Agriculture Reference
In-Depth Information
climate matching include BIOCLIM122 Climate
Change Impact, Adaptation, and Mitigation in
Agriculture (Busby
1991
), CLIMEX (Sutherst
and Maywald
1985
), HABITAT (Walker and
Cocks
1991
), and WORLD. Climate matching
may be used for climate change impact assess-
ment by identifying those locations on the globe
with a current climate that is similar to the pre-
dicted future climate at the location of interest.
An analysis of the plant disease problems at the
matching locations based on disease distribution
maps made it possible to predict the future dis-
ease risk at the location of interest.
CLIMEX software can be used to generate dis-
tribution maps of insect species and to assess the
possible distributions of these insects in changing
climate (Sutherst and Maywald
1985
). It holds the
weather data for monthly long-term average maxi-
mum and minimum temperatures, rainfall, and rela-
tive humidity from 2031 meteorological stations
worldwide from 1931 to 1960. Additional weather
data can be added into CLIMEX meteorological
database from different meteorological stations.
CLIMEX can predict species potential distri-
bution through weather parameters of its current
habitat range or directly by the species biological
parameters such as minimum, maximum, and
optimum temperatures for development. On the
basis of biological parameters of the species,
CLIMEX generates a map for the potential geo-
graphical distribution of the species by counting
an ecoclimatic index (EI). EI is a numerical value
for climatic suitability and relative abundance of
the species. CLIMEX calculates EI from an
annual growth index, describing conditions favor-
able for population growth together with stress
factors that limit population growth during unfa-
vorable season in the following manner:
EI = [100/52
The temperature index consists of the lower
temperature threshold (DV0), the lower and upper
optimum temperatures (DV1 and DV2), and the
upper temperature threshold (DV3). Further, the
number of degree days (PDD) required to com-
plete a generation cycle is also used. Four param-
eters are used in the calculations of the moisture
index (MI); these are lower and upper soil mois-
ture thresholds (SM0 and SM3) and the lower
(SM1) and upper (SM2) bounds of optimum
range. Diapause index is composed of diapause
induction day length (DPD0), diapause induction
temperature (DPT0), diapause termination tem-
perature (DPT1), and diapause development days
(DPD). The stress indices used are heat stress
(HS), dry stress (DR), and wet stress (WS).
The ecoclimatic index (EI) values range from
0 to 100, describing climatic suitability of the
location for the species. At the EI value of 0, the
species cannot establish a viable population at
the location. Values over 20 indicate a very favor-
able climate for the species.
CLIMEX modeling software has been used to
predict the future distribution ranges of two cen-
tral European serious forest pest species, the nun
moth (
Lymantria monacha
) and the gypsy moth
(
L. dispar
).
7.18.3 Empirical Models
Empirical models based on long-term data on
pest incidence and weather variables can be used
to assess the likely impact of climate change on
pest status in a region.
Chander et al. (
2003
) have related the aphid
incidence on barley crop variety “DL-70” dur-
ing rabi season from 1985-1986 to 1999-2000
to weather parameters. There was appreciable
interannual variation in the aphid incidence on
barley, perhaps due to interannual climatic vari-
ability. The aphid population on barley exhib-
ited a declining trend with time. The aphid
population showed a negative relationship with
the January mean minimum temperature
(
r
= −0.37, Fig.
7.6
), while it was not related to
the February mean minimum temperature. The
February total rainfall and aphid population
(TIw × MIw × DIw)] × [(1 − CS/100)
(1 − HS/100)
52 W = 1 where TIw is the growth index counts
for weekly temperature index, MIw is the mois-
ture index, DIw is the diapause index, and w is the
week of the year. Each of the stress indices is cal-
culated on weekly basis and expressed as a sum
over the year as annual heat (HS), cold (CS), wet
(WS), and dry stress (DS) indices, all indicative of
the climatic requirements of the species.
(1 − DS/100)
(1 − WS/100)]
ʣ
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