态空间、生活生产空间。生活生产、生产生态空间面积连续上升,仅生态生产空间面积减少,生态空间面积以波动变化为主。(2)2005—2025年该区域以中等空间冲突为主。(3)2005—2025年,总体而言空间冲突值的高-高聚集区主要位于四县域的农牧交错带、生活生产空间的交叉区域且表现明显,高-高聚集区在松潘县和马尔康县的农牧交错带有逐渐扩大的趋势,黑水县和理县集聚区面积先减少后轻微扩张;空间冲突值的低-低集聚区主要位于以生态生产空间为主与生态空间的交叉区域;集聚不显著的区域以生态空间为主。(4)整体来看,川西农牧交错区域“三生”空间中生态生产空间冲突强度最高。

NPP vulnerability of the potential vegetation of China to climate change in the past and future

Using the Integrated Biosphere Simulator, a dynamic vegetation model, this study initially simulated the net primary productivity（NPP） dynamics of China＇s potential vegetation in the past 55 years（1961–2015） and in the future 35 years（2016–2050）. Then, taking the NPP of the potential vegetation in average climate conditions during 1986–2005 as the basis for evaluation, this study examined whether the potential vegetation adapts to climate change or not. Meanwhile, the degree of inadaptability was evaluated. Finally, the NPP vulnerability of the potential vegetation was evaluated by synthesizing the frequency and degrees of inadaptability to climate change. In the past 55 years, the NPP of desert ecosystems in the south of the Tianshan Mountains and grassland ecosystems in the north of China and in western Tibetan Plateau was prone to the effect of climate change. The NPP of most forest ecosystems was not prone to the influence of climate change. The low NPP vulnerability to climate change of the evergreen broad-leaved and coniferous forests was observed. Furthermore, the NPP of the desert ecosystems in the north of the Tianshan Mountains and grassland ecosystems in the central and eastern Tibetan Plateau also had low vulnerability to climate change. In the next 35 years, the NPP vulnerability to climate change would reduce the forest–steppe in the Songliao Plain, the deciduous broad-leaved forests in the warm temperate zone, and the alpine steppe in the central and western Tibetan Plateau. The NPP vulnerability would significantly increase of the temperate desert in the Junggar Basin and the alpine desert in the Kunlun Mountains. The NPP vulnerability of the subtropical evergreen broad-leaved forests would also increase. The area of the regions with increased vulnerability would account for 27.5% of China.

Modeling net primary productivity of the terrestrial ecosystem in China from 1961 to 2005

Net primary productivity （NPP） is the structure and function of the ecosystem. NPP can most important index that represents the be simulated by dynamic global vegetation models （DGVM）, which are designed to represent vegetation dynamics relative to environ- mental change. This study simulated the NPP of China＇s ecosystems based on the DGVM Integrated Biosphere Simulator （IBIS） with data on climate, soil, and topography. The appli- cability of IBIS in the NPP simulation of China＇s terrestrial ecosystems was verified first. Comparison with other relevant studies indicates that the range and mean value of simula- tions are generally within the limits of observations; the overall pattern and total annual NPP are close to the simulations conducted with other models. The simulations are also close to the NPP estimations based on remote sensing. Validation proved that IBIS can be utilized in the large-scale simulation of NPP in China＇s natural ecosystem. We then simulated NPP with climate change data from 1961 to 2005, when warming was particularly striking. The following are the results of the simulation. （1） Total NPP varied from 3.61 GtC/yr to 4.24 GtC/yr in the past 45 years and exhibited minimal significant linear increase or decrease. （2） Regional differences in the increase or decrease in NPP were large but exhibited an insignificant overall linear trend. NPP declined in most parts of eastern and central China, especially in the Loess Plateau. （3） Similar to the fluctuation law of annual NPP, seasonal NPP also displayed an insignificant increase or decrease; the trend line was within the general level. （4） The re- gional differences in seasonal NPP changes were large. NPP declined in spring, summer, and autumn in the Loess Plateau but increased in most parts of the Tibetan Plateau.

