ALGORITHM SCREENING AND EVALUATION OF HABITAT SUITABILITY INDEX FOR GLYPTOTHORAX SINENSE IN THE HEISHUI RIVER
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摘要:
为研究中华纹胸鮡(Glyptothorax sinensis)栖息地适宜性指数(Habitat suitability index, HSI)模型最优算法, 科学评估其适宜栖息地分布, 基于2018—2019年黑水河中华纹胸鮡渔获物数据及同步采集的13个环境因子, 采用一元非线性函数拟合构建单个环境因子SI曲线, 并结合最大值法(Maximum, MAX)、最小值法(Minimum, MIN)、算术平均法(Arithmetic mean model, AMM)、几何平均法(Geometric mean model, GMM)、加权平均法(Weighted moving average, WMA)分别计算中华纹胸鮡HSI值。计算结果表明: 在各模型算法中, 算术平均法和加权平均法两种方法的预测结果误差最小, 最大值法与最小值法的预测结果与中华纹胸鮡实际分布偏差较大, 在进行算法选择时要慎重考虑。黑水河中华纹胸鮡栖息地适宜性指数总体呈现上游至下游纵向上升趋势, HSI值大于0.7的点位为下游自然河段S3和S4。水温、海拔等物理环境是驱动中华纹胸鮡栖息地空间分布差异的主要因素。算术平均法及加权平均法为黑水河中华纹胸鮡栖息地适宜性指数模型预测最优算法。研究结果可为黑水河鱼类栖息地评估提供参考资料, 促进鱼类栖息地保护。
Abstract:Habitat assessment is a prerequisite for in-situ conservation of fish, and appropriate model algorithms is an important basis for improving the prediction accuracy of habitat assessment models. This study aims to identify the optimal algorithm for the habitat suitability index (HSI) model of Glyptothorax sinensis and to scientifically evaluate its suitable habitat distribution. We utilized fishery catch data and 13 environmental factors collected synchronously from the Heishui River from 2018 to 2019. A one-dimensional nonlinear function was employed to fit a single environmental factor curve, and HSI values of G. sinensis were calculated using the maximum value method, minimum value method, arithmetic mean model, geometric mean model, and weighted moving average. The results indicate that among the various model algorithms, the arithmetic mean model and weighted moving average model exhibited the smallest prediction error, while the maximum and minimum value method showed significant prediction error and deviated notably from the actual distribution of G. sinensis. Therefore, caution should be taken when choosing model algorithms. Overall, the HSI index of G. sinensis in the Heishui River shows an upward trend from the upstream to the downstream, with sections S3 and S4 exhibiting HSI values greater than 0.7. Water temperature and elevation are the main driving factors for the spatial distribution differences in G. sinensis habitat. The arithmetic mean model and weighted moving average model are identified as the optimal algorithm for predicting the habitat suitability index of G. sinensis in the Heishui River. The research results can provide reference for the assessment of fish habitats in the Heishui River and promote the protection of fish habitats.
