Excessive climate warming exacerbates nitrogen limitation on microbial metabolism in an alpine meadow of the Tibetan Plateau: Evidence from soil ecoenzymatic stoichiometry.

Soil ecoenzymatic stoichiometry reflects the dynamic equilibrium between microorganism's nutrient requirements and resource availability. However, uncertainties persist regarding the key determinants of nutrient restriction in relation to microbial metabolism under varying degrees of warming. Our long-term and multi-level warming field experiment (control treatment, +0.42 °C, +1.50 °C, +2.55 °C) in a typical alpine meadow unveiled a decline in carbon (C)- and nitrogen (N)-acquired enzymes with escalating warming magnitudes, while phosphorus (P)-acquired enzymes displayed an opposite trend. Employing enzymatic stoichiometry modeling, we assessed the nutrient limitations of microbial metabolic activity and found that C and N co-limited microbial metabolic activities in the alpine meadow. Remarkably, high-level warming (+2.55 °C) exacerbated microbe N limitation, but alleviate C limitations. The structural equation modeling further indicated that alterations in soil extracellular enzyme characteristics (SES) were more effectively elucidated by microbial characteristics (microbial biomass C, N, P, and their ratios) rather than by soil nutrients (total nutrient contents and their ratios). However, the microbial control over SES diminished with higher levels of warming magnitude. Overall, our results provided novel evidence that the factors driving microbe metabolic limitation may vary with the degree of warming in Tibet alpine grasslands. Changes in nutrient demand for microorganism's metabolism in response to warming should be considered to improve nutrient management in adapting to different future warming scenarios.

Decadal soil total carbon loss in northern hinterland of Tibetan Plateau.

As the largest and highest plateau in the world, ecosystems on the Tibetan Plateau (TP) imply fundamental ecological significance to the globe. Among the variety, alpine grassland ecosystem on the TP forms a critical part of the global ecosystem and its soil carbon accounts over nine tenths of ecosystem carbon. Revealing soil carbon dynamics and the underlying driving forces is vital for clarifying ecosystem carbon sequestration capacity on the TP. By selecting northern TP, the core region of the TP, this study investigates spatiotemporal dynamics of soil total carbon and the driving forces based on two phases of soil sampling data from the 2010s and the 2020s. The research findings show that soil total carbon density (STCD) in total-surface (0-30 cm) in the 2010s (8.85 ± 3.08 kg C m-2) significantly decreased to the 2020s (7.15 ± 2.90 kg C m-2), with a decreasing rate (ΔSTCD) of -0.17 ± 0.39 kg C m-2 yr-1. Moreover, in both periods, STCD exhibited a gradual increase with soil depth deepening, while ΔSTCD loss was more apparent in top-surface and mid-surface than in sub-surface. Spatially, ΔSTCD loss in alpine desert grassland was -0.41 ± 0.48 kg C m-2 yr-1, which is significantly higher than that in alpine grassland (-0.11 ± 0.31 kg C m-2 yr-1) or alpine meadow (-0.04 ± 0.28 kg C m-2 yr-1). The STCD in 2010s explained >30 % of variances in ΔSTCD among the set of covariates. Moreover, rising temperature aggravates ΔSTCD loss in alpine desert grassland, while enhanced precipitation alleviates ΔSTCD loss in alpine meadow. This study sheds light on the influences of climate and background carbon on soil total carbon loss, which can be benchmark for predicting carbon dynamics under future climate change scenarios.

Altitude explains insignificant autumn phenological changes across regions with large topography relief in the Tibetan Plateau.

