Small, specialised and highly mobile? The tree-hole breeding frog, Phrynobatrachus guineensis, lacks...

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Small, specialised and highly mobile?The tree-hole breeding frog,Phrynobatrachus guineensis, lacks fine-scale population structureLaura Sandberger a , Heike Feldhaar b , Kathrin P. Lampert c ,Dunja K. Lamatsch d & Mark-Oliver Rödel aa Museum für Naturkunde, Leibniz Institute for Research onEvolution and Biodiversity at the Humboldt University Berlin,Berlin, Germanyb Behavioral Biology, University of Osnabrück, Osnabrück,Germanyc Evolutionary Ecology and Biodiversity of Animals, University ofBochum, Bochum, Germanyd Austrian Academy of Sciences and Institute for Limnology,Mondsee, Austria

Version of record first published: 15 Jun 2010.

To cite this article: Laura Sandberger, Heike Feldhaar, Kathrin P. Lampert, Dunja K. Lamatsch& Mark-Oliver Rödel (2010): Small, specialised and highly mobile? The tree-hole breeding frog,Phrynobatrachus guineensis, lacks fine-scale population structure, African Journal of Herpetology,59:1, 79-94

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Original article

Small, specialised and highly mobile? The tree-holebreeding frog, Phrynobatrachus guineensis, lacks

fine-scale population structure

LAURA SANDBERGER1$, HEIKE FELDHAAR

2$,

KATHRIN P. LAMPERT3, DUNJA K. LAMATSCH

4 &

MARK-OLIVER RODEL1*

1Museum fur Naturkunde, Leibniz Institute for Research on Evolution and Biodiversity at the Humboldt

University Berlin, Berlin, Germany; 2Behavioral Biology, University of Osnabruck, Osnabruck, Germany;3Evolutionary Ecology and Biodiversity of Animals, University of Bochum, Bochum, Germany; 4Austrian

Academy of Sciences and Institute for Limnology, Mondsee, Austria

Abstract.—Data on population dynamics and distribution are of primary interest tobiologists because they reveal information about the species’ ecology and evolution and arethus essential for conservation efforts. Patchily distributed species are especially interestingfor conservation studies, because of their sometimes very specific environmental require-ments. An example of a highly specialised species is the leaf litter frog Phrynobatrachus

guineensis. This small species (B20 mm) is short lived, presumably weakly mobile and highlyspecialised because it uses tree-holes and other small water-filled cavities with veryparticular abiotic and biotic characteristics for breeding. Previous field studies revealedthat P. guineensis exhibited a clumped distribution in Taı National Park (TNP), IvoryCoast, suggesting that the park’s population might be subdivided into several (sub)popula-tions. We therefore investigated the population genetic structure of the park using fourmicrosatellite loci, which are the first described microsatellite markers for any Africananuran in general and for a species of the family Phrynobatrachidae in particular. Incontrast to our expectations, we detected only a slightly significant genetic differentiationbased on allele frequencies. We found no correlation between the geographic and geneticdistances (isolation by distance) and Bayesian clustering revealed no genetic substructure.We did, however, detect small but significant genetic differentiation between subsequentseasons. The most probable explanation for the lack of population structure is thatP. guineensis is more mobile than expected. Adults, most likely females but possibly alsojuveniles, are able to traverse matrix habitats in which no breeding activities were detected.The temporal genetic differentiation may be the consequence of genetic drift due to highmortality rates and/or non-random mating. Both explanations would be consistent with ourfield data.

Key words.—Amphibia, Anura, Phrynobatrachidae, microsatellites, phytotelmata, populationgenetic structure, rainforest, West Africa

Species are often patchily distributed in nature (Alexandrino et al. 2000; Zeisset et al.

2000; Newman & Squire 2001). Dispersal rates can vary markedly among

*Corresponding author. Email: [email protected]$These authors contributed equally to the work.Supplementary Material is available for this article which can be accessed via the onlineversion of this journal available at www.tandf.co.uk/journals/THER.

African Journal of Herpetology,

Vol. 59, No. 1, April 2010, 79�94

ISSN 0441-6651 print/ISSN 2153-3660 online

# 2010 Herpetological Association of Africa

DOI: 10.1080/04416651003788619

http://www.informaworld.com

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populations (Avise 2000; Lampert et al. 2003; Burns et al. 2004), and these determine

to what degree populations function as demographically independent units (Palo

et al. 2004a). Gene flow diminishes genetic differences among populations (Wright

1931; Malecot 1975; Perrin & Mazalov 2000; Kraaijeveld-Smit et al. 2005), and,

through interactions with other microevolutionary processes like inbreeding, drift

and selection, produces patterns of differentiation (Wright 1943; Palo et al. 2004b;

Aars et al. 2006). In species with locally restricted gene flow, distance effects may beobserved (Wright 1943; Malecot 1975). These effects are based on a higher

probability that two individuals within a small to moderate range will be able to

mate than two individuals from more distant areas (Balloux & Lugon-Moulin 2002).

This may lead to two different population structures: either a gradual genetic

differentiation termed isolation by distance or a more categorical division in

genetically differentiated (sub)populations. Isolation by distance has been observed

in a number of amphibian species e.g. in Rana temporaria (Hitchings & Beebee 1997),

Physalaemus pustulosus (Lampert et al. 2003; Prohl et al. 2006), Dendropsophus

ebraccatus and Agalychnis callidryas (Robertson et al. 2009).

