Modelling the population dynamics of the Queensland fruit fly, Bactrocera (Dacus) tryoni: a cohort-based approach incorporating the effects of weather

Yonow, Tania; Zalucki, Myron P.; Sutherst, R. W.; Dominiak, Bernard C.; Maywald, G. F.; Maelzer, D. A.; Kriticos, Darren J.

doi:10.1016/s0304-3800(03)00306-5

Cited by 82 publications

(105 citation statements)

References 30 publications

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“…A more sophisticated simulation model may be able to have superior results using this kind of site-specific variables. When these kinds of site-specific parameters are included in a simulation model it is prudent to check the model is portable to other sites (Yonow et al 2004). …”

Section: Discussionmentioning

confidence: 99%

Site-specific temporal and spatial validation of a generic plant pest forecast system with observations of Bactrocera dorsalis (oriental fruit fly)

Hong¹,

Magarey²,

Borchert³

et al. 2015

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Citation: Hong SC, Magarey RD, Borchert DM, Vargas RI, Souder SK (2015) Site-specific temporal and spatial validation of a generic plant pest forecast system with observations of Bactrocera dorsalis (oriental fruit fly). NeoBiota 27: 37-67. doi: 10.3897/neobiota.27.5177 Abstract This study introduces a simple generic model, the Generic Pest Forecast System (GPFS), for simulating the relative populations of non-indigenous arthropod pests in space and time. The model was designed to calculate the population index or relative population using hourly weather data as influenced by developmental rate, high and low temperature mortalities and wet soil moisture mortality. Each module contains biological parameters derived from controlled experiments. The hourly weather data used for the model inputs were obtained from the National Center of Environmental Prediction Climate Forecast System Reanalysis (NCEP-CFSR) at a 38 km spatial resolution. A combination of spatial and site-specific temporal data was used to validate the GPFS models. The oriental fruit fly, Bactrocera dorsalis (Hendel), was selected as a case study for this research because it is climatically driven and a major pest of fruit production. Results from the GPFS model were compared with field B. dorsalis survey data in three locations: 1) Bangalore, India; 2) Hawaii, USA; and 3) Wuhan, China. The GPFS captured the initial outbreaks and major population peaks of B. dorsalis reasonably well, although agreement varied between sites. NeoBiota 27: 37-67 (2015) doi: 10.3897/neobiota.27.5177 http://neobiota.pensoft.net Seung Cheon Hong et al. / NeoBiota 27: 37-67 (2015) 38 the highest match between the observed and simulated B. dorsalis populations, with indices of agreement of 0.85. The site-specific temporal comparisons implied that the GPFS model is informative for prediction of relative abundance. Spatial results from the GPFS model were also compared with 161 published observations of B. dorsalis distribution, mostly from East Asia. Since parameters for pupal overwintering and survival were unknown from the literature, these were inferred from the distribution data. The study showed that GPFS has promise for estimating suitable areas for B. dorsalis establishment and potentially other non-indigenous pests. It is concluded that calibrating prediction models with both spatial and sitespecific temporal data may provide more robust and reliable results than validations with either data set alone. RESEARCH ARTICLE Advancing research on alien species and biological invasions A peer-reviewed open-access journal NeoBiota

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Section: Discussionmentioning

confidence: 99%

Site-specific temporal and spatial validation of a generic plant pest forecast system with observations of Bactrocera dorsalis (oriental fruit fly)

Hong¹,

Magarey²,

Borchert³

et al. 2015

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“…The ANOVAs for fruit species in relation to emergence of B. invadens and C. cosyra took particular account of various sampling seasons (months) and the weather parameters (precipitation, air temperature and relative humidity). Relationship between fly emergence and weather variables was tested using multiple linear regression analysis following the procedure of Yonow et al (2004) to look at the changes in fruit fly abundance across host fruits, seasons and climatic factors.…”

Section: Discussionmentioning

confidence: 99%

Seasonal phenology of <i>Bactrocera invadens</i> (Drew, Tsuruta and White) and <i>Ceratitis cosyra</i> (Walker) (Diptera: Tephritidae) in Northern Ghana

