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Sea-level rise is one of the most critical challenges facing coastal ecosystems under climate change. Observations of elevated tree mortality in global coastal forests are increasing, but important knowledge gaps persist concerning the mechanism of salinity stress-induced nonhalophytic tree mortality. We monitored progressive mortality and associated gas exchange and hydraulic shifts in Sitka-spruce (Picea sitchensis) trees located within a salinity gradient under an ecosystem-scale change of seawater exposure in Washington State, USA. Percentage of live foliated crown (PLFC) decreased and tree mortality increased with increasing soil salinity during the study period. A strong reduction in gas exchange and xylem hydraulic conductivity (Ks) occurred during tree death, with an increase in the percentage loss of conductivity (PLC) and turgor loss point (πtlp). Hydraulic and osmotic shifts reflected that hydraulic function declined from seawater exposure, and dying trees were unable to support osmotic adjustment. Constrained gas exchange was strongly related to hydraulic damage at both stem and leaf levels. Significant correlations between foliar sodium (Na+) concentration and gas exchange and key hydraulic parameters (Ks, PLC, and πtlp) suggest that cellular injury related to the toxic effects of ion accumulation impacted the physiology of these dying trees. This study provides evidence of toxic effects on the cellular function that manifests in all aspects of plant functioning, leading to unfavourable osmotic and hydraulic conditions., (© American Society of Plant Biologists 2021. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Background: Evacuation and sheltering is both a disaster response measure and a strategy to adapt to climate change, and consequently address the Sustainable Development Goals. Research has found that displacement does cause negative health impacts to evacuees, but few studies have observed how planned sheltering might reduce adverse health impacts. This article identifies the good practice and lessons learned from China's response to severe flooding in Anhui province in 2016., Methods: First, we identified the key phases for disaster sheltering by analyzing related government reports. We then interviewed 21 relevant professionals in order to identify good practice and lessons learned which could lead to better health outcomes (e.g., reduce fatalities, infectious diseases, and mental health problems). Interviewees were selected through a purposive sampling strategy, which identified emergency management professionals and those who had been assigned evacuation, sheltering, or medical tasks. Finally, thematic analysis and the constant comparative method were used to code, identify, and describe the good practice and challenges during key phases., Results: Good practice included: using early warning systems to advise communities of risks and enforce evacuation in the flood zone; preparing and using schools as shelters with open-ended periods of operation; and, providing stable shelter accommodations which offered medical and public health services, clean drinking water and food, sanitation, and toilet hygiene through multiagency cooperation. Challenges included: providing mental health services, evaluating intervention effectiveness, managing volunteers, monitoring long-term health effects, and providing economic support., Conclusions: The unintended negative effects caused by sheltering during extreme weather can be reduced. This requires close cooperation among government entities to establish planned mass shelters with appropriate levels of personal, environmental and healthcare support and to ensure long-term physical and mental health support. Additionally, if disaster mitigation strategies are integrated with climate adaptation plans, we can design more health-oriented and sustainable cities., (Copyright © 2019. Published by Elsevier B.V.)

Key message: The responses of tree leaf δ13C to climatic and geographic factors were different among major climate zones in China, suggesting that the environmental influences on tree ecophysiology are different among climates. Leaf stable carbon isotope composition (δ13C) integrates information about environmental effects on plant carbon and water balance. However, extensive inconsistent findings have been reported regarding the variability of leaf δ13C along environmental gradients, impeding the interpretations of plant physiological responses to environmental changes using δ13C values. In this study, data from 505 tree leaf δ13C measurements and climatic and geographic information at 186 sites across China were collected from peer-reviewed articles. The dataset was grouped according to the Köppen–Geiger climate classification for investigating the variations in tree leaf δ13C with climatic and geographic factors among different climate zones. Multiple regression analyses were conducted using this dataset to provide a predictive model for tree leaf δ13C variability in China. The results showed that the tree leaf δ13C was − 28.05‰ on average and was highest in the polar climate (− 26.82‰), lowest in the warm temperate climate (− 29.66‰), and almost the same in the temperate arid (− 27.60‰) and cold temperate (− 27.69‰) climate zones. We found that the magnitude of the leaf δ13C values of certain climates was partly determined by the functional type of local tree species. Moreover, the relationship between tree leaf δ13C and mean annual precipitation (MAP) was found to be significantly positive only for the temperate arid climate zone, while significant negative correlations were found for the other climate zones. Tree leaf δ13C was significantly negatively related to mean annual temperature (MAT) in the warm temperate and polar climate zones, and it was positively related to altitude in the warm temperate and cold temperate climate zones. These results suggest that the widely observed inconsistent responses of leaf δ13C to environmental factors, as well as the inconsistent δ13C values of a specific tree functional type, can be attributed to the climate conditions in which the tree inhabits. Finally, a simple regression model incorporating MAT, MAP, and altitude was proposed, which explained 45% of the variation in tree leaf δ13C. These findings could be useful in evaluating potential changes in tree physiological traits under the changing climate in China. [ABSTRACT FROM AUTHOR]

