SEARCH

SEARCH BY CITATION

Keywords:

  • bottleneck;
  • colonization;
  • human migration;
  • microsatellite;
  • rapid evolution;
  • sexual signal;
  • Teleogryllus oceanicus

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References

Teleogryllus oceanicus, a cricket native to Australia, was introduced to Hawaii where it encounters a novel natural enemy responsible for their recent rapid evolutionary loss of singing ability. To explore how genetic diversity varies across their broad range, their mode of introduction to Hawaii and nonadaptive influences on the sexual signalling system, we assessed variation at seven microsatellite loci in 19 Australian and island populations. Genetic variability was highest in Australia, intermediate in Oceania and lowest in Hawaii, and differentiation among local populations was a clear function of geographical distance. Hawaiian populations are most closely related to those from the Society Islands and Cook Islands, and a neighbour-joining tree based on DA is consistent with movement by Polynesian settlers. We found evidence of bottlenecks in six island populations (including three Hawaiian populations), supporting previous findings in which bottlenecks were implicated in the crickets’ loss of singing ability.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References

‘Historical’ or nonadaptive events play an important role in determining the degree of genetic variation present in populations at colonization. Island populations are typically founded by very few individuals, resulting in a ‘founder effect’ (Mayr, 1942), with subsequent genetic reorganization by recombination and drift. As rare alleles are lost and allele frequencies change, recently colonized populations may experience a reduction in genetic diversity relative to their sources as well as rapid differentiation from source populations (Chakraborty & Nei, 1977; Dlugosch & Parker, 2008). Selection in the novel environment can then act on the genetic variation in the new population. Under extreme conditions, colonization processes are thought to be capable of initiating reproductive isolation (founder-effect speciation; Mayr, 1942; Coyne & Orr, 2004). These effects are particularly well observed after multiple, sequential introductions, as occurs when founding populations have a broad distribution (Clegg et al., 2002). More recently, researchers have recognized that many introduced populations do not exhibit this characteristic reduction in genetic diversity, perhaps owing to multiple independent introductions, which merge among-population genetic diversity in one location (Calsbeek & Smith, 2003; Wares et al., 2005; Roman & Darling, 2007). In opposition to these forces, we expect ongoing gene flow to homogenize populations genetically (Slatkin, 1987; although recent emphasis has been placed on the ‘multifarious’ effects of gene flow, e.g. Ghalambor et al., 2007).

Colonization is associated not only with genetic drift and bottlenecks, but also with exposure of organisms to novel selection pressures, and new populations often show rapid evolution in novel environments (Reznick & Ghalambor, 2001). Sexually selected traits may be particularly amenable to rapid divergence following introduction to new environments (Shaw & Lugo, 2001; Zuk & Tinghitella, 2008), although rapid evolution of sexually selected characters has been very rarely observed empirically (Svensson & Gosden, 2007). Such traits, usually male signals and female preferences for them, should be equally as likely as others to experience genetic drift and, additionally, are subject to selection pressures such as the impacts of the environment on signal transmission, competing signallers and unintended receivers who are attracted to sexual signals (Zuk & Kolluru, 1998; Boake, 2002; Zuk & Tinghitella, 2008). Work in Dark-eyed Juncos and field crickets suggests that colonizing novel environments does indeed impact the evolution of male sexual signals (Yeh, 2004; Yeh & Price, 2004; Zuk & Tinghitella, 2008; Tinghitella & Zuk, 2009; Tinghitella et al., 2009) and female mating requirements (Kaneshiro, 1989; Shaw and Lugo, 2001; Tinghitella & Zuk, 2009). Recent rapid evolution in the sexual signal of field crickets in Hawaii (Zuk et al., 2006) affords us an opportunity to investigate the contributions that population history makes to rapid evolution following introduction to a novel environment.

The biota of the central Pacific is predominantly derived from the Western Pacific Rim or continental regions like Australia and SE Asia (Miller, 1996). Organisms colonize the Pacific region in one of the two ways: (i) by jumping from island to island in a stepping-stone fashion [as demonstrated by blackflies (Craig et al., 2001; Craig, 2003), lizards (Austin, 1999) and weevils (Claridge, 2006)] or (ii) by repeated independent colonization from a mainland source (Gillespie et al., 2008). Far east in the Pacific Ocean, the Hawaiian Islands (formed de novo by volcanic activity) are no exception, accumulating biodiversity by colonization and subsequent within and between island diversification (Gillespie & Roderick, 2002; Whittaker & Fernández- Palacios, 2007, Garb & Gillespie, 2009). Hawaii is extremely isolated (3200 km from the nearest continent), and natural colonizations are rare, being restricted to exceptional dispersers (Gressitt, 1956). Human-aided introductions, however, occur frequently, and human movement patterns may thus drive biological evolution on such islands (Hendry et al., 2000; Palumbi, 2001; Hurles et al., 2003; Stockwell et al., 2003; Streelman et al., 2004). For instance, Polynesian colonists reaching islands in the Pacific purposefully brought with them plants and animals for food and agriculture (Keast & Miller, 1996) and also likely transported others they were not aware of moving. Human-assisted introduction of these animals impacted the island ecosystems they entered in serious and often negative ways (Steadman, 1995; Steadman et al., 2002; Hurles et al., 2003). Introduced organisms, likewise, were affected as they responded to novel environmental factors and interacted with previously unencountered organisms.

Here, we investigate the genetic differentiation of Polynesian field crickets, Teleogryllus oceanicus (Orthoptera: Gryllidae), and the manner in which they moved through the Pacific to better understand the nonadaptive forces responsible for their introduction to Hawaii and the subsequent rapid evolution of their sexual signalling system. The cricket is native to northern regions of the Australian continent, found on numerous Pacific Islands, and was introduced to Hawaii sometime prior to 1877 (Kevan, 1990; Otte, 1994). Teleogryllus oceanicus may have moved through most of the Pacific via flight or floating on flotsam, but their limited flight capabilities, short generation times and the vast inter-island distances make it unlikely that they travelled to Hawaii without human intervention (Zuk et al., 1998). Intriguingly, T. oceanicus may have been moved through the Pacific intentionally with the Polynesian settlers (see Discussion). Alternatively, they may have travelled on ships in the 19th century.

The crickets’ sexual signal is divergent across their broad geographic range (Rotenberry et al., 1996; Zuk et al., 2001) and selection pressures impacting sexual signalling vary geographically. On the three Hawaiian Islands where it occurs (Oahu, Kauai and the Big Island of Hawaii), the cricket encounters a novel natural enemy, a parasitoid fly attracted to the male crickets’ song, found nowhere else in their range (Cade, 1975; Zuk et al., 1993; Lehmann, 2003). In Hawaii, males have altered song structure, diel distribution of calling and response to risk, relative to those in unparasitized portions of their range, all of which are consistent with adaptation to avoid the fly (Zuk et al., 1993, 1998, 2001; Lewkiewicz & Zuk, 2004). These differences are present in laboratory colonies as well, suggesting the parasitoid-induced adaptive evolutionary changes in signalling and behaviour. Most recently, a mutation in wing morphology on one Hawaiian Island eliminated the crickets’ singing ability altogether, rendering > 90% of males on the island of Kauai obligately mute (Zuk et al., 2006; Tinghitella, 2008). As a result of this mutation, ‘flatwing’, there is some asymmetric reproductive isolation among populations; females from six populations across the crickets’ range do not discriminate among males from different populations where song is still produced (accepting on average 83% of males in no-choice courtship trials), but accept only 9–50% of silent ‘flatwing’ males (depending on the females’ source population; Tinghitella & Zuk, 2009). If the crickets were taken to Hawaii with humans, this leads to the possibility that anthropogenic disturbance introduced the crickets to novel environments, which selected for dramatic changes in sexual signalling, and consequent reproductive isolation.

