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Effective and targeted conservation action requires detailed information about species, their distribution, systematics and ecology as well as the distribution of threat processes which affect them. Knowledge of reptilian diversity remains surprisingly disparate, and innovative means of gaining rapid insight into the status of reptiles are needed in order to highlight urgent conservation cases and inform environmental policy with appropriate biodiversity information in a timely manner. We present the first ever global analysis of extinction risk in reptiles, based on a random representative sample of 1500 species (16% of all currently known species). To our knowledge, our results provide the first analysis of the global conservation status and distribution patterns of reptiles and the threats affecting them, highlighting conservation priorities and knowledge gaps which need to be addressed urgently to ensure the continued survival of the world’s reptiles. Nearly one in five reptilian species are threatened with extinction, with another one in five species classed as Data Deficient. The proportion of threatened reptile species is highest in freshwater environments, tropical regions and on oceanic islands, while data deficiency was highest in tropical areas, such as Central Africa and Southeast Asia, and among fossorial reptiles. Our results emphasise the need for research attention to be focussed on tropical areas which are experiencing the most dramatic rates of habitat loss, on fossorial reptiles for which there is a chronic lack of data, and on certain taxa such as snakes for which extinction risk may currently be underestimated due to lack of population information. Conservation actions specifically need to mitigate the effects of human-induced habitat loss and harvesting, which are the predominant threats to reptiles.
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The conservation status of the world’s reptiles
Monika Böhm
a,
, Ben Collen
a
, Jonathan E.M. Baillie
b
, Philip Bowles
c
, Janice Chanson
d,e
, Neil Cox
c,d
,
Geoffrey Hammerson
f
, Michael Hoffmann
g
, Suzanne R. Livingstone
h
, Mala Ram
a
, Anders G.J. Rhodin
i
,
Simon N. Stuart
j,k,l,m,n
, Peter Paul van Dijk
l
, Bruce E. Young
o
, Leticia E. Afuang
p
, Aram Aghasyan
q
, Andrés
García
r
, César Aguilar
s
, Rastko Ajtic
t
, Ferdi Akarsu
u
, Laura R.V. Alencar
v
, Allen Allison
w
, Natalia Ananjeva
x
,
Steve Anderson
y
, Claes Andrén
z
, Daniel Ariano-Sánchez
aa
, Juan Camilo Arredondo
ab
, Mark Auliya
ac
,
Christopher C. Austin
ad
, Aziz Avci
ae
, Patrick J. Baker
af,ag
, André F. Barreto-Lima
ah
, César L. Barrio-Amorós
ai
,
Dhruvayothi Basu
aj
, Michael F. Bates
ak
, Alexandre Batistella
al
, Aaron Bauer
am
, Daniel Bennett
an
, Wolfgang
Böhme
ao
, Don Broadley
ap
, Rafe Brown
aq
, Joseph Burgess
ar
, Ashok Captain
as
, Santiago Carreira
at
, Maria del
Rosario Castañeda
au
, Fernando Castro
av
, Alessandro Catenazzi
aw
, José R. Cedeño-Vázquez
ax
, David G.
Chapple
ay,az
, Marc Cheylan
ba
, Diego F. Cisneros-Heredia
bb
, Dan Cogalniceanu
bc
, Hal Cogger
bd
, Claudia
Corti
be
, Gabriel C. Costa
bf
, Patrick J. Couper
bg
, Tony Courtney
bh
, Jelka Crnobrnja-Isailovic
bi
, Pierre-André
Crochet
ba
, Brian Crother
bj
, Felix Cruz
bk
, Jennifer C. Daltry
bl
, R.J. Ranjit Daniels
bm
, Indraneil Das
bn
, Anslem
de Silva
bo,bp
, Arvin C. Diesmos
bq
, Lutz Dirksen
br
, Tiffany M. Doan
bs
, C. Kenneth Dodd Jr.
bt
, J. Sean Doody
ay
,
Michael E. Dorcas
bu
, Jose Duarte de Barros Filho
bv
, Vincent T. Egan
bw
, El Hassan El Mouden
bx
, Dirk
Embert
by
, Robert E. Espinoza
bz
, Alejandro Fallabrino
ca
, Xie Feng
cb
, Zhao-Jun Feng
cc
, Lee Fitzgerald
cd
, Oscar
Flores-Villela
ce
, Frederico G.R. França
cf
, Darrell Frost
cg
, Hector Gadsden
ch
, Tony Gamble
ci
, S.R. Ganesh
cj
,
Miguel A. Garcia
ck
, Juan E. García-Pérez
cl
, Joey Gatus
cm
, Maren Gaulke
cn
, Philippe Geniez
co
, Arthur
Georges
cp
, Justin Gerlach
cq
, Stephen Goldberg
cr
, Juan-Carlos T. Gonzalez
p,cs
, David J. Gower
ct
, Tandora
Grant
cu
, Eli Greenbaum
cv
, Cristina Grieco
cw
, Peng Guo
cx
, Alison M. Hamilton
cy
, Kelly Hare
cz
, S. Blair
Hedges
da
, Neil Heideman
db
, Craig Hilton-Taylor
dc
, Rod Hitchmough
dd
, Bradford Hollingsworth
de
, Mark
Hutchinson
df
, Ivan Ineich
dg
, John Iverson
dh
, Fabian M. Jaksic
di
, Richard Jenkins
dj,dk,dl
, Ulrich Joger
dm
, Reizl
Jose
dn
, Yakup Kaska
do
,Ug
˘ur Kaya
dp
, J. Scott Keogh
dq
, Gunther Köhler
dr
, Gerald Kuchling
ds
, Yusuf
Kumlutasß
dt
, Axel Kwet
du
, Enrique La Marca
dv
, William Lamar
dw
, Amanda Lane
dx
, Bjorn Lardner
dy
, Craig
Latta
dz
, Gabrielle Latta
dz
, Michael Lau
ea
, Pablo Lavin
eb
, Dwight Lawson
ec
, Matthew LeBreton
ed
, Edgar
Lehr
ee
, Duncan Limpus
ef
, Nicola Lipczynski
eg
, Aaron S. Lobo
eh
, Marco A. López-Luna
ei
, Luca Luiselli
ej
,
Vimoksalehi Lukoschek
ek,el
, Mikael Lundberg
em
, Petros Lymberakis
en
, Robert Macey
eo
, William E.
Magnusson
ep
, D. Luke Mahler
eq
, Anita Malhotra
er
, Jean Mariaux
es
, Bryan Maritz
et
, Otavio A.V. Marques
eu
,
Rafael Márquez
ev
, Marcio Martins
v
, Gavin Masterson
et
, José A. Mateo
ew
, Rosamma Mathew
ex
, Nixon
Mathews
ey
, Gregory Mayer
ez
, James R. McCranie
fa
, G. John Measey
fb
, Fernando Mendoza-Quijano
fc
,
Michele Menegon
fd
, Sébastien Métrailler
fe
, David A. Milton
ff
, Chad Montgomery
fg
, Sérgio A.A. Morato
fh
,
Tami Mott
, Antonio Muñoz-Alonso
fj
, John Murphy
fk
, Truong Q. Nguyen
ao,
, Göran Nilson
fm
, Cristiano
Nogueira
fn
, Herman Núñez
fo
, Nikolai Orlov
x
, Hidetoshi Ota
fp
, José Ottenwalder
fq
, Theodore Papenfuss
fr
,
Stesha Pasachnik
fs
, Paulo Passos
ft
, Olivier S.G. Pauwels
fu
, Néstor Pérez-Buitrago
fv
, Valentín Pérez-
Mellado
fw
, Eric R. Pianka
fx
, Juan Pleguezuelos
fy
, Caroline Pollock
dc
, Paulino Ponce-Campos
fz
, Robert
Powell
ga
, Fabio Pupin
fd
, Gustavo E. Quintero Díaz
gb
, Raju Radder
gc
, Jan Ramer
gd
, Arne R. Rasmussen
ge
,
Chris Raxworthy
cg
, Robert Reynolds
gf
, Nadia Richman
a
, Edmund L. Rico
gg
, Elisa Riservato
gh
, Gilson Rivas
gi
,
Pedro L.B. da Rocha
gj
, Mark-Oliver Rödel
gk
, Lourdes Rodríguez Schettino
gl
, Willem M. Roosenburg
gm
,
James P. Ross
bt,gn
, Riyad Sadek
go
, Kate Sanders
gp
, Georgina Santos-Barrera
gq
, Hermann H. Schleich
gr
,
Benedikt R. Schmidt
gs,gt
, Andreas Schmitz
gu
, Mozafar Sharifi
gv
, Glenn Shea
dx
, Hai-Tao Shi
gw
, Richard
Shine
gc
, Roberto Sindaco
cw
, Tahar Slimani
bx
, Ruchira Somaweera
gc
, Steve Spawls
gx
, Peter Stafford
ct
, Rob
0006-3207/$ - see front matter Ó2012 Elsevier Ltd. All rights reserved.
http://dx.doi.org/10.1016/j.biocon.2012.07.015
Biological Conservation 157 (2013) 372–385
Contents lists available at SciVerse ScienceDirect
Biological Conservation
journal homepage: www.elsevier.com/locate/biocon
Stuebing
fk
, Sam Sweet
gy
, Emerson Sy
gz
, Helen J. Temple
ha
, Marcelo F. Tognelli
c,hb
, Krystal Tolley
hc
, Peter J.
