Bailey, Joseph John
(2018)
Advancing biodiversity and species distribution modelling using geodiversity information.
PhD thesis, University of Nottingham.
Abstract
EXTENDED THESIS ABSTRACT
Context
Understanding spatial patterns of biodiversity and species’ distributions is important for scientific theory, and for conservation and management of the natural world. Climatic variables are widely recognised as strong correlates of species richness over large spatial extents. Correlates of species richness at smaller extents (regional and landscape scales) are less well established, but environmental heterogeneity is widely thought to be important. A large number of environmental heterogeneity measures have been used, but in particular there is a growing interest in ‘geodiversity’, which I define here as the diversity of abiotic terrestrial and hydrological nature, comprising earth surface materials and landforms. Recent research has emphasised both geodiversity’s inherent value and its potential as a correlate and predictor of spatial biodiversity and species’ distribution patterns. However, despite this clear potential of geodiversity for improving our understanding of how patterns of life relate to environmental heterogeneity, its incorporation into biodiversity and species’ distribution modelling is substantially underdeveloped. In this thesis, using a macroecological approach I begin to address some of these knowledge gaps by analysing the relationships between geodiversity data, and its constituent ‘geofeatures’, and species richness and distributions for multiple taxa and across several scales (grain size and extent) and geographic locations. My main aims in this thesis are to more fully evaluate geodiversity itself, and improve our understanding of its role with respect to the spatial patterning of biodiversity, both conceptually and empirically.
Locations and Spatial Scales
Analyses were carried out within and across Great Britain (England, Scotland, and Wales) and Finland. The order of the four quantitative papers generally reflects the largest spatial extent (i.e. size of the study area) at which they were conducted, from national (PAPERS II and III) through landscape (PAPER IV), to the local scale (vegetation plots within a small upland river catchment; PAPER V). PAPER II is a study across several spatial extents (from landscape to national) and uses two grain sizes (1 km2 and 100 km2). PAPER I is a review paper that considers multiple scales and geographic locations conceptually.
Time period
Present day: data were from between 1995 and 2016 across all of the quantitative studies.
Taxa
Multiple: alien and native vascular plants across Great Britain (PAPER II); threatened bryophytes, beetles, fungi, lepidoptera, lichens, mammals, molluscs, and vascular plants across Finland (PAPER III); common and rare vascular plants across the Cairngorms, Scotland (PAPER IV); angiosperms, conifers, fungi, lichens, liverworts, lycophytes, mosses, and pteridophytes (and productivity) across an upland river catchment within the Cairngorms (PAPER V); and conceptual consideration of multiple taxa (PAPER I).
Methods
For studies in Great Britain, plant data were provided by the Botanical Society of Britain and Ireland (BSBI) for PAPERS II and IV, and by the Centre for Ecology and Hydrology (CEH) for PAPER V. The threatened species data in Finland were from Finnish Environment Institute (PAPER II). Species richness (PAPERS II, III, and IV), rarity-weighted richness (RWR; PAPER III), species’ distributions (PAPERS IV and V), and productivity (measured using NDVI from colour infrared aerial imagery; PAPER V) were all analysed using Boosted Regression Tree (BRT) modelling, allowing comparisons between studies.
For geodiversity data in the British studies, I compiled geodiversity data on landforms, soils, hydrological and geological features using existing national datasets (e.g. British Geological Survey), and used a geomorphometric method to extract landform coverage data (landforms included: hollows, ridges, valleys, and peaks). These data were analysed alongside environmental data, which varied between papers, relating to climate, standard topography (e.g. slope; elevation), land use, and human population. The sources of other geodiversity data in Finland, and environmental data on topography and climate, came from a variety of sources, which are detailed within each paper.
Results
Geodiversity improved biodiversity and species’ distribution models throughout all of the quantitative analyses and generally declined in importance as spatial scale coarsened beyond the landscape scale. At most spatial scales and in most places, the roles of climate and/or coarse topography dominated, and geodiversity played a relatively small role, as was expected. Geodiversity, however, made consistent positive contributions to the models independently of traditionally used topographic metrics such as standard deviation of elevation and slope. Taxonomically, geodiversity: (i) was slightly more relevant for native vascular plants than alien in Great Britain (PAPER II); (ii) of similar relevance to common and rare vascular plants in the Scottish Highlands, except that the coverage of soil parent material was especially important for rare species’ distributions (PAPER IV); of similar relevance to most sessile taxa (angiosperms, fungi, mosses, liverworts, lichens, pteridophytes, and lycophytes; conifers were not related to geodiversity) in an upland Scottish river catchment (PAPER V); and more important for threatened vascular plants and bryophytes over other studied taxa in Finland (PAPER II). Geodiversity also improved models of productivity, and the variability in productivity, in PAPER V.
Main conclusions and Future Directions
Geodiversity improves our understanding of, and ability to model, the relationship between biodiversity and environmental heterogeneity at multiple spatial scales, by allowing us to get closer to the real-world conditions and processes that affect life. I found that the greatest benefit comes from measuring ‘geofeatures’, which describe the constituent parts of geodiversity separately, rather than as one combined variable. Automatically extracted landform data, the use of which is novel in ecology, biogeography and macroecology, proved particularly valuable throughout this body of work, and as too did data from expert geological and hydrological maps.
The idea of ‘Conserving Nature’s Stage’ (CNS), and identifying areas that are most capable of supporting high biodiversity into the future, the benefits and caveats of which are discussed in this thesis, has recently emerged. It requires a sound empirical and conceptual basis, to which my research contributes. In this thesis, I have gone some way towards demonstrating the conceptual and empirical value of incorporating geodiversity into ecological analyses across multiple spatial scales, paving the way for this recent approach to be more extensively used for theoretical and applied purposes. I accomplished this by carrying out an assessment of existing geodiversity literature and, importantly, looking forwards to consider the prospects of geodiversity within ecology (PAPER I), supported by four quantitative studies. The conservation significance is emphasised in PAPER III.
Much remains to be done, however, and future research directions are detailed in PAPER I. We need to develop predictive models to test the role of geodiversity across an array of geographical and taxonomic domains, as well as to assess metrics beyond species richness and species’ distributions. One example may involve beta diversity: does spatial turnover in species relate to spatial turnover in geofeatures? Fully analysing the role of geodiversity through time will also be important, including in relation to refugia, given predicted environmental changes in climate. In progressing with this line of enquiry, we will improve our knowledge and understanding of patterns of life on Earth and, specifically, how the geophysical landscape helps shape them.
Actions (Archive Staff Only)
 |
Edit View |
Tools
Tools
![[thumbnail of Joseph_J_Bailey__PhD_Thesis__2017-05.pdf]](https://eprints.nottingham.ac.uk/style/images/fileicons/application_pdf.png "Joseph_J_Bailey__PhD_Thesis__2017-05.pdf")