Optimization of environmental variables in habitat suitability modeling for mantis shrimp <i>Oratosquilla oratoria</i> in the Haizhou Bay and adjacent waters

Yunlei Zhang; Huaming Yu; Haiqing Yu; Binduo Xu; Chongliang Zhang; Yiping Ren; Ying Xue; Lili Xu

doi:10.1007/s13131-020-1546-8

Volume 39 Issue 6

Jun. 2020

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Yunlei Zhang, Huaming Yu, Haiqing Yu, Binduo Xu, Chongliang Zhang, Yiping Ren, Ying Xue, Lili Xu. Optimization of environmental variables in habitat suitability modeling for mantis shrimp Oratosquilla oratoria in the Haizhou Bay and adjacent waters[J]. Acta Oceanologica Sinica, 2020, 39(6): 36-47. doi: 10.1007/s13131-020-1546-8

Citation:

Yunlei Zhang, Huaming Yu, Haiqing Yu, Binduo Xu, Chongliang Zhang, Yiping Ren, Ying Xue, Lili Xu. Optimization of environmental variables in habitat suitability modeling for mantis shrimp Oratosquilla oratoria in the Haizhou Bay and adjacent waters[J]. Acta Oceanologica Sinica, 2020, 39(6): 36-47. doi: 10.1007/s13131-020-1546-8

Citation:

Yunlei Zhang, Huaming Yu, Haiqing Yu, Binduo Xu, Chongliang Zhang, Yiping Ren, Ying Xue, Lili Xu. Optimization of environmental variables in habitat suitability modeling for mantis shrimp Oratosquilla oratoria in the Haizhou Bay and adjacent waters[J]. Acta Oceanologica Sinica, 2020, 39(6): 36-47. doi: 10.1007/s13131-020-1546-8

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Optimization of environmental variables in habitat suitability modeling for mantis shrimp Oratosquilla oratoria in the Haizhou Bay and adjacent waters

doi: 10.1007/s13131-020-1546-8

1.
College of Fisheries, Ocean University of China, Qingdao 266003, China
2.
Laboratory for Marine Fisheries Science and Food Production Processes, Pilot National Laboratory for Marine Science and Technology (Qingdao), Qingdao 266237, China
3.
College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao 266100, China
4.
Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China

Funds: The National Key R&D Program of China under contract No. 2017YFE0104400; the National Natural Science Foundation of China under contract No. 31772852; the Marine S&T Fund of Shandong Province for Pilot National Laboratory for Marine Science and Technology (Qingdao) under contract No. 2018SDKJ0501-2.

More Information

Corresponding author: E-mail: xueying@ouc.edu.cn
Received Date: 2019-04-29
Accepted Date: 2019-07-30

Available Online: 2020-12-28

Publish Date: 2020-06-25

Abstract

Abstract

Habitat suitability index (HSI) models have been widely used to analyze the relationship between species abundance and environmental factors, and ultimately inform management of marine species. The response of species abundance to each environmental variable is different and habitat requirements may change over life history stages and seasons. Therefore, it is necessary to determine the optimal combination of environmental variables in HSI modelling. In this study, generalized additive models (GAMs) were used to determine which environmental variables to be included in the HSI models. Significant variables were retained and weighted in the HSI model according to their relative contribution (%) to the total deviation explained by the boosted regression tree (BRT). The HSI models were applied to evaluate the habitat suitability of mantis shrimp Oratosquilla oratoria in the Haizhou Bay and adjacent areas in 2011 and 2013–2017. Ontogenetic and seasonal variations in HSI models of mantis shrimp were also examined. Among the four models (non-optimized model, BRT informed HSI model, GAM informed HSI model, and both BRT and GAM informed HSI model), both BRT and GAM informed HSI model showed the best performance. Four environmental variables (bottom temperature, depth, distance offshore and sediment type) were selected in the HSI models for four groups (spring-juvenile, spring-adult, fall-juvenile and fall-adult) of mantis shrimp. The distribution of habitat suitability showed similar patterns between juveniles and adults, but obvious seasonal variations were observed. This study suggests that the process of optimizing environmental variables in HSI models improves the performance of HSI models, and this optimization strategy could be extended to other marine organisms to enhance the understanding of the habitat suitability of target species.
- habitat suitability index,
- mantis shrimp,
- generalized additive model,
- boosted regression tree,
- Haizhou Bay

