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fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
McCarroll, Julia
Languages: English
Types: Doctoral thesis
Subjects: GE
In a recent discussion of research priorities for palaeoecology, it was suggested that palaeoecological data can be applied and used to inform nature conservation practice. The present study exemplifies this approach. It was conducted on three degraded blanket mires in Yorkshire, UK, in collaboration with a field-based moorland restoration agency. High-resolution, multiproxy palaeoecological analyses on peat cores from Mossdale Moor, Oxenhope Moor and West Arkengarthdale reconstructed mid- to late-Holocene vegetation changes. Humification, pollen, plant macrofossil and charcoal analyses carried out throughout the peat profile at each site show marked changes in species composition and indicate their potential causes. Results suggest that human clearance in the Mesolithic–Neolithic transition may have initiated peat growth at Mossdale Moor, making this landscape ‘semi-natural’ in its origin. Further human-induced changes are identified at 1300 cal. years BP at Mossdale Moor, 2100 cal. BP at Oxenhope Moor and c. 3250 cal. BP at West Arkengarthdale, most likely deliberate clearance by fire. Increased anthropogenic activity is identified at each site since the industrial revolution where monocots and Eriophorum vaginatum increase, consistent with rises in charcoal at Mossdale Moor and West Arkengarthdale. These are interpreted as recent (<300 years) management practices using burning to encourage browse on the moor. Climatic deteriorations have also been identified, with wetter conditions at 5000 cal. BP and 4400 cal. BP at West Arkengarthdale and Oxenhope Moor, c. 2400 cal. BP at Mossdale Moor and West Arkengarthdale and the Little Ice Age at each site. It is intended that these long-term ecological histories of the sites, derived using palaeoecological techniques, will be used to inform conservation practice and can help set feasible targets for restoration and conservation.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

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