Chinese Journal of Applied Ecology ›› 2017, Vol. 28 ›› Issue (6): 2063-2072.doi: 10.13287/j.1001-9332.201706.006
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YANG Xiao-long1, YANG Chao-jie1, HU Cheng-ye1, ZHANG Xiu-mei1,2*
Received:
2016-09-28
Published:
2017-06-18
Contact:
*E-mail:gaozhang@ouc.edu.cn
Supported by:
YANG Xiao-long, YANG Chao-jie, HU Cheng-ye, ZHANG Xiu-mei. Application of species distribution models in the prediction of marine potential habitat: A review[J]. Chinese Journal of Applied Ecology, 2017, 28(6): 2063-2072.
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[1] Zhang Y-Y (张燕燕), Hu G-Y (胡光宇). Exploitation and development of the ocean. China Venture Capital (中国科技投资), 2011(6): 61-63 (in Chinese) [2] Walker DI, Kendrick GA. Threats to macroalgal diversity: Marine habitat destruction and fragmentation, pollution and introduced species. Botanica marina, 1998, 41: 105-112 [3] Hovel KA. Habitat fragmentation in marine landscapes: Relative effects of habitat cover and configuration on juvenile crab survival in California and North Carolina seagrass beds. Biological Conservation, 2003, 110: 401-412 [4] Wang D (王 栋). Study on Economic Value of Marine Biodiversity Preservation. PhD Thesis. Qingdao: Ocean University of China, 2012 (in Chinese) [5] Robinson LM, Elith J, Hobday AJ, et al. Pushing the limits in marine species distribution modelling: Lessons from the land present challenges and opportunities. Glo-bal Ecology and Biogeography, 2011, 20: 789-802 [6] iaulys A, Bucˇas M. Species distribution modelling of benthic invertebrates in the south-eastern Baltic Sea. Baltica, 2012, 25: 163-170 [7] Li G-Q (李国庆), Liu C-C (刘长成), Liu Y-G (刘玉国), et al. Advance in theoretical issues of species distribution models. Acta Ecologica Sinica (生态学报), 2013, 33(16): 4827-4835 (in Chinese) [8] Whittaker RH. Vegetation of the great smoky mountains. Ecological Monographs, 1956, 26: 1-80 [9] Nix H, McMahon J, Mackenzie D. Potential areas of production and the future of pigeon pea and other grain legumes in Australia// Wallis ES, Whiteman PC, eds. The Potential for Pigeon Pea in Australia. Proceedings of Pigeon Pea (Cajanus cajan (L.) Millsp.) Field Day. Queensland, Australia: University of Queensland, 1977: 1-12 [10] Fairbanks RG, Sverdlove M, Free R, et al. Vertical distribution and isotopic fractionation of living planktonic foraminifera from the Panama Basin. Nature, 1982, 298: 841-844 [11] Elith J, Leathwick JR. Species distribution models: Eco-logical explanation and prediction across space and time. Annual Review of Ecology, Evolution, and Systematics, 2009, 40: 677-697 [12] Manel S, Dias JM, Buckton ST, et al. Alternative metho-ds for predicting species distribution: An illustration with Himalayan river birds. Journal of Applied Ecology, 1999, 36: 734-747 [13] Loiselle BA, Howell CA, Graham CH, et al. Avoiding pitfalls of using species distribution models in conservation planning. Conservation Biology, 2003, 17: 1591-1600 [14] Phillips SJ, Dudík M, Schapire RE. A maximum entropy approach to species distribution modeling. Procee-dings of the Twenty-first International Conference on Machine Learning, New York, 2004: 655-662 [15] Guisan A, Thuiller W. Predicting species distribution: offering more than simple habitat models. Ecology Letters, 2005, 8: 993-1009 [16] Raes N, ter Steege H. A null-model for significance testing of presence-only species distribution models. Eco-graphy, 2007, 30: 727-736 [17] Larson ER, Olden JD. Using avatar species to model the potential distribution of emerging invaders. Global Ecology and Biogeography, 2012, 21: 1114-1125 [18] Tian B (田 波), Zhou Y-X (周云轩), Zhang L-Q (张利权), et al. A GIS and remote sensing-based ana-lysis of migratory bird habitat suitability for Chongming Dongtan Nature