Temperature Impacts the Development and Survival of Common Cutworm (Spodoptera litura): Simulation and Visualization of Potential Population Growth in India under Warmer Temperatures through Life Cycle Modelling and Spatial Mapping.

The common cutworm, Spodoptera litura, has become a major pest of soybean (Glycine max) throughout its Indian range. With a changing climate, there is the potential for this insect to become an increasingly severe pest in certain regions due to increased habitat suitability. To examine this possibility, we developed temperature-based phenology model for S. litura, by constructing thermal reaction norms for cohorts of single life stages, at both constant and fluctuating temperatures within the ecologically relevant range (15-38°C) for its development. Life table parameters were estimated stochastically using cohort updating and rate summation approach. The model was implemented in the geographic information system to examine the potential future pest status of S. litura using temperature change projections from SRES A1B climate change scenario for the year 2050. The changes were visualized by means of three spatial indices demonstrating the risks for establishment, number of generations per year and pest abundance according to the temperature conditions. The results revealed that the development rate as a function of temperature increased linearly for all the immature stages of S. litura until approximately 34-36°C, after which it became non-linear. The extreme temperature of 38°C was found lethal to larval and pupal stages of S. litura wherein no development to the next stage occurred. Females could lay no eggs at the extreme low (15°C) and high (> 35°C) test temperatures, demonstrating the importance of optimum temperature in determining the suitability of climate for the mating and reproduction in S. litura. The risk mapping predicts that due to temperature increase under future climate change, much of the soybean areas in Indian states like Madhya Pradesh, Maharashtra and Rajasthan, will become suitable for S. litura establishment and increased pest activity, indicating the expansion of the suitable and favourable areas over time. This has serious implication in terms of soybean production since these areas produce approximately 95% of the total soybeans in India. As the present model results are based on temperature only, and the effects of other abiotic and biotic factors determining the pest population dynamics were excluded, it presents only the potential population growth parameters for S. litura. However, if combined with the field observations, the model results could certainly contribute to gaining insight into the field dynamics of S. litura

Temperature-dependent senescence rates (1/ day) for adults of <i>S</i>. <i>litura</i>.

<p>Female(a) and Male (b). Fitted curves: Modified Sharpe and DeMichele model for both sexes. The upper and lower 95% confidence intervals of the model are indicated. Bars represent standard deviation of the mean.</p

Temperature-dependent mortality rates of immature life stages S. litura.

<p>Egg (a), Larva (b) and Pupa (c). Fitted curves: Wang model for all immature stages. The upper and lower 95% confidence intervals of the model are indicated. Markers are observed means, bars represent standard deviation.</p

Comparisons between the developmental effects of diurnal temperature fluctuations predicted from models based on thermal reaction norms designed for constant temperatures with those observed in fluctuating temperatures.

<p>Comparisons between the developmental effects of diurnal temperature fluctuations predicted from models based on thermal reaction norms designed for constant temperatures with those observed in fluctuating temperatures.</p

Temperature-dependent reproduction of <i>S</i>. <i>litura</i>.

<p>Total egg production curve, fitted function: exponential polynomial model (a); and Age-related oviposition rate, fitted curve: Gamma distribution function (b). The upper and lower 95% confidence intervals of the model are indicated. The dots are observed data points.</p

Life table parameters of <i>S</i>. <i>litura</i> estimated at six constant temperatures.

<p>Intrinsic rate of natural increase (a), Net reproduction rate (b), Gross reproductive rate (c), Mean generation time (d), Finite rate of increase (e), and Doubling time (f).</p

Change in number of generations per year of <i>S</i>. <i>litura</i> in soybean growing areas of India based on generation index (GI).

<p>Current climatic conditions (a), Future climatic conditions (b), and Absolute change in GI (c). Economic damage is most likely to occur in the regions with generation index values > 7.0.</p

Scheme of model implementation for estimating temperature-dependent <i>S</i>. <i>litura</i> population growth.

<p>Scheme of model implementation for estimating temperature-dependent <i>S</i>. <i>litura</i> population growth.</p

Distribution of the cumulative development/ senescence time frequencies for different life stages of <i>S</i>. <i>litura</i> at various constant temperatures in laboratory (Fitted function: logit model for all stages).

<p>¹‘a’ represents the intercepts at respective temperatures</p><p>Distribution of the cumulative development/ senescence time frequencies for different life stages of <i>S</i>. <i>litura</i> at various constant temperatures in laboratory (Fitted function: logit model for all stages).</p

Estimated parameters of the four parameter Sharpe and DeMichele model fitted to the temperature-dependent development rate of immature life stages of <i>S</i>. <i>litura</i>.

<p>Estimated parameters of the four parameter Sharpe and DeMichele model fitted to the temperature-dependent development rate of immature life stages of <i>S</i>. <i>litura</i>.</p