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Models of upland species’ distributions are improved by accounting for geodiversity

Bailey, Joseph, Boyd, Doreen S. and Field, Richard (2018) Models of upland species’ distributions are improved by accounting for geodiversity. Landscape Ecology.

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Abstract

Context
Recent research suggests that novel geodiversity data on landforms, hydrology and surface materials can improve biodiversity models at the landscape scale by quantifying abiotic variability more effectively than commonly used measures of spatial heterogeneity. However, few studies consider whether these variables can account for, and improve our understanding of, species’ distributions.
Objectives
Assess the role of geodiversity components as macro-scale controls of plant species’ distributions in a montane landscape.
Methods
We used an innovative approach to quantifying a landscape, creating an ecologically meaningful geodiversity dataset that accounted for hydrology, morphometry (landforms derived from geomorphometric techniques), and soil parent material (data from expert sources). We compared models with geodiversity to those just using topographic metrics (e.g. slope and elevation) and climate data. Species distribution models (SDMs) were produced for ‘rare’ (N = 76) and ‘common’ (N = 505) plant species at 1 km2 resolution for the Cairngorms National Park, Scotland.
Results
The addition of automatically produced landform geodiversity data and hydrological features to a basic SDM (climate, elevation, and slope) resulted in a significant improvement in model fit across all common species’ distribution models. Adding further geodiversity data on surface materials resulted in a less consistent statistical improvement, but added considerable conceptual value to many individual rare and common SDMs.
Conclusions
The geodiversity data used here helped us capture the abiotic environment’s heterogeneity and allowed for explicit links between the geophysical landscape and species’ ecology. It is encouraging that relatively simple and easily produced geodiversity data have the potential to improve SDMs. Our findings have important implications for applied conservation and support the need to consider geodiversity in management.

Item Type: Article
Status: Published
DOI: https://doi.org/10.1007/s10980-018-0723-z
Subjects: G Geography. Anthropology. Recreation > G Geography (General)
G Geography. Anthropology. Recreation > GB Physical geography
G Geography. Anthropology. Recreation > GE Environmental Sciences
Q Science > Q Science (General)
Q Science > QK Botany
Q Science > QL Zoology
School/Department: School of Humanities, Religion & Philosophy
URI: http://ray.yorksj.ac.uk/id/eprint/3549

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