Reserve, Shanghai. Acta Ecologica Sinica (生态学报), 2008, 28(7): 3049-3059 (in Chinese) [19] Wang Z-Q (王志强), Chen Z-C (陈志超), Hao C-Y (郝成元). Breeding habitat suitability evaluation of Red-crown crane in Zhalong National Nature Reserve by the method of habitat suitability index. Wetland Science (湿地科学), 2009, 7(3): 197-201 (in Chinese) [20] Wu J-G (吴建国). Potential effects of climate change on the distribution of seven protected plants in China. Journal of Wuhan Botanical Research (武汉植物学研究), 28(4): 437-452 (in Chinese) [21] Cui Y-P (崔耀平), Liu J-Y (刘纪远), Hu Y-F (胡云锋), et al. Estimating and analyzing the optimum temperature for vegetation growth in China. Journal of Natural Resources (自然资源学报), 2012, 27(2): 281-292 (in Chinese) [22] Hu Z-J (胡忠俊), Zhang Y-L (张镱锂), Yu H-B (于海彬). Simulation of Stipa purpurea species’ distribution pattern on Tibetan Plateau based on MaxEnt mo-del and GIS. Chinese Journal of Applied Ecology (应用生态学报), 2015, 26(2): 505-511 (in Chinese) [23] Yu H-B (于海彬), Zhang Y-L (张镱锂), Li S-C (李士成), et al. Predicting the dispersal routes of alpine plant Pedicularis longiflora (Orobanchaceae) based on GIS and species distribution models. Chinese Journal of Applied Ecology (应用生态学报), 2014, 25(6): 1669-1673 (in Chinese) [24] Li J (李 佳), Li Y (李 言), Miao L-J (缪泸君), et al. Habitat assessment of sika deer (Cervus nippon) in the Taohongling National Nature Reserve, Jiangxi Pro-vince, China. Acta Ecologica Sinica (生态学报), 2014, 34(5): 1274-1283 (in Chinese) [25] Skov H, Humphreys E, Garthe S, et al. Application of habitat suitability modelling to tracking data of marine animals as a means of analyzing their feeding habitats. Ecological Modelling, 2008, 212: 504-512 [26] Zheng B (郑 波), Chen X-J (陈新军), Li G (李 纲). Relationship between the resource and fishing ground of mackerel and environmental factors based on GAM and GLM models in the East China Sea and Yellow Sea. Journal of Fisheries of China (水产学报), 2008, 32(3): 379-386 (in Chinese) [27] Chen X-Z (陈雪忠), Fan W (樊 伟), Cui X-S (崔雪森), et al. Fishing ground forecasting of Thunnus alalung in Indian Ocean based on random forest. Acta Oceanologica Sinica (海洋学报), 2013, 35(1): 158-164 (in Chinese) [28] Lauria V, Power AM, Lordan C, et al. Spatial transferability of habitat suitability models of Nephrops norvegicus among fished areas in the Northeast Atlantic: Sufficiently stable for marine resource conservation? PLoS One, 2015, 10(2): e0117006 [29] Guisan A, Zimmermann NE. Predictive habitat distribution models in ecology. Ecological Modelling, 2000, 135: 147-186 [30] Leclerc M, Saint-Hilaire A, Bechara J. State-of-the-art and perspectives of habitat modelling for determining conservation flows. Canadian Water Resources Journal, 2003, 28: 135-151 [31] Clark, RD, Christensen, JD, Monaco, ME, et al. A habitat-use model to determine essential fish habitat for juvenile brown shrimp (Farfantepenaeus aztecus) in Galveston Bay, Texas. Fishery Bulletin, 2004, 102: 264-277 [32] Topping DT, Lowe CG, Caselle JE. Home range and habitat utilization of adult California sheephead, Semico-ssyphus pulcher (Labridae), in a temperate no-take marine reserve. Marine Biology, 2005, 147: 301-311 [33] Brown SK, Buja KR, Jury SH, et al. Habitat suitability index models for eight fish and invertebrate species in Casco and Sheepscot Bays, Maine. North American Journal of Fisheries Management, 2000, 20: 408-435 [34] Soniat TM, Brody MS. Field validation of a habitat suitability index model for the American oyster. Estuaries, 1988, 11: 87-95 [35] Barry JP, Kochevar RE, Baxter CH. The influence of pore-water chemistry and physiology on the distribution of vesicomyid clams at cold seeps in Monterey Bay: Implications for patterns of chemosynthetic community organization. Limnology and Oceanography, 1997, 42: 318-328 [36] Barnes