Your browser doesn't support javascript.
loading
The predictive model of hydrobiological diversity in the Asana-Tumilaca basin, Peru based on water physicochemical parameters and sediment metal content.
Flores Del Pino, Lisveth; Carrasco Apaza, Nancy Marisol; Caro Sánchez Benites, Víctor; Téllez Monzón, Lena Asunción; Visitación Bustamante, Kimberly Karime; Arana-Maestre, Jerry; Suárez Ramos, Diego; Wetzell Canales-Springett, Ayling; Dioses Morales, Jacqueline Jannet; Jaco Rivera, Evilson; Uriarte Ortiz, Alex; Jorge-Montalvo, Paola; Visitación-Figueroa, Lizardo.
Afiliação
  • Flores Del Pino L; Center for Research in Chemistry, Toxicology, and Environmental Biotechnology, Department of Chemistry, Faculty of Science, Universidad Nacional Agraria La Molina, 15024, Lima, Peru.
  • Carrasco Apaza NM; Center for Research in Chemistry, Toxicology, and Environmental Biotechnology, Department of Chemistry, Faculty of Science, Universidad Nacional Agraria La Molina, 15024, Lima, Peru.
  • Caro Sánchez Benites V; Center for Research in Chemistry, Toxicology, and Environmental Biotechnology, Department of Chemistry, Faculty of Science, Universidad Nacional Agraria La Molina, 15024, Lima, Peru.
  • Téllez Monzón LA; Center for Research in Chemistry, Toxicology, and Environmental Biotechnology, Department of Chemistry, Faculty of Science, Universidad Nacional Agraria La Molina, 15024, Lima, Peru.
  • Visitación Bustamante KK; Center for Research in Chemistry, Toxicology, and Environmental Biotechnology, Department of Chemistry, Faculty of Science, Universidad Nacional Agraria La Molina, 15024, Lima, Peru.
  • Arana-Maestre J; Museum of Natural History, Department of Limnology, Universidad Nacional Mayor de San Marcos, 15072, Lima, Peru.
  • Suárez Ramos D; Center for Research in Chemistry, Toxicology, and Environmental Biotechnology, Department of Chemistry, Faculty of Science, Universidad Nacional Agraria La Molina, 15024, Lima, Peru.
  • Wetzell Canales-Springett A; Center for Research in Chemistry, Toxicology, and Environmental Biotechnology, Department of Chemistry, Faculty of Science, Universidad Nacional Agraria La Molina, 15024, Lima, Peru.
  • Dioses Morales JJ; Center for Research in Chemistry, Toxicology, and Environmental Biotechnology, Department of Chemistry, Faculty of Science, Universidad Nacional Agraria La Molina, 15024, Lima, Peru.
  • Jaco Rivera E; Universidad Politécnica de Cataluña, 08034, Barcelona, Spain.
  • Uriarte Ortiz A; Organismo de Evaluación y Fiscalización Ambiental (OEFA), Ministerio Del Ambiente, 15076, Lima, Peru.
  • Jorge-Montalvo P; Center for Research in Chemistry, Toxicology, and Environmental Biotechnology, Department of Chemistry, Faculty of Science, Universidad Nacional Agraria La Molina, 15024, Lima, Peru.
  • Visitación-Figueroa L; Center for Research in Chemistry, Toxicology, and Environmental Biotechnology, Department of Chemistry, Faculty of Science, Universidad Nacional Agraria La Molina, 15024, Lima, Peru.
Heliyon ; 10(6): e27916, 2024 Mar 30.
Article em En | MEDLINE | ID: mdl-38524626
ABSTRACT
The hydrobiological diversity in the basin depends on biotic and abiotic factors. A predictive model of hydrobiological diversity for periphyton and macrobenthos was developed through multiple linear regression analysis (MLRA) based on the physicochemical parameters of water (PPW) and metal content in sediments (MCS) from eight monitoring stations in the Asana-Tumilaca Basin during the dry and wet seasons. The electrical conductivity presented values between 47.9 and 3617 µS/cm, showing the highest value in the Capillune River due to the influence of geothermal waters. According to Piper's diagram, the water in the basin had a composition of calcium sulfate and calcium bicarbonate-sulfate. According to the Wilcox diagram, the water was found to be between good and very good quality, except for in the Capillune River. The Shannon-Wiener diversity indices (H') were 2.62 and 2.88 for periphyton, and 2.10 and 2.44 for macrobenthos, indicating moderate diversity; for the Pielou's evenness index (J'), they were 0.68 and 0.70 for periphyton, and 0.68 and 0.59 for macrobenthos, indicating similar equity, in the dry and wet seasons, respectively, for both indices. In the model there were three cases, where the first two cases only worked with PPW or MCS, and case 3 worked with PPW and MCS. For case 3, the predicted values for H' and J' of periphyton and macrobenthos concerning those observed presented correlation coefficients of 0.7437 and 0.6523 for periphyton and 0.9321 and 0.8570 for macrobenthos, respectively, which were better than those of cases 1 and 2. In addition, principal component analysis revealed that the As, Pb, and Zn contents in the sediments negatively influenced the diversity, uniformity, and richness of the macrobenthos. In contrast, Cu and Cr had positive impacts because of the adaptation processes.
Palavras-chave

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE País/Região como assunto: America do sul / Peru Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE País/Região como assunto: America do sul / Peru Idioma: En Ano de publicação: 2024 Tipo de documento: Article