Loss of microsatellite diversity and low effective population size in an overexploited population of New Zealand snapper (Pagrus auratus) Lorenz Hauser*†, Greg J. Adcock*‡, Peter J. Smith§, Julio H. Bernal Ramı´rez*¶, and Gary R. Carvalho* *Molecular Ecology and Fisheries Genetics Laboratory, Department of Biological Sciences, University of Hull, Hull HU6 7RX, United Kingdom; and §National Institute of Water and Atmospheric Research, P.O. Box 14901, Wellington, New Zealand Edited by John C. Avise, University of Georgia, Athens, GA, and approved June 27, 2002 (received for review April 23, 2002) Although the effects of overfishing on species diversity and abun- ered being in danger of losing genetic diversity (8), and so there dance are well documented, threats to the genetic diversity of appears to be little cause for concern from a genetic perspective. marine fish populations have so far been largely neglected. Indeed, On the other hand, the number of fish in a population (census there seems to be little cause for concern, as even ‘‘collapsed’’ population size, N) is often much larger than the genetically stocks usually consist of several million individuals, whereas pop- effective population size (Ne), which determines the genetic ulation genetics theory suggests that only very small populations properties of a population (12). The long-term evolutionary Ne suffer significant loss of genetic diversity. On the other hand, in is often orders of magnitude smaller than current population many marine species the genetically effective population size (Ne), sizes, probably because of historic population bottlenecks, ‘‘se- which determines the genetic properties of a population, may be lective sweeps,’’ or colonization histories (13). However, recent orders of magnitude smaller than the census population size (N). evidence suggests that even the short-term Ne without consid- Here, microsatellite analyses of a time series of archived scales eration of such historical events may be very much lower than demonstrated a significant decline in genetic diversity in a New census population numbers. Especially in marine organisms, Zealand snapper population during its exploitation history. Effec- high fecundity, a strong bias in reproductive success, large tive population sizes estimated both from the decline in heterozy- variations in year class strength, and size-dependent fecundity gosity and from temporal fluctuations in allele frequency were five may reduce the effective population size by several orders of orders of magnitude smaller than census population sizes from magnitude (14). Millions of individuals may therefore be equiv- fishery data. If such low Ne͞N ratios are commonplace in marine alent to an effective population size of only hundreds or thou- species, many exploited marine fish stocks may be in danger of sands. The notion that collapsed fish stocks may lose genetic losing genetic variability, potentially resulting in reduced adapt- diversity is thus not as far-fetched as is often assumed, despite ability, population persistence, and productivity. their large spawning stock biomasses. The demonstration of changes in genetic diversity in wild populations is often complicated by the lack of suitable popu- n 1883, Thomas Huxley, then president of the Royal Society of lations for comparison. Most commercially exploited species are ILondon, declared that ‘‘the cod fishery, the herring fishery and fished wherever they occur, and thus comparisons between probably all of the great sea fisheries are inexhaustible; that is to exploited and unexploited stocks are not possible. Temporal say that nothing we do seriously affects the numbers of fish’’ (1). comparisons based on archived material such as scales, otoliths, Since then, the status of the major fisheries and its perception by and bones, on the other hand (15), are usually restricted by a lack fisheries scientists has changed considerably. Several cod and of preexploitation samples, as routine sampling is usually initi- herring fisheries have had high profile ‘‘collapses’’ in recent ated long after the onset of the commercial fishery. Here, we decades (2), and in 1997, it was estimated that 60% of the major used a collection of scales of two New Zealand snapper (Pagrus marine fisheries were either fully exploited or overexploited (3). auratus) populations, dating back in one population to the Such high levels of exploitation not only affect the abundance of beginning of exploitation, to investigate the genetic effects of target species (4) but also change the physical (5) and trophic (6) reductions in stock biomass caused by commercial fishing. structure of marine ecosystems. Among attempts to ameliorate The history of the snapper fishery in the north of New Zealand such immediate far-reaching ecological effects of fishing, there is typical for many other fisheries in the world (16, 17): yields of is usually little consideration for more long-term impacts, such the commercial fishery in Hauraki Gulf (Fig. 1), which devel- as changes in the genetic constitution of exploited species. oped in the mid 