Global patterns and controls of soil organic carbon dynamics as simulated by multiple terrestrial biosphere models: Current status and future directions

Soil is the largest organic carbon (C) pool of terrestrial ecosystems, and C loss from soil accounts for a large proportion of land-atmosphere C exchange. Therefore, a small change in soil organic C (SOC) can affect atmospheric carbon dioxide (CO2) concentration and climate change. In the past decades, a wide variety of studies have been conducted to quantify global SOC stocks and soil C exchange with the atmosphere through site measurements, inventories, and empirical/process-based modeling. However, these estimates are highly uncertain, and identifying major driving forces controlling soil C dynamics remains a key research challenge. This study has compiled century-long (1901-2010) estimates of SOC storage and heterotrophic respiration (Rh) from 10 terrestrial biosphere models (TBMs) in the Multi-scale Synthesis and Terrestrial Model Intercomparison Project and two observation-based data sets. The 10 TBM ensemble shows that global SOC estimate ranges from 425 to 2111 Pg C (1 Pg = 1015 g) with a median value of 1158 Pg C in 2010. The models estimate a broad range of Rh from 35 to 69 Pg C yr-1 with a median value of 51 Pg C yr-1 during 2001-2010. The largest uncertainty in SOC stocks exists in the 40-65°N latitude whereas the largest cross-model divergence in Rh are in the tropics. The modeled SOC change during 1901-2010 ranges from -70 Pg C to 86 Pg C, but in some models the SOC change has a different sign from the change of total C stock, implying very different contribution of vegetation and soil pools in determining the terrestrial C budget among models. The model ensemble-estimated mean residence time of SOC shows a reduction of 3.4 years over the past century, which accelerate C cycling through the land biosphere. All the models agreed that climate and land use changes decreased SOC stocks, while elevated atmospheric CO2 and nitrogen deposition over intact ecosystems increased SOC stocks-even though the responses varied significantly among models. Model representations of temperature and moisture sensitivity, nutrient limitation, and land use partially explain the divergent estimates of global SOC stocks and soil C fluxes in this study. In addition, a major source of systematic error in model estimations relates to nonmodeled SOC storage in wetlands and peatlands, as well as to old C storage in deep soil layers.

Detection and attribution of vegetation greening trend in China over the last 30 years

The reliable detection and attribution of changes in vegetation growth is a prerequisite for the development of strategies for the sustainable management of ecosystems. This is an extraordinary challenge. To our knowledge, this study is the first to comprehensively detect and attribute a greening trend in China over the last three decades. We use three different satellite-derived Leaf Area Index (LAI) datasets for detection as well as five different process-based ecosystem models for attribution. Rising atmospheric CO2 concentration and nitrogen deposition are identified as the most likely causes of the greening trend in China, explaining 85% and 41% of the average growing-season LAI trend (LAIGS) estimated by satellite datasets (average trend of 0.0070 yr(-1), ranging from 0.0035 yr(-1) to 0.0127 yr(-1)), respectively. The contribution of nitrogen deposition is more clearly seen in southern China than in the north of the country. Models disagree about the contribution of climate change alone to the trend in LAIGS at the country scale (one model shows a significant increasing trend, whereas two others show significant decreasing trends). However, the models generally agree on the negative impacts of climate change in north China and Inner Mongolia and the positive impact in the Qinghai-Xizang plateau. Provincial forest area change tends to be significantly correlated with the trend of LAIGS (P < 0.05), and marginally significantly (P = 0.07) correlated with the residual of LAIGS trend, calculated as the trend observed by satellite minus that estimated by models through considering the effects of climate change, rising CO2 concentration and nitrogen deposition, across different provinces. This result highlights the important role of China's afforestation program in explaining the spatial patterns of trend in vegetation growth.

Seasonally different response of photosynthetic activity to daytime and night-time warming in the Northern Hemisphere

Over the last century the Northern Hemisphere has experienced rapid climate warming, but this warming has not been evenly distributed seasonally, as well as diurnally. The implications of such seasonal and diurnal heterogeneous warming on regional and global vegetation photosynthetic activity, however, are still poorly understood. Here, we investigated for different seasons how photosynthetic activity of vegetation correlates with changes in seasonal daytime and night-time temperature across the Northern Hemisphere (>30°N), using Normalized Difference Vegetation Index (NDVI) data from 1982 to 2011 obtained from the Advanced Very High Resolution Radiometer (AVHRR). Our analysis revealed some striking seasonal differences in the response of NDVI to changes in day- vs. night-time temperatures. For instance, while higher daytime temperature (Tmax) is generally associated with higher NDVI values across the boreal zone, the area exhibiting a statistically significant positive correlation between Tmax and NDVI is much larger in spring (41% of area in boreal zone--total area 12.6×10(6) km2) than in summer and autumn (14% and 9%, respectively). In contrast to the predominantly positive response of boreal ecosystems to changes in Tmax, increases in Tmax tended to negatively influence vegetation growth in temperate dry regions, particularly during summer. Changes in night-time temperature (Tmin) correlated negatively with autumnal NDVI in most of the Northern Hemisphere, but had a positive effect on spring and summer NDVI in most temperate regions (e.g., Central North America and Central Asia). Such divergent covariance between the photosynthetic activity of Northern Hemispheric vegetation and day- and night-time temperature changes among different seasons and climate zones suggests a changing dominance of ecophysiological processes across time and space. Understanding the seasonally different responses of vegetation photosynthetic activity to diurnal temperature changes, which have not been captured by current land surface models, is important for improving the performance of next generation regional and global coupled vegetation-climate models.