Snowpack in winter is very sensitive to climate change, and may in turn induce complex effects on terrestrial biochemistry processes. Here we synthesized the results from 49 papers based on snow depth manipulation experiments and conducted a meta-analysis to evaluate the general response of 9 variables related to terrestrial carbon pools and dynamics to the altered snowpack depth. Our meta-analysis results indicated that increasing snowpack depth significantly increased litter biomass (+18.4%), MBC (+18.2%) and CO 2 emission (+15.5%), and significantly decreased litter C: N ratio (−5.8%) and total soil carbon (−28.5%) under snow addition manipulation, but did not significantly affect fine root biomass, MBC: MBN ratio and soil dissolved organic carbon (DOC). However, increasing snowpack depth only significantly altered litter C: N ratio (+11.2%) under snow removal manipulation. The different responses between snow addition and removal were possibly related to the higher soil temperature and moisture under snow addition than under snow removal manipulation experiments. In addition, the effect of increasing snowpack depth on CH 4 flux was not significant, presumably because all these studies were compiled from snow-removal experiments. These results are useful for a better understanding of the effects of altered snowpack on terrestrial carbon cycling under climate change scenarios. [ABSTRACT FROM AUTHOR]

Snowpack in winter is very sensitive to climate change, and may in turn induce complex effects on nutrient cycling in terrestrial ecosystems. This study synthesized data from 41 publications based on snow depth manipulation experiments and conducted a meta-analysis to assess the general responses of 12 variables related to terrestrial nitrogen (N) pools and dynamics to altered snowpack depth. Our results indicated that increasing snow depth significantly increased foliar N (+4.5%) and microbial N (MBN, +35.9%), but significantly decreased soil N 2 O efflux (−34.1%). However, altered snow depth did not significantly affect soil dissolved organic N (DON), total inorganic N, nitrate and N leaching. The decreased net nitrification (−24.8%) by deeper snowpack suggested that less soil N transformed to nitrate, which might contribute to reduce soil N losses. Since increasing snowpack depth promoted MBN, the unchanged net N mineralization and soil ammonium content were probably due to limitation of the soil N availability and other soil abiotic factors rather than soil microbes. In addition, long-term and snowfence or shelter methods generated the most significant effects on N dynamics for snow addition or removal experiments, respectively. Our results provide a comprehensive understanding of how N cycling responses to altered snow cover under climate change scenarios. [ABSTRACT FROM AUTHOR]

Carbon dioxide (CO 2 ) is the most important anthropogenic greenhouse gas contributing to global climate change. Understanding the temporal and spatial variations of CO 2 concentration over terrestrial ecosystems provides additional insight into global atmospheric variability of CO 2 concentration. Using 355 site-years of CO 2 concentration observations at 104 eddy-covariance flux tower sites in Northern Hemisphere, we presented a comprehensive analysis of evolution and variation of atmospheric CO 2 concentration over terrestrial ecosystem (ACTE) for the period of 1997–2006. Our results showed that ACTE exhibited a strong seasonal variations, with an average seaonsal amplitude (peak-trough difference) of 14.8 ppm, which was approximately threefold that global mean CO 2 observed in Mauna Loa in the United States (MLO). The seasonal variation of CO 2 were mostly dominant by terrestrial carbon fluxes, i.e., net ecosystem procution (NEP) and gross primary produciton (GPP), with correlation coefficient( r ) were −0.55 and −0.60 for NEP and GPP, respectively. However, the influence of carbon fluxes on CO 2 were not significant at interannual scale, which implyed that the inter-annual changing trends of atmospheric CO 2 in Northern Hemisphere were likely to depend more on anthropogenic CO 2 emissions sources than on ecosystem change. It was estimated, by fitting a harmonic model to monthly-mean ACTE, that both annual mean and seasonal amplitude of ACTE increased over the 10-year period at rates of 2.04 and 0.60 ppm yr −1 , respectively. The uptrend of annual ACTE could be attributed to the dramatic global increase of CO 2 emissions during the study period, whereas the increasing amplitude could be related to the increases in Northern Hemisphere biospheric activity. This study also found that the annual CO 2 concentration showed large variation among ecosystems, with the high value appeared in deciduous broadleaf forest, evergreen broadleaf forest and cropland. We attribute these discrepancies to both differential local anthropogenic impacts and carbon sequestration abilities across ecosystem types. [ABSTRACT FROM AUTHOR]

