Geology topics

Research about Red River catchment

Source-linked reports with geographic coverage including Red River catchment.

5 recordsLinked to original sources

USGS2024

Length-weight relationships of native and non-native fishes in the lower Red River catchment, USA

Length-weight relationships are useful for stock assessments and modeling alternative conservation and management strategies for both native and non-native fishes. We developed length-weight relationships for 18 native and non-native riverine fishes in the lower Red River catchment. Fishes were sampled in the summer and autumn seasons between May 2021 and March 2024 via electrofishing and gill nets. Measurements for each specimen consisted of total length (mm) and weight (g). We provide L-W relationships for 14 native fishes consisting of 5 families (Lepisosteidae, Catostomidae, Ictaluridae, Sciaenidae, and Polyodontidae) and 4 non-native species belonging to the family Cyprinidae. We collected 6,845 individuals ranging from 67 alligator gar to 1,848 smallmouth buffalo. All the L-W relationships were significant ( p < 0.05), and the majority (72% of species) of relationships between length and weight had r 2 values > 0.70. Our findings provide insight into the L-W relationships of riverine fishes and can be useful for modeling alternatives targeted at native fishes of recreational value and the removal efforts of non-native fishes.

Arkansas, Oklahoma, Texas↗

USGS2024

Processing time and precision of aging structures for Bighead Carp and Silver Carp in the lower Red River catchment in the southern Great Plains

Objective Population demographics of invasive species are commonly evaluated to better develop management actions that are useful for reducing their abundance or controlling the population. Bighead Carp Hypophthalmichthys nobilis and Silver Carp H. molitrix are emblematic invaders in the United States, where they continue to expand their range. There is currently no consensus about which hard structure from these species is best for age estimation. Our study objective was to compare the processing time and precision of five hard structures used for age estimation of both species. Methods We sampled fish in the lower Red River catchment of Oklahoma, Arkansas, and Texas during summer and autumn 2021–2022 and removed the lapillus otolith, left primary pectoral fin ray, postcleithrum, urohyal bone, and anterior-most pterygiophore of the dorsal fin from both Bighead and Silver carp. The structures ( n = 1204) were either embedded in epoxy or thin-sectioned and mounted on slides. Two readers estimated the age of the fish by using each structure and came to a consensus. Processing time was recorded from the onset of laboratory processing to the termination of polishing the cross sections for age estimation. Result Processing of otoliths was comparable to or faster than processing of the other structures and resulted in the highest between-reader agreement. The lowest coefficients of variation in age estimation were represented using lapillus otoliths for Bighead Carp and postcleithra for Silver Carp. Our age bias plots indicated that all other structures underestimated age relative to the lapillus otoliths. Conclusion Our results indicated that using lapillus otoliths for age estimation of these species would have the highest between-reader agreement and would incur no additional laboratory processing time. However, validation is needed to assess whether lapillus otoliths correctly age these species. From a management perspective, use of this structure would facilitate improved population comparisons.

Arkansas, Oklahoma, Texas↗

USGS2024

Evaluating the context dependency of large river nursery habitats for fishes in the lower Red River catchment

Both fine- and coarse-scale physicochemical conditions affect the quantity and quality of nursery habitats within riverine ecosystems. Nursery habitats in large, braided, and sandbed streams such as the lower Red River of Oklahoma, Texas, and Arkansas are not well described and likely vary among species. Identification of nursery habitats is important for developing proper conservation and management actions. We used an occupancy model framework to determine how hierarchical habitat factors related to the occupancy of 38 juvenile fish species. Our findings indicate that large river nursery habitats can generally be defined by reaches with off-channel slackwater habitat, having deep pools but shallow thalweg depths, typically located further away from dams, and with low percentages of limestone lithology. Species within the same genera often exhibited variable relationships with river slope, amount of large woody debris, channel shape, discharge, and position of reaches within the stream network. Our results indicate important species-specific relationships that define nursery habitats, indicating an important context dependency of nursery habitats even within fishes that are taxonomically similar. If the goal is to improve recruitment by native fishes, then consideration of the important species-specific differences would be beneficial if improvements are made to nursery habitats. Moreover, careful consideration of the effects of dam operations will help maintain proper connectivity to off-channel habitats important in downriver portions of the river network.

