青藏高原植被生态系统垂直分布变化的情景模拟

如何模拟和揭示青藏高原植被生态系统垂直分布在全球气候变化驱动下的时空变化情景,对定量解析青藏高原陆地生态系统对气候变化响应效应具有重要意义。该论文基于Holdridge life zone （HLZ）模型,结合数字高程模型（DEM）数据,改变模型输入参数模式,发展了改进型HLZ生态系统模型。结合1981-2010（T0）时段的气候观测数据和IPCC CMIP5 RCP2.6、RCP4.5、RCP8.5三种情景2011-2040（T1）、2041-2070（T2）、2071-2100（T3）三个时段气候情景数据,实现了青藏高原植被生态系统垂直分布的时空变化情景模拟。引入生态系统平均中心时空偏移趋势模型和生态多样性指数模型,定量揭示了青藏高原植被生态系统在不同垂直带上的时空变化情景。结果显示：青藏高原共有16种植被生态系统类型;冰雪/冰原、高山潮湿苔原和亚高山湿润森林为青藏高原主要的植被生态系统类型,其面积之和占到了青藏高原总面积的56.26%;高山干苔原、亚高山潮湿森林、山地灌丛、山地湿润森林和荒漠等对气候变化的敏感性总体上高于其它类型;在T0-T3期间,青藏高原的高山湿润苔原、高山干苔原、荒漠呈持续减少趋势,平均每10年将分别减少1.96×10⁴km²、0.15×10⁴km²和1.58×10⁴km²;亚高山潮湿森林、山地湿润森林和山地灌丛呈持续增加趋势,平均每10年将分别增加3.42×10⁴km²、2.98×10⁴km²和1.19×10⁴km²;RCP8.5情景下青藏高原的植被生态系统平均中心的偏移幅度最大,RCP4.5情景下的偏移幅度次之,而RCP2.6情景下的偏移幅度最小。另外,在三种气候变化情景驱动下,青藏高原植被生态系统的生态多样性呈减少趋势。总之,未来不同情景的气候变化将直接影响青藏高原植被生态系统的时空分布格局及其生态多样性,气候变化强度越高,影响就越大,而且气候变化对青藏高原植被生态系统的影响呈现出从低海拔到高海拔递增的影响效应。     

Potential Effects of Climate Change on the Distribution of Cold-Tolerant Evergreen Broadleaved Woody Plants in the Korean Peninsula

Climate change has caused shifts in species’ ranges and extinctions of high-latitude and altitude species. Most cold-tolerant evergreen broadleaved woody plants (shortened to cold-evergreens below) are rare species occurring in a few sites in the alpine and subalpine zones in the Korean Peninsula. The aim of this research is to 1) identify climate factors controlling the range of cold-evergreens in the Korean Peninsula; and 2) predict the climate change effects on the range of cold-evergreens. We used multimodel inference based on combinations of climate variables to develop distribution models of cold-evergreens at a physiognomic-level. Presence/absence data of 12 species at 204 sites and 6 climatic factors, selected from among 23 candidate variables, were used for modeling. Model uncertainty was estimated by mapping a total variance calculated by adding the weighted average of within-model variation to the between-model variation. The range of cold-evergreens and model performance were validated by true skill statistics, the receiver operating characteristic curve and the kappa statistic. Climate change effects on the cold-evergreens were predicted according to the RCP 4.5 and RCP 8.5 scenarios. Multimodel inference approach excellently projected the spatial distribution of cold-evergreens (AUC = 0.95, kappa = 0.62 and TSS = 0.77). Temperature was a dominant factor in model-average estimates, while precipitation was minor. The climatic suitability increased from the southwest, lowland areas, to the northeast, high mountains. The range of cold-evergreens declined under climate change. Mountain-tops in the south and most of the area in the north remained suitable in 2050 and 2070 under the RCP 4.5 projection and 2050 under the RCP 8.5 projection. Only high-elevations in the northeastern Peninsula remained suitable under the RCP 8.5 projection. A northward and upper-elevational range shift indicates change in species composition at the alpine and subalpine ecosystems in the Korean Peninsula.     

