skip to main content

Search for: All records

Creators/Authors contains: "Chen, Fei"

Note: When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher. Some full text articles may not yet be available without a charge during the embargo (administrative interval).
What is a DOI Number?

Some links on this page may take you to non-federal websites. Their policies may differ from this site.

  1. Abstract The large size and complexity of most fern genomes have hampered efforts to elucidate fundamental aspects of fern biology and land plant evolution through genome-enabled research. Here we present a chromosomal genome assembly and associated methylome, transcriptome and metabolome analyses for the model fern species Ceratopteris richardii . The assembly reveals a history of remarkably dynamic genome evolution including rapid changes in genome content and structure following the most recent whole-genome duplication approximately 60 million years ago. These changes include massive gene loss, rampant tandem duplications and multiple horizontal gene transfers from bacteria, contributing to the diversification of defence-related gene families. The insertion of transposable elements into introns has led to the large size of the Ceratopteris genome and to exceptionally long genes relative to other plants. Gene family analyses indicate that genes directing seed development were co-opted from those controlling the development of fern sporangia, providing insights into seed plant evolution. Our findings and annotated genome assembly extend the utility of Ceratopteris as a model for investigating and teaching plant biology.
    Free, publicly-accessible full text available September 1, 2023
  2. Free, publicly-accessible full text available April 8, 2023
  3. Abstract. This study proposes a novel structural self-organizingmap (S-SOM) algorithm for synoptic weather typing. A novel feature of theS-SOM compared with traditional SOMs is its ability to deal with input datawith spatial or temporal structures. In detail, the search scheme for thebest matching unit (BMU) in a S-SOM is built based on a structuralsimilarity (S-SIM) index rather than by using the traditional Euclideandistance (ED). S-SIM enables the BMU search to consider the correlation inspace between weather states, such as the locations of highs or lows, that is impossible when using ED. The S-SOM performance is evaluated by multipledemo simulations of clustering weather patterns over Japan using theERA-Interim sea-level pressure data. The results show the S-SOM'ssuperiority compared with a standard SOM with ED (or ED-SOM) in tworespects: clustering quality based on silhouette analysis and topologicalpreservation based on topological error. Better performance of S-SOM versusED is consistent with results from different tests and node-sizeconfigurations. S-SOM performs better than a SOM using the Pearsoncorrelation coefficient (or COR-SOM), though the difference is not as clear as it is compared to ED-SOM.
  4. Abstract When compared with differences in snow accumulation predicted by widely used hydrological models, there is a much greater divergence among otherwise “good” models in their simulation of the snow ablation process. Here, we explore differences in the performance of the Variable Infiltration Capacity model (VIC), Noah land surface model with multiparameterization options (Noah-MP), the Catchment model, and the third-generation Simplified Simple Biosphere model (SiB3) in their ability to reproduce observed snow water equivalent (SWE) during the ablation season at 10 Snowpack Telemetry (SNOTEL) stations over 1992–2012. During the ablation period, net radiation generally has stronger correlations with observed melt rates than does air temperature. Average ablation rates tend to be higher (in both model predictions and observations) at stations with a large accumulation of SWE. The differences in the dates of last snow between models and observations range from several days to approximately a month (on average 5.1 days earlier than in observations). If the surface cover in the models is changed from observed vegetation to bare soil in all of the models, only the melt rate of the VIC model increases. The differences in responses of models to canopy removal are directly related to snowpack energy inputs, whichmore »are further affected by different algorithms for surface albedo and energy allocation across the models. We also find that the melt rates become higher in VIC and lower in Noah-MP if the shrub/grass present at the observation sites is switched to trees.« less