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3. The impacts of feral boar on woodland flora and fauna in Great Britain

Author

Mayle, B., Harmer, R., Kewitt, A., Peace, A., Straw, N., Williams, D., and Upson, M.

Subjects
biodiversity, feral boar, impacts, Sus scrofa, woodland, Agriculture, Botany, QK1-989
Abstract

Feral boar have relatively recently become established in woodlands in Great Britain, but the long-term effect of their presence, in particular rooting activity, on woodland habitats and biodiversity is unknown. Protocols to investigate boar presence, densities and impacts to inform policy makers and practitioners are being investigated within a collaborative project by Forest Research and The Food and Environment Research Agency, funded by Forestry Commission and Defra. Results are presented from initial studies on plants and invertebrates carried out in a series of woodlands in south east England.

Published
2011
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5. Modelled agroforestry outputs at field and farm scale to support biophysical and environmental assessments

Author

Palma, J.H.N., Oliveira, T., Crous-Duran, J., Graves, A.R., Garcia de Jalon, S., Upson, M., Giannitsopoulos, M., Burgess, P.J., Tomé, Margarida, Ferreiro-Dominguez, N., Mosquera-Losada, M.R., Gonzalez-Hernandez, P., Kay, S., Mirk, J., Smith, J., Moreno, G., Pantera, A., Mantovani, D., Rosati, A., Luske, B., and Hermansen, J.

Subjects
AGFORWARD, agroforestry
Abstract

Submitted by Margarida Galamba (galamba@isa.utl.pt) on 2018-01-29T14:46:13Z No. of bitstreams: 1 REP-CEF-4-Deliverable 6.17 Updated October 2017.pdf: 6016263 bytes, checksum: f3d745f09adc8d4c49f13fe302e5f284 (MD5) Made available in DSpace on 2018-01-29T14:46:13Z (GMT). No. of bitstreams: 1 REP-CEF-4-Deliverable 6.17 Updated October 2017.pdf: 6016263 bytes, checksum: f3d745f09adc8d4c49f13fe302e5f284 (MD5) Previous issue date: 2017-10 N/A

Published
2017

6. Yield-SAFE model improvements. Milestone Report 29 (6.4)

Author

Palma, J.H.N., Graves, A., Crous-Duran, J., Upson, M., Paulo, Joana Amaral, Oliveira, T.S., Garcia de Jálon, S., and Burgess, P.

Subjects
AGFORWARD, agroforestry
Abstract

The Yield-SAFE model is a parameter-sparse, process-based dynamic model for predicting resource capture, growth, and production in agroforestry systems that has been frequently used by various research organisations in recent years. Within the AGFORWARD project, the model has been enhanced to more accurately predict the delivery of ecosystem services provided by agroforestry systems relative to forestry and arable systems. This report also summar izes the new developments made in the model which were partially implemented during AGFORWARD modelling workshops held in 1) Monchique in Portugal in May 2015, 2) Kriopigi in Greece in June 2015, 3) Lisbon in Portugal in November 2015 and 4) Lisbon in Febru ary 2016 .

Published
2016

8. AGFORWARD Project Periodic Report: January to December 2014

Author

Burgess, P.J., Crous-Duran, J., den Herder, M., Dupraz, C., Fagerholm, N., Freese, D., Garnett, K., Graves, A.R., Hermansen, J.E., Liagre, F., Mirck, J., Moreno, G., Mosquera-Losada, M.R., Palma, J.H.N., Pantera, A., Plieninger, T., and Upson, M.

Subjects
AGFORWARD, agroforestry
Abstract

Submitted by Margarida Galamba (galamba@isa.utl.pt) on 2015-09-09T15:24:37Z No. of bitstreams: 1 REP-CEF-3-AGFORWARD 613520 First Year Report 27 Feb 2015.pdf: 3329372 bytes, checksum: c2952e247a91e50d2f66c42d33b80387 (MD5) Made available in DSpace on 2015-09-09T15:24:37Z (GMT). No. of bitstreams: 1 REP-CEF-3-AGFORWARD 613520 First Year Report 27 Feb 2015.pdf: 3329372 bytes, checksum: c2952e247a91e50d2f66c42d33b80387 (MD5) Previous issue date: 2015-02

Published
2015

9. Innovations to be examined for high nature and cultural value agroforestry. Milestone 2.2 (MS3)

Author

Moreno, G., Staffan, B., Burgess, P.J., Camilli, F., Crous-Duran, J., Franca, A., Hongtao, H., Hartel, T., Lind, T., Mirck, J., Palma, J.H.N., Paulo, Joana Amaral, Pisanelli, A., Seddaiu, G., Thenail, C., Tsonkova, P., Upson, M., Valinger, E., Varga, A., Viaud, V., and Vityi, A.

Subjects
AGFORWARD, agroforestry
Abstract

Submitted by Margarida Galamba (galamba@isa.utl.pt) on 2015-09-09T15:34:59Z No. of bitstreams: 1 REP-CEF-4-Milestone2_2_Innovations.pdf: 860388 bytes, checksum: db3260b3fff30a6a34ec9309c682990a (MD5) Made available in DSpace on 2015-09-09T15:34:59Z (GMT). No. of bitstreams: 1 REP-CEF-4-Milestone2_2_Innovations.pdf: 860388 bytes, checksum: db3260b3fff30a6a34ec9309c682990a (MD5) Previous issue date: 2015-01-20

Published
2015

12. Where does prepotency come from on developmental tests of inhibitory control?

Author

Simpson A, Upson M, and Carroll DJ

Subjects
Association Learning, Child, Preschool, Female, Humans, Male, Task Performance and Analysis, Child Development, Cognition, Executive Function, Inhibition, Psychological
Abstract

Understanding the processes that make responses prepotent is central to understanding the role of inhibitory control in cognitive development. The question of what makes responses prepotent was investigated using the two most widely studied measures of preschoolers' inhibitory control. Across two experiments, 80 children were tested either on a series of stimulus-response compatibility (SRC) tasks or on a series of Go/No-go tasks. Results indicated that high levels of prepotency on SRC tasks (such as the Day/Night task) occur only under specific conditions; making a verbal response can be highly prepotent if the stimulus and response are associated with each other (e.g., saying "cup" to a cup) but is less prepotent when they are unassociated (e.g., saying "cup" to a doorstop). Action responses (e.g., lifting a cup to your mouth) show little prepotency irrespective of whether the stimulus and response are associated. In contrast, with Go/No-go tasks, a much wider variety of behaviors are highly prepotent regardless of whether the stimulus and response are associated. These data suggest that prepotency arises in very different ways, depending on the type of task used. Although both Go/No-go tasks and SRC tasks can make inhibitory demands, they do so for fundamentally different reasons., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Published
2017
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