Amphibians often have patchy distributions due to habitat specificity and strict

ecophysiological requirements (Pope et al. 2000; Wells 2007; Zamudio & Wieczorek

2007). Hence, it is often assumed that the population structure of most amphibian

species is that of a classical metapopulation system (Alford & Richards 1999; Marsh

& Trenham 2001; Burns et al. 2004). This is thought to be especially true for species

that breed in large ponds. Amphibian species breeding in temporary water-bodies,e.g. small ponds, puddles, or phytotelmata however, frequently cannot return to their

natal larval habitat for reproduction, because it may no longer exist. This should

increase the dispersal probability of the respective species. On the other hand

individuals belonging to these species are often very small and presumably

comparatively immobile, very sensitive to particular physiological constrains and

hence, have high demands concerning their breeding sites. This should favour

individuals with high fidelity to sites that are known to be suitable for reproduction

and thus limit dispersal. Dispersal rates are thus likely to be driven by the trade-off

between the need to search for unpredictably spaced resources, the risk of missing

those during the reproductive lifetime, the dispersal ability and the predation risk of

the species in question. Generally, dispersal may occur less often in species using

breeding sites that are limited but predictable in space and time, like larger ponds, or

streams, than in species reproducing in unpredictable but non-limited breeding sites.

Herein we examined Phrynobatrachus guineensis, a small (B20 mm body length),

diurnal frog of the leaf litter in West African primary rainforests, which breeds in

water-filled tree-holes and empty snail shells (Rodel et al. 2004). Males utter mutedadvertisement calls at or close to potential breeding sites to attract females. During

one breeding season, most males call only for a few days from a certain breeding site

before moving to another breeding site. Hence, they often move between breeding

sites, however, rarely over large distances (mean �24 m, Rodel et al. 2004). Females

visit breeding sites only for spawning, possibly inspecting several sites and males

before mating. Although breeding sites suitable for this species have very specific

attributes (Rudolf & Rodel 2005), they seem not to be limited in number (Rodel et al.

2004). The size of breeding sites is an important factor, as too large breeding sites

might contain dragonfly larvae, which prey on tadpoles, and too small breeding sites

have an increased desiccation risk. Both factors, predation and desiccation, can result

80 AFRICAN JOURNAL OF HERPETOLOGY 59(1) 2010

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in 100% tadpole mortality (Rodel et al. 2004). In response to larval predators,

breeding site choice in P. guineensis comprises not only evaluation of particular

habitat parameters, but favours selection of tree-holes already occupied by tadpoles,

indicating a predator-free environment. The latter behaviour is presumably

responsible for the very patchy and clustered distribution of breeding populations

(Rudolf & Rodel 2005).

A monitoring program conducted within Taı National Park with individually

known frogs, comprising field data for 17 months, revealed 12 distinguishable

breeding patches. During the study period we never detected frogs that were

dispersing between the patches, nor did we detect frogs at suitable breeding sites

between these patches, probably due to other environmental constraints in these

areas. Individuals of P. guineensis were almost exclusively tracked in or near breeding

sites (Rodel et al. 2004; Rudolf & Rodel 2005, 2007). Phrynobatrachus guineensis

reproduces only in the rainy season from March to October/November. The

monitoring data revealed that almost no adults survived the dry season from

November/December to February (Rodel et al. 2004), resulting in non-overlapping

generations from one breeding season to the next. Hence, we hypothesised that P.

guineensis should show genetically differentiated sub-populations due to limited gene

flow between patches. The hypothesis was tested with a population genetic analysis

based on microsatellites especially designed for this study.

MATERIALS AND METHODS

Study Area and Sampling

The study area was situated within the Taı National Park (TNP) in south-western

Ivory Coast (5808?�6807? N, 6847?�7825? W). TNP is the largest remaining, protected

block of evergreen rainforest in West Africa (approximately 4 550 km2). Our study

site (5850? N, 7820? W) comprised about 1.2�2.1 km of primary forest (Fig. 1).

Annually, two distinct rainy seasons can be differentiated, separated by a long

(November to February/March) and a short (August) dry season. For more details

about the study area see Riezebos et al. (1994) and Rodel et al. (2004).

From May 2001 to September 2002 all potential breeding sites from which a P.

guineensis male was heard calling at least once were monitored for frogs, eggs and

tadpoles on a nearly daily basis. Potential breeding sites were identified by tracking

calling males and by searching small water-filled tree-holes and empty snail shells. In

total 146 potential breeding sites were included in the monitoring (Rodel et al. 2004;

Rudolf & Rodel 2005, 2007). Of these potential sites, 74 (50.7%) were used for

reproduction at least once. Breeding site patches were defined as sites that were located

in geographic proximity, separated from each other by areas where no breeding activity

was observed. At every site all adults were marked individually by toe-clipping. We

hence obtained capture and observation histories of all encountered adult frogs (dates

and locations), including conspecific associations (presence of other known indivi-

duals). The toe-tips and four whole individuals (anaesthetised with chlorobutanol)

were preserved in 96% ethanol for subsequent genetic analyses and kept at 48C.

