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( Sebastes Schlegelii ) Under Changing Climate

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( Sebastes Schlegelii ) Under Changing Climate Ecological Indicators 128 (2021) 107799 Contents lists available at ScienceDirect Ecological Indicators journal homepage: www.elsevier.com/locate/ecolind Predicting current and future global distribution of black rockfish( Sebastes schlegelii) under changing climate Yunlong Chen a,b, Xiujuan Shan a,b, Daniel Ovando c, Tao Yang a,b, Fangqun Dai a,b, Xianshi Jin a,b,* a Key Laboratory of Sustainable Development of Marine Fisheries, Ministry of Agriculture and Rural affairs, Shandong Provincial Key Laboratory of Fishery Resources and Ecological Environment, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao 266071, PR China b Function Laboratory for Marine Fisheries Science and Food Production Processes, Pilot National Laboratory for Marine Science and Technology (Qingdao), Qingdao 266100, PR China c School of Aquatic and Fishery Sciences, University of Washington, Seattle, WA 98195, USA ARTICLE INFO ABSTRACT Keywords: Changes in the marine environment, particularly climate change, can have large effects on the distribution Habitat suitability patterns of various marine species, and alter the biodiversity, structure and functions of the affected ecosystems. Demersal fish Species distribution models (SDM) are tools often used to link species’ ecological niches with their environment. Species distribution models We applied SDM to investigate the effects of fivebiologically relevant climatic variables from multiple databases, Multi-model ensemble techniques including bottom temperature, bottom salinity, current velocity, depth and primary productivity, on habitat suitability of Sebastes schlegelii in the marine waters of China, Korea and Japan. Nine individual SDM and an ensemble model were used to predict the current and future distribution of S. schlegelii under alternative climate change scenarios (Representative Concentration Pathways, RCP). Results indicated that the ensemble model produced more accurate projections than any individual model. Among the environmental variables investi­ gated, bottom temperature was the most important in determining the range of S. schlegelii. Its current distri­ bution demonstrated that suitable habitat for S. schlegelii was mostly concentrated in the Bohai Sea, coastal areas of the central and northern Yellow Sea, and in the Sea of Japan. Negative effects from climate change on the distribution patterns of S. schlegelii were predicted to lead to varying degrees of habitat reduction, with highest estimate of 45% occurring under RCP8.5 at the end of 2100. Our results illustrate the potential effects of climate change on the future distribution of S. schlegelii populations and can assist with implementing adaptive man­ agement measures of this species. 1. Introduction to implementing effective conservation and resource management strategies (Melo-Merino et al., 2020). Changes in the marine environment, particularly climate change, are Species distribution models (SDM) provide an approach to assess expected to affect the distribution patterns of many marine species, and climatically generated impacts by linking species occurrence records to alter the biodiversity, structure and functions of their ecosystems. with environmental variables and estimating the potential effects under (Hazen et al., 2013; Becker et al., 2019). Marine species are expected to plausible future scenarios (Briscoe et al., 2019). SDM have been con­ shift their spatial and temporal distributions in response to changing structed from bioclimatic envelope models, generalized linear models environmental conditions (Hollowed et al., 2013). Tropical regions, (GLM) and machine learning methods such as generalized boosting semi-enclosed seas, and sub-polar areas may experience more loss of models (GBM) and random forests (RF, Hao et al., 2019). SDM can help local populations, whilst polar areas may have more species invasion with understanding species population distributions and provide valu­ issues (Cheung et al., 2009). Acquiring a comprehensive and accurate able implications due to their potential applicability to different spatial understanding of current species distributions and providing reliable resolutions, and available data sources, even for seldom studied species predictions under future environmental change scenarios, are important (Melo-Merino et al., 2020). Ensemble modeling has been increasingly * Corresponding author at: Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao 266071, PR China. E-mail address: [email protected] (X. Jin). https://doi.org/10.1016/j.ecolind.2021.107799 Received 16 November 2020; Received in revised form 6 May 2021; Accepted 