Assessment of the correlation between the nutrient load from migratory bird excrement and water quality by principal component analysis in a freshwater habitat

Environ Sci Pollut Res Int. 2023 May;30(24):66033-66049. doi: 10.1007/s11356-023-27065-3. Epub 2023 Apr 25.

Abstract

Waterbirds depend on a dispersed network of wetlands for their annual life cycle during migration. Climate and land use changes raise new concerns about the sustainability of these habitat networks, as water scarcity triggers ecological and socioeconomic impacts threatening wetland availability and quality. During the migration period, birds can be present in large enough numbers to influence water quality themselves linking them and water management in efforts to conserve habitats for endangered populations. Despite this, the guidelines within laws do not properly account for the annual change of water quality due to natural factors such as the migration periods of birds. Principal component analysis and principal component regression was used to analyze the correlations between the presence of a multitude of migratory waterbird communities and water quality metrics based on a dataset collected over four years in the Dumbrăvița section of the Homoród stream in Transylvania. The results reveal a correlation between the presence and numbers of various bird species and the seasonal changes in water quality. Piscivorous birds tended to increase the phosphorus load, herbivorous waterbirds the nitrogen load, while benthivorous duck species influenced a variety of parameters. The established PCR water quality prediction model showed accurate prediction capabilities for the water quality index of the observed region. For the tested data set, the method provided an R2 value of 0.81 and a mean squared prediction error of 0.17.

Keywords: Bird migration; Nutrient load; Principal component regression (PCR); River; Water quality assessment; Water quality index (WQI); Waterbird species.

MeSH terms

  • Animals
  • Birds
  • Conservation of Natural Resources
  • Ecosystem*
  • Principal Component Analysis
  • Rivers
  • Water Quality*
  • Wetlands