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A wide range of insects affect crop production and cause considerable yield losses. Difficulties reside on the development and adaptation of adequate strategies to predict insect pests for their timely management to ensure enhanced agricultural production. Several conceptual modelling frameworks have been proposed, and the choice of an approach depends largely on the objective of the model and the availability of data. This paper presents a summary of decades of advances in insect population dynamics, phenology models, distribution and risk mapping. Existing challenges on the modelling of insects are listed; followed by innovations in the field. New approaches include artificial neural networks, cellular automata (CA) coupled with fuzzy logic (FL), fractal, multi-fractal, percolation, synchronization and individual/agent-based approaches. A concept for assessing climate change impacts and providing adaptation options for agricultural pest management independently of the United Nations Intergovernmental Panel on Climate Change (IPCC) emission scenarios is suggested. A framework for estimating losses and optimizing yields within crop production system is proposed and a summary on modelling the economic impact of pests control is presented. The assessment shows that the majority of known insect modelling approaches are not holistic; they only concentrate on a single component of the system, i.e. the pest, rather than the whole crop production system. We suggest system thinking as a possible approach for linking crop, pest, and environmental conditions to provide a more comprehensive assessment of agricultural crop production. [ABSTRACT FROM AUTHOR]

Tuta absoluta is an invasive insect that originated from South America and has spread to Europe Africa and Asia. Since its detection in Spain in 2006, the pest is continuing to expand its geographical range, including the recent detection in several Sub-Saharan African countries. The present study proposed a model based on cellular automata to predict year-to-year the risk of the invasion and spread of T. absoluta across Africa. Using, land vegetation cover, temperature, relative humidity and yield of tomato production as key driving factors, we were able to mimic the spreading behavior of the pest, and to understand the role that each of these factors play in the process of propagation of invasion. Simulations by inferring the pest’s natural ability to fly long distance revealed that T. absoluta could reach South of Africa ten years after being detected in Spain (Europe). Findings also reveal that relative humidity and the presence of T. absoluta host plants are important factors for improving the accuracy of the prediction. The study aims to inform stakeholders in plant health, plant quarantine, and pest management on the risks that T. absoluta may cause at local, regional and event global scales. It is suggested that adequate measures should be put in place to stop, control and contain the process used by this pest to expand its range. [ABSTRACT FROM AUTHOR]

The main purpose of this study was to understand the spatio-temporal spread of the maize stem borer Busseola fusca (Fuller) (Lepidoptera: Noctuidae) in smallholder maize farms. The analysis carried out allowed the establishment of complementary sampling scheme and analysis that can be applied to investigate the propagation of stem borer damages and extended to other insect pests. This approach requires consideration of all plants point locations, the knowledge on the level of damage and its characterization. Results showed that there was a two-week interval between occurrence of the peaks of leaf damage and male adult moth abundance. The prior role of leaf damages in the farm infestation by B. fusca is revealed, and an estimate of the mean transition time between different damage types is provided. Furthermore, damaged plants exhibited a local spatial autocorrelation within a range of dependence of 0-10 meters; and the spatio-temporal pattern of B. fusca damage spread evolves as a spiral around an initial patch of damaged plants. By assuming a neighbor configuration of distribution of damaged plants nearby non-damaged, we showed that the inner plants are likely to become damaged within a time period of a week; thus, B. fusca infests farms in a systematic fashion. Overall, these results have useful implications for improving and optimizing existing field sampling methods for insect pest damages. The approaches used in carrying out the analysis further provided a deep understanding helpful to improve integrated pest management (IPM) strategies against stem borers, and offer IPM practitioners’ the opportunity to design, develop, and implement optimum control methods against B. fusca , an important pest of maize in Africa. [ABSTRACT FROM AUTHOR]

