Geology topics

K. J. Killgore

Publications and source records attributed to K. J. Killgore.

3 recordsLinked to original sources

USGS2013

Fish depth distributions in the Lower Mississippi River

A substantial body of literature exists about depth distribution of fish in oceans, lakes and reservoirs, but less is known about fish depth distribution in large rivers. Most of the emphasis on fish distributions in rivers has focused on longitudinal and latitudinal spatial distributions. Knowledge on depth distribution is necessary to understand species and community habitat needs. Considering this void, our goal was to identify patterns in fish benthic distribution along depth gradients in the Lower Mississippi River. Fish were collected over 14 years in depths down to 27 m. Fish exhibited non-random depth distributions that varied seasonally and according to species. Species richness was highest in shallow water, with about 50% of the 62 species detected no longer collected in water deeper than 8 m and about 75% no longer collected in water deeper than 12 m. Although richness was highest in shallow water, most species were not restricted to shallow water. Rather, most species used a wide range of depths. A weak depth zonation occurred, not as strong as that reported for deep oceans and lakes. Larger fish tended to occur in deeper water during the high-water period of an annual cycle, but no correlation was evident during the low-water period. The advent of landscape ecology has guided river research to search for spatial patterns along the length of the river and associated floodplains. Our results suggest that fish assemblages in large rivers are also structured vertically.

Lower Mississippi River↗

USGS2013

Fish assemblages in borrow-pit lakes of the Lower Mississippi River

Borrow-pit lakes encompass about a third of the lentic water habitats (by area) in the active floodplain of the Lower Mississippi River, yet little is known about their fish assemblages. We investigated whether fish assemblages supported by borrow-pit lakes resembled those in oxbow lakes to help place the ecological relevance of borrow-pit lakes in context with that of natural floodplain lakes. In all, we collected 75 fish species, including 65 species in eight borrow-pit lakes, 52 species in four riverside oxbow lakes, and 44 species in eight landside oxbow lakes. Significant differences in several species richness metrics were evident between borrow-pit lakes and landside oxbow lakes but not between borrow-pit lakes and riverside oxbow lakes. All three lake types differed in fish assemblage composition. Borrow-pit lakes and riverside oxbow lakes tended to include a greater representation of fish species that require access to diverse environments, including lentic, lotic, and palustrine habitats; fish assemblages in landside oxbow lakes included a higher representation of lacustrine species. None of the fish species collected in borrow-pit lakes was federally listed as threatened or endangered, but several were listed as species of special concern by state governments in the region, suggesting that borrow-pit lakes provide habitat for sensitive riverine and wetland fish species. Differences in fish assemblages among borrow-pit lakes were linked to engineered morphologic features, suggesting that diversity in engineering can contribute to diversity in fish assemblages; however, more research is needed to match engineering designs with fish assemblage structures that best meet conservation needs.

Lower Mississippi River↗

USGS2012

A direct-gradient multivariate index of biotic condition

Multimetric indexes constructed by summing metric scores have been criticized despite many of their merits. A leading criticism is the potential for investigator bias involved in metric selection and scoring. Often there is a large number of competing metrics equally well correlated with environmental stressors, requiring a judgment call by the investigator to select the most suitable metrics to include in the index and how to score them. Data-driven procedures for multimetric index formulation published during the last decade have reduced this limitation, yet apprehension remains. Multivariate approaches that select metrics with statistical algorithms may reduce the level of investigator bias and alleviate a weakness of multimetric indexes. We investigated the suitability of a direct-gradient multivariate procedure to derive an index of biotic condition for fish assemblages in oxbow lakes in the Lower Mississippi Alluvial Valley. Although this multivariate procedure also requires that the investigator identify a set of suitable metrics potentially associated with a set of environmental stressors, it is different from multimetric procedures because it limits investigator judgment in selecting a subset of biotic metrics to include in the index and because it produces metric weights suitable for computation of index scores. The procedure, applied to a sample of 35 competing biotic metrics measured at 50 oxbow lakes distributed over a wide geographical region in the Lower Mississippi Alluvial Valley, selected 11 metrics that adequately indexed the biotic condition of five test lakes. Because the multivariate index includes only metrics that explain the maximum variability in the stressor variables rather than a balanced set of metrics chosen to reflect various fish assemblage attributes, it is fundamentally different from multimetric indexes of biotic integrity with advantages and disadvantages. As such, it provides an alternative to multimetric procedures.

Arkansas, Mississippi↗