Research about Apalachicola–Chattahoochee–Flint River Basin

USGS2018

Genetic population structure of Shoal Bass within their native range

Endemic to the Apalachicola River basin of the southeastern USA, the Shoal Bass Micropterus cataractae is a fluvial‐specialist sport fish that is imperiled because of anthropogenic habitat alteration. To counter population declines, restorative stocking efforts are becoming an increasingly relevant management strategy. However, population genetic structure within the species is currently unknown, but it could influence management decisions, such as brood source location. Leveraging a collaborative effort to collect and genotype specimens with 16 microsatellite loci, our objective was to characterize hierarchical population structure and genetic differentiation of the Shoal Bass across its native range, including an examination of structuring mechanisms, such as relatedness and inbreeding levels. Specimens identified as Shoal Bass were collected from 13 distinct sites ( N ranged from 17 to 209 per location) and were then taxonomically screened to remove nonnative congeners and hybrids (pure Shoal Bass N ranged from 13 to 183 per location). Our results revealed appreciable population structure, with five distinct Shoal Bass populations identifiable at the uppermost hierarchical level that generally corresponded with natural geographic features and anthropogenic barriers. Substructure was recovered within several of these populations, wherein differences appeared related to spatial isolation and local population dynamics. An analysis of molecular variance revealed that 3.6% of the variation in our data set was accounted for among three larger river drainages, but substructure within each river drainage also explained an additional 8.9% of genetic variation, demonstrating that management at a scale lower than the river drainage level would likely best conserve genetic diversity. Results provide a population genetic framework that can inform future management decisions, such as brood source location, so that genetic diversity within and among populations is conserved and overall adaptability of the species is maintained.

Apalachicola–Chattahoochee–Flint River Basin↗

USGS2014

Evaluation of statistically downscaled GCM output as input for hydrological and stream temperature simulation in the Apalachicola–Chattahoochee–Flint River Basin (1961–99)

The accuracy of statistically downscaled general circulation model (GCM) simulations of daily surface climate for historical conditions (1961–99) and the implications when they are used to drive hydrologic and stream temperature models were assessed for the Apalachicola–Chattahoochee–Flint River basin (ACFB). The ACFB is a 50 000 km 2 basin located in the southeastern United States. Three GCMs were statistically downscaled, using an asynchronous regional regression model (ARRM), to ⅛° grids of daily precipitation and minimum and maximum air temperature. These ARRM-based climate datasets were used as input to the Precipitation-Runoff Modeling System (PRMS), a deterministic, distributed-parameter, physical-process watershed model used to simulate and evaluate the effects of various combinations of climate and land use on watershed response. The ACFB was divided into 258 hydrologic response units (HRUs) in which the components of flow (groundwater, subsurface, and surface) are computed in response to climate, land surface, and subsurface characteristics of the basin. Daily simulations of flow components from PRMS were used with the climate to simulate in-stream water temperatures using the Stream Network Temperature (SNTemp) model, a mechanistic, one-dimensional heat transport model for branched stream networks. The climate, hydrology, and stream temperature for historical conditions were evaluated by comparing model outputs produced from historical climate forcings developed from gridded station data (GSD) versus those produced from the three statistically downscaled GCMs using the ARRM methodology. The PRMS and SNTemp models were forced with the GSD and the outputs produced were treated as “truth.” This allowed for a spatial comparison by HRU of the GSD-based output with ARRM-based output. Distributional similarities between GSD- and ARRM-based model outputs were compared using the two-sample Kolmogorov–Smirnov (KS) test in combination with descriptive metrics such as the mean and variance and an evaluation of rare and sustained events. In general, precipitation and streamflow quantities were negatively biased in the downscaled GCM outputs, and results indicate that the downscaled GCM simulations consistently underestimate the largest precipitation events relative to the GSD. The KS test results indicate that ARRM-based air temperatures are similar to GSD at the daily time step for the majority of the ACFB, with perhaps subweekly averaging for stream temperature. Depending on GCM and spatial location, ARRM-based precipitation and streamflow requires averaging of up to 30 days to become similar to the GSD-based output. Evaluation of the model skill for historical conditions suggests some guidelines for use of future projections; while it seems correct to place greater confidence in evaluation metrics which perform well historically, this does not necessarily mean those metrics will accurately reflect model outputs for future climatic conditions. Results from this study indicate no “best” overall model, but the breadth of analysis can be used to give the product users an indication of the applicability of the results to address their particular problem. Since results for historical conditions indicate that model outputs can have significant biases associated with them, the range in future projections examined in terms of change relative to historical conditions for each individual GCM may be more appropriate.

Florida, Georgia↗