scholarly journals Actual and Potential Distribution of Five Regulated Avocado Pests Across Mexico, Using the Maximum Entropy Algorithm

2017 ◽  
Vol 100 (1) ◽  
pp. 92-100 ◽  
Author(s):  
Andrea Luna ◽  
Víctor López-Martínez ◽  
Nidia Bélgica Pérez-De la O ◽  
Daniel Jiménez-García ◽  
Robert W. Jones ◽  
...  
Keyword(s):  
Maximum Entropy ◽  
Potential Distribution ◽  
Avocado Pests

Using maximum entropy to predict the potential distribution of an invasive freshwater snail

2016 ◽  
Vol 61 (4) ◽  
pp. 457-471 ◽  
Author(s):  
Monica Papeş ◽  
John E. Havel ◽  
M. Jake Vander Zanden
Keyword(s):  
Maximum Entropy ◽  
Potential Distribution ◽  
Freshwater Snail

A study on Ptyas doriae (Boulenger, 1888) with comments on the status of Ptyas hamptoni (Boulenger, 1900) (Squamata: Colubridae: Colubrinae)

Zootaxa ◽  
2018 ◽  
Vol 4457 (4) ◽  
pp. 537
Author(s):  
ASEM BIPIN MEETEI ◽  
SUNANDAN DAS ◽  
PATRICK D. CAMPBELL ◽  
SUJOY RAHA ◽  
PROBHAT BAG
Keyword(s):  
Maximum Entropy ◽  
Potential Distribution ◽  
Southern China ◽  
Original Description ◽  
Colour Morph ◽  
Northeastern India ◽  
Maximum Entropy Modeling ◽  
The Status ◽  
Intrapopulational Variation

Ptyas doriae is a rare snake in northeastern India, Myanmar and southern China. The original description and subsequent accounts of this species were all very brief. We studied most of the available specimens of this species and on this basis we provide a detailed redescription of the species. We give an account of intrapopulational variation in scalation characters and colouration and we also report on a previously undescribed colour morph from Manipur, India. We have examined the holotype of Ptyas hamptoni and found that characters used to distinguish it from P. doriae are inadequate and therefore we herein synonymize the former with the latter species. We also predict the potential distribution of P. doriae by using Maximum Entropy modeling.

Potential distribution of Mexican primates: modeling the ecological niche with the maximum entropy algorithm

Primates ◽  
2011 ◽  
Vol 52 (3) ◽  
pp. 261-270 ◽  
Author(s):  
Francisca Vidal-García ◽  
Juan Carlos Serio-Silva
Keyword(s):  
Maximum Entropy ◽  
Ecological Niche ◽  
Potential Distribution

Predicting the potential distribution of main malaria vectors Anopheles stephensi, An. culicifacies s.l. and An. fluviatilis s.l. in Iran based on maximum entropy model

Acta Tropica ◽  
2017 ◽  
Vol 169 ◽  
pp. 93-99 ◽  
Author(s):  
Kamran Pakdad ◽  
Ahmad Ali Hanafi-Bojd ◽  
Hassan Vatandoost ◽  
Mohammad Mehdi Sedaghat ◽  
Ahmad Raeisi ◽  
...  
Keyword(s):  
Maximum Entropy ◽  
Potential Distribution ◽  
Anopheles Stephensi ◽  
Malaria Vectors ◽  
Maximum Entropy Model ◽  
Entropy Model

scholarly journals Modeling the potential distribution of three lichens of the Xanthoparmelia pulla group (Parmeliaceae, Ascomycota) in Central Europe

2015 ◽  
Vol 84 (4) ◽  
pp. 431-438 ◽  
Author(s):  
Katarzyna Szczepańska ◽  
Daniel Pruchniewicz ◽  
Maria Kossowska
Keyword(s):  
Czech Republic ◽  
Maximum Entropy ◽  
Geographical Distribution ◽  
Central Europe ◽  
Potential Distribution ◽  
Climatic Conditions ◽  
The Czech Republic ◽  
Bioclimatic Variables ◽  
Maxent Modeling ◽  
Northeastern Poland

The paper presents models of potential geographical distribution of <em>Xanthoparmelia delisei</em>, <em>X. loxodes</em>, and <em>X. verruculifera</em> in Central Europe. The models were developed with MaxEnt (maximum entropy algorithm) based on 224 collection localities and bioclimatic variables. The applied method enabled to identify the areas where climatic conditions are the most suitable for modeled species outside their known localities. According to obtained model, high potential distribution of the <em>X. delisei</em> and <em>X. loxodes</em> was found in the northern and northeastern Poland, when areas most suitable for <em>X. verruculifera</em> were placed in the south, especially in the Carpathians. Model also suggests that potential distribution of <em>X. delisei</em> could be wider than known data on its occurrence and extend to Lithuania, Belarus and the Czech Republic. MaxEnt modeling of <em>X. loxodes</em> showed the widest potential distribution for this species in Central Europe with the best regions in Lithuania. Potential distribution in all models was strongly influenced by precipitation-related variables. All the modelled species prefer areas where precipitation in the coldest quarter is very low.

scholarly journals Potential distribution model of Leontochir ovallei using remote sensing data

2019 ◽  
pp. 59
Author(s):  
S. Payacán ◽  
F.D. Alfaro ◽  
W. Pérez-Martínez ◽  
I. Briceño-de-Urbaneja
Keyword(s):  
Maximum Entropy ◽  
Potential Distribution ◽  
Remote Sensing Data ◽  
Local Scale ◽  
Distribution Model ◽  
Natural Distribution ◽  
Coastal Desert ◽  
Restricted Distribution ◽  
Distribution Ranges ◽  
Coastal Fog

<p>Predicting the potential distribution of short-lived species with a narrow natural distribution range is a difficult task, especially when there is limited field data. The possible distribution of <em>L. ovallei</em> was modeled using the maximum entropy approach. This species has a very restricted distribution along the hyperarid coastal desert in northern Chile. Our results showed that local and regional environmental factors define its distribution. Changes in altitude and microhabitat related to the landforms are of critical importance at the local scale, whereas cloud cover variations associated with coastal fog was the principal factor determining the presence <em>of L. ovallei</em> at the regional level. This study verified the value of the maximum entropy in understanding the factors that influence the distribution of plant species with restricted distribution ranges.</p>

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