The start of the growing season (SGS) and the end of the growing season (EGS) are widely employed in global change studies to represent the spring and autumn phenology, respectively. Despite the Tibetan Plateau (TP) experiencing significant warming in recent decades, EGS has exhibited only slight changes. Previous studies have concentrated on exploring the environmental regulation of phenology, ignoring the distinctive influences of elevation. Therefore, a more in-depth investigation into the underlying mechanism is warranted. In this study, we investigate the variability of EGS among alpine vegetation regions at different elevations and conduct an analysis based on satellite data. Phenology data of alpine vegetation are extracted from SPOT NDVI dataset spanning from 1999 to 2018, using a piecewise-logistic-maximum-ratio method. We analyze the factors influencing EGS trends at different elevations. The results show that the overall insignificant variation in EGS is mainly attributed to altitude. With the altitude increasing, the annual mean EGS experiences a delay of 0.28 days/100 m below 3500 m, while it advances by 0.2 days/100 m above 3500 m. The opposing shift in elevation below and above 3500 m leads to this counteraction. Elevation emerges as the predominant factor influencing EGS trends, explaining the highest variations (38 %), followed by SGS (22 %) and precipitation (22 %). The elevation effect is most pronounced in areas with substantial topography fluctuations. Moreover, the elevation lapse rate of EGS (ELR_EGS) exhibits an opposite trend with growing season (GS) temperature and a similar trend with GS precipitation between the regions below and above 3500 m, ultimately linking to this counteraction. This study underscores elevation is a critical regulator of vegetation EGS responses to climatic changes over the TP, revealing significant spatial heterogeneities in these responses.

Coarse spatial resolution remote sensing data with AVHRR and MODIS miss the greening area compared with the Landsat data in Chinese drylands.

The warming-wetting climates in Chinese drylands, together with a series of ecological engineering projects, had caused apparent changes to vegetation therein. Regarding the vegetation greening trend, different remote sensing data had yielded distinct findings. It was critical to evaluate vegetation dynamics in Chinese drylands using a series of remote sensing data. By comparing the three most commonly used remote sensing datasets [i.e., MODIS, Advanced Very High Resolution Radiometer (AVHRR), and Landsat], this study comprehensively investigated vegetation dynamics for Chinse drylands. All three remote sensing datasets exhibited evident vegetation greening trends from 2000 to 2020 in Chinese drylands, especially in the Loess Plateau and Northeast China. However, Landsat identified the largest greening areas (89.8%), while AVHRR identified the smallest greening area (58%). The vegetation greening areas identified by Landsat comprise more small patches than those identified by MODIS and AVHRR. The MODIS data exhibited a higher consistency with Landsat than with AVHRR in terms of detecting vegetation greening areas. The three datasets exhibited high consistency in identifying vegetation greening in Northeast China, Loess Plateau, and Xinjiang. The percentage of inconsistent areas among the three datasets was 39.56%. The vegetation greening areas identified by Landsat comprised more small patches. Sensors and the atmospheric effect are the two main reasons responsible for the different outputs from each NDVI product. Ecological engineering projects had a great promotion effect on vegetation greening, which can be detected by the three NDVI datasets in Chinese drylands, thereby combating desertification and reducing dust storms.

Visit-to-visit HbA1c variability, dementia, and hippocampal atrophy among adults without diabetes.

OBJECTIVES: Adults without diabetes are not completely healthy; they are probably heterogeneous with several potential health problems. The management of hemoglobin A1c (HbA1c) is crucial among patients with diabetes; but whether similar management strategy is needed for adults without diabetes is unclear. Thus, this study aimed to investigate the associations of visit-to-visit HbA1c variability with incident dementia and hippocampal volume among middle-aged and older adults without diabetes, providing potential insights into this question. METHODS: We conducted a prospective analysis for incident dementia in 10,792 participants (mean age 58.9 years, 47.8 % men) from the UK Biobank. A subgroup of 3793 participants (mean age 57.8 years, 48.6 % men) was included in the analysis for hippocampal volume. We defined HbA1c variability as the difference in HbA1c divided by the mean HbA1c over the 2 sequential visits ([latter - former]/mean). Dementia was identified using hospital inpatient records with ICD-9 codes. T1-structural brain magnetic resonance imaging was conducted to derive hippocampal volume (normalized for head size). The nonlinear and linear associations were examined using restricted cubic spline (RCS) models, Cox regression models, and multiple linear regression models. RESULTS: During a mean follow-up (since the second round) of 8.4 years, 90 (0.8 %) participants developed dementia. The RCS models suggested no significant nonlinear associations of HbA1c variability with incident dementia and hippocampal volume, respectively (All P > 0.05). Above an optimal cutoff of HbA1c variability at 0.08, high HbA1c variability (increment in HbA1c) was associated with an increased risk of dementia (Hazard Ratio, 1.88; 95 % Confidence Interval, 1.13 to 3.14, P = 0.015), and lower hippocampal volume (coefficient, -96.84 mm3, P = 0.037), respectively, in models with adjustment of covariates including age, sex, etc. Similar results were found for a different cut-off of 0. A series of sensitivity analyses verified the robustness of the findings. CONCLUSIONS: Among middle-aged and older adults without diabetes, increasing visit-to-visit HbA1c variability was associated with an increased dementia risk and lower hippocampal volume. The findings highlight the importance of monitoring and controlling HbA1c fluctuation in apparently healthy adults without diabetes.

