黑水河中华纹胸栖息地适宜性指数算法筛选及评估

ALGORITHM SCREENING AND EVALUATION OF HABITAT SUITABILITY INDEX FOR GLYPTOTHORAX SINENSE IN THE HEISHUI RIVER

  • 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)、算数平均法(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, 算数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。算数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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