Predicting Periphyton Cover Frequency Distributions across New Zealand's Rivers

Regression models of mean and mean annual maximum (MAM) cover were derived for two categories of periphyton cover (filaments and mats) using 22 years of monthly monitoring data from 78 river sites across New Zealand. Explanatory variables were derived from observations of water quality variables, hydrology, shade, bed sediment grain size, temperature, and solar radiation. The root mean square errors of these models were large (75‐95% of the mean of the estimated values). The at‐site frequency distributions of periphyton cover were approximated by the exponential distribution, which has the mean cover as its single parameter. Independent predictions of cover distributions at all sites were calculated using the mean predicted by the regression model and the theoretical exponential distribution. The probability that cover exceeds specified thresholds and estimates of MAM cover, based on the predicted distributions, had large uncertainties (~80‐100%) at the site scale. However, predictions aggregated by classes of an environmental classification accurately predicted the proportion of sites for which cover exceeded nominated criteria in the classes. The models are useful for assessing broad‐scale patterns in periphyton cover and for estimating changes in cover with changes in nutrients, hydrological regime, and light.