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Notoginseng saponin R1; ginsenosides Rg1, Re, Rb1, and Rd; the sum of the five saponins; and underground-part fresh weight (UPFW) of single plants were used as quality evaluation indices for Panax notoginseng (Burk.) F. H. Chen (P. notoginseng). Comprehensive evaluation of P. notoginseng samples from 30 production areas was performed using that MaxEnt model. Spatial pattern changes in suitable P. notoginseng habitats were predicted for current and future periods (2050s, 2070s, and 2090s) using SSP126 and SSP585 models. The results revealed that temperature, precipitation, and solar radiation were important environmental variables. Suitable habitats were located mainly in Yunnan, Guizhou, and Sichuan Provinces. The distribution core of P. notoginseng is predicted to shift southeast in the future. The saponin content decreased from the southeast to the northwest of Yunnan Province, which was contrary to the UPFW trend. This study provides the necessary information for the protection and sustainable utilization of P. notoginseng resources, and a theoretical reference for its application in the quality evaluation of Chinese medicinal products. [ABSTRACT FROM AUTHOR]

Amidst global climate change and unsustainable human exploitation of water resources, water has emerged as a critical factor constraining global agricultural food production and ecological environments. Particularly in agricultural powerhouses like China, irrigation water accounts for a significant portion of freshwater resource utilization. However, the inefficiency of irrigation water usage has become a weak link in water resource management. To better assess irrigation water efficiency, an accurate estimation of regional irrigated areas is urgently needed. This study proposes a method for identifying actual irrigated areas based on remote sensing-derived evapotranspiration (ET) to address the challenge of accurately interpreting irrigated areas in tropical regions. Using Yunnan Province's Yuanmou irrigation district as a case study, this research combined ground monitoring data and remote sensing data to identify actual irrigated areas through ET inversion and downscaling methods using the Penman–Monteith–Leuning (PML) model. In 2023, the total irrigated area interpreted from remote sensing in the study area was approximately 15,000 hm2, with a comparison against validation points revealing an extraction error of 16%. The small error indicates that this method can effectively enhance the reliability of monitoring actual irrigated areas, thus providing valuable data support for agricultural irrigation water management. [ABSTRACT FROM AUTHOR]

Tinospora Miers is considered a valuable medicinal herb that is suffering from severe habitat degradation due to climate change and human activities, but the variations in its suitable habitats and ecological service values remain unclear, especially in the context of accelerating global warming. In this study, we employed the MaxEnt model to estimate the suitable habitat changes and ecological service values of three rare Tinospora (T. craveniana, T. yunnanensis, and T. sinensis) species in China under four climate change scenarios (SSP126, SSP245, SSP370, and SSP585) from 2041 to 2100. The results show that the suitable habitats of T. craveniana, T. yunnanensis, and T. sinensis are mainly distributed in Sichuan, Yunnan, and Guangxi, respectively. Under the future climate scenarios, the suitable habitat of T. craveniana and T. sinensis is projected to expand toward the northeast and north, while that of T. yunnanensis will contract toward the northeast. The mean diurnal temperature range is the main environmental factor affecting T. craveniana and T. yunnanensis, while the annual mean temperature is a more important factor affecting T. sinensis. In the SSP245 scenario, T. craveniana and T. yunnanensis are expected to have the highest ecological service values from 2081 to 2100, while they will be relatively consistent in other climate scenarios and chronologies. The case of water protection accounts for the highest proportion of the total ecosystem service values, except for the economic value. This study provides a scientific reference for the diversity conservation of these rare species. [ABSTRACT FROM AUTHOR]

Biodiversity is crucial for ecosystem functioning, but it is rapidly declining due to human activities and climate change. Protecting biodiversity has become a key priority for global environmental conservation actions. Rare and endangered species have a great impact on the ecosystem, yet due to their limited survival capacity, they are more prone to extinction, thus exerting a significant impact on biodiversity. However, current research reveals a lack of information concerning the potential distribution and changes of these species. This study used the maximum entropy model to predict the present and future potential habitats of rare and endangered species in Yunnan Province. After superimposing model results, four richness regions are divided by the natural breakpoint method and analyzed. Existing protected areas are compared with hotspots, and the land-use composition of hotspots is also analyzed. The results revealed that, in both current and future scenarios, rare and endangered species in Yunnan Province are primarily found in the western mountainous region, the Xishuangbanna–Wenshan high temperature area, and the Kunming–Qujing dense vegetation cover area. These species are also expanding their distribution towards the western mountainous area. However, under the low carbon emission scenario (RCP2.6), these species will spread from the high abundance regions to the low altitude hotspots by 2070. In the high carbon emissions scenario (RCP8.5), there will be fewer high abundance areas in 2070 than in 2050. The transfer matrix analysis reveals regional richness variations over time. Furthermore, the analysis revealed significant conservation gaps and found that existing hotspot areas were heavily affected by human activities. To improve conservation efficiency, it is necessary to enhance the protection of existing hotspots in Yunnan Province. Climate change plays a significant role in species migration, with precipitation levels being a key factor. The necessary actions should be taken to address the insufficient protection, resolve conflicts between human activities and land use in critical areas, and formulate effective strategies for adapting to future climate changes. Yunnan Province, with its rich species resources, has the potential to become a global innovator in biodiversity conservation by implementing improved conservation strategies. [ABSTRACT FROM AUTHOR]