Here, we quantify the neutral genetic variation in microsatellites within and among T. oceanicus populations with three aims: (i) to evaluate genetic diversity across their range in the Pacific, (ii) to elucidate the crickets’ pattern of movement through the Pacific and (iii) to identify the genetic fingerprint of neutral processes that might influence sexual signal evolution in this group (bottlenecks and gene flow).

Methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References

Genetic analysis

Samples for DNA analysis were collected from nineteen locations in Australia and on Pacific islands (Fig. 1, Table 1) between 2004 and 2007, including eight locations in the putatively ancestral range (A = Australia), eight island populations from the portion of the range where the cricket and fly do not overlap (O = Oceania) and three Hawaiian populations from the parasitized portion of the crickets’ range (H = Hawaii). Seven of these populations were part of an earlier study of genetic distance and sensoribehavioural regression in T. oceanicus (Fullard et al., 2010). Geographic distances between sampled localities ranged from 83 km (between Cooktown and the Daintree region in eastern Australia) to 11 582 km (between Broome, Australia and Hiva Oa, Marquesas) (Tables 2 and 3). We removed one leg from each cricket, dissected out the femur muscle and stored the samples in ethanol at −80 °C until the time of DNA extraction. DNA was extracted using a standard salt extraction protocol, and neutral genetic variation was assayed at seven highly polymorphic microsatellite loci developed specifically for T. oceanicus (Beveridge & Simmons, 2005).

image

Figure 1.  Geographic distribution of nineteen Teleogryllus oceanicus populations sampled in Northern and Eastern Australia, across numerous Pacific Islands, and in their introduced range of Hawaii. In three cases (Hawaii, Fiji and the Cook Islands), multiple island populations were sampled from a given island chain.

Download figure to PowerPoint

Table 1.   Allelic diversity, allelic richness (AR), heterozygosity and bottlenecks in the nineteen Teleogryllus oceanicus populations. Samples are ordered roughly from west to east in their geographic distribution. Regions are Australia (A: mainland populations), Oceania (O: nonparasitized island populations) and Hawaii (H: parasitized island populations in the crickets’ introduced range of Hawaii). Primers are 1 = Totri 9a, 2 = Totri 54, 3 = Totri 55a, 4 = Totri 57, 5 = Totri 59 and 6 = Totri 78 (after Beveridge & Simmons, 2005). In the Allelic diversity/Allelic richness column, NA can be found above and AR below. AR is based on a minimum sample size of four diploid individuals and was calculated using fstat. bottleneck estimates heterozygote excess when compared with expected equilibrium heterozygosity. Significance of the bottleneck results was estimated by Wilcoxin signed-rank tests (P < 0.05).
SamplenAllelic diversity (NA) & AR by locusNAMean ARHEbottleneck (IAM/SMM/TPM)
123456
Australia (A)1597171109917184497   
 Carnarvon22861013811565.0650.836375+/−/−
4.8153.6745.9086.1704.6375.188
 Broome20101119151211785.5390.849887−/−/−
5.4225.4146.9796.0633.6625.692
 Darwin10657917354.9660.729798−/−/−
6.0004.3786.1336.30815.978
 Kunnunura22991313912655.1950.803631−/−/−
5.1804.8726.1716.3602.9285.659
 Cooktown2299127912584.7450.786283−/−/−
5.1604.8105.5533.9373.2545.754
 Daintree191011131089615.1760.846231−/−/−
5.4555.2806.1874.7133.9625.461
 Cairns21111019111211745.2730.837901−/−/−
5.2395.1156.9233.9254.8695.568
 Mission Beach2381016131211705.2980.838534−/−/−
5.2604.5606.8404.2965.1715.662
Oceania (O)162304577405143286   
 Efate, Vanuatu245812749454.0030.698906−/−/−
2.9183.9165.7513.8712.0825.481
 Viti Levu, Fiji2045136107454.2690.756145+/−/−
3.2513.4996.3624.1944.4113.898
 Vanua Levu, Fiji2058106117474.2920.760558−/−/−
3.1894.0655.3834.1484.6854.281
 Upolu, Samoa254711565383.5740.644544−/−/−
2.2754.1575.4203.7363.1942.660
 Atiu, Cook Islands5344343213.1820.608333−/−/−
2.9563.4003.5782.9563.4002.800
 Rarotonga, Cook Islands185510462323.8140.685892+/−/−
3.8193.2366.3333.3614.1471.988
 Moorea, Society Islands25378365323.4140.639832+/−/−
2.2624.0625.0452.4533.6992.964
 Atuona, Marquesas25119645262.5580.392766−/−/−
115.0153.7452.1082.479
Hawaii (H)73716201413980   
 Oahu24367555313.4210.623423+/−/−
2.4534.4524.1933.8862.9882.555
 Hawaii24254442212.6150.515700+/−/−
1.9793.6473.0472.9582.4441.616
 Kauai25269542282.9840.522880+/−/−
1.8224.2384.9353.2922.2051.414
Table 2.   Population pairwise differentiation (FST) among 19 populations of Teleogryllus oceanicus. Pairwise FST values were estimated as in Weir & Cockerham (1984) using genepop version 3.4 on the web.
 CarnarvonBroomeKununurrraDarwinCooktownDaintreeCairnsMission BeachVanuatuViti LevuVanua LevuSamoaAtiuRarotongaMooreaMarquesasOahuHilo
Broome0.0326                 
Kununurrra0.0284−0.006                
Darwin0.0960.02640.0089               
Cooktown0.06160.02920.02170.0498              
Daintree0.04770.02490.02340.06990.0064             
Cairns0.06010.04280.04140.08340.01180.0052            
Mission Beach0.04970.03730.03360.06980.0080.0093−0.0074           
Vanuatu0.09020.14480.14530.21840.10890.10360.09020.1168          
Viti Levu0.07560.08410.07710.15450.06720.06120.0790.0880.0729         
Vanau Levu0.07150.06790.06320.13760.03780.03650.0580.06260.08880.0042        
Samoa0.16770.18650.18860.26370.1590.13840.15730.16020.11040.10110.094       
Atiu0.16550.12380.13410.15590.14760.13020.15190.14040.24330.16320.13850.2017      
Rarotonga0.13260.13980.14550.18330.1430.11290.14190.1320.18320.12130.12880.11760.0491     
Moorea0.12590.12580.12280.18930.1380.11690.14140.13650.18130.12180.10750.10890.09560.0923    
Marquesas0.30860.31220.32240.42980.27210.26140.26980.28860.18740.22960.21370.15540.35240.28920.2241   
Oahu0.1330.13060.12970.20220.13010.13680.16790.15290.26250.16820.1630.22560.15990.12670.14720.3842  
Hilo0.18420.18740.18420.26090.17660.18470.23290.22030.30050.18040.17380.22570.18480.15430.13630.36930.0442 
Kauai0.19440.19130.18510.26250.170.1750.22180.20930.31130.18820.18440.24010.22050.14980.16760.41740.03690.027
Table 3.   Population pairwise geographic distances (km) were calculated using a surface distance calculator available at (http://www.wcrl.ars.usda.gov/cec/java/lat-long.htm).
 CarnarvonBroomeKununurrraDarwinCooktownDaintreeCairnsMission BeachVanuatuViti LevuVanua LevuSamoaAtiuRarotongaMooreaMarquesasOahuHilo
Broome775.78                 
Kununurra1866.691766.01                
Darwin2269.372087.21438.46               
Cooktown3442.713519.61772.581591.53              
Daintree3416.353512.321775.171614.1183.51             
Cairns3431.753547.871822.071678.21169.1790.44            
Mission Beach3428.083570.931863.711744.44285.74240.06116.56           
Vanuatu5674.125905.394213.544056.452465.312448.242393.792350.5          
Viti Levu6604.866866.45185.35028.073437.483421.053366.473321.72972.84         
Vanua Levu6614.597070.075381.285002.843414.343613. 063348.453518.611168.19213.81        
Samoa7826.228080.716381.86200.484618.644608. 823922.074522.242175.541221.531012.76       
Atiu8906.629288.717692.267574.645985.165960.545898.165840.093532.672578.162416.711601.53      
Rarotonga8697.099086.527501.537391.865804.55778.015714.145653.83360.412416.732264.531510.1217.24     
Moorea11443.7410181.018582.968458.546867.616844.956784.066728.014407.613443.643270.72371.39893.221095.21    
Marquesas11239.2911582.139920.269749.078164.88152. 398100.168056.755706.834735.024539.683548.732344.592559.131496.37   
Oahu10824.6310701.548993.858624.847422.037461.827464.717495.625688.185077.884889.74188.334596.354734.244441.753924.24  
Hilo11023.3210933.079208.178849.567600.097636.147634.447659.565766.755103.944908.544148.9144294578.724213.873618.07302.04 
Kauai10750.0710568.768870.578540.357318.287359.957365.187399.025638.375056.954873.014204.274678.334809.74555.914080.94181.84526.72

