Ecological Indicators (Mar 2024)
Dynamic habitat modelling for water-dependent species in the Murray-Darling Basin
Abstract
Improved knowledge of how habitat for water-dependent species is changing over space and time across entire river catchments is important in developing indicators for tracking changes and quantifying the effectiveness of environmentally-targeted water management actions. Such information is often difficult to obtain across large catchments, given that habitat for water-dependent species can change rapidly and typically depends on complex interactions of environmental variables. Models can help in filling these information gaps, by using incomplete data to generalise patterns at fine spatial and temporal resolution across large catchments. We developed dynamic habitat models for seven water-dependent species across the Murray-Darling Basin, the longest river system in Australia. We considered two plant species (river red gum and lignum), two waterbird species (royal spoonbill and straw-necked ibis), two fish species (Murray cod and golden perch) and a macroinvertebrate group (Decapoda). We utilised advances in basin-wide data on stream flow and inundation to derive a range of ecologically meaningful spatiotemporal habitat predictors, and used these to model occurrence and physiological condition for each species. This data-driven approach identified the environmental variables most important in predicting habitat quality for each species, and their associated response functions. The dynamic habitat models were used to generate basin-wide, fine resolution (≈90 m) predictions for each species across a time-series of several decades (1995–2020). The model predictions were summarised into indicators to identify changes in habitat quality over time and identify areas that consistently provided the highest quality habitat. These habitat models and predictions extend our understanding of the environmental drivers of habitat for each water-dependent species studied and enable a variety of assessments to quantify the ecological outcomes of past water management.
