Projecting the distribution of forests in New England in response to climate change

Aim To project the distribution of three major forest types in the northeastern USA in response to expected climate change. Location The New England region of the United States. Methods We modelled the potential distribution of boreal conifer, northern deciduous hardwood and mixed oak-hickory forests using the process-based BIOME4 vegetation model parameterized for regional forests under historic and projected future climate conditions. Projections of future climate were derived from three general circulation models forced by three global warming scenarios that span the range of likely anthropogenic greenhouse gas emissions. Results Annual temperature in New England is projected to increase by 2.2-3.3 °C by 2041-70 and by 3.0-5.2 °C by 2071-99 with corresponding increases in precipitation of 4.7-9.5% and 6.4-11.4%, respectively. We project that regional warming will result in the loss of 71-100% of boreal conifer forest in New England by the late 21st century. The range of mixed oak-hickory forests will shift northward by 1.0-2.1 latitudinal degrees (c. 100-200 km) and will increase in area by 149-431% by the end of the 21st century. Northern deciduous hardwoods are expected to decrease in area by 26% and move upslope by 76 m on average. The upslope movement of the northern deciduous hardwoods and the increase in oak-hickory forests coincide with an approximate 556 m upslope retreat of the boreal conifer forest by 2071-99. In our simulations, rising atmospheric CO2 concentrations reduce the losses of boreal conifer forest in New England from expected losses based on climatic change alone. Main conclusion Projected climate warming in the 21st century is likely to cause the extensive loss of boreal conifer forests, reduce the extent of northern hardwood deciduous forests, and result in large increases of mixed oak-hickory forest in New England. © 2010 Blackwell Publishing Ltd

Estimating potential forest NPP, biomass and their climatic sensitivity in New England using a dynamic ecosystem model

Accurate estimation of forest net primary productivity (NPP), biomass, and their sensitivity to changes in temperature and precipitation is important for understanding the fluxes and pools of terrestrial carbon resulting from anthropogenically driven climate change. The objectives of this study were to (1) estimate potential forest NPP and biomass for New England using a regional ecosystem model, (2) compare modeled forest NPP and biomass with other reported data for New England, and (3) examine the sensitivity of modeled forest NPP to historical climatic variation. We addressed these objectives using the regional ecosystem model LPJ-GUESS implemented with eight plant functional types representing New England forests. We ran the model using 30-arc second spatial resolution climate data in monthly timesteps for the period 1901-2006. The modeled forest NPP and biomass were compared to empirically-based MODIS and FIA estimates of NPP and U.S. forest biomass. Our results indicate that forest NPP in New England averages 428 g C m-2yr-1 and ranges from 333 to 541 g C m-2yr-1 for the baseline period (1971- 2000), while forest biomass averages 135 Mg/ha and ranges from 77 to 242 Mg/ha. Modeled forest biomass decreased at a rate of 0.11 Mg/ha (R2=0.74) per year in the period 1901-1949 but increased at a rate of 0.25 Mg/ha (R2=0.95) per year in the period 1950-2006. Estimates of NPP and biomass depend on forest type: spruce-fir had the lowest mean of 395 g C m-2yr-1 and oak forest had the highest mean of 468 g C m-2yr-1. Similarly, forest biomass was highest in oak (153 Mg/ha) and lowest in red-jack pine (118 Mg/ ha) forests. The modeled NPP for New England agrees well with FIA-based estimates from similar forests in the mid-Atlantic region but was smaller than MODIS NPP estimates for New England. Nevertheless, the modeled inter-annual variability of NPP was strongly correlated with the MODIS NPP data. The modeled biomass agrees well with U.S. forest biomass data for New England but was less than FIA-based estimates in the mid-Atlantic region. For the region as a whole, the modeled NPP and biomass are within the ranges of MODIS- and FIA-based estimates. Forest NPP was sensitive to changes in temperature and precipitation: NPP was positively related to temperatures in April, May and October but negatively related to summer temperature. Increases in precipitation in the growing season enhanced forest NPP. © 2010 Tang et al

A Kind of New Surface Modeling Method Based on DEM Data

Surface elevation changes greatly in the river erosion area. Due to the limitation of the acquisition equipment and cost, the traditional seismic acquisition data has sparse physical points both horizontally and longitudinally, the density of surface measurement data is not enough to survey the surface structure in detail. With the development of science and technology, and the application of satellite technology, the DEM elevation data obtained from the geographic information system (GIS) are becoming more and more accurate. In this paper, a precise modeling is performed on the surface based on the geographic information from the river erosion area and combined with the results of the surface survey control points, a good effect is achieved.Key words: River erosion area; Geographic information; Similarity coefficient; Kriging interpolation; Surface modeling; High and low frequency static

