scholarly journals Phylogeography of the rare and endangered lycophyte Isoetes yunguiensis

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e8270
Author(s):  
Tao Zheng ◽  
Xuanze He ◽  
Honghuan Ye ◽  
Wei Fu ◽  
Maimai Peng ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Maximum Entropy ◽  
Ssr Markers ◽  
Expressed Sequence Tag ◽  
Rapid Expansion ◽  
Distribution Area ◽  
Maximum Entropy Model ◽  
Entropy Model ◽  
Living Fossil ◽  
Genetic Diversity And Structure

Background Isoetes yunguiensis Q. F. Wang & W. C. Taylor is a lycophyte of an ancient genus, and it is endemic to China. It is a first-class protected plant in China. This living fossil is used in paleoecology and studies on the evolution of Lycophytes in the Yunnan-Guizhou Plateau. In recent years, human activities have caused the disappearance of several wild populations, and the number of plants in the existing populations is low. Study of the genetic structure, distribution pattern, and historical dynamics of I. yunguiensis in all areas of its distribution is of guiding significance for its rational and effective protection. Methods Expressed sequence tag-simple sequence repeat (EST-SSR) markers were used to study the genetic diversity and structure of I. yunguiensis, and noncoding chloroplast DNA (cpDNA) sequences were used to study the pedigree, population dynamics history, and glacial shelter of I. yunguiensis. A maximum entropy model was used to predict the past, present, and future distribution patterns of I. yunguiensis. Results Analysis with EST-SSR markers revealed that I. yunguiensis showed high genetic diversity and that genetic variation was significantly higher within populations than between populations. Based on cpDNA data, it was concluded that there was no significant geographic pedigree in the whole area of I. yunguiensis distribution (NST = 0.344 >  GST = 0.183, p > 0.05); 21 haplotypes were detected using DnaSP v5. Neutral test and LAMARC simulation showed that I. yunguiensis has experienced rapid expansion in recent years. The maximum entropy model predicted that the potential distribution area of I. yunguiensis in the last glacial maximum period has increased significantly compared with the present distribution area, but the future distribution area did not show substantial changes.

scholarly journals Genetic Diversity and Structure of Japanese Endemic Genus Thujopsis (Cupressaceae) Using EST-SSR Markers

Forests ◽  
2020 ◽  
Vol 11 (9) ◽  
pp. 935
Author(s):  
Michiko Inanaga ◽  
Yoichi Hasegawa ◽  
Kentaro Mishima ◽  
Katsuhiko Takata
Keyword(s):  
Genetic Diversity ◽  
Ssr Markers ◽  
Structure Analysis ◽  
Expressed Sequence Tag ◽  
Distribution Range ◽  
Distribution Area ◽  
Neighbor Joining ◽  
Genetic Population ◽  
Distribution Ranges ◽  
Genetic Diversity And Structure

The genus Thujopsis (Cupressaceae) comprises monoecious coniferous trees endemic to Japan. This genus includes two varieties: Thujopsis dolabrata (L.f.) Siebold et Zucc. var. dolabrata (southern variety, Td) and Thujopsis dolabrata (L.f.) Siebold et Zucc. var. hondae Makino (northern variety, Th). The aim of this study is to understand the phylogeographic and genetic population relationships of the genus Thujopsis for the conservation of genetic resources and future breeding. A total of 609 trees from 22 populations were sampled, including six populations from the Td distribution range and 16 populations from the Th distribution range. The genotyping results for 19 expressed sequence tag (EST)-based simple sequence repeat (SSR) markers, followed by a structure analysis, neighbor-joining tree creation, an analysis of molecular variance (AMOVA), and hierarchical F statistics, supported the existence of two genetic clusters related to the distribution regions of the Td and Th varieties. The two variants, Td and Th, could be defined by their provenance, in spite of the ambiguous morphological differences between the varieties. The distribution ranges of both variants, which have been defined from their morphology, was confirmed by genetic analysis. The Th populations exhibited relatively uniform genetic diversity, most likely because Th refugia in the glacial period were scattered throughout their current distribution area. On the other hand, there was a tendency for Td’s genetic diversity to decrease from central to southern Honshu island. Notably, the structure analysis and neighbor-joining tree suggest the hybridization of the two varieties in the contact zone. More detailed studies of the genetic structure of Td are required in future analyses.

