过去可以从数据中复原吗?古生态学数据不确定性的伪代理建模

Quinn Asena, George LW Perry, Janet M Wilmshurst
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引用次数: 0

摘要

人们越来越关注当代生态系统对不断增加的新的人为压力和环境条件的反应。古生态学对于了解生态系统如何应对过去的环境变化至关重要,可以为当代生态系统的管理提供信息,并有助于预测生态系统对变化的反应。然而,古生态学数据受环境过程、野外和实验室方法以及数据处理所产生的不确定性的影响,并影响从中得出的推论。对不同的不确定性来源如何影响代用记录分析的了解仍然有限,而且记录往往只得到定性的解释。我们提出了一种虚拟生态学方法,用于评估经验代用数据中固有的不确定性如何影响统计分析以及由此得出的推论。在虚拟生态学方法中,数据和观测过程都是通过模拟重现的,以评估取样和分析方法。我们展示了一个新模型的结果,该模型模拟了可与经验代用指标数据相媲美的伪代用指标核心样本,但不受代用指标和年代学不确定性的影响。这些在已知驱动条件下生成的 "无误 "伪代用指标系统地引入了不确定因素(如岩心混合、子取样和代用指标量化),以评估单个和综合不确定因素如何影响分析方法。结果表明,从统计分析中得出的推论,如系统的稳定性或生态更替率,在 "无误 "伪代用指标与退化和次级取样数据之间会发生很大变化。我们展示了我们的方法如何促进对古生态学数据不确定性的理解,以及如何通过量化它们对代用数据的影响来帮助确定研究问题。
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Is the past recoverable from the data? Pseudoproxy modelling of uncertainties in palaeoecological data
There is growing concern about the response of contemporary ecosystems to increasing and novel anthropogenic pressures and environmental conditions. Palaeoecology is crucial to understanding how ecosystems have responded to past environmental changes and can inform management of contemporary ecosystems and contribute to forecasts of ecosystem responses to change. However, palaeoecological data are subject to uncertainties that arise from environmental processes, field and laboratory methods, and data processing, and that affects inferences drawn from them. Understanding how different sources of uncertainty affect the analyses of proxy records remains limited, and records are often interpreted solely qualitatively. We present a virtual ecology approach for assessing how uncertainties inherent in empirical proxy data influence statistical analyses and the inferences drawn from them. In the virtual ecology approach, both the data and the observational process are recreated in simulation to assess sampling and analytical methods. We demonstrate results from a new model for simulating core-type samples of pseudoproxies comparable to empirical proxy data but not subject to the same sources of proxy and chronological uncertainties. These ‘error-free’ pseudoproxies generated under known driving conditions have uncertainties (e.g. core mixing, sub-sampling, and proxy quantification) systematically introduced to them to assess how individual and combined sources of uncertainty influence analytical methods. Results indicate that inferences drawn from statistical analysis, such as the stability of a system, or the rate of ecological turnover, can change substantially between the ‘error-free’ pseudoproxies, and degraded and sub-sampled data. We show how our approach can advance understanding of uncertainties in palaeoecological data and how it can help shape research questions by quantifying of their influence on proxy data.
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