气候变化领域集成服务门户(CCPortal): Informing management decisions for ecological networks, using dynamic models calibrated to noisy time-series data

CCPortal

DOI	10.1111/ele.13465
	Informing management decisions for ecological networks, using dynamic models calibrated to noisy time-series data
	Adams M.P.; Sisson S.A.; Helmstedt K.J.; Baker C.M.; Holden M.H.; Plein M.; Holloway J.; Mengersen K.L.; McDonald-Madden E.
发表日期	2020
ISSN	1461023X
英文摘要	Well-intentioned environmental management can backfire, causing unforeseen damage. To avoid this, managers and ecologists seek accurate predictions of the ecosystem-wide impacts of interventions, given small and imprecise datasets, which is an incredibly difficult task. We generated and analysed thousands of ecosystem population time series to investigate whether fitted models can aid decision-makers to select interventions. Using these time-series data (sparse and noisy datasets drawn from deterministic Lotka-Volterra systems with two to nine species, of known network structure), dynamic model forecasts of whether a species’ future population will be positively or negatively affected by rapid eradication of another species were correct > 70% of the time. Although 70% correct classifications is only slightly better than an uninformative prediction (50%), this classification accuracy can be feasibly improved by increasing monitoring accuracy and frequency. Our findings suggest that models may not need to produce well-constrained predictions before they can inform decisions that improve environmental outcomes. © 2020 John Wiley & Sons Ltd/CNRS
英文关键词	Conservation; decision science; ecological forecasting; ecological modelling; food webs; interaction network; population dynamics; predator–prey interactions; prediction; uncertainty propagation
语种	英语
来源期刊	Ecology Letters
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/120971
作者单位	School of Earth and Environmental Sciences, The University of Queensland, St Lucia, QLD 4072, Australia; Centre for Biodiversity and Conservation Science, The University of Queensland, St Lucia, QLD 4072, Australia; ARC Centre of Excellence for Mathematical and Statistical Frontiers, The University of Queensland, St Lucia, QLD 4072, Australia; School of Mathematics and Statistics, The University of New South Wales, Sydney, NSW 2052, Australia; School of Mathematical Sciences, Queensland University of Technology, Brisbane, QLD 4001, Australia; ARC Centre of Excellence for Mathematical and Statistical Frontiers, Queensland University of Technology, Brisbane, QLD 4001, Australia; School of Biological Sciences, The University of Queensland, St Lucia, QLD 4072, Australia; CSIRO Ecosystem Sciences, Ecosciences Precinct, Dutton Park, QLD 4102, Australia; Centre of Excellence for Environmental Decisions, The University of Queensland, St Lucia, QLD 4072, Australia; Centre for Applications in Natural Resou...
推荐引用方式 GB/T 7714	Adams M.P.,Sisson S.A.,Helmstedt K.J.,et al. Informing management decisions for ecological networks, using dynamic models calibrated to noisy time-series data[J],2020.
APA	Adams M.P..,Sisson S.A..,Helmstedt K.J..,Baker C.M..,Holden M.H..,...&McDonald-Madden E..(2020).Informing management decisions for ecological networks, using dynamic models calibrated to noisy time-series data.Ecology Letters.
MLA	Adams M.P.,et al."Informing management decisions for ecological networks, using dynamic models calibrated to noisy time-series data".Ecology Letters (2020).