Population size estimates based on GPS telemetry.
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ABSTRACT:
SUBMITTER: Fan YX
PROVIDER: S-EPMC10839658 | biostudies-literature | 2024 Jan
REPOSITORIES: biostudies-literature
Publications
Population size estimates based on GPS telemetry.
Fan Yu-Xuan YX Xie Pu-Zheng PZ Ma Chi C Chen Ting T Ye Xiao X Xu Hua-Lin HL Yang Qiong Q Fan Peng-Fei PF
Zoological research 20240101 1
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Project description:Estimating population density as precise as possible is a key premise for managing wild animal species. This can be a challenging task if the species in question is elusive or, due to high quantities, hard to count. We present a new, mathematically derived estimator for population size, where the estimation is based solely on the frequency of genetically assigned parent-offspring pairs within a subsample of an ungulate population. By use of molecular markers like microsatellites, the number of these parent-offspring pairs can be determined. The study's aim was to clarify whether a classical capture-mark-recapture (CMR) method can be adapted or extended by this genetic element to a genetic-based capture-mark-recapture (g-CMR). We numerically validate the presented estimator (and corresponding variance estimates) and provide the R-code for the computation of estimates of population size including confidence intervals. The presented method provides a new framework to precisely estimate population size based on the genetic analysis of a one-time subsample. This is especially of value where traditional CMR methods or other DNA-based (fecal or hair) capture-recapture methods fail or are too difficult to apply. The DNA source used is basically irrelevant, but in the present case the sampling of an annual hunting bag is to serve as data basis. In addition to the high quality of muscle tissue samples, hunting bags provide additional and essential information for wildlife management practices, such as age, weight, or sex. In cases where a g-CMR method is ecologically and hunting-wise appropriate, it enables a wide applicability, also through its species-independent use.
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Project description:BackgroundThe use of molecular genetic technologies for broodstock management and selective breeding of aquaculture species is becoming increasingly more common with the continued development of genome tools and reagents. Several laboratories have produced genetic maps for rainbow trout to aid in the identification of loci affecting phenotypes of interest. These maps have resulted in the identification of many quantitative/qualitative trait loci affecting phenotypic variation in traits associated with albinism, disease resistance, temperature tolerance, sex determination, embryonic development rate, spawning date, condition factor and growth. Unfortunately, the elucidation of the precise allelic variation and/or genes underlying phenotypic diversity has yet to be achieved in this species having low marker densities and lacking a whole genome reference sequence. Experimental designs which integrate segregation analyses with linkage disequilibrium (LD) approaches facilitate the discovery of genes affecting important traits. To date the extent of LD has been characterized for humans and several agriculturally important livestock species but not for rainbow trout.ResultsWe observed that the level of LD between syntenic loci decayed rapidly at distances greater than 2 cM which is similar to observations of LD in other agriculturally important species including cattle, sheep, pigs and chickens. However, in some cases significant LD was also observed up to 50 cM. Our estimate of effective population size based on genome wide estimates of LD for the NCCCWA broodstock population was 145, indicating that this population will respond well to high selection intensity. However, the range of effective population size based on individual chromosomes was 75.51 - 203.35, possibly indicating that suites of genes on each chromosome are disproportionately under selection pressures.ConclusionsOur results indicate that large numbers of markers, more than are currently available for this species, will be required to enable the use of genome-wide integrated mapping approaches aimed at identifying genes of interest in rainbow trout.
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Project description: Not available
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