Females were only rarely caught (B40 compared to �300 males). Recaptures of

females were much rarer than in males. However, all males and females were

exclusively recaptured at or close to their original capture site (Rodel et al. 2004). We

SANDBERGER ET AL.—Population structure of Phrynobatrachus guineensis 81

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calculated all analyses with all individuals and with males only. In all analyses results

for all individuals and males only were very similar, hence only the results for males

are shown herein. The distances between the 12 breeding site patches ranged from

90�600 m and patches had a mean radius of 15 m (Rudolf & Rodel 2005). Four of the12 breeding site patches consisted of only one tree-hole and were excluded from

population genetic analyses. In addition to the TNP samples, four toe-tips of

P. guineensis males were collected at two locations at Mount Nimba, Guinea

(approximately 230 km from the TNP sites), in August 2007.

As generations of P. guineensis were non-overlapping (see above) frogs collected

in 2001 before the onset of the dry-season and frogs collected in 2002 after the dry-

season represent two consecutive generations. We defined the November�February

dry period, as the time when generations are completely replaced. We based our

Figure 1. Position of the study area within Taı National Park, Cote d’Ivoire, West Africa.

Within the study area the positions of the eight patches that have been included in all analyses

are shown. The patches comprised 2�16 breeding sites. For patches 9�12 no exact position

could be determined. Patch 9 was located northwest of patch 1, patches 10�12 were close to

patch 3.


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analyses on a hierarchically structured data set of different ‘sub-population levels’,

defined as follows: (1) all males within the study site considered as a single

population (‘population of study site’); (2) all males from both years grouped into

eight patches (12 minus the four patches with only one breeding site, Fig. 1; ‘patch

populations’); (3) all males grouped into eight patches and considering males caught

in different years as part of different populations due to non-overlapping generations

between years, resulting in a total of 16 ‘populations’ (‘year populations’).

Molecular Methods

For microsatellite isolation DNA was extracted from muscle tissue of at least two of

the four whole individuals with PuregeneTM (Gentra Systems, Minneapolis, USA)

following the manufacturer’s protocol. Microsatellite markers were isolated from

genomic DNA using the enrichment strategy of Rutten et al. (2001) with

modifications by Feldhaar et al. (2004). Approximately 2.5 mg of high molecular

weight DNA were digested with HinfI. An annealed adapter (300 nm; forward: 5?-AXTGGTACGCAGTCTAC-3? where X� Inosine, reverse: 5?-GTAGACTGCGTACC-

3?; Rutten et al. 2001) was ligated to the resulting restriction cleavage site. The ligated

fragments were precipitated and resolved in 6x SSC. After heat denaturation the

single stranded DNA was hybridised to a biotin-labelled (CA)10 oligo-probe

(150 nm). Hybrids were subsequently bound to streptavidin-coated iron beads

(Dynal), captured by using a magnetic particle concentrator (Dynal) and then

washed with increasing stringency to enrich microsatellite-containing DNA frag-

ments. We repeated the enrichment procedure a second time in order to increase the

yield of fragments containing microsatellites, beginning with the addition of

the hybridisation of single-stranded DNA to the biotin-labelled (CA)10 oligoprobe.

The target DNA was amplified via PCR using the reverse adaptor oligonucleotide as

single primer. PCR products were ligated into the pCR†2.1-TOPO† vector

(InvitrogenTM) and transformed into OneShot†ChemicallyCompetent Escherichia

coli cells (InvitrogenTM). The cells were plated on ampicillin/X-Gal LB plates,

allowing recognition of positive clones. Positive clones were sequenced and primers

were designed for PCR amplification of the identified microsatellites.

DNA from toe-tips was extracted with a DNeasy Tissue Kit (Qiagen, Hamburg,

Germany), following the manufacturer’s protocol for animal tissue. Four poly-

morphic microsatellites were amplified using the following PCR conditions: initial

denaturation for 3 min at 948C, followed by 35 cycles of denaturation at 948C,

annealing temperature (see Table 1) and 728C elongation. Each temperature within

the cycle was kept for 45 sec. The amplification finished with a final elongation at

728C for 1.5 min. A final reaction mix of 12.5 ml was used (containing approximately

10 ng of template DNA, 7.40 ml dH20, 1x PCR-buffer (10 mM Tris-HCl, 50 mM KCl,

0.08% Nonidet P40), 2 mM MgCl2, 160 mM dNTPs, 2.5 mM of each primer (forward

primer labelled with fluorescent IR-700 or IR-800dye) and 0.5 U of Taq DNA

polymerase (MolTaq by Omni LifeSciences). For all included individuals the allele

lengths of the microsatellite loci were determined using a LI-COR 4300 DNA

Analyzer according to the manufacturer’s protocol. The fragment lengths were

obtained with the program SAGAGT GENERATION 2 (version 3.2.1, personal

edition).


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Statistical Analysis

Expected and observed heterozygosity, deviations from Hardy-Weinberg-

Equilibrium and Analysis of Molecular Variance (AMOVA) were calculated with

ARLEQUIN 3.1 (Excoffier et al. 2006). FST-values following Weir and Cockerham

(1984), were calculated with the program GDA (Lewis & Zaykin 2001) and pairwise

FST calculated with GenePop (Raymond & Rousset 1995). We tested the data for

linkage disequilibrium with GenePop using contingency matrices followed by

probability tests using a Markov chain (Raymond & Rousset 1995). MicroChecker

(van Oosterhout et al. 2004) was used to estimate the probability of scoring errors,

large allele dropout and the possible presence of null alleles. The power of the genetic

data to distinguish between genotypes similar by descent and similar by chance was

estimated using the probability of identity (PID) measure implemented in

the program Gimlet (Valiere 2002). Based on allele frequencies the PID gives the

probability that two individuals are, by chance, genotyped identically and therefore

determines the power of the microsatellite loci used in the study (Waits et al. 2001).