Tolson
hd
, Boris Tuniyev
he
, Sako Tuniyev
he
, Nazan Üzüm
ae
, Gerard van Buurt
hf
, Monique Van Sluys
hg
,
Alvaro Velasco
hh
, Miguel Vences
hi
, Milan Vesely
´
hj
, Sabine Vinke
hk
, Thomas Vinke
hk
, Gernot Vogel
hl
, Milan
Vogrin
hm
, Richard C. Vogt
ep
, Oliver R. Wearn
a
, Yehudah L. Werner
hn,ho
, Martin J. Whiting
hp
, Thomas
Wiewandt
hq
, John Wilkinson
hr
, Byron Wilson
hs
, Sally Wren
b
, Tara Zamin
ht
, Kaiya Zhou
hu
, George Zug
cy
a
Institute of Zoology, Zoological Society of London, Regent’s Park, London NW1 4RY, UK
b
Conservation Programmes, Zoological Society of London, Regent’s Park, London NW1 4RY, UK
c
IUCN – CI Biodiversity Assessment Unit, Conservation International, 2011 Crystal Drive Ste 500, Arlington, VA 22202, USA
d
Species Programme, IUCN, Rue Mauverney 28, 1196 Gland, Switzerland
e
IUCN – CI Biodiversity Assessment Unit, c/o 130 Weatherall Road, Cheltenham 3192, Vic., Australia
f
NatureServe, 746 Middlepoint Road, Port Townsend, WA 98368, USA
g
IUCN SSC Species Survival Commission, c/o United Nations Environment Programme World Conservation Monitoring Centre, 219 Huntingdon Road, Cambridge CB3 0DL, UK
h
Ecology and Evolutionary Biology, Faculty of Biomedical & Life Sciences, Graham Kerr Building, University of Glasgow, Glasgow, Scotland G12 8QQ, UK
i
Chelonian Research Foundation, 168 Goodrich St., Lunenburg, MA 01462, USA
j
IUCN Species Survival Commission, Rue Mauverney 28, 1196 Gland, Switzerland
k
United Nations Environment Programme World Conservation Monitoring Centre, 219 Huntington Road, Cambridge CB3 0DL, UK
l
Conservation International, 2011 Crystal Drive Ste 500, Arlington, VA 22202, USA
m
Department of Biology and Biochemistry, University of Bath, Bath BA2 7AY, UK
n
Al Ain Wildlife Park and Resort, PO Box 45553, Abu Dhabi, United Arab Emirates
o
NatureServe, 4600 N. Fairfax Dr., 7th Floor, Arlington, VA 22203, USA
p
Institute of Biological Sciences, University of the Philippines, Los Banos, College, Laguna 4031, Philippines
q
Protected Areas Management Department, Bioresources Management Agency of Ministry of Nature Protection, Yerevan, Armenia
r
Estación de Biología Chamela, Instituto de Biología, U.N.A.M., Apdo. Postal 21, San Patricio, Jalisco 48980, Mexico
s
Departamento de Herpetología, Museo de Historia Natural, Universidad Nacional Mayor de San Marcos, Peru
t
Institute for Nature Conservation of Serbia, dr Ivana Ribara 91, 11070 Belgrade, Serbia
u
Dog
˘a Derneg
˘i (Nature Association), Hürriyet cad. 43/12 Dikmen, Ankara, Turkey
v
Departamento de Ecologia, Instituto de Biociencias, Universidade de São Paulo, 05508-090 São Paulo, SP, Brazil
w
Bishop Museum, 1525 Bernice Street, Honolulu, HI 96817, USA
x
Zoological Institute, Russian Academy of Sciences, St. Petersburg 199034, Universitetskaya nab. 1, Russia
y
University of the Pacific, 3601 Pacific Avenue, Stockton, California 95211, USA
z
Nordens Ark, Åby säteri, SE-456 93 Hunnebostrand, Sweden
aa
Organización Zootropic, General Projects, 12 Calle 1–25, Zona 10, Edificio Geminis 10, Guatemala 1001, Guatemala
ab
Museu de Zoologia, Universidade de São Paulo, Caixa Postal 42494, São Paulo 04218-170, Brazil
ac
Helmholtz Centre for Environmental Research - UFZ, Department of Conservation Biology, Permoserstrasse 15, 04318 Leipzig, Germany
ad
Department of Biological Sciences, Museum of Natural Science, Louisiana State University, 119 Foster Hall, Baton Rouge, LA 70803-3216, USA
ae
Adnan Menderes University, Faculty of Science and Arts, Department of Biology, Aydın, Turkey
af
Texas A& M University System, AgriLIFE Research, Blackland Research and Extension Center, 720 E Blackland Rd, Temple, TX 76502, USA
ag
The Wetlands Institute, 1075 Stone Harbor Blvd, Stone Harbor, NJ 08247, USA
ah
Universidade Federal do Rio Grande do Sul – Instituto de Biociências, Avenida Bento Gonçalves 9500, Agronomia, 91-540-000 Porto Alegre-RS, Brazil
ai
Fundación Andígena, PO Box 210, Mérida 5101-A, Mérida, Venezuela
aj
The Katerniaghat Foundation, C-421 Sector-B, Mahanagar, Lucknow 226 006, India
ak
Department of Herpetology, National Museum, PO Box 266, Bloemfontein 9300, South Africa
al
Department of the Environment – Mato Grosso, Brazil
am
Department of Biology, Villanova University, 800 Lancaster Avenue, Villanova, PA 19085, USA
an
Mampam Conservation, Glossop, UK
ao
Zoologisches Forschungsmuseum Alexander Koenig (ZFMK), Adenauerallee 160, 53113 Bonn, Germany
ap
Department of Herpetology, Natural History Museum of Zimbabwe, P.O. Box 240, Bulawayo, Zimbabwe
aq
University of Kansas Natural History Museum and Biodiversity Institute, Department of Ecology and Evolutionary Biology, University of Kansas, Dyche Hall, 1345 Jayhawk Blvd,
Lawrence, KS66045-7593, USA
ar
Guana Tolomato Matanzas National Estuarine Research Reserve, Ponte Vedra, FL 32082, USA
as
3/1 Boat Club Road, Pune 411 001, Maharashtra, India
at
Laboratorio de Sistemática de Vertebrados e Historia Natural, Instituto de Ecología y Ciencias Ambientales, Facultad de Ciencias (UDELAR) and Museo Nacional de Historia Natural,
Montevideo, Uruguay
au
Museum of Comparative Zoology, Harvard University, 26 Oxford Street, Cambridge, MA 02138, USA
av
Departamento de Biología, Universidad del Valle, Cali, Colombia
aw
University of California, Berkeley, CA 94720-3160, USA
ax
Instituto Tecnológico de Chetumal, Av. Insurgentes No. 330, C.P. 77013, Col. David Gustavo Gtz., Chetumal, Quintana Roo, Mexico
ay
School of Biological Sciences, Monash University, Clayton, Vic. 3800, Australia
az
Allan Wilson Centre for Molecular Ecology & Evolution, School of Biological Sciences, Victoria University of Wellington, PO Box 600, Wellington, New Zealand
ba
CNRS-UMR5175, Centre d’Ecologie Fonctionnelle et Evolutive, 1919 route de Mende, 34293 Montpellier
C
edex 5, France
bb
Universidad San Francisco de Quito, Colegio de Ciencias Biológicas y Ambientales, calle Diego de Robles y Vía Interoceánica, campus Cumbayá, edif. Darwin, DW-010A. Casilla Postal
17-12-841, Quito, Ecuador
bc
University Ovidius Constanta, Faculty of Natural Sciences, Romania
bd
Australian Museum, 6 College Street, Sydney, NSW 2010, Australia
be
Museo di Storia Naturale dell’Università di Firenze, Sezione di Zoologia ‘‘La Specola’’, Italy
bf
Universidade Federal do Rio Grande do Norte, Natal-RN, Brazil
bg
Biodiversity Program, Queensland Museum, PO Box 3300, South Bank, Brisbane, Qld 4101, Australia
bh
Queensland Department of Employment, Economic Development and Innovation, Southern Fisheries Centre, PO Box 76, Deception 4508, Qld, Australia
bi
Faculty of Sciences and Mathematics, University of Niš & IBISS Beograd, Serbia
bj
Department of Biological Sciences, Southeastern Louisiana University, Hammond, LA 70402, USA
bk
INIBIOMA (CONICET-UNComa), Quintral 1250, (8400) Bariloche, Rio Negro, Argentina
bl
Fauna & Flora International, Jupiter House, Station Road, Cambridge CB1 2JD, UK
bm
Care Earth Trust, No 5, 21st Street, Thillaiganganagar, Chennai 600 061, India
bn
Institute of Biodiversity and Environmental Conservation, Universiti Malaysia Sarawak, 94300 Kota Samarahan, Sarawak, Malaysia
bo
Rajarata University of Sri Lanka, Mihintale, Sri Lanka
bp
Amphibian Specialist Group IUCN SSC Working Group, Sri Lanka
M. Böhm et al. / Biological Conservation 157 (2013) 372–385 373
bq
Herpetology Department, Philippine National Museum, Padre Burgos St, Manila, Philippines
br
Reptile and Animal Presentation, Neukirchstr. 37a,13089 Berlin, Germany
bs
Department of Biology, Central Connecticut State University, New Britain, CT 06050, USA
bt
Department of Wildlife Ecology and Conservation, University of Florida, Gainesville, FL 32611, USA
bu
Department of Biology, Davidson College, Davidson, NC 28035-7118, USA
bv
Laboratório de Zoologia de Vertebrados, Universidade Estadual do Rio de Janeiro (LAZOVERTE – UERJ), Brazil
bw
Department of Economic Development, Environment & Tourism, P. Bag X 9484, Polokwane 0700, Limpopo, South Africa
bx
Université Cadi Ayyad, Département de Biologie, BP 2390, Marrakech, Morocco
by
Fundacion Amigos de la Naturaleza, Santa Cruz de la Sierra, Bolivia
bz
Department of Biology, California State University, Northridge, CA 91330-8303, USA
ca
Karumbe, D. Murillo 6334, Montevideo, Uruguay
cb
Chengdu Institute of Biology, Chinese Academy of Sciences, P.O. Box 416, Chengdu, Sichuan, China
cc
Xuzhou Normal University, Jiangsu Province, China
cd
Texas A&M University, 210 Nagle Hall, College Station, TX 77843-2258, USA
ce
Museo de Zoologia, Fac. De Cienicas, Universidad Nacional Autónoma de México (U.N.A.M.), Mexico
cf
Universidade Federal da Paraíba, Rio Tinto, PB, Brazil
cg
American Museum of Natural History, Central Park West at 79th St., New York, NY 10024, USA
ch
Instituto de Ecología, A. C., Chihuahua 31109, Chihuahua, Mexico
ci
University of Minnesota, Minneapolis, MN 55455, USA
cj
Chennai Snake Park, Rajbhavan post, Chennai 600 022, Tamil Nadu, India
ck
Department of Natural Resources, Puerto Rico
cl
Museo de Zoologı
`a, UNELLEZ-Guanare, Venezuela
cm
Biology Department, University of San Carlos, Cebu, Philippines
cn
GeoBio Center, Ludwig-Maximilians-Universität München, Richard-Wagner-Str. 10, 80333 München, Germany
co
EPHE-UMR5175, Centre d’Ecologie Fonctionnelle et Evolutive, 1919 route de Mende, 34293 Montpellier
C
edex 5, France
cp
Institute for Applied Ecology, University of Canberra, ACT 2601, Australia
cq
Nature Protection Trust of Seychelles, 133 Cherry Hinton Road, Cambridge CB1 7BX, UK
cr
Whittier College, Department of Biology, Whittier, CA 90608, USA
cs
Edward Grey Institute for Field Ornithology, Department of Zoology, University of Oxford, South Parks Road, Oxford OX1 3PS, UK
ct
Department of Zoology, Natural History Museum, London SW7 5BD, UK
cu
San Diego Zoo Institute for Conservation Research, 15600 San Pasqual Valley Road, Escondido, CA 92027, USA
cv
Department of Biological Sciences, University of Texas at El Paso, 500 West University Avenue, El Paso, TX 79968, USA
cw
Istituto per le Piante da Legno e l’Ambiente, corso Casale 476, I-10132 Torino, Italy
cx
Yibin University, Sichuan, China
cy