Hydrological processes change from the impacts of climate variability and human activities. Runoff in the upper reaches of the Hun-Taizi River basin, which is mainly covered by forests in northeast China, decreased from 1960 to 2006. The data used in this study were based on runoff records from six hydrological stations in the upper reaches of the Hun-Taizi River basin. Nonparametric Mann-Kendall statistic was used to identify change trends and abrupt change points and consequently analyze the change characteristics in hydrological processes. The abrupt change in the annual runoff in most subcatchments appeared after 1975. Finally, the effects of climate change and land cover change on water resources were identified using regression analysis and a hydrology model. Results of the regression analysis suggest that the correlation coefficients between precipitation and runoff prior to the abrupt change were higher compared with those after the abrupt change. Moreover, using hydrology model analysis, the water yield was found to increase because of the decrease in forest land. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

ABSTRACT The long-term tower-based eddy covariance measurements of CO2/H2O fluxes are carried out in a temperate mature forest in Northeast China. The current study investigates the atmospheric (net radiation and vapour pressure deficit) and vegetation (surface conductance) controls of the evapotranspiration (ET) within the two observational years with different water conditions. The results show that the ET during the short dry season of 2004 was higher than that during the wet season of 2005. The ET is mainly driven by the meteorological factor of vapour pressure deficit. The mixed forest did not show clear signs of ET suppression during the summer drought because of its slightly reduced surface conductance, whereas its water demands from the atmosphere significantly increased. Thus, the annual ET slightly varied (416·2 to 462·1 mm) despite the large interannual variation in precipitation (488·7 to 761·6 mm). The 0-100 cm deep soil water storages are important sources of water supply for ET during dry seasons. The findings of this study suggest that the possible reduction in precipitation under future climate change scenarios with invariable or even enhanced ET will decrease the replenishment of groundwater and outflow and, consequently, the downstream water supply. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Abstract: Understanding the temporal evolution of CO2 over specific ecosystems can provide additional insight into atmospheric CO2 variability. From 2003 to 2010, CO2 ambient concentrations in an old-growth temperate forest were measured continuously by using an infrared analyzer. The results show that daily cycle and seasonal variation of CO2 were mostly dominated by vegetation activity, whereas the weak turbulent mixing at night contributed frequently to CO2 build-up below the canopy. As a result, CO2 concentrations changed considerably during daytime and nighttime in the forest stand. The monthly means exhibited a seasonal variation characterized by a primary peak in December and a minimum during July to August, with an average seasonal amplitude (the difference of minimum and maximum monthly means) of 60.5 ppmv. By fitting a harmonic model to the monthly means, linear increase trends of 1.7 ppmv yr−1 in the annual mean CO2 concentrations and 0.58 ppmv yr−1 in the amplitude of the seasonal cycle were estimated. The upward trend of annual mean CO2 concentration may be attributed to the dramatic global increase in CO2 emissions during the study period. This study also found that the stratification of CO2 concentrations below the canopy during nighttime was easily disrupted after sunrise, which suggests that forest floor plants are not, as previous assumed, exposed to significantly greater CO2 concentrations than the normal atmospheric concentrations. [Copyright &y& Elsevier]

Carbon (C) isotope discrimination during photosynthetic CO2 assimilation has been extensively studied, but the whole process of fractionation from leaf to soil has been less well investigated. In the present study, we investigated the δ13C signature along the C transfer pathway from air to soil in a coniferous and broad-leaved mixed forest in northeast China and examined the relationship between δ13C of respiratory fluxes (leaf, trunk, soil, and the entire ecosystem) and environmental factors over a full growing season. This study found that the δ13C signal of CO2 from canopy air was strongly imprinted in the organic and respiratory pools throughout C transfer due to the effects of discrimination and isotopic mixing on C assimilation, allocation, and respiration processes. A significant difference in isotopic patterns was found between conifer and broadleaf species in terms of seasonal variations in leaf organic matter. This study also found that δ13C in trunk respiration, compared with that in leaf and soil respiration, was more sensitive to seasonal variations of environmental factors, especially soil temperature and soil moisture. Variation in the δ13C of ecosystem respiration was correlated with air temperature with no time lag and correlated with soil temperature and vapor pressure deficit with a lag time of 10 days, but this correlation was relatively weak, indicating a delayed linkage between above- and belowground processes. The isotopic linkage might be confounded by variations in atmospheric aerodynamic and soil diffusion conditions. These results will help with understanding species differences in isotopic patterns and promoting the incorporation of more influencing factors related to isotopic variation into process-based ecosystem models. [ABSTRACT FROM AUTHOR]

