Predicting spatial distribution patterns and hotspots of fish assemblage in a coastal basin of the central-south of Chile, by geostatistical techniques

Prediction of fish diversity using geostatistics

  • Sam Catchpole Fundación Organización para el Desarrollo y la Sustentabilidad; Pares and Álvarez Gestión Ambiental, Concepción, Chile.
  • Reinaldo Rivera | reijavier@gmail.com Departamento de Zoología, Universidad de Concepción, Chile.
  • Cristián E. Hernández Departamento de Zoología, Universidad de Concepción, Chile.
  • Javiera De La Peña Pares & Álvarez Gestión Ambiental, Concepción, Chile.
  • Pablo González Centro Regional de Estudios Ambientales, Universidad Católica de la Santísima Concepción, Concepción, Chile.

Abstract

Currently the application of geographic information systems in the subjects of biology and ecology has facilitated the study patterns of distribution, richness y diversity of species. However, in freshwater ecosystems the application of geostatistical analysis are scarcely used in the worldwide, including Chile. Therefore, in our study we developed predictive maps using simple Kriging (resolution 12.5 x 12.5 m), based on richness and Shannon-Weaver diversity, and we analyzed spatial autocorrelation of fish assemblages (Moran and Getis-Ord index) present in the Andalién River basin. Our results established a fish assemblage composition of 24 species, most of them native (79%) and with endanger conservation status. Predictive maps showed highest values of richness and diversity of fish species in the potamon zone of the Andalién and Nonguén streams, while the low values were described in the Chaimavida sub-basin and the transition zone of Andalién River. The Moran and Getis-Ord index determined a cluster pattern of the data and define hotspot and coldspot zones, concordant with the predictive maps of richness and Shannon-Weaver diversity. The geostatistical and spatial techniques showed to be relevant tools for the determination of distribution patterns of freshwater species and conservation issues.

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Published
2019-05-09
Info
Issue
Section
Original Articles
Edited By
Pietro Volta, CNR-IRSA Verbania, Italy
Supporting Agencies
CONICYT Doctoral Fellowship (21160866) to R. Rivera, FONDECYT project 1170815
Keywords:
Kriging, interpolation, spatial autocorrelation, Andalién River basin
Statistics
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How to Cite
1.
Catchpole S, Rivera R, Hernández CE, De La Peña J, González P. Predicting spatial distribution patterns and hotspots of fish assemblage in a coastal basin of the central-south of Chile, by geostatistical techniques: Prediction of fish diversity using geostatistics. J Limnol [Internet]. 2019May9 [cited 2020Aug.10];78(2). Available from: https://www.jlimnol.it/index.php/jlimnol/article/view/jlimnol.2019.1881