Construction of an integral index based on macroinvertebrates to determine the quality of water with agro-industrial influence

IF 1 Q3 AGRICULTURE, DAIRY & ANIMAL SCIENCE
Michael Niño-de-Guzman Tito, J. M. Vásquez-Ramos
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Abstract

The physicochemical and biological indices have been used in isolation; if the parameters of these indices were applied in an integrated manner, they would bring together in a single measure the functional and structural variability of the biotic and abiotic components of water quality. The aim of this study was to build a comprehensive water quality index. Eleven sampling points were selected considering different degrees of agro-industrial intervention. 21 abiotic variables and 27 biological metrics were measured. Macroinvertebrates were quantitatively collected and identified to family taxonomic level. Using Principal Component Analysis, after standardization and exclusion of uncorrelated variables (VIF ≤ 10), the abiotic gradient was determined, which represented the abiotic variables that explained the disturbances in the water; with the abiotic gradient and the biological metrics, a Pearson correlation was performed, and those biological metrics that presented a high and non-redundant correlation were selected (Pearson 0.6 ≤ r ≤ 0.8); with the selected biological metrics, we proceeded to formulate and categorize the index; finally, by means of simple linear regression, the proposed index was compared with five other indexes (ICA, ICOMO, EPT, BMWP/col. and ASPT). The results showed that the abiotic gradient was defined by CP 1 which explained 65.5% of the accumulated variance, represented by altitude (r = 0.411), iron (r = 0.345) and dissolved oxygen (r = 0.329). The biological metrics used for the index design were: % scrapers, % swimmers, NEF of order 2, Ephemeroptera and Trichoptera tolerance. It was concluded that the integral index presents a higher predictive level (R2 = 0.87) of water quality, compared to the other indices: ASPT (R2 = 0.79), BMWP/col. (R2 = 0.68), EPT (R2 = 0.61), ICOMO (R2 = 0.35) and ICA (R2 = 0.27).
基于大型无脊椎动物的综合指标构建评价农工影响水质
理化和生物学指标已单独使用;如果以综合方式应用这些指数的参数,它们将把水质的生物和非生物成分的功能和结构变异性汇集在一个单一的测量中。本研究的目的是建立一个综合性的水质指标。考虑不同程度的农工干预,选取了11个采样点。测量了21个非生物变量和27个生物指标。对大型无脊椎动物进行了定量收集和科级鉴定。采用主成分分析方法,标准化并排除不相关变量(VIF≤10)后,确定了非生物梯度,该梯度代表了解释水体扰动的非生物变量;对非生物梯度与生物指标进行Pearson相关性分析,选择相关性高且无冗余的生物指标(Pearson 0.6≤r≤0.8);根据选定的生物指标,我们开始制定和分类指数;最后,通过简单线性回归与ICA、ICOMO、EPT、BMWP/col等5个指标进行比较。和ASPT)。结果表明,非生物梯度由CP 1定义,解释了累计方差的65.5%,分别为海拔(r = 0.411)、铁(r = 0.345)和溶解氧(r = 0.329)。指数设计采用的生物学指标为:刮刀虫百分比、游泳虫百分比、第2目NEF、蜉蝣目和毛翅目耐受性。综合指数对水质的预测水平(R2 = 0.87)高于ASPT指数(R2 = 0.79)、BMWP/col指数(R2 = 0.79)。(R2 = 0.68)、EPT (R2 = 0.61)、ICOMO (R2 = 0.35)、ICA (R2 = 0.27)。
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来源期刊
Scientia Agropecuaria
Scientia Agropecuaria AGRICULTURE, DAIRY & ANIMAL SCIENCE-
CiteScore
3.50
自引率
0.00%
发文量
27
审稿时长
12 weeks
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