scholarly journals Modelling the potential distribution and habitat suitability of the alien fungus Clathrus archeri in Romania

2021 ◽  
Vol 45 (2) ◽  
pp. 241-250
Author(s):  
Ciprian Bîrsan ◽  
Constantin Mardari ◽  
Ovidiu Copoţ ◽  
Cătălin Tănase
Keyword(s):  
Habitat Suitability ◽  
Potential Distribution ◽  
Rapid Expansion ◽  
Distribution Area ◽  
Maximum Entropy Model ◽  
Invasive Potential ◽  
Entropy Model ◽  
The Mean ◽  
Suitable Habitats ◽  
Model Approach

Clathrus archeri is a saprophytic fungus native to the southern hemisphere which was introduced in Europe in the early twentieth century. Although it is naturalized in most regions of Central Europe, in Romania it is considered rather a rare species because it has been identified in only a few localities. Because of the rapid expansion of its range throughout Europe some authors assign this species an invasive potential. The objective of the paper was to identify both the potential distribution area and the potential suitable habitats for expansion in Romania and to highlight the environmental variables driving the probability of its occurrence. The maximum entropy model approach implemented in Maxent was used to model the species? potential distribution. The results highlighted altitude, snow cover length, the mean temperature of the driest quarter, and precipitation in the coldest quarter as the most important predictors of species? potential distribution in Romania. The map of the predicted distribution showed that the highest probability of occurrence for this species is in the mountainous and adjacent areas, while the map of habitat suitability confirmed that the best environmental conditions are in the Carpathians, while the most unfavourable are in the south-eastern regions of the country.

scholarly journals Pairwise maximum entropy model explains the role of white matter structure in shaping emergent co-activation states

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Arian Ashourvan ◽  
Preya Shah ◽  
Adam Pines ◽  
Shi Gu ◽  
Christopher W. Lynn ◽  
...  
Keyword(s):  
White Matter ◽  
Maximum Entropy ◽  
Large Scale ◽  
Structural Connectivity ◽  
Quantitative Relationship ◽  
Brain Regions ◽  
Maximum Entropy Model ◽  
Entropy Model ◽  
Activation Patterns ◽  
Co Activation

AbstractA major challenge in neuroscience is determining a quantitative relationship between the brain’s white matter structural connectivity and emergent activity. We seek to uncover the intrinsic relationship among brain regions fundamental to their functional activity by constructing a pairwise maximum entropy model (MEM) of the inter-ictal activation patterns of five patients with medically refractory epilepsy over an average of ~14 hours of band-passed intracranial EEG (iEEG) recordings per patient. We find that the pairwise MEM accurately predicts iEEG electrodes’ activation patterns’ probability and their pairwise correlations. We demonstrate that the estimated pairwise MEM’s interaction weights predict structural connectivity and its strength over several frequencies significantly beyond what is expected based solely on sampled regions’ distance in most patients. Together, the pairwise MEM offers a framework for explaining iEEG functional connectivity and provides insight into how the brain’s structural connectome gives rise to large-scale activation patterns by promoting co-activation between connected structures.

Video segmentation using Maximum Entropy Model

2005 ◽  
Vol 6 (S1) ◽  
pp. 47-52
Author(s):  
Li-juan Qin ◽  
Yue-ting Zhuang ◽  
Yun-he Pan ◽  
Fei Wu
Keyword(s):  
Maximum Entropy ◽  
Video Segmentation ◽  
Maximum Entropy Model ◽  
Entropy Model
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