ing or supplemented biocontrol agents are more effective.
Several factors have limited the adop- tion of classical biological weed control in agronomic crops, including limited host spectrum, lack of consistency and slow or inadequate weed suppression (Kennedy and Kremer, 1996). A few bioherbicides have been successfully marketed, typi- cally in systems where no conventional herbicides are available for a specific weed problem (Boyetchko, 1997). Collego™ is a commercial formulation of the fungus Col- letotrichum gloeosporioides used to control northern jointvetch (Aeschynomene vir- ginica) in rice and soybean (Bowers, 1986).
Future success in this area lies in enhanc- ing the effectiveness of pathogens through genetic manipulation or enhanced delivery systems (Hallett, 2005).
The conservation approach to biologi- cal control is a fundamental component of ecological weed management systems.
The ability of a soil to suppress weeds is enhanced by adopting practices that enhance soil biological activity (Kennedy, 1999; Kremer and Li, 2003). Another form of biological control that influences weed densities within agronomic fields is seed predation (Marino et al., 2005; Mauchline et al., 2005). The relative importance of vertebrate and invertebrate predators var- ies among cropping systems and the activ- ity of predators varies throughout the year (Westerman et al., 2003; Mauchline et al., 2005). Westerman et al. (2005) reported that velvetleaf seed losses due to predation were nearly twice as great in a 4-year rotation system than in a 2-year rotation. Mauchline et al. (2005) concluded that to fully capture benefits of weed seed predation the primary predators must be identified and produc- tion practices be implemented that maxi- mize the activity of these predators at the time of seed shed.
Mechanical control
Mechanical removal or disruption of weeds was the primary tool used to manage weeds from the development of agriculture until the introduction of modern herbicides in the 1950s. Some form of soil disturbance
remains a component of virtually all crop- ping systems. Mechanical weed control tactics can be divided into two broad strate- gies: (i) pre-plant tillage, which is used to prepare a seedbed and which eliminates existing weeds to provide the crop with an even start with weeds; and (ii) post-plant tillage, which is used to kill weeds that emerge after crop planting.
Weed communities are influenced by tillage through changes in the soil environ- ment, changes in seed distribution in the soil, effects on seed predators and effects on weed control practices (Brust and House, 1988; Buhler, 1995). Tillage for seedbed preparation can reduce densities of annual weed populations, especially if planting is delayed to allow weed seed germination prior to final seedbed preparation (Gunsolus, 1990; Buhler and Gunsolus, 1996). Pre- plant tillage may also reduce weed densi- ties by placing weed seeds at depths in the soil profile that are too deep for successful establishment, particularly for species with small seeds (Pareja et al., 1985; Buhler and Mester, 1991). Seed burial can be particu- larly beneficial in years following high seed rain due to weed control failures (Hartzler and Roth, 1993).
Post-plant tillage can also be part of IWM, especially during the production of annual crops (Gunsolus, 1990). Shallow tillage before crop emergence and cultiva- tion between rows after crop establishment are effective in removing annual weeds and inhibiting the growth of perennial species.
Timely rotary hoeing reduces weed density up to 85% (Buhler and Gunsolus, 1996).
When used in combination with rotary hoe- ing (Gunsolus, 1990; Buhler and Gunsolus, 1996) or supplemented with broadcast (Gebhardt, 1981; Steckel et al., 1990) or band applications of herbicides (Buhler et al., 1992, 1993; Wiltshire et al., 2003), cul- tivation between rows can provide effective weed control, reduce the quantity of herbi- cide applied and bring diversity to the weed management system.
Although post-plant tillage can be highly effective in managing weeds, its importance in recent times has dimin-
ished due to less flexibility in timing and greater labour requirements than selective herbicides (Gunsolus, 1990). Opportunities exist to enhance the efficacy of mechanical control strategies through new designs of mechanical weed control tools (Kouwen- hoven, 1997; Fogelberg and Kritz, 1999), and the use of automatic guidance systems (Søgaard, 1998; Tillett et al., 2002; Wiltshire et al., 2003) as well as of decision tools to improve timing of operations (Oriade and Forcella, 1998).