We analysed the correlation between genetic and spatial distances with the

program Isolde, implemented in GenePop (Raymond & Rousset 1995) based on

predefined subpopulations (the patches) as well as between individuals. When

isolation by distance is tested between individuals, a priori designation of individuals

into sub-populations is not required, but the exact capture position is required for

Table 1. Characteristics of microsatellite primers designed for Phrynobatrachus guineensis.

Locus Sequence TM TA

Length

(bp) N

#

alleles A Hobs Hexp p(HWE)

phry2-F 5? ACA ACT CTA GTC

CTC GAG TGC 3?61.3 53 160 326 3 3.0 0.23 0.23 n.s.

phry2-R 5? CTC CCC TAG CCC

AGA AAT G 3?59.5

phry59-F 5? GGA TTT CCG CCA

GAA CAT TA 3?55.3 55 209 325 22 21.9 0.80 0.86 B0.001

phry59-R 5? ATC CGT CTG TGG

CAG ACA T 3?56.7

phry7-F 5? AGA TGT CTT CAT

TGT ATG TCC 3?54.0 53 380 312 32 32.0 0.75 0.91 B0.001

phry7-R 5? ACC ATG ACC AAT

CAT TCT TAG 3?54.0

phry8-F 5? TCC AAT GTA AAC

AAA ACA CC 3?51.1 62 170 311 27 27.0 0.76 0.93 B0.001

phry8-R 5? AAA CCT GTG AAG

CCT GTG AA 3?55.3

Mean 318.5 21 21.0 0.63 0.73

SD 8.1 12.7 12.7 0.23 0.28

Notes: Given are primer name (locus), sequences for the forward (-F) and reverse (-R) primers (sequence),melting temperatures (TM) and annealing temperatures (TA) in 8C, lengths of sequenced fragments fromenrichment (length), number of individuals for which amplification was possible (N), number of allelesfound (# alleles), allelic richness over the whole TNP population (A), the observed (Hobs) and expectedheterozygosity (Hexp) and significant deviation from Hardy-Weinberg-Equilibrium [p(HWE)].


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each individual. Unfortunately due to dense canopy cover the resolution of a hand-

held GPS was not sufficient to determine the position of every breeding site which

clearly lowered the power of our analysis. However, the exact position of at least one

and up to eight breeding sites per patch could be determined. This resulted in the

inclusion of 26 breeding sites and 109 individuals for the individual-based

calculations of isolation by distance.

In order to detect possible population substructure, other than given by

predefined breeding patches, the number of populations contained within all sampled

individuals was estimated with a Bayesian clustering approach using BAPS 4

(Corander et al. 2006, run with 15 000 randomisations). BAPS 4 estimates the

number of populations within a sample by minimising deviations from Hardy-

Weinberg-Equilibrium over all individuals. We performed 10 runs with the maximal

number of populations K �50 (without pre-defined populations). To include

geographic data we carried out a spatial clustering analysis with BAPS as well.

The analysed samples were the same as for the isolation-by-distance analyses.

RESULTS

Field Collection

In total we had available toe-tips of 352 individuals (301 males, 39 females and 12

individuals of unknown sex); of these we successfully genotyped 326 individuals. The

number of investigated adult tissue samples was similar in both years [2001(males/

females): 145/15; 2002(males/females): 142/24]. Due to sampling close to breeding

sites which were occupied by males, capture probability differed strongly between

sexes (included in the genetic analysis: males/females: 287/39; for details see Table 2).

During the monitoring program 12 distinct breeding site patches were determined

(Fig. 1). Marks by toe-clipping allowed identification of individuals but no inter-

patch migration was observed. A patch comprised one to 16 breeding sites.

We caught an average of 4.1 males (range: 1�18 males) per breeding site during

the whole study period. Four patches scattered over the study area consisted of only a

single used breeding site. As a single breeding site in a patch would make the results

for the patch too susceptible to random variation those patches were excluded from

analyses at the patch and year population level. The number of individuals caught in

the eight remaining patches ranged from 11 to 85 individuals (all frogs mean �38.3;

males only: mean �33.5, range: 9�73; N �8). Within all patches at least one female

was caught. On average 14% of all individuals caught within one patch were females.

We found the mean male population size per year to be 16.6 per patch (range: 3�41

males; N �16).

Microsatellite Isolation

For microsatellite isolation we repeated the entire isolation process six times and

picked 970 clones, of which 767 clones contained an insert of P. guineensis DNA. Of

these inserts only 25 indicated and 10 actually contained a microsatellite. For these

ten microsatellite loci primer pairs were designed. Of those 10 primer pairs, four

(phry2, phry59, phry7 and phry8) could be optimised to amplify the focal


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microsatellite locus. Three of the four primers, phry59, phry7 and phry8 were highly

polymorphic (Table S1, Online Supplementary Material). All loci were in linkage

equilibrium with all of the other loci when tested across the total study site within

TNP. For primer sequences and locus details see Table 1.

Amplification was successful for at least 311 (phry8) out of the 326 individuals

analysed (phry2: 326 individuals, phry7: 313 individuals, phry59: 325 individuals).