Division of Amphibian & Reptiles, National Museum of Natural History, Smithsonian Institution, Washington, DC 20013, USA
cz
Department of Zoology, University of Otago, P.O. Box 56, Dunedin 9054, New Zealand
da
Department of Biology, Pennsylvania State University, University Park, PA 16802, USA
db
University of the Free State, P.O. Box 339, Bloemfontein 9300, South Africa
dc
Species Programme, IUCN, 219c Huntingdon Road, Cambridge CB3 0DL, UK
dd
Department of Conservation, P.O. Box 10-420, Wellington 6143, New Zealand
de
Department of Herpetology, San Diego Natural History Museum, P.O. Box 121390, San Diego, CA 92112, USA
df
South Australian Museum, North Terrace, Adelaide, SA 5000, Australia
dg
Muséum National d’Histoire Naturelle, UMR CNRS 7205 (Origine, Structure et Evolution de la Biodiversite), Departement Systematique et Evolution, CP 30, 25 rue Cuvier, F-75005
Paris, France
dh
Department of Biology, Earlham College, Richmond, IN 47374, USA
di
Center for Advanced Studies in Ecology and Biodiversity (CASEB), Catholic University of Chile, Santiago, Chile
dj
Madagasikara Voakajy, B.P. 5181, Antananarivo, Madagascar
dk
Durrell Institute of Conservation and Ecology, School of Anthropology and Conservation, University of Kent, Canterbury CT2 7NR, UK
dl
School of Environment, Natural Resources and Geography, Bangor University, Gwynedd LL57 2UW, UK
dm
State Natural History Museum (Staatliches Naturhistorisches Museum), Pockelsstr. 10, 38106 Braunschweig, Germany
dn
Bohol Island State University, Bohol, Philippines
do
Pamukkale University, Department of Biology, Denizli, Turkey
dp
Department of Zoology, Section of Biology, Faculty of Science, Ege University, 35100 Bornova/Izmir, Turkey
dq
Research School of Biology, The Australian National University, Canberra, ACT 0200, Australia
dr
Senckenberg Forschungsinstitut und Naturmuseum, Senckenberganlage 25, D-60325 Frankfurt, Germany
ds
School of Animal Biology, The University of Western Australia, 35 Stirling Highway, Crawley, Perth, WA 6009, Australia
dt
Dokuz Eylül University, Faculty of Education, Department of Biology, Buca, _
Izmir, Turkey
du
Staatliches Museum für Naturkunde Stuttgart, Zoologie, Rosenstein 1, D-70191 Stuttgart, Germany
dv
Laboratorio de Biogeografía, Escuela de Geografía, Facultad de Ciencias Forestales y Ambientales, Universidad de Los Andes, Apartado Postal 116, Merida 5101-A, Venezuela
dw
University of Texas at Tyler, 3900 University Blvd., Tyler, TX 75799, USA
dx
Faculty of Veterinary Science, University of Sydney, NSW 2006, Australia
dy
Colorado State University, Fort Collins, CO 80523, USA
dz
Australian Freshwater Turtle Conservation & Research Association (AFTCRA Inc.), 53 Jubilee Road, Carters Ridge, Qld, Australia
ea
WWF – Hong Kong, Hong Kong Special Administrative Region
eb
Universidad Autonoma de Ciudad Juarez, Chihuahua, Mexico
ec
Zoo Atlanta, 800 Cherokee Avenue, SE Atlanta, GA 30315, USA
ed
Global Viral Forecasting Initiative, Cameroon
ee
Illinois Wesleyan University, Bloomington, IL 61702-2900, USA
ef
Environment and Resource Science Division, Department of Environment and Resource Management, Australia
eg
WildScreen, Ground Floor, The Rackhay, Queen Charlotte Street, Bristol BS1 4HJ, UK
eh
Department of Zoology, University of Cambridge CB2 3EJ, UK
ei
Universidad Juárez Autónoma de Tabasco, División Académica de Ciencias Biológicas, Villahermosa, Tabasco, Mexico
ej
Centre of Environmental Studies Demetra, via Olona 7, 00198 Roma, Italy
ek
University of California, Irvine, CA 92697, USA
el
ARC Centre of Excellence for Coral Reef Studies, James Cook University, Townsville, Qld 4811, Australia
em
Staatliche Naturhistorische Sammlungen Dresden, Museum für Tierkunde, Königsbrücker Landstr. 159, D-01109 Dresden, Germany
en
Natural History Museum of Crete, University of Crete, 71409 Irakleio, Greece
eo
Department of Biology, Merritt College, 12500 Campus Drive, Oakland, CA 94619, USA
374 M. Böhm et al. / Biological Conservation 157 (2013) 372–385
ep
Instituto Nacional de Pesquisas da Amazônia, Av. André Araújo, 2936, Aleixo, CEP 69083-000, Manaus, Amazonas, Brazil
eq
Center for Population Biology, University of California at Davis, Davis, CA 95616, USA
er
School of Biological Sciences, College of Natural Sciences, Bangor University, Deiniol Road, Bangor LL57 2UW, UK
es
Museum of Natural History, Route de Malagnou 1, 1208 Geneva, Switzerland
et
School of Animal, Plant and Environmental Sciences, University of the Witwatersrand, P.O. Wits 2050, South Africa
eu
Laboratório de Ecologia e Evolução, Instituto Butantan, Av. Vital Brazil 1500, São Paulo, SP 05503-900, Brazil
ev
Fonoteca Zoológica, Dept Biodiversidad y Biologia Evolutiva, Museo Nacional de Ciencias Naturales (CSIC), José Gutierrez Abascal 2, 28006 Madrid, Spain
ew
BIOGES, University of Las Palmas, 35001 Las Palmas, Canary Islands, Spain
ex
Zoological Survey of India, North Eastern Regional Centre, Fruit Garden, Risa Colony, Shillong 793 003, Meghalaya, India
ey
Wildlife Trust for India (WTI), Species Recovery Program, India
ez
Department of Biological Sciences, University of Wisconsin-Parkside, Kenosha, WI 53141, USA
fa
Smithsonian Institution Research Associate, USA
fb
School of Environmental Sciences and Development, North-West University, Private Bag X6001, Potchefstroom 2520, South Africa
fc
Instituto Tecnológico de Huejutla, Carr. Huejutla-Chalahuiyapa, A.P. 94, Huejutla de Reyes, Hidalgo 43000, Mexico
fd
Museo Tridentino di Scienze Naturali, Via Calepina 14, 38122 Trento, Italy
fe
Ch. du Bosquet 6, 1967 Bramois, Switzerland
ff
CSIRO Marine and Atmospheric Research, P.O. Box 120, Cleveland, 4163 Qld, Australia
fg
Truman State University, Kirksville, MO 63501, USA
fh
Universidade Tuiuti do Paraná, Curitiba, Parana State, Brazil
Departamento de Biologia e Zoologia, Instituto de Biociências, Universidade Federal do Mato Grosso, Cuiabá, Brazil
fj
El Colegio de la Frontera Sur, Chiapas, Mexico
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Field Museum of Natural History, 1400 S. Lake Shore Dr, Chicago, IL 60605-2496, USA
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Institute of Natural and Environmental Sciences, University of Hyogo, Yayoigaoka 6, Sanda, Hyogo 669-1546, Japan
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Museum of Vertebrate Zoology, 3101 Valley Life Sciences Building, University of California, Berkeley, CA 94720-3160, USA
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Departamento de Vertebrados, Museu Nacional, Universidade Federal do Rio de Janeiro, São Cristovão, Rio de Janeiro, RJ 20940-040, Brazil
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Département des Vertébrés Récents, Institut Royal des Sciences naturelles de Belgique, Rue Vautier 29, 1000 Brussels, Belgium
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Universidad Autónoma de Aguascalientes, C. P. 20131, Aguascalientes, Mexico
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School of Biological Sciences A08, University of Sydney, NSW 2006, Australia
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Indianapolis Zoo, Indianapolis, IN 46222, USA
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School of Conservation, The Royal Danish Academy of Fine Arts, Esplanaden 34, DK-1263 Copenhagen K, Denmark
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Biology Department, American University of Beirut, Beirut, Lebanon
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Filadelfia 853, 9300 Fernheim, Paraguay
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Society for Southeast Asian Herpetology, Im Sand 3, D-69115 Heidelberg, Germany
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M. Böhm et al. / Biological Conservation 157 (2013) 372–385 375
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Department of Biology, Queens University, Kingston, Ont., Canada K7L 3N6
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College of Life Sciences, Nanjing Normal University, Nanjing, China
article info
Article history:
Received 17 February 2012
Received in revised form 15 June 2012
Accepted 13 July 2012
Keywords:
IUCN Red List
Extinction risk
Threatened species
Lizards
Snakes
Turtles
Distribution maps
abstract
Effective and targeted conservation action requires detailed information about species, their distribution,
systematics and ecology as well as the distribution of threat processes which affect them. Knowledge of
reptilian diversity remains surprisingly disparate, and innovative means of gaining rapid insight into the
status of reptiles are needed in order to highlight urgent conservation cases and inform environmental
policy with appropriate biodiversity information in a timely manner. We present the first ever global
analysis of extinction risk in reptiles, based on a random representative sample of 1500 species (16%
of all currently known species). To our knowledge, our results provide the first analysis of the global con-
servation status and distribution patterns of reptiles and the threats affecting them, highlighting conser-
vation priorities and knowledge gaps which need to be addressed urgently to ensure the continued
survival of the world’s reptiles. Nearly one in five reptilian species are threatened with extinction, with
another one in five species classed as Data Deficient. The proportion of threatened reptile species is high-
est in freshwater environments, tropical regions and on oceanic islands, while data deficiency was high-
est in tropical areas, such as Central Africa and Southeast Asia, and among fossorial reptiles. Our results
emphasise the need for research attention to be focussed on tropical areas which are experiencing the
most dramatic rates of habitat loss, on fossorial reptiles for which there is a chronic lack of data, and
on certain taxa such as snakes for which extinction risk may currently be underestimated due to lack
of population information. Conservation actions specifically need to mitigate the effects of human-
induced habitat loss and harvesting, which are the predominant threats to reptiles.
Ó2012 Elsevier Ltd. All rights reserved.
