Development and application of predictive models of surface water extent to identify aquatic refuges in eastern Australian temporary stream networks

摘要: Many organisms living in temporary streams rely on remnant surface water to survive during extended dry periods and recolonize newly established habitats when flow resumes. However, research the spatio‐temporal variations of extent for entire river networks is scarce. In this study, we first present a new field method rapid assessment. Next, develop predictive models relating observed environmental attributes at large number surveyed stream segments (n=241) eastern Australian coastal catchments. We use predict daily dynamics throughout over period 1911‐2017, based available long‐term influencing hydrological processes. find descriptors can be accurately predicted robust internal external validations. Environmental predictor variables representing gaining processes were more important predicting than losses. Simulated highly dynamic through space time, particularly inland streams, which driest average. Total length with ranged from 8,974 13,742 km across study period. Our presents novel practical approach quantifying extent, potential applicability other parts world. The simulated time used identify prioritize aquatic refuge areas that sustain biodiversity periods.