A hybrid CART-GAMs model to evaluate benthic macroinvertebrate habitat suitability in the Pearl River Estuary, China
A hybrid CART-GAMs model to evaluate benthic macroinvertebrate habitat suitability in the Pearl River Estuary, China
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DOI：
10.1016/j.ecolind.2022.109368
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发表时间：
2022-10
影响因子：
6.9
通讯作者：
Zhoubao Shen;Ying Yang;Lisha Ai;Chunxue Yu;Mei-rong Su
中科院分区：
文献类型：
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作者：
Zhoubao Shen;Ying Yang;Lisha Ai;Chunxue Yu;Mei-rong Su
底栖大型无脊椎动物是河口水生食物链的重要组成部分。因此，了解其相关的栖息地需求对于维持河口生态系统的稳定性至关重要，迄今为止一直使用栖息地适宜性评价来评估。虽然大多数基于生境适宜性指数（HSI）的方法可以确定目标物种对少数特定生境因子的偏好，但河口底栖大型无脊椎动物受到多种生境因子的影响。然而，过多的生境因子会导致数据冗余，从而降低模型效率。此外，物种与生境因子之间的非线性关系以及不同生境因子之间的相互作用往往难以评估。以前的研究并没有把重点放在同时解决这两个问题的方法上。基于此，本研究引入了CART- gams、分类回归树模型（CART）和广义加性模型（GAM）混合模型，对河口底栖大型无脊椎动物相关的多种生境因子进行适宜性评价。首先，为了去除无关变量（即数据冗余），利用CART识别对底栖大型无脊椎动物有重大影响的关键生境因子。然后利用GAMs量化临界生境因子与物种之间的非线性关系。最后，利用GAMs拟合的响应曲线确定物种的生境偏好（即适宜的临界生境因子范围）。本研究将CART-GAMs模型应用于珠江口（PRE），验证其有效性。结果表明，CART从12个测量因子中识别出4个关键水质因子，即盐度（SAL）、总磷（TP）、pH和氨氮（NH3-N），从而减少了66.7%的数据冗余。利用关键水质因子，GAMs解释了底栖大型无脊椎动物Margalef多样性指数（dM）变异的66.2%。GAM响应曲线显示dM与SAL呈显著正相关，与TP、TN呈显著负相关，dM与pH呈单峰关系。最后，研究确定了底栖大型无脊椎动物适宜的水质因子范围（SAL = 21.15‰~ 32.32‰，TP = 0.05 ~ 0.2 mg/L, pH = 7.7 ~ 8.2, TN = 0.4 ~ 1.5 mg/L）。研究结果表明，混合CART-GAMs模型能有效地综合考虑多种生境因子对河口生境适宜性进行评价，为河口生境管理提供参考。
Benthic macroinvertebrates are an important part of the aquatic food chain in estuaries. Therefore, understanding their associated habitat requirements is critical in maintaining estuarine ecosystem stability, which has until now been evaluated using habitat suitability evaluations. Although most habitat suitability index (HSI)-based methods can determine the target species preferences for a few specific habitat factors, benthic macroinvertebrates are influenced by multiple habitat factors in estuaries. However, applying too many habitat factors can result in data redundancy, thereby reducing model efficiency. Additionally, nonlinear relationships between species and habitat factors and interactions between different habitat factors are often difficult to evaluate. Previous studies have not focused on methods that can simultaneously address these two issues. Accordingly, this study introduced CART-GAMs, a classification and regression tree model (CART) and a generalized additive model (GAM) hybrid, which can evaluate the suitability of multiple habitat factors relevant to benthic macroinvertebrates in estuaries. First, to remove irrelevant variables (i.e., data redundancy), CART was used to identify critical habitat factors that have significant impacts on benthic macroinvertebrates. GAMs were then used to quantify the nonlinear relationships between critical habitat factors and species. Finally, response curves fitted by GAMs were used to determine species habitat preferences (i.e., suitable critical habitat factor ranges). This study applied the CART-GAMs model to the Pearl River Estuary (PRE) to test its effectiveness. The results showed that CART identified four critical water quality factors, that is, salinity (SAL), total phosphorus (TP), pH, and ammonia nitrogen (NH3-N) from the 12 measured factors, subsequently reducing data redundancy by 66.7%. Using critical water quality factors, GAMs explained 66.2% of the variance in Margalef’s diversity index (dM) of benthic macroinvertebrates. Additionally, the GAM response curves showed that dM was positively correlated with SAL and negatively correlated with TP and TN. The response curve between dM and pH is unimodal. Finally, this study determined suitable water quality factor ranges for benthic macroinvertebrates (SAL = 21.15‰ ∼ 32.32‰, TP = 0.05 ∼ 0.2 mg/L, pH = 7.7 ∼ 8.2, and TN = 0.4 ∼ 1.5 mg/L). This study demonstrates that the hybrid CART-GAMs model can effectively evaluate estuarine habitat suitability with multiple habitat factors, while providing a reference for estuary habitat management.