Herbicides
Herbicides are the principle weed manage- ment tool in many cropping systems across the world. In 2001, herbicides accounted for 44% of all pesticides used globally (Keily et al., 2004). The adoption of herbicides has facilitated the development of no-till and other forms of reduced tillage, reduced labour requirements for weed management and decreased risks of weed control failures associated with adverse weather condi- tions (Kudsk and Streibig, 2003). The use of modern genetic techniques to transfer resistance to non-selective herbicides such as glyphosate and gluphosinate into several important agronomic crops has provided additional herbicide options. Fundamen- tally, these herbicide-resistant crops do not change weed control. They are simply an advance in technology that provides her- bicides with a broader spectrum of control and more flexibility in application time (Burnside, 1992; Owen, 2000).
Although herbicides provide growers with several advantages compared to other control tactics, they have decoupled weed management from cultural practices that once were an integral component of the procedure. This has resulted in simplifica- tion of weed management, facilitating the development of herbicide-resistant weeds and rapid shifts in weed populations.
The opportunity to enhance herbicide effectiveness through improved manage- ment or integration with other strategies is well documented (Zhang et al., 2000).
Techniques that have allowed successful reductions in herbicide rates include: (i) combining band applications of herbicides over the crop row with interrow cultivation (Rosales-Robles et al., 1999); (ii) enhanc- ing crop competitiveness through cultivar selection (Gealy et al., 2003) or planting arrangement (Wait et al., 1999); (iii) adjust- ing herbicide rate to target species (Knezevik et al., 1998); (iv) using synergistic herbicide combinations (Scott et al., 1998); (v) opti- mizing application timing (O’Sullivan and Bouw, 1997); and (vi) using appropriate till- age practices (Bostrom and Fogelfors, 1999).
Although reductions in rates may increase the likelihood of control failures compared with full label rates, this risk can be man- aged by utilizing this approach in fields with low initial weed densities and appro- priate integration with other management strategies (Zhang et al., 2000; Bussan and Boerboom, 2001).
Thresholds and Weed Management Economic thresholds are usually consid- ered a critical component of IPM systems (Bottrell, 1979). Various types of thresholds have been described, most developed with the purpose of assisting farmers in making better weed control decisions (Cousens, 1987). Economic threshold is the most com- monly described and is defined as the weed density at which the cost of control equals the value of the crop that would be lost due to interference if the weeds were left in the field. At weed densities below the economic threshold, it is recommended that weeds be left in the field because net returns would be higher than if they were controlled.
Although much effort has been devoted in developing economic thresholds, their acceptance by both weed scientists and pro- ducers has been limited. A survey of Illinois farmers found that only 9% used economic thresholds as a basis for weed control (Cza- paret al., 1995). Biological and agronomic limitations of economic thresholds have been reviewed (O’Donovan, 1996; Norris, 1999). Norris (1999) stated that the con-
cept of economic thresholds was initially developed for arthropod control and then adapted for weed control with little change.
He argued that differences in the ecology and population biology between weeds and arthropods limit the transferability of threshold concepts between pest classes.
A primary argument against economic thresholds is the future effect of weed seed production by weeds below threshold den- sities. Subthreshold densities of velvetleaf resulted in a rapid increase in the weed seedbank and subsequent velvetleaf den- sities (Zanin and Sattin, 1988; Hartzler, 1996; Cardina and Norquay, 1997). Eco- nomic optimum thresholds (EOTs) differ from economic thresholds in that EOTs consider the long-term cost associated with seed production (Cousens, 1987). The EOTs for velvetleaf and common sunflower in soybean were calculated to be respec- tively 7.5-fold and 3.6-fold lower than the economic threshold (Bauer and Mortensen, 1992).
The instability of yield losses has been cited as another limitation of economic thresholds. The yield loss attributable to a specific weed infestation can vary by a factor of two or more depending upon the environ- ment and crop production practices (Stoller et al., 1987; Bauer et al., 1991). The distri- bution of weeds within agricultural fields is rarely uniform; weeds are typically found in patches having a high relative density sur- rounded by areas with a few plants (Cardina et al., 1996). Because the spatial pattern of weeds is not regular, the mean density alone is of little value in predicting yield losses.
Assuming a regular distribution of weeds when predicting yield losses resulted in an overestimation of weed-related yield losses (Wiles et al., 1992).
Auld and Tisdell (1987) stated that risk aversion by farmers and uncertainty of the yield-loss function limited the relevance of economic thresholds. Cousens (1987) con- cluded that subjectivity in decision mak- ing is acceptable as long as knowledge of competition, weed population dynamics and herbicide performance is used to guide management practices.