Enhanced dominance of soil moisture stress on vegetation growth in Eurasian drylands.

Despite the mounting attention being paid to vegetation growth and their driving forces for water-limited ecosystems, the relative contributions of atmospheric and soil moisture dryness stress on vegetation growth are an ongoing debate. Here we comprehensively compare the impacts of high vapor pressure deficit (VPD) and low soil water content (SWC) on vegetation growth in Eurasian drylands during 1982-2014. The analysis indicates a gradual decoupling between atmospheric dryness and soil dryness over this period, as the former has expanded faster than the latter. Moreover, the VPD-SWC relation and VPD-greenness relation are both non-linear, while the SWC-greenness relation is near-linear. The loosened coupling between VPD and SWC, the non-linear correlations among VPD-SWC-greenness and the expanded area extent in which SWC acts as the dominant stress factor all provide compelling evidence that SWC is a more influential stressor than VPD on vegetation growth in Eurasian drylands. In addition, a set of 11 Earth system models projected a continuously growing constraint of SWC stress on vegetation growth towards 2100. Our results are vital to dryland ecosystems management and drought mitigation in Eurasia.

Climate warming alters the relative importance of plant root and microbial community in regulating the accumulation of soil microbial necromass carbon in a Tibetan alpine meadow.

Climate warming is predicted to considerably affect variations in soil organic carbon (SOC), especially in alpine ecosystems. Microbial necromass carbon (MNC) is an important contributor to stable soil organic carbon pools. However, accumulation and persistence of soil MNC across a gradient of warming are still poorly understood. An 8-year field experiment with four levels of warming was conducted in a Tibetan meadow. We found that low-level (+0-1.5°C) warming mostly enhanced bacterial necromass carbon (BNC), fungal necromass carbon (FNC), and total MNC compared with control treatment across soil layers, while no significant effect was caused between high-level (+1.5-2.5°C) treatments and control treatments. The contributions of both MNC and BNC to soil organic carbon were not significantly affected by warming treatments across depths. Structural equation modeling analysis demonstrated that the effect of plant root traits on MNC persistence strengthened with warming intensity, while the influence of microbial community characteristics waned along strengthened warming. Overall, our study provides novel evidence that the major determinants of MNC production and stabilization may vary with warming magnitude in alpine meadows. This finding is critical for updating our knowledge on soil carbon storage in response to climate warming.

Association of spouse's health status with the onset of depressive symptoms in partner: Evidence from the China Health and Retirement Longitudinal Study.

BACKGROUND: This study aimed to evaluate the associations between the multidimensional health status of one spouse and the onset of depressive symptoms in partner, and whether the associations differed by gender and residence. METHODS: We analyzed data from 2401 females and their husbands (scenario 1), and 2830 males and their wives (scenario 2) who participated in the 2011/2012 and 2015 waves of China Health and Retirement Longitudinal Study. Depressive symptoms were assessed using the 10-item Centre for Epidemiological Studies Depression Scale. Multidimensional health indicators included mobility disability, activities of daily living disability, frailty, global cognition, depressive symptoms, comorbidity, and self-reported health. Principal component analysis was used to construct a composite health indicator reflecting overall health status that was then categorized into three groups (poor, moderate, and excellent). Logistic regression models were performed. RESULTS: We observed strong associations of spouse's health status with the onset of depressive symptoms in partner. For instance, females whose husbands had poor overall health status reported more depressive symptoms than those having husbands with excellent overall health after four years (OR: 1.75; 95 % CI: 1.35, 2.26). These associations were statistically significant in rural females and urban males, but surprisingly disappeared in rural males and urban females. LIMITATIONS: No exact timing of depressive symptoms onset. CONCLUSIONS: In Chinese middle-aged and older adults, spouse's health status is associated with depressive symptoms in partner and the associations vary by gender and residence. The findings underscore the importance of considering partner's health status to manage one spouse's mental health.

