根據 Ideal free distribution (IFD) 理論，生物個體的分佈會反應棲地品質，棲地品質越高的地方、個體數量越高。生態棲位模擬利用物種出現點位以及相對應之環境條件，模擬物種實際生態棲位，再據此推估研究地區內每一地點的棲地適合度。棲地適合度可反應棲地品質，因此根據 IFD 之預測，棲地適合度越高的地點，可能有越高的族群數量。囓齒動物具短暫生活史，其族群數量往往能快速反應棲地品質，因而與棲地適合度可能存在正向關係。本研究利用最大熵演算法建立臺灣山區四種囓齒目動物 (臺灣森鼠 Apodemus semotus、高山白腹鼠 Niviventer culturatus、黑腹絨鼠 Eothenomys melanogaster、臺灣高山田鼠 Alexandromys kikuchii) 之生態棲位模型，並由文獻中彙整出各物種不同地點的捕捉率 (代表族群相對豐度)，以檢測生態棲位模型所建立的棲地適合度，是否能夠反應各物種之族群豐度。結果顯示，臺灣森鼠、黑腹絨鼠與臺灣高山田鼠的棲地適合度與族群相對豐度存在顯著正向關係。此外，黑腹絨鼠與臺灣高山田鼠在特定族群豐度情境下，能以棲地適合度對應族群豐度的趨勢變化。為了更周全地評估棲地適合度是否為值得信賴之族群豐度指標，未來應建立豐度資料的標準化方法。

The theory of ideal free distribution (IFD) predicts that organisms distribute themselves according to habitat quality thereby a higher number of individuals would be found in areas of higher habitat quality. Ecological niche modeling combines species occurrences with environmental conditions to establish a species’ realized niche, based on which habitat suitability of a given geographic extent can be projected. Such habitat suitability could potentially reflect habitat quality, and according to IFD, area with higher suitability are likely higher population abundance. Rodents have relatively short life history, and their population abundance often responds quickly to habitat quality. Consequently, rodent population abundance is likely to increase positively with habitat suitability. In this study, I used Maxent algorithm to build the ecological niche models for four rodent species (Apodemus semotus, Niviventer culturatus, Eothenomys melanogaster, Alexandromys kikuchii) in Taiwan’s montane region. Furthermore, I collected literature values of capture rate as an index of relative population abundance to examine whether habitat suitability from the ecological niche model can reflect population abundance of the rodents. I found positive relationships between habitat suitability and relative population abundance for A. semotus, E. melanogaster and A. kikuchii. Moreover, under certain scenarios of population abundance, such positive relationships also exist for E. melanogaster and A. kikuchii. To improve the evaluation of whether habitat suitability is an appropriate indicator of population abundance, I suggest that standardized abundance data should be established.

Adler, G. H. (1996). Habitat relations of two endemic species of highland forest rodents in Taiwan. Zoological Studies-Taipei-, 35, 105–110.
Aertsen, W., Kint, V., van Orshoven, J., Özkan, K., & Muys, B. (2010). Comparison and ranking of different modelling techniques for prediction of site index in Mediterranean mountain forests. Ecological Modelling, 221(8), 1119–1130.
Anderson, R. P., & Raza, A. (2010). The effect of the extent of the study region on GIS models of species geographic distributions and estimates of niche evolution: Preliminary tests with montane rodents (genus Nephelomys) in Venezuela. Journal of Biogeography, 37(7), 1378–1393.
Araújo, M. B., & Luoto, M. (2007). The importance of biotic interactions for modelling species distributions under climate change. Global Ecology and Biogeography, 16(6), 743–753.
Arias-González, C., González-Maya, J. F., González Zamorano, P., & Ortega Rubio, A. (2021). Climate refugia for two Colombian endemic tamarin primates are critically under-protected. Mammalian Biology. in press,1-13.
Auffray, J.-C., Renaud, S., & Claude, J. (2009). Rodent biodiversity in changing environments. Agriculture and Natural Resources, 43(1), 83–93.
Ball, S. J., Lindenmayer, D. B., & Possingham, H. P. (2003). The predictive accuracy of population viability analysis: A test using data from two small mammal species in a fragmented landscape. Biodiversity & Conservation, 12(12), 2393–2413.
Battersby, S. A. (2015). Rodents as carriers of disease. Rodent Pests and Control, 2nd Edn. CAB International, Wallingford, 81–100.
