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R. Daniel Morton

Researcher at Lancaster University

Publications -  11
Citations -  1417

R. Daniel Morton is an academic researcher from Lancaster University. The author has contributed to research in topics: Pollinator & Land cover. The author has an hindex of 10, co-authored 10 publications receiving 1189 citations. Previous affiliations of R. Daniel Morton include University of York.

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Permanence and the assembly of ecological communities

Richard Law, +1 more
- 01 Apr 1996 - 
TL;DR: A numerical technique for assembly of ecological communities of Lotka- Volterra form based upon a global criterion for coexistence of species known as permanence provides a relatively fast and accurate method to determine the sequence of communities that develops when species are drawn sequentially and in an arbitrary order from a regional pool of species.
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Historical nectar assessment reveals the fall and rise of floral resources in Britain

TL;DR: It is shown that overall floral rewards can be estimated at a national scale by combining vegetation surveys and direct nectar measurements, and this national-scale assessment of floral resource provision affords new insights into the links between plant and pollinator declines, and offers considerable opportunities for conservation.
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Alternative Permanent States of Ecological Communities

Richard Law, +1 more
- 01 Jul 1993 - 
TL;DR: In this paper, the authors explored the use of a global theory called "permanence" that indicates whether the boundary of a phase space is a repellor to orbits in the phase space.
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The impact of over 80 years of land cover changes on bee and wasp pollinator communities in England

TL;DR: This work explores, for the first time, land cover changes in England over more than 80 years, and relates them to concurrent shifts in bee and wasp species richness and community composition, and provides an insight into how increases in habitat diversity may benefit species diversity.
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Evaluating Combinations of Temporally Aggregated Sentinel-1, Sentinel-2 and Landsat 8 for Land Cover Mapping with Google Earth Engine

TL;DR: This study demonstrates that temporal aggregation is a promising tool for integrating large amounts of data in an efficient way and that it can compensate for the lower quality of automatic image selection and cloud masking and shows that combining data from different sensors can improve classification accuracy.