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Table 1 Principal component analysis for agro-chemicals and agricultural practice

From: Abundance of insects and aerial insectivorous birds in relation to pesticide and fertilizer use

Loading matrix

PC1

PC2

PC3

PC4

PC5

Fertilizer

0.018

0.952

0.289

0.088

0.034

Agriculture

− 0.117

− 0.409

0.903

0.053

0.009

Area

0.950

− 0.114

− 0.296

0.092

0.012

Insecticides

0.949

− 0.274

− 0.041

0.091

0.116

Air pollution

0.961

0.124

0.191

− 0.143

− 0.032

Non-methane pollutants

0.983

− 0.053

0.012

0.055

− 0.164

Ammonia

0.962

− 0.137

0.207

− 0.88

0.008

  1. We reduced the number of variables in a Principal Component Analysis based on the correlation matrix and the varimax rotation. The three principal components with eigenvalues larger than 1.0 are listed. The PCA resulted in three eigen-values of 4.63, 1.20 and 1.05 accounting for an accumulated amount of variance of 83.3% of the variance. The first PC had weights of 0.950 for agricultural area, 0.949 for insecticides, 0.961 for air pollution, 0.983 for non-methane and 0.962 for ammonia. PC2 had a weight of 0.952 for fertilizer and PC3 had a weight of 0.903 for agriculture. Variables larger than 0.4 are generally considered to be significant and they are highlighted in bold font