A Capture-Recapture Design Robust to Unequal Probability of Capture

1982 ◽  
Vol 46 (3) ◽  
pp. 752 ◽  
Author(s):  
Kenneth H. Pollock
Keyword(s):  
Unequal Probability ◽  
Capture Recapture ◽  
Probability Of Capture

scholarly journals Sampling designs matching species biology produce accurate and affordable abundance indices

2013 ◽  
Author(s):  
Grant Harris ◽  
Sean Farley ◽  
Gareth J Russell ◽  
Matthew J Butler ◽  
Jeff Selinger
Keyword(s):  
Expert Opinion ◽  
Equal Probability ◽  
Sampling Frame ◽  
Brown Bears ◽  
Encounter Rates ◽  
Unequal Probability ◽  
Targeted Sampling ◽  
Abundance Estimates ◽  
Abundance Indices ◽  
Probability Of Capture

Wildlife biologists often use grid-based designs to sample animals and generate abundance estimates. Although sampling in grids is theoretically sound, in application, the method can be logistically difficult and expensive when sampling elusive species inhabiting extensive areas. These factors make it challenging to sample animals and meet the statistical assumption of all individuals having an equal probability of capture. Violating this assumption biases results. Does an alternative exist? Perhaps by sampling only where resources attract animals (i.e. targeted sampling), it would provide accurate abundance estimates more efficiently and affordably. However, biases from this approach would also arise if individuals have an unequal probability of capture, especially if some failed to visit the sampling area. Since most biological programs are resource limited, and acquiring abundance data drives many conservation and management applications, it becomes imperative to identify economical and informative sampling designs. Therefore, we evaluated abundance estimates generated from grid and targeted sampling designs using simulations based on geographic positioning system (GPS) data from 42 Alaskan brown bears (Ursus arctos). Migratory salmon drew brown bears from the wider landscape, concentrating them at anadromous streams. This provided a scenario for testing the targeted approach. Grid and targeted sampling varied by trap amount, location (traps placed randomly, systematically or by expert opinion), and traps stationary or moved between capture sessions. We began by identifying when to sample, and if bears had equal probability of capture. We compared abundance estimates against seven criteria: bias, precision, accuracy, effort, plus encounter rates, and probabilities of capture and recapture. One grid (49 km2 cells) and one targeted configuration provided the most accurate results. Both placed traps by expert opinion and moved traps between capture sessions, which raised capture probabilities. The grid design was least biased (-10.5%), but imprecise (CV 21.2%), and used most effort (16,100 trap-nights). The targeted configuration was more biased (-17.3%), but most precise (CV 12.3%), with least effort (7,000 trap-nights). Targeted sampling generated encounter rates four times higher, and capture and recapture probabilities 11% and 60% higher than grid sampling, in a sampling frame 88% smaller. Bears had unequal probability of capture with both sampling designs, partly because some bears never had traps available to sample them. Hence, grid and targeted sampling generated abundance indices, not estimates. Overall, targeted sampling provided the most accurate and affordable design to index abundance. Targeted sampling may offer an alternative method to index the abundance of other species inhabiting expansive and inaccessible landscapes elsewhere, provided their attraction to resource concentrations.

scholarly journals Optimal sampling design for spatial capture-recapture

2020 ◽  
Author(s):  
Gates Dupont ◽  
J. Andrew Royle ◽  
Muhammad Ali Nawaz ◽  
Chris Sutherland
Keyword(s):  
Sampling Design ◽  
Spatial Configuration ◽  
Optimal Sampling ◽  
Density Estimates ◽  
Practical Applications ◽  
Industry Standard ◽  
Optimal Sampling Design ◽  
Capture Recapture ◽  
Spatial Locations ◽  
Probability Of Capture

AbstractSpatial capture-recapture (SCR) has emerged as the industry standard for estimating population density by leveraging information from spatial locations of repeat encounters of individuals. The precision of density estimates depends fundamentally on the number and spatial configuration of traps. Despite this knowledge, existing sampling design recommendations are heuristic and their performance remains untested for most practical applications. To address this issue, we propose a genetic algorithm that minimizes any sensible, criteria-based objective function to produce near-optimal sampling designs. To motivate the idea of optimality, we compare the performance of designs optimized using three model-based criteria related to the probability of capture. We use simulation to show that these designs out-perform those based on existing recommendations in terms of bias, precision, and accuracy in the estimation of population size. Our approach allows conservation practitioners and researchers to generate customized and improved sampling designs for wildlife monitoring.