Beyer, R. M., & Manica, A. (2020). Historical and projected future range sizes of the world’s mammals, birds, and amphibians. Nature Communications, 11(1), 1–8.
Bonebrake, T. C., Rezende, E. L., & Bozinovic, F. (2020). Climate Change and Thermoregulatory Consequences of Activity Time in Mammals. The American Naturalist, 196(1), 45–56.
Boria, R. A., & Blois, J. L. (2018). The effect of large sample sizes on ecological niche models: Analysis using a North American rodent, Peromyscus maniculatus. Ecological Modelling, 386, 83–88.
Brito, D., & de Souza Lima Figueiredo, M. (2003). Minimum viable population and conservation status of the Atlantic Forest spiny rat Trinomys eliasi. Biological Conservation, 113(1), 153–158.
Busby, J.R. (1991). BIOCLIM – a bioclimate analysis and prediction system. In: Nature Conservation: Cost Effective Biological Surveysand Data Analysis (eds Margules, C.R. & Austin, M.P.). CSIRO, Melbourne, pp. 64–68
Cano, I., & Guevara, L. (2021). Potential distribution of a montane rodent (Cricetidae, Handleyomys chapmani) through time in Mexico: The importance of occurrence data. Journal of Mountain Science, 18(8), 2024–2033.
Carpenter, G., Gillison, A. N., & Winter, J. (1993). DOMAIN: A flexible modelling procedure for mapping potential distributions of plants and animals. Biodiversity & Conservation, 2(6), 667–680.
Chou, P.-H. (2014). Foraging ecology of Taiwan field vole (Microtus kikuchii) in a Taiwan fir-Taiwan hemlock forest at the Hehuan area: Effects of plant attributes. Master thesis. National Taiwan University, Institute of Ecology and Evolutionary Biology. Taipei, Taiwan.
Elith J, Graham H. C., Anderson P. R., Dudik M., Ferrier S., Guisan A., Hijmans J. R., Huettmann F., Leathwick R. J., Lehmann A., Li J., Lohmann G. L., Loiselle A. B., Manion G., Moritz C., Nakamura M., Nakazawa Y., Overton M. J., Peterson A. T., Phillips J. S., Richardson K., Scachetti-Pereira R., Schapire E.R., Soberon J., Williams S., Wisz S. M., Zimmermann E. N. (2006). Novel methods improve prediction of species’ distributions from occurrence data. Ecography, 29(2), 129–151.
Elith, J., & Leathwick, J. (2009). The contribution of species distribution modelling to conservation prioritization. Spatial Conservation Prioritization: Quantitative Methods & Computational Tools, 70–93.
Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861–874.
Franklin, J. (2010). Mapping species distributions: Spatial inference and prediction. Cambridge University Press.
Fretwell, S.D. (1972). Populations in a seasonal environment. Princeton University Press, Princeton, New Jersey
González, C., Wang, O., Strutz, S. E., González-Salazar, C., Sánchez-Cordero, V., & Sarkar, S. (2010). Climate change and risk of leishmaniasis in North America: Predictions from ecological niche models of vector and reservoir species. PLoS Neglected Tropical Diseases, 4(1), e585.
Guisan, A., & Zimmermann, N. E. (2000). Predictive habitat distribution models in ecology. Ecological Modelling, 135(2), 147–186.
Hansson, L., & Henttonen, H. (1985). Gradients in density variations of small rodents: The importance of latitude and snow cover. Oecologia, 67(3), 394–402.
Hidasi-Neto, J., Joner, D. C., Resende, F., Monteiro, L. de M., Faleiro, F. V., Loyola, R. D., & Cianciaruso, M. V. (2019). Climate change will drive mammal species loss and biotic homogenization in the Cerrado Biodiversity Hotspot. Perspectives in Ecology and Conservation, 17(2), 57–63.
Ho, H.-C. (2009). The interactions between Taiwan Vole (Microtus kikuchii) and alpine meadow herbs at the Ho-huan area: Effects of nutrition and abundance of dominant herbs. Master thesis. National Taiwan University, Institute of Ecology and Evolutionary Biology. Taipei, Taiwan.
