Using high-resolution LiDAR-derived canopy structure and topography to characterise hibernaculum locations of the hazel dormouse.
Oecologia
; 202(4): 641-653, 2023 Aug.
Article
em En
| MEDLINE
| ID: mdl-37543993
The hazel dormouse is predominantly an arboreal species that moves down to the ground to hibernate in the autumn in temperate parts of its distributional ranges at locations not yet well understood. The main objective of this study is to test whether environmental characteristics surrounding hazel dormouse hibernacula can be identified using high-resolution remote sensing and data collected in situ. To achieve this, remotely sensed variables, including canopy height and cover, topographic slope, sky view, solar radiation and cold air drainage, were modelled around 83 dormouse hibernacula in England (n = 62) and the Netherlands (n = 21), and environmental characteristics that may be favoured by pre-hibernating dormice were identified. Data on leaf litter depth, temperature, canopy cover and distance to the nearest tree were collected in situ and analysed at hibernaculum locations in England. The findings indicated that remotely sensed data were effective in identifying attributes surrounding the locations of dormouse hibernacula and when compared to in situ information, provided more conclusive results. This study suggests that remotely sensed topographic slope, canopy height and sky view have an influence on hazel dormice choosing suitable locations to hibernate; whilst in situ data suggested that average daily mean temperature at the hibernaculum may also have an effect. Remote sensing proved capable of identifying localised environmental characteristics in the wider landscape that may be important for hibernating dormice. This study proposes that this method can provide a novel progression from habitat modelling to conservation management for the hazel dormouse, as well as other species using habitats where topography and vegetation structure influence fine-resolution favourability.
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Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Myoxidae
Tipo de estudo:
Prognostic_studies
Limite:
Animals
País/Região como assunto:
Europa
Idioma:
En
Ano de publicação:
2023
Tipo de documento:
Article