An expert system for insect pest population dynamics prediction

Ibrahim, Eric Ali; Salifu, Daisy; Mwalili, Samuel; Dubois, Thomas; Collins, Richard; Tonnang, Henri E. Z.

doi:10.1016/j.compag.2022.107124

Cited by 12 publications

(12 citation statements)

References 38 publications

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“…This result is in line with previous studies reporting humidity as a key component of B. dorsalis population dynamics (e.g. Ibrahim et al, 2022; Chuang et al, 2014; Vayssières et al, 2009). The relationship between the demographic estimate t 0 and PC2 indicated that even a very small amount of precipitation (most correlated variable with PC2) occurring between February and April (episodic rainfall events called the “mango rain” in Senegal (Wade et al, 2015)) could be involved in creating favourable microhabitats leading to early development of BD populations in orchards.…”

Section: Discussionsupporting

confidence: 93%

Hierarchizing multi-scale environmental effects on agricultural pest population dynamics: a case study on the annual onset ofBactrocera dorsalispopulation growth in Senegalese orchards

Caumette,

Diatta,

Piry

et al. 2023

Preprint

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Implementing integrated pest management programs to limit agricultural pest damage requires an understanding of the interactions between the environmental variability and population demographic processes. However, identifying key environmental drivers of spatiotemporal pest population dynamics remains challenging as numerous candidate factors can operate at a range of scales, from the field (e.g. agricultural practices) to the regional scale (e.g. weather variability). In such a context, data-driven approaches applied to pre-existing data may allow identifying patterns, correlations, and trends that may not be apparent through more restricted hypothesis-driven studies. The resulting insights can lead to the generation of novel hypotheses and inform future experimental work focusing on a limited and relevant set of environmental predictors. In this study, we developed an ecoinformatics approach to unravel the multi-scale environmental conditions that lead to the early re-infestation of mango orchards by a major pest in Senegal, the oriental fruit flyBactrocera dorsalis(BD). We gathered abundance data from a three-year monitoring conducted in 69 mango orchards as well as environmental data (i.e. orchard management, landscape structure and weather variability) across a range of spatial scales. We then developed a flexible analysis pipeline centred on a recent machine learning algorithm (GPBoost), which allows the combination of gradient boosting and mixed-effects models or Gaussian processes, to hierarchize the effects of multi-scale environmental variables on the timing of annual BD population growth in orchards. We found that physical factors (temperature, humidity), and to some extent landscape features, were the main drivers of the spatio-temporal variability of the onset of population growth in orchards. These results suggest that favourable microclimate conditions could provide refuges for small BD populations that could survive, with little or no reproduction, during the mango off-season and, then, recolonize neighbouring orchards at the beginning of the next mango season. Confirmation of such a hypothesis could help to prioritize surveillance and preventive control actions in refuge areas.

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Section: Discussionsupporting

confidence: 93%

Hierarchizing multi-scale environmental effects on agricultural pest population dynamics: a case study on the annual onset ofBactrocera dorsalispopulation growth in Senegalese orchards

Caumette,

Diatta,

Piry

et al. 2023

Preprint

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“…However, there are advantages that fuzzy logic offers in terms of flexibility and simplicity, which reduce the model’s vulnerability to uncertainty as no exact information on the system is needed [ 46 ]. Given these advantages, the fuzzy logic model is one of the most useful Artificial Intelligence algorithms in many agricultural applications, and its importance is growing considerably in ecology with successful applications in insect pest management (e.g., [ 29 , 60 ]) and biological control [ 30 ]. For example, Center and Verma [ 61 ] described the applications of fuzzy logic in biological and agricultural systems.…”

Section: Discussionmentioning

confidence: 99%

A Fuzzy-Based Model to Predict the Spatio-Temporal Performance of the Dolichogenidea gelechiidivoris Natural Enemy against Tuta absoluta under Climate Change

Agboka

Tonnang

Abdel‐Rahman

et al. 2022

Biology

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The South American tomato pinworm, Tuta absoluta, causes up to 100% tomato crop losses. As Tuta absoluta is non-native to African agroecologies and lacks efficient resident natural enemies, the microgastrine koinobiont solitary oligophagous larval endoparasitoid, Dolichogenidea gelechiidivoris (Marsh) (Syn.: Apanteles gelechiidivoris Marsh) (Hymenoptera: Braconidae) was released for classical biological control. This study elucidates the current and future spatio-temporal performance of D. gelechiidivoris against T. absoluta in tomato cropping systems using a fuzzy logic modelling approach. Specifically, the study considers the presence of the host and the host crop, as well as the parasitoid reproductive capacity, as key variables. Results show that the fuzzy algorithm predicted the performance of the parasitoid (in terms of net reproductive rate (R0)), with a low root mean square error (RMSE) value (< 0.90) and a considerably high R2 coefficient (= 0.98), accurately predicting the parasitoid performance over time and space. Under the current climatic scenario, the parasitoid is predicted to perform well in all regions throughout the year, except for the coastal region. Under the future climatic scenario, the performance of the parasitoid is projected to improve in all regions throughout the year. Overall, the model sheds light on the varying performance of the parasitoid across different regions of Kenya, and in different seasons, under both current and future climatic scenarios.

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“…An explicit statement to this effect is made by Baker et al [ 5 ]: “ The ‘dorsalis complex’ is one of the most destructive pest species complexes in global fruit production due to polyphagy, invasiveness, high reproductive potential, multivoltinism and continuous activity throughout the year ” [our emphasis]. Implicitly it can be seen in models where temperature is the primary driver of population cycles [ 21 , 22 , 23 , 24 ], or in population models which seek correlation between fly numbers and environmental variables [ 25 , 26 , 27 ].…”

Section: Introductionmentioning

confidence: 99%

“…Over the last decade numerous researchers have applied increasingly sophisticated multivariate, neural network and fuzzy-logic analyses to seek correlations between B. dorsalis population numbers and weather and/or crop variables [ 25 , 26 , 27 , 120 , 121 , 122 , 123 , 124 , 125 ]. In some cases correlations have been very high and it could be argued that such analyses are evidence against B. dorsalis having anything more than a ‘simple’ weather/host-availability driven phenological cycle.…”

Section: Introductionmentioning

confidence: 99%

“…Secondly, important correlative variables are not always those that might be expected in a ‘weather and breeding-up-within-crop’ phenology. Notably, Kamala Jayanthi and Verghese [ 120 ], Kamal Jayanthi et al [ 122 ] and Ibrahim et al [ 25 ] all demonstrate strong correlations between fly trap catches and the abundance of immature fruit, but not the abundance of mature fruit. Thus these studies show that fly populations are correlated with the crop still to come, rather than being directly correlated with breeding within that crop, a subtle but important difference that reinforces the early work of Newell and Haramoto [ 116 ] in understanding the difference between adult abundance and adult reproduction.…”

Section: Introductionmentioning

confidence: 99%

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The Fallacy of Year-Round Breeding in Polyphagous Tropical Fruit Flies (Diptera: Tephritidae): Evidence for a Seasonal Reproductive Arrestment in Bactrocera Species

Clarke

Measham²

2022

Insects

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The genus Bactrocera (Diptera: Tephritidae) is endemic to the monsoonal rainforests of South-east Asia and the western Pacific where the larvae breed in ripe, fleshy fruits. While most Bactrocera remain rainforest restricted, species such as Bactrocera dorsalis, Bactrocera zonata and Bactrocera tryoni are internationally significant pests of horticulture, being both highly invasive and highly polyphagous. Almost universally in the literature it is assumed that Bactrocera breed continuously if temperature and hosts are not limiting. However, despite that, these flies show distinct seasonality. If discussed, seasonality is generally attributed to the fruiting of a particular breeding host (almost invariably mango or guava), but the question appears not to have been asked why flies do not breed at other times of the year despite other hosts being available. Focusing initially on B. tryoni, for which more literature is available, we demonstrate that the seasonality exhibited by that species is closely correlated with the seasons of its endemic rainforest environment as recognised by traditional Aboriginal owners. Evidence suggests the presence of a seasonal reproductive arrest which helps the fly survive the first two-thirds of the dry season, when ripe fruits are scarce, followed by a rapid increase in breeding at the end of the dry season as humidity and the availability of ripe fruit increases. This seasonal phenology continues to be expressed in human-modified landscapes and, while suppressed, it also partially expresses in long-term cultures. We subsequently demonstrate that B. dorsalis, across both its endemic and invasive ranges, shows a very similar seasonality although reversed in the northern hemisphere. While high variability in the timing of B. dorsalis population peaks is exhibited across sites, a four-month period when flies are rare in traps (Dec–Mar) is highly consistent, as is the fact that nearly all sites only have one, generally very sharp, population peak per year. While literature to support or deny a reproductive arrest in B. dorsalis is not available, available data is clear that continuous breeding does not occur in this species and that there are seasonal differences in reproductive investment. Throughout the paper we reinforce the point that our argument for a complex reproductive physiology in Bactrocera is based on inductive reasoning and requires specific, hypothesis-testing experiments to confirm or deny, but we do believe there is ample evidence to prioritise such research. If it is found that species in the genus undergo a true reproductive diapause then there are very significant implications for within-field management, market access, and biosecurity risk planning which are discussed. Arguably the most important of these is that insects in diapause have greater stress resistance and cold tolerance, which could explain how tropical Bactrocera species have managed to successfully invade cool temperate regions.

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An expert system for insect pest population dynamics prediction

Cited by 12 publications

References 38 publications

Hierarchizing multi-scale environmental effects on agricultural pest population dynamics: a case study on the annual onset ofBactrocera dorsalispopulation growth in Senegalese orchards

Hierarchizing multi-scale environmental effects on agricultural pest population dynamics: a case study on the annual onset ofBactrocera dorsalispopulation growth in Senegalese orchards

A Fuzzy-Based Model to Predict the Spatio-Temporal Performance of the Dolichogenidea gelechiidivoris Natural Enemy against Tuta absoluta under Climate Change

The Fallacy of Year-Round Breeding in Polyphagous Tropical Fruit Flies (Diptera: Tephritidae): Evidence for a Seasonal Reproductive Arrestment in Bactrocera Species

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