Genetic network and breeding patterns of a sicklefin lemon shark (Negaprion acutidens) population in the Society Islands, French Polynesia

Abstract

Human pressures have put many top predator populations at risk of extinction. Recent years have seen alarming declines in sharks worldwide, while their resilience remains poorly understood. Studying the ecology of small populations of marine predators is a priority to better understand their ability to withstand anthropogenic and environmental stressors. In the present study, we monitored a naturally small island population of 40 adult sicklefin lemon sharks in Moorea, French Polynesia over 5 years. We reconstructed the genetic relationships among individuals and determined the population's mating system. The genetic network illustrates that all individuals, except one, are interconnected at least through one first order genetic relationship. While this species developed a clear inbreeding avoidance strategy involving dispersal and migration, the small population size, low number of breeders, and the fragmented environment characterizing these tropical islands, limits its complete effectiveness.

Figure 1. Genetic network of the sicklefin lemon shark population from Moorea and Bora Bora.

(A) Map of the study location. (B) The genetic network of adult lemon sharks. Each individual is indicated by a node labelled by shark ID. Circles and squares indicate females and males respectively and symbol size is indicative of the body length of the shark. Node colour corresponds to the three defined residency groups. Dyads sharing a first-order genetic relationship are connected by a line, with line thickness indicating the strength of the genetic relationship (proportional to R values). A ‘spring embedding’ algorithm with node repulsion for laying out the nodes’ positions [38] was used to cluster densely connected nodes together with less connected nodes placed around the edge. (C) Genetic degree (number of first-order genetic relationships an individual has) distribution within the population.

Figure 2. Inference of reproductive cycle from underwater surveys.

(A–D) A two-year reproductive cycle as displayed by female F11 which was pregnant in 2007 (A), then entered in a resting period (B) and mated in 2008 as shown by dermal bite wounds on its flanks (C), and was pregnant again in 2009 (D). (E–F) Female F01 is pregnant in 2008 (E) and is followed by males M10 and M31 in a courtship behavior just after parturition in 2008 (F).

Figure 3. Female reproduction inferred from parentage assignment.

Litters are shown by years for each female with the assigned father(s) and juvenile(s). Sampled individual adult sharks are indicated in bold. Mothers and fathers inferred through genotype reconstruction by the program COLONY are identified by #ID and *ID, respectively. Colour of juveniles refers to their sampling nursery site (Figure S1). Note that juvenile Tet5 was sampled in 2008 in Tetiaroa but was assigned to the birth year 2007 due to its size (110 cm) corresponding to an age-1 juvenile, while subadult Sub1 was sampled in 2008 at the size of 125 cm and subsequently assigned to year of birth 2006. Finally, Tet1 was assigned to an unknown year as we were not able to determine its year of birth.

Figure 4. Patterns of distribution in internal relatedness values (IR).

(A) IR values across the maturity stage of individuals (categories: juvenile < 100 cm, immature = 100-199 cm and mature > 200 cm). (B) IR values of newborn sharks (cohorts) across years. Box plots show the median (line within the boxes), mean (white diamond) and interquartile ranges IQR (boxes). Raw data points are indicated by black circles.