Rapid urbanization of Southern California has drastically altered its stream systems through the construction of impervious surfaces in watersheds and the damming and hindered connectivity of channels. Climate change provides further concerns for organisms in snowmelt-fed streams that may suffer longer intermittent periods and changes in streamflow variability. Effective conservation of these waterways requires predictive modeling techniques incorporating a firm understanding of the abiotic, biotic, and spatiotemporal components structuring stream communities. This study analyzed the importance of stream order, stream distance, Euclidean (linear) distance, percentage of watershed urbanization, and distance from dams in influencing the family richness of aquatic arthropods in the highly anthropogenically modified Santa Ana River Watershed, California, USA. Data were obtained from large spatial scale sampling efforts reported by government agencies including the United States Geological Service and the California Environmental Data Exchange Network. A total of 93 sampled stream sites with counts of arthropod family richness and calculated abiotic variables were fit within a GIS-delineated stream network using the STARs package for ArcGIS and analyzed using a generalized linear model with lowest AIC value.
Both proximity to dams and increasing watershed urbanization were found to have a significant negative impact on arthropod richness in a Southern California watershed. Increasing stream order was also found to negatively influence richness, but may be confounded by greater levels of urbanization and runoff in downstream segments. Euclidean distance was a better predictor of richness than stream distance, suggesting characteristics of the surrounding landscape are important considerations in future modelling of stream systems. The r-squared values of the models suggest that these factors alone do not completely explain arthropod richness in this watershed. Future emphasis on biotic variables, such as species dispersal ability, and abiotic variables, including streamflow variability and surrounding land attributes, should be made to improve our ability to predict community responses to climate change and habitat fragmentation. The study has potential to be used in future planning of dam placement to lessen impact on stream ecology.