Species-specific habitat fragmentation assessment, considering the ecological niche requirements and dispersal capability

Biological Conservation

Volumn 152, Issue , 2012, Pages 102-109

  Lu, Nan ^a,b   Jia, Chen Xi ^a   Lloyd, Huw ^c   Sun, Yue Hua ^a  

^a INSTITUTE OF ZOOLOGY   (China)

^b UNIVERSITY OF CHINESE ACADEMY OF SCIENCES   (China)

^c MANCHESTER METROPOLITAN UNIVERSITY   (United Kingdom)

Author keywords

BIOMOD; China; Dispersal; Galliformes; Habitat fragmentation; MaxEnt; Species distribution models

Indexed keywords

ASSESSMENT METHOD; CONSERVATION MANAGEMENT; DISPERSAL; ECOLOGICAL MODELING; ENDANGERED SPECIES; GAMEBIRD; HABITAT CONSERVATION; HABITAT FRAGMENTATION; HABITAT LOSS; NICHE; POPULATION STRUCTURE; RISK FACTOR; SYMPATRY;

CHINA;

ANIMALIA; AVES; BONASA SEWERZOWI; GALLIFORMES; ITHAGINIS CRUENTUS;

EID: 84862698372     PISSN: 00063207     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.biocon.2012.04.004     Document Type: Article

References (60)