高寒草毡层基本属性与固碳能力沿水分和海拔梯度的变化

高寒草毡层是高原寒区自然植被下形成的松软而坚韧且耐搬运的表土层,认识其生态功能是促进草牧业生产休养保护和工程施工主动利用的前提。通过对青藏高原东部若尔盖高原植被的广泛调查,在布设沼泽、退化沼泽、沼泽化草甸、湿草甸、干草甸和退化草甸水分梯度群落样地,以及亚高山草甸、亚高山灌丛草甸、高山灌丛草甸和高山草甸海拔梯度群落样地的基础上,通过对不同类型群落样地草毡层容重、土壤颗粒组成和土壤有机碳(SOC)含量的测定分析,比较了水分和海拔梯度下草毡层固碳能力。结果表明,草毡层厚度平均为30cm,沼泽湿地草毡层容重最小,SOC含量在300g/kg以上;退化草甸容重最高,SOC含量显著下降。不同群落草毡层SOC密度在10—24kg C/m~2之间,随着土壤水分有效性的降低而降低;高山灌丛草甸草毡层SOC密度比草甸高15%。研究得出,保持草毡层稳定的质量含水量阈值为30%,SOC含量阈值为30g/kg;高寒植被草毡层在沼泽到草甸的退化演替中,容重、紧实度变大,有机碳含量减少,碳密度和碳储量下降;灌丛草甸的固碳能力大于草甸,但灌丛草甸的生产功能降低;保持可持续发展的草地生产能力,维护固碳生态功能,需要防止草毡层退化,抑制草甸向灌丛草甸演替。     

气候变化对我国南方人工林地上生物量影响的模拟研究——以会同生态站磨哨实验林场为例

全球气候变暖对陆地生态系统尤其是森林生态系统有着重要的影响,气温升高、辐射强迫的增强将显著改变森林生态系统的结构和功能.南方人工林作为我国森林的重要组成部分,对气候变化的响应日益强烈.为了探究未来气候情景下我国南方人工林对气候变化的响应,降低未来气候变化对人工林可能带来的损失,本研究采用3种最新的气候情景—典型浓度排放路径情景(RCP2.6情景、RCP4.5情景、RCP8.5情景)预估数据,应用生态系统过程模型PnET-Ⅱ和空间直观景观模型LANDIS-Ⅱ模拟2014—2094年间湖南省会同森林生态实验站磨哨实验林场森林的地表净初级生产力(ANPP)、物种建立可能性(SEP)和地上生物量的变化.结果表明: 不同森林类型的SEP和ANPP对气候变化的响应有明显的差异,各森林类型对气候变化的响应程度表现为: 对于SEP,在RCP2.6和RCP4.5情景下,人工针叶林＞天然阔叶林＞人工阔叶林;在RCP8.5情景下,天然阔叶林＞人工阔叶林＞人工针叶林.对于ANPP,在RCP2.6情景下,人工阔叶林＞天然阔叶林＞人工针叶林;在RCP4.5和RCP8.5情景下,天然阔叶林＞人工阔叶林＞人工针叶林.人工针叶林的地上生物量在2050年左右开始下降,天然阔叶林和人工阔叶林整体呈现上升趋势.2014—2094年,研究区地上总生物量在不同气候情景下增加幅度不同,RCP2.6情景下增加了68.2%,RCP4.5情景下增加了79.3%,RCP8.5情景下增加了72.6%.3种情景下的总地上生物量大小排序为: RCP4.5> RCP8.5> RCP2.6.我们认为,适当的增温将有助于未来研究区森林总地上生物量的积累,但过度的增温也可能会阻碍森林的生产和生态功能的持续发展.     