1. Introduction
Reptiles
1
and their immediate diapsid ancestors have had a long
and complex evolutionary history, having first appeared on the planet
in the late Palaeozoic Era, more than 250 million years ago (based on
molecular phylogeny estimates and early fossil records: e.g., Hedges
and Poling, 1999; Reisz et al., 2011; van Tuinen and Hadly, 2004). High
rates of cladogenesis in the Triassic and Jurassic periods (Vidal and
Hedges, 2009) produced a diverse group of animals adapted to almost
every temperate, tropical and desert environment, and to terrestrial,
freshwater and marine habitats. Reptiles play important roles in nat-
ural systems, as predators, prey, grazers, seed dispersers and com-
mensal species; they serve as bioindicators for environmental
health, and their often specific microhabitat associations provide the
ideal study system to illustrate the biological and evolutionary pro-
cesses underlying speciation (Raxworthy et al., 2008; Read, 1998).
Reptiles generally have narrower distributional ranges than other ver-
tebrates such as birds and mammals (Anderson, 1984; Anderson and
Marcus, 1992), making them more susceptible to threat processes;
however, it should be noted that there is some marked variation in
range size between different clades of reptiles, so that generalisations
and comparisons may not hold true universally [e.g., range sizes of
snakes are generally larger than those of lizards (Anderson and Mar-
cus, 1992)]. This combination of often small range and narrow niche
requirements makes reptiles susceptible to anthropogenic threat pro-
cesses, and they are therefore a group of conservation concern. Regio-
nal assessments in Europe (Cox and Temple, 2009) and southern Africa
(South Africa, Lesotho and Swaziland; Bates et al., in press) indicate
that one-fifth and one-tenth of reptilian species respectively are
threatened with extinction. It has also been proposed that reptilian
declines are similar in taxonomic breadth, geographic scope and
severity to those currently observed in amphibians (Gibbons et al.,
2000), although this claim was not quantitatively assessed by the
authors. Reptilian declines have been attributed to habitat loss and
degradation, as well as unsustainable trade, invasive species, pollu-
tion, disease and climate change (Cox and Temple, 2009; Gibbons
et al., 2000; Todd et al., 2010).
A total of 9,084 species of reptiles have been described so far
(Uetz, 2010), and new molecular evidence continues to unearth
numerous cryptic species that had not previously been detected
by morphological analyses (e.g., Adalsteinsson et al., 2009; Nagy
et al., 2012; Oliver et al., 2009). Yet as a group, reptiles are currently
poorly-represented on the IUCN Red List of Threatened Species, with
only 35% of described species evaluated, and those that are evalu-
ated were done so in a non-systematic manner (IUCN, 2011a).
Although the Global Reptile Assessment (GRA) will in the long run
address this bias, the current assessment process relies on regional
workshops and the formation of IUCN SSC Specialist Groups for spe-
cific reptilian taxa, which introduces geographical as well as taxo-
nomic bias into the analysis. Specifically, the Global Reptile
Assessment has carried out comprehensive assessments for North
America, Madagascar and New Caledonia, with complete endemic-
only assessments having been carried out in the Philippines, Europe
and selected island groups (Seychelles, Comoros and Socotra). As a
result, there are still large geographical gaps which are only slowly
being addressed, namely in Africa, Latin America, Asia and Australia.
This limits our understanding of how threat processes affect reptiles,
so that these taxa are often overlooked in conservation decisions,
specifically because the geographical, taxonomic and threatened
species bias still inherent in the current IUCN Red List for reptiles
makes taking conservation decisions impractical.
We present the results of the first assessment of extinction risk in
a randomly selected, representative and global sample of 1500 rep-
tiles, as a shortcut for deriving group patternson which to base sound
global conservation action. We produce the first global species- and
threatened species-richness maps for reptiles. The results highlight
key regions, taxa and anthropogenic threat processes which need
to be urgently targeted to effectively conserve the world’s reptiles.
Corresponding author. Tel.: +44 20 7449 6676.
E-mail address: monika.bohm@ioz.ac.uk (M. Böhm).
1
Here considered to include the various taxa that belong to the non-avian and non-
mammalian amniotes: Crocodylia, Testudines and Lepidosauria (snakes, lizards,
amphisbaenians, tuataras).
376 M. Böhm et al. / Biological Conservation 157 (2013) 372–385
2. Methods
2.1. Sampled approach to Red Listing
Following an approach set out in Baillie et al. (2008), we ran-
domly selected 1500 species from a list of all described reptilian
species (Uetz, 2010), using the sample function in R [sample (x,
size); R Development Core Team, 2007]. A sample of 1500 species
is sufficiently large to report on extinction risk and trends, and
buffers against falsely detecting improvements in extinction risk
(Baillie et al., 2008). Similarly, the representation of spatial patterns
derived from a sample of 1500 species was found to be in broad
agreement with spatial patterns derived from comprehensive
assessments in both mammals and amphibians (Collen, unpub-
lished data). Although the taxonomy of the full species list by Uetz
(2010) does not necessarily follow the taxonomy used by all herpe-
tologists, it is the only comprehensive reptile species list available
for the purpose of this project. Nevertheless, taxonomic changes
based on new research have been incorporated into the sampled
species list throughout the project (e.g., the split of Colubridae into
numerous families, as suggested by Zaher et al., 2009). It should be
noted that the rapid rate at which new species are being described
may have some bearing on the representativeness of our sample in
the future. Overall, however, we believe that this sampled approach
allows for analysis of extinction risk as well as the depiction of
broad-scale spatial threat status and processes. A full list of species
in the sample, and summaries by habitat system and biogeograph-
ical realm, are given in Tables S1 and S2 in the online supplemen-
tary material.
Our sample closely reflected the contribution of each group
towards total reptilian diversity, with the sample being made
up of 58% lizards, 37% snakes, 3% turtles/tortoises, 2% amphis-
baenians and <1% crocodiles (tuataras were not represented).
Overall, 220 of the 1500 selected species had been previously as-
sessed by IUCN, and these assessments were still up-to-date (i.e.,
they had been assessed since 2006); for the remaining 1280 spe-
cies, new or updated assessments were produced through con-
sultation with a global network of herpetologists and following
the IUCN Red List Categories and Criteria (IUCN, 2001). Through
a centralised editorial and reviewing process we ensured that
the IUCN Red List Categories and Criteria were consistently ap-
plied between species and regions. A total of 124 species were
re-assessed from previous assessments, and genuine changes
(category changes showing a real increase or decrease in extinc-
tion risk) or non-genuine changes (changes in category which
are due to new or better information becoming available, incor-
rect information used previously, taxonomic change affecting the
species, or previously incorrect application of the IUCN Red List
Criteria, rather than a true improvement or decline in Red List
category) were noted.
Extinction risk was assessed using the IUCN Red List Categories
and Criteria (IUCN, 2001). The IUCN Red List Categories classify
species’ extinction risk from Extinct (EX) and Extinct in the Wild
(EW), via the threatened categories Critically Endangered (CR),
Endangered (EN) and Vulnerable (VU) to Near Threatened (NT)
and Least Concern (LC). A species is listed as Data Deficient (DD)
if insufficient data are available to make a conservation assess-
ment. The Red List categories are assigned objectively based on a
number of criteria that indicate level of extinction risk, e.g., rate
of population decline (Criterion A), population size (Criteria C
and D), geographic range size and decline (Criterion B), or quanti-
tative analyses (Criterion E) (IUCN, 2001; Mace et al., 2008). Given
the nature of biological information available for reptiles, and the
general lack of population data for this group, most of the threa-
tened species in the sample were listed on the basis of restricted
geographic range under criteria B or D2 (see Appendix S3 in the on-
line supplementary material for more information on the assess-
ment process and the use of criteria).
Threats were recorded for each species. These were coded fol-
lowing Salafsky et al. (2008) and broadly defined as: threats due
to agriculture/aquaculture; biological resource use (e.g., hunting
and harvesting of species; logging activities); urban development
(residential and commercial); pollution; invasive or problematic
species; energy production and mining (oil drilling and mining);
natural system modifications (e.g., fire regimes, damming and
channelling of waterways); climate change and severe weather;
human intrusion and disturbance; transportation and service cor-
ridors (e.g., roads and shipping lanes); and geological events.
All of the species assessments have been reviewed and accepted
by the IUCN and are now published online (www.iucnredlist.org,
IUCN, 2011a), with the exception of some turtle and crocodilian
assessments which are still undergoing sign-off.
2.2. Species distributions and maps of threat processes
Distributions were mapped in ArcGIS for 1497 species [three
species lacked adequate distributional data: Anolis baccatus (DD),
Dipsas maxillaris (DD), Typhlops filiformis (DD)], based on georefer-
encing of distribution maps published in the literature, conversion
of point locations into ranges and expert feedback. Only extant
ranges were included in the analysis (i.e., extinct, possibly extinct
and uncertain parts of the range were omitted). We produced maps
of global species richness, threatened species richness and Data
Deficient species richness, by overlaying a hexagonal grid onto
the aggregated species’ distribution. The grid is defined on an ico-
sahedron, projected to the sphere using the inverse Icosahedral
Snyder Equal Area (ISEA) projection, and takes account of the
Earth’s spherical nature. We then summed the number of species
occurring in each hexagonal grid cell (cell size was approximately
7770 km
2
) to obtain the species richness pattern of our sample. We
also mapped the proportion of species classed as threatened (CR,
EN and VU categories), Near Threatened and Data Deficient per grid
cell.
We mapped underlying threat processes for all 1497 mapped
species as the number of threatened and Near Threatened spe-
cies within each grid cell affected by the threat process in ques-
tion. We expressed threat process prevalence using two
approaches. Approach A used the number of species affected
by a predominant threat and approach B the proportion of spe-
cies affected by each predominant threat type out of the total
number of species (all categories) present in each grid cell.
Although coarse in resolution, as threat processes are unlikely
to be equally distributed across a species’ range, these aggrega-
tions provide an impression of those locations where each threat
is affecting a particularly large number of species. The two ap-
proaches to threat mapping are likely to emphasise different as-
pects of the pattern, with approach A more likely to be
influenced by underlying species richness patterns, and approach
B by threat patterns being observed across areas of low reptile
numbers in our sample, where the presence of threat in one or
a few species is going to result in a larger proportional value
compared to species rich areas. It is also likely to be more easily
affected by biases in our sample in areas of overall low reptile
numbers. In terms of conservation action, approach A is likely
to correspond most closely to prioritisation measures which
maximise species richness through targeted conservation (similar
to hotspot approaches, although in this case driven by underly-
ing threat processes), while approach B gives a better indication
of areas where a threat process is affecting a larger proportion of
species (though most likely in areas of low species richness).
