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从动物运动数据预测农业生态系统中的功能反应,以改善入侵害虫的管理。

Predicting functional responses in agro-ecosystems from animal movement data to improve management of invasive pests.

机构信息

Department of Biology, Colorado State University, Fort Collins, Colorado, 80523, USA.

USDA, Animal and Plant Health Inspection Service, Wildlife Services, National Wildlife Research Center, Fort Collins, Colorado, 80521-2154, USA.

出版信息

Ecol Appl. 2020 Jan;30(1):e02015. doi: 10.1002/eap.2015. Epub 2019 Nov 4.

DOI:10.1002/eap.2015
PMID:31596984
Abstract

Functional responses describe how changing resource availability affects consumer resource use, thus providing a mechanistic approach to prediction of the invasibility and potential damage of invasive alien species (IAS). However, functional responses can be context dependent, varying with resource characteristics and availability, consumer attributes, and environmental variables. Identifying context dependencies can allow invasion and damage risk to be predicted across different ecoregions. Understanding how ecological factors shape the functional response in agro-ecosystems can improve predictions of hotspots of highest impact and inform strategies to mitigate damage across locations with varying crop types and availability. We linked heterogeneous movement data across different agro-ecosystems to predict ecologically driven variability in the functional responses. We applied our approach to wild pigs (Sus scrofa), one of the most successful and detrimental IAS worldwide where agricultural resource depredation is an important driver of spread and establishment. We used continental-scale movement data within agro-ecosystems to quantify the functional response of agricultural resources relative to availability of crops and natural forage. We hypothesized that wild pigs would selectively use crops more often when natural forage resources were low. We also examined how individual attributes such as sex, crop type, and resource stimulus such as distance to crops altered the magnitude of the functional response. There was a strong agricultural functional response where crop use was an accelerating function of crop availability at low density (Type III) and was highly context dependent. As hypothesized, there was a reduced response of crop use with increasing crop availability when non-agricultural resources were more available, emphasizing that crop damage levels are likely to be highly heterogeneous depending on surrounding natural resources and temporal availability of crops. We found significant effects of crop type and sex, with males spending 20% more time and visiting crops 58% more often than females, and both sexes showing different functional responses depending on crop type. Our application demonstrates how commonly collected animal movement data can be used to understand context dependencies in resource use to improve our understanding of pest foraging behavior, with implications for prioritizing spatiotemporal hotspots of potential economic loss in agro-ecosystems.

摘要

功能反应描述了资源可利用性的变化如何影响消费者对资源的利用,从而为入侵物种(IAS)的可入侵性和潜在破坏提供了一种机械方法。然而,功能反应可能因上下文而异,因资源特征和可用性、消费者属性以及环境变量而异。确定上下文依赖性可以预测不同生态区的入侵和破坏风险。了解生态因素如何塑造农业生态系统中的功能反应,可以提高对高影响热点的预测能力,并为不同作物类型和可用性的地点提供减轻破坏的策略。我们链接了不同农业生态系统中的异质运动数据,以预测功能反应中的生态驱动变异性。我们将我们的方法应用于野猪(Sus scrofa),这是世界上最成功和最具破坏性的入侵物种之一,农业资源掠夺是其传播和建立的重要驱动因素。我们使用大陆尺度的农业生态系统内的运动数据,量化了相对于作物和自然草料可利用性的农业资源的功能反应。我们假设,当自然草料资源较低时,野猪会更频繁地选择性地使用作物。我们还研究了个体属性(如性别、作物类型)和资源刺激(如距作物的距离)如何改变功能反应的幅度。存在强烈的农业功能反应,即当作物密度较低时(III 型),作物利用是作物可利用性的加速函数,并且高度依赖于上下文。正如假设的那样,随着非农业资源可用性的增加,作物利用的反应会降低,这强调了作物破坏水平很可能高度异质,这取决于周围的自然资源和作物的时间可用性。我们发现了作物类型和性别的显著影响,雄性比雌性多花费 20%的时间,多访问作物 58%,并且两种性别都根据作物类型表现出不同的功能反应。我们的应用演示了如何使用通常收集的动物运动数据来了解资源利用中的上下文依赖性,以提高我们对害虫觅食行为的理解,这对确定农业生态系统中潜在经济损失的时空热点具有重要意义。

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