The temperature-dependent population growth potential of Phenacoccus solenopsis Tinsley, a highly polyphagous and invasive mealybug species, was studied on sprouted potatoes under laboratory conditions at six constant temperatures (15–40 °C). Several non-linear equations were fitted to the obtained data to model temperature-dependent population growth and species life history. The established equations for each life age/stage of the species were compiled to obtain an overall temperature-dependent phenology model. The life table parameters of P. solenopsis were estimated using stochastic simulation centred on a rate summation and cohort up-dating approach. The theoretical lower development threshold temperatures estimated using linear regressions applied to mean development rates were 11.2, 8.9, 9.8 and 12.7 °C, and the thermal constants for development were 93.7, 129.8, 97.1 and 100.0 degree days (DD) for nymph 1, nymph 2, nymph 3 and male pupa stages, respectively. The developed phenology model predicted temperatures between 25 and 35 °C as the favourable range for P. solenopsis development, survival and reproduction. P. solenopsis population attained a maximum net reproductive rate (107–108 females/female/generation) and total fecundity (216.6–226.5 individuals/female/generation) at temperatures between 25 and 30 °C. Mean length of generations decreased from 75.6 days at 15 °C to 21 days at 40 °C. The maximum finite rate of increase (1.12–1.16 females/female/day) and shortest doubling time (4.3–6.1 days) were also observed at temperatures between 25 and 35 °C. The simulation of phenology model at fluctuating temperatures indicated that P. solenopsis populations might potentially increase with a finite rate of 1.06 females/female/day with an average generation time of 58.7 days and a doubling time of 12.1 days. The obtained life table parameters were reasonably similar when compared with literature data. The present model can be simulated spatially for estimating the pest risk and undertaking agro-ecoregion specific pest management strategies. [ABSTRACT FROM AUTHOR]

The performance of discrete mathematical models to describe the population dynamics of diamondback moth (DBM) (Plutella xylostella L.) and its parasitoid Diadegma semiclausum was investigated. The parameter values for several well-known models (Nicholson¿Bailey, Hassell and Varley, Beddington, Free and Lawton, May, Holling type 2, 3 and Getz and Mills functional responses) were estimated. The models were tested on 20 consecutive sets of time series data collected at 14 days interval for pest and parasitoid populations obtained from a highland cabbage growing area in eastern Kenya. Model parameters were estimated from minimized squared difference between the numerical solution of the model equations and the empirical data using Powell's method. Maximum calculated DBM growth rates varied between 0.02 and 0.07. The carrying capacity determined at 16.5 DBM/plant by the Beddington et al. model was within the range of field data. However, all the estimated parameter values relating to the parasitoid, including the instantaneous searching rate (0.07¿0.28), per capita searching efficiency (0.20¿0.27), search time (5.20¿5.33), handling time (0.77¿0.90), and parasitism aggregation index (0.33), were well outside the range encountered empirically. All models evaluated for DBM under Durbin¿Watson criteria, except the May model, were not autocorrelated with respect to residuals. In contrast, the criteria applied to the parasitoid residuals showed strong autocorrelations. Thus, these models failed to estimate parasitoid dynamics. We conclude that the interactions of the DBM with its parasitoid cannot be explained by any of the models tested. Two factors may be associated with this failure. First, the parasitoid in this integrated biological control system may not be playing a major role in regulating DBM population. Second, and perhaps more likely, poor correlations reflect gross inadequacies in the theoretical assumptions that underlie the existing models. [Copyright &y& Elsevier]

Abstract: The Lotka–Volterra model was applied to the population densities of diamondback moth (DBM), Plutella xylostella (L.) and its exotic larval parasitoid Diadegma semiclausum (Hellen) data that was collected earlier by icipe’s DBM biological control team. The collections were done for 15 months before the release and 36 months after release of the parasitoid in two areas; in Werugha, Coast Province of Kenya and Tharuni, Central Province of Kenya, respectively. For each area in pre- and post-release periods, we estimated Lotka–Volterra model parameters from the minimization of the loss function between the theoretical and experimental time-series datasets following the Nelder-Mead multidimensional method. The model estimated a reduction in the value of the steady state of DBM population from 4.86 to 2.17 in Werugha and from 6.11 to 3.76 and 3.45 (with and without exclusion of the time before D. semiclausum recovery) in Tharuni when transiting from the pre- and post-release periods, respectively. This change was a consequence of the newly introduced parasitoid, in the areas. The study presented a successful and detailed technique for non-linear model parameters restoration which was demonstrated by the correct mimicking of empirical datasets from the classical biological control with D. semiclausum, in different areas of Kenya. The applied model has measured the parasitoids impact on the DBM biological control through a quantitative estimate of the effectiveness of the newly introduced species D. semiclausum. These equations may therefore be used as tool for decision making in the implementation for such pests’ management system strategy. [Copyright &y& Elsevier]

