Evaluating the role of environmental familiarity and behaviour in the success of wildlife translocation: A grizzly bear case study using agent-based modelling

IF 3.1 3区 环境科学与生态学 Q2 ECOLOGY
Alejandra Zubiria-Perez , Christopher Bone , Gordon Stenhouse
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引用次数: 0

Abstract

Human-carnivore systems are built on multi-scalar complex processes often resulting in conflicts that force wildlife managers to address what are conceived as problem individuals. In North America, the grizzly bear (Ursus arctos) is often involved in human-bear conflict with management measures such as translocations, in which problem individuals are moved to new areas, being used to reduce conflict risk. While translocations offer a non-lethal alternative to managing conflict animals, they show varying levels of success. Our objective was to perform a novel assessment of grizzly bear translocation success through agent-based simulation by evaluating how familiarity with landscape features coupled with behavioral traits affects the way individuals use resources in a new environment. Our results showed that bears translocated to familiar habitat used high-quality habitat more than bears moved to areas with unfamiliar landscape characteristics. Increased exploration led to greater use of high-quality habitat in the long run but resulted in reduced use of high-quality habitat during the first two years following a translocation. Habitat quality use depended on scale, with bears translocated to less familiar environments accessing higher quality areas at a finer scale than bears translocated to familiar habitats. We emphasize the need to account for wildlife behavioral traits and habitat characteristics at multiple scales when selecting suitable translocation locations. Understanding the role of factors such as these on translocation outcome will help ensure the success of translocations not only as a method for managing problem wildlife, but also for population restoration, species reestablishment, and conservation translocations across the globe.

评估环境熟悉度和行为在野生动物迁移成功中的作用:基于代理建模的灰熊案例研究
人类食肉动物系统建立在多标量复杂过程的基础上,通常会导致冲突,迫使野生动物管理者解决被认为是问题个体的问题。在北美,灰熊(Ursus arctos)经常卷入人熊冲突,管理措施包括转移,将问题个体转移到新的地区,以降低冲突风险。虽然迁移为管理冲突动物提供了一种非致命的替代方案,但它们的成功程度各不相同。我们的目标是通过基于代理的模拟,通过评估对景观特征和行为特征的熟悉程度如何影响个体在新环境中使用资源的方式,对灰熊迁移的成功进行新的评估。我们的研究结果表明,迁移到熟悉栖息地的熊比迁移到不熟悉景观特征的地区的熊更多地使用高质量的栖息地。从长远来看,勘探的增加导致了高质量栖息地的更多使用,但在迁移后的头两年,高质量栖息地使用减少。栖息地质量的使用取决于规模,与迁移到熟悉栖息地的熊相比,迁移到不太熟悉环境的熊以更精细的规模进入更高质量的区域。我们强调,在选择合适的迁移地点时,需要在多个尺度上考虑野生动物的行为特征和栖息地特征。了解这些因素对迁移结果的作用将有助于确保迁移的成功,这不仅是一种管理问题野生动物的方法,也是全球种群恢复、物种重建和保护迁移的方法。
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来源期刊
Ecological Complexity
Ecological Complexity 环境科学-生态学
CiteScore
7.10
自引率
0.00%
发文量
24
审稿时长
3 months
期刊介绍: Ecological Complexity is an international journal devoted to the publication of high quality, peer-reviewed articles on all aspects of biocomplexity in the environment, theoretical ecology, and special issues on topics of current interest. The scope of the journal is wide and interdisciplinary with an integrated and quantitative approach. The journal particularly encourages submission of papers that integrate natural and social processes at appropriately broad spatio-temporal scales. Ecological Complexity will publish research into the following areas: • All aspects of biocomplexity in the environment and theoretical ecology • Ecosystems and biospheres as complex adaptive systems • Self-organization of spatially extended ecosystems • Emergent properties and structures of complex ecosystems • Ecological pattern formation in space and time • The role of biophysical constraints and evolutionary attractors on species assemblages • Ecological scaling (scale invariance, scale covariance and across scale dynamics), allometry, and hierarchy theory • Ecological topology and networks • Studies towards an ecology of complex systems • Complex systems approaches for the study of dynamic human-environment interactions • Using knowledge of nonlinear phenomena to better guide policy development for adaptation strategies and mitigation to environmental change • New tools and methods for studying ecological complexity
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