M. Böhm et al. / Biological Conservation 157 (2013) 372–385 377
2.3. Summarising the extinction risk of the world’s reptiles
We summarised extinction risk across all reptiles and sub-
groups (amphisbaenians, crocodiles, lizards, snakes, turtles/tor-
toises), and by biogeographical realm (see S3.3 in the online sup-
plementary material for information on the geographical extent
of biogeographical realms) and habitat system (terrestrial, fresh-
water, marine). We calculated proportions of threatened (Critically
Endangered, Endangered and Vulnerable) species by assuming that
Data Deficient species will fall into these categories in the same
proportion as non-Data Deficient species:
Prop
threat
¼ðCR þEN þVUÞ=ðNDDÞ;
where Nis the total number of species in the sample, CR, EN and VU
are the numbers of species in the Critically Endangered, Endangered
and Vulnerable categories respectively, and DD is the number of
species in the Data Deficient category. Threat levels have been re-
ported in this way in similar studies (e.g., Clausnitzer et al., 2009;
Hoffmann et al., 2010; Schipper et al., 2008), representing the cur-
rent consensus among conservation biologists about how the pro-
portion of threatened species should be presented, while also
accounting for the uncertainty introduced by DD species. The ap-
proach is likely to result in a conservative estimate of threat propor-
tions, since Data Deficient reptiles are often rare and restricted in
range, thus likely to fall within a threatened category in future
based on additional data [although in other taxa, indications are
that DD species will often fall into Least Concern categories (e.g.,
birds; Butchart and Bird, 2010) or remain largely Data Deficient
(e.g., mammals; Collen et al., 2011)]. Overall, the re-assessment of
DD species into different categories is very taxon-specific and de-
pends greatly on the attitude of the assessor to risk, so that it is dif-
ficult to make any generalisations about what the future status of
DD species might be. To deal with this uncertainty we calculated
upper and lower bounds of threat proportions by assuming that
(a) no Data Deficient species were threatened [lower margin:
Prop
threat
= (CR + EN + VU)/(N)], and (b) all Data Deficient species
were threatened [upper margin; Prop
threat
= (CR + EN + VU + DD)/N].
2.4. Taxonomic differences in extinction risk and the effect of range size
We followed Bielby et al. (2006) to evaluate whether extinction
risk is randomly distributed across taxonomic families [based on
the taxonomy by Uetz (2010), but including some Australasian
geckos in the Diplodactylidae (Han et al., 2004), see Table S1 for de-
tails], and tested for significant variation in threat levels across
families using a chi-square test. The absence of a random distribu-
tion of risk suggests that biological or geographical drivers of risk
exist, which can help focus conservation activity (Cardillo and
Meijaard, 2011). Where we detected taxonomically non-random
extinction risk, further analyses were employed to determine
which families deviated from the expected level of threat. Using
binomial tests, we calculated the smallest family size necessary
to detect a significant deviation from the observed proportion of
threatened species and excluded families represented by an insuf-
ficient number of species from subsequent analysis. We generated
a null frequency distribution of the number of threatened species
from 10,000 unconstrained randomizations, by randomly assigning
Red List categories to all species, based on the frequency of occur-
rence of each category in the sample. We then counted the number
of threatened species in the focal family and compared this with
the null frequency distribution. The null hypothesis (extinction risk
is taxonomically random) was rejected if this number fell in the
2.5% at either tail.
Because reptiles are mostly listed as threatened under the
range-size dependent criteria B and D2, we explored differences
in range size between species groups (specifically between lizards
and snakes) in order to assess whether increased threat status in
the absence of population data could be potentially linked to
taxa-specific patterns of range size. This is particularly of interest
since it has previously been observed that snakes have larger range
sizes (and hence extent of occurrences) than lizards (Anderson,
1984; Anderson and Marcus, 1992). All tests and randomizations
were conducted in R version 2.11.1 (R Development Core Team,
2007).
3. Results
3.1. Global extinction risk of reptiles
We classified more than half of reptilian species (59%) in the
assessment as Least Concern, 5% as Near Threatened, 15% as threa-
tened (Vulnerable, Endangered or Critically Endangered) and 21%
as Data Deficient. Based on this, we estimated the true percentage
of threatened reptiles in the world to be 19% (range: 15–36%), as de-
scribed in Section 2.3. Using the same approach, another 7% of spe-
cies are estimated as Near Threatened (range: 5–26%); these species
are the most likely candidates to become threatened in the future if
measures are not taken to eliminate anthropogenic processes which
currently affect populations of these species. None of the species in
our sample was classed as Extinct or Extinct in the Wild, although
three lizard species in the Critically Endangered category were
flagged as possibly extinct (Anolis roosevelti,Ameiva vittata and Ste-
nocercus haenschi) and may be up-listed during future reassess-
ments, once ‘‘exhaustive surveys in known and/or expected
habitat, at appropriate times (diurnal, seasonal, annual), throughout
its historic range have failed to record an individual’’ (IUCN, 2001).
Of the 223 reptilian species classed as threatened, around half
(47%) were assigned to the Vulnerable category; another 41% and
12% were assessed as Endangered and Critically Endangered,
respectively. Threat estimates for terrestrial species mirrored that
recorded for all reptiles (19% threatened), because the vast major-
ity of reptiles inhabit terrestrial systems (N= 1473; Table 1). How-
ever, for reptiles associated with marine and freshwater
environments, 30% were estimated to be threatened (N= 94; Ta-
ble 1). Note that 68 species were dependent on both terrestrial
and non-terrestrial environments.
Of the 124 species reassessed during this project, 72 species did
not change from the previously assigned category. Overall, 46 cat-
egory changes were documented, only three of which were genu-
ine changes showing an increase in extinction risk. All other
changes (N= 43) were non-genuine changes. Six species had previ-
ously been listed on the IUCN Red List as Not Evaluated, but have
now been assigned categories.
3.2. Global species richness and distribution of threatened and Data
Deficient reptiles
Overall species richness in our sample was highest in tropical
regions, specifically in Central America and parts of northern South
America (especially Brazil), tropical West Africa, parts of Southeast
Africa, Sri Lanka and Southern India and throughout Southeast
Asia, from Eastern India to Indonesia and the Philippines (Fig. 1).
The tropics also harboured the highest proportions of threa-
tened and Data Deficient species in the sample. Data deficiency
was highest in the Indomalayan realm (33%), followed by the Neo-
tropics (20%) and Afrotropics (18%; Table 1). A high percentage of
Data Deficient species will give rise to wide margins of uncertainty
on any estimates of the percentage of threatened species (see
upper and lower margins in Table 1). Oceania had the highest pro-
portion of threatened species (43%; Table 1), although this was
based on very low species richness in our sample (N= 7), while
378 M. Böhm et al. / Biological Conservation 157 (2013) 372–385
25% and 20% of species were estimated as threatened in the Afro-
tropical and Neotropical realms, respectively (Table 1). The lowest
level of extinction risk was recorded in the Palaearctic, where 12%
of species were estimated as threatened (Table 1).
Localised centres of threatened species richness were particu-
larly apparent in the Caribbean (Hispaniola), Florida and the Flor-
ida panhandle, the Ecuadorian Andes, Madagascar, the
northeastern Indian subcontinent, Central Asia, Eastern China and
oceanic islands such as New Caledonia (Fig. 2A). Prevalence of Near
Threatened species was particularly pronounced across Europe,
central North America, Central and West Africa, Central China
and the South Island of New Zealand (Fig. 2B). Data deficiency
was particularly pronounced in tropical regions, specifically in
parts of the Indomalayan realm (e.g., throughout India, Borneo
and the Philippines) and Central Africa (Fig. 2C).
Some apparently low-diversity areas (for species richness, as
well as threatened species richness) are likely explained by the lack
of research in particularly inaccessible areas (e.g., the Congo basin;
Fig. 2C) and isolated island groups. It is likely that both relative spe-
cies richness and data deficiency is higher in these areas than is cur-
rently apparent. Furthermore, in some localised areas, the fact that
all our analysis was based on a random sample may have led to a
slight underestimate of species richness, threatened species rich-
ness or Data Deficient species richness. Additional maps of species
richness are available in the online supplementary material (S4).
3.3. Global distribution of threat processes
Over 80% of all threatened species in our sample were affected
by more than one threat process. Agriculture and biological re-
source use (predominantly logging and harvesting) present the
most common threats to terrestrial reptiles (74% and 64% of threa-
tened species affected, respectively). Urban development (34%),
natural system modification (by use of fire, damming, etc., 25%)
and invasive or problematic native species (22%) also played a role
in threat to terrestrial species.
Biological resource use was also the most significant threat to
freshwater and marine reptiles (87% of threatened species), with
Table 1
Extinction risk in a subsample of 1500 reptiles by order, biogeographic realm and habitat system. The number of species falling into each IUCN Category are listed, from which %
threatened has been calculated as described in Section 2.3.
Taxon DD LC NT VU EN CR N No. of species % Threatened
Described % Sampled Threatened % Lower Upper
Reptiles 318 881 78 105 92 26 1500 9413 15.9 18.9 14.9 36.1
Amphisbaenia 14 11 2 0 1 0 28 181 15.5 7.1 3.6 53.6
Crocodylia 0 1 0 2 0 1 4 24 16.7 75 75 75
Sauria 164 506 48 72 63 14 867 5537 15.7 21.2 17.2 36.1
Serpentes 135 352 19 24 20 5 555 3346 16.6 11.7 8.8 33.2
Testudines 5 11 9 7 8 6 46 323 14.2 51.2 45.7 56.5
Realm
Afrotropical 53 161 15 33 22 5 289 25.4 20.8 39.1
Australasian 32 149 9 10 14 5 219 15.5 13.2 27.9
Indomalayan 105 167 13 15 10 5 315 14.3 9.5 42.9
Nearctic 2 72 7 7 3 3 94 14.1 13.8 16.0
Neotropical 107 309 27 38 35 11 527 20.0 15.9 36.2
Oceanian 0 4 0 0 2 1 7 42.9 42.9 42.9
Palaearctic 25 105 8 6 8 2 154 12.4 10.4 26.6
Habitat system
Terrestrial 313 861 78 105 91 25 1473 19.1 15.0 36.3
Freshwater and marine 16 44 11 9 8 6 94 29.5 24.5 41.5
Subsurface 50 46 5 1 5 0 107 10.5 5.6 57.0
DD – Data Deficient; LC – Least Concern; NT – Near Threatened; VU – Vulnerable; EN – Endangered; CR – Critically Endangered. Percentage threatened: assumes DD species
are threatened in the same proportion as non-DD species; Lower margin: no DD species threatened; Upper margin: all DD species threatened. Number of described species is
based on Uetz (2010). Rhynchocephalia (Tuatara) was not represented in our random sample. Subsurface includes completely or primarily fossorial families: Amphisbae-
nidae, Anomalepidae, Dibamidae, Leptotyphlopidae, Trogonophidae, Typhlopidae, Uropeltidae, Xenopeltidae.
