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Generalized Stressors on Hive and Forager Bee Colonies.
Elzinga, David C; Strickland, W Christopher.
Afiliación
  • Elzinga DC; Department of Mathematics and Statistics, University of Wisconsin-La Crosse, La Crosse, WI, 54601, USA. delzinga@uwlax.edu.
  • Strickland WC; Department of Mathematics, University of Tennessee Knoxville, Knoxville, TN, 37916, USA. delzinga@uwlax.edu.
Bull Math Biol ; 85(11): 112, 2023 10 12.
Article en En | MEDLINE | ID: mdl-37823943
ABSTRACT
Hive-forming bees play an integral role in promoting agricultural sustainability and ecosystem preservation. The recent worldwide decline of several species of bees, and in particular, the honeybee in the United States, highlights the value in understanding possible causes. Over the past decade, numerous mathematical models and empirical experiments have worked to understand the causes of colony stress, with a particular focus on colony collapse disorder. We integrate and enhance major mathematical models of the past decade to create a single, analytically tractable model using a traditional disease modeling framework that incorporates both lethal and sublethal stressors. On top of this synthesis, a major innovation of our model is the generalization of stressor attributes including their transmissibility, impairment level, lethality, duration, and temporal-occurrence. Our model is validated against numerous emergent, biological characteristics and demonstrates that precocious foraging and labor destabilization can produce colony collapse disorder. The thresholds for these phenomena to occur depend on the characteristics and timing of the stressor, thus motivating further empirical and theoretical studies into stressor characteristics.
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Texto completo: 1 Base de datos: MEDLINE Asunto principal: Ecosistema / Modelos Biológicos Tipo de estudio: Prognostic_studies Límite: Animals Idioma: En Revista: Bull Math Biol Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Ecosistema / Modelos Biológicos Tipo de estudio: Prognostic_studies Límite: Animals Idioma: En Revista: Bull Math Biol Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos