8 resultados para model validation

em Aquatic Commons


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This report describes the working of National Centers for Coastal Ocean Service (NCCOS) Wave Exposure Model (WEMo) capable of predicting the exposure of a site in estuarine and closed water to local wind generated waves. WEMo works in two different modes: the Representative Wave Energy (RWE) mode calculates the exposure using physical parameters like wave energy and wave height, while the Relative Exposure Index (REI) empirically calculates exposure as a unitless index. Detailed working of the model in both modes and their procedures are described along with a few sample runs. WEMo model output in RWE mode (wave height and wave energy) is compared against data collected from wave sensors near Harkers Island, North Carolina for validation purposes. Computed results agreed well with the wave sensors data indicating that WEMo can be an effective tool in predicting local wave energy in closed estuarine environments. (PDF contains 31 pages)

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For the last two decades most general circulation models (GCMs) have included some kind of surface hydrology submodel. The content of these submodels is becoming increasingly complex and realistic. It is still easy to identify defects in present treatments. Yet, to improve our ability to model the contribution of land hydrology to climate and climate change, we must be concerned not with just the surface hydrology submodel per se, but also with how it works in the overall context of the GCM.

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EXTRACT (SEE PDF FOR FULL ABSTRACT): A local climate model (LCM) has been developed to simulate the modern and 18 ka climate of the southwestern United States. ... LCM solutions indicate summers were about 1°C cooler and winters 11°C cooler at 18 ka. Annual PREC increased 68% at 18 ka, with large increases in spring and fall PREC and diminished summer monsoonal PREC. ... Validation of simulations of 18 ka climate indicate general agreement with proxy estimates of climate for that time. However, the LCM estimates of summer temperatures are about 5 to 10°C higher than estimates from proxy reconstructions.

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Each year, more than 500 motorized vessel groundings cause widespread damage to seagrasses in Florida Keys National Marine Sanctuary (FKNMS). Under Section 312 of the National Marine Sanctuaries Act (NMSA), any party responsible for the loss, injury, or destruction of any Sanctuary resource, including seagrass, is liable to the United States for response costs and resulting damages. As part of the damage assessment process, a cellular automata model is utilized to forecast seagrass recovery rates. Field validation of these forecasts was accomplished by comparing model-predicted percent recovery to that which was observed to be occurring naturally for 30 documented vessel grounding sites. Model recovery forecasts for both Thalassia testudinum and Syringodium filiforme exceeded natural recovery estimates for 93.1% and 89.5% of the sites, respectively. For Halodule wrightii, the number of over- and under-predictions by the model was similar. However, where under-estimation occurred, it was often severe, reflecting the well-known extraordinary growth potential of this opportunistic species. These preliminary findings indicate that the recovery model is consistently generous to Responsible Parties in that the model forecasts a much faster recovery than was observed to occur naturally, particularly for T. testudinum, the dominant seagrass species in the region and the species most often affected. Environmental setting (i.e., location, wave exposure) influences local seagrass landscape pattern and may also play a role in the recovery dynamics for a particular injury site. An examination of the relationship between selected environmental factors and injury recovery dynamics is currently underway. (PDF file contains 20 pages.)

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This study documents validation of vertebral band-pair formation in spotted gully shark (Triakis megalopterus) with the use of fluorochrome injection and tagging of captive and wild sharks over a 21-year period. Growth and mortality rates of T. megalopterus were also estimated and a demographic analysis of the species was conducted. Of the 23 OTC (oxytetracycline) -marked vertebrae examined (12 from captive and 11 from wild sharks), seven vertebrae (three from captive and four from wild sharks) exhibited chelation of the OTC and fluoresced under ultraviolet light. It was concluded that a single opaque and translucent band pair was deposited annually up to at least 25 years of age, the maximum age recorded. Reader precision was assessed by using an index of average percent error calculated at 5%. No significant differences were found between male and female growth patterns (P>0.05), and von Bertalanffy growth model parameters for combined sexes were estimated to be L∞=1711.07 mm TL, k=0.11/yr and t0=–2.43 yr (n=86). Natural mortality was estimated at 0.17/yr. Age at maturity was estimated at 11 years for males and 15 years for females. Results of the demographic analysis showed that the population, in the absence of fishing mortality, was stable and not significantly different from zero and particularly sensitive to overfishing. At the current age at first capture and natural mortality rate, the fishing mortality rate required to result in negative population growth was low at F>0.004/ yr. Elasticity analysis revealed that juvenile survival was the principal factor in explaining variability in population growth rate.

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The long-snouted seahorse (Hippocampus guttulatus) (Cuvier, 1829), was used to validate the pre-dictive accuracy of three progressively realistic models for estimating the realized annual fecundity of asyn-chronous, indeterminate, multiple spawners. Underwater surveys and catch data were used to estimate the duration of the reproductive season, female spawning frequency, male brooding frequency, and batch fecun-dity. The most realistic model, a generalization of the spawning fraction method, produced unbiased estimates of male brooding frequency (mean ±standard deviation [SD]=4.2 ±1.6 broods/year). Mean batch fecundity and realized annual fecundity were 213.9 (±110.9) and 903.6 (±522.4), respectively. However, females prepared significantly more clutches than the number of broods produced by males. Thus, methods that infer spawning frequency from patterns in female egg production may lead to significant overestimates of realized annual fecundity. The spawning fraction method is broadly applicable to many taxa that exhibit parental care and can be applied nondestructively to species for which conservation is a concern.

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The purpose of this study was to validate aging results of juvenile Shortfin Mako (Isurus oxyrinchus) by vertebral band counts. Vertebrae of 29 juvenile Shortfin Mako marked with oxytetracycline (OTC) were obtained from tag-recapture activities to determine centrum growth-band deposition. Tagging occurred off southern California from 1996 to 2010, and time at liberty of the 29 sharks ranged from 4 months to 4.4 years (mean=1.3 years). Growth information also was obtained from length-frequency modal analyses (MULTIFAN and MIXDIST) by using a 29-year data set of commercial and research catch data, in addition to a tag-recapture growth model (e.g, the GROTAG model). For vertebrae samples used for age validation, shark size at time of release ranged from 79 to 142 cm fork length (FL) and from 98 to 200 cm FL at recapture. Results from band counts of vertebrae distal to OTC marks indicate 2 band pairs (2 translucent and 2 opaque) are formed each year for Shortfin Mako of the size range examined. Length-frequency analyses identified 3 age class modes. Growth rate estimates from 26.5 to 35.5 cm/year were calculated for the first age-class mode (85 cm FL) and from 22.4 to 28.6 cm/year for the second age-class mode (130 cm FL). Results from the tag-recapture growth model revealed fast growth during time at liberty for tagged fish of the 2 youngest age classes. Collectively, these methods suggest rapid growth of juvenile Shortfin Mako in the southern California study area and indicate biannual deposition of growth bands in vertebrae for the first 5 years.

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EXTRACT (SEE PDF FOR FULL ABSTRACT): Current projections of the response of the biosphere to global climatic change indicate as much as 50 to 90% spatial displacement of extratropical biomes. The mechanism of spatial shift could be dominated either by competitive displacement of northern biomes by southern biomes or by drought-induced dieback of areas susceptible to change. The current suite of global biosphere models cannot distinguish between these two processes, hence the need for a mechanistically based biome model. The first steps have been taken toward development of a rule-based, mechanistic model of regional biomes at a continental scale. ... The model is in an early stage of development and will require several enhancements, including: explicit simulation of potential evapotranspiration, extension to boreal and tropical biomes, a shift from steady-state to transient dynamics, and validation on other continents.