Fig. 1. Global species richness distribution of the sampled reptile assessment (N
terr/fw
= 1485; N
marine
= 22), showing number of species and proportion of species in sample per
grid cell. Terr/fw – terrestrial and freshwater species.
M. Böhm et al. / Biological Conservation 157 (2013) 372–385 379
most of this threat stemming from targeted harvesting of species.
This reflects the large percentage of turtles in the threatened fresh-
water and marine sample and their role in human trade activities.
Agriculture and aquaculture, urban development and pollution (all
affecting 43% of threatened species) were also significant threats to
non-terrestrial reptiles.
Species richness of terrestrial and freshwater species affected
by habitat loss was particularly high in tropical regions, especially
in the Indomalayan realm (mainland southeast Asia, Sri Lanka,
Indonesia, the Philippines and Borneo), but also in Central America
(specifically Panama and Costa Rica) and northern South America
(especially Brazil) (Fig. 3A). Harvesting was highlighted as a major
threat in the Indomalayan realm, specifically in southeastern Asia,
Java and eastern parts of the Indian sub-continent (Fig. 3B). Both of
these patterns were largely reflecting underlying species distribu-
tion and richness patterns shown in Fig. 1. Controlling for species
richness per grid cell, habitat loss remained an important factor
in parts of Sri Lanka and north-western South America, and addi-
tionally in Madagascar, with high risk also in some areas of lower
reptilian species richness, namely across central USA, the Carib-
bean, southwestern Europe (particularly Spain), localised areas of
North and East Africa, China, northeastern Australia and the South
Island of New Zealand (Fig. 3C). Similarly, the picture of risk
through harvesting changed to similar areas of lower richness by
controlling for species richness per grid cell, with large parts of
Europe and Central Asia particularly highlighted (Fig. 3D). In addi-
tion to habitat loss and harvesting, invasive species appear to in-
crease extinction risk on islands, but relatively low frequencies of
this threat in our sample mask any pattern at the global scale.
However, invasive species pose the main threat in New Caledonia,
Oceania, New Zealand, southern Australia and on Caribbean
islands.
Fig. 2. Distribution of threatened (CR, EN, VU), Near Threatened (NT) and Data Deficient (DD) species in the sample (terrestrial and freshwater only), expressed as the
proportion of all species present per grid cell: (A) proportion of species classed as threatened, adjusted to account for DD species as described in Section 2.3; (B) proportion of
species classed as Near Threatened, adjusted to account for DD species as described in Section 2.3; and (C) proportion of species classed as Data Deficient per grid cell.
380 M. Böhm et al. / Biological Conservation 157 (2013) 372–385
3.4. Taxonomic differences in extinction risk
The percentage of threatened species varied greatly among
higher-level taxa, driven by the relatively higher levels of threat
to species associated with freshwater and marine habitats com-
pared with terrestrial ones (Table 1), as well as taxa-specific pat-
terns of range size. Three of the four crocodilian species and 52%
of freshwater turtles were estimated to be threatened (N= 37, mar-
gins: 46–57%). As a whole, Testudines (N= 46; comprising 37
freshwater species, one marine species and eight terrestrial spe-
cies) were equally spread among Red List categories, with 51% of
species estimated as threatened and another 22% assessed as Near
Threatened (Table 1). In contrast, only 21% of lizards, 12% of snakes
and 7% of worm lizards were threatened. The lower percentages of
threatened species in these groups were paralleled by a lower per-
centage of species in the Near Threatened category for all three
groups (lizards: 7%; snakes: 5%; worm lizards: 14%), compared
with Testudines. Proportions of threatened worm lizards were af-
fected by high levels of data deficiency in this group (50% versus
11% in the Testudines, 19% in lizards and 24% in snakes; Table 1).
Similarly, our sample contained large numbers of Data Deficient
species in snake families that are exclusively, or largely, fossorial
or semi-fossorial, such as Typhlopidae [24 out of 49 species (49%)
were Data Deficient], Leptotyphlopidae [4 out of 10 (40%)] and
Uropeltidae [5 out of 13 (38%)]. Overall, of the exclusively or
primarily fossorial families, 47% of species were classed as Data
Fig. 3. Global distribution of species affected by the two major threats to terrestrial and freshwater reptiles: (A) number of species affected by habitat loss from agriculture
and logging and (B) number of species affected by harvesting. Controlling for species richness per grid cell, we expressed the number of species in elevated threat categories
(CR, EN, VU, NT) affected by the threat in question as the proportion of the total species richness (all categories) per grid cell for (C) habitat loss from agriculture and logging
and (D) harvesting.
M. Böhm et al. / Biological Conservation 157 (2013) 372–385 381
Deficient. As a result, the estimated percentage of threatened fos-
sorial species is relatively low at 11%, but this is associated with
a wide margin of uncertainty (range: 6–57%).
Criterion B was applied to 72% of species assessed as threa-
tened, with another 12% of species being listed under criterion
D2. As such, the majority of threatened listings were based on
criteria of restricted range rather than population data (only 12%
of species, mainly turtles and crocodiles, were listed under crite-
rion A). As a result, range size differences between taxa may at
least in part explain differences in perceived extinction risk. Range
sizes were significantly larger for snakes compared to lizards (for
terrestrial species only: Kruskal–Wallis
v
2
= 44.8, d.f. = 1,
p< 0.001). Median range size was 24,510 km
2
for lizards and
110,175 km
2
for snakes (additional information is available in Sec-
tion S5 of the online supplementary material).
To establish whether a particular taxonomic family was at
greater risk of extinction than expected by chance (p< 0.025)
required a minimum of three non-Data Deficient species in our
sample from that family, given a background proportion of 223
threatened species from 1182 species assessed in non-Data Defi-
cient categories. As a result, 18 families were excluded from the
analysis (Table 2). Each family required a minimum number of
18 species in our sample to establish whether a family was less
threatened than expected by chance (p< 0.025). Threat was not
evenly distributed across families (
v
2
= 141.73, d.f. = 44,
p< 0.001), with 34 of the 45 families more threatened than ex-
pected by chance and only one (Colubridae) less threatened than
expected by chance (Table 2). Of the nine families which showed
non-significant differences between observed and expected pro-
portions of threatened species, six were snakes, two were lizards
and one was turtles (Table 2).
Overall, the most threatened families were the Geoemydidae
(turtles, 88% threatened, N= 8), Crocodylidae (crocodiles, 75%,
N= 4), Pygopodidae (lizards, 75%, N= 4), Xantusiidae (lizards,
75%, N= 4), Chelidae (turtles, 50%, N= 11) and Iguanidae (lizards,
50%, N=4)(Table 2).
4. Discussion
4.1. Extinction risk of the world’s reptiles
This analysis starts to close the knowledge gap between the
extinction risk of reptiles and other better-studied vertebrate
groups. By establishing a shortcut using a representative sample
of 1500 species, we gain for the first time an overview of the global
distribution of reptilian diversity and threat, consequently high-
lighting important areas for conservation attention and gaps in
knowledge. Our results support recent reports of high levels of
threat in freshwater habitats (e.g., freshwater crabs; Cumberlidge
et al., 2009). In particular, freshwater turtles were highly threa-
tened (46–57%), thus mirroring the alarming trends reported else-
where (Buhlmann et al., 2009).
Some authors have argued that reptiles are undergoing similar
declines to those experienced by amphibians, in terms of taxo-
nomic breadth, geographic scope and severity (Gibbons et al.,
2000). On a global scale, our assessment shows that threat levels
are more severe in amphibians (42% of amphibians are threatened,
assuming Data Deficient species are threatened in the same pro-
portion as non-Data Deficient species) relative to reptiles (20%).
Overall, threat levels in reptiles are slightly lower than those
observed in other taxa such as mammals and freshwater fish (both
25% threatened; Collen, B., unpublished data; Hoffmann et al.,
2010), but higher than in birds (13%; IUCN, 2011a). Estimates of
5% for Near Threatened species were similar to those observed in
other vertebrate species groups, such as mammals, amphibians
(6% each) and freshwater fishes (4%).
Recently reported local declines in snake and lizard populations
(Cagle, 2008; Reading et al., 2010; Sinervo et al., 2010) suggest
localised elevated extinction risks for both taxa. While we estimate
that about one in five lizard species is threatened with extinction,
only 12% of snakes were estimated to be threatened with extinc-
tion. One barrier to listing, which could be partly responsible for
the discrepancy between our analysis and those of snake popula-
tion trends, is that in the majority of cases there are sufficient data
on species distributions only, rather than population trends, at a
global scale. Therefore the majority of reptilian species were listed
under criteria B and D2 (restricted range). The differences in
extinction risk between snakes and lizards may therefore be partly
explained by the fact that snakes in our sample (and in previous
studies, e.g., Anderson and Marcus, 1992) had larger ranges than
lizards. Local population declines such as those reported by Sinervo
et al. (2010) are evaluated with finer scale population data than
those used to evaluate extinction risk, so could serve as a warning
sign of what is to come. In order to understand more fully what is
happening to the world’s snakes, it is vital that we obtain better
global population data for this species group. Based on range size
estimation alone, we may be missing ongoing declines which are
occurring at sub-threshold levels and thus underestimating extinc-
tion risk to this particular species group. Furthermore, snakes are
morphologically more conservative and harder to sample (fewer
specimens are generally available compared to lizards) which,
compared to lizards, makes it harder to detect cryptic species.
Thus, larger ranges for some snake species may be masking the
range of one or more cryptic species.
4.2. Data deficiency: addressing the knowledge gap
High proportions of data deficiency can significantly hinder our
understanding of threat, yet such uncertainty is apparent in many
species groups that have been assessed to date. Levels of data
deficiency in reptiles (21%) were lower than those reported for
amphibians (25%; IUCN, 2011a), dragonflies and damselflies
(35%; Clausnitzer et al., 2009) and freshwater crabs (49%; Cumber-
lidge et al., 2009), but still exceeded those of the more charismatic
or conspicuous birds and mammals (less than 1% and 15% respec-
tively; BirdLife International, 2008b; Schipper et al., 2008).
Patterns of regional or taxonomical data deficiency could be used
to prompt research programmes on specific local faunas or
taxonomical groups. For example, data deficiency in reptiles was
highest in tropical regions and in exclusively fossorial or semi-
fossorial reptiles such as the Amphisbaenia. Similar patterns have
been observed in amphibians, where approximately two-thirds of
caecilians were classified as Data Deficient (Gower et al., 2005),
despite estimates that fossorial species potentially comprise
around 20% of the world’s herpetofauna (Measey, 2006). It is clear
that research attention should focus specifically on fossorial and
other elusive taxa (e.g., arboreal species) in order to reduce rates
of data deficiency during the course of future re-assessments of
the sample.
