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Title: Incorporating spatial and temporal variability in analyses of the relationship between biodiversity and ecosystem functioning
Author: Tanadini, Matteo
ISNI:       0000 0004 6499 8615
Awarding Body: University of Oxford
Current Institution: University of Oxford
Date of Award: 2016
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In the last few decades, a growing literature has examined how biodiversity influences ecosystem functioning. This body of work has greatly improved our understanding of ecosystem functioning and its modulation by biodiversity. In particular, there is nowadays large consensus that biodiversity increases ecosystem productivity, and stabilises ecosystems. Early investigations were largely theoretical or involved simple experiments run in laboratory conditions, but over time biodiversity ecosystem-functioning experiments evolved to more realistic field experiments that better represent the real conditions found in natural ecosystems. In particular, these experiments are often run on larger spatial scales and over longer time frames allowing for the effect of environmental heterogeneity and temporal fluctuations to be explored. The designs of these experiments evolved along with the questions addressed in this field of research. However, the analytical tools used in the analyses of these experiments followed a slightly different path. In particular, most of the metrics currently used to analyse biodiversity ecosystem functioning experiments are not entirely suited to properly deal with the complexity of modern designs as they make a number of assumptions that are not met any more. In my thesis I developed a unified framework, based on the tailored use of Linear Mixed Effects Models, to analyse biodiversity-ecosystem functioning experiments such that the new complexities of these experiments can be taken into account. This thesis aimed to bring the focus of the analysis back to the biological interpretation of the results. I successfully applied my approach to several data sets. The framework developed here is expected to improve greatly our understanding of ecosystem functioning and how biodiversity modulates it. It also sheds new light on past research in this field. The great flexibility of the new approach makes it possible to let these experiments to evolve such that new biological questions can be addressed.
Supervisor: Hector, Andrew Sponsor: Berrow Foundation
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Biodiversity ecosystem-functioning experiments ; Ecological statistics