On the reliability of enumeration for mark and recapture census of voles

1976 ◽  
Vol 54 (6) ◽  
pp. 1019-1024 ◽  
Author(s):  
Ray Hilborn ◽  
James A. Redfield ◽  
Charles J. Krebs
Keyword(s):  
Computer Simulation ◽  
Population Size ◽  
Individual Variation ◽  
Population Parameters ◽  
Small Rodents ◽  
Capture Recapture ◽  
Sampling Intervals ◽  
Average Individual ◽  
Probability Of Capture

Some studies of populations in small rodents rely on enumeration of individuals to provide an estimate of population size. A computer simulation of the capture–recapture process was used to examine the influence of five population parameters on the reliability of enumeration. Enumeration is shown to be insensitive to population size, survival between sampling intervals, and individual variation in the probability of capture. Enumeration is sensitive to the probability of capture; if the probability of capture for the average individual falls below 0.5, the enumeration technique provides a poor estimate of population size. Enumeration is also extremely sensitive to reduced probabilities of capture for unmarked animals. Data from capture–recapture studies of five species of Microtus were used in the computer simulation, and it was concluded for these five species that enumerated populations are at least 10–20% smaller than the actual populations.

scholarly journals Sampling designs matching species biology produce accurate and affordable abundance indices

2013 ◽  
Author(s):  
Grant Harris ◽  
Sean Farley ◽  
Gareth J Russell ◽  
Matthew J Butler ◽  
Jeff Selinger
Keyword(s):  
Expert Opinion ◽  
Equal Probability ◽  
Sampling Frame ◽  
Brown Bears ◽  
Encounter Rates ◽  
Unequal Probability ◽  
Targeted Sampling ◽  
Abundance Estimates ◽  
Abundance Indices ◽  
Probability Of Capture

Wildlife biologists often use grid-based designs to sample animals and generate abundance estimates. Although sampling in grids is theoretically sound, in application, the method can be logistically difficult and expensive when sampling elusive species inhabiting extensive areas. These factors make it challenging to sample animals and meet the statistical assumption of all individuals having an equal probability of capture. Violating this assumption biases results. Does an alternative exist? Perhaps by sampling only where resources attract animals (i.e. targeted sampling), it would provide accurate abundance estimates more efficiently and affordably. However, biases from this approach would also arise if individuals have an unequal probability of capture, especially if some failed to visit the sampling area. Since most biological programs are resource limited, and acquiring abundance data drives many conservation and management applications, it becomes imperative to identify economical and informative sampling designs. Therefore, we evaluated abundance estimates generated from grid and targeted sampling designs using simulations based on geographic positioning system (GPS) data from 42 Alaskan brown bears (Ursus arctos). Migratory salmon drew brown bears from the wider landscape, concentrating them at anadromous streams. This provided a scenario for testing the targeted approach. Grid and targeted sampling varied by trap amount, location (traps placed randomly, systematically or by expert opinion), and traps stationary or moved between capture sessions. We began by identifying when to sample, and if bears had equal probability of capture. We compared abundance estimates against seven criteria: bias, precision, accuracy, effort, plus encounter rates, and probabilities of capture and recapture. One grid (49 km2 cells) and one targeted configuration provided the most accurate results. Both placed traps by expert opinion and moved traps between capture sessions, which raised capture probabilities. The grid design was least biased (-10.5%), but imprecise (CV 21.2%), and used most effort (16,100 trap-nights). The targeted configuration was more biased (-17.3%), but most precise (CV 12.3%), with least effort (7,000 trap-nights). Targeted sampling generated encounter rates four times higher, and capture and recapture probabilities 11% and 60% higher than grid sampling, in a sampling frame 88% smaller. Bears had unequal probability of capture with both sampling designs, partly because some bears never had traps available to sample them. Hence, grid and targeted sampling generated abundance indices, not estimates. Overall, targeted sampling provided the most accurate and affordable design to index abundance. Targeted sampling may offer an alternative method to index the abundance of other species inhabiting expansive and inaccessible landscapes elsewhere, provided their attraction to resource concentrations.