4.3. Conservation prioritisation: lessons from the world’s reptiles
Conservation priorities often focus on regions of high biodiver-
sity value and/or high threat to effectively target conservation
funds (Brooks et al., 2006). The assessment of biodiversity value
often relies on the distribution patterns of certain indicator taxa
(e.g., birds), and the effectiveness of the resulting prioritisation
mechanism greatly depends on the degree to which such distribu-
tion patterns are congruent with those of other taxa. However,
cross-taxon congruence varies with given metrics of biodiversity
382 M. Böhm et al. / Biological Conservation 157 (2013) 372–385
(Grenyer et al., 2006). While reptilian species richness broadly mir-
rored species richness patterns observed in mammals, amphibians
and birds (BirdLife International, 2008a; Schipper et al., 2008;
Stuart et al., 2004), additional areas rich in reptiles (e.g., around
the Gulf of Guinea and southern Africa) or threatened reptiles
(e.g., islands such as Hispaniola, Sri Lanka, New Caledonia) were
highlighted in our assessment and may be overlooked if conserva-
tion priorities are set based on patterns in a small number of non-
reptilian taxa alone. This has also recently been demonstrated for
Australian lizards (Powney et al., 2010). Thus far, both amphibians
and reptiles have been greatly overlooked in reserve selection
strategies based on coarse-scale biodiversity surrogate measures
(Araújo et al., 2001). Our results provide the opportunity for a more
representative view of biodiversity to be compiled in order to
benefit multiple taxa.
Assessing the global distribution of threat processes, both cur-
rent and projected, has the potential to provide another powerful
tool for conservation prioritization. While for some taxa, the distri-
bution of predominant threats significantly overlaps areas of high
species richness (e.g., amphibians, Hof et al., 2011), other studies
have shown incongruence between threat distribution and
endemic or threatened species richness (e.g., Grenyer et al., 2006;
Lee and Jetz, 2008; Orme et al., 2005); however, the latter has tra-
ditionally been favoured as a selection tool for conservation prior-
ity areas. Similarly, distributions of different threat types may not
always spatially overlap (Hof et al., 2011), so that effective mitiga-
tion strategies have to be developed in a spatially explicit context
in order to reduce extinction risk of species. Reptiles in general are
particularly sensitive to habitat degradation because of their com-
paratively low dispersal ability, morphological specialisation on
substrate type, relatively small home ranges and thermoregulatory
constraints (Kearney et al., 2009). Clearly, the distribution and
severity of threat processes, such as habitat loss from agricultural
conversion, logging and over-exploitation, will shape the future
fortune of reptiles. Identifying centres of threat, and tackling the
origins and effects of anthropogenic threats in these regions
through targeted projects (particularly in areas affected by multi-
ple threat processes such as Southeast Asia) will allow more proac-
tive action to be taken to secure the future of reptiles. At the
moment the spatial resolution of our species-specific maps of
threat processes is still somewhat coarse and allows only the
depiction of broad patterns in threat distribution, but future
Table 2
Threat distribution across families included in our random sample of 1500 species: ns, not significant; significantly under threatened; + significantly over threatened.
Family Proportion
observed
Proportion
expected
Total species (non-
DD)
>Expected threat level p-
value
<Expected threat level p-
value
Under or over
threatened
Agamidae 0.05 0.05 61 0.635 0.365 ns
Amphisbaenidae 0.07 0.01 14 <0.001 1 +
Anguidae 0.29 0.01 17 <0.001 1 +
Atractaspidae 0.00 0.00 6 0.714 0.286 ns
Boidae 0.15 0.01 13 <0.001 1 +
Calamariidae 0.18 0.01 11 <0.001 1 +
Carphodactylidae 0.17 0.00 6 <0.001 1 +
Chamaeleonidae 0.43 0.03 35 <0.001 1 +
Chelidae 0.50 0.01 10 <0.001 1 +
Colubridae 0.04 0.07 78 0.98 0.02
Cordylidae 0.44 0.01 9 <0.001 1 +
Crocodylidae 0.75 0.00 4 <0.001 1 +
Crotaphytidae 0.33 0.00 3 <0.001 1 +
Diplodactylidae 0.23 0.01 13 <0.001 1 +
Dipsadidae 0.10 0.08 98 0.147 0.853 ns
Elapidae 0.15 0.05 55 <0.001 1 +
Emydidae 0.33 0.00 6 <0.001 1 +
Gekkonidae 0.12 0.08 91 0.01 0.999 +
Geoemydidae 0.88 0.01 8 <0.001 1 +
Gerrhosauridae 0.17 0.00 6 <0.001 1 +
Gymnophthalmidae 0.39 0.03 31 <0.001 1 +
Homalopsidae 0.17 0.00 6 <0.001 1 +
Iguanidae 0.50 0.00 4 <0.001 1 +
Lacertidae 0.16 0.03 37 <0.001 1 +
Lamprophiidae 0.27 0.03 30 <0.001 1 +
Leptotyphlopidae 0.00 0.00 6 0.72 0.28 ns
Natricidae 0.04 0.02 26 0.049 0.951 +
Pelomedusidae 0.00 0.00 4 0.566 0.434 ns
Phrynosomatidae 0.17 0.03 30 <0.001 1 +
Phyllodactylidae 0.08 0.01 13 <0.001 1 +
Polychrotidae 0.31 0.05 61 <0.001 1 +
Psammophiidae 0.00 0.00 4 0.596 0.404 ns
Pseudoxenodontidae 0.00 0.00 3 0.468 0.532 ns
Pygopodidae 0.75 0.00 4 <0.001 1 +
Scincidae 0.22 0.14 167 <0.001 1 +
Sphaerodactylidae 0.22 0.03 32 <0.001 1 +
Teiidae 0.22 0.01 18 <0.001 1 +
Testudinidae 0.43 0.00 7 <0.001 1 +
Trionychidae 0.33 0.00 3 <0.001 1 +
Tropiduridae 0.13 0.04 45 <0.001 1 +
Typhlopidae 0.20 0.02 25 <0.001 1 +
Uropeltidae 0.00 0.00 8 0.832 0.168 ns
Varanidae 0.00 0.01 10 0.875 0.125 ns
Viperidae 0.19 0.04 42 <0.001 1 +
Xantusiidae 0.75 0.00 4 <0.001 1 +
M. Böhm et al. / Biological Conservation 157 (2013) 372–385 383
developments and refinements of the method are likely to provide
a powerful tool with which to focus threat-specific mitigation
projects.
4.4. Reptile conservation: the next steps
This study provides a first step in assessing the global extinction
risk of reptiles by employing a short-cut method based on a repre-
sentative sample of 1500 species. While this assessment feeds into
broader scale assessments of biodiversity as a whole, as part of the
Sampled Red List Index project (Baillie et al., 2008), it is also impor-
tant to feed this information into similar regional assessments,
since concrete policy decisions are generally being taken at sub-
global levels. Specifically, it is important that the data presented
here is used to assess how existing and planned protected areas
are benefitting the world’s reptiles. This will allow us to identify
species which at present fall outside protected areas and are most
in need of conservation actions, and address the fact that the
world’s herpetofauna is still often overlooked when conservation
decisions are taken. The Global Reptile Assessment (GRA) is
currently carrying out assessments via regional workshops, which
bring together species experts to discuss extinction risk and
conservation priorities. For example, the recent assessment of
Madagascan snakes and lizards has helped in evaluating the effec-
tiveness of protected areas for reptiles, with new conservation
areas being designated across the island aiming to provide protec-
tion to some of the most threatened species (IUCN, 2011b).
While the extensive expert network established during this pro-
ject is undoubtedly going to feed into global and regional assess-
ment projects, regional data gaps are apparent. It is vital that
these are addressed in order to complete our picture of the distri-
bution and extinction risk patterns of reptiles, so that conservation
actions can be targeted at regions and areas most in need. Specifi-
cally, surveys are needed for key areas (e.g., areas rich in Data
Deficient reptiles) and species (e.g., possibly extinct and Data
Deficient species; establishing snake population time series to
complement distribution data) in order to fill knowledge gaps
and to build regional survey capacity via collaborations and
targeted capacity building projects.
While we have established a snapshot of the current status of
reptiles worldwide, it is now vital to establish trends in this status
in order to gauge the rate of change in reptilian extinction risk over
time. The next step is to establish a baseline for reptilian extinction
risk against which we can compare current status as well as future
re-assessments of the sample. This information is vital in order to
assess our progress toward global biodiversity targets, such as the
Aichi targets and the Millennium Development Goals, and fuel
efforts to address the conservation needs of reptiles.
Acknowledgements
MB and MR were funded by a grant from the Esmée Fairbairn
Foundation, BC by the Rufford Foundation. North American and
Mexican species assessments were funded by the Regina Bauer
Frankenberg Foundation for Animal Welfare. Species assessments
under the Global Reptile Assessment (GRA) initiative are supported
by: Moore Family Foundation, Gordon and Betty Moore Founda-
tion, Conservation International, Critical Ecosystem Partnership
Fund (CEPF), and European Commission. Additional acknowledge-
ments are included in the online supplementary material.
The assessment workshop for Mexican reptiles was kindly
hosted by Ricardo Ayala and the station personnel of the Estación
de Biología Chamela, Instituto de Biología, Universidad Nacional
Autonoma de Mexico. Workshop and logistical organisation of
the Philippines assessments was provided by the Conservation
International Philippines Office, in particular Ruth Grace Rosell-
Ambal, Melizar V. Duya and Oliver Coroza. Workshop and logistical
organisation for the European Reptile and Amphibian Assessments
was provided by Dog
˘a Derneg
˘i, in particular Özge Balkiz and Özgür
Koç. Workshop and logistical organisation for assessments of sea
snakes and homalopsids was provided by the International Sea
Turtle Symposium and Dr. Colin Limpus (Australian Government
Environmental Protection Agency). Special thanks to Jenny Chap-
man (EPA) and Chloe Schauble (ISTS). Thank you also to Dr. Gordon
Guymer (Chief Botanist – Director of Herbarium) for accommodat-
ing us at the Herbarium in the Brisbane Botanical Gardens, and
Mark Read and Kirsten Dobbs (Great Barrier Reef Marine Parks
Association) and Dave Pollard and Brad Warren (OceanWatch Aus-
tralia) for institutional support. Mohamed Bin Zayed Species Con-
servation Fund, Conservation International Madagascar and the
Darwin Initiative contributed to funding the costs of the Madagas-
car reptile workshop.
