Bumble-BEEHAVE: A systems model for exploring multifactorial causes of bumblebee decline at individual, colony, population and community level.
Bumble-BEEHAVE: A systems model for exploring multifactorial causes of bumblebee decline at individual, colony, population and community level.
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Bumble-Beehave：一种用于探索个体，殖民地，人口和社区层面大黄蜂下降的多因素原因的系统模型。
DOI：
10.1111/1365-2664.13165
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发表时间：
2018-11
期刊：
影响因子：
--
通讯作者：
Osborne JL
中科院分区：
文献类型：
--
作者：
Becher MA;Twiston-Davies G;Penny TD;Goulson D;Rotheray EL;Osborne JL
包括熊蜂在内的传粉者在世界范围内的减少归因于多种压力因素，如栖息地丧失、资源可用性、新出现的病毒和寄生虫、暴露于农药以及气候变化，这些因素在不同的空间和时间尺度上起作用。解开这些压力源的个体和相互作用的影响，并了解它们在个体，群体和群体水平上的影响是系统生态学的挑战。对所有组合和背景进行实证检验是不可行的。需要一个多层次系统模型（个体-群体-群体-社区）来探索压力下群体和社区的恢复机制。我们提出了一个模型，可以模拟生长，行为和生存的六个英国大黄蜂物种生活在任何映射的景观。Bumble-BEEHAVE以基于代理的方法模拟大黄蜂在现实景观中的殖民地发展，以研究多种压力源如何影响蜜蜂数量和种群动态。我们提供广泛的文件，包括敏感性分析和验证，基于文献中的数据。该模型可免费获得，具有灵活的设置，并包括用户手册，以确保研究人员，农民，政策制定者，非政府组织或其他相关方可以使用。模型结果比较以及与经验数据的个人觅食行为，群体的生长和繁殖，估计巢密度。模拟农药暴露引起的生殖抑制的影响表明，在这个模型中捕获的复杂的反馈机制预测更高的殖民地的应变能力比以前的，简单的模型。 合成与应用。Bumble-BEEHAVE模型代表了以空间明确的方式预测大黄蜂种群动态的重要一步。它使研究人员能够了解影响大黄蜂生存的多种压力源的个体和相互作用的影响，以及可能缓冲殖民地对环境压力的反馈机制，或者确实导致螺旋式殖民地崩溃。该模型可用于帮助设计的现场实验，风险评估，为保护和农业决策提供信息，并在景观尺度分配定制的管理建议。Bumble-BEEHAVE模型代表了以空间明确的方式预测大黄蜂种群动态的重要一步。它使研究人员能够了解影响大黄蜂生存的多种压力源的个体和相互作用的影响，以及可能缓冲殖民地对环境压力的反馈机制，或者确实导致螺旋式殖民地崩溃。该模型可用于帮助设计的现场实验，风险评估，为保护和农业决策提供信息，并在景观尺度分配定制的管理建议。
World‐wide declines in pollinators, including bumblebees, are attributed to a multitude of stressors such as habitat loss, resource availability, emerging viruses and parasites, exposure to pesticides, and climate change, operating at various spatial and temporal scales. Disentangling individual and interacting effects of these stressors, and understanding their impact at the individual, colony and population level are a challenge for systems ecology. Empirical testing of all combinations and contexts is not feasible. A mechanistic multilevel systems model (individual‐colony‐population‐community) is required to explore resilience mechanisms of populations and communities under stress. We present a model which can simulate the growth, behaviour and survival of six UK bumblebee species living in any mapped landscape. Bumble‐BEEHAVE simulates, in an agent‐based approach, the colony development of bumblebees in a realistic landscape to study how multiple stressors affect bee numbers and population dynamics. We provide extensive documentation, including sensitivity analysis and validation, based on data from literature. The model is freely available, has flexible settings and includes a user manual to ensure it can be used by researchers, farmers, policy‐makers, NGOs or other interested parties. Model outcomes compare well with empirical data for individual foraging behaviour, colony growth and reproduction, and estimated nest densities. Simulating the impact of reproductive depression caused by pesticide exposure shows that the complex feedback mechanisms captured in this model predict higher colony resilience to stress than suggested by a previous, simpler model. Synthesis and applications. The Bumble‐BEEHAVE model represents a significant step towards predicting bumblebee population dynamics in a spatially explicit way. It enables researchers to understand the individual and interacting effects of the multiple stressors affecting bumblebee survival and the feedback mechanisms that may buffer a colony against environmental stress, or indeed lead to spiralling colony collapse. The model can be used to aid the design of field experiments, for risk assessments, to inform conservation and farming decisions and for assigning bespoke management recommendations at a landscape scale. The Bumble‐BEEHAVE model represents a significant step towards predicting bumblebee population dynamics in a spatially explicit way. It enables researchers to understand the individual and interacting effects of the multiple stressors affecting bumblebee survival and the feedback mechanisms that may buffer a colony against environmental stress, or indeed lead to spiralling colony collapse. The model can be used to aid the design of field experiments, for risk assessments, to inform conservation and farming decisions and for assigning bespoke management recommendations at a landscape scale.
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影响因子：
2.7
作者：
Goulson D
通讯作者：
Goulson D
DOI：
10.1111/1365-2664.12112
发表时间：
2013-08
期刊：
The Journal of applied ecology
影响因子：
--
作者：
Becher MA;Osborne JL;Thorbek P;Kennedy PJ;Grimm V
通讯作者：
Grimm V
影响因子：
3.1
作者：
Becher, M. A.;Grimm, V.;Knapp, J.;Horn, J.;Twiston-Davies, G.;Osborne, J. L.
通讯作者：
Osborne, J. L.
影响因子：
2.2
作者：
Cresswell, James E.
通讯作者：
Cresswell, James E.
农药减少了大黄蜂菌落的启动，并增加了人口灭绝的可能性。
影响因子：
16.8
作者：
Baron GL;Jansen VAA;Brown MJF;Raine NE
通讯作者：
Raine NE