• A modelling process to estimate the optimum distance between traps and the number of auto dissemination devices per unit of space (ha, km2). • An approach to optimize the traps spatial configuration in an agro-system in IPM context. • A solution to improve insect pest management strategy in agricultural farms. • an efficient protocol for field experiment, to assess the dispersal ability of the insect infected by an entomopathogenic fungi with auto dissemination strategy. Agricultural research often relies on methods and approaches to represent and explain complex agro-ecosystems processes. In the context of biological control, auto dissemination strategies have been widely embraced for the management of various pests. One such strategy is using traps that attract arthropods into the hub of fungal based entomopathogens. The trapped pests are infected with the entomopathogen, which can then disseminate it among its conspecifics after being released. Despite the potential of the technique, its adoption especially by smallholder farmers has been limited, most likely due to the lack of an efficient trap positioning strategy. In this study, we propose an approach to improve the field application of fungal-based bio-pesticides (entomopathogenic fungi or EPF) by optimizing the spatial distribution of traps. The optimal field distribution of traps can be determined based on the following steps: (i) a field experiment to assess the dispersal ability of the pest infected by an entomopathogenic fungi (EPF) and (ii) the model-based estimation of the optimum traps density and distribution per unit of space (ha, km2). Based on experimental data we applied nonlinear regression and spatial optimization processes to calculate the radius covered by one trap and to estimate the optimum number and spatial positioning of the traps. We applied the method to a case study using the fungal isolate ICIPE 62 to control the invasive fruit fly Bactrocera dorsalis. The research revealed that nine pheromone traps per ha are required with a spacing distance of 37.45 m between the traps. The proposed approach can also be applied to other pest species, to help farmers reduce the number of traps used on a farm and to assist researchers and policymakers to optimize auto dissemination strategies in the context of integrated pest management (IPM). [ABSTRACT FROM AUTHOR]

The antestia bug Antestiopsis thunbergii (Hemiptera: Pentatomidae) is a major pest of Arabica coffee in African tropical highlands. It feeds on coffee plant vegetative parts and berries leading to a direct reduction in coffee yield and quality. This study aimed to determine A. thunbergii thermal requirements, and to obtain new information on the pest demography as influenced by temperature. Temperature-dependent models were developed using the Insect Life Cycle Modelling software (ILCYM) through a complete life table study at seven constant temperatures in the range 18–32 °C. Non-linear functions were fitted to A. thunbergii development, mortality, fecundity and senescence. Model parameters and demographic variables obtained from the models were given for each temperature and development stage. Life table parameters were estimated for nine constant temperatures, from 18 °C to 26 °C, using stochastic simulations. The minimum temperature threshold ( T min ) and the thermal constant ( k ) for the development from egg to adult were estimated from a linear function at 12.1 °C and 666.67° days, respectively. The maximum temperature threshold ( T max ) was estimated at 33.9 °C from a Logan model. The optimum temperature for immature stages’ survival was estimated to be between 22.4 and 24.7 °C. The maximum fecundity was 147.7 eggs female −1 at 21.2 °C. Simulated A. thunbergii life table parameters were affected by temperature, and the maximum value of intrinsic rate of increase ( r m ) was 0.029 at 22 °C and 23 °C. In general, the life cycle data, models and demographic parameters we obtained were in line with previous reports for antestia bugs or other stink bug species. The relationships between the pest thermal requirements and ecological preferences in highland coffee were discussed. Our results will contribute to risk prediction under climate change for this important coffee pest. [ABSTRACT FROM AUTHOR]

