Quantifying species' range shifts in relation to climate change: A case study of Abies spp. in China

PLoS ONE

Volumn 6, Issue 8, 2011, Pages

  Kou, Xiaojun ^a   Li, Qin ^a   Liu, Shirong ^b  

^a BEIJING NORMAL UNIVERSITY   (China)

^b RESEARCH INSTITUTE OF FORESTRY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ABIES; ARTICLE; CHINA; CLIMATE CHANGE; CONTROLLED STUDY; CORRELATION ANALYSIS; LATITUDE; LONGITUDE; MATHEMATICAL PARAMETERS; NONHUMAN; PREVALENCE; RANGE INCREMENT INDEX; RANGE OVERLAPPING INDEX; RELIABILITY; SPECIES DISTRIBUTION; BIODIVERSITY; BIOLOGICAL MODEL; DATA BASE; PHYSIOLOGY; SPECIES DIFFERENCE; STATISTICAL MODEL;

ABIES;

ABIES; BIODIVERSITY; CHINA; CLIMATE CHANGE; DATABASES AS TOPIC; MODELS, BIOLOGICAL; MODELS, STATISTICAL; SPECIES SPECIFICITY;

EID: 80052003320     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0023115     Document Type: Article

References (45)

1. Elith J, Graham CH, Anderson RP, Dudik M, Ferrier S, et al. (2006) Novel methods improve prediction of species' distributions from occurrence data. Ecography 29: 129-151.
2. Lawler JJ, White D, Neilson RP, Blaustein AR, (2006) Predicting climate-induced range shifts: model differences and model reliability. Global Change Biology 12: 1568-1584.
3. Meehl GA, Covey C, Delworth T, Latif M, McAvaney B, et al. (2007) The WCRP CMIP3 multimodel dataset- A new era in climate change research. Bulletin of the American Meteorological Society 88: 1383-+.
4. Wisz MS, Hijmans RJ, Li J, Peterson AT, Graham CH, et al. (2008) Effects of sample size on the performance of species distribution models. Diversity and Distributions 14: 763-773.
5. Thuiller W, Lafourcade B, Engler R, Araujo MB, (2009) BIOMOD- a platform for ensemble forecasting of species distributions. Ecography 32: 369-373.
6. New M, Lister D, Hulme M, Makin I, (2002) A high-resolution data set of surface climate over global land areas. Climate Research 21: 1-25.
7. Hijmans RJ, Cameron SE, Parra JL, Jones PG, Jarvis A, (2005) Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology 25: 1965-1978.
8. Tabor K, Williams JW, (2010) Globally downscaled climate projections for assessing the conservation impacts of climate change. Ecological Applications 20: 554-565.
9. Kou XJ, Li Q, Liu SR, (2011) High resolution bioclimatic dataset derived from future climate projections for plant species distribution modeling. Ecological Infomatics doi:10.1016/j.ecoinf.2011.01.004.
10. Harrison JA, Allan DG, Underhill LG, Herremans M, Tree AJ, et al. (1997) The atlas of Southern African Birds Birdlife South Africa, Johannesburg.
11. Kurtto A, Lampinen R, (1999) Atlas of the distribution of vascular plants in Finland: A digital view of the national floristic database. Acta Botanica Fennica 162: 67-74.
12. Patterson BD, Ceballos G, Sechrest W, (2003) Digitial distribution maps of the mammals of the western hemisphere, Version 1.0 NatureServe, Arlington, VA.
13. Dunn AM, Weston MA, (2008) A review of terrestrial bird atlases of the world and their application. Emu 108: 42-67.
14. Robertson MP, Cumming GS, Erasmus BFN, (2010) Getting the most out of atlas data. Diversity and Distributions 16: 363-375.
15. Thuiller W, Araujo MB, Pearson RG, Whittaker RJ, Brotons L, et al. (2004) Biodiversity conservation- Uncertainty in predictions of extinction risk. Nature 430.
16. Poyry J, Luoto M, Heikkinen RK, Saarinen K, (2008) Species traits are associated with the quality of bioclimatic models. Global Ecology and Biogeography 17: 403-414.
17. Coetzee BWT, Robertson MP, Erasmus BFN, van Rensburg BJ, Thuiller W, (2009) Ensemble models predict Important Bird Areas in southern Africa will become less effective for conserving endemic birds under climate change. Global Ecology and Biogeography 18: 701-710.
18. Zanini F, Pellet J, Schmidt BR, (2009) The transferability of distribution models across regions: an amphibian case study. Diversity and Distributions 15: 469-480.
19. Lobo JM, Jimenez-Valverde A, Hortal J, (2010) The uncertain nature of absences and their importance in species distribution modelling. Ecography 33: 103-114.
