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Sampling Costs (sampling + cost)
Selected AbstractsEvaluating capture,recapture population and density estimation of tigers in a population with known parametersANIMAL CONSERVATION, Issue 1 2010R. K. Sharma Abstract Conservation strategies for endangered species require accurate and precise estimates of abundance. Unfortunately, obtaining unbiased estimates can be difficult due to inappropriate estimator models and study design. We evaluate population,density estimators for tigers Panthera tigris in Kanha Tiger Reserve, India, using camera traps in conjunction with telemetry (n=6) in a known minimum population of 14 tigers. An effort of 462 trap nights over 42 days yielded 44 photographs of 12 adult tigers. Using closed population estimators, the best-fit model (program capture) accounted for individual heterogeneity (Mh). The least biased and precise population estimate ( (SE) []) was obtained by the Mh Jackknife 1 (JK1) [14 (1.89)] in program care -2. Tiger density ( (SE) []) per 100 km2 was estimated at 13 (2.08) when the effective trapping area was estimated using the half mean maximum distance moved (1/2 MMDM), 8.1 (2.08), using the home-range radius, 7.8 (1.59), with the full MMDM and 8.0 (3.0) with the spatial likelihood method in program density 4.1. The actual density of collared tigers (3.27 per 100 km2) was closely estimated by home-range radius at 3.9 (0.76), full MMDM at 3.48 (0.81) and spatial likelihood at 3.78 (1.54), but overestimated by 1/2 MMDM at 6 (0.81) tigers per 100 km2. Sampling costs (Rs. 450 per camera day) increased linearly with camera density, while the precision of population estimates leveled off at 25 cameras per 100 km2. At simulated low tiger densities, a camera density of 50 per 100 km2 with an effort of 8 trap nights km,2 provided 95% confidence coverage, but estimates lacked precision. [source] A cost analysis of ranked set sampling to estimate a population meanENVIRONMETRICS, Issue 3 2005Rebecca A. Buchanan Abstract Ranked set sampling (RSS) can be a useful environmental sampling method when measurement costs are high but ranking costs are low. RSS estimates of the population mean can have higher precision than estimates from a simple random sample (SRS) of the same size, leading to potentially lower sampling costs from RSS than from SRS for a given precision. However, RSS introduces ranking costs not present in SRS; these costs must be considered in determining whether RSS is cost effective. We use a simple cost model to determine the minimum ratio of measurement to ranking costs (cost ratio) necessary in order for RSS to be as cost effective as SRS for data from the normal, exponential, and lognormal distributions. We consider both equal and unequal RSS allocations and two types of estimators of the mean: the typical distribution-free (DF) estimator and the best linear unbiased estimator (BLUE). The minimum cost ratio necessary for RSS to be as cost effective as SRS depends on the underlying distribution of the data, as well as the allocation and type of estimator used. Most minimum necessary cost ratios are in the range of 1,6, and are lower for BLUEs than for DF estimators. The higher the prior knowledge of the distribution underlying the data, the lower the minimum necessary cost ratio and the more attractive RSS is over SRS. Copyright © 2005 John Wiley & Sons, Ltd. [source] THE EVOLUTION OF FILIAL CANNIBALISM AND FEMALE MATE CHOICE STRATEGIES AS RESOLUTIONS TO SEXUAL CONFLICT IN FISHESEVOLUTION, Issue 2 2000Kai Lindström Abstract., Filial cannibalism (the consumption of one's own viable offspring) is common among fish with paternal care. In this study, I use a computer simulation to study simultaneous evolution of male filial cannibalism and female mate choice. Under certain conditions, selection on parental males favors filial cannibalism. When filial cannibalism increases a male's probability to raise the current brood successfully, filial cannibalism also benefits the female. However, when egg eating is a male investment into future reproduction, a conflict between female and male interests emerges. Here I investigate how female discrimination against filial cannibals affects evolution of filial cannibalism and how different female choice criteria perform against filial cannibalism. The introduction of discriminating females makes the fixation of filial cannibalism less likely. I introduced three different female choice criteria: (1) females who could discern a male's genotype, that is, whether the male was going to eat eggs as an investment in future reproductive events; (2) energy-choosing females that preferred to mate with males who had enough energy reserves to live through the current brood cycle without consuming eggs; and (3) females that preferred to mate with already mated males, that is, males with eggs in their nest. Genotype choice never coexisted with filial cannibals at fixation and filial cannibals were unable to invade a population with genotype-choosing females. Energy choice was successful only when males had high energy reserves and were less dependent on filial cannibalism as an alternative energy source. The egg choosers frequently coexisted with the cannibals at fixation. When the female strategies were entered simultaneously, the most frequent outcome for low mate sampling costs was that both the cannibals and the egg choice was fixed and all other strategies went extinct. These results suggest that sexual conflicts may not always evolve toward a resolution of the conflict, but sometimes the stable state retains the conflict. In the present case, this was because the egg-preference strategy had a higher fitness than the other female strategies. The outcome of this simulation is similar to empirical findings. In fish with paternal care, male filial cannibalism and female preference for mates with eggs commonly co-occur. [source] Bayesian Optimal Design for Phase II Screening TrialsBIOMETRICS, Issue 3 2008Meichun Ding Summary Most phase II screening designs available in the literature consider one treatment at a time. Each study is considered in isolation. We propose a more systematic decision-making approach to the phase II screening process. The sequential design allows for more efficiency and greater learning about treatments. The approach incorporates a Bayesian hierarchical model that allows combining information across several related studies in a formal way and improves estimation in small data sets by borrowing strength from other treatments. The design incorporates a utility function that includes sampling costs and possible future payoff. Computer simulations show that this method has high probability of discarding treatments with low success rates and moving treatments with high success rates to phase III trial. [source] | |||||||||||||