Pheromone dispersion in forests

Fares, Y.; Sharpe, Peter J. H.; Magnuson, C. E.

doi:10.1016/s0022-5193(80)80010-5

Cited by 67 publications

(35 citation statements)

References 8 publications

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“…Not only must organisms identify the signature of an attractive chemical odorant, they must also orient and navigate towards its source while compensating for discontinuities in the signal caused by turbulence, convection and the movement of the animal itself (David et al, 1982;Fares et al, 1980;Vickers, 2000;Vickers et al, 2001). Furthermore, unlike visual or acoustic stimuli, odors contain no spatial information.…”

Section: Introductionmentioning

confidence: 99%

Context-dependent olfactory enhancement of optomotor flight control inDrosophila

Chow

Frye

2008

Journal of Experimental Biology

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Section: Introductionmentioning

confidence: 99%

Context-dependent olfactory enhancement of optomotor flight control inDrosophila

Chow

Frye

2008

Journal of Experimental Biology

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“…This concept is based on various Gaussian equations that calculate the odor concentrations in still and moving air (Sutton 1953;Bossert and Wilson 1963;Fares et al 1980). The active space has been investigated in several studies by observing wing-fanning of male moths in cages at various points within a pheromone plume .…”

Section: Introductionmentioning

confidence: 99%

Active Space of Pheromone Plume and its Relationship to Effective Attraction Radius in Applied Models

Byers

2008

J Chem Ecol

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The release rate of a semiochemical lure that attracts flying insects has a specific effective attraction radius (EAR) that corresponds to the lure's orientation response strength. EAR is defined as the radius of a passive sphere that intercepts the same number of insects as a semiochemical-baited trap. It is estimated by calculating the ratio of trap catches in the field in baited and unbaited traps and the interception area of the unbaited trap. EAR serves as a standardized method for comparing the attractive strengths of lures that is independent of population density. In two-dimensional encounter rate models that are used to describe insect mass trapping and mating disruption, a circular EAR (EAR c ) describes a key parameter that affects catch or influence by pheromone in the models. However, the spherical EAR, as measured in the field, should be transformed to an EAR c for appropriate predictions in such models. The EAR c is calculated as (π/2EAR2 )/F L , where F L is the effective thickness of the flight layer where the insect searches. F L was estimated from catches of insects (42 species in the orders Coleoptera, Lepidoptera, Diptera, Hemiptera, and Thysanoptera) on traps at various heights as reported in the literature. The EAR c was proposed further as a simple but equivalent alternative to simulations of highly complex active-space plumes with variable response surfaces that have proven exceedingly difficult to quantify in nature. This hypothesis was explored in simulations where flying insects, represented as coordinate points, moved about in a correlated random walk in an area that contained a pheromone plume, represented as a sector of active space composed of a capture probability surface of variable complexity. In this plume model, catch was monitored at a constant density of flying insects and then compared to simulations in which a circular EAR c was enlarged until an equivalent rate was caught. This demonstrated that there is a circular EAR c , where all insects that enter are caught, which corresponds in catch effect to any plume. Thus, the EAR c , based on the field-observed EAR, can be used in encounter rate models to develop effective control programs based on mass trapping and/or mating disruption.

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“…This simplification is not entirely unreasonable in that many kinds of insects fly at relatively set heights above the ground, typically at heights that make contact with a plume from a natural source likely. Plumes do, however, disperse to some extent vertically, especially under some unstable (adiabatic) atmospheric conditions typical of midday (Fares et al, 1980), but also at night (Schal, 1982). Nonetheless, simulation modeling allows estimates of how improvements in trap range or efficiency of a trap might enhance detection protocols.…”

Section: Interpretation Of Trap Catchmentioning

confidence: 99%

Use of Semiochemicals for Survey and Detection of Exotic Insects: Principles and Constraints

Cardé¹

2002

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155This review concentrates on the principles of surveying for exotic invaders with semiochemical-baited traps and examines three possible strategies for improving detection of exotic insects. 1) What constrains the development of traps having an extended range of attraction? 2) Is the trap's detection sensitivity influenced by the failure of some insects attracted to a trap to be captured? 3) What empirical and simulation techniques can be used to enhance our understanding of the meaning zero trap catch and to optimize spatial patterns of deployment? Selected evidence from a variety of survey and detection cases is considered, but examples relate mainly to survey methods used to detect the spread and invasion of the gypsy moth {Lymantria dispai), which is a species of special interest. It is concluded that improvements in the technology of trapping are attainable with simple behavioral assays. Such improvements should lower the cost of surveys and enhance their reliability. Correlation of negative trap catch with the probability of missing an incipient infestation remains at the heart of survey interpretation. Mark-recapture protocols and simulation modeling are two techniques that should prove useful for improving patterns of trap deployment and interpretation of survey results

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Pheromone dispersion in forests

Cited by 67 publications

References 8 publications

Context-dependent olfactory enhancement of optomotor flight control inDrosophila

Context-dependent olfactory enhancement of optomotor flight control inDrosophila

Active Space of Pheromone Plume and its Relationship to Effective Attraction Radius in Applied Models

Use of Semiochemicals for Survey and Detection of Exotic Insects: Principles and Constraints

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