lake texoma
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2019 ◽  
Vol 40 (3) ◽  
pp. 544-554 ◽  
Author(s):  
Andrew T. Taylor ◽  
James M. Long ◽  
Richard A. Snow ◽  
Michael J. Porta

<em>Abstract</em>.—Striped bass <em>Morone saxatilis </em>have been introduced into hundreds of inland impoundments, and in several instances, natural reproduction and recruitment has developed. Three of these impoundments are Lake Texoma, John H. Kerr Reservoir, and Santee Cooper Reservoir, whose natural recruitment is dependent on their tributary rivers. Historic management of these populations has required addressing issues of excess reproduction, excess harvest, and spawning flow alteration. Initial high abundance fostered a harvest oriented mind set among striped bass anglers in these reservoirs, which today can only be sustained on Lake Texoma. Supplemental stocking of both Kerr and Santee-Cooper reservoirs has been used to replace declines in natural recruitment. Mortality estimates suggest that reproductive overfishing may be the underlying cause of natural recruitment declines. Recent adjustments to harvest regulations at both Kerr and Santee-Cooper were required to increase the number of striped bass reaching reproductive age. Both management approaches reduce fishing mortality through reduced daily bag and higher size limits, but also recognize that high catch-and-release mortality makes length limits counterproductive during the summer.


<em>Abstract</em>.—Striped bass <em>Morone saxatilis</em> provide important commercial and recreational fisheries in many Atlantic coast states, in addition to providing popular recreational reservoir fisheries in numerous inland states. Measurements of fishery-dependent data such as harvest, catch, and effort are essential to determining whether management actions are effective. Many states, including Texas, use creel-survey methods for measuring striped bass catch and effort statistics for recreational anglers. However, a systematic overview of the performance of the various types of creel surveys, or creel surveys in general, for measuring striped bass catch and effort has not been performed previously. In many states, both roving and access creel surveys are used, and effort may be allocated using unequal probabilities. In fisheries with low harvests of <em>Morone </em>spp., survey statistics for these fish typically have high relative standard errors (RSE), from 30% to 115%.As directed effort increases, the RSE typically decreases; in systems with high angling effort directed at striped bass, RSE is much lower (e.g., 18% in Lake Texoma, Texas–Oklahoma).We used these and other data from striped bass creel surveys throughout the United States to assess the reliability of estimates from various methods. We recommend making survey sampling effort coincide with the fishing effort. While it may be possible to improve the precision by increasing the amount of manpower devoted to the current creel survey, stratifying or using unequal spatial and temporal probabilities are techniques more likely to improve precision in a cost-effective manner. Once the data have been collected, we show how using model-based estimation, such as using Kalman filters or empirical Bayesian estimation, could also prove advantageous.


2009 ◽  
Vol 29 (4) ◽  
pp. 1006-1014 ◽  
Author(s):  
William P. Baker ◽  
Jeff Boxrucker ◽  
Kurt E. Kuklinski
Keyword(s):  

<em>Abstract</em>.—While processes of depositional filling and ecological succession in natural lakes have been well described, these concepts are relatively new and seldom applied to reservoirs, especially at the landscape scale. However, ecological time has been sufficient to allow us to see successional processes in many reservoir systems. Illustrative of such processes, Lake Texoma is a 36,000-ha reservoir located in southern Oklahoma and northern Texas, and patterns of depositional filling and subsequent processes are apparent in the up-lake ends (there are two large-river tributaries) of this system. Completed in 1944, Lake Texoma has a drainage area of more than100,000 km2, most of which is highly erodable agricultural lands. We used historic aerial photographs, geographic information systems technology, and field measurements to examine a variety of surface and habitat features and analyzed experimental gill-net samples using ordination techniques to characterize the fish communities in portions of the reservoir most affected by sedimentation. Extensive sedimentation and accretion of sediments above water level has effectively resulted in surface area reduction, cove isolation, fragmentation of lacustrine habitats, morphometric changes, and establishment of terrestrial vegetation on newly deposited lands. Most notably, sedimentation has led to the development of linear bars of deposition above normal pool elevation that have blocked mouths of coves, bisected large areas of the reservoir, and fragmented several pools. In our study site alone, 332 ha (surface area) of reservoir has experienced accretion of land above the water level. Reservoir fragments had lower shoreline development values (mean = 2.21) than comparable control sites (mean = 3.39). Depositional shorelines associated with sedimentation exhibited lower gradients than nondepositional shorelines (mean = 2.0% versus 4.2%, respectively), and habitat heterogeneity was lower along depositional shorelines than along nondepositional shorelines. Fish communities in isolated reservoir fragments appeared to be distinct from fish communities in nonfragmented habitats. This change in community structure may be driven by an appreciable reduction of pelagic species from fragmented sites, as these sites have limited or no connectivity to the main body of the reservoir. With respect to the newly deposited lands, ecological succession of vegetation followed a progression from mud flats to dense, nearly monotypic stands of black willow Salix nigra forests within a few years. These habitat changes had strong implications to the fish communities as well as to adjacent terrestrial wildlife communities and will likely pose many challenges, and perhaps opportunities, for natural resource managers.


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