From the camp pathway to search the ketamine-related learning and memory

Protein kinase A (PKA) phosphorylates and activates cAMP response element-binding protein (CREB), which then binds to CRE domain on DNA and in turn activates genes involved in the process of learning and memorization. It has been demonstrated that CREB is involve in the learning and memory deficits that are caused by ketamine. In this review, we attempt to discuss the role of ketamine and cAMP pathway and relevant regulatory protein ERK in learning and memory through the molecular mechanism and signaling pathways. In this review, we also try to find a new way to treat the impairment in learning and memory induced by ketamine.

Explanation of colon cancer pathophysiology through analyzing the disrupted homeostasis of bile acids

BACKGROUND

The colon plays a key role in regulating the homeostasis of bile acids.

AIM

The present study aims to evaluate the influence of colon cancer towards the homeostasis of bile acids.

METHODS

The free and conjugated bile acids were determined using ultraperformance LC (UPLC) coupled with ABI 4000 QTRAP triple quadrupole instruments.

RESULTS

The results showed that the free bile acids in serum of patients with colon cancers tend to increase, and the conjugated bile acids tended to decrease, especially for taurolithocholate (TLCA) (p<0.001).

CONCLUSION

The alteration of bile acids balance in colon cancers indicated the possibility of complicated diseases due to the disrupted balance of bile acids.

The phosphodiesterase-4 inhibitor Ro 20-1724 reverses learning and memory impairments, and downregulation of CREB in the hippocampus and cortex induced by ketamine anesthesia in immature rats

AIM

The objective of the study was to examine the effects and possible mechanisms of phosphodiesterase-4 inhibitor Ro 20-1724 on learning and memory impairments induced by ketamine anesthesia. Further, expression the cAMP response element binding proteins (CREB), transcription factors involved in long-term memory, were analyzed in conjunction with these effects of Ro 20-1724.

METHODS

Ninety-six immature (21-day-old) Sprague-Dawley rats were divided into eight groups. To assess the learning and memory impairments, Morris Water Maze task was used. Expression of total and phosphorylated CREB in the hippocampus and cerebral cortex was evaluated by Western blot.

RESULTS

THE escape latency and frequency of passing the platform in Morris Water Maze task were markedly longer after ketamine anesthesia. However, treatment with Ro 20-1724 significantly (P<0.05) improved both learning and memory performance. Further, administration of Ro 20-1724 reverted the down-regulation of total and phosphorylated CREB caused by ketamine (P<0.05), as demonstrated by Western blot analysis of CREB expression in the hippocampus and cortex.

CONCLUSION

Treatment with Ro 20-1724 improves learning and memory deficits caused by ketamine anesthesia in immature rats, possibly via increases in expression of total and phosphorylated CREB in the hippocampus and cerebral cortex.

Expression profile of Nanos2 gene in dairy goat and its inhibitory effect on Stra8 during meiosis

OBJECTIVES

Nanos2, an RNA-binding protein, belongs to the Nanos gene-coding family and contains two CCHC zinc-finger motifs. In mouse, it plays a pivotal role in male germ cell development, and self-renewal of spermatogonial stem cells. However, little is known of its expression pattern and functions in dairy goat testis.

MATERIALS AND METHODS

Immunohistochemistry and quantitative reverse transcription-polymerase chain reaction (qRT-PCR) were used to generate the expression profile of Nanos2 in dairy goat testis. Furthermore, its overexpression effects on male germline stem cells (mGSCs) were studied using qRT-PCR, immunofluorescence, dual-luciferase reporter assay and western blotting.

RESULTS

Nanos2 is a conservative gene expressed widely in various tissues, especially in pancreas, and it displays higher expression in adult testes than in other age groups. Overexpression of Nanos2 significantly downregulated meiosis-related genes, including Stra8 and Scp3, which induced inhibition of meiosis. Results from dual-luciferase reporter assay and western blotting indicated that Nanos2 directly downregulated Stra8 in goat GmGSCs.

CONCLUSIONS

Taken together, these results suggest that Nanos2 plays an important role in spermatogonia and that its overexpression restrained meiosis in the dairy goat.

The influence of local spring temperature variance on temperature sensitivity of spring phenology

The impact of climate warming on the advancement of plant spring phenology has been heavily investigated over the last decade and there exists great variability among plants in their phenological sensitivity to temperature. However, few studies have explicitly linked phenological sensitivity to local climate variance. Here, we set out to test the hypothesis that the strength of phenological sensitivity declines with increased local spring temperature variance, by synthesizing results across ground observations. We assemble ground-based long-term (20-50 years) spring phenology database (PEP725 database) and the corresponding climate dataset. We find a prevalent decline in the strength of phenological sensitivity with increasing local spring temperature variance at the species level from ground observations. It suggests that plants might be less likely to track climatic warming at locations with larger local spring temperature variance. This might be related to the possibility that the frost risk could be higher in a larger local spring temperature variance and plants adapt to avoid this risk by relying more on other cues (e.g., high chill requirements, photoperiod) for spring phenology, thus suppressing phenological responses to spring warming. This study illuminates that local spring temperature variance is an understudied source in the study of phenological sensitivity and highlight the necessity of incorporating this factor to improve the predictability of plant responses to anthropogenic climate change in future studies.