TK, Volety AK, Chartier K, et al. A habitat suitability index model for the eastern oyster (Crassostrea virginica), a tool for restoration of the Caloosahatchee Estuary, Florida. Journal of Shellfish Research, 2007, 26: 949-959 [37] Pollack JB, Cleveland A, Palmer TA, et al. A restoration suitability index model for the Eastern oyster (Crassostrea virginica) in the Mission-Aransas Estuary, TX, USA. PLoS One, 2012, 7(7): e40839 [38] Degraer S, Verfaillie E, Willems W, et al. Habitat suita-bility modelling as a mapping tool for macrobenthic communities: An example from the Belgian part of the North Sea. Continental Shelf Research, 2008, 28: 369-379 [39] Chen X, Li G, Feng B, et al. Habitat suitability index of Chub mackerel (Scomber japonicus) from July to September in the East China Sea. Journal of Oceanography, 2009, 65: 93-102 [40] Monk J, Ierodiaconou D, Bellgrove A, et al. Remotely sensed hydroacoustics and observation data for predicting fish habitat suitability. Continental Shelf Research, 2011, 31: 17-27 [41] Stephenson N. Actual evapotranspiration and deficit: Bio-logically meaningful correlates of vegetation distribution across spatial scales. Journal of Biogeography, 1998, 25: 855-870 [42] Running SW. Generalization of a forest ecosystem process model for other biomes, Biome-BGC, and an application for global-scale models// Roy J,eds. Sca-ling Physiological Processes: Leaf to Globe. Amsterdam, the Netherlands: Elsevier, 1993: 141-158 [43] Peñuelas J, Boada M. A global change-induced biome shift in the Montseny Mountains (NE Spain). Global Change Biology, 2003, 9: 131-140 [44] Sarmiento JL, Slater R, Barber R, et al. Response of ocean ecosystems to climate warming. Global Biogeochemical Cycles, 2004, 18: 1-23 [45] Treml EA, Halpin PN, Urban DL, et al. Modeling po-pulation connectivity by ocean currents, a graph-theore-tic approach for marine conservation. Landscape Ecology, 2008, 23: 19-36 [46] Cowen RK, Paris CB, Srinivasan A. Scaling of connectivity in marine populations. Science, 2006, 311: 522-527 [47] Beerling DJ, Huntley B, Bailey JP. Climate and the distribution of Fallopia japonica: Use of an introduced species to test the predictive capacity of response surfaces. Journal of Vegetation Science, 1995, 6: 269-282 [48] Rangel TF, Loyola RD. Labeling ecological niche mo-dels. Natureza & Conservação, 2012, 10: 119-126 [49] Qiao H-J (乔慧捷), Hu J-H (胡军华), Huang J-H (黄继红). Theoretical basis, future directions, and challenges for ecological niche models. Scientia Sinica Vitae (中国科学:生命科学), 2013, 43(11): 915-927 (in Chinese) [50] Hernandez PA, Graham CH, Master LL, et al. The effect of sample size and species characteristics on performance of different species distribution modeling metho-ds. Ecography, 2006, 29: 773-785 [51] Li S-C (李双成), Gao J-B (高江波). Prediction of spacial distribution of Eupatorium adenophorum Sprengel based on GARP model: A case study in Longitudinal Range-gorge Region of Yunnan Province. Chinese Journal of Ecology (生态学杂志), 2008, 27(9): 1531-1536 (in Chinese) [52] Merow C, Smith MJ, Silander JA. A practical guide to MaxEnt for modeling species’ distributions: What it does, and why inputs and settings matter. Ecography, 2013, 36: 1058-1069 [53] Foerster S, Zhong Y, Pintea L, et al. Feeding habitat quality and behavioral trade-offs in chimpanzees: A case for species distribution models. Behavioral Ecology, 2016, 27, doi: 10.1093/beheco/arw004 [54] Hirzel AH, Hausser J, Chessel D, et al. Ecological-niche factor analysis: How to compute habitat-suitability maps without absence data? Ecology, 2002, 83: 2027-2036 [55] Praca E, Gannier A. Ecological niches of three teuthophageous odontocetes in the northwestern Mediterranean Sea. Ocean Science, 2008, 4: 49-59 [56] Galparsoro I, Borja Á, Bald J, et al. Predicting