Temperature response quotient ( Q 10 ) is a critical parameter for evaluating global additional carbon (C) release with climate change. However, its value is usually derived from time span or instantaneous rate or cumulative amount of C flux, giving a very one-sided account of thermal sensitivity of C cycling. Through a 117-day laboratory incubation study, we estimated Q 10 values simultaneously with the labile (a 0 ) and recalcitrant C proportions and their rate constants, and then tested for any variances of these kinetic properties in different vegetation stands, soil horizons, aeration statuses, and thermal settings (i.e., diurnally-varying, constant low and constant high temperatures). A regularly varying temperature regime increased the exploitation of labile C resources (i.e., high a 0 ) and required longer time spans (i.e., low rate constants). The constant high temperature induced the exhaustive depletion of the labile C pool and motivated a very rapid and short-term C mineralization process. The constant low temperature treatment was characterized by the lowest a 0 but by medium rate constants because low temperature slowed the C mineralization processes but retained high level of the original C processing diversity. Therefore, a 0 and the rate constants showed discrepancies in their temperature sensitivities as revealed by pairwise comparisons of temperature regimes. Such discrepancies were also supported by pairwise comparisons of aeration statuses, forest stands and soil horizons. The Q 10 bias between C mineralization a 0 and rate constants in this laboratory experiment is attributed to the inherently distinct properties of these two parameters, as a 0 and its Q 10 are closely correlated with the sizes of the easily available C pool, while rate constants and their Q 10 variances explain the temporal scale of the same C mineralization process. Our findings suggest a combined application of a 0 and rate constants for exploring the temperature sensitivity of C mineralization in future studies. [ABSTRACT FROM AUTHOR]

• Global forest ET increased significantly (11.30 ± 4.23 mm year−1 decade-1). • Forest ET trend was mainly dominated by climate forcing change (+) and increased CO 2 (−). • LAI is not the main driving factor for the change of ET in forest area. • The driving factors played a dominant role (53.09%) in forest ET increase. • The forest area played a secondary role (46.91%) in forest ET increase. Forest evapotranspiration (ET) is expected to increase under global warming. However, the relative contribution of the major drivers (such as leaf area index (LAI), climate forcing, atmospheric CO 2 , etc.) to long-term ET trends in forest is unclear. In addition, the effects of ET changes induced by driving factors and ET changes induced by forest area changes on total forest ET are still remain to be determined. We aim to explore long-term ET trends in global forest and assess the relative contributions of their influencing factors by a remote sensing-based carbon–water coupling model, the second edition of the Penman-Monteith-Leuning (PML-V2). The results showed that: 1) the ET of global forest increased slightly (11.30 ± 4.23 mm year−1 decade-1, p < 0.05), with the greatest increase observed in evergreen broadleaf forest (20.89 ± 6.96 mm year−1 decade-1, p < 0.01). 2) Simulation experiment indicated that upward global forest ET trend was mainly dominated by climate forcing change (56.71 %), increased LAI (5.07 %), albedo and emissivity change (−0.77 %) and increased CO 2 (−37.45 %). Only mixed forest exhibited a decrease in ET trend, which was caused by CO 2 concentration counteracted the increase trend of ET induced by climate forcing change and LAI increase, resulting in a decrease trend of ET. Different from broadleaf forests and MF, the increase of LAI in needleleaf forests caused a negative contribution of ET. 3) In the overall increasing trend of global forest ET, the driving factors played a dominant role (53.09 %) and the forest area played a secondary role (46.91 %). Our findings highlight the divergent responses of various forest types under climate change, which is beneficial to forest management and sustainable development. [ABSTRACT FROM AUTHOR]