东北地区玉米适应气候变化措施对生产潜力的影响

为探求东北玉米未来如何更好地适应气候变化,本研究采用抗逆品种和推迟播种期两种适应措施,结合区域气候模式模拟的2010-2099年间RCP4.5、RCP8.5两种浓度路径逐日气象资料,分析了不同气候变化情景下东北玉米适应措施的生产潜力变化.结果表明: 2010-2099年间,东北区玉米气候生产潜力的空间分布特征基本为东南向西北减小的趋势,RCP4.5情景下东北玉米生产潜力高于RCP8.5情景,且RCP8.5情景出现极低值年份明显多于RCP4.5情景.所有抗逆品种的玉米生产潜力均高于原有品种,在RCP4.5情景下,耐高温品种的玉米生产潜力更高,在RCP8.5情景下,耐旱品种表现更好,双耐(耐高温、耐旱)品种的玉米生产潜力在2种气候变化情景下均最高.RCP4.5情景下,推迟播种均出现增产情况,其中,推迟30~40 d播种的玉米增产率达到最大;RCP8.5情景下,部分地区出现减产情况.说明适当推迟播种期有利于提高玉米气候生产潜力,但地区间存在差异.     

Forecasting shifts in habitat suitability of three marine predators suggests a rapid decline in inter‐specific overlap under future climate change

Understanding how environmental and climate change can alter habitat overlap of marine predators has great value for the management and conservation of marine ecosystems. Here, we estimated spatiotemporal changes in habitat suitability and inter‐specific overlap among three marine predators: Baltic gray seals (Halichoerus grypus), harbor seals (Phoca vitulina), and harbor porpoises (Phocoena phocoena) under contemporary and future conditions. Location data (>200 tagged individuals) were collected in the southwestern region of the Baltic Sea; one of the fastest‐warming semi‐enclosed seas in the world. We used the maximum entropy (MaxEnt) algorithm to estimate changes in total area size and overlap of species‐specific habitat suitability between 1997–2020 and 2091–2100. Predictor variables included environmental and climate‐sensitive oceanographic conditions in the area. Sea‐level rise, sea surface temperature, and salinity data were taken from representative concentration pathways [RCPs] scenarios 6.0 and 8.5 to forecast potential climate change effects. Model output suggested that habitat suitability of Baltic gray seals will decline over space and time, driven by changes in sea surface salinity and a loss of currently available haulout sites following sea‐level rise in the future. A similar, although weaker, effect was observed for harbor seals, while suitability of habitat for harbor porpoises was predicted to increase slightly over space and time. Inter‐specific overlap in highly suitable habitats was also predicted to increase slightly under RCP scenario 6.0 when compared to contemporary conditions, but to disappear under RCP scenario 8.5. Our study suggests that marine predators in the southwestern Baltic Sea may respond differently to future climatic conditions, leading to divergent shifts in habitat suitability that are likely to decrease inter‐specific overlap over time and space. We conclude that climate change can lead to a marked redistribution of area use by marine predators in the region, which may influence local food‐web dynamics and ecosystem functioning.     

Predicting the responses of forest distribution and aboveground biomass to climate change under RCP scenarios in southern China

