Bayesian Modeling of the Effects of Extreme Flooding and the Grazer Community on Algal Biomass Dynamics in a Monsoonal Taiwan Stream.

The effects of grazing and climate change on primary production have been studied widely, but seldom with mechanistic models. We used a Bayesian model to examine the effects of extreme weather and the invertebrate grazer community on epilithic algal biomass dynamics over 10 years (from January 2004 to August 2013). Algal biomass and the invertebrate grazer community were monitored in the upstream drainage of the Dajia River in Taiwan, where extreme floods have been becoming more frequent. The biomass of epilithic algae changed, both seasonally and annually, and extreme flooding changed the growth and resistance to flow detachment of the algae. Invertebrate grazing pressure changes with the structure of the invertebrate grazer community, which, in turn, is affected by the flow regime. Invertebrate grazer community structure and extreme flooding both affected the dynamics of epilithic algae, but in different ways. Awareness of the interactions between algal communities and grazers/abiotic factors can help with the design of future studies and could facilitate the development of management programs for stream ecosystems.