• India is a hotspot for biological control agents of Rastrococcus iceryoides. • Eleven old and new R. iceryoides (host)-parasitoid associations were described. • Praleurocerus viridis and Anagyrus chryos were the most promising parasitoids recorded. • We predicted optimal suitability for parasitoid introduction into Africa and Southeast Asia. • Predictive modelling are novel tools to support future classical biological control program. Rastrococcus iceryoides (Green) (Homoptera: Pseudococcidae) is a major invasive pest of several horticultural crops [in Africa and Asia, outside its native range in India], with damage levels ranging from 30% to complete crop failure. Due to lack of effective co-evolved parasitoids in the invaded regions, maximum entropy (MaxEnt) and genetic algorithm for ruleset production (GARP) were used to identify climatically suitable areas in India for foreign exploration. Based on the outcome of the predictive models, an extensive survey was conducted in 15 major mango growing regions in the state of Tamil Nadu, India. Thereafter, both models were used to identify climatic compatibility habitats in the invaded regions of R. iceryoides. Our results revealed ten host plants belonging to eight families with considerably low levels of infestation. The percentage parasitism established using mummified R. iceryoides was relatively high ranging between 16.7 ± 1.4 to 91.3 ± 3.7%. Both old and new host-parasitoid associations were recorded with eleven parasitoid species described. Eight of the parasitoids recorded were new records of R. iceryoides. Among these parasitoids, Praleurocerus viridis Agarwal, Anagyrus chryos Noyes & Hayat and Neoplatycerus tachikawai Subba Rao were the most dominant and widespread parasitoid species, highly specific to R. iceryoides with percent parasitism of 53.2 ± 5.4, 31.3 ± 2.7 and 8.8 ± 2.9%, respectively. Using the occurrence data of the parasitoids, both models successfully identified optimal suitable habitats in Africa and Asia. Both models showed optimal performances with the value of the average area under the curve (AUC) of 0.98 for MaxEnt and 0.95 for GARP. However, the percentage contribution of the predictor variables that influenced the current and future predictions in the native and invaded range varied considerably. These findings demonstrate the importance of predictive modelling as novel tools to support future classical biological control program targeting R. iceryoides in the invaded regions. Our results provide important information to guide strategic planning for future classical biological control programmes. [ABSTRACT FROM AUTHOR]

In the Eastern Africa highlands, the gradual transformation of natural ecosystems to smallholding coffee-based agrosystems has resulted in more fragmented landscapes. Major pests of coffee find appropriate living conditions leading to high infestation rates and the need for smallholder farmers to implement pest control measures. This study aims to understand the influence of landscapes on the ecology of three major coffee pests: the coffee berry borer (CBB), Hypothenemus hampei , and the Antestia bugs Antestiopsis thunbergii (ABT) and A. facetoides (ABF). The study was conducted on a typical smallholder coffee-based landscape in central Kenya. The pest abundance was assessed monthly for two years in a network of 30 coffee plots spread across the coffee agro-ecological subzones (AEsZ), namely upper midland UM1 and UM2, and the transition zones between UM1 and UM2 and between UM2 and UM3, herein referred to as TZ1 and TZ2, respectively. Landscape metrics, viz. patch density, Euclidean nearest neighbour distance, proximity index, contagion index, interspersion and juxtaposition index were derived from a spatially explicit land cover map, based on 10 m Sentinel 2 data for nine buffer zones of radius ranging from 50 m to 1000 m around each sampled plot. Redundancy analysis (RDA) was used to establish the relationships between the observed pest abundances and landscape metrics, elevation, and AEsZ. Landscape indicators achieved the highest correlation with the pest abundances within a 300 m radius (Adjusted R2 > 0.5). Whereas beyond 300 m landscape scale, the predictor variables resulted in weak relationships (Adjusted R2 < 0.5) between the pests abundance and landscape metrics. We noted a strong influence of elevation and adjacency to cropland on Antestia bug populations. Specifically, ABF populations were negatively correlated with low elevation, whereas ABT's were positively correlated with high elevation zone. On the other hand, CBB was strongly influenced by contiguous coffee patches, especially in UM1 and UM2. Therefore, we recommend reducing connectivity between coffee patches for the management of CBB, whereas further studies should be conducted to identify secondary hosts of Antestia bugs that should not be adjacent or within coffee stands. • Landscape indicators achieved the highest correlation with pest abundances within a 300 m landscape scale • Antestia bugs were strongly influenced by elevation gradient and adjacency to cropland. • Coffee berry borer was strongly influenced by contiguous coffee patches within a limited landscape scale of 100 m • Reducing the connectivity of coffee patches will be useful in managing coffee berry borer. • Further studies should be conducted to identify secondary hosts of Antestia bugs. [ABSTRACT FROM AUTHOR]