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References(80)

References

[1]	Ahmadi-Nedushan B, St-Hilaire A, Bérubé M, et al. 2006. A review of statistical methods for the evaluation of aquatic habitat suitability for instream flow assessment. River Research & Applications, 22(5): 503–523
[2]	Akaike H. 1998. Information theory and an extension of the maximum likelihood principle. In: Parzen E, Tanabe K, Kitagawa G, eds. Selected Papers of Hirotugu Akaike. New York: Springer, 199–213
[3]	Becker E A, Forney K A, Ferguson M C, et al. 2010. Comparing California current cetacean-habitat models developed using in situ and remotely sensed sea surface temperature data. Marine Ecology Progress Series, 413: 163–183. doi: 10.3354/meps08696
[4]	Brooks R P. 1997. Improving habitat suitability index models. Wildlife Society Bulletin, 25(1): 163–167
[5]	Brown S K, Buja K R, Jury S H, et al. 2000. Habitat suitability index models for eight fish and invertebrate species in Casco and Sheepscot Bays, Maine. North American Journal of Fisheries Management, 20(2): 408–435. doi: 10.1577/1548-8675(2000)020<0408:HSIMFE>2.3.CO;2
[6]	Chang J H, Chen Yong, Holland D, et al. 2010. Estimating spatial distribution of American lobster Homarus americanus using habitat variables. Marine Ecology Progress Series, 420: 145–156. doi: 10.3354/meps08849
[7]	Chang Y J, Sun Chilu, Chen Yong, et al. 2012. Habitat suitability analysis and identification of potential fishing grounds for swordfish, Xiphias gladius, in the South Atlantic Ocean. International Journal of Remote Sensing, 33(23): 7523–7541. doi: 10.1080/01431161.2012.685980
[8]	Chen Lingzhi. 1993. China’s Biodiversity: Current Status and Protection Countermeasures (in Chinese). Beijing: Science Press
[9]	Chen Xinjun. 2004. Fishery Resources and Fishing Grounds (in Chinese). Beijing: China Ocean Press
[10]	Chen Xinjun, Feng Bo, Xu Liuxiong. 2008. A comparative study on habitat suitability index of bigeye tuna, Thunnus obesus in the Indian Ocean. Journal of Fishery Sciences of China (in Chinese), 15(2): 269–278
[11]	Chen Changsheng, Gao Guoping, Zhang Yu, et al. 2016. Circulation in the Arctic Ocean: Results from a high-resolution coupled ice-sea nested Global-FVCOM and Arctic-FVCOM system. Progress in Oceanography, 141: 60–80.
[12]	Chen Xinjun, Tian Siquan, Chen Yong, et al. 2010. A modeling approach to identify optimal habitat and suitable fishing grounds for neon flying squid (Ommastrephes bartramii) in the Northwest Pacific Ocean. Fisheries Bulletin, 108(1): 1–14 doi: 10.1016/j.pocean.2015.12.002
[13]	Chen Xinjun, Tian Siquan, Liu Bilin, et al. 2011. Modeling a habitat suitability index for the eastern fall cohort of Ommastrephes bartramii in the central North Pacific Ocean. Chinese Journal of Oceanology and Limnology, 29(3): 493–504. doi: 10.1007/s00343-011-0058-y
[14]	Compton T J, Morrison M A, Leathwick J R, et al. 2012. Ontogenetic habitat associations of a demersal fish species, Pagrus auratus, identified using boosted regression trees. Marine Ecology Progress Series, 462(8): 219–230
[15]	Cormon X, Loots C, Vaz S, et al. 2014. Spatial interactions between saithe (Pollachius virens) and hake (Merluccius merluccius) in the North Sea. ICES Journal of Marine Science, 71(6): 1342–1355. doi: 10.1093/icesjms/fsu120