In the past three decades, our global climate has been experiencing unprecedented warming. This warming has and will continue to significantly influence the structure and function of forest ecosystems. While studies have been conducted to explore the possible responses of forest landscapes to future climate change, the representative concentration pathways (RCPs) scenarios under the framework of the Coupled Model Intercomparison Project Phase 5 (CMIP5) have not been widely used in quantitative modeling research of forest landscapes. We used LANDIS‐II, a forest dynamic landscape model, coupled with a forest ecosystem process model (PnET‐II), to simulate spatial interactions and ecological succession processes under RCP scenarios, RCP2.6, RCP4.5 and RCP8.5, respectively. We also modeled a control scenario of extrapolating current climate conditions to examine changes in distribution and aboveground biomass (AGB) among five different forest types for the period of 2010–2100 in Taihe County in southern China, where subtropical coniferous plantations dominate. The results of the simulation show that climate change will significantly influence forest distribution and AGB. (i) Evergreen broad‐leaved forests will expand into Chinese fir and Chinese weeping cypress forests. The area percentages of evergreen broad‐leaved forests under RCP2.6, RCP4.5, RCP8.5 and the control scenarios account for 18.25%, 18.71%, 18.85% and 17.46% of total forest area, respectively. (ii) The total AGB under RCP4.5 will reach its highest level by the year 2100. Compared with the control scenarios, the total AGB under RCP2.6, RCP4.5 and RCP8.5 increases by 24.1%, 64.2% and 29.8%, respectively. (iii) The forest total AGB increases rapidly at first and then decreases slowly on the temporal dimension. (iv) Even though the fluctuation patterns of total AGB will remain consistent under various future climatic scenarios, there will be certain responsive differences among various forest types.     

1980-2011年川东平行岭谷区农田土壤有机碳动态

选取重庆市垫江县为川东平行岭谷的典型区,使用1980第二次土壤普查和2011年实测土壤数据,基于土壤类型,运用通用SOC密度/储量计算法和逐步回归分析,对研究区1980—2011年0—20 cm农田SOC动态和动因进行分析,结果表明:(1)1980—2011年农田0—20 cm土层SOC密度/储量总体表现为略有增加态势,单位面积碳增量2307.63 kg C/hm2,碳增汇235945.83 t,增幅为10.74%,年均增长速率为72.11 kg C hm-2a-1;(2)丢碳、固碳和相对平衡面积比37.61∶49.03∶13.36,总体呈西部、西北部高于南部、东南部,更高于东北部和西南部的格局;(3)宏观上1980—2011年农田0—20 cm土层SOC密度/储量变化与土壤类型的分布及利用有很大关系,尤其是黄壤和紫色土在相异的质地本底和不同的扰动下,展现出相反的碳汇/源状态;(4)微观上SOC密度年均变化速率影响最大的因素是SOC密度初始值全N密度C/N比,且全N密度和C/N比拥有正向影响,SOC密度初始值则相反;⑸结果为川东平行岭谷区借助施加适当投入和合适的耕作与管理实践,有效管理农田表层SOC库提供科学依据。     

美味猕猴桃地理分布模拟与气候变化影响分析

为了解气候变化对美味猕猴桃(Actinidia deliciosa)地理分布的影响,结合气候情景,采用Maxent预测美味猕猴桃的适生区的变化趋势。结果表明,基准气候和未来情景下构建的美味猕猴桃分布模型的AUC值均达到极好的标准。基准气候条件下,美味猕猴桃在中国的适生区为22°~38°N,96°~122°E,总面积为3.367 9×106 km2,高适生区位于秦岭-巴山、四川盆地东部、云贵高原东部、武陵山-巫山、武夷山脉。RCP4.5和RCP8.5情景下,美味猕猴桃在中国的高适生区面积将显著减少,中适生区面积则呈增加趋势,两种情景下高、中质心均向偏南或低纬度方向移动,RCP8.5情景下质心的迁移轨迹最长,变动范围最大。Maxent模型的准确预测对于优化猕猴桃产业结构具有重要指导意义。     

