Segmenting Chinese outbound tourists by perceived constraints

This study examines travel constraints experienced by Chinese outbound tourists. Four constraint factors are identified from visitor data collected in 2006: structural constraint, cultural constraint, information constraint, and knowledge constraint. Information constraint is identified as a factor unique to outbound tourists from China. Among the four constraint factors, structural constraint is the most dominant. Four clusters of visitors are therefore identified: culturally constrained, structurally constrained, absence of sufficient information, and knowledge constrained. The four clusters are distinct in terms of their destination loyalty. The characteristics of each segment are given, and the practical implications of the findings are discussed

Riverine Carbon Cycling Over The Past Century in the Mid‐Atlantic Region of the United States

The lateral transport and degassing of carbon in riverine ecosystems is difficult to quantify on large spatial and long temporal scales due to the relatively poor representation of carbon processes in many models. Here, we coupled a scale‐adaptive hydrological model with the Dynamic Land Ecosystem Model to simulate key riverine carbon processes across the Chesapeake and Delaware Bay Watersheds from 1900 to 2015. Our results suggest that throughout this time period riverine CO2 degassing and lateral dissolved inorganic carbon fluxes to the coastal ocean contribute nearly equally to the total riverine carbon outputs (mean ± standard deviation: 886 ± 177 Gg C∙yr−1 and 883 ± 268 Gg C∙yr−1, respectively). Following in order of decreasing importance are the lateral dissolved organic carbon flux to the coastal ocean (293 ± 81 Gg C∙yr−1), carbon burial (118 ± 32 Gg C∙yr−1), and lateral particulate organic carbon flux (105 ± 35 Gg C∙yr−1). In the early 2000s, carbon export to the coastal ocean from both the Chesapeake and Delaware Bay watersheds was only 15%–20% higher than it was in the early 1900s (decade), but it showed a twofold increase in standard deviation. Climate variability (changes in temperature and precipitation) explains most (225 Gg C∙yr−1) of the increase since 1900, followed by changes in atmospheric CO2 (82 Gg C∙yr−1), atmospheric nitrogen deposition (44 Gg C∙yr−1), and applications of nitrogen fertilizer and manure (27 Gg C∙yr−1); in contrast, land conversion has resulted in a 188 Gg C∙yr−1 decrease in carbon export

Hydroclimatic extremes contribute to asymmetric trends in ecosystem productivity loss

Gross primary production is the basis of global carbon uptake. Gross primary production losses are often related to hydroclimatic extremes such as droughts and heatwaves, but the trend of such losses driven by hydroclimatic extremes remains unclear. Using observationally-constrained and process-based model data from 1982-2016, we show that drought-heat events, drought-cold events, droughts and heatwaves are the dominant drivers of gross primary production loss. Losses associated with these drivers increase in northern midlatitude ecosystem but decrease in pantropical ecosystems, thereby contributing to around 70% of the variability in total gross primary production losses. These asymmetric trends are caused by an increase in the magnitude of gross primary production losses in northern midlatitudes and by a decrease in the frequency of gross primary production loss events in pantropical ecosystems. Our results suggest that the pantropics may have become less vulnerable to hydroclimatic variability over recent decades whereas gross primary production losses and hydroclimatic extremes in northern midlatitudes have become more closely entangled

The paleoclimatic footprint in the soil carbon stock of the Tibetan permafrost region

Data and code availability The authors declare that the majority of the data supporting the findings of this study are available through the links given in the paper. The unpublished data are available from the corresponding author upon request. The new estimate of Tibetan soil carbon stock and R code are available in a persistent repository (https://figshare.com/s/4374f28d880f366eff6d). Acknowledgements This study was supported by the Strategic Priority Research Program (A) of the Chinese Academy of Sciences (XDA20050101), the National Natural Science Foundation of China (41871104), Key Research and Development Programs for Global Change and Adaptation (2017YFA0603604), International Partnership Program of the Chinese Academy of Sciences (131C11KYSB20160061) and the Thousand Youth Talents Plan project in China. Jinzhi Ding acknowledges the General (2017M620922) and the Special Grade (2018T110144) of the Financial Grant from the China Postdoctoral Science Foundation.Peer reviewedPublisher PD

Assessing Model Predictions of Carbon Dynamics in Global Drylands

Drylands cover ca. 40% of the land surface and are hypothesised to play a major role in the global carbon cycle, controlling both long-term trends and interannual variation. These insights originate from land surface models (LSMs) that have not been extensively calibrated and evaluated for water-limited ecosystems. We need to learn more about dryland carbon dynamics, particularly as the transitory response and rapid turnover rates of semi-arid systems may limit their function as a carbon sink over multi-decadal scales. We quantified aboveground biomass carbon (AGC; inferred from SMOS L-band vegetation optical depth) and gross primary productivity (GPP; from PML-v2 inferred from MODIS observations) and tested their spatial and temporal correspondence with estimates from the TRENDY ensemble of LSMs. We found strong correspondence in GPP between LSMs and PML-v2 both in spatial patterns (Pearson’s r = 0.9 for TRENDY-mean) and in inter-annual variability, but not in trends. Conversely, for AGC we found lesser correspondence in space (Pearson’s r = 0.75 for TRENDY-mean, strong biases for individual models) and in the magnitude of inter-annual variability compared to satellite retrievals. These disagreements likely arise from limited representation of ecosystem responses to plant water availability, fire, and photodegradation that drive dryland carbon dynamics. We assessed inter-model agreement and drivers of long-term change in carbon stocks over centennial timescales. This analysis suggested that the simulated trend of increasing carbon stocks in drylands is in soils and primarily driven by increased productivity due to CO$_2$ enrichment. However, there is limited empirical evidence of this 50-year sink in dryland soils. Our findings highlight important uncertainties in simulations of dryland ecosystems by current LSMs, suggesting a need for continued model refinements and for greater caution when interpreting LSM estimates with regards to current and future carbon dynamics in drylands and by extension the global carbon cycle