[16]	Deng Jingyao, Zhu Jinsheng, Cheng Jisheng, et al. 1988. Fishery biology of the economic invertebrates in the Bohai Sea. Marine Fisheries Research (in Chinese), (9): 91–120
[17]	Du Nanshan. 1993. Crustacean (in Chinese). Beijing: Science Press
[18]	Elith J, Leathwick J R, Hastie T. 2008. A working guide to boosted regression trees. Journal of Animal Ecology, 77(4): 802–813. doi: 10.1111/j.1365-2656.2008.01390.x
[19]	Fox J Jr, Weisberg S. 2019. An R Companion to Applied Regression. 3rd ed. Thousand Oaks CA: SAGE
[20]	Friedman J H, Meulman J J. 2003. Multiple additive regression trees with application in epidemiology. Statistics in Medicine, 22(9): 1365–1381. doi: 10.1002/sim.1501
[21]	Gao Feng, Chen Xinjun, Guan Wenjiang, et al. 2015. Fishing ground forecasting of chub mackerel in the Yellow Sea and East China Sea using boosted regression trees. Haiyang Xuebao (in Chinese), 37(10): 39–48
[22]	Gong Caixia, Chen Xinjun, Gao Feng, et al. 2011. Review on habitat suitability index in fishery science. Journal of Shanghai Ocean University (in Chinese), 20(2): 260–269
[23]	Gong Caixia, Chen Xinjun, Gao Feng, et al. 2012. Importance of weighting for multi-variable habitat suitability index model: A case study of winter-spring cohort of Ommastrephes bartramii in the Northwestern Pacific Ocean. Journal of Ocean University of China, 11(2): 241–248. doi: 10.1007/s11802-012-1898-6
[24]	Hamano T, Matsuura S. 1984. Egg laying and egg mass nursing behaviour in the Japanese mantis shrimp. Nippon Suisan Gakkaishi, 50: 1969–1973. doi: 10.2331/suisan.50.1969
[25]	Hastie T J, Tibshirani R J. 1990. Generalized Additive Models. London: Chapman & Hall
[26]	Hastie T, Tibshirani R, Friedman J. 2001. The Elements of Statistical Learning: Data Mining, Inference, and Prediction. New York: Springer
[27]	Huang Zongguo. 2008. Marine Species and Their Distribution in China (in Chinese). Beijing: China Ocean Press
[28]	Johnson A F, Jenkins S R, Hiddink J G, et al. 2013. Linking temperate demersal fish species to habitat: scales, patterns and future directions. Fish & Fisheries, 14(3): 256–280
[29]	Kabacoff R. 2015. R in Action: Data Analysis and Graphics with R. 2nd ed. New York: Manning Publications Co
[30]	Leathwick J R, Elith J, Hastie T. 2006. Comparative performance of generalized additive models and multivariate adaptive regression splines for statistical modelling of species distributions. Ecological Modelling, 199(2): 188–196. doi: 10.1016/j.ecolmodel.2006.05.022
[31]	Lewin W C, Mehner T, Ritterbusch D, et al. 2014. The influence of anthropogenic shoreline changes on the littoral abundance of fish species in German lowland lakes varying in depth as determined by boosted regression trees. Hydrobiologia, 724(1): 293–306. doi: 10.1007/s10750-013-1746-8
[32]	Li Guangxue, Li Ping, Liu Yong, et al. 2014. Sedimentary system response to the global sea level change in the East China Seas since the last glacial maximum. Earth-Science Reviews, 139: 390–405. doi: 10.1016/j.earscirev.2014.09.007
[33]	Li Bai, Tanaka K R, Chen Yong, et al. 2017. Assessing the quality of bottom water temperatures from the Finite-Volume Community Ocean Model (FVCOM) in the Northwest Atlantic Shelf region. Journal of Marine Systems, 173: 21–30. doi: 10.1016/j.jmarsys.2017.04.001