suitable habitat for the European lobster (Homarus gammarus), on the Basque continental shelf (Bay of Biscay), using ecological-niche factor analysis. Ecological Modelling, 2009, 220: 556-567 [57] Valle M, Borja Á, Chust G, et al. Modelling suitable estuarine habitats for Zostera noltii, using ecological niche factor analysis and bathymetric LiDAR. Estuarine, Coastal and Shelf Science, 2011, 94: 144-154 [58] McManus JP, Prandle D. Development of a model to reproduce observed suspended sediment distributions in the southern North Sea using principal component analysis and multiple linear regression. Continental Shelf Research, 1997, 17: 761-778 [59] Lenoir S, Beaugrand G, Lecuyer E. Modelled spatial distribution of marine fish and projected modifications in the North Atlantic Ocean. Global Change Biology, 2011, 17: 115-129 [60] Bond ME, Babcock EA, Pikitch EK, et al. Reef sharks exhibit site-fidelity and higher relative abundance in marine reserves on the Mesoamerican Barrier Reef. PLoS One, 2012, 7(3): e32983 [61] Stoner AW, Manderson JP, Pessutti JP. Spatially explicit analysis of estuarine habitat for juvenile winter flounder: Combining generalized additive models and geo-graphic information systems. Marine Ecology Progress Series, 2001, 213: 253-271 [62] Chen X-J (陈新军), Tian S-Q (田思泉). Temp-spatial distribution on abundance index of nylon flying squid Ommastrephes bartrami in the Northwestern Pacific using generalized additive models. Journal of Jimei University (Natural Science) (集美大学学报:自然科学版), 2006, 11(4): 295-300 (in Chinese) [63] Leathwick JR, Elith J, Hastie T. Comparative perfor-mance of generalized additive models and multivariate adaptive regression splines for statistical modelling of species distributions. Ecological Modelling, 2006, 199: 188-196 [64] Loots C, Koubbi P, Duhamel G. Habitat modelling of Electrona antarctica (Myctophidae, Pisces) in Ker-guelen by generalized additive models and geographic information systems. Polar Biology, 2007, 30: 951-959 [65] Drexler M, Ainsworth CH. Generalized additive models used to predict species abundance in the Gulf of Mexico: An ecosystem modeling tool. PloS One, 2013, 8(5): e64458 [66] Jowett IG, Davey AJH. A comparison of composite habitat suitability indices and generalized additive models of invertebrate abundance and fish presence-habitat availability. Transactions of the American Fisheries Society, 2007, 136: 428-444 [67] Murawski SA. Climate change and marine fish distributions: Forecasting from historical analogy. Transactions of the American Fisheries Society, 1993, 122: 647-658 [68] Rodriguez-Galiano V, Sanchez-Castillo M, Chica-Olmo M, et al. Machine learning predictive models for mineral prospectivity: An evaluation of neural networks, random forest, regression trees and support vector machines. Ore Geology Reviews, 2015, 71: 804-818 [69] Pittman SJ, Christensen JD, Caldow C, et al. Predictive mapping of fish species richness across shallow-water seascapes in the Caribbean. Ecological Modelling, 2007, 204: 9-21 [70] Holmes KW, Van Niel KP, Radford B, et al. Modelling distribution of marine benthos from hydroacoustics and underwater video. Continental Shelf Research, 2008, 28: 1800-1810 [71] Ierodiaconou D, Monk J, Rattray A, et al. Comparison of automated classification techniques for predicting benthic biological communities using hydroacoustics and video observations. Continental Shelf Research, 2011, 31: 28-38 [72] Yoo JW, Lee YW, Lee CG, et al. Effective prediction of biodiversity in tidal flat habitats using an artificial neural network. Marine Environmental Research, 2013, 83: 1-9 [73] Lee S, Park I, Koo BJ, et al. Macrobenthos habitat potential mapping using GIS-based artificial neural network models. Marine Pollution Bulletin, 2013, 67: 177-186 [74] Jaynes