Model and scenario variations in predicted number of generations of Spodoptera litura Fab. on peanut during future climate change scenario

PLoS One. 2015 Feb 11;10(2):e0116762. doi: 10.1371/journal.pone.0116762. eCollection 2015.

Abstract

The present study features the estimation of number of generations of tobacco caterpillar, Spodoptera litura. Fab. on peanut crop at six locations in India using MarkSim, which provides General Circulation Model (GCM) of future data on daily maximum (T.max), minimum (T.min) air temperatures from six models viz., BCCR-BCM2.0, CNRM-CM3, CSIRO-Mk3.5, ECHams5, INCM-CM3.0 and MIROC3.2 along with an ensemble of the six from three emission scenarios (A2, A1B and B1). This data was used to predict the future pest scenarios following the growing degree days approach in four different climate periods viz., Baseline-1975, Near future (NF) -2020, Distant future (DF)-2050 and Very Distant future (VDF)-2080. It is predicted that more generations would occur during the three future climate periods with significant variation among scenarios and models. Among the seven models, 1-2 additional generations were predicted during DF and VDF due to higher future temperatures in CNRM-CM3, ECHams5 & CSIRO-Mk3.5 models. The temperature projections of these models indicated that the generation time would decrease by 18-22% over baseline. Analysis of variance (ANOVA) was used to partition the variation in the predicted number of generations and generation time of S. litura on peanut during crop season. Geographical location explained 34% of the total variation in number of generations, followed by time period (26%), model (1.74%) and scenario (0.74%). The remaining 14% of the variation was explained by interactions. Increased number of generations and reduction of generation time across the six peanut growing locations of India suggest that the incidence of S. litura may increase due to projected increase in temperatures in future climate change periods.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Arachis*
  • Climate Change*
  • Models, Statistical*
  • Spodoptera*
  • Temperature
  • Time Factors
  • Uncertainty

Grants and funding

The work was supported by grants from the Indian Council of Agricultural Research (ICAR) in the form of National Initiative on Climate Resilient Agriculture (NICRA), http://nicra-icar.in/. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.