The Hengduan Mountains, with their strong altitudinal vegetation zonation, form a biodiversity hotspot which offers the potential for comparison between sites in order to understand how this zonation arose and how it has responded to climate change and human impacts through time. This paper presents a 22 570-year pollen record of vegetational and climatic change based on a core 320 cm in depth collected from Wenhai Lake on Jade Dragon Snow Mountain, one of the highest peaks in the Hengduan Mountains region of Yunnan, Southwest China. From 22 570 to 21 140 cal yr BP, the vegetation was dominated by broad-leaved forest (comprising mainly Quercus, Betula and Castanopsis), accompanied by needle-leaved forest (mainly Pinus and Abies), indicating a rather cold and dry climate relative to the present followed by cold and wet conditions. In the period between 21 140 and 19 350 cal yr BP, the vegetation was still dominated by broad-leaved forest and needle-leaved forest as before but with a notable increase in Betula pollen and a sharp decrease in Quercus pollen, implying a relatively cold and dry climate with several fluctuations in humidity. The period 19 350 to 17 930 cal yr BP was a transition stage from broad-leaved forest to needle-leaved forest, with a dramatic decrease in Quercus pollen and a maximum reading for Abies pollen, reflecting the coldest and driest climate since 22 570 cal yr BP. The expansion in needle-leaved forest dominated by Pinus and Abies (22 570-17 930 cal yr BP) along with an increase of Betula might correspond to the Last Glacial Maximum (LGM; the start of the LGM perhaps occurred prior to the basal age of the core). Between 17 930 and 9250 cal yr BP, needle-leaved forest declined and broad-leaved forest began to increase at first, suggesting increases in temperature and humidity, while towards the end of the period, needle-leaved forest expanded and broad-leaved forest shrank, indicating a colder and drier climate, possibly corresponding to the Younger Dryas. From 9250 cal yr BP to the present, the vegetation has been dominated by needle-leaved forest (comprising mainly Pinus, Abies and Tsuga), interspersed with broad-leaved Quercus and Betula, reflecting a significant decline in humidity from the early to late Holocene. During this period, human activity likely increased in this region, with impacts on the vegetation such as a distinct decrease in Pinus and Quercus pollen and an increase in Polygonaceae pollen in the upper 30 cm of the core. The marked decline in Quercus pollen compared with the early stage of this period, in particular, in the Wenhai core can be correlated with that observed in the Haligu core (situated about 2 km away) between 2400 cal yr BP and the present. [ABSTRACT FROM AUTHOR]

Rhodiola L. has high nutritional and medicinal value. Little is known about the properties of its habitat distribution and the important eco-environmental factors shaping its suitability. Rhodiola coccinea (Royle) Boriss., Rhodiola gelida Schrenk, Rhodiola kirilowii (Regel) Maxim., and Rhodiola quadrifida (Pall.) Fisch. et Mey., which are National Grade II Protected Plants, were selected for this research. Based on high-resolution environmental data for the past, current, and future climate scenarios, we modeled the suitable habitat for four species by MaxEnt, evaluated the importance of environmental factors in shaping their distribution, and identified distribution shifts under climate change scenarios. The results indicate that the growth distribution of R. coccinea, R. kirilowii, and R. quadrifida is most affected by bio10 (mean temperature of warmest quarter), bio3 (isothermality), and bio12 (annual precipitation), whereas that of R. gelida is most affected by bio8 (mean temperature of wettest quarter), bio13 (precipitation of wettest month), and bio16 (precipitation of wettest quarter). Under the current climate scenario, R. coccinea and R. quadrifida are primarily distributed in Tibet, eastern Qinghai, Sichuan, northern Yunnan, and southern Gansu in China, and according to the 2070 climate scenario, the suitable habitats for both species are expected to expand. On the other hand, the suitable habitats for R. gelida and R. kirilowii, which are primarily concentrated in southwestern Xinjiang, Tibet, eastern Qinghai, Sichuan, northern Yunnan, and southern Gansu in China, are projected to decrease under the 2070 climate scenario. Given these results, the four species included in our study urgently need to be subjected to targeted observation management to ensure the renewal of Rhodiola communities. In particular, R. gelida and R. kirilowii should be given more attention. This study provides a useful reference with valuable insights for developing effective management and conservation strategies for these four nationally protected plant species. [ABSTRACT FROM AUTHOR]