21世纪上半叶内蒙古草地植被净初级生产力变化趋势

基于中国气象局国家气候中心新发布的中短期适应气候变化的新情景(RCP4.5)和极端情景(RCP8.5)下的气候预估数据,采用空间化后的CENTURY模型模拟探讨2011－2050年内蒙古草地植被净初级生产力(NPP)的时空变化特征.结果表明: 区域尺度上,未来气候变化情景下内蒙古草地NPP年下降速率分别为0.57 g C·m^-2·a^-1(RCP4.5)、0.89 g C·m^-2·a^-1(RCP8.5);相对于基准时段,RCP4.5情景下内蒙古草地NPP在2020s、2030s、2040s分别下降11.6%、12.0%、18.0%,而RCP8.5情景下降幅分别为23.8%、21.2%、30.1%.不同气候情景下内蒙古草地NPP时空变化特征差异较大,但即使在RCP4.5下未来40年绝大部分草地NPP也将呈现下降趋势,15.6%的草地减产超过20%.这表明未来气候变化情景下内蒙古草地降水略增的态势不足以补偿因温度升高对草地植被初级生产力所产生的负面作用,草地资源的可持续发展将面临更大挑战.     

Storage, patterns and controls of soil organic carbon in the Tibetan grasslands

The soils of the Qinghai-Tibetan Plateau store a large amount of organic carbon, but the magnitude, spatial patterns and environmental controls of the storage are little investigated. In this study, using data of soil organic carbon (SOC) in 405 profiles collected from 135 sites across the plateau and a satellite-based dataset of enhanced vegetation index (EVI) during 2001–2004, we estimated storage and spatial patterns of SOC in the alpine grasslands. We also explored the relationships between SOC density (soil carbon storage per area) and climatic variables and soil texture. Our results indicated that SOC storage in the top 1 m in the alpine grasslands was estimated at 7.4 Pg C (1 Pg=10¹⁵ g), with an average density of 6.5 kg m⁻². The density of SOC decreased from the southeastern to the northwestern areas, corresponding to the precipitation gradient. The SOC density increased significantly with soil moisture, clay and silt content, but weakly with mean annual temperature. These variables could together explain about 72% of total variation in SOC density, of which 54% was attributed to soil moisture, suggesting a key role of soil moisture in shaping spatial patterns of SOC density in the alpine grasslands.     

Modelling past and future peatland carbon dynamics across the pan‐Arctic

The majority of northern peatlands were initiated during the Holocene. Owing to their mass imbalance, they have sequestered huge amounts of carbon in terrestrial ecosystems. Although recent syntheses have filled some knowledge gaps, the extent and remoteness of many peatlands pose challenges to developing reliable regional carbon accumulation estimates from observations. In this work, we employed an individual‐ and patch‐based dynamic global vegetation model (LPJ‐GUESS) with peatland and permafrost functionality to quantify long‐term carbon accumulation rates in northern peatlands and to assess the effects of historical and projected future climate change on peatland carbon balance. We combined published datasets of peat basal age to form an up‐to‐date peat inception surface for the pan‐Arctic region which we then used to constrain the model. We divided our analysis into two parts, with a focus both on the carbon accumulation changes detected within the observed peatland boundary and at pan‐Arctic scale under two contrasting warming scenarios (representative concentration pathway—RCP8.5 and RCP2.6). We found that peatlands continue to act as carbon sinks under both warming scenarios, but their sink capacity will be substantially reduced under the high‐warming (RCP8.5) scenario after 2050. Areas where peat production was initially hampered by permafrost and low productivity were found to accumulate more carbon because of the initial warming and moisture‐rich environment due to permafrost thaw, higher precipitation and elevated CO₂ levels. On the other hand, we project that areas which will experience reduced precipitation rates and those without permafrost will lose more carbon in the near future, particularly peatlands located in the European region and between 45 and 55°N latitude. Overall, we found that rapid global warming could reduce the carbon sink capacity of the northern peatlands in the coming decades.     