We would also particularly like to thank all our assessors and
the following people who helped with the compilation and finali-
sation of SRLI Red List assessments and distribution maps: Jennifer
Sears, Gary Powney, Paul Lintott, Sarah Lewis, Penny Wilson, Maiko
Lutz, Felix Whitton, Ranmali de Silva and Harriet Milligan. For facil-
itating working groups at GRA and other workshops: Melanie Bilz,
Thomas Brooks, Oliver Coroza, Naamal De Silva, Melizar V. Duya,
Michael Jensen, Jason Van de Merwe, Kate Hodges, Matthew Foster,
Penny Langhammer, Seema Mundoli, Ana Nieto, Lily Paniagua,
Ruth Grace Rosell-Ambal, Jan Schipper and Sarah Wyatt.
Shai Meiri, Lital Dabool, Anat Feldman, Yuval Itescu, Amy Kad-
ison, Erez Maze, Maria Novosolov, Lian Pin Koh and other anony-
mous reviewers commented on and helped to greatly improve an
earlier version of this manuscript.
Appendix A. Supplementary data
Supplementary data associated with this article can be found,
in the online version, at http://dx.doi.org/10.1016/j.biocon.2012.
07.015.
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... As a taxonomic group, non-avian reptiles are incredibly speciose (>11,000 species) and many are threatened with extinction [17,18]. Despite this, there has been a relatively limited number of investigations into cryopreservation [7,19,20]. ...
... Table 1 as final concentrations following a 1:1 dilution (v/v) with semen. Four randomized groupings of males were used to test the CPA control mixture (control) and a set of CPA treatment mixtures (Group A = CPAs #3, 4, 5, 7; Group B = CPAs #2, 14, 15, 16; Group C = CPAs #6, 11, 12, 13; Group D = CPAs #8, 9,10,17). We tested CPA mixtures based on three categories of experimental tests: CPA base in TEST = CPA #2; Extender base plus additives = CPAs #3-8; and glycerol tests (high vs low) = CPAs #9-17). ...
... However, both the percent of motile sperm found to be moving forward (Kruskal-Wallis, H (2) = 18.2, p < 0.001),) and FPM index (Kruskal-Wallis, H (2) = 18.8, p < Table 1 as final concentrations following a 1:1 dilution (v/v) with semen. Four randomized groupings of males were used to test the CPA control mixture (control) and a set of CPA treatment mixtures (Group A = CPAs #3, 4, 5, 7; Group B = CPAs #2, 14, 15, 16; Group C = CPAs #6, 11, 12, 13; Group D = CPAs #8, 9,10,17). We tested CPA mixtures based on three categories of experimental tests: CPA base in TEST = CPA #2; Extender base plus additives = CPAs #3-8; and glycerol tests (high vs low) = CPAs #9-17). ...
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... Among at-risk fauna, a fifth of all reptile species may be threatened with extinction (Böhm et al., 2013), and snakes are declining at an alarming rate (Gibbons et al., 2000;Reading et al., 2010). Marine populations may be increasingly susceptible to pathogens, predators, boat strikes, environmental changes (Somaweera et al., 2021), and trawlers (Fry et al., 2001), but numbers may also be reduced by inexplicable causes (Elfes et al., 2013;Goiran and Shine, 2013;Lukoschek et al., 2013;Udyawer et al., 2018). ...
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... It has been estimated that up to 19 % of reptile species are threatened with extinction (Böhm et al., 2013). This figure includes Crocodilian species, in particular those subject to poaching and habitat loss. ...
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... It has been estimated that up to 19 % of reptile species are threatened with extinction (Böhm et al., 2013). This figure includes Crocodilian species, in particular those subject to poaching and habitat loss. ...
Article
Full-text available
ABSTRACT In this preliminary study we examined the application of dual stable isotope analysis (δ13C and δ15N) to identify the origin of skins and meat derived from wild and farmed crocodiles. Traceability protocols can benefit from analytical techniques that are able to distinguish farmed or wild organisms. Scutes and muscle samples were obtained from wild and farmed crocodiles Crocodylus acutus (n = 14) and C. moreletii (n = 9). Isotopic values in scutes differed significantly between wild and farmed organisms, this difference being higher for δ15N than for δ13C values. When both isotopic values were integrated using a discriminant analysis, we observed a significant categorization. The isotopic values of muscle samples were very similar to those measured in scutes from the same individuals. In addition, two specimens of C. acutus were kept on a constant diet for 97 days to obtain reference isotopic values and tissues were compared. We also estimated the isotopic discrimination factors between tissues and the supplied diet.
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Overall, 9.2% of bees are considered threatened in all of Europe, while at the EU 27 level, 9.1% are threatened with extinction. A further 5.2% and 5.4% of bees are considered Near Threatened in Europe and the EU 27, respectively (101 species at both levels). However, for 1,101 species (56.7%) in Europe and 1,048 species (55.6%) at the EU 27, there was not enough scientific information to evaluate their risk of extinction and thus, they were classified as Data Deficient. When more data become available, many of these might prove to be threatened as well. Looking at the population trends of European bee species, 7.7% (150 species) of the species have declining populations, 12.6% (244 species) are more or less stable and 0.7% (13 species) are increasing. The population trends for 1,535 species (79%) remains unknown. A high proportion of threatened bee species are endemic to either Europe (20.4%, 400 species) or the EU 27 (14.6%, 277 species), highlighting the responsibility that European countries have to protect the global populations of these species. Almost 30% of all the species threatened (Critically Endangered, Endangered, or Vulnerable) at the European level are endemic to Europe (e.g., found nowhere else in the world). The species richness of bees increases from north to south in Europe, with the highest species richness being found in the Mediterranean climate zone. In particular, the Iberian, Italian and Balkan peninsulas are important areas of species richness. Regarding the distribution of endemic species, southern Europe shows the highest concentration of endemism. The largest numbers of threatened species are located in south-central Europe and the pattern of distribution of Data Deficient species is primarily concentrated in the Mediterranean region. The main threat to European bees is habitat loss as a result of agriculture intensification (e.g., changes in agricultural practices including the use of pesticides and fertilisers), urban development, increased frequency of fires and climate change.
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Although small, nocturnal, fossorial snakes are a significant component of the reptile fauna in many parts of the world, their biology is poorly known. An 11-year pit-trapping study in urban bushland remnants near the city of Perth, Western Australia, provided data from > 500 captures of small fossorial snakes of the genus Simoselaps. The five species differed in relative abundances and in distribution, both among localities and among habitats within a single locality. For example, three saurophagous taxa (Simoselaps bertholdi, S. bimaculatus, S. calonotos) were most abundant in Banksia woodland, whereas two species that feed on reptile eggs (S. semifasciatus, S. fasciolatus) were most abundant in coastal heath. Capture rates for most species were low (for three of the five species, < one specimen captured per 1000 trapdays), and these taxa may be genuinely rare in most of the habitats that we surveyed. Activity patterns were highly seasonal, with little activity in winter or in midsummer. The two oophagous species showed a more restricted activity period (late spring-early summer) than did species with broader dietary habits. In the most abundant taxon (Simoselaps bertholdi), males were active mainly during spring (the mating season) and females during autumn, after oviposition. Capture rates and body condition of the captured snakes varied substantially among seasons and across years. Low capture rates mean that very prolonged surveys are needed to determine reliably whether or not a taxon occurs on any given site.
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Species are classified as Data Deficient on the IUCN Red List if there is inadequate information to make an assessment of their extinction risk based on distribution and/or population status. Data Deficient is probably the most controversial and misunderstood of IUCN Red List categories. All 63 globally Data Deficient bird species lack sufficient information on population size, trends, distribution and/or threats to assess them against the Red List criteria. For 10 species (16%) the paucity of data may be a consequence of taxonomic uncertainty. Three species are known only from specimens of uncertain geographic provenance. Since 1988, 58 Data Deficient birds have been recategorised, mainly as Near Threatened (48%) or Least Concern (16%). We speculate that of the remaining Data Deficient birds, just 14% may prove to be threatened. Proportionately fewer birds (0.6%) are listed as Data Deficient as compared with mammals (15%), amphibians (25%), corals (17%), conifers (4%) and cycads (6%), because birds are better known and perhaps because for birds greater use is made of contextual information (e.g. condition of habitats, likely ecology/habitat preferences and trends in known threatening processes) to assign alternative categories where this is plausible and precautionary. Ensuring consistency between taxonomic groups is essential for the credibility of the IUCN Red List. For non-avian taxa, the higher proportions of Data Deficient species introduces greater uncertainty in estimates of overall extinction risk, but the results from birds hint that the real values may fall at the lower end of these estimates. Data Deficient species should be treated precautionarily in terms of protection and assessing environmental impacts, and regarded as urgent priorities for surveys and research to elucidate their true status. Greater attention should also be given to documenting data quality and uncertainty for Red List assessments of threatened and non-threatened species.
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We present phylogenetic analyses of 42 new partial mitochondrial-DNA sequences in combination with 28 previously published sequences representing all eight major groups of the lizard clade Iguanidae (sensu lato). These sequences include 1838 aligned positions (1013 parsimony informative for ingroup taxa) extending from the protein-coding gene ND1 (subunit one of NADH dehydrogenase) through the genes encoding tRNAIle, tRNAGln, tRNAMet, ND2 (NADH dehydrogenase subunit two), tRNATrp, tRNAAla, tRNAAsn, tRNACys, tRNATyr, to the protein-coding gene COI (subunit I of cytochrome c oxidase). These data, analyzed in combination with 67 previously published morphological characters, provide statistical support for monophyly of iguanid clades Corytophaninae, Crotaphytinae, Hoplocercinae, Iguaninae, Oplurinae, and Phrynosomatinae. Monophyly is neither supported nor statistically rejected for Polychrotinae and Tropidurinae. Polychrotinae* and Tropidurinae* may be recognized as metataxa, to denote the fact that evidence for their monophyly is equivocal, or replaced by recognizing constituent groups whose monophyly has stronger empirical support. A phylogenetically (non-ranked) based, statistically robust taxonomy of iguanian lizards is proposed. The Old World lizard clade, Acrodonta, is composed of Chamaeleonidae and Agamidae* with the Agaminae, Amphibolurinae, Draconinae, Hydrosaurinae, Leiolepidinae, and Uromas- tycinae nested within Agamidae*. The predominately New World clade, Iguanidae, contains the groups Corytophaninae, Crotaphytinae, Hoplocercinae, Iguaninae, Oplurinae, Phrynosomatinae, Polychrotinae*, and Tropidurinae*; with Anolis, Leiosaurini (composed of the Leiosaurae and Anisolepae), and Polychrus as the subgroups of Polychrotinae*; and Leiocephalus, Liolaemini, and Tropidurini as the subgroups of Tropidurinae*.