Related Experiment Video
Updated: Jun 13, 2026

Development of New Methods for Quantifying Fish Density Using Underwater Stereo-video Tools
Published on: November 20, 2017
Using isolation by distance and effective density to estimate dispersal scales in anemonefish
Malin L Pinsky1, Humberto R Montes, Stephen R Palumbi
1Hopkins Marine Station, Department of Biology, Stanford University, 120 Oceanview Blvd., Pacific Grove, CA 93950, USA. mpinsky@stanford.edu
Abstract:
Robust estimates of dispersal are critical for understanding population dynamics and local adaptation, as well as for successful spatial management. Genetic isolation by distance patterns hold clues to dispersal, but understanding these patterns quantitatively has been complicated by uncertainty in effective density. In this study, we genotyped populations of a coral reef fish (Amphiprion clarkii) at 13 microsatellite loci to uncover fine-scale isolation by distance patterns in two replicate transects. Temporal changes in allele frequencies between generations suggested that effective densities in these populations are 4-21 adults/km. A separate estimate from census densities suggested that effective densities may be as high as 82-178 adults/km. Applying these effective densities with isolation by distance theory suggested that larval dispersal kernels in A. clarkii had a spread near 11 km (4-27 km). These kernels predicted low fractions of self-recruitment in continuous habitats, but the same kernels were consistent with previously reported, high self-recruitment fractions (40-60%) when realistic levels of habitat patchiness were considered. Our results suggested that ecologically relevant larval dispersal can be estimated with widely available genetic methods when effective density is measured carefully through cohort sampling and ecological censuses, and that self-recruitment studies should be interpreted in light of habitat patchiness.
Related Concept Videos
Distribution and Dispersion
Testing a Claim about Mean: Known Population SD
Estimating a population mean requires the samples to be distributed normally. The data should be collected from the randomly selected samples having no sampling bias. The sample size needed to be higher than 30, and most importantly, the population standard deviation should be already known.
In most realistic situations, the population standard deviation is often unknown, but in rare circumstances, when it...
Formation of Species
Speciation Rates