Each 15-μL PCR contained 1 × PCR buffer (10 mm Tris–HCl pH 8.3, 50 mm KCl), 1.5 mm or 3.5 mm MgCl2 (see Beveridge & Simmons, 2005 for details; Invitrogen, Carlsbad, CA, USA), 200 μM of each dNTP (Invitrogen), 250 nm of the forward primer (labelled and unlabelled in a ratio of 1 : 5), 250 nm of the reverse primer (Integrated DNA Technologies), 1 unit of Platinum Taq DNA polymerase (Invitrogen) and ∼10ng of DNA. PCR amplification was performed with the following cycling conditions: 94 °C for 1 min, then 30 cycles at 94 °C for 1 min, 55 °C for 1 min, and 72 °C for 1 min and finally 72 °C for 45 min. We analysed the products on an abi 3100 Genetic Analyzer and sized alleles using a LIZ internal size standard and GeneMapper V3.7(2) software (optimizing sizing by eye).

We screened 394 samples from nineteen mainland Australian and Pacific Island populations with sample sizes ranging from 5 to 25 individuals per population (Table 1). We assessed whether populations were in Hardy–Weinberg equilibrium at each locus using genepop 3.4 (Raymond & Rousset, 1995). Six loci were in equilibrium (one population per locus was out of equilibrium after Bonferroni correction), but locus Totri88a was out of equilibrium in > 70% of the populations studied. This is consistent with Beveridge & Simmons (2005) observation that this locus shows null alleles and appears to be X-linked. We therefore omitted the seventh locus, Totri88a, and concentrated our analyses on the remaining six loci that amplify cleanly and have the fewest null alleles based on Hardy–Weinberg equilibrium. This left Totri 9a, Totri 54, Totri 55a, Totri 57, Totri 59 and Totri 78. Linkage disequilibrium was assessed for each locus pair within each population and across all populations using the genotypic disequilibrium option in genepop version 3.4. Totri 9a and Totri 57 were found to be in disequilibrium, indicating the two may not segregate independently, but were only in disequilibrium in three of the 19 populations, namely Vanuatu, Samoa and Kauai. We retained both loci in this study.

Allelic diversity (NA; for each population and locus and pooled across the six loci), allelic richness (AR) and mean AR per population, expected heterozygosity (calculated using Levene’s corretion for small sample size) and a matrix of pairwise genetic distances (FST estimated by Weir & Cockerham, 1984) were produced using genepop version 3.4 (Raymond & Rousset, 1995) and fstat version 2.9.3.2 (for AR; Goudet, 1995; Tables 1 and 2). Genetic distances were then used in conjunction with population pairwise geographic distances calculated using a surface distance calculator (http://www.chemical-ecology.net/java/lat-long.htm) to test for isolation by distance using the isolde option in genepop version 3.4. A Mantel test with 1000 permutations assessed how well geographic distance estimated genetic distance. Geographic trends in the measures of genetic diversity were assessed by regressing the expected heterozygosities and allelic richnesses against longitude. Also, for the three measures of genetic diversity (HO, HE and AR), and population differentiation (FST), a group comparison according to region (Australia, Oceania, Hawaii) was performed with permutation tests in fstat. We asked whether the 19 populations had recently experienced severe reductions in effective population size using bottleneck version 1.2.02 (Piry et al., 1999). bottleneck estimates observed heterozygosity excess relative to expected equilibrium heterozygosity. We performed the tests using all three options available in bottleneck, the infinite alleles model (IAM; Kimura & Crow, 1964), stepwise mutation model (SMM; Ohta & Kimura, 1973) and the two-phase model (TPM; probability of SMM 70%, variance 30%; Di Rienzo et al., 1994), and significance was assessed with Wilcoxon signed-rank tests (P < 0.05; Table 1) (Cornuet & Luikart, 1996).

DA distances (Nei et al., 1983) were calculated based on microsatellite data for all populations with 1000 randomized permutations to assess statistical support using Microsatellite Analyser (MSA; Deiringer & Schlotterer, 2002). Takezaki & Nei (2008) demonstrated that the probability of obtaining the correct branching pattern in a tree built on microsatellite data is highest when using the standard genetic distance, DA, which is thought to increase roughly linearly with time since separation (assuming a low mutation rate, Slatkin, 1995). To assess sources for populations introduced to Hawaii and establish the likely route of Pacific colonization, relatedness trees were constructed using DA in phylip Version 3.65 (Felsenstein, 2005). The data set was first converted to phylip’s preferred format, a gene frequency format, using the program convert version 1.31 (Glaubitz, 2004). Bootstrap values (500 replications) were calculated using seqboot, and unrooted consensus neighbour-joining trees were obtained using the following sequence: seqboot, gendist, neighbor and drawtree. Trees were visualized with the software TreeEdit version 1.0 (Rambaut & Charleston, 2000). Finally, global migration was estimated using the private alleles method (Barton & Slatkin, 1986) in genepop version 3.4 on the web.