• Based on the principles of SPEI, we develop a GDAI. • The relationship between GDAI and AI is closer. • The correlation between GDAI and SPEI is also better. Climate change has increased the risk of drought in both arid and non-arid regions of the globe. Therefore, in order to monitor and evaluate global drought and aridity, based on the principle of standardized precipitation evapotranspiration index (SPEI), this paper selected precipitation and potential evapotranspiration data and used a frequency calculation method to develop a multi-scale global drought aridity index (GDAI) that concurrently considers spatial and temporal variation characteristics: the spatiotemporal standardized precipitation evapotranspiration index. The index was compared with the aridity index (AI) and SPEI. The results showed that the correlation coefficients between GDAI and AI were greater than 0.8 in most areas, and the relationship was closer and could reveal the global aridity and wetness zoning. In addition, the correlation between GDAI and SPEI was also better, which could capture the temporal change characteristics of drought. Moreover, this study also compared the grades of GDAI and SPEI with the actual drought grades in Yunnan from September 2009 to August 2010, and found that GDAI was better than SPEI, and GDAI was the most accurately evaluated at the 3 month time scale, with an accuracy rate of 86.11%. Therefore, this index is more helpful for the assessment and monitoring of global drought and aridity. [ABSTRACT FROM AUTHOR]

Climate change is a major factor affecting biodiversity and species distribution, particularly of montane species. Species may respond to climate change by shifting their range to higher elevations. The southeastern Qinghai‐Tibetan Plateau (QTP) and the Hengduan Mountains are considered as global biodiversity hotspots. However, information on the response of maple species to climate change in these regions was limited. Therefore, we selected two maple species that occur there and assessed changes in their habitat suitability under past, present and future climate scenarios in Biomod2. The results showed that temperature seasonality (bio4) was the most critical factor influencing their potential distributions. The distribution of potentially suitable habitat for Acer caesium and Acer stachyophyllum was predicted to be larger during the LGM compared to the present. Under the current climate scenario, the largest areas of potentially suitable habitat for these species were mainly located in southeastern Tibet, the Hengduan Mountains in northwestern Yunnan and western Sichuan, the Qinling‐Daba Mountains in southern Gansu and the Wumeng‐Daliang Mountains in northeastern Yunnan, western Guizhou and southeastern Sichuan. Under future climate change scenarios, the predicted loss of suitable habitat areas for these two species ranged from 13.78% to 45.71% and the increase ranged from 18.88% to 57.98%, with an overall increasing trend. The suitable habitat areas were predicted to shift towards the eastern parts of the QTP under both the pessimistic and optimistic future climate change scenarios in the 2050s and the 2070s, which became evident as global warming intensified, particularly in the eastern QTP and the Hengduan Mountains. Our results highlight the possibility that the diverse topography along altitudinal gradients in the QTP and the Hengduan Mountains may potentially mitigate the range contraction of mountain plants in response to climate warming. These findings provide a basis for planning conservation areas, planting and species conservation in the mountainous areas of southern China under the anticipated global warming. [ABSTRACT FROM AUTHOR]

Nature-based Solutions (NbS) can undoubtedly play a significant role in carbon neutrality strategy. Forests are a major part of the carbon budget in terrestrial ecosystems. The possible response of the carbon balance of southwestern forests to different climate change scenarios was investigated through a series of simulations using the forest ecosystem carbon budget model for China (FORCCHN), which clearly represents the influence of climate factors on forest carbon sequestration. Driven by downscaled global climate model (GCM) data, the FORCCHN evaluates the carbon sink potential of southwestern forest ecosystems under different shared socioeconomic pathways (SSPs). The results indicate that, first, gross primary productivity (GPP), ecosystem respiration (ER) and net primary productivity (NPP) of forest ecosystems are expected to increase from 2020 to 2060. Forest ecosystems will maintain a carbon sink, but net ecosystem productivity (NEP) will peak and begin to decline in the 2030s. Second, not only is the NEP in the SSP1-2.6 scenario higher than in the other climate change scenarios for 2025–2035 and 2043–2058, but the coefficient of variation of the NEP is also narrower than in the other scenarios. Third, in terms of spatial distribution, the carbon sequestration potential of northwest and central Yunnan is significantly higher than that of other regions, with a slight upward trend in NEP in the future. Finally, GPP and ER are significantly positively correlated with temperature and insignificantly correlated with precipitation, and the increasing temperature will have a negative and unstable impact on forest carbon sinks. This study provides a scientific reference for implementing forest management strategies and achieving sustainable development. [ABSTRACT FROM AUTHOR]