Locus phry2 was exceptional in several respects: with only three alleles it was the

least polymorphic, the least heterozygous and the only locus in Hardy-Weinberg-

Equilibrium (HWE) for the entire population. For the other loci 22 (phry59), 27

(phry8) and 32 (phry7) alleles were recognised. Mean observed heterozygosity was

0.63 (range: 0.23�0.80), mean expected heterozygosity was 0.73 (range: 0.23�0.93).

When HWE was tested separately for patches per year (only including patches per

year with at least four males; see Table 2) phry7 and phry8 each showed significant

deviation from HWE in eight of 19 patches and phry59 in two patches. Two loci

deviating in the same patch were only found four times. After Bonferroni correction

only two tests out of 76 tests performed (19 patches X four loci) were significant. Out

of the 114 tests of linkage disequilibrium (LD) performed (6 tests X 19 patches) 11

were significant, with six of them between phry7 and phry8 and the others varying

between loci.The power test using probability of identity revealed the sequential sum over all

loci of PID’s of 1.518e�6. Locus phry8 was found to be the most informative locus

followed by phry7, phry59 and phry2. Mean FIS values were high: TNP and Guinea:

Table 2. Details of Phrynobatrachus guineensis samples collected in Taı National Park, Ivory

Coast in 2001�2002. Samples were collected from 12 identified breeding patches.

# individuals # males # females

Patch # # breeding sites total total total

1 13 66 (32/34) 57 (30/27) 9 (2/7)

2 7 11 (6/5) 9 (4/5) 2 (2/0)

3 7 40 (24/16) 39 (24/15) 1 (0/1)

4 9 37 (13/24) 33 (12/21) 4 (1/3)

5 6 25 (14/11) 24 (13/11) 1 (1/0)

6 16 85 (37/48) 73 (32/41) 12 (5/7)

7 6 24 (11/13) 20 (8/12) 4 (3/1)

8 6 18 (9/9) 14 (9/5) 4 (0/4)

9 1 3 (2/1) 2 (2/0) 1 (0/1)

10 1 5 (5/0) 5 (5/0) 0 (0/0)

11 1 5 (1/4) 5 (1/4) 0 (0/0)

12 1 7 (6/1) 6 (5/1) 1 (1/0)

Samples used 74 326 (160/166) 287 (145/142) 39 (15/24)

Samples not used 26 (22/4) 14 (11/3) 0 (0/0)

Total available 352 (182/169) 301 (156/145) 39 (15/24)

Notes: Number of used breeding sites within a patch (# breeding sites); total number of all samples (#individuals), males (# males), females (# females) (discrepancies between the total individual and the sumof males and females are due to individuals of unknown sex). For each category total number of samplesand samples collected in a particular year (2001/2002) are given. Several samples could not be used aseither the DNA was degraded, sex was unknown (N �12) or exact capture date or location data was lost.Additionally we included four individuals captured at Mount Nimba, Guinea collected in 2007.


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FIS�0.124 (N �2), TNP patch populations: FIS�0.120 (N �8); TNP year

populations: FIS�0.117 (N �16). No evidence of scoring errors or large allele

dropout was detected at the four loci. Three of the four microsatellite loci however

showed excess of homozygotes (phry7, phry8 and phry59) and could potentially

include null alleles. Analysis of the genotypes of all individuals with Microchecker

revealed that the loci phry8 and phry7 are likely to include a null allele but not locus

phry59. That a null allele was present in the former two loci was corroborated by

complete failure of amplification of 15 individuals of phry8 and 13 individuals in

phry7, respectively. Assuming that all of these individuals were homozygous for a

single null allele this would mean that the frequency of the null allele could be 0.24 in

phry8 and 0.27 in phry7 (calculated from the p2 in the Hardy-Weinberg equation).

On the same reasoning a potential null allele in phry59 would be present only at very

low frequency since only a single individual showed no amplification. Individuals

failing to amplify in phry8 and phry7 were found in seven of the 12 patches in the

former and six of the 12 patches in the latter, respectively. In phry8 those patches

included the most populous patches 1 to 7 (see Table 2) and in phry7 again the five

most populous patches (1, 3 to 6) and patch 12. For phry7 each patch contained 0�3

individuals without amplification and similarly for phry8, except for patch 6 that

contained seven such individuals.

Utilising the method of van Oosterhout et al. (2004), to adjust genotypes for null

alleles in Microchecker, we produced a second dataset where genotypes of phry7 and

phry8 were corrected for null alleles, i.e. homozygous individuals were changed to

heterozygous for the null allele in accordance with the frequency of the respective

visible allele. Thus, a larger number of ‘real’ homozygous individuals were expected

for alleles with high frequencies than when alleles were rare.

As the method of van Oosterhout et al. (2004) assumes HWE, the significant

deviations from HWE and the number of linked loci were reduced in the corrected

data set. With the corrected data set the significant deviations from HWE were only

found in two of 19 patches (dataset for patches and year separately, only including

patches per year with at least four males; see Table 2). Significant LD was still

detected in five out of the 114 tests performed (6 tests X 19 patches), with four of

them involving either phry7 or phry8. Most of the following population genetic

analyses were performed with both datasets, the original dataset containing potential

null alleles and the corrected dataset. Since the results for the corrected dataset did

not differ from the results for the uncorrected dataset only the results for the original

data set are shown and discussed in the following sections.