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References

Six highly polymorphic loci with 14–31 alleles per locus were sampled in 19 populations across the broad Pacific range of T. oceanicus. Alleles per locus were as follows: Totri 9a had 14, Totri 54 had 21, Totri 55 had 31, Totri 57 had 26, Totri 59 had 25, and Totri 78 had 14. Allelic diversity (NA) and AR decreased roughly from west to east, both when observed at individual loci and when summed (or averaged for AR) across the six loci (Table 1), consistent with a spread of the cricket from their native Australia to the islands of the Pacific via a series of serial bottlenecks. NA was highest in the Australian region (which includes eight Australian populations distributed from the mid-coastal regions of Western Australia to the NE coast), intermediate in Oceania and lowest in the Hawaiian Islands (Table 1). The lowest levels of allelic diversity were found on Atiu in the Cook Islands and the Big Island of Hawaii; each had only 21 alleles summed across the six loci. Low allelic diversity in Atiu is likely due, at least partially, to the small number of samples collected there. The NW Australian population of Broome was the most diverse, with 78, followed by Cairns with 74 alleles. The highest allele richness, with an average of 5.539 alleles, per locus was found in Broome and the lowest in the Marquesas, with an average of 2.558 alleles (Table 1). We found evidence of only one allele at two loci in the Marquesas population (at Totri 9a, Totri 54) and at one locus in the Darwin, Australia population (Totri 59).

Levels of gene diversity (HE) within populations ranged from a high of 0.849 in the Western Australian population of Broome to a low of 0.393 in the island population of Hiva Oa, Marquesas (Table 1). When testing for geographical trends in genetic diversity, the highest genetic diversities were found in the western portion of the crickets’ range, and diversity (measured as both HE and AR) decreased from west to east (R2 = 0.7278, F1,16 = 42.78, P < 0.001 and R2 = 0.8959, F1,16 = 137.77, < 0.001 respectively). Figure 2 demonstrates the characteristic reduction in allelic diversity noted across the crickets’ distribution using the distribution of alleles at just one representative locus, Totri 9a. Indeed, island populations appear to have fewer alleles at each locus, and the characteristic bottleneck ‘shape’ is apparent.

image

Figure 2.  Allele size distribution of a representative Teleogryllus oceanicus locus (Totri 9a) across the crickets’ broad distribution. All plots use the same scale. There is a characteristic reduction in allelic diversity, as you move from west to east in the crickets’ distribution consistent with their introduction to Pacific islands from their native range in Australia. Notice the characteristic ‘bottleneck effect’ in island populations. Allelic diversity is significantly lower in the Oceania region relative to Australia and in the Hawaiian region relative to Oceania.

Download figure to PowerPoint

On average, the Australian region had significantly higher AR and gene diversity than the Oceania and Hawaii regions (Table 4) following permutation tests in fstat. Pairwise FST and observed heterozygosity (HO), however, did not differ significantly among the three regions (P = 0.218 and P = 0.148 respectively, Table 4). That Australian populations are not more genetically distinct from one another than Hawaiian populations, for instance, is consistent with the low pairwise FST values found among Australian populations (despite the vast inter-population distances) and within island chains (see below).

Table 4.   Comparison of allelic richness (AR), observed heterozygosity (HO), gene diversity (HE) and levels of differentiation (FST) among populations for the Australian, Oceanic and Hawaiian regions of Teleogryllus oceanicus distribution.
 N (populations)AR**HOHE*FST
  1. Significance levels were *P < 0.01, **P < 0.001 following permutation tests in fstat.

Australia85.1560.6890.8300.030
Oceania83.6380.5630.6410.146
Hawaii33.0070.5700.5570.037

Pairwise genetic differentiation (FST) estimated as in Weir & Cockerham (1984) ranged from a low of 0.0042 (between two Fijian islands of Viti Levu and Vanua Levu) to a high of 0.4374 between the Hawaiian island of Kauai and the Marquesas (an island nation 4080 km SE of Hawaii; Tables 2 and 3). In three locations, we were able to sample multiple islands within an island chain (Atiu and Rarotonga in the Cook Islands, Viti Levu and Vanua Levu in Fiji and Oahu, Hawaii and Kauai in Hawaii). In all three cases, pairwise population differentiation values within the island chains were among the lowest we observed (ranging from 0.0042 to 0.0491). Pairwise population differentiation also remains low among Australian populations, ranging from 0.0052 to 0.0616, despite the vast geographic distances separating these populations (up to 3571 km). Marquesas consistently returned some of the largest measures of pairwise population differentiation we observed, ranging from a low of 0.1534 with Samoa (3548 km away) to 0.4374 with Kauai, Hawaii (4080 km NW of the Marquesas).

We found a strong pattern of isolation by distance (as assessed by Mantel test with 1000 permutations in genepop V3.4 isolde) in the data set, indicating restricted gene flow among the samples in accordance with geographic distances (Spearman Rank Correlation, r = 1.0, N (total comparisons) = 153, P = 0.000; Fig. 3). The 19 unique, or private, alleles in the data set were distributed among the following eight populations (number of private alleles per population indicated in parentheses): Cairns (5), Broome (2), Daintree (2), Carnarvon (1), Mission Beach (1), Cooktown (1), Samoa (5) and Viti Levu (1). We did, however, find evidence of ongoing gene flow across the crickets’ range. Global migration was assessed using the private alleles method (Barton & Slatkin, 1986), and the number of migrants was estimated to be 2.595 per generation after correction for sample size.

image

Figure 3.  Isolation by distance. There is a strong pattern of isolation by distance in the data set indicating restricted gene flow among the samples in accordance with geographic distances. Points circled represent relationships between the Marquesas population and other mainland Australian or island populations. These population pairs experienced the highest genetic distances, although they are not always particularly geographically distant from one another relative to other pairs studied, highlighting the apparent genetic isolation of the Marquesas (Table 3). In contrast, the points enclosed in the shaded box (lower left) represent select population pairs within Australia or within an island chain, where gene flow appears to homogenize populations genetically, in some cases despite vast geographic distances. For instance, Broome and Kununurra are separated by 1766 km. (a) Marquesas/Atiu, Cook Islands, (b) Marquesas/Hilo, HI, (c) Marquesas/Oahu, HI, (d) Marquesas/Kauai, HI, (e) Marquesas/Darwin, Australia. Shaded points include Viti Levu, Fiji/Vanua Levu, Fiji (Fst = 0.0042), Broome, Australia/Kununurra, Australia (Fst = 0.006), Cairns, Australia/Mission Beach, Australia (Fst = 0.0074), Mission Beach, Australia/Cooktown, Australia (Fst = 0.008), Darwin, Australia/Kununurra, Australia (Fst = 0.0089) and Daintree, Australia/Mission Beach, Australia (Fst = 0.0093).

