Agricultural intensification (AI) is a great threat to biodiversity and its negative effects on species richness of different communities have been repea'/> Community variability in aphid parasitoids versus predators in response to agricultural intensification
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Community variability in aphid parasitoids versus predators in response to agricultural intensification

机译:应对农业集约化的蚜虫寄生虫与捕食者的群落变异性

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Agricultural intensification (AI) is a great threat to biodiversity and its negative effects on species richness of different communities have been repeatedly shown. The effects of AI on community composition and variability, however, are important for assessing the predictability of community responses, but have rarely been studied simultaneously and across different taxonomic groups. In this study, we focused on parasitoids (primary and secondary) and predators (hoverflies and carabid beetles) of aphids in winter wheat fields with contrasting AI regimes (low AI, i.e. organic fields in structurally complex landscapes vs. high AI, i.e. conventional fields in structurally simple landscapes). We found divergence in species composition of more specialised, low-dispersing primary and secondary parasitoids within high AI fields, probably due to the disruption of the exchanges of species between local populations in structurally simple landscapes. In contrast, species composition of less specialised, highly dispersing carabid beetles and hoverflies converged in fields with high AI, where they were characterised by the dominance of a single, vagile species adapted to high land-use conditions. Furthermore, temporal community shifts were only pronounced in primary parasitoids and hoverflies, with higher temporal changes in fields with high AI in primary parasitoids. Collectively, our results illustrate that environmental homogenisation due to AI does not necessarily induce spatio-temporal homogenisation of communities, but rather can have contrasting effects on more specialised, low-dispersive parasitoids versus more generalised, high-dispersive predators, thereby demonstrating great differences in the predictability of responses to AI among aphid natural enemies.
机译:农业集约化(AI)对生物多样性构成了巨大威胁,并且已反复表明其对不同社区物种丰富度的负面影响。然而,人工智能对社区组成和变异性的影响对于评估社区反应的可预测性很重要,但是很少同时进行和在不同的分类学组中进行研究。在这项研究中,我们重点研究了具有不同AI体制(低AI,即结构复杂景观中的有机田与高AI,即常规田)的冬小麦田间蚜虫的拟寄生物(主要和次要)和捕食者(蚜虫和甲壳虫)。在结构简单的景观中)。我们发现,在高AI领域内,更专业,分布较分散的初级和次级寄生类动物的物种组成存在差异,这可能是由于结构简单的景观中本地种群之间的物种交换受到干扰所致。相比之下,较少专业化,高度分散的甲虫和蚜虫的物种组成在具有较高AI的领域汇聚,它们的特征是适应高土地利用条件的单一易变物种的优势。此外,时间群落的变化仅在原发性寄生虫和盘旋蝇中才明显,而在原发性寄生虫中具有较高AI的田地具有更高的时间变化。总的来说,我们的研究结果表明,人工智能造成的环境同质化并不一定会引起社区的时空同质化,而是对更专业,低分散性的拟寄生物与更广义,高分散性的捕食者具有相反的影响,从而证明了两者之间的巨大差异。蚜虫天敌对AI反应的可预测性。

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