Comparison of benthic macroinvertebrate assessment methods along a salinity gradient in headwater streams.

Benthic macroinvertebrate community assessments are used commonly to characterize aquatic systems and increasingly for identifying their impairment caused by myriad stressors. Yet sampling and enumeration methods vary, and research is needed to compare their abilities to detect macroinvertebrate community responses to specific water quality variables. A common assessment method, rapid bioassessment, uses subsampling procedures to identify a fixed number of individual organisms regardless of total sample abundance. In contrast, full-enumeration assessments typically allow for expanded community characterization resulting from higher numbers of identified organisms within a collected sample. Here, we compared these two sampling and enumeration methods and their abilities to detect benthic macroinvertebrate response to freshwater salinization, a common stressor of streams worldwide. We applied both methods in headwater streams along a salinity gradient within the coal-mining region of central Appalachia USA. Metrics of taxonomic richness, community composition, and trophic function differed between the methods, yet most metrics exhibiting significant response to SC for full-enumeration samples also did for rapid bioassessment samples. However, full-enumeration yielded taxonomic-based metrics consistently more responsive to the salinization gradient. Full-enumeration assessments may potentially provide more complete characterization of macroinvertebrate communities and their response to increased salinization, whereas the more cost-effective and widely employed rapid bioassessment method can detect community alterations along the full salinity gradient. These findings can inform decisions regarding such tradeoffs for assessments of freshwater salinization in headwater streams and highlight the need for similar research of sampling and enumeration methodology in other aquatic systems and for other stressors.

Wetness index based on landscape position and topography (WILT): Modifying TWI to reflect landscape position.

Water and land resource management planning benefits greatly from accurate prediction and understanding of the spatial distribution of wetness. The topographic wetness index (TWI) was conceived to predict relative surface wetness, and thus hydrologic responsiveness, across a watershed based on the assumption that shallow slope-parallel flow is a major driver of the movement and distribution of soil water. The index has been extensively used in modeling of landscape characteristics responsive to wetness, and some studies have shown the TWI performs well in landscapes where interflow is a dominant process. However, groundwater flow dominates the hydrology of low-slope landscapes with high subsurface conductivities, and the TWI assumptions are not likely to perform well in such environments. For groundwater dominated systems, we propose a hybrid wetness index (Wetness Index based on Landscape position and Topography, WILT) that inversely weights the upslope contributing area by the distance to the nearest surface water feature and the depth to groundwater. When explicit depth to groundwater data are not available, height above and separation from surface water features can act as surrogates for proximity to groundwater. The resulting WILT map provides a more realistic spatial distribution of relative wetness across a low-slope Coastal Plain landscape as demonstrated by improved prediction of hydric soils, depth to groundwater, nitrogen and carbon concentrations in the A horizon of the soil profile, and sensitivity to DEM scale.