R.W. Sutherst et al. Agriculture, Ecosystems and Environment 82 2000 303–319 315
Table 3 Vulnerability analysis of rice in Jakarta to climate change using the RatHopper model
Scenario Rice kg
Rats No. BPH 1000’s
Predators 100’s Bait cost
Insecticide Profit
Current climate 2 crops no pests
731 1095 11
42 19
731 3 crops no pests
740 1658 45
60 19
740 Baits 10 rats
1144 6
60 19
12 1132
Baits 10 rats 1611
5 1
0.4 8
175 1427
Spray 1000 BPH baits 10 rats×10 predators
1521 5
12 22
12 1509
Scenario +2
◦
C 2 crops no pests
505 1229 107
20 505
3 crops no pests 354 1860
36 145
20 354
Baits 10 rats 756
6 145
20 8
748 Baits 10 rats
1809 5
0.5 0.5
12 165
1632 Spray 1000 BPH baits 10
rats×10 predators 1353
6 64
23 16
1337
economic threshold proved to be a relatively robust and effective adaptation to climate change. However,
this relies on an appreciation of the correct cause of the changes in pest numbers and seasonal phenology,
otherwise changes in pest pressure could not be effec- tively interpreted. It also relies on the use of chemical
pesticides, some of which may not be sustainable for environmental reasons or due to the emergence of
resistant strains.
The Internet has the potential to communicate infor- mation on the effects of global change on pests to an
international audience and also to maintain collabora- tive links between members of an interest group. The
report from the rice-pest workshop Sutherst et al., 1999 is available from the IC-SEA Impacts Cen-
tre or the authors, and a summary can be viewed at http:www.icsea.or.idTrsep98.htm. It illustrates how
risks and management strategies can be designed and delivered in socio-economic terms for policymakers,
with communication through the Internet, targeting national laboratories in developing countries where
wider access is unavailable.
The group of participants now constitute a regional ‘interest group’ with the common aim of developing
and applying models to describe the population dy- namics and management of the rice pests. It provides
one possible model for a global pest network on global change research. The group collaborated by pooling
data and expertise to build a model that belongs to the group, while the DYMEX support team provides
archiving and documentation support to manage the software ‘version control’. However, a major con-
straint with the creation of networks is the question of funding the ongoing collaboration, even though it is
perceived by participants to be very cost-effective by adding great value to their current activities. This is
despite the recognition by agencies such as the World Bank that networks are potentially powerful tools in
national development http:www.vita.orgtechnet.
4. DYMEX modelling networks and workshops
The IGBP-GCTE global collaborative research pro- gram emphasises the development of global networks
and consortia to achieve its aims of relevant collabora- tive research Ingram et al., 1999. It relies heavily on
multidisciplinary workshops to define and implement agendas for global change research. DYMEX-based
Modelling Workshops http:www.ento.csiro.auresea- rchpestmgmtIPMModellingNetworkindex.htm are
one process being used to foster the development of collaborative, integrated approaches to estimates
of vulnerability to pests under global change. This can be achieved by developing regional and global
networks of interest groups around major pests and by training scientists from developing countries in a
partnership between GCTE and the Global Change System for Analysis Research and Training START
Sutherst et al., 1999. The networks jointly develop,
316 R.W. Sutherst et al. Agriculture, Ecosystems and Environment 82 2000 303–319
Table 4 Collation of data and functions for models as used in DYMEX modelling workshops. The reformatted example shows extracts from the
lifecycle, damage and control relationships of the rice-field rat R. argentiventer in southeast Asia Sutherst et al., 1999. Instructions to participants: Enter life-stages and processes into the proforma as necessary for a given species. Enter code and author name against each
process×lifestage, where data or functions can be provided. Complete a meta-data sheet for each set of your own data
R.W. Sutherst et al. Agriculture, Ecosystems and Environment 82 2000 303–319 317
test and apply models for use in impact assessment and design of strategies to adapt to change exam-
ples of which are given below. These can range in complexity from a model of a single species to more
complex, multi-species model similar to that seen in the DYMEX ‘RatHopper’ model mentioned above,
which links simple models of rice, rice-field rats, brown planthoppers and a generalist insect predator
of the hoppers.
4.1. Workshop and networking processes, and data sharing agreements
The workshops ideally last 3–5 days and start with sessions to clarify participants’ expectations of mod-
els in general and the objectives of the workshop in particular. This process defines the purpose and vi-
sion for the use of the model after the workshop and therefore focusses the model building effort on the
group’s needs. These are followed by an introduction to DYMEX software, and agreements on behaviour
adapted from Covey 1990 by Sutherst and Maywald 1998, data and model-sharing Ingram et al., 1999
and other intellectual property issues. This provides the groundwork to enable participants to address the
specific modelling issues, which are handled in later sessions. They cover model specifications; including
the lifecycles to be described, damage relationships and control methods; identification and collation of
data sets for both building the models and validating them against independent data; model formulation and
testing; analysis of model behaviour and exploration of management options. A final session addresses fu-
ture plans and possible projects, including the option of establishing a collaborative research network.
Research networks are facilitated, not only by shar- ing of software and workshop processes, but also by
sharing data and models. In order to make this pos- sible, it helps to have agreed formats for display of
meta-data, which summarize the raw data in a form that potential collaborators can see what topics and
data are available to the network. GCTE has devel- oped a number of meta-databases to support the crop
network in particular Ingram et al., 1999. These de- scribe data sets that are used to evaluate and to apply
simulation models. While suited to crop growth and yield trials, the formats do not lend themselves readily
to pest data and so need some modifications. In addi- tion, the primary demand in the GCTE networks ad-
dressing pests at present is to construct models of key pests that include temporal and spatial scales, and lev-
els of resolution that are appropriate for global change studies as opposed to detailed plot studies. Thus there
is a demand for a proforma to describe data sets needed for construction of models that are driven by environ-
mental conditions. A proforma for collating sources of data on lifecycle processes has been developed by
the Australian IPM modelling network see above and has been contributed to the GCTE pest network
Table 4. It consists of two layers of information, firstly, a table shown that identifies sources of infor-
mation on each process with a function if available, and secondly, meta-data sheets that describe each data
set.
5. Conclusions