Download figure to PowerPoint

Signs of recent bottlenecks (using the program bottleneck) were noted in only one Australian population (Carnarvon), three of the eight island populations in the Oceania group (Viti Levu, Rarotonga, and Moorea) and all three of the Hawaiian Island populations tested (Table 1). Despite the low heterozygosity and AR noted in the Marquesas population (Table 1), no recent bottleneck was evident, but this may be an artefact of high homozygosity in the Marquesas; two loci in this population revealed only one allele each and therefore 0% heterozygosity. Having a single allele at each of these loci is consistent with a founder effect.

Neighbour-joining analysis based on DA revealed several well-supported groupings of populations (Fig. 4). For the most part, these represent regional clusters – Australia, and two clusters within Oceania (A = Vanuatu, Fiji, Samoa, Marquesas, and B = Cook Islands, Society Islands, Hawaiian Islands).

image

Figure 4.  Unrooted consensus (500 bootstrap replications) Neighbour-Joining tree based on DA. Three groups corresponding roughly to geographic locations can be seen: (i) Australian populations, (ii) Fiji, Vanuatu, Samoa and Marquesas and (iii) Hawaii + Moorea (Society Islands) and the Cook Islands of Atiu and Rarotonga. The close relationship between Hawaiian populations and the group Moorea + Cook Islands suggests the Hawaiian crickets are derived from one of these two locations.

Download figure to PowerPoint

Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References

Despite their recent spread through the Pacific, Polynesian field cricket populations are highly structured. Genetic variability decreased from west to east through their distribution and differentiation among local populations was a clear function of geographical distance. Genetic relationships based on microsatellite data suggest the Hawaiian populations are least distant from those in Moorea (in the Society Islands) and the two populations from the Cook Islands. Finally, we found evidence of genetic bottlenecks in one mainland and six island populations (three outside of Hawaii as well as all three Hawaiian islands sampled), a nonadaptive process thought to have consequences for the evolution of sexual signalling systems in general (Kaneshiro, 1989), and for T. oceanicus in particular (Tinghitella & Zuk, 2009). We discuss each of these results in turn below.

Genetic diversity across the Pacific

Although theory suggests that genetic diversity should decrease along a colonization route (Hewitt, 1996; Austerlitz et al., 1997), both historical and contemporary factors can impact genetic structuring of populations and modify such reduction in diversity. For example, contemporary admixture may be greater than historical levels because human movement through the Pacific removes a barrier to dispersal – the vast open ocean distances between islands. This can make reconstruction of historical population relationships difficult. The pattern of genetic diversity loss in our data agrees with earlier suggestions that T. oceanicus was introduced to the western Pacific islands from their native Australia and then spread progressively further east, arriving most recently in remote locations such as the Hawaiian Islands and the Marquesas (Otte, 1994). Our analyses suggest a loss of allelic diversity (NA), AR and expected heterozygosity (HE) moving east through the crickets’ distribution (Tables 1 and 4, Fig. 2). This pattern is not universally observed in introduced island populations, however. Several recent studies have found increased levels of diversity when multiple introductions were made from different locations (Calsbeek & Smith, 2003; Wares et al., 2005; Roman & Darling, 2007). We suggest that the probability of multiple colonization events is likely to decrease with distance to source populations and hostility of the environment into which introductions are made. Because the movement of T. oceanicus was relatively linear as west to east colonization progressed, the likelihood of multiple introductions from the source (Australia) to any given island is low and not supported. We also found a clear pattern of isolation by distance, indicating restricted gene flow among the samples in accordance with geographic distance (Fig. 3). This might be expected among island populations as the open ocean serves as a barrier to organisms with limited dispersal ability and suggests that T. oceanicus populations in the Pacific have reached an equilibrium between migration and drift.

Island hopping through the Pacific

Our proposed route of colonization, from west to east, is further supported by relationships among populations noted in our consensus neighbour-joining tree. Our findings suggest that Hawaiian populations are most closely related to those from the Society Islands and the Cook Islands (Fig. 4). Intriguingly, this is consistent with some models of human movement during the Polynesian expansion. Polynesian folklore indicates the calls of crickets are thought to represent the cries of dead ancestors (in Loher & Orsak, 1985) and crickets figure prominently in Polynesian spirit traditions (Clerk, 1990). If Polynesian settlers aided the dispersal of the crickets, we would expect the genetic relationships among cricket populations to reflect the patterns of human movement during the Polynesian expansion (see Fig. 5). Human colonization of eastern Polynesia may have occurred from a broad central region encompassing the Societies and the Cooks, but probably not the Marquesas, with at least two introductions to Hawaii (from the Societies and the Marquesas) (Matisoo-Smith et al., 1998). Our findings are not consistent with introduction to Hawaii from the Marquesas (with humans or otherwise). The close relationships between crickets from Hawaii and the Societies/Cooks, and those from Samoa and the Marquesas (Fig. 4), however, are consistent with Matisoo-Smith et al.’s (1998) model of human-aided dispersal. Within Hawaii, Oahu has the highest levels of genetic diversity (Table 1) followed by Kauai and Hawaii, suggesting that of these three, Oahu was settled first.

image

Figure 5.  Human migration patterns during the Polynesian expansion, following the ‘Express Train to Polynesia’ hypothesis. Polynesian settlers are thought to have their origins in SE Asia. Near Oceania (Bismarck, Solomon Islands) was settled by non-Austronesian speaking people between 40 and 60 000 years BP (Summerhayes et al., 2010). Remote Oceania (Vanuatu, Fiji, Tonga, Samoa, New Caledonia) was settled by 3100 BP at the earliest, with Samoa and Tonga settled by 2900 BP (Kirch, 2000; Hurles et al., 2003; Bedford et al., 2006). The appearance of Lapita (and assumed arrival of Austronesian expansion into Near Oceania) is about 3350 BP. The two best-known scenarios for Pacific colonization include the ‘Express Train’ characterized by the simple spread of Polynesian ancestors into Near Oceania then Remote Oceania with little genetic exchange (pictured here), and the ‘Entangled Bank’, a reticulate model postulating ongoing interaction among populations (Hurles et al., 2003). Human mitochondrial DNA studies also support a third hypothesis, the ‘Slow Boat’ or ‘Slow Train’ in which more genetic mixture occurred before humans reached Remote Oceania (Hurles et al., 2003). Broken arrows indicate proposed movement in the region between approximately 3500–2700 years BP, and solid arrows indicate movement in the region between 1200 and 500 years BP (the settlement of East Polynesia and Polynesian outliers; following Addison & Matisoo-Smith, 2010).