Simple Summary: To form a better understanding and benefit future conservation of the apollo and swallowtail butterflies in the Hengduan Mountains in China, the present research projected the 59 Papilionidae species' spatial richness using the Maxent model and predicted the response to climate change. The spatial pattern of apollos concentrated in the subalpine to alpine areas in western Sichuan, northwestern Yunnan, and eastern Tibet, while that of swallowtails is more confined to the tropical and subtropical valleys of western Yunnan and western Sichuan. Both subfamilies would exhibit northward and upward range shifts with climate change but many apollos would experience drastic habitat contraction, resulting in lower species richness, while most swallowtails would experience habitat expansion, and the species richness would increase. Species with habitat contraction, narrow-ranged distribution and endemicity require more conservation measures in the future. The family of Papilionidae (Lepidoptera: Papilionoidea) is a group of butterflies with high ecological and conservation value. The Hengduan Mountains (HMDs) in Southwest China is an important diversity centre for these butterflies. However, the spatial distribution pattern and the climate vulnerability of Papilionidae butterflies in the HDMs remain unknown to date. The lack of such knowledge has already become an obstacle in formulating effective butterfly conservation strategies. The present research compiled a 59-species dataset with 1938 occurrence points. The Maxent model was applied to analyse the spatial pattern of species richness in subfamilies Parnassiinae and Papilioninae, as well as to predict the response under the influence of climate change. The spatial pattern of both subfamilies in the HDMs has obvious elevation prevalence, with Parnassiinae concentrated in the subalpine to alpine areas (2500–5500 m) in western Sichuan, northwestern Yunnan and eastern Tibet, while Papilioninae is concentrated in the low- to medium-elevation areas (1500–3500 m) in the river valleys of western Yunnan and western Sichuan. Under the influence of climate change, both subfamilies would exhibit northward and upward range shifts. The majority of Parnassiinae species would experience drastic habitat contraction, resulting in lower species richness across the HDMs. In contrast, most Papilioninae species would experience habitat expansion, and the species richness would also increase significantly. The findings of this research should provide new insights and a clue for butterfly diversity and climatic vulnerability in southwestern China. Future conservation efforts should be focused on species with habitat contraction, narrow-ranged distribution and endemicity with both in situ and ex situ measures, especially in protected areas. Commercialised collecting targeting these species must also be regulated by future legislation. [ABSTRACT FROM AUTHOR]

Bamboo is a plant that may replace plastics and wood as a new green environmental protection material that can be developed. Ferrocalamus strictus is a very special and rare bamboo which is a plant species with extremely small populations (PSESP) endemic to Yunnan, China, and it is listed as a China key national first-class protected wild plant. To explore the effects of extreme climate and environmental changes on this PSESP, we conducted a case study on the response of F. strictus to climate under two extreme future emission scenarios. We combined 29 environmental variables, including the temperature, precipitation, altitude, slope, aspect, soil pH, soil organic carbon content, and mean UV-B radiation of the highest month, to analyze the important environmental factors limiting the distribution of F. strictus and identified the priority conservation areas (PCAs) of F. strictus. Under the two future extreme climate scenarios, the core potential suitable distribution area of F. strictus would decrease by 26%–34% in 2040, 44%–46% in 2060, and 23%–58% in 2080, respectively. Bio18 (precipitation in the warmest quarter) and Bio3 (isotherm) were the two key factors limiting the geographical distribution of F. strictus (the contribution rates were 40.1% and 18.45%, respectively). The results of this study show that F. strictus is in urgent need of protection and PSESPs require more attention. [ABSTRACT FROM AUTHOR]

Climate change is an important driver of species distribution and biodiversity. Understanding the response of plants to climate change is helpful to understand species differentiation and formulate conservation strategies. The genus Polyspora (Theaceae) has an ancient origin and is widely distributed in subtropical evergreen broad‐leaved forests. Studies on the impacts of climate change on species geographical distribution of Chinese Polyspora can provide an important reference for exploring the responses of plant groups in subtropical evergreen broad‐leaved forests with geological events and climate change in China. Based on the environmental variables, distribution records, and chloroplast genomes, we modeled the potential distribution of Chinese Polyspora in the Last Glacial Maximum, middle Holocene, current, and future by using MaxEnt‐ArcGIS model and molecular phylogenetic method. The changes in the species distribution area, centroid shift, and ecological niche in each periods were analyzed to speculate the response modes of Chinese Polyspora to climate change in different periods. The most important environmental factor affecting the distribution of Polyspora was the precipitation of the driest month, ranging from 13 to 25 mm for the highly suitable habitats. At present, highly suitable distribution areas of Polyspora were mainly located in the south of 25°N, and had species‐specificity. The main glacial refugia of the Chinese Polyspora might be located in the Ailao, Gaoligong, and Dawei Mountains of Yunnan Province. Jinping County, Pingbian County, and the Maguan County at the border of China and Vietnam might be the species differentiation center of the Chinese Polyspora. Moderate climate warming in the future would be beneficial to the survival of P. axillaris, P. chrysandra, and P. speciosa. However, climate warming under different shared socio‐economic pathways would reduce the suitable habitats of P. hainanensis and P. longicarpa. [ABSTRACT FROM AUTHOR]

