7 resultados para thermodynamic calculation
em Aquatic Commons
Resumo:
CHAP 1 - Introduction to the Guide CHAP 2 - Solution chemistry of carbon dioxide in sea water CHAP 3 - Quality assurance CHAP 4 - Recommended standard operating procedures (SOPs) SOP 1 - Water sampling for the parameters of the oceanic carbon dioxide system SOP 2 - Determination of total dissolved inorganic carbon in sea water SOP 3a - Determination of total alkalinity in sea water using a closed-cell titration SOP 3b - Determination of total alkalinity in sea water using an open-cell titration SOP 4 - Determination of p(CO2) in air that is in equilibrium with a discrete sample of sea water SOP 5 - Determination of p(CO2) in air that is in equilibrium with a continuous stream of sea water SOP 6a - Determination of the pH of sea water using a glass/reference electrode cell SOP 6b - Determination of the pH of sea water using the indicator dye m-cresol purple SOP 7 - Determination of dissolved organic carbon and total dissolved nitrogen in sea water SOP 7 en Español - Determinacion de carbono organico disuelto y nitrogeno total disuelto en agua de mar SOP 11 - Gravimetric calibration of the volume of a gas loop using water SOP 12 - Gravimetric calibration of volume delivered using water SOP 13 - Gravimetric calibration of volume contained using water SOP 14 - Procedure for preparing sodium carbonate solutions for the calibration of coulometric CT measurements SOP 21 - Applying air buoyancy corrections SOP 22 - Preparation of control charts SOP 23 - Statistical techniques used in quality assessment SOP 24 - Calculation of the fugacity of carbon dioxide in the pure gas or in air CHAP 5 - Physical and thermodynamic data Errata - to the hard copy of the Guide to best practices for ocean CO2 measurements
Resumo:
This article discusses problems of modelling the seasonal succession of algal species in lakes and reservoirs, and the adaptive selection of certain groups of algae in response to changes in the inputs and relative concentrations of nutrients and other environmental variables. A new generation of quantitative models is being developed which attempts to translate some important biological properties of species (survival, variation, inheritance, reproductive rates and population growth) into predictions about the survival of the fittest, where ”fitness” is measured or estimated in thermodynamic terms. The concept of ”exergy” and its calculation is explored to examine maximal exergy as a measure of fitness in ecosystems, and its use for calculating changes in species composition by means of structural dynamic models. These models accomodate short-term changes in parameters that affect the adaptive responses (species selection) of algae.
Resumo:
In recent years, a decrease in the abundance of bluefish (Pomatomus saltatrix) has been observed (Fahay et al., 1999; Munch and Conover, 2000) that has led to increased interest in a better understanding the life history of the species. Estimates of several young-of-the-year (YOY) life history characteristics, including the importance and use of estuaries as nursery habitat (Kendall and Walford, 1979) and size-dependant mortality (Hare and Cowen, 1997), are reliant upon the accuracy of growth determination. By using otoliths, it is possible to use back-calculation formulae (BCFs) to estimate the length at certain ages and stages of development for many species of fishes. Use of otoliths to estimate growth in this way can provide the same information as long-term laboratory experiments and tagging studies without the time and expense of rearing or recapturing fish. The difficulty in using otoliths in this way lies in validating that 1) there is constancy in the periodicity of the increment formation, and 2) there is no uncoupling of the relationship between somatic and otolith growth. To date there are no validation studies demonstrating the relationship between otolith growth and somatic growth for bluefish. Daily increment formation in otoliths has been documented for larval (Hare and Cowen, 1994) and juvenile bluefish (Nyman and Conover, 1988). Hare and Cowen (1995) found ageindependent variability in the ratio of otolith size to body length in early age bluefish, although these differences varied between ontogenetic stages. Furthermore, there have been no studies where an evaluation of back-calculation methods has been combined with a validation of otolithderived lengths for juvenile bluefish.
Resumo:
Age and growth estimates for salmon sharks (Lamna ditropis) in the eastern North Pacific were derived from 182 vertebral centra collected from sharks ranging in length from 62.2 to 213.4 cm pre-caudal length (PCL) and compared to previously published age and growth data for salmon sharks in the western North Pacific. Eastern North Pacific female and male salmon sharks were aged up to 20 and 17 years, respectively. Relative marginal increment (RMI) analysis showed that postnatal rings form annually between January and March. Von Bertalanffy growth parameters derived from vertebral length-at-age data are L∞ =207.4 cm PCL, k=0.17/yr, and t0=−2.3 years for females (n=166), and L∞ =182.8 cm PCL, k=0.23/yr , and t0=−1.9 years for males (n=16). Age at maturity was estimated to range from six to nine years for females (median pre-caudal length of 164.7 cm PCL) and from three to five years old for males (median precaudal length of 124.0 cm PCL). Weight-length relationships for females and males in the eastern North Pacific are W=8.2 × 10_05 × L2.759 –06 × L3.383 (r2 =0.99) and W=3.2 × 10 (r2 =0.99), respectively. Our results show that female and male salmon sharks in the eastern North Pacific possess a faster growth rate, reach sexual maturity earlier, and attain greater weight-at-length than their same-sex counterparts living in the western North Pacific.
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This paper presents an algorithm and software (available from ICLARM) for estimating the possible amount of sunlight that may fall on any location of the earth, any day of the year, as might be required for ecological modelling.
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.