Is the past recoverable from the data? Pseudoproxy modelling of uncertainties in palaeoecological data

Author:

Asena Quinn12ORCID,Perry George LW1,Wilmshurst Janet M13ORCID

Affiliation:

1. School of Environment, University of Auckland, New Zealand

2. Department of Geography, University of Wisconsin-Madison, USA

3. Manaaki Whenua – Landcare Research, New Zealand

Abstract

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.

Publisher

SAGE Publications

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3