Climate change will significantly affect the distribution area of species. Through establishing distribution model, we can simulate the current and future potential distribution range and provide reference for the introduction and cultivation planning of rare or economic plants. Dendrocalamus sinicus, endemic to Yunnan Province of China, is the strongest woody bamboo in the world. In the present study, the MaxEnt model was performed to simulate the distribution of different types of D. sinicus in China and neighboring countries or regions. The results suggested that the suitable distribution range of "straight type", the main type for cultivation and utilization, was 8°-30°N and 73°-122°E under the current climate conditions, while the potential distribution range of "bending type" was 6°-31°N and 79°-109°E. The two most key climate variables associated with distribution of "straight type" were "Temperature Annual Range" with 36.6% contribution rate and "Temperature Seasonality" (32.4%), while "Isothermality" (47.8%) and "Precipitation of Driest Month" (24.8%) for "bending type". Under different climate change scenarios (SSP1-2.6, SSP5-8.5) and periods (2050, 2090), the potential distribution area of the "straight type" were apparently different, indicating that the distribution area of D. sinicus will be affected significantly by climate changes in the future. Our findings would be not only beneficial to understanding limiting factors for natural distribution of D. sinicus, but also helpful for further germplasm conservation, introduction and cultivation planning of this rare woody bamboo. [ABSTRACT FROM AUTHOR]

Background. With the exacerbating effects of the global climate change and the more and more attention to the study of plant carbon sink, an increasing number of researches on plant carbon sinks has grown. Although many studies exist on shrub vegetation, soil and litters, most studies focus on the community structure, biomass, surface soil of single plant and shrub layer vegetation, and lack the studies which included the potential relationships between climate change and ecological stoichiometric elements, comprehensive research on main species, even herb and litter layer. In order to provide relevant theoretical basis and data support, it is necessary to take the main terrestrial shrub ecosystem in Central Yunnan as the starting point to analyze and explore its carbon sink distribution characteristics, formation causes, the correlation between climatic factors (temperature and precipitation) and stoichiometric elements, which from community and species levels. Methods. Plants which originated from 12 main shrub species, litter and soil samples which collected in 69 plots were from 23 plots (Q1-Q23) of 11 cities (countries) in the central Yunnan, China. The biomass and carbon density distribution pattern of each shrub ecosystem and the potential correlations with main climate factors was explored and identified. Some indexes were analyzed such as biomass and carbon density of each part of the shrub ecosystem distribution pattern, correlation, significant changes, formation reasons with the mean value (±standard deviation: SD). Through the redundancy analysis(RDA) of carbon (c), nitrogen (n), phosphorus (P) and main climate factors (precipitation and temperature), the distribution pattern of stoichiometric elements in shrub ecosystem can be judged. Results. (1) The above-ground biomass (AGB), under-ground biomass (UGB) and root-shoot ratio (R/S) were between 1.13-2.03 t/hm2, 0.62-1.49 t/hm2, and 0.38-0.84, the carbon element was distributed in herb layer under-ground part and rhizomes of the shrub layer mostly. (2) The fitting slope of AGB and UGB of shrub communities and species was in accordance with the allometric distribution growth relationship, the R/S of shrubs was smaller than other vegetation types. Mean annual temperature (MAT) and mean annual precipitation (MAP) are not the main factors which affect the biomass and R/S. (3) The contents of C, N and P elements in leaves were significantly higher than other parts in shrub layer. P in shrub layer above-ground part is much higher than under-ground part. The surface soil layer has the highest C content, and decreased with the depth, so as the impact of vegetation and litter on the content of soil elements. Both of the correlation of MAT with N content of leaf, C/N of stem, the correlation of MAP with C content, C/N of soil is the greatest. [ABSTRACT FROM AUTHOR]

