scholarly journals A Maximum Entropy Model Predicts the Potential Geographic Distribution of Sirex noctilio

Forests ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 175
Author(s):  
Xueting Sun ◽  
Qiang Xu ◽  
Youqing Luo

Sirex noctilio, the Sirex woodwasp, is an invasive pest that causes significant economic damage to native and commercial conifer stands through the introduction of a fungal wood decay pathogen. We combined the latitudes and longitudes of S. noctilio distribution points with historical climate data to predict its potential global distribution using a maximum entropy model implemented in the Maxent software. The annual mean temperature, the mean temperature of the warmest quarter, and the precipitation of the wettest month were important meteorological factors that affected the predictions, probably because they have a strong effect on the development of S. noctilio. Our predictions cover the most recent occurrence sites of S. noctilio in China. We predict that suitable habitats for S. noctilio are currently concentrated between 30° N to 60° N and 25° S to 55° S on the world map. All continents except for Antarctica contain suitable areas for S. noctilio, and such areas account for approximately 26% of the total area of these six continents. Predictions for 2050 and 2070 show that global climate change will affect the distribution of S. noctilio. With a decrease in carbon dioxide emissions, areas of moderate to high habitat suitability for S. noctilio will increase; with an increase in emissions, these areas will decrease.

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Arian Ashourvan ◽  
Preya Shah ◽  
Adam Pines ◽  
Shi Gu ◽  
Christopher W. Lynn ◽  
...  

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.


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

2019 ◽  
Vol 677 ◽  
pp. 281-298 ◽  
Author(s):  
Narges Kariminejad ◽  
Mohsen Hosseinalizadeh ◽  
Hamid Reza Pourghasemi ◽  
Anita Bernatek-Jakiel ◽  
Giandiego Campetella ◽  
...  

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