KCAT: A Knowledge-Constraint Typing Annotation Tool

Fine-grained Entity Typing is a tough task which suffers from noise samples extracted from distant supervision. Thousands of manually annotated samples can achieve greater performance than millions of samples generated by the previous distant supervision method. Whereas, it's hard for human beings to differentiate and memorize thousands of types, thus making large-scale human labeling hardly possible. In this paper, we introduce a Knowledge-Constraint Typing Annotation Tool (KCAT), which is efficient for fine-grained entity typing annotation. KCAT reduces the size of candidate types to an acceptable range for human beings through entity linking and provides a Multi-step Typing scheme to revise the entity linking result. Moreover, KCAT provides an efficient Annotator Client to accelerate the annotation process and a comprehensive Manager Module to analyse crowdsourcing annotations. Experiment shows that KCAT can significantly improve annotation efficiency, the time consumption increases slowly as the size of type set expands.Comment: 6 pages, acl2019 demo pape

Gene expression profile analysis of human hepatocellular carcinoma using SAGE and LongSAGE

<p>Abstract</p> <p>Background</p> <p>Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide and the second cancer killer in China. The initiation and malignant transformation of cancer result from accumulation of genetic changes in the sequences or expression level of cancer-related genes. It is of particular importance to determine gene expression profiles of cancers on a global scale. SAGE and LongSAGE have been developed for this purpose.</p> <p>Methods</p> <p>We performed SAGE in normal liver and HCC samples as well as the liver cancer cell line HepG2. Meanwhile, the same HCC sample was simultaneously analyzed using LongSAGE. Computational analysis was carried out to identify differentially expressed genes between normal liver and HCC which were further validated by real-time quantitative RT-PCR.</p> <p>Results</p> <p>Approximately 50,000 tags were sequenced for each of the four libraries. Analysis of the technical replicates of HCC indicated that excluding the low abundance tags, the reproducibility of SAGE data is high (R = 0.97). Compared with the gene expression profile of normal liver, 224 genes related to biosynthesis, cell proliferation, signal transduction, cellular metabolism and transport were identified to be differentially expressed in HCC. Overexpression of some transcripts selected from SAGE data was validated by real-time quantitative RT-PCR. Interestingly, sarcoglycan-ε (SGCE) and paternally expressed gene (PEG10) which is a pair of close neighboring genes on chromosome 7q21, showed similar enhanced expression patterns in HCC, implicating that a common mechanism of deregulation may be shared by these two genes.</p> <p>Conclusion</p> <p>Our study depicted the expression profile of HCC on a genome-wide scale without the restriction of annotation databases, and provided novel candidate genes that might be related to HCC.</p

The Effects of Warfarin on the Pharmacokinetics of Senkyunolide I in a Rat Model of Biliary Drainage After Administration of Chuanxiong

The aim of this study was to elucidate the effects of warfarin on senkyunolide I in a rat model of biliary drainage after oral administration Chuanxiong extract based on pharmacokinetics. Thirty-two rats were randomly divided into four groups: CN, healthy rats after a single administration of Chuanxiong; CO, rats with biliary drainage after a single administration of Chuanxiong; WCN, healthy rats after the administration of Chuanxiong and warfarin; WCO, rats with biliary drainage after the administration of Chuanxiong and warfarin. A series of blood samples were collected at different time points before and after oral administration. An ultra-performance liquid chromatography coupled to tandem mass spectrometry (UPLC-MS/MS) method for quantification of the main components of Chuanxiong and methyclothiazide (internal standard) have been established. The validated method was successfully applied to a comparative pharmacokinetics study. After calculated by the DAS 2.1.1 software, the pharmacokinetics parameters of senkyunolide I showed a significant difference between the CN and CO groups, the AUC0−t, and Cmax of CO group increased by 5.45, 4.02 folds, respectively. There was a significant difference between the WCO and WCN groups, the Tmax of WCO group prolonged 67%; compared to the CN group, the AUC0−t, and Cmax of WCN group raised 4.84, 3.49 folds, respectively; the Tmax and Cmax between the CO and WCO groups also showed a significant difference. The drug warfarin significantly affected the senkyunolide I disposition, which partly due to its enterohepatic circulation process in rat plasma after oral administration of Chuanxiong. The present study highlights an urgent evidence for drug-herb interactions

Effidit: Your AI Writing Assistant

In this technical report, we introduce Effidit (Efficient and Intelligent Editing), a digital writing assistant that facilitates users to write higher-quality text more efficiently by using artificial intelligence (AI) technologies. Previous writing assistants typically provide the function of error checking (to detect and correct spelling and grammatical errors) and limited text-rewriting functionality. With the emergence of large-scale neural language models, some systems support automatically completing a sentence or a paragraph. In Effidit, we significantly expand the capacities of a writing assistant by providing functions in five categories: text completion, error checking, text polishing, keywords to sentences (K2S), and cloud input methods (cloud IME). In the text completion category, Effidit supports generation-based sentence completion, retrieval-based sentence completion, and phrase completion. In contrast, many other writing assistants so far only provide one or two of the three functions. For text polishing, we have three functions: (context-aware) phrase polishing, sentence paraphrasing, and sentence expansion, whereas many other writing assistants often support one or two functions in this category. The main contents of this report include major modules of Effidit, methods for implementing these modules, and evaluation results of some key methods.Comment: Technical report for Effidit. arXiv admin note: text overlap with arXiv:2202.0641