Frequently occurring mega-droughts under current global climate change have attracted broad social attention. A paleoclimatic perspective is needed to increase our understanding of the causes and effects of droughts. South-western (SW) China has been threatened by severe seasonal droughts. Our current knowledge of millennial-scale dry and wet phases in this region is primarily based on the variability of the Indian summer monsoon. However, water availability over land does not always follow patterns of monsoonal precipitation but also depends on water loss from evaporation and transpiration. Here, we reconstructed precipitation intensity, lake hydrological balance and the soil water stress index (SWSI) for the last 27 000 years. Grain size, geochemical and pollen records from Yilong Lake reveal the long-term relationships and inconsistencies of dry–wet patterns in meteorological, hydrological and soil systems in the central Yunnan region, SW China. Our results show that the long-term trends among precipitation, hydrological balance and soil moisture varied through time. The hydrological balance and soil moisture were primarily controlled by temperature-induced evaporation change during periods of low precipitation such as the Last Glacial Maximum and Younger Dryas. During periods of high precipitation (the early to late Holocene), intensified evaporation from the lake surface offset the effects of increased precipitation on the hydrological balance. However, abundant rainfall and the dense vegetation canopy circumvented a soil moisture deficit that might have resulted from rising temperature. In conclusion, the hydrological balance in the central Yunnan region was more sensitive to temperature change while soil moisture could be further regulated by vegetation changes over millennial timescales. Therefore, under future climate warming, the surface water shortage in the central Yunnan region may become even more serious. Our study suggests that reforestation efforts may provide some relief to soil moisture deficits in this region. [ABSTRACT FROM AUTHOR]

Satellite observations reveal that China has been leading the global greening trend in the past 2 decades. We assessed the impact of land cover change as well as climate variability on total biogenic volatile organic compound (BVOC) emission in China from 2001–2016. We found the greening trend in China is leading a national-scale increase in BVOC emission. The BVOC emission level in 2016 could be 11.7 % higher than that in 2001 because of higher tree cover fraction and vegetation biomass. On the regional scale, the BVOC emission level from 2013–2016 could be 8.6 %–19.3 % higher than that from 2001–2004 in hotspots including (1) northeastern China, (2) Beijing and its surrounding areas, (3) the Qin Mountains, (4) Yunnan Province, (5) Guangxi–Guangdong provinces, and (6) Hainan island because of the land cover change without considering the impact of climate variability. The comparison among different scenarios showed that vegetation changes resulting from land cover management are the main driver of BVOC emission change in China. Climate variability contributed significantly to interannual variations but not much to the changing trend during the study period. In the standard scenario, which considers both land cover change and climate variability, a statistically significant increasing trend can still be found in regions including Beijing and its surroundings, Yunnan Province, and Hainan island, and BVOC emission total amount in these regions from 2013–2016 is 11.0 %–17.2 % higher that from 2001–2004. We compared the long-term HCHO vertical columns (VC) from the satellite-based Ozone Monitoring Instrument (OMI) with the estimation of isoprene emission in summer. The results showed statistically significant positive correlation coefficients over the regions with high vegetation cover fractions. In addition, the isoprene emission and HCHO VC both showed statistically significant increasing trends in the south of China where these two variables have high positive correlation coefficients. This result may support our estimation of the variability and trends of BVOC emission in this region; however, the comparison still has large uncertainties since the chemical and physical processes, including transportation, diffusion and chemical reactions, were not considered. Our results suggest that the continued increase in BVOC will enhance the importance of considering BVOC when making policies for controlling ozone pollution in China along with ongoing efforts to increase the forest cover fraction. [ABSTRACT FROM AUTHOR]

The impact of global climate change on vegetation has become increasingly prominent over the past several decades. Understanding vegetation change and its response to climate can provide fundamental information for environmental resource management. In recent years, the arid climate and fragile ecosystem have led to great changes in vegetation in Yunnan Province, so it is very important to further study the relationship between vegetation and climate. In this study, we explored the temporal changes of normalized difference vegetation index (NDVI) in different seasons based on MOD13Q1 NDVI by the maximum value composite and then analyzed spatial distribution characteristics of vegetation using Sen's tendency estimation, Mann–Kendall significance test, and coefficient of variation model (CV) combined with terrain factors. Finally, the concurrent and lagged effects of NDVI on climate factors in different seasons and months were discussed using the Pearson correlation coefficient. The results indicate that (1) the temporal variation of the NDVI showed that the NDVI values of different vegetation types increased at different rates, especially in growing season, spring, and autumn; (2) for spatial patterns, the NDVI, CV, and NDVI trends had strong spatial heterogeneity owning to the influence of altitudes, slopes, and aspects; and (3) the concurrent effect of vegetation on climate change indicates that the positive effect of temperature on NDVI was mainly in growing season and autumn, whereas spring NDVI was mainly influenced by precipitation. In addition, the lag effect analysis results revealed that spring precipitation has a definite inhibition effect on summer and autumn vegetation, but spring and summer temperature can promote the growth of vegetation. Meanwhile, the precipitation in the late growing season has a lag effect of 1-2 months on vegetation growth, and air temperature has a lag effect of 1 month in the middle of the growing season. Based on the above results, this study provided valuable information for ecosystem degradation and ecological environment protection in the Yunnan Province. [ABSTRACT FROM AUTHOR]

