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Identifying and understanding behavioral resistance to insecticides is vital for maintaining global food security, public health, and ecological balance. Behavioral resistance has been documented to occur in a multitude of insect taxa dating back to the 1940s, but has not received significant research attention due primarily to the complexities of studying insect behavior and a lack of any clear definition of behavioral resistance. In recent years, a systematic effort to investigate the mechanism(s) of behavioral resistance in pest taxa (e.g. the German cockroach and the house fly) has been undertaken. Here, we practically define behavioral resistance, describe the efforts taken by research groups to elucidate resistance mechanisms, and provide insight on designing appropriate bioassays for investigating behavioral resistance mechanisms in the future.

Effectively promoting the stability and quality of ecosystem services involves the successful management of domesticated species and the control of introduced species. In the pollinator literature, interest and concern regarding pollinator species and pollinator health dramatically increased in recent years. Concurrently, the use of loaded terms when discussing domesticated and non-native species may have increased. As a result, pollinator ecology has inherited both the confusion associated with invasion biology’s lack of a standardized terminology to describe native, managed, or introduced species as well as loaded terms with very strong positive or negative connotations. The recent explosion of research on native bees and alternative pollinators, coupled with the use of loaded language, has led to a perceived divide between native bee and managed bee researchers. In comparison, the bird literature discusses the study of managed (poultry) and non-managed (all other birds) species without an apparent conflict with regard to the use of terms with strong connotations or sentiment. Here, we analyze word usage when discussing non-managed and managed bee and bird species in 3614 ecological and evolutionary biology papers published between 1990 and 2019. Using time series analyses, we demonstrate how the use of specific descriptor terms (such as wild, introduced, and exotic) changed over time. We then conducted co-citation network analyses to determine whether papers that share references have similar terminology and sentiment. We predicted a negative language bias towards introduced species and positive language bias towards native species. We found an association between the term invasive and bumble bees and we observed significant increases in the usage of more ambiguous terms to describe non-managed species, such as wild. We detected a negative sentiment associated with the research area of pathogen spillover in bumble bees, which corroborates the subjectivi

The northern fowl mite, Ornithonyssus sylviarum, is one of the most common and damaging ectoparasites of poultry. As an obligate blood feeding mite, the northern fowl mite can cause anaemia, slower growth, and decreased egg production of parasitized birds. However, the impact of mites or other ectoparasites on hen behaviour or welfare is not well studied. Here, we use activity sensors (three-axis accelerometers) affixed to individual birds to continuously record hen movement before, during, and after infestation with mites. Movements recorded by sensors were identified to specific bird behaviours through a previously trained algorithm, with frequency of these behaviours recorded for individual birds. Hen welfare was also determined before, during, and after mite infestation of hens using animal-based welfare metrics. Northern fowl mites significantly increased hen preening behaviour and resulted in increased skin lesions of infested birds.

The northern fowl mite, Ornithonyssus sylviarum, is one of the most common and damaging ectoparasites of poultry. As an obligate blood feeding mite, the northern fowl mite can cause anaemia, slower growth, and decreased egg production of parasitized birds. However, the impact of mites or other ectoparasites on hen behaviour or welfare is not well studied. Here, we use activity sensors (three-axis accelerometers) affixed to individual birds to continuously record hen movement before, during, and after infestation with mites. Movements recorded by sensors were identified to specific bird behaviours through a previously trained algorithm, with frequency of these behaviours recorded for individual birds. Hen welfare was also determined before, during, and after mite infestation of hens using animal-based welfare metrics. Northern fowl mites significantly increased hen preening behaviour and resulted in increased skin lesions of infested birds.

Time series classification is an important task in its own right, and it is often a precursor to further downstream analytics. To date, virtually all works in the literature have used either shape-based classification using a distance measure or feature-based classification after finding some suitable features for the domain. It seems to be underappreciated that in many datasets it is the case that some classes are best discriminated with features, while others are best discriminated with shape. Thus, making the shape vs. feature choice will condemn us to poor results, at least for some classes. In this work, we propose a new model for classifying time series that allows the use of both shape and feature-based measures, when warranted. Our algorithm automatically decides which approach is best for which class, and at query time chooses which classifier to trust the most. We evaluate our idea on real world datasets and demonstrate that our ideas produce statistically significant improvement in classification accuracy.