20. Platts PJ, Ahrends A, Gereau RE, McClean CJ, Lovett JC, et al. (2010) Can distribution models help refine inventory-based estimates of conservation priority? A case study in the Eastern Arc forests of Tanzania and Kenya. Diversity and Distributions 16: 628-642.
21. Thomas CD, Cameron A, Green RE, Bakkenes M, Beaumont LJ, et al. (2004) Extinction risk from climate change. Nature 427: 145-148.
22. Lawler JJ, Shafer SL, White D, Kareiva P, Maurer EP, et al. (2009) Projected climate-induced faunal change in the Western Hemisphere. Ecology 90: 588-597.
23. Svenning JC, Kerr J, Rahbek C, (2009) Predicting future shifts in species diversity. Ecography 32: 3-4.
24. Randin CF, Dirnbock T, Dullinger S, Zimmermann NE, Zappa M, et al. (2006) Are niche-based species distribution models transferable in space? Journal of Biogeography 33: 1689-1703.
25. Jimenez-Valverde A, Lobo JM, Hortal J, (2008) Not as good as they seem: the importance of concepts in species distribution modelling. Diversity and Distributions 14: 885-890.
26. Phillips SJ, (2008) Transferability, sample selection bias and background data in presence-only modelling: a response to Petersonet al. (2007). Ecography 31: 272-278.
27. Lobo JM, Jimenez-Valverde A, Real R, (2008) AUC: a misleading measure of the performance of predictive distribution models. Global Ecology and Biogeography 17: 145-151.
28. Araujo MB, Pearson RG, Thuiller W, Erhard M, (2005) Validation of species-climate impact models under climate change. Global Change Biology 11: 1504-1513.
29. Araujo MB, Whittaker RJ, Ladle RJ, Erhard M, (2005) Reducing uncertainty in projections of extinction risk from climate change. Global Ecology and Biogeography 14: 529-538.
30. Araujo MB, Guisan A, (2006) Five (or so) challenges for species distribution modelling. Journal of Biogeography 33: 1677-1688.
31. Elith J, Graham CH, (2009) Do they? How do they? WHY do they differ? On finding reasons for differing performances of species distribution models. Ecography 32: 66-77.
32. Thuiller W, (2004) Patterns and uncertainties of species' range shifts under climate change. Global Change Biology 10: 2020-2027.
33. Diniz JAF, Bini LM, Rangel TF, Loyola RD, Hof C, et al. (2009) Partitioning and mapping uncertainties in ensembles of forecasts of species turnover under climate change. Ecography 32: 897-906.
34. Nogues-Bravo D, (2009) Predicting the past distribution of species climatic niches. Global Ecology and Biogeography 18: 521-531.
35. Robertson MP, Villet MH, Palmer AR, (2004) A fuzzy classification technique for predicting species' distributions: applications using invasive alien plants and indigenous insects. Diversity and Distributions 10: 461-474.
36. Real R, Marquez AL, Olivero J, Estrada A, (2010) Species distribution models in climate change scenarios are still not useful for informing policy planning: an uncertainty assessment using fuzzy logic. Ecography 33: 304-314.
37. Broennimann O, Thuiller W, Hughes G, Midgley GF, Alkemade JMR, et al. (2006) Do geographic distribution, niche property and life form explain plants' vulnerability to global change? Global Change Biology 12: 1079-1093.
38. Editorial Committee of Flora of China CAS (1978) Flora of China (Volume 7) Beijing Science Press.
39. Wu ZY, (1980) Vegetation of China Beijing Science Press.
40. Hou XY, (2001) The Vegetation Atlas of China(1:1000 000) Beijing Science Press.
41. Harrison SP, Prentice IC, Barboni D, Kohfeld KE, Ni J, et al. (2010) Ecophysiological and bioclimatic foundations for a global plant functional classification. Journal of Vegetation Science 21: 300-317.
42. Phillips SJ, Anderson RP, Schapire RE, (2006) Maximum entropy modeling of species geographic distributions. Ecological Modelling 190: 231-259.
43. Phillips SJ, Dudik M, (2008) Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation. Ecography 31: 161-175.
44. Allouche O, Tsoar A, Kadmon R, (2006) Assessing the accuracy of species distribution models: prevalence, kappa and the true skill statistic (TSS). Journal of Applied Ecology 43: 1223-1232.
45. Manel S, Williams HC, Ormerod SJ, (2001) Evaluating presence-absence models in ecology: the need to account for prevalence. Journal of Applied Ecology 38: 921-931.