Assessing the risk of mango quarantine pest Deanolis sublimbalis Snellen under different climate change scenarios

Abstract

Considering the quarantine importance of the red-banded mango caterpillar, Deanolis sublimbalis (Crambidae: Lepidoptera), studies were carried out to predict the impact of climate change on its geographical distribution using the ecological niche modeling. Predictions were made based on the analysis of the relationship between occurrence points of D. sublimbalis and the corresponding current and future climate data of the study area, which was retrieved from the worldclim database. Spatial analysis software DIVA-GIS was used for visualization of the maps. The maximum entropy algorithm provided reasonable estimates of the species range in respect of discrimination of suitable and unsuitable areas for its occurrence in both present and future climatic conditions. The model provided a good fit for species distribution with a high value of area under the curve (0.971). Jackknife test indicated temperature seasonality to be the most important bioclimatic variable determining the potential geographical distribution of D. sublimbalis. The model predicted higher suitability areas for the pest occurrence in eastern parts of Andhra Pradesh, coastal regions of Orissa, southern parts of West Bengal, and some parts of Tripura. In future climate scenarios of 2030, 2050, 2070, and 2080, model-predicted relative increase in its distribution. Prediction of likely changes in the pest distribution with climate change will be useful in formulating effective management strategies against mango fruit borer.

Diagnosis and potential invasion risk of Thrips parvispinus under current and future climate change scenarios

“…1 ). To reduce the uncertainty and sample biasness, duplicate records and neighboring occurrence points were removed by ‘spThin’ R package as previously described by Baradevanal et al (2021) .…”

“…Current data of 19 bioclimatic variables with a resolution at 2.5 m were retrieved from World clim data base version 1.4 ( ). To meet the requirement of the study, the data were further processed and muticollinearity among the bioclimatic variables was verified as suggested by Baradevanal et al (2021) . Highly correlated bio-climatic variables were determined by using Pearson correlation coefficient through pair-wise comparisons.…”

“…Whereas values 0.5 and 0.7 indicate poor model performance, 0.7 to 0.9 indicates reasonable performance, and >0.9 indicates high model performance ( Pearson et al, 2007 ). Predicted distribution maps were processed as per the procedure described by Baradevanal et al (2021) .…”

“…ENM has been used widely in biological invasion, conservation biology, biological responses to climate change, and various aspects of ecological and evolutionary biological research ( Peterson, Bauer & Mills, 2004 ). Recently, mapping of the potential distribution of agriculturally important insect pests using maximum entropy modelling is extensively being used for suitability assessment and risk zoning of invasive species ( Wang et al, 2020 ; Baloch et al, 2020 ; Baradevanal et al, 2021 ).…”

Occurrence and spread of invasive thrips <i>Thrips parvispinus</i> (Karny) in north India

“…These observations corroborate with those observed in Southeast Asian countries (Sartiami and Mound, 2013;Johari, 2015). Since this pest is new to the Indian subcontinent, it is very difficult to predict its spread within India, probable reasons for its rapid spread might be the unrestricted movement of agricultural commodities and planting materials from infested nurseries (Shashank et al, 2016); availability of host plants around the year might be other reason (large scale cultivation of solanaceous and papaya crops); and subtropical weather conditions favour this (Sartiami and Mound, 2013;Johari, 2015;Baradevanal et al, 2021;Timmanna et al, 2022). The innate ability of pests viz., higher reproduction potential and aggressive feeding behaviour of T. parvispinus, might favour its multiplication, establishment, and further spread.…”