1. Allouche O., Tsoar A., Kadmon R. Assessing the accuracy of species distribution models: prevalence, kappa and the true skill statistic (TSS). J. Appl. Ecol. 2006, 43:1223-1232.
2. Araújo M.B., New M. Ensemble forecasting of species distributions. Trends Ecol. Evol. 2007, 22:42-47.
3. Baguette M., Van Dyck H. Landscape connectivity and animal behavior: functional grain as a key determinant for dispersal. Landscape Ecol. 2007, 22:1117-1129.
4. Barbet-Massin M., Thuiller W., Jiguet F. The fate of European breeding birds under climate, landuse and dispersal scenarios. Glob. Change Biol. 2012, 18:881-890.
5. Bélisle M. Measuring landscape connectivity: the challenge of behavioral landscape ecology. Ecology 2005, 86:1988-1995.
6. Breiman L. Classification and Regression Trees 1984, Chapman & Hall/CRC.
7. Breiman L. Random forests. Machine Learning 2001, 45:5-32.
8. Cohen J. A coefficient of agreement for nominal scales. Educ. Psychol. Measur. 1960, 20:37-46.
9. Cordellier M., Pfenninger M. Inferring the past to predict the future: climate modelling predictions and phylogeography for the freshwater gastropod Radix balthica (Pulmonata, Basommatophora). Mol. Ecol. 2009, 18:534-544.
10. Diniz-Filho J.A.F., Mauricio Bini L., Fernando Rangel T., Loyola R.D., Hof C., Nogués-Bravo D., Araújo M.B. Partitioning and mapping uncertainties in ensembles of forecasts of species turnover under climate change. Ecography 2009, 32:897-906.
11. Elith J., Graham C.H., Anderson R.P., Dudik M., Ferrier S., Guisan A., Hijmans R.J., Huettmann F., Leathwick J.R., Lehmann A., Li J., Lohmann L.G., Loiselle B.A., Manion G., Moritz C., Nakamura M., Nakazawa Y., Overton J.M., Peterson A.T., Phillips S.J., Richardson K., Scachetti-Pereira R., Schapire R.E., Soberon J., Williams S., Wisz M.S., Zimmermann N.E. Novel methods improve prediction of species' distributions from occurrence data. Ecography 2006, 29:129-151.
12. Fielding A.H., Bell J.F. A review of methods for the assessment of prediction errors in conservation presence/absence models. Environ. Conserv. 1997, 24:38-49.
13. Fischer J., Lindenmayer D.B. The conservation value of paddock trees for birds in a variegated landscape in southern New South Wales. 2. Paddock trees as stepping stones. Biodivers. Conserv. 2002, 11:833-849.
14. Fischer J., Fazey I., Briese R., Lindenmayer D.B. Making the matrix matter: challenges in Australian grazing landscapes. Biodivers. Conserv. 2005, 14:561-578.
15. Fitzpatrick M.C., Sanders N.J., Ferrier S., Longino J.T., Weiser M.D., Dunn R. Forecasting the future of biodiversity: a test of single-and multi-species models for ants in North America. Ecography 2011, 34:836-847.
16. Forman R.T.T., Godron M. Landscape Ecology 1986, John Wiley and Sons, New York.
17. Fouquet A., Ficetola G.F., Haigh A., Gemmell N. Using ecological niche modelling to infer past, present and future environmental suitability for Leiopelma hochstetteri, an endangered New Zealand native frog. Biol. Conserv. 2010, 143:1375-1384.
18. Freeman E.A., Moisen G. PresenceAbsence: an R package for presence absence analysis. J. Stat. Softw. 2008, 23:1-31.
19. Freeman E.A., Moisen G.G. A comparison of the performance of threshold criteria for binary classification in terms of predicted prevalence and kappa. Ecol. Model. 2008, 217:48-58.
20. Graf R.F., Kramer-Schadt S., Fernandez N., Grimm V. What you see is where you go? Modeling dispersal in mountainous landscapes. Landscape Ecol. 2007, 22:853-866.
21. Hastie T.J., Tibshirani R.J. Generalized Additive Models 1990, Chapman & Hall/CRC.
22. Hastie T., Tibshirani R., Buja A. Flexible discriminant analysis by optimal scoring. J. Am. Stat. Assoc. 1994, 1255-1270.
23. Hernandez P.A., Graham C.H., Master L.L., Albert D.L. The effect of sample size and species characteristics on performance of different species distribution modeling methods. Ecography 2006, 29:773-785.
24. Hijmans R.J., Cameron S.E., Parra J.L., Jones P.G., Jarvis A. Very high resolution interpolated climate surfaces for global land areas. Int. J. Climatol. 2005, 25:1965-1978.
25. Hijmans, R., Phillips, S., Leathwick, J., Elith, J., 2010. Dismo: species distribution modeling. R package version 0.5-4.
26. Hu J.H., Hu H.J., Jiang Z.G. The impacts of climate change on the wintering distribution of an endangered migratory bird. Oecologia 2010, 164:555-565.
27. IUCN, 2011. IUCN Red List of Threatened Species. Version 2011.1. http://www.iucnredlist.org.
28. Jacquemyn H., Brys R., Hermy M. Patch occupancy, population size and reproductive success of a forest herb (Primula elatior) in a fragmented landscape. Oecologia 2002, 130:617-625.
29. Jia C.X., Swenson J.E., Sun Y.H. Unusual incubation behavior and embryonic tolerance of hypothermia by the Blood Pheasant (Ithaginis Cruentus). Auk 2010, 127:926-931.