A full analysis of 3-month Standardized Precipitation-Evapotranspiration index (SPEI-3) changes and attribution analyses are of significance for deeply understanding dryness/wetness evolutions and thus formulating specific measures to sustain regional development. In this study, we analyze monthly and annual SPEI-3 changes over Southwest China (SWC; including Sichuan (SC), Chongqing (CQ), Guizhou (GZ), Yunnan (YN), and west Guangxi (wGX)) during 1961–2012, using the SPEI model and routine meteorological measurements at 269 weather sites. For SWC and each subregion (excluding wGX), annual SPEI-3 during 1961–2012 tends to decrease, and drying is at most of months in January and September–December, but wetting is in February–August (excluding March for wGX). Additionally, more than 50% of sites show declined and increased SPEI-3 in January, April, June, and August–December and the remaining months, respectively. Except for wGX with dominant of ET0, annual SPEI-3 changes in SWC and other four subregions have dominant of precipitation. Spatially, annual SPEI-3 changes at 59% of sites are because of precipitation, generally located in southeast SC, south YN, CQ, GZ, and south and northeast wGX. Nevertheless, dominants at regional and site scales vary among months, e.g., SWC, SC, CQ, and GZ, having dominant of precipitation (ET0) during September–December (most of months during January–August), YN always with dominant of precipitation, and wGX with dominant of precipitation (ET0) in February–April and July–December (January, May, and June). Importantly, this study provides a reference for quantitatively evaluating spatiotemporal dryness/wetness variations with climate change, especially for regions with significant drying/wetting. [ABSTRACT FROM AUTHOR]

CO2 concentrations of 21 soil profiles were measured in Zhaotong City, Yunnan Province. The varying characteristics of soil profile CO2 concentrations are distinguishable between carbonate and noncarbonate areas. In noncarbonate areas, soil profile CO2 concentrations increase and show significant positive correlations with soil depth. In carbonate areas, however, deep-soil CO2 concentrations decrease and have no significant correlations with soil depth. Soil organic carbon is negatively correlated with soil CO2 concentrations in noncarbonate areas. In carbonate areas, such relationships are not clear. This means that the special geological process in carbonate areas – carbonate corrosion – absorbs part of the deep-soil-profile CO2. Isotope and soil pH data also support such a process. A mathematical model simulating soil profile CO2 concentration was proposed. In noncarbonate areas, the measured and the simulated values are almost equal, while the measured CO2 concentrations of deep soils are less than the simulated in carbonate areas. Such results also indicate the occurrence of carbonate corrosion and the consuming of deep-soil CO2 in carbonate areas. The decreased CO2 concentration was roughly evaluated based on stratigraphic unit and farming activities. Soil pH and the purity of CaCO3 in carbonate bedrock deeply affect the corrosion. The corrosion in carbonate areas decreases deep-soil CO2 greatly (accounting for 5.2 %–66.3 % with average of 36 %) and naturally affects the soil CO2 released into the atmosphere. Knowledge of this process is important for karst carbon cycles and global climate changes and it may be a part of the "missing carbon sink". [ABSTRACT FROM AUTHOR]

Improved understanding of climate-growth relationships of multiple species is fundamental to understanding and predicting the response of forest growth to future climate change. Forests are mainly composed of conifers in Northwestern Yunnan Plateau, but variations of growth response to climate conditions among the species are not well understood. To detect the growth response of multiple species to climate change, we developed residual chronologies of four major conifers, i.e., George’s fir (Abies georgei Orr), Likiang spruce (Picea likiangensis (Franch.) E.Pritz.), Gaoshan pine (Pinus densata Mast.) and Chinese larch (Larix potaninii Batalin) at the upper distributional limits in Shika Snow Mountain. Using the dendroclimatology method, we analyzed correlations between the residual chronologies and climate variables. The results showed that conifer radial growth was influenced by both temperature and precipitation in Shika Snow Mountain. Previous November temperature, previous July temperature, and current May precipitation were the common climatic factors that had consistent influences on radial growth of the four species. Temperature in the previous post-growing season (September–October) and moisture conditions in the current growing season (June–August) were the common climatic factors that had divergent impacts on the radial growth of the four species. Based on the predictions of climate models and our understanding of the growth response of four species to climate variables, we may understand the growth response to climate change at the species level. It is difficult to predict future forest growth in the study area, since future climate change might cause both increases and decreases for the four species and indirect effects of climate change on forests should be considered. [ABSTRACT FROM AUTHOR]