Arkansas, Louisiana, Oklahoma, Texas↗

USGS2022

Increased landscape disturbance and streamflow variability threaten fish biodiversity in the Red River catchment, USA

Aim Stream fish distributions are hypothesized to be strongly associated with landscape characteristics at multiple scales. Variation in flow regimes and intensity of landscape disturbance are associated with stream fish distributions; however, relationships are poorly understood in many high-diversity regions. Our objective was to identify occurrence relationships between fish distributions and streamflow and landscape characteristics in the south-central United States. Location Our study area was the central Red River catchment in Oklahoma, Texas and Arkansas, USA. Methods We used existing fish surveys to model the occurrence of a diverse, warmwater assemblage among hydraulic response units (HRUs). We used multispecies occupancy modelling to identify variation in occurrence probability among 111 stream fishes in relation to landscape disturbance and flow regime characteristics. Results We found occurrence relationships with landscape disturbance and 11 metrics comprising all flow-regime components. The relationships varied within both major species groups and some genera. Frequency and duration were the most common metrics underlying flow regime relationships. More common stream fishes tended to be positively associated with higher levels of landscape disturbance and flow regime metrics representing variability; conversely, narrow-ranged fishes tended to be negatively associated. Occurrence relationships with flow metrics representing high-flow events were predominately negative. As expected, many species were strongly associated with ecoregion with landscape disturbance and flow relationships held constant. Main conclusions Our study informs land use and water management decisions and stream fish conservation at multiple spatial scales. Collectively, the findings suggest potential homogenization of the Red River fish assemblage with increased landscape disturbance and streamflow variability. A reduction in landscape disturbance and maintenance of natural flow patterns at coarser scales may benefit endemic and narrow-ranged fishes. Our findings also help guide finer-scale land use and water management decisions by identifying stream network areas with a high occurrence probability of less tolerant fishes.

Arkansas, Oklahoma, Texas↗

USGS2021

Fragmentation and streamflow metrics drive prairie chub (Macrhybopsis australis) occurrence in the upper Red River basin

Dam construction threatens global aquatic biodiversity by fragmenting stream networks and altering flow regimes. The negative effects of dams are exacerbated by increased drought periods and associated water withdrawals, especially in semi-arid regions. Stream fishes are particularly threatened owing to their mobile nature and requirement for multiple habitats to complete their life cycles. An understanding of relationships with fragmentation and flow regimes, particularly as coarse-scale (e.g. catchment) constraints on species distributions, is essential for stream fish conservation strategies. Prairie chub ( Macrhybopsis australis ) is a small-bodied minnow (Cyprinidae) with poorly understood ecology endemic to the North American Great Plains. Suspected declines in abundance and extirpations have resulted in conservation interest for prairie chub at state and federal levels. Prairie chub is thought to share its reproductive strategy with pelagic-broadcast spawning minnows (pelagophils). Freshwater pelagic-broadcast spawning fishes have been disproportionately affected by fragmentation and streamflow alteration globally. Relationships of prairie chub occurrence with coarse-scale fragmentation and streamflow metrics were examined in the upper Red River catchment. Occurrence probability was modelled using existing survey data, while accounting for variable detection. The modelled relationships were used to project the distribution of prairie chub in both a wet and dry climatic period. The probability of prairie chub occurrence was essentially zero at sites with higher densities of upstream dams, but increased sharply with increases in flow magnitude, downstream open mainstem, and flood duration. The projected distribution of prairie chub was broader than indicated by naïve occurrence, but similar in both climatic periods. The occurrence relationships are consistent with the hypotheses of pelagic broadcast spawning and represent coarse-scale constraints that are useful for identifying areas of the stream network with higher potential for finer-scale prairie chub conservation and recovery efforts. In addition to informing pelagophil conservation, the relationships are also applicable to pelagic-broadcast spawning fishes in marine environments.

Oklahoma, Texas↗