• The correlation between tree-ring δ13C and ecosystem GPP was assessed in a forest. • Early-wood and late-wood δ13C were analyzed separately. • Tree-ring δ13C positively correlated with forest GPP of the current-year. • Early- and late-wood δ13C traced GPP seasonally and annually. Tree-ring carbon (C) isotope composition (δ13C) varies depending on photosynthetic capacity and stomatal conductance, and it is therefore intrinsically associated with vegetation productivity. Still, very little is known about the relationship between tree-ring δ13C values and forest gross primary productivity (GPP). Here, we investigated relationships between tree-ring δ13C, tree-ring width index (RWI) and ecosystem-level GPP in a Korean pine (Pinus koraiensis)-dominated old-growth temperate forest in northeastern China. Specifically, we generated chronologies of RWI and δ13C from early-wood (δ13C EW) and late-wood (δ13C LW) of Korean pines, and we built a 17-year continuous ecosystem-level GPP series using eddy covariance measurements, in which a GPP model was used for gap filling. RWI showed vague relationships with tree-ring δ13C and whole-forest GPP, and it was insensitive to interannual variations in climate at the study site. By contrast, both δ13C EW and δ13C LW showed significant relationships with climate variables and GPP. This suggests that isotopic signals of photosynthetic C uptake were imprinted on the formation of tree rings and that tree-ring δ13C of Korean pine is a better proxy for forest GPP than RWI. In addition, tree-ring δ13C of Korean pines was positively correlated with GPP, with an especially close relationship between δ13C EW and GPP of the current year. This implies that photosynthetic activity, rather than stomatal conductance, was the main driver of tree-ring δ13C signals of Korean pine and it was mainly influenced by the climate conditions of the current year, probably because of a limited use of previously fixed C during early-wood formation. Our findings demonstrate the great potential of tree-ring δ13C for reconstructing GPP timeseries at the centennial scale for forest ecosystems, and they could help to constrain parameters in terrestrial C cycle models to improve predictions of C fluxes. [ABSTRACT FROM AUTHOR]

Summary: Hydrological processes in river systems have been changing under the impacts of both climate variability and human activities. The non-parametric Mann–Kendall statistic was used to identify change trends and points in the annual streamflow in the Hun–Tai River basin in northeast China. The identifications were based on streamflow records from six hydrological stations during 1961–2006, and the purpose was to analyze the change characteristics of the hydrological processes. The results indicated that all hydrological stations presented downward trends in annual streamflows. Abrupt changes in the annual streamflow occurred around 1978 in the Hun River basin, and around 1998 in the Taizi River basin. The impact of climate variability on the mean annual streamflow was also analyzed based on the relationships among streamflow, precipitation, and potential evapotranspiration. Precipitation and meteorological data from 22 rainfall stations and 10 weather stations within the basin were employed in the analysis. Daily potential evapotranspiration was calculated using the Penman–Monteith equation. Climate variability was estimated to account for 43% of the reduction in the annual streamflow, and human activities accounted for about 57%. [ABSTRACT FROM AUTHOR]

Abstract: The methane exchange in an oligotrophic mire complex was measured on the ecosystem and microform scale with the eddy covariance (EC) and the closed chamber technique, respectively. Information about the distribution of three distinct microform types in the area of interest and in each 30min EC flux source area was derived from a high-resolution (1m2) landcover map in combination with an analytical source weight model (). The mean weighted coverage of flark, lawn and hummock microforms in the EC source area (0.3%:57%:43%) closely mirrors the overall distribution in the area of interest (0.5%:50.1%:49.4%), despite great differences in microform coverage between individual 30min EC source areas. The measured ecosystem flux was fitted to the sum of three microform flux models based on environmental variables and weighted by their fractional coverage in the EC source area. This method resulted in a better representation of the ecosystem flux compared to an approach based on only one flux model for the whole ecosystem (R 2 =0.87, RMSE=0.44 vs. R 2 =0.74, RMSE=0.61, n =5181) and thus constitutes a successful down-scaling of measured ecosystem scale flux to the microform scale. A comparison of down-scaled and measured microform fluxes reveals a good agreement for lawn microforms and systematic differences for flark and hummock microforms. Reasons for the differences are thought to be the limited resolution of the landcover classification and the systematic underestimation of hummock fluxes by the closed chamber technique. As a result, hummock fluxes derived by down-scaling of EC fluxes are considered to be more dependable than closed chamber fluxes. The seasonal ecosystem methane budget from gap-filled EC measurements was 9.4±0.2gCH4 m−2; the budget derived from up-scaled microform measurements was 8.0±0.8gCH4 m−2. The lower value of the latter budget is attributed to the underestimation of flark and hummock fluxes by closed chamber measurements and to the microform gap-filling procedure. Generally, estimates from up-scaled microform measurements are found to be less certain than estimates from EC measurements. [Copyright &y& Elsevier]