Poultry farms are a major contributor to the human food chain. However, around the world, there have been growing concerns about the quality of life for the livestock in poultry farms; and increasingly vocal demands for improved standards of animal welfare. Recent advances in sensing technologies and machine learning allow the possibility of monitoring birds, and employing the lessons learned to improve the welfare for all birds. This task superficially appears to be easy, yet, studying behavioral patterns involves collecting enormous amounts of data, justifying the term Big Data. Before the big data can be used for analytical purposes to tease out meaningful, well-conserved behavioral patterns, the collected data needs to be pre-processed. The pre-processing refers to processes for cleansing and preparing data so that it is in the format ready to be analyzed by downstream algorithms, such as classification and clustering algorithms. However, as we shall demonstrate, efficient pre-processing of chicken big data is both non-trivial and crucial towards success of further analytics., Comment: arXiv admin note: text overlap with arXiv:1811.03149

Poultry farms are an important contributor to the human food chain. Worldwide, humankind keeps an enormous number of domesticated birds (e.g. chickens) for their eggs and their meat, providing rich sources of low-fat protein. However, around the world, there have been growing concerns about the quality of life for the livestock in poultry farms; and increasingly vocal demands for improved standards of animal welfare. Recent advances in sensing technologies and machine learning allow the possibility of automatically assessing the health of some individual birds, and employing the lessons learned to improve the welfare for all birds. This task superficially appears to be easy, given the dramatic progress in recent years in classifying human behaviors, and given that human behaviors are presumably more complex. However, as we shall demonstrate, classifying chicken behaviors poses several unique challenges, chief among which is creating a generalizable dictionary of behaviors from sparse and noisy data. In this work we introduce a novel time series dictionary learning algorithm that can robustly learn from weakly labeled data sources.

BackgroundNorthern fowl mites (Ornithonyssus sylviarum) are obligate hematophagous ectoparasites of both feral birds and poultry, particularly chicken layers and breeders. They complete their entire life-cycle on infested birds while feeding on blood. Infestations of O. sylviarum are difficult to control and resistance to some chemical classes of acaricides is a growing concern. The contact susceptibility of O. sylviarum to a new active ingredient, fluralaner, was evaluated, as well as other compounds representative of the main chemical classes commonly used to control poultry mite infestations in Europe and the USA.MethodsSix acaricides (fluralaner, spinosad, phoxim, propoxur, permethrin, deltamethrin) were dissolved and serially diluted in butanol:olive oil (1:1) to obtain test solutions used for impregnation of filter paper packets. A carrier-only control was included. Thirty adult northern fowl mites, freshly collected from untreated host chickens, were inserted into each packet for continuous compound exposure. Mite mortality was assessed after incubation of the test packets for 48 h at 75% relative humidity and a temperature of 22 °C.ResultsAdult mite LC50 /LC99 values were 2.95/8.09 ppm for fluralaner, 1587/3123 ppm for spinosad, 420/750 ppm for phoxim and 86/181 ppm for propoxur. Permethrin and deltamethrin LC values could not be calculated due to lack of mortality observed even at 1000 ppm.ConclusionsNorthern fowl mites were highly sensitive to fluralaner after contact exposure. They were moderately sensitive to phoxim and propoxur, and less sensitive to spinosad. Furthermore, the tested mite population appeared to be resistant to the pyrethroids, permethrin and deltamethrin, despite not being exposed to acaricides for at least 10 years.

BackgroundNorthern fowl mites (Ornithonyssus sylviarum) are obligate hematophagous ectoparasites of both feral birds and poultry, particularly chicken layers and breeders. They complete their entire life-cycle on infested birds while feeding on blood. Infestations of O. sylviarum are difficult to control and resistance to some chemical classes of acaricides is a growing concern. The contact susceptibility of O. sylviarum to a new active ingredient, fluralaner, was evaluated, as well as other compounds representative of the main chemical classes commonly used to control poultry mite infestations in Europe and the USA.MethodsSix acaricides (fluralaner, spinosad, phoxim, propoxur, permethrin, deltamethrin) were dissolved and serially diluted in butanol:olive oil (1:1) to obtain test solutions used for impregnation of filter paper packets. A carrier-only control was included. Thirty adult northern fowl mites, freshly collected from untreated host chickens, were inserted into each packet for continuous compound exposure. Mite mortality was assessed after incubation of the test packets for 48 h at 75% relative humidity and a temperature of 22 °C.ResultsAdult mite LC50 /LC99 values were 2.95/8.09 ppm for fluralaner, 1587/3123 ppm for spinosad, 420/750 ppm for phoxim and 86/181 ppm for propoxur. Permethrin and deltamethrin LC values could not be calculated due to lack of mortality observed even at 1000 ppm.ConclusionsNorthern fowl mites were highly sensitive to fluralaner after contact exposure. They were moderately sensitive to phoxim and propoxur, and less sensitive to spinosad. Furthermore, the tested mite population appeared to be resistant to the pyrethroids, permethrin and deltamethrin, despite not being exposed to acaricides for at least 10 years.