Behavioural landscape ecology: scaling-up from individuals to populations under rapid environmental changes / Écologie comportementale à l'échelle du paysage: de l'individu à la population lors de changements rapides des conditions environnementales

当个体未能认识到与特定资源或行为相关的感知和实际健康结果之间的不匹配时，快速的环境变化可能会导致适应不良的行为反应。事实上，快速的环境变化可以改变环境线索和健康之间的历史关联，并导致个体参与最终降低其繁殖成功或生存的行为。这种不适应的反应被称为进化陷阱，当与栖息地选择有关时，被称为生态陷阱。野生蜜蜂和农田鸟类，特别是空中食虫鸟类，在最近发生在北美和欧洲的农业集约化(AI)的同时，显示出种群的急剧下降。这种人工智能的快速，以及精耕细作地区保留了天然草原和“古老”农田的栖息地属性的事实，可能有利于使用“现代”农田的动物做出不适应的行为反应。事实上，至少在生长季节的早期，耕地很可能呈现出类似于草原等自然开阔栖息地的环境条件。因此，耕种的田地可能会吸引个人定居在最终因机械处理(如收割)或农药使用产生的毒理和营养效应而质量突然下降的地点。更糟糕的是，耕地甚至可以比其他栖息地产生更大的吸引力，尽管它是有害的。因此，人工智能具有创造进化陷阱的潜力，如果扩散不能帮助生物体避免或逃脱这种陷阱，那么个体和种群的表现必须取决于表型可塑性和/或进化反应。我的学生和我将研究人工智能如何影响扩散行为，并导致燕子树偏离理想的栖息地选择。我们还将评估景观组成线索的可靠性，以此作为猎物可获得性和杀虫剂对这种不断下降的空中杀虫剂的污染的指标。此外，我们将模拟当地树燕种群趋势和北美各地杀虫剂使用变化之间的时空动态。我们还将调查人工智能如何影响熊蜂群体的生活史、生产力和存活率，以及评估其形态上的表型可塑性是否有助于熊蜂缓解人工智能的影响。填补这些知识空白是必要的，以便提高我们预测进化陷阱更有可能发生在哪里、何时和如何发生，以及如何避免或减轻其影响的能力。

Rapid environmental changes can lead to maladaptive behavioral responses when individuals fail to recognise the mismatch between perceived and actual fitness outcomes associated to specific resources or behaviors. Indeed, rapid environmental changes can alter the historical correlations between environmental cues and fitness, and lead individuals to engage into behaviors that ultimately lower their breeding success or survival. Such maladaptive responses have been referred to as evolutionary traps, and when related to habitat selection, as ecological traps.Wild bees and farmland birds, particularly aerial insectivorous ones, show strong population declines coinciding with the recent agricultural intensification (AI) that occurred in North America and Europe. The rapidity of this AI and the fact that intensively cultivated areas retain habitat attributes of natural grasslands and “ancient” farmlands are likely conducive to maladaptive behavioral responses by animals using “modern” farmlands. Indeed, cultivated fields are likely to present environmental conditions analogous to those found in natural open habitats such as grasslands, at least early in the growing season. Cultivated fields may thereby draw individuals to settle in sites which eventually decrease abruptly in quality because of mechanical treatments, such as harvesting, or toxicological and trophic effects resulting from pesticide applications. Worse, cultivated fields could even exert a greater attraction than alternative habitats despite being detrimental. Hence, AI has the potential to create evolutionary traps and if dispersal cannot help organisms avoid or escape such traps, then individual performance as well as that of their populations must depend on phenotypic plasticity and/or on evolutionary responses.My students and I will investigate how AI can influence dispersal behavior and cause departures from “ideal” habitat selection in the Tree Swallow. We will also assess the reliability of landscape composition cues as indicators of prey availability and contamination by pesticides for this declining aerial insectivore. In addition, we will model the spatiotemporal dynamics between local population trends of Tree Swallows and local changes in pesticide use across North America. We will also investigate how AI affects the life history, productivity and survival of bumblebee colonies, as well as assess if phenotypic plasticity in their morphology could help bumblebees mitigate the impacts of AI. Filling such knowledge gaps is necessary in order to improve our ability to predict where, when, and how evolutionary traps are more likely to occur and how their impacts can be avoided or mitigated.