Potential aboveground biomass increase in Brazilian Atlantic Forest fragments with climate change

Fragmented tropical forest landscapes preserve much of the remaining biodiversity and carbon stocks. Climate change is expected to intensify droughts and increase fire hazard and fire intensities, thereby causing habitat deterioration, and losses of biodiversity and carbon stock losses. Understanding the trajectories that these landscapes may follow under increased climate pressure is imperative for establishing strategies for conservation of biodiversity and ecosystem services. Here, we used a quantitative predictive modelling approach to project the spatial distribution of the aboveground biomass density (AGB) by the end of the 21st century across the Brazilian Atlantic Forest (AF) domain. To develop the models, we used the maximum entropy method with projected climate data to 2100, based on the Intergovernmental Panel on Climate Change Representative Concentration Pathway (RCP) 4.5 from the fifth Assessment Report. Our AGB models had a satisfactory performance (area under the curve > 0.75 and p value < .05). The models projected a significant increase of 8.5% in the total carbon stock. Overall, the projections indicated that 76.9% of the AF domain would have suitable climatic conditions for increasing biomass by 2100 considering the RCP 4.5 scenario, in the absence of deforestation. Of the existing forest fragments, 34.7% are projected to increase their AGB, while 2.6% are projected to have their AGB reduced by 2100. The regions likely to lose most AGB—up to 40% compared to the baseline—are found between latitudes 13° and 20° south. Overall, although climate change effects on AGB vary latitudinally for the 2071–2100 period under the RCP 4.5 scenario, our model indicates that AGB stocks can potentially increase across a large fraction of the AF. The patterns found here are recommended to be taken into consideration during the planning of restoration efforts, as part of climate change mitigation strategies in the AF and elsewhere in Brazil.     

Priming effect stimulates carbon release from thawed permafrost

Climate warming leads to widespread permafrost thaw with a fraction of the thawed permafrost carbon (C) being released as carbon dioxide (CO₂), thus triggering a positive permafrost C-climate feedback. However, large uncertainty exists in the size of this model-projected feedback, partly owing to the limited understanding of permafrost CO₂ release through the priming effect (i.e., the stimulation of soil organic matter decomposition by external C inputs) upon thaw. By combining permafrost sampling from 24 sites on the Tibetan Plateau and laboratory incubation, we detected an overall positive priming effect (an increase in soil C decomposition by up to 31%) upon permafrost thaw, which increased with permafrost C density (C storage per area). We then assessed the magnitude of thawed permafrost C under future climate scenarios by coupling increases in active layer thickness over half a century with spatial and vertical distributions of soil C density. The thawed C stocks in the top 3 m of soils from the present (2000–2015) to the future period (2061–2080) were estimated at 1.0 (95% confidence interval (CI): 0.8–1.2) and 1.3 (95% CI: 1.0–1.7) Pg (1 Pg = 10¹⁵ g) C under moderate and high Representative Concentration Pathway (RCP) scenarios 4.5 and 8.5, respectively. We further predicted permafrost priming effect potential (priming intensity under optimal conditions) based on the thawed C and the empirical relationship between the priming effect and permafrost C density. By the period 2061–2080, the regional priming potentials could be 8.8 (95% CI: 7.4–10.2) and 10.0 (95% CI: 8.3–11.6) Tg (1 Tg = 10¹² g) C year⁻¹ under the RCP 4.5 and RCP 8.5 scenarios, respectively. This large CO₂ emission potential induced by the priming effect highlights the complex permafrost C dynamics upon thaw, potentially reinforcing permafrost C-climate feedback.     

Climate warming alters subsoil but not topsoil carbon dynamics in alpine grassland

Subsoil contains more than half of soil organic carbon (SOC) globally and is conventionally assumed to be relatively unresponsive to warming compared to the topsoil. Here, we show substantial changes in carbon allocation and dynamics of the subsoil but not topsoil in the Qinghai‐Tibetan alpine grasslands over 5 years of warming. Specifically, warming enhanced the accumulation of newly synthesized (¹⁴C‐enriched) carbon in the subsoil slow‐cycling pool (silt‐clay fraction) but promoted the decomposition of plant‐derived lignin in the fast‐cycling pool (macroaggregates). These changes mirrored an accumulation of lipids and sugars at the expense of lignin in the warmed bulk subsoil, likely associated with shortened soil freezing period and a deepening root system. As warming is accompanied by deepening roots in a wide range of ecosystems, root‐driven accrual of slow‐cycling pool may represent an important and overlooked mechanism for a potential long‐term carbon sink at depth. Moreover, given the contrasting sensitivity of SOC dynamics at varied depths, warming studies focusing only on surface soils may vastly misrepresent shifts in ecosystem carbon storage under climate change.     