[34]	Liang Jie, Hua Shanshan, Zeng Guangming, et al. 2015. Application of weight method based on canonical correspondence analysis for assessment of Anatidae habitat suitability: A case study in East Dongting Lake, Middle China. Ecological Engineering, 77: 119–126. doi: 10.1016/j.ecoleng.2015.01.016
[35]	Liu Xiuze, Guo Dong, Wang Aiyong, et al. 2014. The resource characteristics and their variation of Oratosquilla oratoria in Liaodong Bay. Acta Hydrobiologica Sinica (in Chinese), 38(3): 602–608
[36]	Liu Xiaoxiao, Wang Jing, Zhang Yunlei, et al. 2019. Comparison between two GAMs in quantifying the spatial distribution of Hexagrammos otakii in Haizhou Bay, China. Fisheries Research, 218: 209–217. doi: 10.1016/j.fishres.2019.05.019
[37]	Liu Haiying, Xu Hailong, Lin Yuejiao. 2006. The effect of salinity on survival and growth of mantis shrimp (Oratosquilla oratoria) in Dalian coast. Journal of Dalian Fisheries University (in Chinese), 21(2): 180–183
[38]	Luan Jing, Zhang Chongliang, Xu Binduo, et al. 2018. Modelling the spatial distribution of three Portunidae crabs in Haizhou Bay, China. PLoS One, 13: e0207457. doi: 10.1371/journal.pone.0207457
[39]	Morrison M L, Marcot B C, Mannan R W. 2006. Wildlife-Habitat Relationships: Concepts and Applications. 3rd ed. Washington: Island Press
[40]	Ohtiomi J, Shimizu M, Vergara J A M. 1988. Spawning season of the Japanese mantis shrimp Oratosquilla oratoria in Tokyo Bay. Nippon Suisan Gakkaishi, 54(11): 1929–1933. doi: 10.2331/suisan.54.1929
[41]	Pang Zhiwei, Xu Binduo, Zan Xiaoxiao, et al. 2015. Shrimp community structure and its relationships with environmental factors in Haizhou Bay and adjacent waters in spring. Acta Ecologica Sinica, 35(6): 191–195. doi: 10.1016/j.chnaes.2015.09.005
[42]	Pikitch E K, Santora C, Babcock E A, et al. 2004. Ecosystem-based fishery management. Science, 305(5682): 346–347. doi: 10.1126/science.1098222
[43]	Planque B, Loots C, Petitgas P, et al. 2011. Understanding what controls the spatial distribution of fish populations using a multi-model approach. Fisheries Oceanography, 20(1): 1–17. doi: 10.1111/j.1365-2419.2010.00546.x
[44]	Ptacnik R, Lepistö L, Willén E, et al. 2008. Quantitative responses of lake phytoplankton to eutrophication in Northern Europe. Aquatic Ecology, 42(2): 227–236. doi: 10.1007/s10452-008-9181-z
[45]	Ridgeway G. 2015. gbm: Generalized boosted regression models. R package version 2. 1. 1. https://CRAN.R-project.org/package=gbm [2015-03-11/2017-02-14]
[46]	Schmiing M, Afonso P, Tempera F, et al. 2013. Predictive habitat modelling of reef fishes with contrasting trophic ecologies. Marine Ecology-Progress Series, 474: 201–216. doi: 10.3354/meps10099
[47]	Shen Guoying, Huang Lingfeng, Guo Feng, et al. 2010. Marine Ecology (in Chinese). 3rd ed. Beijing: Science Press
[48]	Shi Qiang. 2019. Climate response and spatio-temporal modes on the interannual variation of summer temperature-salinity in the South Yellow Sea. Journal of Applied Oceanography (in Chinese), 38(2): 24–36
[49]	Smith P A. 1994. Autocorrelation in logistic regression modelling of species’ distributions. Global Ecology & Biogeography Letters, 4(2): 47–61
[50]	Su Jilan, Huang Daji. 1995. On the current field associated with the yellow sea cold water mass. Oceanologia et Limnologia Sinica (in Chinese), 26(S1): 1–7
