Advancing Integrated Pest Management for Dermanyssus gallinae in laying hen facilities

Pest and diseases in agricultural systems reduce the yield and quality of available food and feed worldwide. To meet the global growing demand for these products, losses should be reduced, preferably in a sustainable way. Integrated Pest Management (IPM) is a sustainable method that aims to minimize economic losses due to pests and diseases. IPM is generally based on eight steps: 1) prevention, 2) monitoring, 3) Decision‐making based on monitoring and thresholds, 4) use of non‐chemical methods, 5) pesticide selection, 6) reduced pesticide use, 7) anti‐resistance strategies, and 8) evaluation. With these steps, it is possible to prevent and control pests and diseases whilst deploying pesticides only as a last resort, thus reducing issues with pesticide contamination and resistance. Implementation of IPM by farmers increases when it is clear that it is compatible with existing farm processes and that it results in benefits for them. Successful IPM is most commonly applied against pests and diseases in crop production. When comparing the number of research articles on IPM in crop production with the number of research articles on IPM in animal production, it becomes clear that a paucity of scientific papers have been published on the latter. In laying hen facilities, for example, the application of all but basic IPM is still rare, even though the benefits of IPM have been described for poultry pests and disease vectors. In laying hen facilities Dermanyssus gallinae (PRM=poultry red mite), an hematophagous parasite, is common in many parts of the world. This mite is hard to control and negatively affects hen health, ‐welfare and farm economics, with estimated costs of infestation reaching 130 million euro per year in Europe. Currently, implementation of IPM for D. gallinae in laying hen facilities is limited to some combination of cleaning between flocks, limited preventive measures, and application of chemically or physically acting products. Implementation of more advanced IPM programmes for D. gallinae should therefore be considered to improve control prospects for this pest in laying hen facilities. This thesis focuses on the knowledge necessary for advancing IPM for D. gallinae in laying hen facilities. More specifically it focuses on prevention, monitoring and population modelling of this significant pest, with preventive measures and monitoring being key in advancing IPM per se. Knowledge assessment. To develop IPM for D. gallinae in laying hen facilities, biological and ecological knowledge of D. gallinae and knowledge of the effects of biotic and a‐biotic factors on this pests’ population development are required (Chapter 2). Therefore, a seminar was organized with eighteen D. gallinae researchers, from eight different European countries, with the aim of amassing existing expertise. This seminar gave insight into the current knowledge and knowledge gaps, regarding D. gallinae, also informing future perspectives and required developments for improving control of D. gallinae in laying hen facilities. During four sessions, the researchers present discussed lifecycle issues, effects of D. gallinae on hen and egg production, monitoring methods for D. gallinae infestations in laying hen facilities and control methods for D. gallinae in laying hen facilities. It was concluded that, where the D. gallinae lifecycle is concerned, a lot is still unknown about the mites feeding behaviour and preferences, mating behaviour, survival and conditions required for reproduction, host finding, aggregation cues, and attractant and repellent substances. When focusing on the effects of D. gallinae on the hen and on egg production it was agreed that a D. gallinae infestation is likely to result in higher water intake, lower egg production, lower feed conversion, increase of the immune response and reduced feather quality. It was also suggested that these effects may be hen genotype dependent, and further noted that effects are rarely quantified and need further investigation. Though monitoring was considered to be most important to improve control of D. gallinae, it was concluded that the available monitoring methods only indicate trends and a robust monitoring plan is lacking. The participants considered heating the hen house combined with a chemical treatment to be the most promising control method. Future promising developments for control of D. gallinae were considered to be use of vaccination, predatory mites and entomopathogenic fungi. The effects of D. gallinae on human health were not extensively discussed, but it was concluded that D. gallinae can be of medical significance, either directly via reaction to mite bites, or indirectly via human exposure to the chemicals used to control D. gallinae. Prevention. To acquire knowledge on the routes of introduction and spread of D. gallinae in laying hens facilities, the Hazard Analysis and Critical Control Points (HACCP) system was used (Chapter 3). The structure of this system allows the user to identify the risk factors and the critical control points for the introduction and spread of pathogens and parasites. This method was further used to identify preventive and corrective actions against D. gallinae. Four experts identified 41 hazards for introduction and spread of D. gallinae in laying hen facilities. To prevent these hazards, these experts made several suggestions for corrective actions. The risks of 41 hazards were calculated by multiplying the likelihood (1= occurring seldomly/theoretically; 2= occurring approximately once a year; 3= occurring repeatedly/more than once a year) by the severity (1 = low / single place in the facility becomes infested with D. gallinae; 2= moderate/ facility becomes infested at more than one location; 3= high/ D. gallinae infestation occurs at almost all places within the laying hen facility) of infestation. Hazards with a risk above 3, or with a severity of 3, were regarded as Critical Control Points (CCP’s). The CCP’s with the highest risks (risk of 6 and higher) for introduction of D. gallinae in laying hen facilities were: introduction of new flocks, containers and crates, the farmer and their employees. The CCP’s with the highest risks (risk of 6 and higher) for spread of D. gallinae between laying hen