ET. Information theory and statistical mechanics. Physical Review, 1957, 106: 620-630 [75] Jones MC, Dye SR, Pinnegar JK, et al. Modelling commercial fish distributions: Prediction and assessment using different approaches. Ecological Modelling, 2012, 225: 133-145 [76] Reiss H, Cunze S, König K, et al. Species distribution modelling of marine benthos: A North Sea case study. Marine Ecology Progress Series, 2011, 442: 71-86 [77] Downie AL, von Numers M, Boström C. Influence of model selection on the predicted distribution of the seagrass Zostera marina. Estuarine, Coastal and Shelf Science, 2013, 121: 8-19 [78] Rinde E, Christie H, Fagerli CW, et al. The influence of physical factors on kelp and sea urchin distribution in previously and still grazed areas in the NE Atlantic. PloS One, 2014, 9(6): e100222 [79] de Rivera CE, Steves BP, Fofonoff PW, et al. Potential for high-latitude marine invasions along western North America. Diversity and Distributions, 2011, 17: 1198-1209 [80] Jiang H (江 洪). DCA ordination, environmental interpretation and geographical distribution model of spruce and fir plant communities in northwest Sichuan and south Gansu. Acta Phytoecologica Sinica (植物生态学报), 1994, 18(3): 209-218 (in Chinese) [81] Tibshirani R. Regression shrinkage and selection via the lasso. Journal of the Royal Statistical Society Series B, 1996, 58: 267-288 [82] Tyberghein L, Verbruggen H, Pauly K, et al. Bio-ORACLE: A global environmental dataset for marine species distribution modelling. Global Ecology and Biogeography, 2012, 21: 272-281 [83] Peterson MS, Ross ST. Dynamics of littoral fishes and decapods along a coastal river-estuarine gradient. Estua-rine, Coastal and Shelf Science, 1991, 33: 467-483 [84] Macpherson E. Large-scale species-richness gradients in the Atlantic Ocean. Proceedings of the Royal Society of London B: Biological Sciences, 2002, 269: 1715-1720 [85] Hsieh C, Reiss CS, Hunter JR, et al. Fishing elevates variability in the abundance of exploited species. Nature, 2006, 443: 859-862 [86] Montgomery DC, Peck EA. Introduction to Linear Regression Analysis. 2nd Ed. New York: John Wiley & Sons, 1992 [87] Tang H (唐 浩), Xu L-X (许柳雄), Zhu G-P (朱国平), et al. Effects of spatiotemporal and environmental factors on the fishing ground of skipjack tuna (Katsuwonus pelamis) in the western and central Pacific Ocean based on generalized additive model. Marine Environmental Science (海洋环境科学), 2013, 32(4): 518-522 (in Chinese) [88] Mellin C, Russell BD, Connell SD, et al. Geographic range determinants of two commercially important marine molluscs. Diversity and Distributions, 2012, 18: 133-146 [89] Flaten AC, Davidsen JG, Thorstad EB, et al. The first months at sea: Marine migration and habitat use of sea trout Salmo trutta post-smolts. Journal of Fish Biology, 2016, 89: 1624-1640 [90] Neter J, Wasserman W, Kunter MG. Applied Linear Regression analysis. 2nd Ed. Homewood, IL: Richard D. Irwin Inc, 1989 [91] Xu Z-L (许仲林), Peng H-H (彭焕华), Peng S-Z (彭守璋). The development and evaluation of species distribution models. Acta Ecologica Sinica (生态学报), 2015, 35(2): 557-567 (in Chinese) [92] Palialexis A, Georgakarakos S, Karakassis I, et al. Prediction of marine species distribution from presence-absence acoustic data: Comparing the fitting efficiency and the predictive capacity of conventional and novel distribution models. Hydrobiologia, 2011, 670: 241-266 [93] Dambach J, Rödder D. Applications and future challenges in marine species distribution modeling. Aquatic Conservation: Marine and Freshwater Ecosystems, 2011, 21: 92-100 [94] Jones MC, Cheung WWL. Multi-model ensemble projections of climate change effects on global marine biodiversity. ICES Journal of Marine Science, 2014, 72: 741-752 |
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