Evaluation of urban expansion and the impacts on vegetation in Chinese Loess Plateau: a multi-scale study.

Vegetation degradation caused by rapid urban expansion is a pressing global challenge. Focusing on the Chinese Loess Plateau (CLP), we use satellite observations from 2000 to 2017 to evaluate the spatiotemporal pattern of urban expansion, and its imprint on vegetation across old urban, new urban, urban, non-urban areas as well as the entire urbanization intensity (UI) gradient (from 0 to 100%). We found a massive increase of urban impervious surface area (UISA) in the CLP from 2000 to 2017, and an uneven expansion of UISA at different urban agglomerations and cities. Less green were found in urban and new urban areas, while old urban and non-urban areas generally showed an improved greening pattern. In addition, the annual maximum EVI (EVImax) differences between urban and non-urban areas were - 0.0995 on average from 2000 to 2017. The Guanzhong Plain urban agglomeration (GPUA) witnessed the most significant EVImax differences (- 0.120), and the Ningxia Yanhuang urban agglomeration (NYUA) witnessed the lowest EVImax differences (- 0.012). The EVImax showed significantly decreased trends along the entire spectrum of urbanization gradient for 97.4% (38 of 39) cities and five urban agglomerations. The most significant decrease was found in the GUPA (slope = - 0.0197/10a, p < 0.01), while the smallest drop was found in the NYUA (slope = - 0.011/10a, p < 0.01). This study offered a fundamental support for understanding the vegetation variation along the urban-rural gradient, which may help stakeholders to make better ecological management policies for urban vegetation in ecologically fragile areas.

Climate Controls on the Spatial Variability of Vegetation Greenup Rate across Ecosystems in Northern Hemisphere.

Variations in individual phenological events in response to global change have received considerable attentions. However, the development of phenological stages is relatively neglected, especially based on in situ observation data. In this study, the rate of vegetation greenup (Vgreenup) across the Northern Hemisphere was examined for different plant functional types (PFTs) by using eddy covariance flux data from 40 sites (417 site-years). Then, the controls of climatic variables on the spatial distribution of Vgreenup across PFTs were further investigated. The mean Vgreenup was 0.22 ± 0.11 g C m-2 day-2 across all sites, with the largest and lowest values observed in cropland and evergreen needle-leaf forest, respectively. A strong latitude dependence by Vgreenup was observed in both Europe and North America. The spatial variations of Vgreenup were jointly regulated by the duration of greenup (Dgreenup) and the amplitude of greenup (Agreenup). However, the predominant factor was Dgreenup in Europe, which changed to Agreenup in North America. Spring climatic factors exerted significant influences on the spatial distribution of Vgreenup across PFTs. Specifically, increasing temperature tended to shorten Dgreenup and promote Agreenup simultaneously, resulting in an acceleration of Vgreenup. Dryness had a depression effect on Vgreenup for the whole study area, as exhibited by a lower Vgreenup with increasing vapor pressure deficit or decreasing soil moisture. However, Vgreenup in North America was only significantly and positively correlated with temperature. Without the limitation of other climatic factors, the temperature sensitivity of Vgreenup was higher in North America (0.021 g C m-2 day-2 °C-1) than in Europe (0.015 g C m-2 day-2 °C-1). This study provides new cognitions for Vgreenup dynamics from in situ observations in complement to satellite observations, which can improve our understanding of terrestrial carbon cycles.

Contribution of life course circumstances to the acceleration of phenotypic and functional aging: A retrospective study.

