Abstract
Dispersal is one of the main determining factors of population structure. In the marine habitat, well-connected populations with large numbers of reproducing individuals are common but even so population structure can exist on a small-scale. Variation in dispersal patterns between populations or over time is often associated to geographic distance or changing oceanographic barriers. Consequently, detecting structure and variation in dispersal on a fine-scale within marine populations still remains a challenge. Here we propose and use a novel approach of combining a clustering model, early-life history trait information from fish otoliths, spatial coordinates and genetic markers to detect very fine-scale dispersal patterns. We collected 1573 individuals (946 adults and 627 juveniles) of the black-faced blenny across a small-scale (2 km) coastline as well as at a larger-scale area (<50 kms). A total of 178 single nucleotide polymorphism markers were used to evaluate relatedness patterns within this well-connected population. In our clustering models we categorized SHORT-range dispersers to be potential local recruits based on their high relatedness within and low relatedness towards other spatial clusters. Local retention and/or dispersal of this potential local recruitment varied across the 2 km coastline with higher frequency of SHORT-range dispersers towards the southwest of the area for adults. An inverse pattern was found for juveniles, showing an increase of SHORT-range dispersers towards the northeast. As we rule out selective movement and mortality from one year to the next, this pattern reveals a complex but not full genetic mixing, and variability in coastal circulation is most likely the main driver of this fine-scale chaotic genetic patchiness within this otherwise homogeneous population. When focusing on the patterns within one recruitment season, we found large differences in temperatures (from approx. 17 °C to 25 °C) as well as pelagic larval duration (PLD) for juveniles from the beginning of the season and the end of the season. We were able to detect fine-scale differences in LONG-range juvenile dispersers, representing distant migrants, depending on whether they were born at the beginning of the season with a longer PLD, or at the end of the reproductive season. The ability to detect such fine-scale dispersal patchiness will aid in our understanding of the underlying mechanisms of population structuring and chaotic patchiness in a wide range of species even with high potential dispersal abilities.
Highlights
In marine ecosystems, larval dispersal and recruitment are the main processes determining population structure of species and understanding how they maintain connectivity is crucial for effective management[1]
Dispersal patterns depend on pelagic larval duration (PLD)[8], reproductive output[9], ocean currents[10] or localized eddies and oceanographic retention patterns[11,12]
Some studies have demonstrated the existence of familial structure with marked genetic distances between recruitment cohorts; the lack of larval mixing during the planktonic period can lead to chaotic genetic patchiness[27,28,29]
Summary
Larval dispersal and recruitment are the main processes determining population structure of species and understanding how they maintain connectivity is crucial for effective management[1]. Www.nature.com/scientificreports and little population structure[3] This paradigm has been largely disproven as many recent studies have revealed that genetic population structure can exist across even small spatial scales and self-recruitment is often larger than previously believed[4,5]. Some studies have demonstrated the existence of familial structure with marked genetic distances between recruitment cohorts; the lack of larval mixing during the planktonic period can lead to chaotic genetic patchiness[27,28,29]. Genetic structure on a very fine-scale has not been investigated and we here present a novel approach to understanding recruitment patterns leading to population structuring. We apply novel and easy-interpretable clustering procedures to genetic relatedness information in order to infer fine-scale genetic structuring and dispersal in large populations
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