419Temperature-Based Phenology
Modeling and GIS-Based
Risk Mapping: A Tool for
Forecasting Potential Changes
in the Abundance of Mealybug
Phenacoccus solenopsis Tinsley
(Hemiptera: Pseudococcidae)
Babasaheb B. Fand, Henri EZ Tonnang, Mahesh
Kumar, Ankush L. Kamble and SK Bal
A. K. Chakravarthy (ed.), New Horizons in Insect Science: Towards Sustainable Pest Management,
DOI 10.1007/978-81-322-2089-3_37, © Springer India 2015
B. B. Fand () · M. Kumar · A. L Kamble · SK Bal
National Institute of Abiotic Stress Management (ICAR),
Malegaon, Baramati, Pune, Maharashtra 413115, India
e-mail: [email protected]
H. EZ Tonnang
Crop Management and Production Systems Division,
International Potato Center (CIP), Lima 12, Peru
Abstract
Phenacoccus solenopsis Tinsley (Hemiptera: Pseudococcidae) is a highly
invasive and a polyphagous pest of worldwide importance. Its recent out-
break and rapid spread in Indian cotton growing belt caused large scale
devastation. A study was undertaken with a basic assumption that the fu-
ture distribution and abundance of P. solenopsis will be affected seriously
by temperature alterations due to global climate change, which might
further aggravate the yield losses. The population growth potential of P.
solenopsis was estimated at six constant temperatures ranging from 15 to
40 °C. The phenology models established using best fitting functions in a
rate summation and cohort up-dating approach were employed in a geo-
graphic information system for mapping population growth potentials ac-
cording to real-time or interpolated temperature data, for both current and
future climate to predict the impact of climate change. The risks for popu-
lation establishment and survival, average numbers of generations and po-
tential population increase/year were computed using interpolated daily
minimum and maximum temperatures at a spatial resolution of 10 arc
minutes obtained from worldclim database (www.worldclim.org). The re-
al-time weather station data from two selected locations across India were
used to analyze within-year variation of pest population increase due to
seasonal climate fluctuations. The model predicted favorable temperature
range for P. solenopsis development, survival, and reproduction within a