Site-specific Management Recent advances in site-specific agriculture have created opportunities for enhancing the efficiency of weed management. Site- specific agriculture has been defined as
‘an information and technology based agri- cultural management system to identify, analyze, and manage spatial and temporal variability within fields for optimum prof- itability, sustainability, and protection of the environment’ (Robert et al., 1994). This concept has direct application to ecologi- cal weed management because of the spa- tial and temporal heterogeneity of weed populations across agricultural landscapes (Johnsonet al., 1995; Cardina et al., 1996).
Although weeds are not uniformly distrib- uted across fields, most weed control prac- tices are applied uniformly. The uniform application of herbicides over non-uniform weed populations has been identified as an important source of inefficiency in weed management (Cardina et al., 1997). Large portions of crop fields are often below the threshold weed density when the average field density is above the threshold, or vice versa (Cardina et al., 1995; Johnson et al., 1995). Cardina et al. (1996) found that with a hypothetical threshold of ten weed plants per square metre, about 40% of a field did not require treatment in one year, but 90%
of the same field required treatment in another year.
Site-specific management requires affor- dable methods to sample and map weed populations (Wiles, 2005). Typically, sam- pling programmes developed for IWM are based on measuring the weed density and are insufficient for site-specific manage- ment. Weed maps can be generated using various methods of interpolation with spa- tially referenced weed density data (Dille et al., 2002). Currently, the expense of gener- ating maps with sufficient detail to guide management decisions has limited site- specific weed management (Wiles, 2005).
An improved understanding of the spatial stability of weed infestations may allow decisions to be based on historic weed dis- tribution maps rather than generating new maps each season (Gerhards et al., 1997;
Colbach et al., 2000). Developing methods to combine growers’ knowledge of weed distribution with spatially referenced data may facilitate the adoption of site-specific management (Wiles, 2005).
Site-specific management of weeds involves new concepts of weed biology and new technology. Principles of weed man- agement and biology will need to be applied more precisely. Much of the effort in site- specific management has focused on devel- oping the technology required to capitalize on the spatial distribution of weeds within fields to minimize external inputs (Woe- bbecke et al., 1993; Medlin et al., 2000).
Aerial photography utilizing multispectral digital images is able to detect high densi- ties (more than ten plants per square metre) of seedling-pitted morning glory and sickle- pod in soybean (Medlin et al., 2000). ‘Smart sprayers’ utilize real-time sensors mounted to the tractor that detect the presence of weeds and control herbicide application (Tiam, 2002). Opportunities also exist to determine the ecological factors that drive weed patchiness within fields (Dieleman et al., 2000; Walter et al., 2002). The rela- tionship between weed occurrence and soil properties is found to be field-specific, and soil characteristics are one of several factors that affected weed patchiness (Walter et al., 2002). Identifying associations between site characteristics and weed abundance may facilitate the development of practices that create less favourable environments for weeds.
Conclusions
Ecological weed management differs from traditional weed management in that the primary focus is on creating an environ- ment unfavourable for weed establishment, growth and reproduction rather than on specific control tactics. Many of the compo- nents of an ecological management system are inextricably intertwined, thereby mak- ing it difficult to measure the individual contributions of specific elements of the sys- tem. A better understanding of the underly- ing mechanisms that influence the success
or failure of weeds in agroecosystems will further the development and adoption of ecological weed management systems for agricultural crops.
The central challenge of developing ecological weed management systems is the integration of the options and tools that are available to make the cropping system unfavourable for weeds and to minimize the impact of any weeds that survive. No single weed management tactic has proven to be the ‘magic bullet’ to eliminate weed problems, and given the nature of weed communities, we should not expect one to appear in the near future. The best approach may be to integrate cropping system design
and knowledge of ecological processes with all available weed control strategies into a comprehensive weed management system.
The integration of ecological principles into weed management decision making presents a major challenge to weed science researchers and practitioners. Weed scien- tists must play a larger role in leading eco- logical research in agricultural systems. An expanded theory of applied ecology pro- vides an excellent framework for expanded approaches to weed management because it allows for new and creative ways of meeting the challenge of managing weeds in ways that are environmentally and economically viable over the long term.
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