Tania Gilbert

Dr. Tania Gilbert

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Research Focus & Metrics

Academic Career Length

21Years (2006-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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24 February 2023 in Science
Verified
Journal Article
Closed access
DSDonal Smith
Donal Smith
TAThomas Abeli
Thomas Abeli
EBEmily Beckman Bruns
Emily Beckman Bruns
SDSarah Elizabeth Dalrymple
Sarah Elizabeth Dalrymple
JFJeremy Foster
Jeremy Foster
JEJohn G. Ewen
John G. Ewen
Extinct in the Wild (EW) species are placed at the highest risk of extinction under the International Union for Conservation of Nature Red List, but the extent and variation in this risk have never been evaluated. Harnessing global databases of ex situ animal and plant holdings, we report on the perilous state of EW species. Most EW animal species—already compromised by their small number of founders—are maintained at population sizes far below the thresholds necessary to ensure demographic security. Most EW plant species depend on live propagation by a small number of botanic gardens, with a minority secured at seed bank institutions. Both extinctions and recoveries are possible fates for EW species. We urgently call for international effort to enable the latter.

1 January 2017 in International Zoo Yearbook
Verified
Journal Article
Closed access
PDF file
Tania GilbertTania Gilbert
Tania Gilbert
RGR. Gardner
R. Gardner
AKA. R. Kraaijeveld
A. R. Kraaijeveld
PRP. Riordan
P. Riordan

1 January 2020 in Biological Conservation
Verified
Journal Article
Closed access
RORob Ogden
Rob Ogden
JCJustin Chuven
Justin Chuven
Tania GilbertTania Gilbert
Tania Gilbert
CHCaroline Hosking
Caroline Hosking
KGKarim Gharbi
Karim Gharbi
HSHelen Senn
Helen Senn

15 May 2007 in Molecular Ecology
Verified
Journal Article
Closed access
PDF file
AIArati Iyengar
Arati Iyengar
Tania GilbertTania Gilbert
Tania Gilbert
TWT. Woodfine
T. Woodfine
JKJ. M. Knowles
J. M. Knowles
FDF. M. Diniz
F. M. Diniz
NMN. Maclean
N. Maclean

24 June 2016
Verified
Book Chapter
Closed access
PDF file
JNJohn Newby
John Newby
TWTim Wacher
Tim Wacher
SDSarah M. Durant
Sarah M. Durant
NPNathalie Pettorelli
Nathalie Pettorelli
Tania GilbertTania Gilbert
Tania Gilbert

25 January 2018 in PLOS ONE
Verified
Journal Article
Open access
PDF file
RCRobert S C Cooke
Robert S C Cooke
Tania GilbertTania Gilbert
Tania Gilbert
PRPhilip Riordan
Philip Riordan
DMDavid Mallon
David Mallon
The International Union for the Conservation of Nature (IUCN) Red List classifies species according to their risk of extinction, informing local to global conservation decisions. Here we look to advance the estimation of generation length, which is used as a time-scalar in the Red List as a way of accounting for differences in species’ life-histories. We calculated or predicted generation length for 86 species of antelope following the Rspan approach. We also tested the importance of both allometry (body-mass) and phylogeny (phylogenetic eigenvectors) as predictors of generation length within a Phylogenetic Eigenvector Map (PEM) framework. We then evaluated the predictive power of this PEM and two binning approaches, following a leave-one-out cross-validation routine. We showed that captive and wild longevity data are nonequivalent and that both body-mass and phylogeny are important predictors for generation length (body-mass explained 64% and phylogeny 36% of the partitioned explained variance). Plus, both the PEM, and the binning approach that included both taxonomic rank and body-mass, had good predictive power and therefore are suitable for extrapolating generation length to missing-data species. Therefore, based on our findings, we advise separating captive and wild data when estimating generation length, and considering the implications of wild and captive data more widely in life-history analyses. We also recommend that body-mass and phylogeny should be used in combination, preferably under a PEM framework (as it was less reliant on available reference species and more explicitly accounts for phylogenetic relatedness) or a binning approach if a PEM is not feasible, to extrapolate generation length to missing-data species. Overall, we provide a transparent, consistent and transferable workflow for improving the use of the Rspan method to calculate generation length for the IUCN Red List.