Skip to main content
    • Aa
    • Aa

Assessing the distribution of a Vulnerable felid species: threats from human land use and climate change to the kodkod Leopardus guigna

  • Griet A.E. Cuyckens (a1), Miriam M. Morales (a1) and Marcelo F. Tognelli (a2)

Climate change and habitat fragmentation are considered key pressures on biodiversity, and mammalian carnivores with a limited geographical distribution are particularly vulnerable. The kodkod Leopardus guigna, a small felid endemic to the temperate forests of southern Chile and Argentina, has the smallest geographical range of any New World felid. Although the species occurs in protected areas in both countries, it is not known how well these areas protect the kodkod either currently or under climate change scenarios. We used species distribution models and spatial analyses to assess the distribution of the kodkod, examining the effects of changes in human land use and future climate change. We also assessed the species’ present representation in protected areas and in light of climate change scenarios. We found that the kodkod has already lost 5.5% of its range as a result of human land use, particularly in central areas of its distribution with intermediate habitat suitability. Climate change, together with human land use, will affect 40% of the kodkod's present potential distribution by the year 2050. Currently, 12.5% of the species’ potential distribution lies in protected areas and this will increase to 14% in the future. This increase does not, however, mean an increase in protected habitat but rather a reduction of the species' total potential range; a relatively larger percentage will be protected in Argentina than in Chile but the species is more susceptible to extinction in Argentina and the Chilean Matorral.

Corresponding author
(Corresponding author) E-mail
Linked references
Hide All

This list contains references from the content that can be linked to their source. For a full set of references and notes please see the PDF or HTML where available.

A. Altamirano & A. Lara (2010) Deforestación en ecosistemas templados de la precordillera andina del centro-sur de Chile. Bosque, 31, 5364.

M.B. Araújo , D. Nogués-Bravo , J.A.F. Diniz-Filho , A.M. Haywood , P.J. Valdes & C. Rahbek (2008) Quaternary climate changes explain diversity among reptiles and amphibians. Ecography, 31, 815.

M.B. Araújo , R.G. Pearson , W. Thuiller & M. Erhard (2005) Validation of species–climate impact models under climate change. Global Change Biology, 11, 15041513.

R.A. Baldwin (2009) Use of maximum entropy modeling in wildlife research. Entropy, 11, 854866.

C.E. Burns , K.M. Johnston & O.J. Schmitz (2003) Global climate change and mammalian species diversity in US national parks. Proceedings of the National Academy of Sciences of the United States of America, 100, 1147411477.

K.F. Conrad , M.S. Warren , R. Fox , M.S. Parsons & I.P. Woiwod (2006) Rapid declines of common, widespread British moths provide evidence of an insect biodiversity crisis. Biological Conservation, 132, 279291.

H.F. Diaz & R.S. Bradley (1997) Temperature variations during the last century at high elevation sites. Climatic Change, 36, 253279.

N. Dunstone , L. Durbin , I. Wylie , R. Freer , G. Acosta-Jamett , M. Mazzolli & S. Rose (2002) Spatial organization, ranging behaviour and habitat use of the kodkod (Oncifelis guigna) in southern Chile. Journal of Zoology (London), 257, 111.

C. Echeverria , D. Coomes , J. Salas , J.M. Rey-Benayas , A. Lara & A. Newton (2006) Rapid deforestation and fragmentation of Chilean Temperate Forests. Biological Conservation, 130, 481494.

J. Elith , C.H. Graham , R.P. Anderson , M. Dudík , S. Ferrier , A. Guisan (2006) Novel methods improve prediction of species’ distributions from occurrence data. Ecography, 29, 129151.

J. Elith , M. Kearney & S. Phillips (2010) The art of modelling range-shifting species. Methods in Ecology and Evolution, 1, 330342.

J.A. Hanley & B.J. McNeil (1982) The meaning and use of area under the receiver operating characteristic (ROC) curve. Radiology, 143, 2936.

P.A. Hernandez , C.H. Graham , L.L. Master & D.L. Albert (2006) The effect of sample size and species characteristics on performance of different species distribution modeling methods. Ecography, 29, 773785.

R.J. Hijmans , S.E. Cameron , J.L. Parra , P.G. Jones & A. Jarvis (2005) Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology, 25, 19651978.

L. Hughes (2000) Biological consequences of global warming: is the signal already apparent? Trends in Ecology and Evolution, 15, 5661.

J.L. Innes (1991) High-altitude and high-latitude tree growth in relation to past, present and future global climate change. Holocene, 1, 168173.

M.D. Jennings (2000) Gap analysis: concepts, methods, and recent results. Landscape Ecology, 15, 520.

J.M. Jeschke & D.L. Strayer (2008) Usefulness of bioclimatic models for studying climate change and invasive species. Annals of the New York Academy of Sciences, 1134, 124.

C. Liu , P.M. Berry , T.P. Dawson & R.G. Pearson (2005) Selecting thresholds of occurrence in the prediction of species distributions. Ecography, 28, 385393.

B.A. Loiselle , C.H. Graham , J.M. Goerck & M.C. Ribeiro (2010) Assessing the impact of deforestation and climate change on the range size and environmental niche of bird species in the Atlantic forests, Brazil. Journal of Biogeography, 37, 12881301.

