Impacts of Stress on Forest Recovery and Its Interaction with Canopy Height

Global climate change is leading to an increase in the frequency, intensity, and duration of drought events, which can affect the functioning of forest ecosystems. Because human activities such as afforestation and forest attributes such as canopy height may exhibit considerable spatial differences, such differences may alter the recovery paths of drought-impacted forests. To accurately assess how climate affects forest recovery, a quantitative evaluation on the effects of forest attributes and their possible interaction with the intensity of water stress is required. Here, forest recovery following extreme drought events was analyzed for Yunnan Province, southwest China. The variation in the recovery of forests with different water availability and canopy heights was quantitatively assessed at the regional scale by using canopy height data based on light detection and ranging (LiDAR) measurements, enhanced vegetation index data, and standardized precipitation evapotranspiration index (SPEI) data. Our results indicated that forest recovery was affected by water availability and canopy height. Based on the enhanced vegetation index measures, shorter trees were more likely to recover than taller ones after drought. Further analyses demonstrated that the effect of canopy height on recovery rates after drought also depends on water availability—the effect of canopy height on recovery diminished as water availability increased after drought. Additional analyses revealed that when the water availability exceeded a threshold (SPEI \u3e 0.85), no significant difference in the recovery was found between short and tall trees (p \u3e 0.05). In the context of global climate change, future climate scenarios of RCP2.6 and RCP8.5 showed more frequent water stress in Yunnan by the end of the 21st century. In summary, our results indicated that canopy height casts an important influence on forest recovery and tall trees have greater vulnerability and risk to dieback and mortality from drought. These results may have broad implications for policies and practices of forest management

Mlsp : A bioinformatics tool for predicting molecular subtypes and prognosis in patients with breast cancer

The molecular landscape in breast cancer is characterized by large biological heterogeneity and variable clinical outcomes. Here, we performed an integrative multi-omics analysis of patients diagnosed with breast cancer. Using transcriptomic analysis, we identified three subtypes (cluster A, cluster B and cluster C) of breast cancer with distinct prognosis, clinical features, and genomic alterations: Cluster A was asso-ciated with higher genomic instability, immune suppression and worst prognosis outcome; cluster B was associated with high activation of immune-pathway, increased mutations and middle prognosis out-come; cluster C was linked to Luminal A subtype patients, moderate immune cell infiltration and best prognosis outcome. Combination of the three newly identified clusters with PAM50 subtypes, we pro-posed potential new precision strategies for 15 subtypes using L1000 database. Then, we developed a robust gene pair (RGP) score for prognosis outcome prediction of patients with breast cancer. The RGP score is based on a novel gene-pairing approach to eliminate batch effects caused by differences in heterogeneous patient cohorts and transcriptomic data distributions, and it was validated in ten cohorts of patients with breast cancer. Finally, we developed a user-friendly web-tool (https://sujiezhulab.shi-nyapps.io/BRCA/) to predict subtype, treatment strategies and prognosis states for patients with breast cancer.(c) 2022 The Authors. Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology. This is an open access article under the CC BY-NC-ND license (http://creative-commons.org/licenses/by-nc-nd/4.0/).Peer reviewe

Bifurcated Response of a Regional Forest to Drought

Several lines of evidence suggest that forest growth in many regions is declining as a consequence of changing climate. To predict the fate of forests in the future, a quantitative understanding of how the key climate variables (insolation, precipitation and temperature) interact with forests to cause the decline is a pressing need. Here we use a regionally-averaged tree-ring width index (RWIr ) to quantify forest growth in the Southwest United States (SWUS). We show that over a period of 100 years, SWUS RWIr bifurcated into forest stands with enhanced (healthy) and reduced (declining) branches when regressed on shortwave-radiation and temperature, respectively. The reduced branch was controlled overwhelmingly by drought as measured with a regionally-averaged precipitationevapotranspiration index (SPEIr ). As SPEIr approached -1.6 (previously shown as a tipping-point for SWUS conifer forest growth), RWIr approached zero and in extreme drought years, wide spread tree mortality has been observed. Modeled trends in SPEI based on four IPCC-GHG scenarios predict SWUS SPEIr falling below -1.6 more or less continuously within a few decades. With drought expanding north- and eastward over larger areas, tree mortality may become a semi-continental phenomenon with coniferous forests transitioning to more xeric ecosystems. Our results provide insights into how to differentiate functions of climate impacts on forest growth and how to identify tipping-point control parameters for forest regime transitions

Construction Dispute Potentials: Mechanism versus Empiricism in Artificial Neural Networks

The booming development of neural network algorithms has shifted the research focus in the field of construction project management from causal investigation to statistical approximation and hence from mechanistic models to empirical models. This paper took construction dispute avoidance as an example and enabled the best efforts to establish paired mechanistic and empirical models to investigate if the pursuit of a mechanistic understanding of construction disputes should be continued. A Bayesian belief network and multilayer perceptron were used for mechanistic and empirical simulations, respectively. A list of critical dispute factors was first identified from the literature and shortlisted by Pearson’s chi-square tests and Pearson product-moment correlational coefficient tests. The structure of the Bayesian belief network was constructed with logical deduction assisted by a further literature review and Delphi surveys. A structured questionnaire survey was conducted to collect quantitative data for factor shortlisting and model quantification. It was revealed that, being assisted with machine learning techniques, both mechanistic and empirical models achieved an accuracy rate of over 95% under ideal conditions. However, Bayesian belief network models predicted better with fewer constraints due to their advantages in reflecting the formation mechanism of construction disputes, while multilayer perceptron models were more constrained by the inconvenience of sourcing high-quality data as model input. This paper demonstrated that it is still necessary to investigate the formation mechanism of construction disputes further for more efficient avoidance strategies. During the investigation of model construction and comparison, this paper also reflected on the interpretation of statistical threshold and proposed that an arbitrary single cut-off point for statistical tests could potentially eliminate factors that should have been included

THE EFFECT OF TEMPERATURE ON THE HALF-WIDTH OF THE ETHYLENE ABSORPTION AT 10μ10 \mu

Author Institution: Department of Physics, East China Normal UniversityThe line strength and Doppler width will vary only with temperature, whereas the half width will vary both with temperature and pressure. A stabilized $10 \mu p(14) CO_{2}$ laser line was used to measure the variation of absorption with temperature at constant density of ethylene. Measurements of almost complete extinction by the ethylene indicate that the $949.454 cm^{-1}$ and $949.501 cm^{-1}$ transitions are the frequencies which used to be considered. The results of five seperate constant density runs were obtained. The curves were computer-calculated for value of the temperature dependent parameter differing by 0.1 and ranging from 0.5 to 1.2. It is concluded that the temperature dependence of the linewidth is close to $T^{-0.6}$, while the value would be $T^{-0.5}$ according to the theoritical interpretation

THE LASER QUANTITATIVE SPECTRA OF DIOXIDE CARBON AT 10μ\mu BANDS

Address: Department of Physics, East-China Normal University, Shanghai, 200062, People's Republic of ChinaAuthor Institution:Recent measuring of $CO_{2}$ vi-rotational lines at 10$\mu$ bands has performed under the temperature dependent conditions, ranging from room temperature to around hundreds. The line strength, half-width due pressure broadening and its temperature dependent factors have been obtained through experiments. The results showed that the theoretical calculating values of atmospheric absorption for laser radiation were strongly dependent on atmosphere temperature since the spectra dependence of the cross section varied at different conditions. The data given referred to a wide range of quantitative spectral parameters, including line strength, self and $N_{2}$-broadening