156 resultados para fonction distance


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Monitoring the abundances of prey is important for informing the management of threatened and endangered predators. We evaluated the usefulness of faecal counts and distance sampling for monitoring the abundances of rusa deer Rusa timorensis, feral pig Sus scrofa and water buffalo Bubalus bubalis, the three key prey of the Komodo dragon Varanus komodoensis, at 11 sites on five islands in and around Komodo National Park, eastern Indonesia. We used species-specific global detection functions and cluster sizes (i.e. multiple covariates distance sampling) to estimate densities of rusa deer and feral pig, but there were too few observations to estimate densities of water buffalo. Rusa deer densities varied from from 2.5 to 165.5 deer/km2 with coefficients of variation (CVs) of 15-105%. Feral pig densities varied from 0.0 to 25.2 pigs/km 2 with CVs of 25-106%. There was a positive relationship between estimated faecal densities and estimated population densities for both rusa deer and feral pig: the form of the relationship was non-linear for rusa deer, but there was similar support for linear and non-linear relationships for feral pig. We found that faecal counts were more useful when ungulate densities were too low to estimate densities with distance sampling. Faecal count methods were also easier for field staff to conduct than distance sampling. Because spatial and temporal variation in ungulate density is likely to influence the population dynamics of the Komodo dragon, we recommend that annual monitoring of ungulates in and around Komodo National Park be undertaken using distance sampling and faecal counts. The relationships reported here will also be useful for managers establishing monitoring programmes for feral pig, rusa deer and water buffalo elsewhere in their native and exotic ranges.

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PURPOSE: To describe the age-specific and gender-specific rates of blindness and visual impairment in urban adults aged 40 years and older. METHODS: A population-based sample of residents was recruited. Presenting and best-corrected distance visual acuities were assessed. Functional near vision was measured at each participant's preferred distance. Visual field examination was performed with a Humphrey Field Analyzer (HFA); those unable to perform the field analyzer test attempted a Bjerrum screen or confrontation field. RESULTS: The study population comprised 3,271 residents (83% of eligible) from ages 40 to 98 years; 54% were women. Overall, 56% of the study population wore distance correction; this was significantly lower in men but higher in the older age groups. Age-adjusted rates of blindness were 0.066% in men and 0.170% in women. Vision with current correction improved after refraction by gender and age. Direct age-standardized rates of functional near vision did not vary significantly by gender. Forty-six people had significant visual field loss in their better eye. The proportion of participants with constriction of the visual field to within 20 degrees of fixation was similar for men and women when controlled for age (odds ratio, 0.81; 95% confidence interval, 0.44 to 1.49) but increased significantly with age controlled for gender. Visual field abnormalities were detected in 548 right eyes (17%) and 533 left eyes (16%). CONCLUSIONS: Although overall rates of blindness because of visual acuity loss were relatively low, nearly three times more people had visual impairment because of visual field loss than visual acuity loss. These results highlight the need to target blindness prevention programs to the aging population, with a special emphasis on women.

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The purpose of the present study was to examine the reliability of middle distance cycling time trials using fast-, even-, and slow-starts. Eighteen endurance-trained male cyclists [mean ± standard deviation; VO2peak 63.1 ± 6.1 mL⋅kg-1⋅min-1] performed nine cycling time trials where the total external work (96.5 ± 11.2 kJ) was identical to the better of two, 5-minute habituation time trials. Power output during the first quarter of the time-trials (24.1 ± 2.8 kJ) was fixed to induce fast-, even- or slow-starting strategies (60, 75 and 90 s, respectively). In consecutive sessions, participants performed three trials of each pacing condition although the order of these pacing conditions was counterbalanced. Average power output and performance time were unaffected by trial number in the fast- (P = 0.60), even- (P = 0.18) and slow-start (P = 0.53) trials. In all three pacing conditions, average power output was highly reliable and similar between trial 1 to 2 and trial 2 to 3 in fast- (standard error of measurement; SEM=8.3 and 8.2W), even (coefficient of variation; CV=2.8 and 2.4%) and slow-start (CV=2.4 and 1.5%) trials. In conclusion, the reproducibility of 5-min cycling time trials is unaffected by starting strategy and is acceptable following two selfpaced habituation trials. Research examining the influence of pacing strategies may therefore be conducted without the need for familiarisation trials using each individual pacing condition.