facilities were mice, rats and flies, wild birds, the feeding system, shared material and equipment, the egg conveyer belt, manure aeration pipes, removal of cadavers, visitors and external personnel, the farmer and their employees. The critical limits, a procedure step of the HACCP system which will be followed by a corrective action when the limit is exceeded, could not be determined as a result of lack of knowledge about thresholds. Subsequently, suggestions were made for monitoring the mite population and for documentation and validation. A checklist was devised using the corrective action from the CCP’s with the highest risks. This management tool for layer farmers was evaluated by UK and Dutch layer farmers as feasible and useful. Monitoring. The approach of Reflexive Interactive Design (RIO) was used to design an automated monitoring tool for D. gallinae, including an automated mite detection sensor (Chapter 6). The approach generated effective and technically feasible solutions for the key functions of the automated mite detection sensor, these being 1) the assessment of the D. gallinae population, 2) localizing the location and assessing the time of detection and 3) removal of mites from the detection area. Three different design concepts were designed using these solutions. As an additional, albeit proven essential step to the RIO approach, the main solutions were tested with live mites ensuring the alignment of solutions with the biology and behaviour of D. gallinae in vivo. A combination of the best solutions were developed in two different prototypes. These prototypes were subsequently tested in the laboratory and on farm. The prototype situated under the perch, with a through beam sensor and a pump to remove mites from the sensor after recording, was the most successful model. The designed automated mite detection sensor, or automated mite counter, for D. gallinae was subsequently validated in experimental laying hen cages with live birds and a growing population of D. gallinae (Chapter 5). The study resulted in 17 data points, each being a combination of ‘number of mites counted’ by the automated mite counter and the ‘number of mites present’ in the experimental laying hen cages. The regression line between the ‘number of mites counted’ and the ‘number of mites present’ demonstrated that the automated mite counter was able to track the D. gallinae population effectively. Population modelling. Step 2 of IPM describes not only pest monitoring in the field, but also ‘scientifically sound warning, forecasting and early diagnosis systems, where feasible, as well as the use of advice from professionally qualified advisors’. To advance this step for D. gallinae we developed and demonstrated an operational model, forecasting the mite population dynamics and evaluating and forecasting the effect of a treatment application for D. gallinae in laying hen facilities. For IPM this model and the required inputs need to be 1) labour‐extensive with minimal staff input, preferably automatically implementing “real time” measurement data into models; 2) operational, providing easily interpretable data, forecasting pest population dynamics and the moment a threshold will be exceeded; 3) able to compensate for different locations and time‐specific‐interactions and variables (e.g. management and temperature), enabling the handling of variability of the parameters of interest; 4) able to identify pest hotspots; 5) able to estimate and forecast treatment efficacy; and 6) applicable for different monitoring methods and therefore able to correct for monitoring measurement errors. Prior to the development of the population dynamics model a high variation in population growth was found which could be only partly explained by temperature, flock age, treatment, and compartment/laying hen facility. A substantial part of the total variation remained unexplained, or was found to be temporal. As a result of this partly temporal variation, a dynamic approach was suggested to improve the forecasting quality of a population dynamics model. With the input of population monitoring data, temperature data and information of the dates of any D. gallinae treatment interventions, the developed model was able to forecast the population dynamics of D. gallinae post treatment and without treatment while compensating for location and time specific interactions, handling the variability of the parameters. Moreover, this population dynamics model was able to forecast the D. gallinae population using data from different monitoring methods. Together with the models compatibility with different housing systems and its ability to forecast the mite population dynamics (requiring only three relative easy obtainable parameters), this model is an improvement over existing approaches for forecasting D. gallinae that could contribute to steps 2 and 8 of IPM for D. gallinae in laying hen facilities. The results from this study directly facilitate advanced IPM programmes for D. gallinae in laying facilities. The new ‘products’ developed are tools for prevention, monitoring, forecasting population dynamics and evaluating treatment effects, representing the requirements of IPM steps 1, 2, and 8. Indirectly the results may accelerate the development of new control measures, with knowledge acquired through use of the developed products it also is likely to contribute to IPM steps 3, 4, 6 and 8 in the future; e.g. the determination of an action threshold, and a tool advising farmers on the most effective and economic time for applying a corrective action or hotspot treatment for D. gallinae. With the obtained knowledge and new products implemented to control D. gallinae in laying hen farms, major advances can be made in IPM for this pest. More specifically, as a result of this work IPM for D. gallinae in laying hen facilities can be advanced by the identification of preventative control measures, the development of an automated monitoring tool and a model forecasting mite population dynamics and evaluating applied treatments. Consequently, the results of this study can be expected to improve hen health, welfare and farm economics for the egg production industry. In the future, advances in other IPM programmes can be expected when the obtained knowledge, tools and methods are transferred to other pest species in multiple sectors.