Hoffmann, M., Hilton-Taylor, C., Angulo, A., Böhm, M., Brooks, T. M., Butchart, S. H. M., Carpenter, K. E., Chanson, J., Collen, B., Cox, N. A., Darwall, W. R. T., Dulvy, N. K., Harrison, L. R., Katariya, V., Pollock, C. M., Quader, S., Richman, N. I., Rodrigues, A. S. L., Tognelli, M. F., … Stuart, S. N. (2010). The Impact of conservation on the status of the world’s vertebrates. Science, 330(6010), 1503–1509.
Hornfeldt, B. (1994). Delayed density dependence as a determinant of vole cycles. Ecology, 75(3), 791–806.
Hutchinson, G. E. (1957). A treatise on limnology. Vol 1: Georgraphy, physics and chemistry. John Wiley & Sons., New York.
Jensen, T. S. (1982). Seed production and outbreaks of non-cyclic rodent populations in deciduous forests. Oecologia, 54(2), 184–192.
Kamilar, J. M., & Tecot, S. R. (2016). Anthropogenic and climatic effects on the distribution of Eulemur species: An ecological niche modeling approach. International Journal of Primatology, 37(1), 47–68.
Karger, D. N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R. W., Zimmermann, N. E., Linder, H. P., & Kessler, M. (2017). Climatologies at high resolution for the earth’s land surface areas. Scientific Data, 4, 170122.
Lehmann, A., Overton, J. M., & Leathwick, J. R. (2002). GRASP: Generalized regression analysis and spatial prediction. Ecological Modelling, 157(2–3), 189–207.
Lin, L.-K., & Shiraishi, S. (1992). Reproductive biology of the Formosan wood mouse, Apodemus semotus. Journal of the Faculty of Agriculture, Kyushu University, 36(3), 183–200.
Lozier, J. D., Aniello, P., & Hickerson, M. J. (2009). Predicting the distribution of Sasquatch in western North America: Anything goes with ecological niche modelling. Journal of Biogeography, 36(9), 1623–1627.
Mantyka-pringle, C. S., Martin, T. G., & Rhodes, J. R. (2012). Interactions between climate and habitat loss effects on biodiversity: A systematic review and meta-analysis. Global Change Biology, 18(4), 1239–1252.
Meerburg, B. G., Singleton, G. R., & Kijlstra, A. (2009). Rodent-borne diseases and their risks for public health. Critical Reviews in Microbiology, 35(3), 221–270.
Morrison, M. L., Marcot, B., & Mannan, W. (2012). Wildlife-habitat relationships: Concepts and applications. Island Press.
Naimi, B., Skidmore, A. K., Groen, T. A., & Hamm, N. a. S. (2011). Spatial autocorrelation in predictors reduces the impact of positional uncertainty in occurrence data on species distribution modelling. Journal of Biogeography, 38(8), 1497–1509.
Nater, C. R., Benthem, K. J. van, Canale, C. I., Schradin, C., & Ozgul, A. (2018). Density feedbacks mediate effects of environmental change on population dynamics of a semidesert rodent. Journal of Animal Ecology, 87(6), 1534–1546.
Pardi, M. I., Terry, R. C., Rickart, E. A., & Rowe, R. J. (2020). Testing climate tracking of montane rodent distributions over the past century within the Great Basin ecoregion. Global Ecology and Conservation, 24, e01238.
Pardiñas, U. F. J., Tammone, M. N., Voglino, D., & Soto, E. C. (2021). Expanding the knowledge on a desert sigmodontine rodent in Central Argentina with remarks on its conservation status. Mammalia.
Peterson, A. T., Papeş, M., & Soberón, J. (2008). Rethinking receiver operating characteristic analysis applications in ecological niche modeling. Ecological Modelling, 213(1), 63–72.
Phillips, S. J., Anderson, R. P., & Schapire, R. E. (2006). Maximum entropy modeling of species geographic distributions. Ecological Modelling, 190(3), 231–259.
Rayner, K., Lohr, C. A., Garretson, S., & Speldewinde, P. (2021). Two species, one island: Retrospective analysis of threatened fauna translocations with divergent outcomes. PLOS ONE, 16(7), e0253962.
Rengstorf, A. M., Yesson, C., Brown, C., & Grehan, A. J. (2013). High-resolution habitat suitability modelling can improve conservation of vulnerable marine ecosystems in the deep sea. Journal of Biogeography, 40(9), 1702–1714.
Reutter, B. A., Helfer, V., Hirzel, A. H., & Vogel, P. (2003). Modelling habitat-suitability using museum collections: An example with three sympatric Apodemus species from the Alps. Journal of Biogeography, 30(4), 581–590.
