Simon Croft
Simon Croft
Quantitiative Ecologist, National Wildlife Management Centre, APHA
Verified email at apha.gsi.gov.uk
TitleCited byYear
The MILLENNIA peat cohort model: predicting past, present and future soil carbon budgets and fluxes under changing climates in peatlands
A Heinemeyer, S Croft, MH Garnett, E Gloor, J Holden, MR Lomas, ...
Climate Research 45, 207-226, 2010
452010
A systematic approach to estimate the distribution and total abundance of British mammals
S Croft, ALM Chauvenet, GC Smith
PLOS ONE 12 (6), e0176339, 2017
202017
Model inter-comparison between statistical and dynamic model assessments of the long-term stability of blanket peat in Great Britain (1940–2099)
JM Clark, MF Billett, M Coyle, S Croft, S Daniels, CD Evans, M Evans, ...
Climate Research 45, 227-248, 2010
172010
The influence of group size and social interactions on collision risk with obstacles
S Croft, R Budgey, JW Pitchford, AJ Wood
Ecological Complexity 16, 77-82, 2013
102013
Obstacle avoidance in social groups: new insights from asynchronous models
S Croft, R Budgey, JW Pitchford, AJ Wood
Journal of The Royal Society Interface 12 (106), 20150178, 2015
72015
Wild boar in focus: Review of existing models on spatial distribution and density of wild boar and proposal for next steps
S Croft, GC Smith, P Acevedo, J Vicente
EFSA Supporting Publications 15 (10), 44, 2018
42018
Predicting population trends using citizen science data: do subsampling methods produce reliable estimates for mammals?
K Callcutt, S Croft, GC Smith
European Journal of Wildlife Research 64 (3), 28, 2018
32018
Careful considerations are required when analysing mammal citizen science data – A response to Massimino et al
PM Wheeler, AI Ward, GC Smith, S Croft, SO Petrovan
Biological Conservation 232, 274-275, 2019
22019
Structuring the unstructured: estimating species-specific absence from multi-species presence data to inform pseudo-absence selection in species distribution models
S Croft, GC Smith
BioRxiv, 10.1101/656629, 2019
12019
ENETwild modelling of wild boar distribution and abundance: initial model output based on hunting data and update of occurrence-based models
P Acevedo, S Croft, GC Smith, J Vicente
EFSA Supporting Publications 16 (5), 25, 2019
12019
Wild boar in focus: initial model outputs of wild boar distribution based on occurrence data and identification of priority areas for data collection
S Croft, GC Smith, P Acevedo, J Vicente
EFSA Supporting Publications 16 (1), 26, 2019
12019
Analysis of hunting statistics collection frameworks for wild boar across Europe and proposals for improving the harmonisation of data collection
J Vicente, R Plhal, JA Blanco‐Aguiar, M Sange, T Podgórski, K Petrovic, ...
EFSA Supporting Publications 15 (12), 33, 2018
1*2018
Evaluating EFSA protection goals for honey bees (Apis mellifera): what do they mean for pollination?
S Croft, M Brown, S Wilkins, A Hart, GC Smith
Integrated Enivronmental Assessment and Managament 14 (6), 750-758, 2018
1*2018
ENETwild modelling of wild boar distribution and abundance: update of occurrence and hunting data-based models
P Acevedo, S Croft, GC Smith, JA Blanco-Aguiar, J Fernandez-Lopez, ...
EFSA Supporting Publications 16 (8), 1674E, 2019
2019
Modeling current and potential distributions of mammal species using presence‐only data: A case study on British deer
S Croft, AI Ward, JN Aegerter, GC Smith
Ecology and Evolution 9 (15), 8724-8735, 2019
2019
The risk of foot-and-mouth disease becoming endemic in a wildlife host is driven by spatial extent rather than density
S Croft, JN Aegerter, G Massei, GC Smith
PLoS ONE 14 (6), e0218898, 2019
2019
Science-based wildlife disease response
J Vicente, M Apollonio, JA Blanco-Aguiar, T Borowik, F Brivio, J Casaer, ...
Science 364 (6444), 943-944, 2019
2019
Mind the data gap! Systematic prediction of distribution and abundance for mammals in GB
S Croft, GC Smith
Mammal News, 18-19, 2016
2016
Modelling collective motion and obstacle avoidance to assess avian collision risk with wind turbines
S Croft
University of York, 2014
2014
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Articles 1–19