Ongoing climate changes reportedly affect the potential distribution and carbon sequestration potential (CSP) of forest vegetation. The combined effects of increasing temperature and decreasing precipitation on these features of forest vegetation are poorly understood. In this study, classification and regression tree (CART) models were used to predict the potential distribution and estimate the CSP of forest vegetation in Yunnan Province, Southwest China, under different simulation scenarios. The minimum temperature of the coldest month (TMW) was the main factor limiting the suitable habitat of all forest vegetation types except for warm–temperate coniferous (WTC) forests. When the temperature increased by 1 °C and the precipitation decreased by 20%, the potential distribution area of the 7 forest vegetation types decreased by 12.41% overall. The potential distribution of WTC forests was the least sensitive to temperature increases and precipitation decreases. The CSP of vegetation was higher (1187.69 TgC) under the constant temperature and 10% precipitation decrease scenario than the CSP of vegetation under the 2 °C temperature increase and constant precipitation scenario (647.24 TgC). Specifically, the highest CSP (1337.88 TgC) was observed under the 1 °C temperature increase and 10% precipitation decrease scenario, and the lowest (617.91 TgC) occurred under the constant temperature and 20% precipitation decrease scenario. In summary, the forest vegetation in Yunnan Province has a high CSP under climate change, and the combined effect of increased temperature and decreased precipitation can increase the CSP of forest vegetation in Yunnan Province. This finding is important for improving scientific decision making and policy planning. [ABSTRACT FROM AUTHOR]

Climate warming has been detected and tree growth is sensitive to climate change in Northwestern Yunnan Plateau. Abies georgei is the main component of subalpine forest in the area. In this study, A. georgei ring width chronologies were constructed at four sites ranging from 3300 to 4150 m a.s.l. in Haba Snow Mountain, Southeastern edge of Tibetan Plateau. We analyzed the relationship between four constructed chronologies and climatic variables (monthly minimum temperature, monthly mean temperature, monthly maximum temperature, monthly total precipitation, the Standardized Precipitation-Evapotranspiration Index, and monthly relative humidity) by using response function analysis, moving interval analysis, and redundancy analysis. Overall, the growth of A. georgei was positively affected by common climatic factors (winter moisture conditions, autumn temperature, and previous autumn precipitation). At low and middle-low sites, May moisture condition and previous December precipitation controlled its radial growth with positive correlations. At middle-high and high sites, previous November temperature was the key factor affecting tree growth. The result of moving interval analysis was consistent with correlation analyses, particularly for May moisture at low altitudes. [ABSTRACT FROM AUTHOR]

Inland lake variations are considered sensitive indicators of global climate change. However, human activity is playing as a more and more important role in inland lake area variations. Therefore, it is critical to identify whether anthropogenic activity or natural events is the dominant factor in inland lake surface area change. In this study, we proposed a method that combines the Douglas-Peucker simplification algorithm and the bend simplification algorithm to locate major lake surface area disturbances. These disturbances were used to extract the features that been used to classify disturbances into anthropogenic or natural. We took the nine lakes in Yunnan Province as test sites, a 31-year long (from 1987 to 2017) time series Landsat TM/OLI images and HJ-1A/1B used as data sources, the official records were used as references to aid the feature extraction and disturbance identification accuracy assessment. Results of our method for disturbance location and disturbance identification could be concluded as follows: (1) The method can accurately locate the main lake changing events based on the time series lake surface area curve. The accuracy of this model for segmenting the time series of lake surface area in our study area was 94.73%. (2) Our proposed method achieved an overall accuracy of 87.75%, with an F-score of 85.71 for anthropogenic disturbances and an F-score of 88.89 for natural disturbances. (3) According to our results, lakes in Yunnan Province of China have undergone intensive disturbances. Human-induced disturbances occurred almost twice as much as natural disturbances, indicating intensified disturbances caused by human activities. This inland lake area disturbance identification method is expected to uncover whether a disturbance to inland lake area is human activity-induced or a natural event, and to monitor whether disturbances of lake surface area are intensified for a region. [ABSTRACT FROM AUTHOR]

Climate change could have dire effects on hydropower systems, especially in southwest China, where hydropower dominates the regional power system. This study examines two large cascade hydropower systems in Yunnan province in southwest China for 10 climate change projections made with 5 global climate models (GCMs) and 2 representative concentration pathways (RCPs) under Coupled Model Intercomparison Project Phase 5 (CMIP5). First, a back propagation neural network rain-runoff model is built for each hydropower station to estimate inflows with climate change. Then, a progressive optimality algorithm maximizes hydropower generation for each projection. The results show generation increasing in each GCM projection, but increasing more in GCMs under scenario RCP8.5. However, yearly generation fluctuates more: generation decreases dramatically with potential for electricity shortages in dry years and more electricity as well as spill during wet years. Average annual spill, average annual inflow and average storage have similar trends. The analysis indicates that a planned large dam on the upper Jinsha River would increase seasonal regulation ability, increase hydropower generation, and decrease spill. Increased turbine capacity increases generation slightly and decreases spill for the Lancang River. Results from this study demonstrate effects of climate change on hydropower systems and identify which watersheds might be more vulnerable, along with some actions that could help adapt to climate change. [ABSTRACT FROM AUTHOR]