海州湾鹰爪虾栖息地适宜性研究

陈艺璇; 张云雷; 黄锘妍; 郭笳; 陈皖; 任一平; 薛莹

doi:10.12284/hyxb2021044

海州湾鹰爪虾栖息地适宜性研究

doi: 10.12284/hyxb2021044

陈艺璇^1,,
张云雷¹,
黄锘妍¹,
郭笳¹,
陈皖¹,
任一平^{1, 2, 3},
薛莹^{1, 3, ,}

1.
中国海洋大学水产学院，山东青岛 266003
2.
青岛海洋科学与技术试点国家实验室海洋渔业科学与食物产出过程功能实验室，山东青岛 266237
3.
海州湾渔业生态系统教育部野外科学观测研究站，山东青岛 266003

基金项目: 青岛海洋科学与技术试点国家实验室重大科技专项（2018 SDKJ0501-2）；国家自然科学基金（31772852）；国家重点研发计划（2018YFD0900904）。

详细信息

作者简介:
陈艺璇（1998—），女，山东省泰安市人，研究方向为海洋资源与环境。E-mail：1209312126@qq.com

通讯作者:
薛莹，教授。E-mail：xueying@ouc.edu.cn

中图分类号: S931.4
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- 文章访问数: 212
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- 被引次数: 0
出版历程
- 收稿日期: 2020-03-30
- 修回日期: 2020-11-30
- 网络出版日期: 2021-03-09
- 刊出日期: 2021-04-01

Study on the habitat suitability of Trachypenaeus curvirostris in the Haizhou Bay

Chen Yixuan^1
,,
Zhang Yunlei¹,
Huang Nuoyan¹,
Guo Jia¹,
Chen Wan¹,
Ren Yiping^{1, 2, 3},
Xue Ying^{1, 3
, ,}

1.
Fisheries College, 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.
Field Observation and Research Station of Haizhou Bay Fishery Ecosystem, Ministry of Education, Qingdao 266003, China

摘要

摘要: 根据2011年及2013−2017年春季和秋季在海州湾进行的底拖网调查数据，结合同步测定的底层水温、底层盐度、水深和资源量等数据，开展鹰爪虾(Trachypenaeus curvirostris)栖息地适宜性的研究，先利用广义加性模型对环境因子进行筛选，再应用提升回归树模型确定各环境因子的权重，然后分别采用算术平均法和几何平均法建立栖息地适宜性指数模型，并通过交叉验证选择最优模型。结果表明：春季鹰爪虾的栖息地适宜性指数模型采用算术平均法构建，选择水深和底层盐度作为变量，具有最小的拟合；秋季鹰爪虾的栖息地适宜性指数模型采用几何平均法构建，选择底层水温和底层盐度作为变量，具有最小的拟合。对春季栖息地适宜性指数模型总偏差贡献率最大的是水深(76.23%)，其次是底层盐度(23.77%)；对秋季栖息地适宜性指数模型总偏差贡献率最大的是底层水温(82.56%)，其次是底层盐度(17.44%)。海州湾春季鹰爪虾的最适栖息水深为24 m以内，底层盐度为29.7～31.8；秋季的最适栖息底层水温为18～24℃，底层盐度为29.2～31.5。本研究表明，环境因子的优化有助于改进栖息地适宜性指数模型，并提升其预测能力。
- 环境因子优化 /
- 栖息地适宜性指数 /
- 鹰爪虾 /
- 广义加性模型 /
- 提升回归树
Abstract: Based on the bottom-trawl survey data collected from the Haizhou Bay in spring and autumn of 2011 and 2013−2017, the habitat suitability of Trachypenaeus curvirostris was analyzed based on environmental factors such as bottom temperature, bottom salinity and water depth. Generalized additive model (GAM) was used to determine the optimal combination of environmental factors. Boosted regression tree (BRT) was used to evaluate the weight of each environmental factor in the habitat suitability index (HSI) model. The arithmetic mean model (AMM) and geometic mean model (GMM) were used to build HSI model, and the best model was selected by cross validations. Results showed that HSI model built with depth and bottom salinity in spring had the minimum AIC value, while HSI model constructed with bottom temperature and bottom salinity in autumn had the minimum AIC value. BRT model showed that the weight of depth and bottom salinity were 76.23% and 23.77% in spring, and the weight of bottom temperature and bottom salinity were 82.56% and 17.44% in autumn. The optimal range of depth and bottom salinity for T. curvirostris in spring were within 24 m and 29.7−31.8, respectively. In autumn, the optimal range of bottom temperature and bottom salinity were 18−24℃ and 29.2−31.5, respectively. This study suggested that the optimization of environmental factors was proved to be able to improve the performance of HSI models.
- optimization of environmental factors /
- habitat suitability index (HSI) /
- Trachypenaeus curvirostris /
- generalized additive model /
- boosted regression tree