[51]	Su Wei, Xue Ying, Zhang Chongliang, et al. 2015. Spatio-seasonal patterns of fish diversity, Haizhou Bay, China. Chinese Journal of Oceanology and Limnology, 33(1): 121–134. doi: 10.1007/s00343-015-3311-y
[52]	Tanaka K, Chen Yong. 2015. Spatiotemporal variability of suitable habitat for American Lobster (Homarus americanus) in Long Island Sound. Journal of Shellfish Research, 34(2): 531–543. doi: 10.2983/035.034.0238
[53]	Tanaka K, Chen Yong. 2016. Modeling spatiotemporal variability of the bioclimate envelope of Homarus americanus in the coastal waters of Maine and New Hampshire. Fisheries Research, 177: 137–152. doi: 10.1016/j.fishres.2016.01.010
[54]	Tang Fenghua, Shen Xingqiang, Wang Yunlong. 2011. Dynamics of fisheries resources near Haizhou Bay waters. Fisheries Science (in Chinese), 30(6): 335–341
[55]	Tang Qisheng, Ye Maozhong. 1990. Development and Protection of Fisheries Resources in Shandong Offshore (in Chinese). Beijing: China Agriculture Press
[56]	Tian Siquan, Chen Xinjun, Chen Yong, et al. 2009. Evaluating habitat suitability indices derived from CPUE and fishing effort data for Ommatrephes bratramii in the northwestern Pacific Ocean. Fisheries Research, 95(2–3): 181–188. doi: 10.1016/j.fishres.2008.08.012
[57]	Torres L G, Sutton P J H, Thompson D R, et al. 2015. Poor transferability of species distribution models for a pelagic predator, the Grey Petrel, indicates contrasting habitat preferences across ocean basins. PLoS One, 10(3): e0120014. doi: 10.1371/journal.pone.0120014
[58]	Valavanis V D, Georgakarakos S, Kapantagakis A, et al. 2004. A GIS environmental modelling approach to essential fish habitat designation. Ecological Modelling, 178(3–4): 417–427. doi: 10.1016/j.ecolmodel.2004.02.015
[59]	Vayghan A H, Poorbagher H, Shahraiyni H T, et al. 2013. Suitability indices and habitat suitability index model of Caspian kutum (Rutilus frisii kutum) in the southern Caspian Sea. Aquatic Ecology, 47(4): 441–451. doi: 10.1007/s10452-013-9457-9
[60]	Vinagre C, Fonseca V, Cabral H, et al. 2006. Habitat suitability index models for the juvenile soles, Solea solea and Solea senegalensis, in the Tagus estuary: defining variables for species management. Fisheries Research, 82(1–3): 140–149. doi: 10.1016/j.fishres.2006.07.011
[61]	Vincenzi S, Caramori G, Rossi R, et al. 2007. A comparative analysis of three habitat suitability models for commercial yield estimation of Tapes philippinarum in a North Adriatic coastal lagoon (Sacca di Goro, Italy). Marine Pollution Bulletin, 55(10-12): 579–590. doi: 10.1016/j.marpolbul.2007.09.016
[62]	Wakeley J S. 1988. A method to create simplified versions of existing habitat suitability index (HSI) models. Environmental Management, 12(1): 79–83. doi: 10.1007/BF01867379
[63]	Wang Chunlin, Xu Shanliang, Mei Wenxiang, et al. 1996a. A biological basic character of Oratosquilla oratoria. Journal of Zhejiang College of Fisheries (in Chinese), 15(1): 60–62
[64]	Wang Chunling, Xu Shanliang, Mei Wenxiang, et al. 1996b. Preliminary observations on appendage morphology and living behaviors of Oratosquilla oratoria. Journal of Zhejiang College of Fisheries (in Chinese), 15(1): 9–14
[65]	Wang Bo, Zhang Xilie, Sun Pixi. 1998. On biological characters and artificial seedling rearing techniques of mantis shrimp (Oratosquilla oratoria). Journal of Oceanograpgy of Huanghai & Bohai Seas (in Chinese), 16(2): 64–72