Forty years of reform and opening up:China’s progress toward a sustainable path

After 40 years of reform and “opening up,” China has made remarkable economic progress. Such economic prosperity, however, has been coupled with environmental degradation. We analyze diverse long-term data to determine whether China is experiencing a decoupling of economic growth and environmental impacts, and where China stands with respect to the Sustainable Development Goals (SDGs) in terms of reducing regional division, urban-rural gap, social inequality, and land-based impacts on oceans. The results highlight that China’s desire to achieve “ecological civilization” has resulted in a decoupling trend for major pollutants since 2015, while strong coupling remains with CO2 emissions. Progress has been made in health care provision, poverty reduction, and gender equity in education, while income disparity continues between regions and with rural-urban populations. There is a considerable way to go toward achieving delivery of the SDGs; however, China’s progress toward economic prosperity and concomitant sustainability provides important insights for other countries

Unraveling the pathogenic potential of the Pentatrichomonas hominis PHGD strain: impact on IPEC-J2 cell growth, adhesion, and gene expression

Pentatrichomonas hominis, a flagellated parasitic protozoan, predominantly infects the mammalian digestive tract, often causing symptoms such as abdominal pain and diarrhea. However, studies investigating its pathogenicity are limited, and the mechanisms underlying P. hominis-induced diarrhea remain unclear. Establishing an in vitro cell model for P. hominis infection is imperative. This study investigated the interaction between P. hominis and IPEC-J2 cells and its impact on parasite growth, adhesion, morphology, and cell viability. Co-cultivation of P. hominis with IPEC-J2 cells resulted in exponential growth of the parasite, with peak densities reaching approximately 4.8 × 105 cells/mL and 1.2 × 106 cells/mL at 48 h for initial inoculation concentrations of 104 cells/mL and 105 cells/mL, respectively. The adhesion rate of P. hominis to IPEC-J2 cells reached a maximum of 93.82% and 86.57% at 24 h for initial inoculation concentrations of 104 cells/mL and 105 cells/mL, respectively. Morphological changes in IPEC-J2 cells co-cultivated with P. hominis were observed, manifesting as elongated and irregular shapes. The viability of IPEC-J2 cells exhibited a decreasing trend with increasing P. hominis concentration and co-cultivation time. Additionally, the mRNA expression levels of IL-6, IL-8, and TNF-α were upregulated, whereas those of CAT and CuZn-SOD were downregulated. These findings provide quantitative evidence that P. hominis can promote its growth by adhering to IPEC-J2 cells, inducing morphological changes, reducing cell viability, and triggering inflammatory responses. Further in vivo studies are warranted to confirm these results and enhance our understanding of P. hominis infection

Net exchanges of CO2, CH4, and N2O between China's terrestrial ecosystems and the atmosphere and their contributions to global climate warming

Author Posting. © American Geophysical Union, 2011. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research 116 (2011): G02011, doi:10.1029/2010JG001393.China's terrestrial ecosystems have been recognized as an atmospheric CO2 sink; however, it is uncertain whether this sink can alleviate global warming given the fluxes of CH4 and N2O. In this study, we used a process-based ecosystem model driven by multiple environmental factors to examine the net warming potential resulting from net exchanges of CO2, CH4, and N2O between China's terrestrial ecosystems and the atmosphere during 1961–2005. In the past 45 years, China's terrestrial ecosystems were found to sequestrate CO2 at a rate of 179.3 Tg C yr−1 with a 95% confidence range of (62.0 Tg C yr−1, 264.9 Tg C yr−1) while emitting CH4 and N2O at rates of 8.3 Tg C yr−1 with a 95% confidence range of (3.3 Tg C yr−1, 12.4 Tg C yr−1) and 0.6 Tg N yr−1 with a 95% confidence range of (0.2 Tg N yr−1, 1.1 Tg N yr−1), respectively. When translated into global warming potential, it is highly possible that China's terrestrial ecosystems mitigated global climate warming at a rate of 96.9 Tg CO2eq yr−1 (1 Tg = 1012 g), substantially varying from a source of 766.8 Tg CO2eq yr−1 in 1997 to a sink of 705.2 Tg CO2eq yr−1 in 2002. The southeast and northeast of China slightly contributed to global climate warming; while the northwest, north, and southwest of China imposed cooling effects on the climate system. Paddy land, followed by natural wetland and dry cropland, was the largest contributor to national warming potential; forest, followed by woodland and grassland, played the most significant role in alleviating climate warming. Our simulated results indicate that CH4 and N2O emissions offset approximately 84.8% of terrestrial CO2 sink in China during 1961–2005. This study suggests that the relieving effects of China's terrestrial ecosystems on climate warming through sequestering CO2 might be gradually offset by increasing N2O emission, in combination with CH4 emission.This study has been supported by NASA LCLUC Program (NNX08AL73G_S01) , NASA IDS Program (NNG04GM39C), and China’s Ministry of Science and Technology (MOST) 973 Program (2002CB412500)