email   Email Us: phone   Call Us: +1 (914) 407-6109   57 West 57th Street, 3rd floor, New York - NY 10019, USA

Lupine Publishers Group

Lupine Publishers

  Submit Manuscript

ISSN: 2637-4676

Current Investigations in Agriculture and Current Research

Research Article(ISSN: 2637-4676)

A Bioclimate-Based Maximum Entropy Model for Comperiella calauanica Barrion, Almarinez & Amalin (Hymenoptera: Encyrtidae), Parasitoid of Aspidiotus rigidus Reyne, in the Philippines

Volume 8 - Issue 4

Billy Joel M Almarinez1,2*, Mary Jane A Fadri3, Richard Lasina4, Thaddeus M Carvajal1,2,5, Kozo Watanabe1,2,5, Mary Angelique A Tavera1,2, Jesusa C Legaspi6 and Divina M Amalin1,2

  • Author Information Open or Close
    • 1Center for Natural Science and Environmental Research, De La Salle University, Philippines
    • 2Biology Department, De La Salle University, Philippines
    • 3Biology Department, Romblon State University, Philippines
    • 44Philippine Coconut Authority-Zamboanga Research Center, Philippines
    • 5Department of Civil and Environmental Engineering, Ehime University, Matsuyama, Japan
    • 6Center for Medical, Agricultural and Veterinary Entomology, Department of Agriculture-Agricultural Research Service, USA

    *Corresponding author:Billy Joel M Almarinez, Biological Control Research Unit, Center for Natural Science and Environmental Research, De La Salle University, Taft Avenue, Manila, Philippines

Received:June 15, 2020;   Published: June 26, 2020

DOI: 10.32474/CIACR.2020.08.000296

Full Text PDF

To view the Full Article   Peer-reviewed Article PDF


Background:Comperiellacalauanica Barrion, Almarinez & Amalin (Hymenoptera: Encyrtidae) is a host-specific endoparasitoid and effective biological control agent of Aspidiotus rigidus Reyne (Hemiptera: Diaspididae), whose outbreak in 2010 to 2015 severely threatened the coconut industry in the Philippines. Using the maximum entropy (MaxEnt) algorithm, we developed a Species Distribution Model (SDM) for calauanica based on 19 bioclimatic variables, using occurrence data obtained mostly from field surveys conducted in A. rigidus-infested areas in Luzon Island from 2014 to 2016.

Results: The calculated AUC values for the model were very high (0.966, standard deviation=0.005), indicating the model’s high predictive power. Precipitation seasonality was found to have the highest relative contribution to model development. Response curves produced by MaxEnt suggested the positive influence of mean temperature of the driest quarter, and negative influence of precipitation of the driest and coldest quarters on habitat suitability.

Conclusion: Given that calauanicahas been found to always occur with A. rigidus in Luzon Island due to high host-specificity, the SDM for the parasitoid may also be considered and used as a predictive model for its host. This was confirmed through field surveys conducted between late 2016 and early 2018, which found and confirmed the occurrence of A. rigidusin three areas predicted by the SDM to have moderate to high habitat suitability or probability of occurrence of C. calauanica: Zamboanga City in Mindanao; Isabela City in Basilan Island; and Tablas Island in Romblon. This validation in the field demonstrated the utility of the bioclimate-based SDM for C. calauanicain predicting habitat suitability or probability of occurrence of A. rigidus in the Philippines.

Keywords: Maximum Entropy; Species Distribution Modeling; Comperiella Calauanica; Aspidiotus Rigidus; Pest Invasion Forecasting

Abstract| Introduction| Materials and Methods| Results and Discussion| Conclusion| Acknowledgement| Conflict of Interest| References|