The oriental fruit fly Bactrocera dorsalis (Diptera: Tephritidae) is a major pest of fruit and vegetable production systems on several continents. The pest has invaded many countries, causing considerable impact on fruit production systems and commercialization. In this study we determined the relationship between temperature and development, survival and reproductive parameters of B. dorsalis on an artificial diet under laboratory conditions under 7 constant temperatures (10, 15, 20, 25, 30, 33 and 35 °C) with 70 ± 10% relative humidity and a photoperiod of L12:D12. We validated the laboratory results with a full life table analysis under semi-natural conditions in a screenhouse. We used the Insect Life Cycle Modeling (ILCYM) software for all mathematical models and simulations applied to all life history parameters. Bactrocera dorsalis completed its development at temperatures ranging between 15 and 33 °C with the mean developmental time of egg, larva, and pupa ranging between 1.46 and 4.31 days, 7.14–25.67 days, and 7.18–31.50 respectively. The models predicted temperatures ranging between 20 and 30 °C as favorable for development and survival, and 20 to 25 °C for optimal fecundity of B. dorsalis. Life table parameters showed the highest gross reproductive rate (GRR), net reproductive rate (R o), intrinsic rate of increase (r m), and finite rate of increase (λ) between 25 and 31 ᵒC while generation time (T) and doubling time (D t) were low at this interval. The effects of future climate change on B. dorsalis life history parameters were further investigated and the outcome from this study will help in the management of B. dorsalis in different agroecologies in the context of ongoing climate change. • Temperature affects the development and survival of Bactrocera dorsalis. • Temperature ranging between 20 and 30 ᵒC are optimal for the development and reproduction of Bactrocera dorsalis. • Non-linear models are suitable to predict the development and reproduction of Bactrocera dorsalis within temperature gradient. [ABSTRACT FROM AUTHOR]

Information on weed occurrence within croplands is vital but is often unavailable to support weeding practices and improve cropland productivity assessments. To date, few studies have been conducted to estimate and map weed abundances within agroecological systems from spaceborne images over wide-area landscapes, particularly for the genus Striga. Therefore, this study attempts to increase the detection capacity of Striga at subpixel size using spaceborne high-resolution imagery. In this study, a two-step classification approach was used to detect Striga (Striga hermonthica) weed occurrence within croplands in Rongo, Kenya. Firstly, multidate and multiyear Sentinel-2 (S2) data (2017 to 2018) were utilized to map cropland and non-cropland areas using the random forest algorithm within the Google Earth Engine. The non-cropland class was thereafter masked out from a single date S2 image of the 13th of December 2017. The remaining cropland area was then used in a subpixel multiple endmember spectral mixture analysis (MESMA) to detect Striga occurrence and infestation using endmembers (EMs) obtained from the in-situ hyperspectral data. The gathered in-situ hyperspectral data were resampled to the spectral waveband configurations of S2 and three representative EMs were inferred, namely: (1) Striga, (2) crop and other weeds, and (3) soil. Overall classification accuracies of 88% and 78% for the pixel-based cropland mapping and subpixel Striga detection were achieved, respectively. Furthermore, an F-score (0.84) and a root mean square error (0.0075) showed that the MESMA subpixel algorithm provides plausible results for predicting the relative abundance of Striga within each S2 pixel at a landscape scale. The capability of MESMA together with a cropland classification hierarchical approach was thus proven to be suited for Striga detection in a heterogenous agroecological system. These results can be used to guide in the adaptation, mitigation, and remediation of already infested areas, thereby avoiding further Striga infestation of new croplands. Unlabelled Image • African cropping systems hinder the spaceborne detection of Striga weeds • Remotely sensed spectral data often shadows analytical spectral characteristics • A cropland mask was used as fraction constraint in MESMA to enhance Striga detection • This integration successfully reduced spectral confusion and computation time • The method is plausible for Striga detection in complex agroecological systems [ABSTRACT FROM AUTHOR]