6 resultados para Random regression models
em Aquatic Commons
Resumo:
Linear regression models are constructed to predict seasonal runoff by fitting streamflow to temperature, precipitation, and snow water content across a range of elevations. The models are quite successful in capturing the differences in discharge between different elevation watersheds and their interannual variations. This exercise thus provides insight into seasonal changes in streamflow at different elevation watersheds that might occur under a changed climate.
Influence of soak time and fish accumulation on catches of reef fishes in a multispecies trap survey
Resumo:
Catch rates from fishery-independent surveys often are assumed to vary in proportion to the actual abundance of a population, but this approach assumes that the catchability coefficient (q) is constant. When fish accumulate in a gear, the rate at which the gear catches fish can decline, and, as a result, catch asymptotes and q declines with longer fishing times. We used data from long-term trap surveys (1990–2011) in the southeastern U.S. Atlantic to determine whether traps saturated for 8 reef fish species because of the amount of time traps soaked or the level of fish accumulation (the total number of individuals of all fish species caught in a trap). We used a delta-generalized-additive model to relate the catch of each species to a variety of predictor variables to determine how catch was influenced by soak time and fish accumulation after accounting for variability in catch due to the other predictor variables in the model. We found evidence of trap saturation for all 8 reef fish species examined. Traps became saturated for most species across the range of soak times examined, but trap saturation occurred for 3 fish species because of fish accumulation levels in the trap. Our results indicate that, to infer relative abundance levels from catch data, future studies should standardize catch or catch rates with nonlinear regression models that incorporate soak time, fish accumulation, and any other predictor variable that may ultimately influence catch. Determination of the exact mechanisms that cause trap saturation is a critical need for accurate stock assessment, and our results indicate that these mechanisms may vary considerably among species.
Resumo:
The influences of age, size, and condition of spawning females on fecundity and oocyte quality were analyzed for the Patagonian stock of Argentine Hake (Merluccius hubbsi). Samples of mature females were collected in the spawning area as part of 2 research surveys conducted in January 2010 and 2011, during the peak of the reproductive season. Batch fecundity (BF) ranged between 40,500 (29 cm total length [TL]) and 2,550,000 (95 cm TL) hydrated oocytes, and was positively correlated with TL, gutted weight, age, hepatosomatic index (HSI), and the relative condition factor (Kn). Relative fecundity ranged between 85 and 1040 hydrated oocytes g–1 and showed significant positive relationships with gutted weight, HSI, and Kn; however, coefficients of determination were low for all regressions. Dry weights of samples of 100 hydrated oocytes ranged between 1.8 and 3.95 mg and were positively correlated with all variables analyzed, including batch and relative fecundity. Multiple regression models created with data of the morphophysiological characteristics of females supported maternal influences on fecundity and egg weights. Within the studied size range (29–95 cm TL), larger individuals had better somatic and egg condition, mainly revealed by higher HSI and hydrated oocytes with larger oil droplets (275.71μm [standard error 1.49]). These results were associated with the higher feeding activity of larger females during the spawning season in comparison with the feeding activity of young individuals (<5 years old); the better nutritional state of larger females, assumed to result from more feeding, was conducive to greater production of high-quality eggs.
Resumo:
Ths report addresses the following two questions: 1) What are the loads (flux) of nutrients transported from the Mississippi-Atchafalaya River Basin to the Gulf of Mexico, and where do they come from within the basin? 2) What is the relative importance of specific human activities, such as agriculture, point-source discharges, and atmospheric deposition in contributing to these loads? These questions were addressed by first estimating the flux of nutrients from the Mississippi-Atchafalaya River Basin and about 50 interior basins in the Mississippi River system using measured historical streamflow and water quality data. Annual nutrient inputs and outputs to each basin were estimated using data from the National Agricultural Statistics Service, National Atmospheric Deposition Program, and point-source data provided by the USEPA. Next, a nitrogen mass balance was developed using agricultural statistics, estimates of nutrient cycling in agricultural systems, and a geographic information system. Finally, multiple regression models were developed to estimate the relative contributions of the major input sources to the flux of nitrogen and phosphorus to the Gulf of Mexico.
Resumo:
Prey-size selectivity by Steller sea lions (Eumetopias jubatus) is relevant for understanding the foraging behavior of this declining predator, but studies have been problematic because of the absence and erosion of otoliths usually used to estimate fish length. Therefore, we developed regression formulae to estimate fish length from seven diagnostic cranial structures of walleye pollock (Theragra chalcogramma) and Atka mackerel (Pleurogrammus monopterygius). For both species, all structure measurements were related with fork length of prey (r2 range: 0.78−0.99). Fork length (FL) of walleye pollock and Atka mackerel consumed by Steller sea lions was estimated by applying these regression models to cranial structures recovered from scats (feces) collected between 1998 and 2000 across the range of the Alaskan western stock of Steller sea lions. Experimentally derived digestion correction factors were applied to take into account loss of size due to digestion. Fork lengths of walleye pollock consumed by Steller sea lions ranged from 3.7 to 70.8 cm (mean=39.3 cm, SD=14.3 cm, n=666) and Atka mackerel ranged from 15.3 to 49.6 cm (mean=32.3 cm, SD=5.9 cm, n=1685). Although sample sizes were limited, a greater proportion of juvenile (≤20 cm) walleye pollock were found in samples collected during the summer (June−September) on haul-out sites (64% juveniles, n=11 scats) than on summer rookeries (9% juveniles, n=132 scats) or winter (February−March) haul-out sites (3% juveniles, n=69 scats). Annual changes in the size of Atka mackerel consumed by Steller sea lions corresponded to changes in the length distribution of Atka mackerel resulting from exceptionally strong year classes. Considerable overlap (>51%) in the size of walleye pollock and Atka mackerel taken by Steller sea lions and the sizes of these species caught by the commercial trawl fishery were demonstrated.
Resumo:
I simulated somatic growth and accompanying otolith growth using an individual-based bioenergetics model in order to examine the performance of several back-calculation methods. Four shapes of otolith radius-total length relations (OR-TL) were simulated. Ten different back-calculation equations, two different regression models of radius length, and two schemes of annulus selection were examined for a total of 20 different methods to estimate size at age from simulated data sets of length and annulus measurements. The accuracy of each of the twenty methods was evaluated by comparing the back-calculated length-at-age and the true length-at-age. The best back-calculation technique was directly related to how well the OR-TL model fitted. When the OR-TL was sigmoid shaped and all annuli were used, employing a least squares linear regression coupled with a log-transformed Lee back-calculation equation (y-intercept corrected) resulted in the least error; when only the last annulus was used, employing a direct proportionality back-calculation equation resulted in the least error. When the OR-TL was linear, employing a functional regression coupled with the Lee back-calculation equation resulted in the least error when all annuli were used, and also when only the last annulus was used. If the OR-TL was exponentially shaped, direct substitution into the fitted quadratic equation resulted in the least error when all annuli were used, and when only the last annulus was used. Finally, an asymptotically shaped OR-TL was best modeled by the individually corrected Weibull cumulative distribution function when all annuli were used, and when only the last annulus was used.