Cj. Swanton et Sd. Murphy, WEED SCIENCE BEYOND THE WEEDS - THE ROLE OF INTEGRATED WEED MANAGEMENT (IWM) IN AGROECOSYSTEM HEALTH, Weed science, 44(2), 1996, pp. 437-445
Integrated weed management (IWM) research has focused on how crop yiel
ds and weed interference are affected by changes in management, e.g.,
tillage, herbicide application timing and rates, cover crops, and plan
ting patterns, Acceptance of IWM will depend on recommendation of spec
ific strategies that manage weeds and maintain crop productivity; such
research will and should continue, However, IWM needs to move from a
descriptive to a predictive phase if long-term strategies are to be ad
opted, Linking management changes with crop-weed modeling that include
s such components as weed population dynamics and the ecophysiological
basis of competition will help predict future weed problems and solut
ions and the economic risks and benefits of intervention, Predictive a
pproaches would help incorporate IWM into models of the processes that
occur in agricultural systems at wider spatial and temporal scales, i
.e., in agroecosystems comprised of the interactions among organisms (
including humans) and the environment, It is at these larger scales th
at decisions about management are initiated and where questions about
the long-term consequences and constraints of IWM and agriculture are
often asked, These questions can be addressed by agroecosystem health,
an approach that integrates biophysical, social, and economic concern
s and recognizes that agriculture is part of a world with many complex
subsystems and interactions, Indicators are used to examine the statu
s of an agroecosystem, e.g., whether or not it contains all that is ne
cessary to continue functioning, Indicators include soil quality, crop
productivity, and water quality; all of these are related to the rati
onale of IWM, hence IWM can he linked to agroecosystem health, Ancilla
ry effects of using IWM relate to other indicators such as diversity a
nd energy efficiency, Linking IWM to agroecosystem health has at least
two benefits: (1) predictive models within IWM can be incorporated in
to larger agroecosystem models to explore hitherto unforseen problems
or benefits of IWM, and (2) the relevance and benefits of IWM should b
ecome clearer to the public and government agencies who otherwise migh
t not examine how IWM promotes many of the larger social, economic and
environmental goals being promulgated.