30. Leclere J., Oberdorff T., Belliard J., Leprieur F. A comparison of modeling techniques to predict juvenile 0+ fish species occurrences in a large river system. Ecol. Inform. 2011, 6:276-285.
31. Lens L., Van Dongen S., Norris K., Githiru M., Matthysen E. Avian persistence in fragmented rainforest. Science 2002, 298:1236-1238.
32. Madge S., McGowan P. Pheasants partridges and grouse. Helm Identification Guides 2002, Christopher Helm, London.
33. McCullagh P., Nelder J.A. Generalized Linear Models 1989, Chapman & Hall/CRC.
34. McGarrigal, K., Marks, B.J., 1995. FRAGSTATS. Spatial Pattern Analysis Programme for Quantifying Landscape Structure. USDA Forest Service. Pacific Northwest Station, GTR-351. Portland., OR, USA.
35. Milne B.T. Lessons from applying fractal models to landscape patterns. Quantitative Methods in Landscape Ecology 1991, 99-235. Springer, New York. M.G. Turner, R.H. Gardner (Eds.).
36. O'Neill R.V., Hunsaker C.T., Timmins S.P., Jackson B.L., Jones K.B., Riitters K.H., Wickham J.D. Scale problems in reporting landscape pattern at the regional scale. Landscape Ecol. 1996, 11:169-180.
37. Pateiro-López B., Rodríguez-Casal A. Generalizing the convex hull of a sample: the R package alphahull. J. Stat. Softw. 2010, 34:1-28.
38. Pearce J., Ferrier S. Evaluating the predictive performance of habitat models developed using logistic regression. Ecol. Model. 2000, 133:225-245.
39. Pearson R.G., Raxworthy C.J., Nakamura M., Peterson A.T. Predicting species distributions from small numbers of occurrence records: a test case using cryptic geckos in Madagascar. J. Biogeogr. 2007, 34:102-117.
40. Peterson A.T., Lash R.R., Carroll D.S., Johnson K.M. Geographic potential for outbreaks of Marburg hemorrhagic fever. Am. J. Trop. Med. Hyg. 2006, 75:9-15.
41. Phillips S.J., Dudik M. Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation. Ecography 2008, 31:161-175.
42. Phillips S.J., Anderson R.P., Schapire R.E. Maximum entropy modeling of species geographic distributions. Ecol. Model. 2006, 190:231-259.
43. Pulliam H.R. On the relationship between niche and distribution. Ecol. Lett. 2000, 3:349-361.
44. Ridgeway G. The state of boosting. Comput. Sci. Stat. 1999, 172-181.
45. Riitters, K., Wickham, J., O'Neill, R., Jones, B., Smith, E., 2000. Global-scale patterns of forest fragmentation. Conserv. Ecol. 4, http://www.consecol.org/vol4/iss2/art3.
46. Ripley B. Neural Networks and Pattern Recognition 1996, Cambridge University.
47. Roberts D.R., Hamann A. Method selection for species distribution modelling: are temporally or spatially independent evaluations necessary?. Ecography 2011.
48. Schumaker N.H. Using landscape indices to predict habitat connectivity. Ecology 1996, 77:1210-1225.
49. Stattersfield A.J., Crosby M.J., Long A.J., Wege D.C. Endemic Bird Areas of the World: Priorities for Biodiversity Conservation 1998, BirdLife International, Cambridge.
50. Suárez-Seoane S., de la Morena E.L.G., Prieto M.B.M., Osborne P.E., de Juana E. Maximum entropy niche-based modelling of seasonal changes in little bustard (Tetrax tetrax) distribution. Ecol. Model. 2008, 219:17-29.
51. Sun Y.H. Distribution and status of the Chinese grouse Bonasa sewerzowi. Wildlife Biol. 2000, 6:271-275.
52. Sun Y.H., Swenson J.E., Fang Y., Klaus S., Scherzinger W. Population ecology of the Chinese grouse, Bonasa sewerzowi, in a fragmented landscape. Biol. Conserv. 2003, 110:177-184.
53. Thuiller W. BIOMOD-optimizing predictions of species distributions and projecting potential future shifts under global change. Glob. Change Biol. 2003, 9:1353-1362.
54. Thuiller W., Lafourcade B., Engler R., Araújo M.B. BIOMOD-a platform for ensemble forecasting of species distributions. Ecography 2009, 32:369-373.
55. Torres J., Brito J.C., Vasconcelos M.J., Catarino L., Goncalves J., Honrado J. Ensemble models of habitat suitability relate chimpanzee (Pan troglodytes) conservation to forest and landscape dynamics in Western Africa. Biol. Conserv. 2010, 143:416-425.
56. Tsoar A., Allouche O., Steinitz O., Rotem D., Kadmon R. A comparative evaluation of presence-only methods for modelling species distribution. Divers. Distrib. 2007, 13:397-405.
57. Urban D., Keitt T. Landscape connectivity: a graph-theoretic perspective. Ecology 2001, 82:1205-1218.
58. Wang, J., Fang, Y., Klaus, S., Sun, Y.H., 2011. Winter foraging strategy of the Chinese Grouse (Bonasa sewerzowi): ecological and physiological factors. J. Ornithol., in press. doi: http://dx.doi.org/10.1007/s10336-011-0717-y.
59. Williams J.N., Seo C.W., Thorne J., Nelson J.K., Erwin S., O'Brien J.M., Schwartz M.W. Using species distribution models to predict new occurrences for rare plants. Divers. Distrib. 2009, 15:565-576.
60. Yao J.C., Wang T.Z. Geographical distribution of Blood Pheasant. J. Shanxi Normal Univ. 1993, 21:54-57.