Download figure to PowerPoint

The second grouping of island populations in our neighbour-joining relationship tree is consistent with patterns of pre-European contact human movement in the Pacific as well (Fig. 4). Before the Society Islands and Marquesas became the locations from which colonizers ventured out, Fiji, Vanuatu, Samoa and the Marquesas were settled. That the Marquesas appear to be very isolated is consistent with evidence from genetic diversity in populations of the Pacific rat, a commensal of humans moved in canoes with Polynesian settlers (Matisoo-Smith et al., 1998). Such isolation is in contrast to earlier views in which the Marquesas are considered to be central in eastern Polynesian interaction and contact (Kirch, 1985). Much debate still surrounds this issue (Kirch & Kahn, 2007), and evidence from a range of different fields, including genetic studies of plants and animals moved with Polynesian settlers, suggests human settlement in the Pacific is far more complex than simple models such as the ‘Express Train’ or ‘Entangled Bank’ (Hurles et al., 2003). Analysing mitochondrial sequences, in addition to microsatellite loci, and sampling more extensively in the Pacific would be especially informative for addressing questions of multiple introductions to remote Oceania and Hawaii, for corroborating the relationships among Pacific populations of T. oceanicus and for dating the crickets’ arrival to Hawaii (either 1500 years ago with Polynesian settlers or more recently travelling on ships post-European settlement). Sampling in New Guinea, the Bismarck Archipelago and the Solomon Islands, for instance, would allow us to address the timing of dispersal into Remote Oceania. We suspect the cricket may also be native to New Guinea (possibly to Sahul and therefore New Guinea and Australia), as it is found on the tip of Cape York (Otte & Alexander, 1983), but we are unaware of references stating absolutely whether that is so.

Nonadaptive contributions to variation in sexual signalling

The reduction in genetic diversity (AR and expected heterozygosity) in eastern relative to western (Australian and Pacific) populations (Table 4) could indicate recent population size reductions, consistent with bottlenecks. We found evidence of bottlenecks in seven populations under the infinite alleles model (Table 1). Notably, we did not find evidence of a bottleneck in the Marquesas, despite those islands’ low allelic diversity and heterozygosity which suggests extreme isolation and low ongoing gene flow (Table 1). This may be because of finding only a single allele at each of two loci in the Marquesan population. Monomorphic loci contribute nothing to heterozygosity, and bottleneck estimates the likelihood of a genetic bottleneck as an increase in observed heterozygosity. Finding monomorphic loci might make such an observation highly unlikely.

The discovery of bottlenecks is relevant to the spread of the flatwing mutation in Hawaii. Previous work suggests that genetic bottlenecks led to the relaxation of female mating requirements in Hawaiian T. oceanicus populations relative to other island and mainland populations. Tinghitella & Zuk (2009) found that female T. oceanicus from island populations, particularly Hawaii, were less discriminating in their mating interactions than females from mainland Australian populations, a pattern consistent with Kaneshiro’s effect (Kaneshiro, 1989) in which bottlenecks select for less choosy females. In no-choice mating trials, a larger proportion of females from islands mated with silent flatwing males than did females from Australia, suggesting these relaxed mating requirements might have facilitated the rapid evolutionary loss of the crickets’ sexual signal in Hawaii (Tinghitella & Zuk, 2009). Until now, however, there was no evidence that genetic bottlenecks did indeed occur upon the colonization of Pacific islands. The likelihood of bottlenecks upon colonization of the Hawaiian populations uncovered here provides the basis on which such changes in female mating requirements could occur.

Finally, we observed low levels of differentiation among populations within Australia (Table 2) despite the vast distances between these continental populations. The results agree with the idea that migration should reduce FST more in older than more recently established populations (Austerlitz et al., 1997). Gene flow also appears to homogenize islands within island chains in our data set, suggesting either a single colonization event for each island group with little subsequent divergence among islands within island chains, or much ongoing movement among islands of a chain. In Fiji, the Cook Islands and Hawaii, where we were able to sample multiple islands within a chain, we observed low genetic differentiation (Table 2). More contemporary human movement patterns like shipping routes in the Pacific or flights between popular Polynesian destinations might counteract differentiation in these areas (for instance, if crickets or eggs are moved in dirt or plant materials). Moreover, in their native range, T. oceanicus have short episodes of high dispersal and at peak times of the year swarm and disperse widely (Simpson et al., 1992). If contemporary gene flow is high, this might slow differentiation across the crickets’ distribution (by homogenizing locations genetically) and could contribute to the spread of the nonsignalling morph in Hawaii by moving flatwing males to new locations. The latter could represent yet another way in which human movement impacts the evolutionary trajectory of T. oceanicus. Interestingly, we recently found flatwing males on Oahu, which we hypothesize is a consequence of migration from Kauai, but which alternatively may represent a separate, but similar, mutation.

Acknowledgments

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References

We thank Cheryl Hayashi for feedback on the experiments and for providing laboratory space and James Fullard for providing leg muscle samples from islands in Fiji and the Cook Islands. David Fang of the UC Riverside Genomics Center provided assistance with running the microsatellites. Lisa Matisoo-Smith and an anonymous reviewer gave very helpful comments on the manuscript. This work was supported by a National Science Foundation Doctoral Dissertation Improvement grant to RMT and MZ, a University of California Pacific Rim Mini-Grant to RMT, a grant from the Orthopterists’ Society to RMT, and the Australian Research Council to LWS.