8 May 2021 Available online 2 June 2021 1470-160X/© 2021 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Y. Chen et al. Ecological Indicators 128 (2021) 107799 explored as a way to integrate the strengths of different individual SDM distribution, and to evaluate the expected changes in suitable habitat (Bevan et al., 2019; Hao et al., 2020). By combining models with over mid-term (2050) and long-term (2100) periods situated under four different assumptions and algorithms, ensemble models are capable of Representative Concentration Pathways (RCP, van Vuuren et al., 2011). providing more robust results than individual models (Zhang et al., This study provides insights about the potential effects of climate change 2019). on the distribution of S. schlegelii populations and can assist the devel­ At present, SDM studies on marine species influenced by climate opment of adaptive strategies for managing this resource. change are mostly focused on pelagic species, especially in tropical and polar areas (Wisz et al., 2015; Erauskin-Extramiana et al., 2019; 2. Materials and methods Schickele et al., 2020). The extent to which demersal species inhabiting temperate regions are affected by climate changes is less commonly 2.1. Study areas and data sources considered (Fredston-Hermann et al., 2020). The black rockfishSebastes schlegelii (class Actinopterygii, order Scorpaeniformes, family Scorpae­ 2.1.1. Study areas nidae) provides a typical example for exploring such issues. It is a Our study area spans the coastal waters adjacent to Japan, Korea, demersal fishwidely distributed in the northwest Pacificalong the coast China and Russia, encompassing the Sea of Japan, the Bohai Sea, the ◦ ◦ of China, Japan and the Korean Peninsula (Wang et al., 2017), and Yellow Sea and the northern region of the East China Sea (28 to 50 N; ◦ ◦ characterized by strong adult site fidelityand a preference for rocky reef, 115 to 150 E, Fig. 1). silt and sand habitat (Zhang et al., 2015). The species usually matures at the of age 3 years with an ovoviviparous reproduction mode (Chin et al., 2.1.2. Presence/absence data of S. Schlegelii 2013; Xu et al., 2019). S. schlegelii is carnivorous, mainly feeding on Global presence/absence data of S. schlegelii were collected and shrimps and fishes and has strong initiative in prey selectivity (Chin merged from three sources: the Global Biodiversity Information Facility et al., 2013; Zhang et al., 2014). As to the status of the S. schlegelii (GBIF, https://www.gbif.org/), the Ocean Biodiversity Information resource in the Yellow Sea, mean individual weight and catch per unit of System (OBIS, https://obis.org/) and systematic fishery surveys con­ effort were both reported to have declined during the last thirty years ducted by the Yellow Sea Fisheries Research Institute, Chinese Academy (Xu and Jin, 2005; Chen et al., 2018). Due to its high economic and of Fishery Sciences in 2016. A total of 563 occurrence records (presence- recreational value, S. schlegelii has been considered as an important only) were obtained from GBIF and OBIS, and 438 high-quality site- target species for stock enhancement programs in China, Japan and occupancy data (presence and absence) were obtained from fishery Korea (Kim et al., 2001; Chin et al., 2013; Wang et al., 2017). Current surveys during all four seasons in 2016. Sites in which S. schlegelii studies of S. schlegelii largely focus on growth, behavior, physiology, occurred at least once were regarded as present, whereas those with no immunity and population genetics (Zhang et al., 2015; Kim and Kang, recorded observations were treated as absent. Overall, occurrence data 2016; Wang et al., 2017; Yin et al., 2018), however, a large scale study of S. schlegelii retrieved from the data sources for our study ranged from focusing on availability of suitable habitat and associated future popu­ the years 1883 to 2018, recent records (since 1990) accounted for 74.5% lation distributions under changing climatic conditions is lacking for (746) of the total observations compared with past (1883–1990) records S. schlegelii. Research on demersal fish like S. schlegelii can help to representing 9.9%, and undated observations 15.6%. Eighty-eight per identify and more comprehensively understand the potential impacts of cent of the records among past and undated observations did not have climate change on fish communities and their ecosystems. longitude and latitude recorded. Due to these limitations, we took a Here, using data sourced from multiple databases, our study presents precautionary approach to narrow down the number of presence/ the firstlarge scale biogeographic study of S. schlegelii analyzed by SDM, absence sites to guaranteed data quality by the following selection
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