HTML全文

图 1 海州湾调查区域

Fig. 1 Sampling areas in the Haizhou Bay

下载: 全尺寸图片幻灯片

图 2 海州湾春季（a1，a2）和秋季（b1，b2）鹰爪虾对底层水温、底层盐度和水深的适宜性指数曲线

断续线表示SI值为0.7

Fig. 2 Suitability index curves of bottom temperature, bottom salinity and water depth for Trachypenaeus curvirostrisin the Haizhou Bay during spring (a1, a2) and autumn (b1, b2)

Dashed lines indicate SI is 0.7

下载: 全尺寸图片幻灯片

3 2011年及2013−2017年春季和秋季海州湾鹰爪虾的HSI分布

3 Distribution of HSI of Trachypenaeus curvirostris in the Haizhou Bay during spring and autumn of 2011 and 2013−2017

下载: 全尺寸图片幻灯片

图 4 2011年及2013−2017年间春季和秋季海州湾温度和盐度的最大年间差异

a. 春季盐度最大年间差异；b. 秋季盐度最大年间差异；c. 秋季温度最大年间差异

Fig. 4 Maximum annual difference in temperature and salinity in the Haizhou Bay during spring and autumn of 2011 and 2013−2017

a. Maximum annual difference in salinity during spring; b. maximum annual difference in salinity during autumn; c. maximum annual difference in temperature during autumn

下载: 全尺寸图片幻灯片

图 5 2011年及2013−2017年春季和秋季海州湾鹰爪虾的HSI平均值分布

a. 春季HSI平均值分布图（实线为等深线）；b. 秋季HSI平均值分布图（实线为等温线）；c. 春季HSI平均值分布图（实线为等盐度线）；d. 秋季HSI平均值分布图（实线为等盐度线）

Fig. 5 Distribution of HSI average of Trachypenaeus curvirostris in the Haizhou Bay during spring and autumn of 2011 and 2013−2017

a. Distribution of HSI average during spring (solid line is the isobath line); b. distribution of HSI average during autumn (solid line is the isotherme); c. distribution of HSI average during spring (solid line is the isohaline); d. distribution of HSI average during autumn (solid line is the isohaline)

下载: 全尺寸图片幻灯片

表 1 海州湾春季和秋季基于不同环境因子组合的GAM模型检验

Tab. 1 Parameters analysis of different combinations of environmental variables by the best generalized additive models (GAMs) in the Haizhou Bay during spring and autumn

	GAM模型	AIC值	残差
春季	水深+底层盐度	535.167	932.389
	水深+底层盐度+底层水温	540.351	906.996
	水深+底层盐度+底层水温+底质类型	541.726	801.401
秋季	底层水温+底层盐度	492.621	1164.971
	底层水温+底层盐度+水深	495.437	1097.580
	底层水温+底层盐度+水深+底质类型	503.414	1024.174

下载: 导出CSV

表 2 AMM和GMM模型预测性能的比较

Tab. 2 Cross-validation of AMM and GMM algorithm in mean confidence interval

季节	AMM		GMM
季节	平均 AIC值	平均 R²	平均AIC值	平均R²
春季	−6.978	0.283	−7.185	0.287
秋季	−34.627	0.378	−34.346	0.367

下载: 导出CSV

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