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DOI: 10.1371/journal.pone.0110968
论文题名:
Understanding Uncertainties in Non-Linear Population Trajectories: A Bayesian Semi-Parametric Hierarchical Approach to Large-Scale Surveys of Coral Cover
作者: Julie Vercelloni; M. Julian Caley; Mohsen Kayal; Samantha Low-Choy; Kerrie Mengersen
刊名: PLOS ONE
ISSN: 1932-6203
出版年: 2014
发表日期: 2014-11-3
卷: 9, 期:11
语种: 英语
英文关键词: Coral reefs ; Spatial and landscape ecology ; Theoretical ecology ; Population ecology ; Corals ; Reefs ; Ecological metrics ; Nonlinear dynamics
英文摘要: Recently, attempts to improve decision making in species management have focussed on uncertainties associated with modelling temporal fluctuations in populations. Reducing model uncertainty is challenging; while larger samples improve estimation of species trajectories and reduce statistical errors, they typically amplify variability in observed trajectories. In particular, traditional modelling approaches aimed at estimating population trajectories usually do not account well for nonlinearities and uncertainties associated with multi-scale observations characteristic of large spatio-temporal surveys. We present a Bayesian semi-parametric hierarchical model for simultaneously quantifying uncertainties associated with model structure and parameters, and scale-specific variability over time. We estimate uncertainty across a four-tiered spatial hierarchy of coral cover from the Great Barrier Reef. Coral variability is well described; however, our results show that, in the absence of additional model specifications, conclusions regarding coral trajectories become highly uncertain when considering multiple reefs, suggesting that management should focus more at the scale of individual reefs. The approach presented facilitates the description and estimation of population trajectories and associated uncertainties when variability cannot be attributed to specific causes and origins. We argue that our model can unlock value contained in large-scale datasets, provide guidance for understanding sources of uncertainty, and support better informed decision making.
URL: http://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0110968&type=printable
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/18042
Appears in Collections:过去全球变化的重建
影响、适应和脆弱性
科学计划与规划
气候变化与战略
全球变化的国际研究计划
气候减缓与适应
气候变化事实与影响

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作者单位: School of Mathematical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia;Australian Institute of Marine Science, Townsville, Queensland, Australia;Australian Institute of Marine Science, Townsville, Queensland, Australia;Bren School of Environmental Science and Management, University of California Santa Barbara, Santa Barbara, California, United States of America;School of Mathematical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia;School of Mathematical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia

Recommended Citation:
Julie Vercelloni,M. Julian Caley,Mohsen Kayal,et al. Understanding Uncertainties in Non-Linear Population Trajectories: A Bayesian Semi-Parametric Hierarchical Approach to Large-Scale Surveys of Coral Cover[J]. PLOS ONE,2014-01-01,9(11)
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