Background: Accelerated aging leads to increasing burdens of chronic diseases in late life, posing a huge challenge to the society. With two well-developed aging measures (i.e., physiological dysregulation [PD] and frailty index [FI]), this study aimed to evaluate the relative contributions of life course circumstances (e.g., childhood and adulthood socioeconomic status) to variance in aging. Methods: We assembled data for 6224 middle-aged and older adults in China from the 2014 life course survey (June to December 2014), the 2015 biomarker collection (July 2015 to January 2016), and the 2015 main survey (July 2015 to January 2016) of the China Health and Retirement Longitudinal Study. Two aging measures (PD and FI) were calculated, with a higher value indicating more accelerated aging. Life course circumstances included childhood (i.e., socioeconomic status, war, health, trauma, relationship, and parents' health) and adulthood circumstances (i.e., socioeconomic status, adversity, and social support), demographics, and behaviours. The Shapley value decomposition, hierarchical clustering, and general linear regression models were performed. Findings: The Shapley value decomposition revealed that all included life course circumstances accounted for about 6·3% and 29·7% of variance in PD and FI, respectively. We identified six subpopulations who shared similar patterns in terms of childhood and adulthood circumstances. The most disadvantaged subpopulation (i.e., subpopulation 6 [more childhood trauma and adulthood adversity]) consistently exhibited accelerated aging indicated by the two aging measures. Relative to the most advantaged subpopulation (i.e., subpopulation 1 [less childhood trauma and adulthood adversity]), PD and FI in the most disadvantaged subpopulation were increased by an average of 0·14 (i.e., coefficient, by one-standard deviation, 95% confidence interval [CI] 0·06-0·21; p < 0·0001) and 0·10 (by one-point, 95% CI 0·09-0·11; p < 0·0001), respectively. Interpretation: Our findings highlight the different contributions of life course circumstances to phenotypic and functional aging. Special attention should be given to promoting health for the disadvantaged subpopulation and narrowing their health gap with advantaged counterparts. Funding: National Natural Science Foundation of China, Milstein Medical Asian American Partnership Foundation, Natural Science Foundation of Zhejiang Province, Fundamental Research Funds for the Central Universities, National Institute on Aging, National Centre for Advancing Translational Sciences, and Yale Alzheimer's Disease Research Centre.

Understory plant removal counteracts tree thinning effect on soil respiration in a temperate forest.

Elucidating the response mechanism of soil respiration (Rs) to silvicultural practices is pivotal to evaluating the effects of management practices on soil carbon cycling in planted forest ecosystems. However, as common management practices, how thinning, understory plant removal, and their interactions affect Rs and its autotrophic and heterotrophic components (Ra and Rh) remains unclear. Therefore, we investigated Rs, Ra and Rh by the trenching method from 2011 to 2015 in a Pinus tabuliformis plantation in northern China, subjecting to four treatments (intact control plots [CK], thinning [T], understory removal [UR], and thinning with understory removal [TUR]). Mean annual Rs was significantly increased by thinning (by 15.3%), whereas decreased by UR (by 17.4%), compared with CK. These variations in Rs were mainly attributed to changes in Ra. The increments of Ra were caused by the enhanced growth of fine root biomass after thinning. However, UR led to lower Ra compared with CK (p < .05), indicating that understory growth is inadequate to compensate for the decreased respiring root biomass induced by understory removal. Rs was unchanged between TUR and the intact control plot due to the opposite effects of thinning and UR on the Ra. Changes in Rh exhibited no significant differences among the treatments, partly because of the stable microbial biomass carbon (MBC) and forest floor mass (litter and fine woody debris). No interaction effect between thinning and understory removal was detected on Rs, Ra, and Rh. The lowest temperature sensitivity (Q10 ) value of Ra was found in CK. This study highlights the necessity of incorporating understory plant effects on soil CO2 efflux in assessing forest management practices on soil carbon cycling.

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Global changes have profound impacts on the structure and function of terrestrial ecosystems. It is a prerequisite to realize the sustainable use of ecosystem to clarify the response and adaptation mechanism of ecosystems to global changes. Network of control experiment is an important way to understand the response and adaptation of the structure and function of ecosystems to global change factors at regional and global scales. The scientific top-level design is conducive to the integration, comparison and analysis of integrative network-data, and then supports the development of universal ecological theory. We comprehensively expounded the theoretical basis, methodological principles and brand-new concepts of experimental network design for future global change control experiment networks design from several aspects, such as research progress, development needs, innovative design and research prospects. Taking Chinese grassland ecosystems as an example, based on the concept of space reference points (mean point of water and heat), the innovative design technology system of China's grassland ecosystem networking experiment was proposed, in order to promote the development of networking research of control experiments at both regional and global scales in the future.

Development and Validation of a New Simple Functional Score in the Older Chinese Population.

