Statistical analyses
The statistical analyses were performed using the R version 4.0.4
software program (R Core Team, 2021). Target eDNA concentrations per PCR
reaction (2 µL template DNA) were converted into per water sample (1 mL
water sample) before the analyses. Linear regressions of the target eDNA
concentration (log10-transformed) against the number of zebrafish
individuals per tank were performed for each filter pore size and DNA
marker length using lm and confint functions, with theirR2 values and slopes with 95% confidence
intervals (CIs) estimated. We also conducted a linear model to assess
the effects of the eDNA size fraction and target marker length on the
accuracy of the relationship between eDNA concentration and species
abundance (i.e., the R2 value of linear
regression). The R2 values were Fisher’s
z-transformed by the package “MAc” in advance (Del Re & Hoyt, 2018)
to meet the normality (Yates et al., 2019) and included as the dependent
variable. Filter pore size (µm; categorical), marker length (bp;
log10-transformed), and interactions were also explanatory variables.
Additionally, a linear mixed model using the lmer function in the
package “lmerTest” (Kuznetsova et al., 2017) was performed to assess
the effects of the eDNA size fraction and marker length on the
sensitivity of the eDNA concentration in response to changes in species
abundance (i.e., the slope of linear regression [Eichmiller et al.,
2016)). The zebrafish eDNA concentration (log10-transformed) was
included as the dependent variable. The number of fish individuals per
tank, filter pore size, marker length (log10-transformed), and primary
interactions of fish individuals with filter pore size and
log10-transformed marker length were included as the fixed effects. The
tank replicates were included as the random effect.