C.R. Margules & R.L. Pressey (2000) Systematic conservation planning. Nature, 405, 243253.

J. Marino , M. Bennett , D. Cossios , A. Iriarte , M. Lucherini , P. Pliscoff (2011) Bioclimatic constraints to Andean cat distribution: a modelling application for rare species. Diversity and Distributions, 17, 311322.

M. Marmion , M. Parviainen , M. Luoto , R.K. Heikkinen & W. Thuiller (2009) Evaluation of consensus methods in predictive species distribution modelling. Diversity and Distributions, 15, 5969.

D.M. Olson , E. Dinerstein , E.D. Wikramanayake , N.D. Burgess , G.V. Powell , E.C. Underwood (2001) Terrestrial ecoregions of the world: a new map of life on earth. BioScience, 51, 933938.

P. Opdam & D. Wascher (2004) Climate change meets habitat fragmentation: linking landscape and biogeographical scale levels in research and conservation. Biological Conservation, 117, 285297.

C. Parmesan & G. Yohe (2003) A globally coherent fingerprint of climate change impacts across natural systems. Nature, 421, 3742.

R.G. Pearson & T.P. Dawson (2003) Predicting the impacts of climate change on the distribution of species: are bioclimate envelope models useful? Global Ecology and Biogeography, 12, 361371.

A.T. Peterson , M.A. Ortega-Huerta , J. Bartley , V. Sánchez-Cordero , J. Soberón , R.H. Buddemeier & D.R.B. Stockwell (2002) Future projections for Mexican faunas under global climate change scenarios. Letters to Nature, 416, 626629.

S.J. Phillips , R.P. Anderson & R.E. Schapire (2006) Maximum entropy modeling of species geographic distributions. Ecological Modelling, 190, 231259.

D.W. Pierce , T.P. Barnett , B.D. Santer & P.J. Gleckler (2009) Selecting global climate models for regional climate change studies. Proceedings of the National Academy of Sciences of the United States of America, 106, 8441.

H.M. Regan , M. Colyvan & M.A. Burgman (2000) A proposal for fuzzy International Union for the Conservation of Nature (IUCN) categories and criteria. Biological Conservation, 92, 101108.

A.S.L. Rodrigues , S.J. Andelman , M.I. Bakarr , L. Boitani , T.M. Brooks , R.M. Cowling (2004) Effectiveness of the global protected area network in representing species diversity. Nature, 428, 640643.

T.L. Root , J.T. Price , K.R. Hall , S.H. Schneider , C. Rosenzweig & J.A. Pounds (2003) Fingerprints of global warming on wild animals and plants. Nature, 421, 5457.

D. Sánchez-Fernández , J.M. Lobo & O.L. Hernández-Manrique (2011) Species distribution models that do not incorporate global data misrepresent potential distributions: a case study using Iberian diving beetles. Diversity and Distributions, 17, 163171.

J. Schipper , J.S. Chanson , F. Chiozza , N.A. Cox , M. Hoffmann , V. Katariya (2008) The status of the world's land and marine mammals: diversity, threat, and knowledge. Science, 322, 225230.

A. Soutullo , S. Dodsworth , S.B. Heard & A. Mooers (2005) Distribution and correlates of carnivore Phylogenetic diversity across the Americas. Animal Conservation, 8, 249258.

C.D. Thomas , A. Cameron , R.E. Green , M. Bakkenes , L.J. Beaumont , Y.C. Collingham (2004) Extinction risk from climate change. Nature, 427, 145148.

J. Thorn , V. Nijman , D. Smith & K. Nekaris (2009) Ecological niche modelling as a technique for assessing threats and setting conservation priorities for Asian slow lorises (Primates: Nycticebus). Diversity and Distributions, 15, 289298.

A. Wilting , A. Cord , A.J. Hearn , D. Hesse , A. Mohamed , C. Traeholdt (2010) Modelling the species distribution of flat-headed cats (Prionailurus planiceps), an Endangered South-east Asian small felid. PLoS ONE, 5(3), e9612.

A.C. Yost , S.L. Petersen , M. Gregg & R. Miller (2008) Predictive modeling and mapping sage grouse (Centrocercus urophasianus) nesting habitat using Maximum Entropy and a long-term dataset from Southern Oregon. Ecological Informatics, 3, 375386.

Recommend this journal

Email your librarian or administrator to recommend adding this journal to your organisation's collection.

  • ISSN: 0030-6053
  • EISSN: 1365-3008
  • URL: /core/journals/oryx
Please enter your name
Please enter a valid email address
Who would you like to send this to? *


Type Description Title
Supplementary Materials

Cuyckens Supplementary Material
Figure S2

 Unknown (6.5 MB)
6.5 MB
Supplementary Materials

Cuyckens Supplementary Material
Table S1

 PDF (101 KB)
101 KB
Supplementary Materials

Cuyckens Supplementary Material
Figure S1

 Unknown (775 KB)
775 KB


Altmetric attention score

Full text views

Total number of HTML views: 4
Total number of PDF views: 29 *
Loading metrics...

Abstract views

Total abstract views: 177 *
Loading metrics...

* Views captured on Cambridge Core between September 2016 - 23rd June 2017. This data will be updated every 24 hours.