基于BIOME-BGC模型的秦岭北坡太白红杉林碳源/汇动态和趋势研究

为了解秦岭北坡太白红杉(Larix chinensis)的碳源/汇动态,运用BIOME-BGC模型模拟了1959-2016年太白红杉生产力、碳储量和碳利用效率(CUE),并利用气候情景设定方法预测碳源/汇功能的未来趋势。结果表明,58年间太白红杉的平均净初级生产力(NPP)、初级生产力(GPP)和净生态系统生产力(NEP)分别为328.59、501.56和31.42 g C m–2a–1,平均碳储量为35.38 kg C m–2a–1,平均CUE为0.65;除1960-1961、1969-1970、1997-1999年为"碳源"年外,绝大多数年份为"碳汇"年,年内呈现"碳源-碳汇-碳源"的变化特征,碳储量总体增加,潜在固碳能力较为稳定。GPP、NPP、碳储量的正向作用排序为气温上升CO_2浓度增加,NEP的正向作用排序反之,降水增加对生产力和碳储量增加起反作用,气温升高对CUE起反作用;气温和CO_2浓度是北坡太白红杉生长的限制因子,气温的限制性强于CO_2浓度,未来气温或CO_2浓度升高有利于碳汇功能发挥,降水增加减弱碳汇效果。RCP4.5、RCP8.5情景下太白红杉生产力和碳储量在21世纪呈上升趋势,RCP8.5上升幅度略大于RCP4.5,潜在固碳能力仍较强;1-3月和10-12月为"碳源"月,5-9月为"碳汇"月。这揭示了气候变化背景下气温、降水和CO_2浓度对太白红杉碳源/汇的影响方式,气温和CO_2浓度上升是碳汇的促进因素,降水增加为阻碍因素。     

China's wetland soil organic carbon pool: New estimation on pool size,change, and trajectory

Robust estimates of wetland soil organic carbon (SOC) pools are critical to understanding wetland carbon dynamics in the global carbon cycle. However, previous estimates were highly variable and uncertain, due likely to the data sources and method used. Here we used machine learning method to estimate SOC storage and their changes over time in China's wetlands based on wetland SOC density database, associated geospatial environmental data, and recently published wetland maps. We built a database of wetland SOC density in China that contains 809 samples from 181 published studies collected over the last 20 years as presented in the published literature. All samples were extended and standardized to a 1-m depth, on the basis of the relationship between SOC density data from soil profiles of different depths. We used three different machine learning methods to evaluate their robustness in estimating wetland SOC storage and changes in China. The results indicated that random forest model achieved accurate wetland SOC estimation with R² being .65. The results showed that average SOC density of top 1 m in China's wetlands was 25.03 ± 3.11 kg C m⁻² in 2000 and 26.57 ± 3.73 kg C m⁻² in 2020, an increase of 6.15%. SOC storage change from 4.73 ± 0.58 Pg in 2000 to 4.35 ± 0.61 Pg in 2020, a decrease of 8.03%, due to 13.6% decreased in wetland area from 189.12 × 10³ to 162.8 × 10³ km² in 2020, despite the increase in SOC density during the same time period. The carbon accumulation rate was 107.5 ± 12.4 g C m⁻² year⁻¹ since 2000 in wetlands with no area changes. Climate change caused variations in wetland SOC density, and a future warming and drying climate would lead to decreases in wetland SOC storage. Estimates under Shared Socioeconomic Pathway 1-2.6 (low-carbon emissions) suggested that wetland SOC storage in China would not change significantly by 2100, but under Shared Socioeconomic Pathway 5-8.5 (high-carbon emissions), it would decrease significantly by approximately 5.77%. In this study, estimates of wetland SOC storage were optimized from three aspects, including sample database, wetland extent, and estimation method. Our study indicates the importance of using consistent SOC density and extent data in estimating and projecting wetland SOC storage.     