Background: Existing aging metrics incorporating cognitive and physical function are often not feasible for application in research and clinical practice. Therefore, this study aimed to develop and validate a new simple functional score based on self-reported cognitive and physical function in the older Chinese population. Methods: The development sample included 3,929 older adults aged 60-95 years from the China Health and Retirement Longitudinal Study (CHARLS). The validation sample included 1,345 older adults aged 60-87 years from the Rugao Longitudinal Aging study (RLAS). Logistic regression models and receiver operating characteristic curves were used to examine the associations of the new functional score with all-cause mortality risk. Results: Six items were selected to construct the new functional score in CHARLS. This functional score was associated with all-cause mortality risk, with an adjusted odds ratio of 1.10 (95% confidence interval = 1.07, 1.13). This functional score presented additional predictive utility beyond age and sex, as demonstrated by the significantly increased C-statistic, integrated discrimination improvement (IDI), and continuous net reclassification improvement (NRI) (all P < 0.001). Furthermore, this functional score was further validated in RLAS, such that adding the new functional score to a model of age and sex improved all-cause mortality risk discrimination (IDI = 0.036, P < 0.001; NRI = 0.485, P < 0.001). To facilitate the quick screening of the older population with deteriorations in cognitive and physical function, we introduced a publicly available online tool designed for this new functional score. Conclusions: A new functional score based on six self-reported items was developed and validated in the older Chinese population, and was demonstrated to be a simple and practical tool to assess functional deterioration, showing good feasibility, and performance.

The stimulatory effect of elevated CO2 on soil respiration is unaffected by N addition.

Global atmospheric CO2 keeps rising and brings about significant effects on ecosystem carbon (C) cycling by altering C processes in soils. Soil C responses to elevated CO2 are highly uncertain, and how elevated CO2 interacts with other factors, such as nitrogen (N) availability, to influence soil C flux comprises an important source of this uncertainty, especially for those under-studied ecosystems. By conducting a manipulated CO2 concentration and N availability experiment on typical alpine grassland (4600 m asl), we combined the five-year in-situ measurement of soil respiration (SR) with an incubation experiment of microbial metabolic efficiency in the lab to explore the response of SR to elevated CO2 and N availability. The results showed that elevated CO2 at ambient N conditions and enriched N equally stimulated SR during the experimental period, whereas N supply had no significant effect. Elevated CO2 enhanced soil dissolved organic C and enzyme activity, while had marginal effects on microbial biomass and C use efficiency (CUE). Strengthened microbial activity dominated SR stimulation under elevated CO2. Enriched N boosted enzyme activity and microbial CUE. N availability played divergent roles in mediating SR. The negliable regulation of N supply on elevated CO2 effects on SR was the offset consequences of the negative impacts of enhanced CUE and the positive contribution of heightened enzyme activity. Our findings suggest that rising CO2 would accelerate soil C cycling of the alpine grassland under various N regimes by stimulating microbial activity instead of lowering microbial metabolic efficiency. Such results are crucial for understanding the role of alpine ecosystems in the global C cycle.

A Machine Learning-Based Aging Measure Among Middle-Aged and Older Chinese Adults: The China Health and Retirement Longitudinal Study.

Objective: Biological age (BA) has been accepted as a more accurate proxy of aging than chronological age (CA). This study aimed to use machine learning (ML) algorithms to estimate BA in the Chinese population. Materials and methods: We used data from 9,771 middle-aged and older Chinese adults (≥45 years) in the 2011/2012 wave of the China Health and Retirement Longitudinal Study and followed until 2018. We used several ML algorithms (e.g., Gradient Boosting Regressor, Random Forest, CatBoost Regressor, and Support Vector Machine) to develop new measures of biological aging (ML-BAs) based on physiological biomarkers. R-squared value and mean absolute error (MAE) were used to determine the optimal performance of these ML-BAs. We used logistic regression models to examine the associations of the best ML-BA and a conventional aging measure-Klemera and Doubal method-BA (KDM-BA) we previously developed-with physical disability and mortality, respectively. Results: The Gradient Boosting Regression model performed the best, resulting in an ML-BA with an R-squared value of 0.270 and an MAE of 6.519. This ML-BA was significantly associated with disability in basic activities of daily living, instrumental activities of daily living, lower extremity mobility, and upper extremity mobility, and mortality, with odds ratios ranging from 1 to 7% (per 1-year increment in ML-BA, all P < 0.001), independent of CA. These associations were generally comparable to that of KDM-BA. Conclusion: This study provides a valid ML-based measure of biological aging for middle-aged and older Chinese adults. These findings support the application of ML in geroscience research and may help facilitate preventive and geroprotector intervention studies.

