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将生物学融入入侵物种管理是根除成功的关键原则:以澳大利亚北部的黄疯蚁(Anoplolepis gracilipes)为例

Integrating biology into invasive species management is a key principle for eradication success: the case of yellow crazy ant Anoplolepis gracilipes in northern Australia.

作者信息

Hoffmann B D

机构信息

CSIRO,Tropical Ecosystems Research Centre,PMB 44 Winnellie NT 0822,Australia.

出版信息

Bull Entomol Res. 2015 Apr;105(2):141-51. doi: 10.1017/S0007485314000662. Epub 2014 Sep 12.

DOI:10.1017/S0007485314000662
PMID:25212433
Abstract

The lack of biological knowledge of many invasive species remains as one of the greatest impediments to their management. Here I detail targeted research into the biology of the yellow crazy ant Anoplolepis gracilipes within northern Australia and detail how such knowledge can be used to improve the management outcomes for this species. I quantified nest location and density in three habitats, worker activity over 24 h, infestation expansion rate, seasonal variation of worker abundance and the timing of production of sexuals. Nests were predominantly (up to 68%) located at the bases of large trees, indicating that search efforts should focus around tree bases. Nest density was one nest per 22, 7.1 and 6.3 m2 in the three habitats, respectively. These data form the baselines for quantifying treatment efficacy and set sampling densities for post-treatment assessments. Most (60%) nests were underground, predominantly (89%) occurring in an open area rather than underneath a rock or log. Some seasonality was evident for nests within leaf litter, with most (83%) occurring during the 'wet season' (October-March). Of the underground nests, most were shallow, with 44% being less than 10 cm deep, and 67% being less than 20 cm deep. Such nest location and density information serves many management purposes, for improving detection, mapping and post-treatment assessments, and also provided strong evidence that carbohydrate supply was a major driver of A. gracilipes populations. Just over half of the nests (56%) contained queens. Of the 62 underground nests containing queens, most queens (80%) were located at the deepest chamber. When queens were present, most often (38%) only one queen was present, the most being 16. Queen number per nest was the lowest in July and August just prior to the emergence of virgin queens in September, with queen numbers then remaining steadily high until April. Nothing is known for any ant species about how the queen number per nest/colony affects treatment efficacy, but further research would no doubt yield important breakthroughs for treating ants. Activity occurred predominantly nocturnally, ceasing during mid-day. These activity data determined the critical threshold above which work must be conducted to be considered reliable, and also suggests that treatments are best applied in the afternoon. Total brood production peaked in February and was the lowest around August and September. These abundance data form the baselines for quantifying treatment efficacy, and may have implications for treatment efficacy. Males were found every month, predominantly between August and November. Queen pupae were found in September. The reproductive timing of sexuals determines the treatment schedule. Targeted, site-specific research such as that described here should be an integral part of any eradication program for invasive species to design knowledge-based treatment protocols and determine assessment benchmarks.

摘要

对许多入侵物种缺乏生物学认识,仍然是对其进行管理的最大障碍之一。在此,我详细介绍了针对澳大利亚北部黄疯蚁(Anoplolepis gracilipes)生物学的定向研究,并阐述了如何利用这些知识来改善对该物种的管理效果。我对三个栖息地的蚁巢位置和密度、工蚁24小时的活动情况、侵扰扩展速率、工蚁数量的季节变化以及有性生殖蚁的产生时间进行了量化。蚁巢主要(高达68%)位于大树基部,这表明搜索工作应集中在树基部周围。三个栖息地的蚁巢密度分别为每22平方米、7.1平方米和6.3平方米有一个蚁巢。这些数据构成了量化处理效果的基线,并为处理后评估设定了采样密度。大多数(60%)蚁巢位于地下,主要(89%)出现在开阔区域,而非岩石或原木下方。落叶层中的蚁巢存在一定的季节性,大多数(83%)出现在“雨季”(10月至次年3月)。在地下蚁巢中,大多数较浅,44%的蚁巢深度小于10厘米,67%小于20厘米。这种蚁巢位置和密度信息有助于实现多种管理目的,可用于改进检测、绘图和处理后评估,还有力地证明了碳水化合物供应是黄疯蚁种群的主要驱动因素。略多于一半(56%)的蚁巢中有蚁后。在62个有蚁后的地下蚁巢中,大多数蚁后(80%)位于最深的蚁室。当有蚁后时,最常见的情况(38%)是只有一只蚁后,最多有16只。每个蚁巢中的蚁后数量在9月处女蚁后出现前的7月和8月最低,之后一直保持较高水平直至4月。对于任何蚁种,目前尚不清楚每个蚁巢 / 蚁群中的蚁后数量如何影响处理效果,但进一步的研究无疑会在蚁类处理方面取得重要突破。活动主要在夜间进行,中午停止。这些活动数据确定了进行可靠工作必须达到的临界阈值,还表明处理最好在下午进行。总育雏产量在2月达到峰值,在8月和9月左右最低。这些数量数据构成了量化处理效果的基线,可能对处理效果有影响。每月都能发现雄蚁,主要在8月至11月之间。9月发现了蚁后蛹。有性生殖蚁的繁殖时间决定了处理时间表。像这里所描述的有针对性的、针对特定地点的研究,应该成为任何入侵物种根除计划的一个组成部分,以设计基于知识的处理方案并确定评估基准。

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