Population Genetic Analysis

To analyse the amount of genetic differentiation between the assumed populations

we calculated the FST-values for all population levels. Genetic differentiation was

first calculated separately for 2001 and 2002. In this analysis FST-values between the

eight patches were very low (2001: min ��0.002, max �0.048, mean �0.010,

SD�0.013; 2002: min��0.029, max�0.016, mean�0.001, SD�0.008). For 2001

we found significant differentiation (Bonferroni corrected p (0.05) level �0.00178)

between patch 7 and several other patches (with: patch 1, p �0.001; patch 3,

p B0.001; patch 5, p �0.002; patch 12, p �0.001). No other FST-values were


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significant. In 2002 no significant level of differentiation could be observed. Since no

significant differentiation among years was found for any patch, data from both

years were pooled for comparison. The resulting FST-values, however, were still very

low (min ��0.002, max �0.014, mean �0.002, SD �0.004) and no significant

differentiation between the patches was found. An analysis separating all patches and

all years (16 patches) revealed low FST-values (min ��0.002, max �0.014,

mean �0.002, SD �0.004) and only isolated events of significant differentiation

[Bonferroni corrected p (0.05) B0.001): patch 7 (2001) and patch 12 (2002)

p B0.001; patch 7 (2001) and patch 1 (2001) p B0.001; patch 7 (2001) and patch

2 (2002) p B0.001].On a larger geographic scale we compared the genetic differentiation between

the males caught in TNP and Mount Nimba, Guinea. We found a significant

population differentiation (FST: overall �0.066, upper boundary �0.105, lower

boundary �0.020). Within the four Guinean individuals six private alleles were

detected (phry7; one, phry8: two, phry59: three, phry2 was monomorphic for the

most common allele) that were not found within individuals from TNP (326

individuals).

To analyse at which level most genetic variability was lost, two hierarchical

AMOVAs per dataset were carried out. Our data can be divided temporally by year

and spatially by patch populations. Hence, for the two AMOVAs we divided the TNP

samples in differing order: (1) first spatially than temporally: population of study

area � patch populations (individuals of both years, separated by patches) � year

populations (patch populations divided by year); (2) first temporally than spatially:

population of study area � years (whole population divided by year) � year

populations (patch populations divided by year). For years, all individuals captured

in the study area were separated according to their capture year since individuals

most probably belonged to consecutive generations (2001/2002). For the year

populations all individuals caught within the study area were separated according

to capture year (2001/2002) and additionally by the patch (patches 1�8) they

originated from, leading to 16 separate groups that were analysed.

The first AMOVA revealed no variation between the populations of the different

patches (0.00% of total variation). The variation found between the two years within

the same patch population was small (0.82% of total variation), but significant

( pB0.05). The highest variation was found within the year populations (99.21% of

total variation). The second AMOVA showed significantly higher genetic variation

between individuals caught in 2001 compared to individuals caught in 2002 (between

years: 0.64% of total variation). When the individuals from the two years were

separated in patch populations the variation (0.27% of total variation) was not

significantly higher than expected. Again, the highest variation was found within the

year populations (99.09% of total variation). Thus, in both hierarchical designs the

variability between patches was very small, but between years it was significantly

(a�5%) higher than expected (a: year populations, b: years).

No isolation by distance could be found based on the original dataset containing

null alleles [fitting FST to a�b (distance): a �0.0047, b �0.0002; Pr(correlation �

observed correlation) �0.7691; Pr(correlation Bobserved correlation) �0.2310;

1000 permutations]. A spatial autocorrelation analysis likewise yielded no significant

result (result not shown).


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To uncover a hidden population structure that differed from our predefined

subpopulations based on geographic distribution of breeding patches we estimated

the number of populations with BAPS. The number of populations with the highest

probability were 37 populations (probability �0.9997). The estimated populations

could not be explained by any geographical or temporal parameter. Individuals

caught in one of the two largest patches (6 and 1) were assigned to all of the

estimated populations. To additionally consider the geographical capture position we

ran a second analysis with these parameters. The results did also not show any

population structure. Individuals captured within one patch were assigned to several

clusters and clusters included individuals of several patches with no ecologically

conclusive explanation. Results were essentially the same for the corrected data set

(results not shown).

DISCUSSION

Many amphibians show high site fidelity and a high degree of population subdivision

on relatively short geographical distances (Shaffer et al. 2000; Veith et al. 2002). On a

regional scale (�100 km) population subdivision has been detected in all amphibians

so far investigated (e.g. Burns et al. 2004; Palo et al. 2004a; Prohl et al. 2006;

Robertson et al. 2009), but even on local scales (B50 km) amphibian populations

seem to exhibit a degree of population genetic structure (Rowe et al. 2000; Lampert

et al. 2003). Habitat fragmentation and isolation together with small effective

population sizes can lead to marked subdivision on a small scale (B5 km; Hitchings

& Beebee 1997; Andersen et al. 2004; Kraaijeveld-Smit et al. 2005). In addition,

recurring founder events following extinction of small local populations could lead to

differences even on very small spatial scales (Newman & Squire 2001). For

amphibians dispersal barriers may be man-made, like roads, railways and settlements

(Hitchings & Beebee 1997; Vos et al. 2001), or natural, such as non-suitable habitat,

rivers and mountains (Kraaijeveld-Smit et al. 2005; Li et al. 2009).