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References
  • Addison, D.J. & Matisoo-Smith, E. 2010. Rethinking Polynesian Origins: a West-Polynesia Triple-I Model. Archaeol. Oceania. 45: 112.
  • Austerlitz, F., Jung-Muller, B., Godelle, B. & Gouyon, P.-H. 1997. Evolution of coalescence times, genetic diversity and structure during colonization. Theor. Pop. Biol. 51: 148164.
  • Austin, C.C. 1999. Lizards took express train to Polynesia. Nature 397: 113114.
  • Barton, N.H. & Slatkin, M. 1986. A Quasi-equilibrium theory of the distribution of rare alleles in a subdivided population. Heredity 56: 409415.
  • Bedford, S., Spriggs, M. & Regenvanu, R. 2006. The Teouma Lapita Site and the early human settlement of the Pacific Islands. Antiquity 80: 812828.
  • Beveridge, M. & Simmons, L.W. 2005. Microsatellite loci for the Australian field cricket Teleogryllus oceanicus and their cross-utility in Teleogryllus commodus. Mol. Ecol. Notes 5: 733735.
  • Boake, C.R.B. 2002. Sexual signaling and speciation, a microevolutionary perspective. Genetica 116: 205214.
  • Cade, W. 1975. Acoustically orienting parasitoids: fly phonotaxis to cricket song. Science 190: 13121313.
  • Calsbeek, R. & Smith, T.B. 2003. Ocean currents mediate evolution in island lizards. Nature 426: 552555.
  • Chakraborty, R. & Nei, M. 1977. Bottleneck effects on average heterozygosity and genetic distance with the stepwise mutation model. Evolution 31: 347356.
  • Claridge, E.M. 2006. The Systematics and Diversification of Rhyncogonus (Entiminae: Curculionidae: Coleoptera) in the Central Pacific. PhD thesis, University of California, Berkeley.
  • Clegg, S.M., Degnan, S.M., Kikkawa, J., Moritz, C., Estoup, A. & Owens, I.P.F. 2002. Genetic consequences of sequential founder events by an island-colonizing bird. PNAS 99: 81278132.
  • Clerk, C. 1990. “That isn’t really a pig”: spirit traditions in the Southern Cook Islands. Oral Tradition 5: 316322.
  • Cornuet, J.-M. & Luikart, G. 1996. Description and power analysis of two tests for detecting recent population bottlenecks from allele frequency data. Genetics 144: 20012014.
  • Coyne, J.A. & Orr, H.A. 2004. Speciation. Sinauer Assoc., Sunderland, MA.
  • Craig, D.A. 2003. Geomorphology, development of running water habitats, and the evolution of black flies on Polynesian islands. Bioscience 53: 10791093.
  • Craig, D.A., Currie, D.C. & Joy, D.A. 2001. Geographical history of the central-western Pacific black fly subgenus Inseliellum (Diptera: Simuliidae: Simulium) based on a reconstructed phylogeny of the species, hot spot archipelagoes and hydrogeological considerations. J. Biogeogr. 28: 11011127.
  • Deiringer, D. & Schlotterer, C. 2002. Microsatellite Analyser (MSA): a platform independent analysis tool for large microsatellite data sets. Mol. Ecol. Notes 3: 167169.
  • Di Rienzo, A.A., Peterson, A.C., Garza, J.C., Valdes, A.M. & Slatkin, M. 1994. Mutational processes of simple sequence repeat loci in human populations. PNAS 91: 31663170.
  • Dlugosch, K.M. & Parker, J.M. 2008. Founding events in species invasions: genetic variation, adaptive evolution, and the role of multiple introductions. Mol. Ecol. 17: 431449.
  • Felsenstein, J. 2005. PHYLIP (Phylogeny Inference Package), Version 3.65. Distributed by the author. Department of Genomic Sciences, University of Washington, Seattle.
  • Fullard, J.H., ter Hofstede, H.M., Ratcliffe, J.M., Pollack, G.S., Brigidi, G.A., Tinghitella, R.M. et al. 2010. Release from bats: genetic distance and sensoribehavioral regression in the Pacific field cricket, Teleogryllus oceanicus. Naturwissenschaften 97: 5361.
  • Garb, J.E. & Gillespie, R.G. 2009. Diversity despite dispersal: colonization history and phylogeography of Hawaiian crab spiders inferred from multilocus genetic data. Mol. Ecol. 18: 17461764.
  • Ghalambor, C.K., McKay, J.K., Carroll, S.P. & Reznick, D.N. 2007. Adaptive versus non-adaptive phenotypic plasticity and the potential for contemporary adaptation in new environments. Func. Ecol. 21: 394407.
  • Gillespie, R.G. & Roderick, G.K. 2002. Arthropods on islands: colonization, speciation, and conservation. Annu. Rev. Entomol. 47: 595632.
  • Gillespie, R.G., Claridge, E.M. & Goodacre, S.L. 2008. Biogeography of the fauna of French Polynesia: diversification within and between a series of hot spot archipelagos. Philos. Trans. R. Soc. Lond. B Biol. Sci. 363: 33353346.
  • Glaubitz, J.C. 2004. Convert: a user friendly program to reformat diploid genotypic data for commonly used population genetic software packages. Mol. Ecol. Notes 4: 309310.
  • Goudet, J. 1995. FSTAT (version 1.2): a computer program to calculate F statistics. J. Heredity 86: 485486.
  • Gressitt, J.L. 1956. Some distribution patterns of Pacific island fauna. Syst. Zool. 5: 1132.
  • Hendry, A.P., Wenberg, J.K., Bentzen, P., Polk, E.C. & Quinn, T.P. 2000. Rapid evolution of reproductive isolation in the wild: evidence from introduced salmon. Science 290: 516518.
  • Hewitt, G.M. 1996. Some genetic consequences of ice ages, and their role in divergence and speciation. Biol. J. Linn. Soc. 58: 247276.
  • Hurles, M.E., Matisoo-Smith, E., Gray, R.D. & Penny, D. 2003. Untangling oceanic settlement: the edge of the knowable. TREE 18: 531540.
  • Kaneshiro, K.Y. 1989. The dynamics of sexual selection and founder effects in species formation. In: Genetics, Speciation, and the Founder Principal (L.V.Giddings, K.Y.Kaneshiro & W.W.Anderson, eds), pp. 279296. Oxford University Press, Oxford, UK.
  • Keast, A. & Miller, S.E. 1996. The Origin and Evolution of Pacific Island Biotas, New Guinea to Eastern Polynesia: Patterns and Processes. SPB Academic Publishing, Amsterdam, The Netherlands.
  • Kevan, D.K.M. 1990. Introduced grasshoppers and crickets in Micronesia. Bol. Sanid. Veg. Plagas 20: 105123.
  • Kimura, M. & Crow, J.F. 1964. The number of alleles that can be maintained in a finite population. Genetics 49: 725738.
  • Kirch, P.V. 1985. Feathered Gods and Fishhooks: An Introduction to Hawaiian Archaeology and Prehistory. University of Hawaii Press, Honolulu.
  • Kirch, P.V. 2000. On the Road of the Winds: An Archaeological History of the Pacific Islands Before European Contact. University of California Press, Berkeley, CA.
  • Kirch, P.V. & Kahn, J.G. 2007. Advances in Polynesian prehistory: a review and assessment of the past decade (1993–2004). J. Archaeol. Res. 15: 191238.
  • Lehmann, G.U.C. 2003. Review of biogeography, host range and evolution of acoustic hunting in Ormiini (Insecta, Diptera, Tachinidae), parasitoids of night-calling bushcrickets and crickets (Insecta, Orthoptera, Ensifera). Zool. Anz. 242: 107120.
  • Lewkiewicz, D.A. & Zuk, M. 2004. Latency to resume calling after disturbance in the field cricket Teleogryllus oceanicus, corresponds to population-level differences in parasitism risk. Behav. Ecol. Sociobiol. 55: 569573.