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Keywords:
- Habitat suitability index /
- Optimal algorithm /
- Heishui River /
- Glyptothorax sinensis
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图 1 黑水河中华纹胸鮡及生境因子采样点分布示意图
Figure 1. Distribution of sampling sites for G. sinensis and habitat factors in Heishui River
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图 2 黑水河中华纹胸鮡环境因子特征权重值
Figure 2. Characteristic weights of environmental factors for G. sinensis in Heishui River
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图 3 黑水河水温、流速、海拔、浊度、溶氧、电导率适宜性曲线(横实线代表SI>0.7, 为生境因子适宜范围)
Figure 3. Suitability curves of water temperature, velocity, elevation, turbidity, dissolved oxygen, and conductivity of Heishui River (The horizontal solid line represents SI>0.7, which is the appropriate range of habitat factor)
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图 4 中华纹胸鮡HSI算术平均法预测结果验证
Figure 4. Verification of prediction results for G. sinensis by HSI arithmetic mean method
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图 5 黑水河中华纹胸鮡HSI算术平均法预测分布图
Figure 5. Distribution map of G. sinensis from Heishui River by HSI weighted average method
表 1 黑水河环境因子与中华纹胸鮡RAD值相关性分析
Table 1 Correlation analysis between environmental factors and G. sinensis RAD value in Heishui River
环境因子
Environmental factor相关系数
Correlation coefficient环境因子
Environmental factor相关系数
Correlation coefficient溶解氧Dissolved oxygen (mg/L) –0.46* 电导率Conductivity (s/m) 0.85** 水温Water temperature (℃) 0.88** 悬浮物Suspended solids (mg/L) 0.28 透明度Transparency (m) 0.05 化学需氧量Chemical oxygen demand (mg/L) –0.04 流速Velocity of flow (m/s) –0.76** 总磷Phosphorus (mg/L) –0.14 水深Water depth (m) –0.37 氨氮Ammonia nitrogen (mg/L) 0.08 海拔Altitude (m) –0.87** 浊度Turbidity (ntu) –0.50* 叶绿素a Chlorophyll a –0.26 注: * 表示P<0.05存在显著性相关; ** 表示P<0.01存在极显著相关; 下同Note: * indicates significant correlation with P<0.05; ** indicates extremely significant correlation with P<0.01; the same applies below 
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表 2 黑水河中华纹胸鮡环境因子拟合函数
Table 2 Environmental factor fitting function of G. sinensis in Heishui River
环境因子Environmental factor 适宜性指数模型Suitability index model P值P-value 水温Water temperature (℃) y=−0.14+1.86×e(−0.5*[(Tem−20.01)/2.1])^2 **P<0.01 流速Velocity of flow (m/s) y=0.02+0.96×e(−0.5*[(Vel−0.42)/0.06])^2 *P<0.05 海拔Altitude (m) y=0.02+1×e(−0.5*[(Alt−723)/73])^2 **P<0.01 浊度Turbidity (ntu) y=0.06+0.91×e(−0.5*[(Tur−56.36)/6.15])^2 *P<0.05 溶解氧Dissolved oxygen (mg/L) y=0.09+0.8×e(−0.5*[(Dis−9.04)/0.12])^2 **P<0.01 电导率Conductivity (s/m) y=0.02+0.82×e(−0.5*[(Con−316.9)/14.27])^2 **P<0.01
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表 3 黑水河环境因子及SI曲线预测适宜范围
Table 3 Suitable range for predicting environmental factors and SI curve of Heishui River
环境因子
Environmental factor最小值
Min最大值
Max平均值±标准差
mean±SD预测适宜范围
Scope of suitability水温 Water temperature (℃) 14.88 17.85 16.37±0.73 17.44—17.85 流速 Flow rate (m/s) 0.33 1.20 0.55±0.27 0.36—0.47 海拔 Altitude (m) 617 1134 834.00±190.94 659—788 浊度 Turbidity (ntu) 41.20 159.74 81.71±43.80 50.57—57.21 溶氧 Dissolved oxygen (mg/L) 8.76 9.93 9.31±0.38 8.96—9.12 电导率 Conductivity (m/s) 203.33 335.50 291.24±38.44 307.85—324.96
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表 4 黑水河中华纹胸鮡五种HSI模型算法预测精度
Table 4 Prediction accuracy of five HSI model algorithms for G. chinensis from Heishuihe River
算法
AlgorithmR2 AIC值
AIC value均方根误差
RMSEP值
P-valueMax 0.70 –4.31 0.18 **P<0.01 Min 0.63 –1.12 0.20 **P<0.01 AMM 0.87 –15.98 0.12 **P<0.01 GMM 0.79 –9.03 0.15 **P<0.01 WAM 0.86 –15.22 0.12 **P<0.01
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