Rondinini, C., Stuart, S., & Boitani, L. (2005). Habitat suitability models and the shortfall in conservation planning for African vertebrates. Conservation Biology, 19(5), 1488–1497.
Sandoval, S., López-González, C., Escobar-Flores, J. G., & Martínez-Rincón, R. O. (2020). Effect of spatial resolution, algorithm and variable set on the estimated distribution of a mammal of concern: The squirrel Sciurus aberti. Écoscience, 27(3), 195–207.
Segan, D. B., Murray, K. A., & Watson, J. E. M. (2016). A global assessment of current and future biodiversity vulnerability to habitat loss–climate change interactions. Global Ecology and Conservation, 5, 12–21.
Shaner, P.-J. L., Wu, S.-H., Ke, L., & Kao, S.-J. (2013). Trophic niche divergence reduces survival in an omnivorous rodent. Evolutionary Ecology Research, 15(8), 933–946.
Stockwell, D. (1999). The GARP modelling system: Problems and solutions to automated spatial prediction. International Journal of Geographical Information Science, 13(2), 143–158.
Taylor, P. J., Nengovhela, A., Linden, J., & Baxter, R. M. (2016). Past, present, and future distribution of Afromontane rodents (Muridae: Otomys) reflect climate-change predicted biome changes. Mammalia, 80(4), 359–375.
Tsianou, M. A., Lazarina, M., Michailidou, D.-E., Andrikou-Charitidou, A., Sgardelis, S. P., & Kallimanis, A. S. (2021). The effect of climate and human pressures on functional diversity and species richness patterns of amphibians, reptiles and mammals in Europe. Diversity, 13(6), 275.
Tuanmu, M.-N., & Jetz, W. (2014). A global 1-km consensus land-cover product for biodiversity and ecosystem modelling. Global Ecology and Biogeography, 23(9), 1031–1045.
Vessey, S. H., & Vessey, K. B. (2007). Linking behavior, life history and food supply with the population dynamics of white-footed mice (Peromyscus leucopus). Integrative Zoology, 2(3), 123–130.
Weber, M. M., Stevens, R. D., Diniz-Filho, J. A. F., & Grelle, C. E. V. (2017). Is there a correlation between abundance and environmental suitability derived from ecological niche modelling? A meta-analysis. Ecography, 40(7), 817–828.
Wolff, J. O. (1996). Population fluctuations of mast-eating rodents are correlated with production of acorns. Journal of Mammalogy, 77(3), 850–856.
Yackulic, C. B., Chandler, R., Zipkin, E. F., Royle, J. A., Nichols, J. D., Campbell Grant, E. H., & Veran, S. (2013). Presence-only modelling using MAXENT: When can we trust the inferences? Methods in Ecology and Evolution, 4(3), 236–243.
Yeh, W.-T. (2012). Using stable isotopes to analyze food partitioning of two small rodent communities in He-huan mountains. Master thesis. National Taiwan University, Institute of Ecology and Evolutionary Biology. Taipei, Taiwan.
Young, M., & Carr, M. H. (2015). Application of species distribution models to explain and predict the distribution, abundance and assemblage structure of nearshore temperate reef fishes. Diversity and Distributions, 21(12), 1428–1440.
Yu, H.-T. (1993). Natural history of small mammals of subtropical montane areas in central Taiwan. Journal of Zoology, 231(3), 403–422.
Yu, H.-T. (1994). Distribution and abundance of small mammals along a subtropical elevational gradient in central Taiwan. Journal of Zoology, 234(4), 577–600.
王玉婷。(2012)。島嶼中的島嶼: 從粒線體DNA 探討台灣不同高山地區台灣高山田鼠 (Microtus kikuchii) 的遺傳結構。東海大學生命科學系研究所碩士論文。臺中，臺灣。
甘慕龍。(1995)。武陵地區三種囓齒類動物(森鼠、黑腹絨鼠、巢鼠)的食性與棲地研究。國立臺灣大學動物學研究所碩士論文。臺北，臺灣。
林良恭。(2002)。玉山國家公園之高山島嶼生態學哺乳類保育遺傳研究。內政部營建署玉山國家公園管理處委託研究報告，臺北，臺灣。
張家豪。(2020)。臺灣兩種鼠科物種在時空棲位的區隔。國立臺灣師範大學生命科學系研究所碩士論文。臺北，臺灣。