  • Loher, W. & Orsak, L.J. 1985. Circadian patterns of premating behavior in Teleogryllus oceanicus LeGuillou under laboratory and field conditions. Beh. Ecol. Soc. 16: 223231.
  • Matisoo-Smith, E., Roberts, R.M., Irwin, G.J., Allen, J.S., Penny, D. & Lambert, D.M. 1998. Patterns of prehistoric human mobility in Polynesia indicated by mtDNA from the Pacific rat. PNAS 95: 1514515150.
  • Mayr, E. 1942. Systematics and the Origin of Species. Columbia University Press, New York.
  • Miller, S.E. 1996. Biogeography of Pacific insects and other terrestrial invertebrates: a status report. In: The Origin and Evolution of Pacific Island Biotas, New Guinea to Eastern Polynesia: Patterns and Processes (J.A.Keast & S.E.Miller, eds), pp. 463475. SPB Academic Publishing, Amsterdam, The Netherlands.
  • Nei, M., Maruyama, T. & Chakraborty, R. 1975. The bottleneck effect and genetic variability in populations. Evolution 29: 110.
  • Nei, M., Tajima, F. & Tateno, Y. 1983. Accuracy of estimated phylogenetic trees from molecular data. J. Mol. Evol. 19: 153170.
  • Ohta, T. & Kimura, M. 1973. A model of mutation appropriate to estimate the number of electophoretically detectable alleles in a finite population. Genet. Res. 22: 201204.
  • Otte, D. 1994. The Crickets of Hawaii: Origin, Systematics, and Evolution. The Orthopterists’ Society, Academy of Natural Sciences, Philadelphia.
  • Otte, D. & Alexander, R.D. 1983. The crickets of Australia (Orthopter: Gryllidae): Monographs of the Academy of Natural Sciences of Philadelphia, No. 22. Academy of Natural Sciences, Philadelphia.
  • Palumbi, S.R. 2001. Humans as the world’s greatest evolutionary force. Science 293: 17861790.
  • Piry, S., Luikart, G. & Cornuet, J.-M. 1999. BOTTLENECK: a computer program for detecting recent reductions in effective population size using allele frequency data. J. Heredity 90: 502503.
  • Rambaut, A. & Charleston, M. 2000. TREEEDIT: phylogenetic tree editor v.1.0 alpha 4-6l. URL http://evolve.zoo.ox.ac.uk/software/TreeEdit/main.html.
  • Raymond, M. & Rousset, F. 1995. GENEPOP (version 1.2) population genetic software for exact tests and ecumenicism. J. Heredity 86: 248249.
  • Reznick, D.N. & Ghalambor, C.K. 2001. The population ecology of contemporary adaptations: what empirical studies reveal about the conditions that promote adaptive evolution. Genetica 112: 183198.
  • Roman, J. & Darling, J.A. 2007. Paradox lost: genetic diversity and the success of aquatic invasions. TREE 22: 454464.
  • Rotenberry, J.T., Zuk, M., Simmons, L.W. & Hayes, C. 1996. Phonotactic parasitoids and cricket song structure: an evaluation of alternative hypotheses. Evol. Ecol. 10: 233243.
  • Shaw, K.L. & Lugo, E. 2001. Mating asymmetry and mate recognition evolution in the Hawaiian cricket genus Laupala. Mol. Ecol. 10: 751759.
  • Simpson, G.B., Mayer, D.G. & Robertson, L.N. 1992. Daily trap catches of two earwig (Dermaptera) and three cricket (Orthoptera) species in central Queensland. J. Aust. Ent. Soc. 31: 255262.
  • Slatkin, M. 1987. Gene flow and the geographical structure of natural populations. Science 236: 787792.
  • Slatkin, M. 1995. A measure of population subdivision based on microsatellite allele frequencies. Genetics 139: 457462.
  • Steadman, D.W. 1995. Prehistoric extinctions of Pacific islands birds: biodiversity meets zooarchaeology. Science 267: 11231131.
  • Steadman, D.W., Pregill, G.K. & Burley, D.V. 2002. Rapid prehistoric extinction of iguanas and birds in Polynesia. PNAS 99: 36733677.
  • Stockwell, C.A., Hendry, A.P. & Kinnison, M.T. 2003. Contemporary evolution meets conservation biology. TREE 18: 94101.
  • Streelman, J.T., Gmyrek, S.M., Kidd, M.R., Kidd, C., Robinson, R.L., Heret, E. et al. 2004. Hybridization and contemporary evolution in an introduced cichlid fish from Lake Malawi National Park. Mol. Ecol. 13: 24712479.
  • Summerhayes, G.R., Leavesley, M., Fairbairn, A., Mandui, H., Field, J., Ford, A. et al. 2010. Human adaptation and plant use in Highland New Guinea 49,000 to 44,000 years ago. Science 330: 7881.
  • Svensson, E.I. & Gosden, T.P. 2007. Contemporary evolution of secondary sexual traits. Func. Ecol. 21: 422433.
  • Takezaki, N. & Nei, M. 2008. Empirical tests of the reliability of phylogenetic trees constructed with microsatellite DNA. Genetics 178: 385392.
  • Tinghitella, R.M. 2008. Rapid evolutionary change in a sexual signal: genetic control of the mutation “flatwing” that renders male field crickets (Teleogryllus oceanicus) mute. Heredity 100: 261267.
  • Tinghitella, R.M. & Zuk, M. 2009. Asymmetric mating preferences accommodated the rapid evolutionary loss of a sexual signal. Evolution 63: 20872098.
  • Tinghitella, R.M., Wang, J.M. & Zuk, M. 2009. Pre-existing behavior renders a mutation adaptive: flexibility in male phonotaxis behavior and the loss of singing ability in the field cricket Teleogryllus oceanicus. Behav. Ecol. 20: 722728.
  • Wares, J.P., Hughes, A.R. & Grosberg, R.K. 2005. Mechanisms that drive evolutionary change: insights from species introductions and invasions. In: Species Invasions: Insights into Ecology, Evolution, and Biogeography (D.F.Sax, J.J.Stachowicz & S.D.Gaines, eds), pp. 229257. Sinauer Associates, Sunderland, MA.
  • Weir, B.S. & Cockerham, C.C. 1984. Estimating F-statistics for the analysis of population structure. Evolution 38: 13581370.
  • Whittaker, R.J. & Fernández- Palacios, J.M. 2007. Island Biogeography: Ecology, Evolution and Conservation. Oxford University Press, Oxford, UK.
  • Yeh, P.J. 2004. Rapid evolution of a sexually selected trait following population establishment in a novel environment. Evolution 58: 166174.
  • Yeh, P.J. & Price, T.D. 2004. Adaptive phenotypic plasticity and the successful colonization of a novel environment. Am. Nat. 164: 531542.
  • Zuk, M. & Kolluru, G.R. 1998. Exploitation of sexual signals by predators and parasitoids. Q. Rev. Biol. 73: 415438.
  • Zuk, M. & Tinghitella, R.M. 2008. Rapid evolution and sexual signals. In: Sociobiology of Communication: An Interdisciplinary Perspective (P.d’Ettore & D.P.Hughes, eds), pp. 139155. Oxford University Press, New York.
  • Zuk, M., Simmons, L.W. & Cupp, L. 1993. Calling characteristics of parasitized and unparasitized populations of the field cricket Teleogryllus oceanicus. Beh. Ecol. Soc. 33: 339343.
  • Zuk, M., Rotenberry, J.T. & Simmons, L.W. 1998. Calling songs of field crickets (Teleogryllus oceanicus) with and without phonotactic parasitoid infection. Evolution 52: 166171.
  • Zuk, M., Rotenberry, J.T. & Simmons, L.W. 2001. Geographical variation in calling song of the field cricket Teleogryllus oceanicus: the importance of spatial scale. J. Evol. Biol. 14: 731741.
  • Zuk, M., Rotenberry, J.T. & Tinghitella, R.M. 2006. Silent night: adaptive disappearance of a sexual signal in a parasitized population of field crickets. Biol. Lett. 2: 521524.