- Record: found
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Predicting Spatial Distribution of Key Honeybee Pests in Kenya Using Remotely Sensed and Bioclimatic Variables: Key Honeybee Pests Distribution Models
David Makori ,
Ayuka Fombong ,
Elfatih Abdel-Rahman ,
Kiatoko Nkoba ,
Juliette Ongus ,
Janet Irungu ,
Gladys Mosomtai ,
Sospeter Makau ,
Onisimo Mutanga ,
John Odindi ,
Suresh Raina ,
Tobias Landmann
March 2017
February 28 2017
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Most cited references45
- Record: found
- Abstract: not found
- Article: not found
TIMESAT—a program for analyzing time-series of satellite sensor data
Per J Jonsson, Lars Eklundh (2004)
- Record: found
- Abstract: not found
- Article: not found
An improved approach for predicting the distribution of rare and endangered species from occurrence and pseudo-absence data
Robin Engler, Antoine Guisan, Luca Rechsteiner (2004)
- Record: found
- Abstract: not found
- Article: not found
A null-model for significance testing of presence-only species distribution models
Niels Raes, Hans ter Steege (2007)