From the Oort cloud to Halley-type comets

1999 ◽  
Vol 173 ◽  
pp. 327-338 ◽  
Author(s):  
J.A. Fernández ◽  
T. Gallardo
Keyword(s):  
Total Population ◽  
Complex Function ◽  
Dynamical Evolution ◽  
Oort Cloud ◽  
Capture Process ◽  
Influx Rate ◽  
Short Period ◽  
Dynamical Properties ◽  
Orbital Periods ◽  
Probability Of Capture

AbstractThe Oort cloud probably is the source of Halley-type (HT) comets and perhaps of some Jupiter-family (JF) comets. The process of capture of Oort cloud comets into HT comets by planetary perturbations and its efficiency are very important problems in comet ary dynamics. A small fraction of comets coming from the Oort cloud − of about 10−2− are found to become HT comets (orbital periods < 200 yr). The steady-state population of HT comets is a complex function of the influx rate of new comets, the probability of capture and their physical lifetimes. From the discovery rate of active HT comets, their total population can be estimated to be of a few hundreds for perihelion distancesq <2 AU. Randomly-oriented LP comets captured into short-period orbits (orbital periods < 20 yr) show dynamical properties that do not match the observed properties of JF comets, in particular the distribution of their orbital inclinations, so Oort cloud comets can be ruled out as a suitable source for most JF comets. The scope of this presentation is to review the capture process of new comets into HT and short-period orbits, including the possibility that some of them may become sungrazers during their dynamical evolution.

Capture recapture électroniques en phosphorescence

1952 ◽  
Vol 12 (7) ◽  
pp. 749-801 ◽  
Author(s):  
Daniel Curie
Keyword(s):  
Capture Recapture

Electrical Anisotropy of Thin Metal Films Growing on Dielectric Substrates

2002 ◽  
Vol 7 (2) ◽  
pp. 45-52
Author(s):  
L. Jakučionis ◽  
V. Kleiza
Keyword(s):  
Magnetic Field ◽  
Thin Films ◽  
Uniaxial Anisotropy ◽  
Metal Films ◽  
Thin Layers ◽  
Electrical Anisotropy ◽  
Electrical Field ◽  
Dielectric Substrates ◽  
Unequal Probability ◽  
Conductive Thin Films

Electrical properties of conductive thin films, that are produced by vacuum evaporation on the dielectric substrates, and which properties depend on their thickness, usually are anisotropic i.e. they have uniaxial anisotropy. If the condensate grow on dielectric substrates on which plane electrical field E is created the transverse voltage U⊥ appears on the boundary of the film in the direction perpendicular to E. Transverse voltage U⊥ depends on the angle γ between the applied magnetic field H and axis of light magnetisation. When electric field E is applied to continuous or grid layers, U⊥ and resistance R of layers are changed by changing γ. It means that value of U⊥ is the measure of anisotropy magnitude. Increasing voltage U0 , which is created by E, U⊥ increases to certain magnitude and later decreases. The anisotropy of continuous thin layers is excited by inequality of conductivity tensor components σ0 ≠ σ⊥. The reason of anisotropy is explained by the model which shows that properties of grain boundaries are defined by unequal probability of transient of charge carrier.

An Urn Model for the Multi-Sample Capture/Recapture Sequential Tagging Process.

1987 ◽  
Author(s):  
Jose G. Leite ◽  
Carlos A. De Braganca Pereira
Keyword(s):  
Urn Model ◽  
Capture Recapture
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