The spatial scale at which migration is no longer sufficient to preclude genetic

structuring may therefore vary considerably between and even within species

depending on life-history and occupied habitat. Finding the spatial threshold at

which genetic differentiation occurs is very important to understand population

dynamics especially in species living in mosaic environments. Our study area

comprises a highly diverse mosaic of forest types (Ernst & Rodel 2005).

Phrynobatrachus guineensis was almost exclusively detected within dryer parts of

primary forest (Rodel et al. 2004), and other forest types may thus hinder dispersal.

The distances between breeding site patches sampled in this study were very small

(0.07�1.5 km), seemingly too small to find genetic structure between sites. However,

P. guineensis is a very small and presumably not very mobile frog. Adult size is below

20 mm and metamorphs measure only about 4 mm (0.5�3.9 mg). The life expectancy

of this species seems to be usually lower than half a year and males have about 1

month to reproduce. Breeding sites are geographically and temporarily unevenly

distributed. Investing time in the search for new breeding areas, which may incur

substantial predation risk, should thus be less favourable than investing time in

reproduction activities in an area where suitable breeding sites are known to exist, i.e.

where the particular frog developed successfully (Rodel et al. 2004; Rudolf & Rodel


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2005, 2007). This assumption was consistent with our field observations. Throughout

three years (2000�2002) a total of 394 males were marked; 272 of them were

recaptured at least once. Some males were recaptured up to 17 times and observed to

change between breeding sites within a patch. However, we never observed a male

migrating between patches (Rodel et al. 2004). We therefore assumed that genetically

differentiated (sub)populations should be identifiable and that the genetic population

structure should mirror the geography of the breeding site patches.

In contrast to our expectations we found the FST-values to be very low within

TNP, indicating only marginal population differentiation among males. With

Bayesian clustering we could not detect any pattern related to the distribution of

P. guineensis individuals over the study site. In addition, we did not detect

significant isolation by distance suggesting that the population is close to panmixia.

The AMOVA suggests that temporal variation of allele frequencies between

consecutive years exceeds variation between patches within the same year. This

might be caused by genetic drift due to high mortality rates or by differences in the

reproductive success between individuals, i.e. through non-random mating.

Phrynobatrachus guineensis is very selective in choosing its breeding sites. Male

persistence at tree-holes varies and clutches are more often deposited than expected

by chance at sites where males remained longer, indicating that males stay longer at

better sites and that females can judge this (Rodel et al. 2004, Rudolf & Rodel

2005). Phrynobatrachus guineensis males seem not or only rarely to defend breeding

sites, as several males were commonly found calling at the same site and conspecific

attraction even favours oviposition site selection (Rudolf & Rodel 2005). The whole

population of the TNP study site is small, comprising a mean of about 50 adult

males calling per week (Rodel et al. 2004). One clutch (mean size: 18.7 eggs) is

presumably the total reproductive investment of a female. Only about 43% of the

eggs survive until the tadpoles hatch. Tadpole survival in P. guineensis is

astonishingly high at around 50% (Rodel et al. 2004). However, although no

data are available for juveniles, it is likely that the tiny froglets face much higher

mortality rates than the tadpoles in their almost predator-free environment. The

fact that adult males are rarely registered for more than a month and that less than

3% of the adult males survive the three-month dry season, also appears to favour

an interpretation of high mortality rates of the terrestrial stages of this species

(Rodel et al. 2004). Such a small population and high mortality should lead to

temporal and spatial differences in allele frequencies due to genetic drift. An

additional reason why FST-values were lower than expected might be that water-

filled tree-holes are constantly changing through decay and P. guineensis breeding

sites thus become unsuitable. We observed a turn-over of breeding sites between

consecutive seasons as high as 75% (Rodel et al. 2004). This may lead to high

intra- and possibly also inter-patch migration events. The absence of genetic

structuring between patches possibly suggests that at least some local recruitment

between patches may occur, perhaps by juveniles or females that are rarely

observed in the study area due to their inconspicuousness. Sex-biased dispersal may

counteract the effect of isolation by distance (Kraaijeveld-Smit et al. 2005; Keogh

et al. 2007). Female-biased dispersal is reported for various frogs e.g. Rana

temporaria (Palo et al. 2004b) and Lithobates catesbeianus (Austin et al. 2003).


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Male-biased dispersal is known from Physalaemus pustulosus (Lampert et al. 2003).

Unfortunately the highly sex-biased capture probability did not allow for testing

sex-biased dispersal in P. guineensis.

Another reason for the small population differentiation in our study area might

be that our analysis was based on only four microsatellite loci. When larger genetic

population differentiation was detected in amphibians, 4�12 loci with a minimum of

6�12 and a maximum of 21�51 alleles per locus were used (Palo et al. 2003; Lampert

et al. 2003; Andersen et al. 2004; Burns et al. 2004; Morgan et al. 2008; Robertson

et al. 2009). Using only a limited number of loci may lead to a genome sampling bias

which could mask small levels of population differentiation but also facilitate false

positive results, e.g. the significant differentiation between years found in our dataset.

However, although the loci number in our study was low, the high allele number

(4�32 alleles; TNP average: 20) may have compensated for that. Based on four

microsatellites (13�30 alleles, average 19 alleles per locus), Morgan et al. (2008) could

detect population structures in two Australian frog species. The four loci in our study

probably were sufficient to detect population structures as well: the PID value for all

four loci combined was 1.518e�6. This is lower than the values (PIDB0.01�0.0001)

required for population genetic and conservation studies (Waits et al. 2001). This

assumption is supported by significant population differentiation between the TNP

and the Guinea populations (distance �200 km).