Climate-Driven Plant Response and Resilience on the Tibetan Plateau in Space and Time: A Review.

Climate change variation on a small scale may alter the underlying processes determining a pattern operating at large scale and vice versa. Plant response to climate change on individual plant levels on a fine scale tends to change population structure, community composition and ecosystem processes and functioning. Therefore, we reviewed the literature on plant response and resilience to climate change in space and time at different scales on the Tibetan Plateau. We report that spatiotemporal variation in temperature and precipitation dynamics drives the vegetation and ecosystem function on the Tibetan Plateau (TP), following the water-energy dynamics hypothesis. Increasing temperature with respect to time increased the net primary productivity (NPP) on most parts of the Tibetan Plateau, but the productivity dynamics on some parts were constrained by 0.3 °C decade-1 rising temperature. Moreover, we report that accelerating studies on plant community assemblage and their contribution to ecosystem functioning may help to identify the community response and resilience to climate extremes. Furthermore, records on species losses help to build the sustainable management plan for the entire Tibetan Plateau. We recommend that incorporating long-term temporal data with multiple factor analyses will be helpful to formulate the appropriate measures for a healthy ecosystem on the Tibetan Plateau.

Spatiotemporal variations of the start of thermal growing season for grassland on the Qinghai-Tibetan Plateau during 1961-2014.

The start of thermal growing season (STGS) is an important indicator for climate change effects on regional plant growth and development. This study comprehensively investigated and compared the spatiotemporal variations in STGS at 0 °C (STGS_0), 5 °C (STGS_5), and 10 °C (STGS_10) thresholds for grassland on the Qinghai-Tibetan Plateau (QTP) during 1961-2014. Although elevation was the predominant influencing factor of the spatial variations of STGSs, the effect of latitude should not be ignored at the low-elevation regions, especially for the STGS with a low-temperature threshold (e.g., STGS_0). With the decrease of temperature thresholds, the effect of elevation became weaker, while the effect of latitude became stronger. Significant advancing trends were observed in all the three STGSs, with greater advancing rate for STGS_0 (0.23 days·year-1) than that of STGS_5 (0.15 days·year-1) and STGS_10 (0.16 days·year-1). More obvious advancing trends were found after 1980, which coincided with more rapid climate warming. The advancing trends weakened after 1998 when climate warming hiatus occurred. Since positive and negative impacts may be simultaneously induced by the advanced STGSs, more observations are still needed to analyze their impacts on the growth and development of alpine grassland on the QTP.

Change in the Green-Up Dates for Quercus mongolica in Northeast China and Its Climate-Driven Mechanism from 1962 to 2012.

The currently available studies on the green-up date were mainly based on ground observations and/or satellite data, and few model simulations integrated with wide coverage satellite data have been reported at large scale over a long time period (i.e., > 30 years). In this study, we combined phenology mechanism model, long-term climate data and synoptic scale remote sensing data to investigate the change in the green-up dates for Quercus mongolica over 33 weather stations in Northeast China and its climate-driven mechanism during 1962-2012. The results indicated that the unified phenology model can be well parameterized with the satellite derived green-up dates. The optimal daily mean temperature for chilling effect was between -27°C and 1°C for Q. mongolica in Northeast China, while the optimal daily mean temperature for forcing effect was above -3°C. The green-up dates for Q. mongolica across Northeast China showed a delayed latitudinal gradient of 2.699 days degree-1, with the earliest date on the Julian day 93 (i.e., 3th April) in the south and the latest date on the Julian day 129 (i.e., 9th May) in the north. The green-up date for Q. mongolica in Northeast China has advanced 6.6 days (1.3 days decade-1) from 1962 to 2012. With the prevailing warming in autumn, winter and spring in Northeast China during the past 51 years, the chilling effect for Q. mongolica has been weakened, while the forcing effect has been enhanced. The advancing trend in the green-up dates for Q. mongolica implied that the enhanced forcing effect to accelerate green-up was stronger than the weakened chilling effect to hold back green-up while the changes of both effects were caused by the warming climate.