Coupled effect of climate change and human activities on the restoration/degradation of the Qinghai-Tibet Plateau grassland

Climate change(CC)and human activities(HA)are the main reasons for the restoration/degradation of the Qinghai-Tibet Plateau(QTP)grassland.Many related studies have been conducted thus far,but the impact mechanism of CC coupled with HA on QTP remains unclear.We summarized the two main coupling factors in recent years(specifically,in the past five years)and obtained the following conclusions.(1)CC and HA have positive and negative effects on the QTP grassland ecosystem.CC primarily affects grassland ecology through temperature,humidification,and extreme climate,and HA mainly affects ecosystems through primary,secondary,and tertiary industries and restoration measures.(2)CC coupled with HA affects soil,plants,animals,and fungi/microbes.CC makes the snow line rise by increasing the temperature,which expands the zone for HA.CC also restricts HA through hydrological changes,extreme climate,and outbreak of pikas and pests.Simultaneously,measures are implemented through HA to control and adapt to CC.Hence,the grassland ecosystem is comprehensively influenced by CC and HA.(3)The grassland ecosystem dynamically adapts to the disturbance caused by CC and HA by changing its physiological characteristics,distribution range,diet structure,community structure,and physical state.Simultaneously,it responds to environmental changes through desertification,poisonous weeds,rodent outbreak,release of harmful gases,and other means.This work can be used as a reference for the sustainable development of the QTP grassland.

Spatio-temporal variation of the wet-dry conditions from 1961 to 2015 in China

As an important part of the regional environment, the wet-dry climate condition is determined by precipitation and potential evapotranspiration （expressed as ETo）. Based on weather station data, this study first calculated ETo by using the FAO56 Penrnan-Monteith model. Then, the dryness index K （ratio of ETo to precipitation） was used to study the spatio-temporal variation of the wet-dry condition in China from 1961 to 2015; moreover, dominant climatic factors of the wet-dry condition change were discussed. The annual precipitation and ETo of the Qinling-Huaihe line were close to a balance （K≈1.0）. The annual precipitation in most areas exceeded the ETo in the south of this line and the east of Hengduan Mountains （K〈0.0）, where the climate is wet. Furthermore, the precipitation in the northwest inland areas of China, where the climate is dry, was markedly lower than ETo （K≥4.0）. The overall annual K of China fluctuated around the 55-year mean and its linear trend was not significant. However, a relatively wet period of about 10 yr （1987-1996） was recorded. The overall annual K of China showed strong cyclicality on the time scale of 3, 7-8, 11 and 26-28 yr, and regional differences of the annual K trends and cyclicality were large. The degrees of wetness in the Northwest China and western Qinghai-Tibet Plateau were substantially increased, whereas the degrees of dryness in the Yunnan-Guizhou Plateau, Sichuan Basin, and Loess Plateau were markedly increased. The linear trend of the annual K in most regions of China was not significant, and the annual K of most areas in China showed strong cyclicality on the 8-14 yr time scale. Precipitation was the dominant factor of wet-dry condition change in most areas, especially in North China, where the annual K change was highly correlated with precipitation.

Terrestrial Ecosystem Modeling with IBIS:Progress and Future Vision

Dynamic Global Vegetation Models(DGVM)are powerful tools for studying complicated ecosystem processes and global changes.This review article synthesizes the developments and applications of the Integrated Biosphere Simulator(IBIS),a DGVM,over the past two decades.IBIS has been used to evaluate carbon,nitrogen,and water cycling in terrestrial ecosystems,vegetation changes,land-atmosphere interactions,land-aquatic system integration,and climate change impacts.Here we summarize model development work since IBIS v2.5,covering hydrology(evapotranspiration,groundwater,lateral routing),vegetation dynamics(plant functional type,land cover change),plant physiology(phenology,photosynthesis,carbon allocation,growth),biogeochemistry(soil carbon and nitrogen processes,greenhouse gas emissions),impacts of natural disturbances(drought,insect damage,fire)and human induced land use changes,and computational improvements.We also summarize IBIS model applications around the world in evaluating ecosystem productivity,carbon and water budgets,water use efficiency,natural disturbance effects,and impacts of climate change and land use change on the carbon cycle.Based on this review,visions of future cross-scale,cross-landscape and cross-system model development and applications are discussed.