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Stephen J. Cornell

Researcher at University of Liverpool

Publications -  89
Citations -  6728

Stephen J. Cornell is an academic researcher from University of Liverpool. The author has contributed to research in topics: Population & Biological dispersal. The author has an hindex of 39, co-authored 87 publications receiving 6215 citations. Previous affiliations of Stephen J. Cornell include Paul Sabatier University & University of Geneva.

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Farming and the Fate of Wild Nature

TL;DR: It is shown that the best type of farming for species persistence depends on the demand for agricultural products and on how the population densities of different species on farmland change with agricultural yield, and that high-yield farming may allow more species to persist.
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Dynamics of the 2001 UK foot and mouth epidemic: stochastic dispersal in a heterogeneous landscape

TL;DR: An individual farm–based stochastic model of the current UK epidemic of foot-and-mouth disease reveals the infection dynamics at an unusually high spatiotemporal resolution, and shows that the spatial distribution, size, and species composition of farms all influence the observed pattern and regional variability of outbreaks.
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Wildlife-friendly oil palm plantations fail to protect biodiversity effectively

TL;DR: In this paper, the abundance and diversity of birds within oil palm plantations, fragments, and contiguous forest were investigated, and the authors reported that the abundance of imperiled birds was 60 times lower in fragments and 200 times higher in oil palm than in contiguous forest.
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Protracted speciation revitalizes the neutral theory of biodiversity

TL;DR: It is shown that it is both necessary and straightforward to incorporate protracted speciation in future studies of neutral models, and argued that non-neutral models should also model speciation as a gradual process rather than an instantaneous one.
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Persistence exponents for fluctuating interfaces

TL;DR: In this paper, the decay of the first return probability of an interface to its initial height is analyzed for a large class of linear Langevin equations, where the models are parametrized by the dynamic roughness exponent.