Lateral Transmission of Yeast Symbionts Among Lucanid Beetle Taxa

To deepen understanding the evolutionary process of lucanid–yeast association, the lateral transmission process of yeast symbionts among stag beetle genera Platycerus and Prismognathus around the border between Japan and South Korea was estimated based on molecular analyses and species distribution modelings. Phylogenetic analyses were based on yeast ITS and IGS sequences and beetle COI sequences using Prismognathus dauricus from the Tsushima Islands and Pr. angularis from Kyushu, Japan, as well as other sequence data from our previous studies. The range overlap based on the species distribution model (SDM) and differentiation in ecological space were analyzed. Based on the IGS sequences, Clade II yeast symbionts were shared by Platycerus hongwonpyoi and Pr. dauricus in South Korea and the Tsushima Islands, and Platycerus viridicuprus in Japan. Clade III yeasts were shared by Pr. dauricus from the Tsushima Islands and Pr. angularis in Japan. During the Last Interglacial period when the land bridge between Japan and the Korean Peninsula existed, range overlap was predicted to occur between Pl. viridicuprus and Pr. dauricus in Kyushu and between Pr. dauricus and Pr. angularis in Kyushu and the Tsushima Islands. The ecological space of Pl. hongwonpyoi was differentiated from that of Pl. viridicuprus and Pr. angularis. We demonstrated the paleogeographical lateral transmission process of Scheffersomyces yeast symbionts among lucanid genera and species: putative transmission of yeasts from Pr. dauricus to Pl. viridicuprus in Kyushu and from Pr. angularis to Pr. dauricus in Kyushu or the Tsushima Islands. We also found that the yeast symbionts are likely being replaced in Pr. dauricus on the Tsushima Islands. We present novel estimates of the lateral transmission process of microbial symbionts based on phylogenetic, SDM and environmental analyses among lucanid beetles.

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Mapping National Plant Biodiversity Patterns in South Korea with the MARS Species Distribution Model

PLoS ONE ◽

10.1371/journal.pone.0149511 ◽

2016 ◽

Vol 11 (3) ◽

pp. e0149511 ◽

Cited By ~ 10

Author(s):

Hyeyeong Choe ◽

James H. Thorne ◽

Changwan Seo

Keyword(s):

South Korea ◽

Species Distribution ◽

Species Distribution Model ◽

Distribution Model ◽

Plant Biodiversity ◽

Biodiversity Patterns

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A Robust Prediction Model for Species Distribution Using Bagging Ensembles with Deep Neural Networks

Remote Sensing ◽

10.3390/rs13081495 ◽

2021 ◽

Vol 13 (8) ◽

pp. 1495

Author(s):

Jehyeok Rew ◽

Yongjang Cho ◽

Eenjun Hwang

Keyword(s):

Neural Networks ◽

Species Distribution ◽

Best Practice ◽

Deep Neural Networks ◽

Species Distribution Models ◽

Species Distribution Model ◽

Environmental Data ◽

Distribution Model ◽

Distribution Models ◽

Robust Prediction

Species distribution models have been used for various purposes, such as conserving species, discovering potential habitats, and obtaining evolutionary insights by predicting species occurrence. Many statistical and machine-learning-based approaches have been proposed to construct effective species distribution models, but with limited success due to spatial biases in presences and imbalanced presence-absences. We propose a novel species distribution model to address these problems based on bootstrap aggregating (bagging) ensembles of deep neural networks (DNNs). We first generate bootstraps considering presence-absence data on spatial balance to alleviate the bias problem. Then we construct DNNs using environmental data from presence and absence locations, and finally combine these into an ensemble model using three voting methods to improve prediction accuracy. Extensive experiments verified the proposed model’s effectiveness for species in South Korea using crowdsourced observations that have spatial biases. The proposed model achieved more accurate and robust prediction results than the current best practice models.

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