Benjamin¹,

Kelvin²,

Afreh-Nuamah³

et al. 2014

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Sustainable management of fruit flies in any given ecology requires proper understanding of the population dynamics of key species in relation to host availability and the influence of abiotic factors. Studies were conducted to determine the phonological patterns of B. invadens and C. cosyra in the northern savanna ecology of Ghana. Fruit samples from 12 main host plants were collected from multiple sites at regular intervals between October, 2011 and September, 2013. These were maintained for pupal and adult fly emergence, and the results compared with the seasons and whether parameters. The widespread variability and abundance of fruit species in the ecology ensured year-round breeding of B. invadens and C. cosyra with different seasonal population levels. Dynamics of emergence of the flies fluctuated at various levels in response to availability of the host fruits and the influence of weather factors. Regression analysis indicated that precipitation showed the strongest influence on the fly populations. Infestation of B. invadens was positively related with temperature, relative humidity (RH) and precipitation while C. cosyra infestation was negatively related with RH. These studies provide baseline information on the natural anundance and occurrence periods of the main hosts and their influence on tephritid population patterns in Ghana. This can be useful in the development of sustainable control programmes by way of developing forecasting models for IPM decision making, applying sanitary measures, male annihilation techniques and setting up bait stations at the best period before the cropping season.

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“…Developing models of population phenology can enhance decision-making processes around pest control and provide greater opportunity to control the pest within integrated pest management programs [3,15]. There are not many references concerning the phenology of C. tenebrionis, perhaps due to the cryptic habits of the juveniles and the long life cycle that characterizes the species.…”

Section: Psychementioning

confidence: 99%

“…The base of each shoot was placed in a plastic tube containing water. The cages were kept at 15,20,25,30,35,40, or 45 ± 1 • C, relative humidity of 50 ± 5% and a photoperiod of 13L : 11D. Seven observations of 60 min each, with an interval of one hour, were carried out at each temperature.…”

Section: Laboratory Experimentmentioning

confidence: 99%

Effects of Environmental Temperature onCapnodis tenebrionisAdult Phenology

Bonsignore

2012

Psyche: A Journal of Entomology

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The phenology of Capnodis tenebrionis adults was presented with reference to two different climate conditions. In a temperate moderate-warm climate, adult density showed two separate peaks during the year: one in early summer of the overwintering generation and one with beetles emerging in the late summer. In a warmer semiarid climate, the overwintering adults and the new generation overlapped during summer with a continuous increase of adult density. The difference in the average annual temperature between areas during the study period was almost 3 • C, and, in the warmer area, the new generation of C. tenebrionis emerged at least one month earlier. To make a prediction of adult presence, a model utilizing degree-days was developed from data collected over a five-year period. Models obtained from equations (Logistic 4-parameter, y(x) = yo + a/(1 + (x/xo) b )) of each year were developed to describe the relationship between degree-day accumulation (with a minimal threshold activity temperature of 14.21 • C calculated in the laboratory) and the cumulative percentage of adult presence. According to the overall model, the 50% of overwintering beetles occurred at 726 degree-days (Biofix: 1st March) and the emerging beetles occurred at 801 degree-days (Biofix: 1st July). The results show that a change in temperature is an important aspect that highlights the adaptability of this species.

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Modelling the population dynamics of the Queensland fruit fly, Bactrocera (Dacus) tryoni: a cohort-based approach incorporating the effects of weather

Cited by 82 publications

References 30 publications

Site-specific temporal and spatial validation of a generic plant pest forecast system with observations of Bactrocera dorsalis (oriental fruit fly)

Site-specific temporal and spatial validation of a generic plant pest forecast system with observations of Bactrocera dorsalis (oriental fruit fly)

Seasonal phenology of <i>Bactrocera invadens</i> (Drew, Tsuruta and White) and <i>Ceratitis cosyra</i> (Walker) (Diptera: Tephritidae) in Northern Ghana

Effects of Environmental Temperature onCapnodis tenebrionisAdult Phenology

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