Machine Learning for Macroscale Ecological Niche Modeling - a Multi-Model, Multi-Response Ensemble Technique for Tree Species Management Under Climate Change

2018 ◽  
pp. 123-139
Author(s):  
Anantha M. Prasad
Keyword(s):  
Climate Change ◽  
Machine Learning ◽  
Tree Species ◽  
Ecological Niche ◽  
Ecological Niche Modeling ◽  
Niche Modeling ◽  
Ensemble Technique ◽  
Species Management

scholarly journals Tracking a Medically Important Spider: Climate Change, Ecological Niche Modeling, and the Brown Recluse (Loxosceles reclusa)

PLoS ONE ◽  
2011 ◽  
Vol 6 (3) ◽  
pp. e17731 ◽  
Author(s):  
Erin E. Saupe ◽  
Monica Papes ◽  
Paul A. Selden ◽  
Richard S. Vetter
Keyword(s):  
Climate Change ◽  
Ecological Niche ◽  
Ecological Niche Modeling ◽  
Niche Modeling ◽  
Loxosceles Reclusa

scholarly journals The fate of the Arctic seaweed Fucus distichus under climate change: an ecological niche modeling approach

2016 ◽  
Vol 6 (6) ◽  
pp. 1712-1724 ◽  
Author(s):  
Alexander Jueterbock ◽  
Irina Smolina ◽  
James A. Coyer ◽  
Galice Hoarau
Keyword(s):  
Climate Change ◽  
Ecological Niche ◽  
Ecological Niche Modeling ◽  
Niche Modeling ◽  
The Arctic ◽  
Modeling Approach ◽  
Fucus Distichus

Ecological niche modeling of coastal dune plants and future potential distribution in response to climate change and sea level rise

2013 ◽  
Vol 19 (8) ◽  
pp. 2524-2535 ◽  
Author(s):  
Gabriela Mendoza-González ◽  
M. Luisa Martínez ◽  
Octavio R. Rojas-Soto ◽  
Gabriela Vázquez ◽  
Juan B. Gallego-Fernández
Keyword(s):  
Climate Change ◽  
Sea Level Rise ◽  
Sea Level ◽  
Ecological Niche ◽  
Potential Distribution ◽  
Ecological Niche Modeling ◽  
Niche Modeling ◽  
Coastal Dune Plants ◽  
Future Potential ◽  
Dune Plants

scholarly journals Korarchaeota Diversity, Biogeography, and Abundance in Yellowstone and Great Basin Hot Springs and Ecological Niche Modeling Based on Machine Learning

PLoS ONE ◽  
2012 ◽  
Vol 7 (5) ◽  
pp. e35964 ◽  
Author(s):  
Robin L. Miller-Coleman ◽  
Jeremy A. Dodsworth ◽  
Christian A. Ross ◽  
Everett L. Shock ◽  
Amanda J. Williams ◽  
...  
Keyword(s):  
Machine Learning ◽  
Great Basin ◽  
Ecological Niche ◽  
Hot Springs ◽  
Ecological Niche Modeling ◽  
Niche Modeling

scholarly journals Geographic shifts in Aedes aegypti habitat suitability in Ecuador using larval surveillance data and ecological niche modeling: Implications of climate change for public health vector control

2019 ◽  
Vol 13 (4) ◽  
pp. e0007322 ◽  
Author(s):  
Catherine A. Lippi ◽  
Anna M. Stewart-Ibarra ◽  
M. E. Franklin Bajaña Loor ◽  
Jose E. Dueñas Zambrano ◽  
Nelson A. Espinoza Lopez ◽  
...  
Keyword(s):  
Public Health ◽  
Climate Change ◽  
Aedes Aegypti ◽  
Vector Control ◽  
Habitat Suitability ◽  
Ecological Niche ◽  
Ecological Niche Modeling ◽  
Niche Modeling ◽  
Surveillance Data

scholarly journals Climatic limits for the present European distribution of hornbeam (Carpinus betulus), with special reference to Ukraine

2018 ◽  
Author(s):  
Volodymyr Tytar
Keyword(s):  
Special Reference ◽  
Tree Species ◽  
Ecological Niche ◽  
Ecological Niche Modeling ◽  
Climatic Factors ◽  
Niche Modeling ◽  
Limiting Factor ◽  
Carpinus Betulus ◽  
Modeling Approach ◽  
The Common

In this study, we used a ecological niche modeling approach to detect the importance of diverse climatic parameters in controlling the distribution of forest tree species, exemplified by the common hornbeam (Carpinus betulus L.), with special reference to Ukraine from where digitized data on the species has been scarce. In Ukraine populations of this tree species are found on the edge of its home range and are exposed to extreme climate conditions. The main objectives of the present study were to model the European-wide ecological niche of the common hornbeam and investigate primary climatic factors that control the potential distribution of this tree in Ukraine. Using an ecological niche modeling approach, we consider having reliably modeled the European-wide bioclimatic niche of the common hornbeam for predicting the response of species geographical distribution to climate. Most contributing to the model was the mean monthly PET (potential evapotranspiration) of the coldest quarter, continentality and annual PET. In terms of the Most Limiting Factor, in Ukraine continentality is crucial throughout the majority of the country.

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