Date of this Version
Food Webs 33 (2022) e00249. https://doi.org/10.1016/j.fooweb.2022.e00249
We demonstrate the use of spatial stream network models (SSNMs) to explore relationships between a semiaquatic bioindicator songbird, Louisiana Waterthrush (Parkesia motacilla), and stream monitoring and benthic macroinvertebrate data in an area undergoing shale gas development. SSNMs allowed us to account for spatial autocorrelation inherent to these environmental data types and stream properties that traditional modeling approaches cannot capture to elucidate factors that affect waterthrush foraging locations. We monitored waterthrush along 58.1 km of 1st- and 2nd-order headwater stream tributaries (n = 14) in northwestern West Virginia over a two year period (2013–2014), sampled benthic macroinvertebrates in waterthrush territories, and collected wetted perimeter stream channel and water chemistry data along a 50 m fixed point stream grid. Spatial models outperformed traditional regression models and made a statistical difference in whether stream covariates of interest were considered relatable to waterthrush foraging. Waterthrush foraging probability index (FPI) was greater in areas where family and genus-level multi-metric indices of biotic stream integrity were higher (i.e. WVSCI and GLIMPSS). Waterthrush were found foraging both among stream flow connected and unconnected sampled sites on relatively further upstream locations where WVSCI and GLIMPSS were predicted to be highest. While there was no significant relationship found between FPI and shale gas land use on a catchment area scale, further information on waterthrush trophic dynamics and bioaccumulation of surface contaminants is needed before establishing the extent to which waterthrush foraging may be affected by shale gas development.