Changes in labile carbon (LC) pools and microbial communities are the primary factors controlling soil heterotrophic respiration (R h ) in warming experiments. Warming is expected to initially increase R h but studies show this increase may not be continuous or sustained. Specifically, LC and soil microbiome have been shown to contribute to the effect of extended warming on R h . However, their relative contribution is unclear and this gap in knowledge causes considerable uncertainty in the prediction of carbon cycle feedbacks to climate change. In this study, we used a two-step incubation approach to reveal the relative contribution of LC limitation and soil microbial community responses in attenuating the effect that extended warming has on R h . Soil samples from three Tibetan ecosystems-an alpine meadow (AM), alpine steppe (AS), and desert steppe (DS)-were exposed to a temperature gradient of 5-25°C. After an initial incubation period, soils were processed in one of two methods: (a) soils were sterilized then inoculated with parent soil microbes to assess the LC limitation effects, while controlling for microbial community responses; or (b) soil microbes from the incubations were used to inoculate sterilized parent soils to assess the microbial community effects, while controlling for LC limitation. We found both LC limitation and microbial community responses led to significant declines in R h by 37% and 30%, respectively, but their relative contributions were ecosystem specific. LC limitation alone caused a greater R h decrease for DS soils than AMs or ASs. Our study demonstrates that soil carbon loss due to R h in Tibetan alpine soils-especially in copiotrophic soils-will be weakened by microbial community responses under short-term warming.
Changes in day (maximum temperature, TMAX) and night temperature (minimum temperature, TMIN) in the preseason (e.g., winter and spring) may have opposite effects on early phenophases (e.g., leafing and flowering) due to changing requirements of chilling accumulations (CAC) and heating accumulations (HAC), which could cause advance, delay or no change in early phenophases. However, their relative effects on phenology are largely unexplored, especially on the Tibetan Plateau. Here, observations were performed using a warming and cooling experiment in situ through reciprocal transplantation (2008–2010) on the Tibetan Plateau. We found that winter minimum temperature (TMIN) warming significantly delayed mean early phenophases by 8.60 d/°C, but winter maximum temperature (TMAX) warming advanced them by 12.06 d/°C across six common species. Thus, winter mean temperature warming resulted in a net advance of 3.46 d/°C in early phenophases. In contrast, winter TMIN cooling, on average, significantly advanced early phenophases by 5.12 d/°C, but winter TMAX cooling delayed them by 7.40 d/°C across six common species, resulting in a net delay of 2.28 d/°C for winter mean temperature cooling. The opposing effects of TMAX and TMIN warming on the early phenophases may be mainly caused by decreased CAC due to TMIN warming (5.29 times greater than TMAX) and increased HAC due to TMAX warming (3.25 times greater than TMIN), and similar processes apply to TMAX and TMIN cooling. Therefore, our study provides another insight into why some plant phenophases remain unchanged or delayed under climate change.
The endemic lobeliad genera Cyanea and Clermontia (Campanulaceae) are among the largest in the native Hawaiian flora, and contain large numbers of endangered and threatened taxa. As a baseline for future studies of rare species in this group, we used RAD markers to estimate genetic variation and spatial genetic structure in single populations of two common species,
Few studies have focused on the response of plant community phenology to temperature change using manipulative experiments. A lack of understanding of whether responses of community reproductive and vegetative phenological sequences to warming and cooling are asymmetrical or symmetrical limits our capacity to predict responses under warming and cooling. A reciprocal transplant experiment was conducted for 3 years to evaluate response patterns of the temperature sensitivities of community phenological sequences to warming (transferred downward) and cooling (transferred upward) along four elevations on the Tibetan Plateau. We found that the temperature sensitivities of flowering stages had asymmetric responses to warming and cooling, whereas symmetric responses to warming and cooling were observed for the vegetative phenological sequences. Our findings showed that coverage changes of flowering functional groups (FFGs; i.e., early-spring FFG, mid-summer FFG, and late-autumn FFG) and their compensation effects combined with required accumulated soil temperatureto codetermined the asymmetric and symmetric responses of community phenological sequences to warming and cooling. These results suggest that coverage change in FFGs on warming and cooling processes can be a primary driver of community phenological variation and may lead to inaccurate phenlogical estimation at large scale, such as based on remote sensing.
Analyzing single-cell transcriptomes promises to decipher the plasticity, heterogeneity, and rapid switches in developmental cellular state transitions. Such analyses require the identification of gene markers for semi-stable transition states. However, there are nontrivial challenges such as unexplainable stochasticity, variable population sizes, and alternative trajectory constructions. By advancing current tipping-point theory-based models with feature selection, network decomposition, accurate estimation of correlations, and optimization, we developed BioTIP to overcome these challenges. BioTIP identifies a small group of genes, called critical transition signal (CTS), to characterize regulated stochasticity during semi-stable transitions. Although methods rooted in different theories converged at the same transition events in two benchmark datasets, BioTIP is unique in inferring lineage-determining transcription factors governing critical transition. Applying BioTIP to mouse gastrulation data, we identify multiple CTSs from one dataset and validated their significance in another independent dataset. We detect the established regulator Etv2 whose expression change drives the haemato-endothelial bifurcation, and its targets together in CTS across three datasets. After comparing to three current methods using six datasets, we show that BioTIP is accurate, user-friendly, independent of pseudo-temporal trajectory, and captures significantly interconnected and reproducible CTSs. We expect BioTIP to provide great insight into dynamic regulations of lineage-determining factors.
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