Evaluation of global warming impacts on the carbon budget of terrestrial ecosystems in monsoon Asia: a multi-model analysis

This study assesses the potential impacts of future global warming on the carbon budget of terrestrial ecosystems across monsoon Asia using the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP) dataset. We used simulation results of two emission pathways (RCP2.6 and RCP8.5), climate projections of five climate models, and seven terrestrial biome models to analyze the changes in net primary production and carbon stocks in the South, Southeast, and East Asian subregions during the period 1981–2099. The simulations indicated that by the end of the 21st century, net primary production would increase by 9–45 % and ecosystem carbon storage would increase by 42–86 Pg C. The clearest climatic impacts were found when using the adaptation-oriented emission scenario (RCP8.5), which assumes a greater CO₂ increase and a larger change in climatic conditions. Substantial disparities in temporal trajectories and spatial patterns were found in the estimated changes, owing to the uncertainties in the emission scenarios, climate projections, and ecosystem models. We attempted to derive consistent patterns throughout the simulations to specify potential hotspots of climatic impacts (e.g., soil carbon change in the southern Tibetan Plateau). Finally, we discuss changes to the climatic characteristics in the study region (e.g., a change in the rainy season), the implications for ecosystem services, and the need for collaborative field monitoring studies.     

Downscaling climate parameters in Fars province,using models of the fifth report and RCP scenarios

Climate change is responsible for many extreme weather events on the Earth, including sea level rising, drastic shifts in temperature and precipitation regimes, and changes in flood and drought frequency. In the present study, based on IPCC's latest report, outputs of three GCMs, the EC-EARTH, the HadGEM2-ES and the MIROC5 were downscaled by the LARS-WG model and under RCP4.5 and RCP8.5 scenarios. Also, variations in precipitation, maximum and minimum temperatures for the time series 2021–2040, 2041–2060 and 2061–2080 have been projected and the precipitation extreme values in Gumbel distribution were evaluated. For this purpose, the climate records obtained from Shiraz, Lar and Abadeh synoptic stations in Fars province were used to establish the baseline period (1985–2010). The results of all the stations show that Changes in maximum and minimum temperatures under RCP4.5 and RCP8.5 scenarios have increased. The increase in minimum temperature for the baseline period compared to the upcoming period 2021–2040 under the selected scenarios were 1.43 and 1.65C, respectively. The increase in precipitation for the baseline period compared to the upcoming period (2021–2040) under the two scenarios were up to 2.93 and 1.95, respectively. Furthermore, longer return periods are accompanied by higher amounts of probable maximum precipitation under RCP4.5 and RCP8.5, where extreme precipitation is showing higher level of rise under the latter scenario.     

四川森林植被碳储量的时空变化

利用平均木法建立森林生物量与蓄积量模型,结合四川森林资源二类调查数据,研究了森林碳密度和碳储量的时空变化.结果表明 四川森林碳储量从1974年的300.02 Tg增加到2004年的469.96 Tg,年均增长率1.51%,表明其是CO2的"汇".由于人工林面积的增加,森林植被的平均碳密度从49.91 Mg·hm-2减少到37.39 Mg·hm-2.四川森林碳储量存在空间差异性,表现为川西北高山峡谷区＞川西南山区＞盆周低山区＞盆地丘陵区＞川西平原区.森林碳密度由东南向西北呈现逐渐增加趋势,即盆地丘陵区＜川西平原区＜川西南山区＜盆周低山区＜川西北高山峡谷区.通过分区森林经营与管理将提高四川森林的碳吸存能力.