dc.contributor.advisor |
Perry, George |
|
dc.contributor.advisor |
Wilmshurst, Janet |
|
dc.contributor.author |
Asena, Quinn |
|
dc.date.accessioned |
2022-02-20T22:32:30Z |
|
dc.date.available |
2022-02-20T22:32:30Z |
|
dc.date.issued |
2021 |
en |
dc.identifier.uri |
https://hdl.handle.net/2292/58282 |
|
dc.description.abstract |
Contemporary ecosystems are experiencing increasing anthropogenic pressure and there is growing concern over
how they will respond to such novel pressures. Palaeoecology offers crucial understanding of how ecosystems
have responded to environmental change in the past, and provides valuable insight into how ecosystems will
change in the future. However, palaeo-proxy records are associated with many uncertainties from environmental
processes and process and observer error that may limit the inferences drawn from them. There is a call for
palaeoecology to move from a descriptive to a quantitative discipline by quantifying uncertainties and employing
rigorous statistical data analysis methods. Thus, the sources of uncertainty in the data must be assessed for their
influence on statistical analyses, in terms of false positive and false negative pattern identification (e.g. of regime
shifts or indicators of resilience). Virtual assessments of how uncertainty in palaeoecological data affect statistical
analyses are few and do not adequately represent the underlying ecological dynamics or the multivariate data
typical of proxy records. This lack of understanding of uncertainties is a key knowledge gap in the scientific
literature that I seek to address in this thesis.
First, I develop a model for generating multivariate proxy data based on underlying ecological dynamics. Second,
I apply multivariate statistics to the simulated data under increasing levels of uncertainty introduced from core
mixing, sub-sampling and proxy counting to determine which individual and combined sources of uncertainty
have the greatest influence on the analyses. Results suggest that individual sources of uncertainty, such as
sub-sampling frequency, have a greater influence on analyses than mixing or proxy counting resolution; however,
the greatest influence is from the interaction effect of the combined uncertainties of sub-sampling with proxy
counting. Third, I apply change point analyses to the multivariate statistics to assess the probability of detecting
a shift in proxy data, caused by a variety of environmental conditions, when subject to proxy uncertainties. The
probability of detecting a shift in proxy data at a known point in time depended on the rate of change in the
driving conditions relative to the response rate of the system. Abrupt environmental shifts combined with fast
ecological responses were detected more frequently than slower environmental changes and ecological response.
The effects of uncertainties in the proxies themselves were inconsistent, but the probability of statistically
detecting change at a known time decreased at the highest level of uncertainty. Finally, both chronological and
proxy uncertainties are introduced to the data to determine how they affect the timing of change points detected
at a known time in the simulated proxy record. Timing was found to be precise to a century level, but the
accuracy of determining the true timing of change reduced as uncertainty increased.
Overall, I conclude that for empirical palaeoecological studies where best to focus effort on reducing uncertainty
depends on the question and scales of interest and knowledge of the study area. In the case of poor knowledge
of a site and its environmental drivers over time, core replication and spatial coverage is likely to be necessary to
increase the probability of detecting key patterns of change over focusing on laboratory methods of sub-sampling
frequency. Furthermore, I recommend applying a suite of statistical methods and report chronological and proxy
uncertainties. |
|
dc.publisher |
ResearchSpace@Auckland |
en |
dc.relation.ispartof |
PhD Thesis - University of Auckland |
en |
dc.relation.isreferencedby |
UoA |
en |
dc.rights |
Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. |
en |
dc.rights |
Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. |
|
dc.rights.uri |
https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm |
en |
dc.rights.uri |
http://creativecommons.org/licenses/by-nc-sa/3.0/nz/ |
|
dc.title |
Pseudoproxy modelling to explore ecosystem dynamics and assess uncertainties in palaeoecology |
|
dc.type |
Thesis |
en |
thesis.degree.discipline |
Environmental Science |
|
thesis.degree.grantor |
The University of Auckland |
en |
thesis.degree.level |
Doctoral |
en |
thesis.degree.name |
PhD |
en |
dc.date.updated |
2022-02-11T04:31:26Z |
|
dc.rights.holder |
Copyright: The author |
en |
dc.rights.accessrights |
http://purl.org/eprint/accessRights/OpenAccess |
en |