Agriculture Reference
In-Depth Information
wheat. A simulation by the same authors applying
different climate change scenarios showed uni-
form increases in average pesticide costs for
corn, soybeans, cotton, and potatoes and mixed
results for wheat.
pest-induced yield losses under global warming.
However, maize productivity also depicted reduc-
tion even without pest stress under climate
change, indicating that despite reduction in pest
stress, crop productivity as such may be adversely
affected by global warming.
Climate change impact assessment through
coupled rice brown plant hopper (BPH) InfoCrop
model, in the light of the projected climate
change scenario for Indian subcontinent, showed
a decline in BPH population of 3.5 % by 2020
and of 9.8-14.0 % by 2050, during the rainy sea-
son at New Delhi, while the pest population
exhibited only a small decline of 2.1-3.5 % dur-
ing winter at Aduthurai, Tamil Nadu, even by
2050. Simulation attributed the decline in BPH
population to reduction in fecundity and survival.
Concomitant to its population decline, the BPH-
induced yield loss also indicated a declining
trend with temperature rise. However, the study
considered the effect of only CO
2
and tempera-
ture rise on the BPH population and crop yield
and not that of probable changes in the feeding
rate and adaptive capacity of the pest.
The impact of climate change on pink borer,
Sesamia inferens
, population, and crop-pest
interaction was analyzed through coupled
InfoCrop model. A rise of 0.5-1.0 °C tempera-
ture showed a small effect on various pest devel-
opmental stages, but a further increase had a
signifi cant adverse effect on them. In accordance
with climate change projections for Indian sub-
continent during kharif season, the study indi-
cated that the population of
S. inferens
might
decline to the extent of 5.82-22.8 % by 2020 and
19.01-42.74 % by 2050. Following decline in
pest population, yield loss due to
S. inferens
also
revealed a declining trend with temperature rise.
7.18
Modeling Approaches
Impact of climate change would depend upon on
complex interactions of climatic and biological
factors with technological and socioeconomic
changes that are diffi cult to predict. Therefore,
these interactions are not amenable to qualitative
analyses. Hence, quantitative (modeling)
approaches, which allow investigating multiple
scenarios and interactions simultaneously, will
become more important for the impact assess-
ment (Coakley and Scherm
1996
). Sutherst et al.
(
1996
) have given a framework for such model-
based assessment of impacts of climate change.
Some of these approaches are discussed here.
7.18.1 InfoCrop Models
InfoCrop-maize, coupled with holometabolous
population dynamics model, was used to simu-
late population dynamics of maize stem borer,
Chilo partellus
, as well as crop-pest interactions.
Maize stem borer acts as a stand reducer and
causes loss of leaf area, leaf weight, stem weight,
and panicle weight to the crop. Larva being the
damaging stage of the pest, larval population
from population dynamics model was linked to
the processes of leaf area, leaf weight, stem
weight, and ear weight in the crop model.
Depending upon larval population and feeding
rate of a larva, these crop growth processes were
affected. The coupled model was calibrated and
validated with fi eld experimental data on larval
population and the corresponding maize yield.
Validated model was used to simulate effect of
0.5-3.0 °C rise in both maximum and minimum
temperatures compared to the ambient conditions
on pest dynamics as well as crop-pest interac-
tions. Simulation of pest dynamics showed a
decline in the pest severity thereby reducing the
7.18.2 Climate Matching
Climate matching involves the calculation of a
“match index” to quantify similarity in the cli-
mate between two or more locations. The match
index is based on variables such as monthly mini-
mum and maximum temperatures, precipitation,
and evaporation rates. Software packages for
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