2.4. Statistical analyses
Before conducting statistical analyses, the Kolmogorov-Smirnov and
Levene’s tests were employed to assess data normality and homogeneity of
variance, respectively.
To analyze the habitat selection preference of D. splendidum across different sex and age groups, Pearson correlation analysis was
conducted to assess autocorrelation among numerical ecological factors,
Kendall correlation analysis was conducted to assess autocorrelation
among classified ecological factors, and Spearman correlation analysis
was conducted to assess autocorrelation between numerical and classified
ecological factors. Factors exhibiting high autocorrelation
(|r| > 0.8; Gardiner et al., 2015;
Chiaverini et al., 2023) were subsequently excluded. Perch height,
reflecting species-specific preferences, was omitted from habitat
selection preference analysis. Subsequently, a random forest model was
constructed using these numerical and classified factors, and trend
charts were generated for the Mean Decrease Gini index (Zhang et al.,
2020; R Development Core Team, 2018). Based on the differential
importance of predictor variables indicated by the mean decrease Gini
index, partial dependence plots were generated for various habitat
factors.
To compare differences in habitat preference factors among different sex
and age groups, a general linear model (GLM) was initially employed to
quantify the effects of sex, age, and their interactions on habitat
selection (Delaney et al., 2016). Subsequently, simple effect analysis
was conducted to evaluate the influence of ecological factor
interactions, excluding non-significant interactions. For numerical
factors conforming to a normal distribution, differences in habitat
selection between different sex and age groups were assessed using
independent sample t -tests. In cases where numerical factors did
not follow a normal distribution, differences in habitat selection among
populations were assessed using the Mann-Whitney U test (Li et al.,
2022). Chi-square tests were performed to analyze disparities in
classified factors, such as slope direction and vegetation type,
regarding sex and age preferences (Shilereyo et al., 2021). When
significant differences were observed (P < 0.05),
Vanderploeg & Scavia’s selection index was employed to elucidate
population-specific habitat preferences.
All statistical analyses were conducted using R Studio (v23.3.1, Racine
et al., 2012) and SPSS software (v22.0).