Because the expected heterozygosity was larger than the observed, the presence of

null alleles probably due to rare mutations in the flanking regions of the

microsatellites could not be excluded (scoring errors or large allele drop-out could

not be detected). The high FIS-values support the probability of null alleles that may

have masked population differentiation. Null alleles were likely present in loci phry7

and phry8. Here the observed heterozygosity was much lower than expected (see

Table 1). After the adjustment of genotypes in these two loci for the presence of null

alleles, no population substructure became evident in P. guineensis. We thus assume

that even though null alleles in the original dataset lead to an overestimate of

homozygous genotypes, population differentiation based on allele frequencies should

have been recognisable.

In conclusion, based on life-history and behavioural observations of P. guineensis

we had expected to find significant levels of genetic differentiation at very small

geographic scales. However, we found that the threshold distance for migration

compensating genetic differentiation was larger than expected and lies somewhere

between the investigated local fine scale (B2 km) and the larger regional

scale (�100 km). Our results suggest that P. guineensis is potentially much more

mobile than expected. As we never observed migration of reproductively active males

between patches, most likely females or juveniles or both may move between these.

The low long-term persistence of tree-holes and thus the increased need of the frogs

to continuously find and settle in new sites, is likely the main reason for the dispersal

of these frogs that otherwise should be limited by their small size and the respective

high mortality risk (Rodel et al. 2004). Our unexpected results show the importance

of combining ecological observations with genetic analyses and suggest that

more research in both fields is needed to fully understand the population structure

and dynamics in amphibians.


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ACKNOWLEDGEMENTS

We thank the ‘Centre de Recherche en Ecologie’ for providing lodging facilities in

TNP. The ‘Station de Recherche en Ecologie Tropicale’ and the ‘Taı Monkey Project’

provided logistic support. Research and collection permission was given by

the ‘Ministere de l’Enseignement Superieur et de la Recherche Scientifique’, of the

Republic of Cote d’Ivoire. The access permit to TNP was issued by the ‘Ministere de

la Construction et de l’Environnement’. S. Frohschammer, G.G. Gbamlin, C.

Harbinger, D. Kratz, J. Ledderose, D. Lorch, C.Y. Ouoro and V.H.W. Rudolf were

of invaluable help during fieldwork and collection of tissue samples. We thank K.

Moller for her help with the microsatellite isolation and other lab work. Three

anonymous reviewers helped to improve a previous draft of the manuscript with their

constructive criticism. This publication is part of the BIOLOG-program of the

German Ministry of Education and Science (BMB�F; Project BIOTA-West III,

amphibian projects, 01LC0617J).

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Received: 7 December 2009; Final acceptance: 16 March 2010


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Small, specialised and highly mobile? The tree-holebreeding frog, Phrynobatrachus guineensis, lacks

fine-scale population structure

LAURA SANDBERGER1$, HEIKE FELDHAAR

2$,

KATHRIN P. LAMPERT3, DUNJA K. LAMATSCH

4 &

MARK-OLIVER RODEL1*

1Museum fur Naturkunde, Leibniz Institute for Research on Evolution and Biodiversity at the Humboldt

University Berlin, Berlin, Germany; 2Behavioral Biology, University of Osnabruck, Osnabruck, Germany;3Evolutionary Ecology and Biodiversity of Animals, University of Bochum, Bochum, Germany; 4Austrian

Academy of Sciences and Institute for Limnology, Mondsee, Austria

ONLINE SUPPLEMENTARY MATERIAL

Table S1. Allelic frequencies for the four loci per patch for all Phrynobatrachus guineensis

within the study area in TNP, Ivory Coast.

allele phry7 phry8 phry59 phry2

1 0.011 0.002 0.002 0.129

2 0.027 0.005 0.011 0.868

3 0.043 0.014 0.185 0.003

4 0.006 0.011 0.008

5 0.021 0.019 0.014

6 0.206 0.014 0.037

7 0.003 0.029 0.243

8 0.033 0.113 0.028

9 0.158 0.008 0.131

10 0.022 0.017 0.049

11 0.006 0.056 0.147

12 0.002 0.097 0.06

13 0.008 0.043 0.015

14 0.009 0.044 0.017

15 0.006 0.011 0.021

16 0.044 0.068 0.008

17 0.062 0.071 0.009

18 0.076 0.084 0.008

19 0.021 0.068 0.002

20 0.068 0.084 0.002

21 0.04 0.083 0.002

22 0.014 0.033 0.005

ISSN 0441-6651 print/ISSN 2153-3660 online

# 2010 Herpetological Association of Africa

DOI: 10.1080/04416651003788619


*Corresponding author. Email: [email protected]$These authors contributed equally to the work.

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Table S1 (Continued )

allele phry7 phry8 phry59 phry2

23 0.013 0.002

24 0.011 0.008

25 0.002 0.013

26 0.013 0.002

27 0.022 0.002

28 0.017

29 0.021

30 0.006

31 0.006

32 0.003

n alleles 632 630 654 658

Notes: Given are the allelic frequencies for all four loci sorted for repeat length (shorter fragments receivedsmaller numbers). Additionally the total number of analysed alleles is given per locus (n alleles).

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Small, specialised and highly mobile? The tree-hole breeding frog, Phrynobatrachus guineensis, lacks...

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