[66]	Wu Qiang, Chen Ruisheng, Huang Jingxian, et al. 2015. Fishery biology characteristics, temporal and spatial distribution of Oratosquilla oratoria in Laizhou Bay, Bohai Sea. Journal of Fisheries of China (in Chinese), 39(8): 1166–1177
[67]	Xu Shanliang, Wang Chunlin, Mei Wenxiang, et al. 1996. Preliminary studies on propagation and feeding habits of Oratosquilla oratoria in Northern Zhejiang sea areas. Journal of Zhejiang College of Fisheries (in Chinese), 15(1): 30–36
[68]	Xu Lili, Xue Ying, Jiao Yan, et al. 2017. Population structure and spatial distribution of Oratosquilla oratoria in Haizhou Bay and adjacent waters. Periodical of Ocean University of China (in Chinese), 47(4): 28–36
[69]	Xu Binduo, Zhang Chongliang, Xue Ying, et al. 2015. Optimization of sampling effort for a fishery-independent survey with multiple goals. Environmental Monitoring & Assessment, 187: 252
[70]	Xue Ying, Guan Lisha, Tanaka K, et al. 2017. Evaluating effects of rescaling and weighting data on habitat suitability modeling. Fisheries Research, 188: 84–94. doi: 10.1016/j.fishres.2016.12.001
[71]	Xue Ying, Tanaka K, Yu Huaming, et al. 2018. Using a new framework of two-phase generalized additive models to incorporate prey abundance in spatial distribution models of juvenile slender lizardfish in Haizhou Bay, China. Marine Biology Research, 14(5): 508–523. doi: 10.1080/17451000.2018.1447673
[72]	Yi Yujun, Sun Jie, Zhang Shanghong. 2016. A habitat suitability model for Chinese sturgeon determined using the generalized additive method. Journal of Hydrology, 534: 11–18. doi: 10.1016/j.jhydrol.2015.12.055
[73]	Yu Wei, Chen Xinjun, Zhang Yang. 2019. Seasonal habitat patterns of jumbo flying squid Dosidicus gigas off Peruvian waters. Journal of Marine Systems, 194: 41–51. doi: 10.1016/j.jmarsys.2019.02.011
[74]	Yu Wei, Guo Ai, Zhang Yang, et al. 2018. Climate-induced habitat suitability variations of chub mackerel Scomber japonicus in the East China Sea. Fisheries Research, 207: 63–73. doi: 10.1016/j.fishres.2018.06.007
[75]	Yu Wei, Yi Qian, Chen Xinjun, et al. 2016. Modelling the effects of climate variability on habitat suitability of jumbo flying squid, Dosidicus gigas, in the Southeast Pacific Ocean off Peru. ICES Journal of Marine Science, 73(2): 239–249. doi: 10.1093/icesjms/fsv223
[76]	Zeng Yiwen, Yeo D C J. 2018. Assessing the aggregated risk of invasive crayfish and climate change to freshwater crabs: A Southeast Asian case study. Biological Conservation, 223: 58–67. doi: 10.1016/j.biocon.2018.04.033
[77]	Zhang Rui, Zhang Fan, Zhang Tiancheng, et al. 2014. Historical sediment record and distribution of polychlorinated biphenyls (PCBs) in sediments from tidal flats of Haizhou Bay, China. Marine Pollution Bulletin, 89(1–2): 487–493. doi: 10.1016/j.marpolbul.2014.09.001
[78]	Zhao Baoren, Tu Dengzhi, Bi Yawen. 1992. Multi-year variations of the tidal front in the section 34˚N on the continental shelf of the western yellow sea and numeric model of the circulations in the section across the front. Marine Sciences (in Chinese), (2): 41–45
[79]	Zou Yiyang, Xue Ying, Ma Qiuyun, et al. 2016. Spatial distribution of Larimichthys Polyactis in Haizhou Bay based on habitat suitability index. Periodical of Ocean University of China (in Chinese), 46(8): 54–63
[80]	Zuur A, Ieno E N, Smith G M. 2007. Analyzing Ecological Data. New York: Springer