Population dynamics of a poultry hematophagous mite: characterization of the population growth and identification of factors of its slowdown using closed mesocosms

BACKGROUND

A thorough knowledge of the population dynamics of pests and of the main factors affecting population growth is an important prerequisite for the development of effective control strategies. Failures of various treatments aimed at regulating populations of Dermanyssus gallinae are regularly reported in poultry farms and pullulations occur very quickly after first detection. To finely characterize population dynamics of D. gallinae, and to identify the factors modulating population growth, we conducted two successive multi-generation experiments using closed mesocosms equipped with or without automatic counters and housing a host full- or part-time (three nights per week).

RESULTS

Population growth was very rapid and the adult to juvenile ratio very different from the prediction by a mathematical model. A male-biased sex ratio was observed in some mesocosms from 21 days and in most mesocosms from 35 days of population growth originating from an inoculum of adult females. A dramatic slowdown in growth was measured in mesocosms equipped with trackers, where the mites' path to the host was constrained. The slowdown in population growth induced by the intermittent presence of the host compared to its full-time presence was much less marked.

CONCLUSION

These findings suggest avenues of research for new management methods. They question the relevance of a critical threshold based on traditional trap monitoring to manage D. gallinae. Our results highlight a unique characteristic of D. gallinae that makes it a recalcitrant case to threshold-based practices recommended for integrated pest management (IPM) against other arthropod pests. The dramatic effect of a physical constraint for the mite to access the host (unnatural constrained path) confirms an observation made in 1917 and is a reason to design perches that are less conducive to parasite traffic. © 2022 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Shift-Invariant Canonical Polyadic Decomposition of Complex-Valued Multi-Subject fMRI Data With a Phase Sparsity Constraint

Canonical polyadic decomposition (CPD) of multi-subject complex-valued fMRI data can be used to provide spatially and temporally shared components among groups with both magnitude and phase information. However, the CPD model is not well formulated due to the large subject variability in the spatial and temporal modalities, as well as the high noise level in complex-valued fMRI data. Considering that the shift-invariant CPD can model temporal variability across subjects, we propose to further impose a phase sparsity constraint on the shared spatial maps to denoise the complex-valued components and to model the inter-subject spatial variability as well. More precisely, subject-specific time delays are first estimated for the complex-valued shared time courses in the framework of real-valued shift-invariant CPD. Source phase sparsity is then imposed on the complex-valued shared spatial maps. A smoothed l₀ norm is specifically used to reduce voxels with large phase values after phase de-ambiguity based on the small phase characteristic of BOLD-related voxels. The results from both the simulated and experimental fMRI data demonstrate improvements of the proposed method over three complex-valued algorithms, namely, tensor-based spatial ICA, shift-invariant CPD and CPD without spatiotemporal constraints. When comparing with a real-valued algorithm combining shift-invariant CPD and ICA, the proposed method detects 178.7% more contiguous task-related activations.