1800s, increased slowly up to the 1970s, when the Although there has been some interest in selective changes in introduction of pair trawls raised catches to 12,000 t (Fig. 2). By exploited fish populations (7), their genetic diversity is generally the mid-1980s annual catches had declined to 6,000 t, and stocks considered to be unaffected by commercial fishing, in an attitude showed signs of overfishing. During this period, the spawning that echoes Huxley’s statement of more than a century ago. stock biomass had decreased from an estimated 280,000 t to Indeed, population genetics theory suggests that genetic diver- 37,000 t, a decline by 87%, although population abundance never sity is significantly reduced only in very small populations (8), fell below 37 million individuals (17). Because of the importance and so even ‘‘collapsed’’ stocks may consist of far too many fish of the fishery and the drastic decrease in stock abundance, to show declines in genetic diversity measurable with feasible research on snapper biology started soon after World War II, not sample sizes (9). For example, the spawning stock biomass of the Newfoundland cod, whose fishery was so famously closed in 1992, remained at 22,000 t [ref. 10; 1 t (tonne) ϭ 1,000 kg], This paper was submitted directly (Track II) to the PNAS office. leaving several million fish in the population. Similarly, even †To whom reprint requests should be sent at the present address: School of Aquatic and Fishery Sciences, University of Washington, Seattle, WA 98195-5020. E-mail: lhauser@ after stock crashes and effective cessation of dependent fisheries, u.washington.edu. the stock biomass of many small pelagic species is generally still ‡Present address: Department of Zoology, University of Melbourne, Melbourne 3010, several tens of thousands of tonnes, and thus populations typically Australia. consist of tens of millions of fish (11). These population sizes are ¶Present address: Asociacion para la Defensa de la Reserva de la Macarena, Calle 29 many orders of magnitude higher than those commonly consid- No. 6-94, Piso 8, Bogota´, Colombia. 11742–11747 ͉ PNAS ͉ September 3, 2002 ͉ vol. 99 ͉ no. 18 www.pnas.org͞cgi͞doi͞10.1073͞pnas.172242899 Downloaded by guest on September 26, 2021 assessment͞plenary͞SNA࿝2&7࿝FAR࿝Apr2002.pdf). There is no, or very little, exchange between the two snapper populations, which thus experienced independent exploitation and demo- graphic histories. Allozyme variation (19), growth rates (20), and microsatellite polymorphism (21) show that the Hauraki Gulf population is part of a larger stock along the northeast coast of the North Island, whereas the Tasman Bay fish are differentiated from the Hauraki Gulf stock and appear to be isolated from other populations. A comparison between the two populations in Hauraki Gulf and Tasman Bay therefore allowed an assess- ment of the genetic effects of different exploitation histories and population sizes. Materials and Methods Molecular Work. Dried scales from 1950 to 1986 were obtained from the Ministry of Fisheries, Wellington, New Zealand, where they had been stored individually at room temperature in paper envelopes. DNA from scales was extracted in a dedicated ancient DNA laboratory by using a previously published protocol (22). Additional samples were obtained from fresh material collected in 1998, and DNA was extracted by using standard methods. Fig. 1. Map of New Zealand showing the sampling sites. DNA extracts were screened at seven microsatellite loci [Pma1, Pma2, Pma5 (23); GA2A, GA2B, GT2, GT4 (22)] on an ALF- express automated sequencer (Amersham Pharmacia Biotech). only in the heavily fished northern populations, but also in Sample sizes are presented in Table 1. hitherto less exploited stocks in the south, such as Tasman Bay in the north of the South Island. There are therefore time series Statistical Analyses. Multilocus genotypes were tested for devia- of scale samples from Tasman Bay, beginning in 1950 just after tions from Hardy–Weinberg equilibrium and for linkage dis- the commencement of the fishery, when spawning stock biomass equilibrium by using Fisher’s exact test in GENEPOP version 3.2 was essentially at natural levels, and covering the entire exploi- (24). Genetic diversity was quantified by using Nei’s (25) unbi- tation history of the stock, with a reduction in biomass by 85% ased heterozygosity (H ) and the mean number of alleles per and in numbers by 75%, and an estimated minimum popula- e locus (Na). Because the number of alleles strongly depends on tion size of 3.3 million fish in 1985 (refs. 16 and 18; Fig. 2; ref. ͞ ͞ ͞ the sample size, 30 individuals from each sample were resampled 18 is available at www.fish.govt.nz sustainability research 1,000 times [by using POPTOOLS (add-in for Microsoft Excel, written by Greg Wood, Commonwealth Scientific and Industrial Research Organization, Australia, available at www.cse.csiro. au͞CDG͞poptools͞)], so not only standardizing the mean (sam- pling without replacement), but also providing estimates of the sampling variance (95% confidence limits, obtained with re- placement).