Atta spp.). The cumulative results of all tests reject every prediction of the riverine barrier hypothesis, but are unable to reject several predictions of the Pleistocene refugia and marine incursion hypotheses. Coalescent dating analyses suggest that population structure formed recently (Pleistocene-Pliocene), but are unable to reject the possibility that Miocene events may be responsible for structuring populations in two of the three species examined. The available data therefore suggest that either marine incursions in the Miocene or climate changes during the Pleistocene—or both—have shaped the population structure of the three species examined. Our results also reconceptualize the traditional Pleistocene refugia hypothesis, and offer a novel framework for future research into the area.The evolutionary basis for high species diversity in tropical regions of the world remains unresolved. Much research has focused on the biogeography of speciation in the Amazon Basin, which harbors the greatest diversity of terrestrial life. The leading hypotheses on allopatric diversification of Amazonian taxa are the Pleistocene refugia, marine incursion, and riverine barrier hypotheses. Recent advances in the fields of phylogeography and species-distribution modeling permit a modern re-evaluation of these hypotheses. Our approach combines comparative, molecular phylogeographic analyses using mitochondrial DNA sequence data with paleodistribution modeling of species ranges at the last glacial maximum (LGM) to test these hypotheses for three co-distributed species of leafcutter ants ( Tropical regions around the world are well known for their rich diversity of life. Yet, the reasons why the tropics harbor more species than temperate and arctic regions remain unclear The Pleistocene refugia hypothesis has been responsible for generating the most interest in the field Although some studies The marine incursion hypothesis stems from evidence that tectonic events combined with elevated sea levels, most recently during the mid-Miocene (approximately 10–15 mya), flooded much of the Amazon Basin in salty or brackish water The riverine barrier hypothesis can be traced to early observations on vertebrate distributions by Alfred Russell Wallace Two recent developments have allowed new insights into the predictions made by these hypotheses see . First, The second recent development combines reconstructions of paleoclimates with a flurry of novel techniques for modeling species distributions under current as well as past (or future) climate conditions. Such “paleodistribution” analyses provide a means of independently assessing the extent to which past climate has influenced species' geographic ranges Several recent studies have demonstrated the utility of combining molecular phylogeography and paleodistribution reconstruction in a complimentary fashion to test a priori biogeographic hypotheses Atta (Formicidae: Attini) to test the Pleistocene refugia, marine incursion, and riverine barrier hypotheses using a combination of paleodistribution modeling and comparative molecular phylogeography. Leafcutter ants are widespread throughout the Neotropics We used three co-distributed species of leafcutter ants in the genus A. cephalotes, A. sexdens, and A. laevigata, are ideal for testing the hypotheses in question because (1) they co-occur throughout much of the Amazon Basin, as well as in adjacent areas Three leafcutter ant species, A. cephalotes is the least tolerant of aridity, A. laevigata the most tolerant, and A. sexdens intermediate between the two Atta cephalotes, while expanding the range of the most arid-tolerant, Atta laevigata, with A. sexdens affected to an intermediate extent. To test these predictions, we used a rigorous statistical framework combining paleodistribution modeling with gene tree reconstructions, population genetic analyses, historical demographic analyses, and coalescent dating analyses.We used these three species as independent tests of the predictions of each hypothesis , approximately 21 kya, are shown in olds see  used to olds see  for A. cA. cephalotes, the potential LGM range spanned most of the Amazon Basin, with a contiguous population throughout the Guiana Shield . However, the gene trees for A. cephalotes and A. laevigata did have the relevant basal and derived populations as predicted by both the Pleistocene refugia and marine incursion hypotheses. The gene tree for A. sexdens is split at the base into two reciprocally monophyletic clades that correspond to geographically distinct populations, such that no statement could be made about which populations are basal versus derived.The topologies of mitochondrial gene trees are shown in A. cephalotes . In contrast, partial Mantel tests .Population genetic analyses (AMOVA and Mantel tests) failed to find any evidence that the lower Amazon River has served as a barrier to gene flow for any of the three species –S4. For el tests  could noD statistic, were all consistent with population expansion . In all other instances, at least one statistic was inconsistent with population expansion, or there were insufficient data.Evidence for population bottlenecks and subsequent expansions was mixed in the two tests used . For thediv) between extant populations for each species are shown in div are given in div has a peak within the Pleistocene, and a long tail that extends into the Pliocene and/or Miocene. The long tail results in a rather wide 95% confidence interval, and is partially due to the high value  used as an upper bound for the time since divergence in all three species. This value was chosen based on the results of dating analyses for the tribe Attini, in which the crown group of leafcutter ants were estimated to have originated between 8 and 14 mya max used in this study is thus somewhat conservative and likely extended the 95% confidence interval farther than would a lower value; however, given the data currently available, it would not be justified to use a lower value for tmax.Coalescent dating analyses that estimated the oldest measurable split  to the lower Pliocene (4.893 mya), but does not include the Miocene  extends into the Miocene, including the period between 10 and 15 mya when marine incursions into the Amazon Basin are thought to have achieved their greatest extent A. sexdens (N = 46) and A. laevigata (N = 30) compared with A. cephalotes (N = 118).The 95% confidence interval for population divergence in  Miocene . It therAtta species are not known, typical flight distances for mated queens are thought to be less than 2 km , with a maximum range of no more than 50 km Combining the results of the paleodistribution models with the molecular phylogeographic analyses , the accAtta laevigata at the LGM . However, because of the reciprocal monophyly of the relevant populations of Atta sexdens, the gene tree could not determine which populations were more basal or derived for this species.The molecular data provided mixed support for the predictions of the Pleistocene refugia and the marine incursion hypotheses . ReciproAtta cephalotes, both the marine incursion and Pleistocene refugia hypotheses for Atta sexdens, and both hypotheses  for Atta laevigata. It would therefore appear that the AMOVA is a more sensitive way of testing for the presence of gene flow barriers, although we are not aware of any studies that directly compare the discriminatory power of these two commonly used tests.The Pleistocene refugia and marine incursion hypotheses predict that areas that were historically unsuitable for a species to occur  formed barriers to gene flow. The two methods used to test for the presence of these barriers (AMOVA and Mantel tests) did not always provide congruent results −S4. In fA. cephalotes predicted by the Pleistocene refugia hypothesis, one population (“Brazilian Shield”) of A. sexdens predicted by the marine incursion hypothesis, and one population (“Guiana Shield”) of A. laevigata predicted by both hypotheses. The results of these tests therefore do not provide much assistance in discriminating between the Pleistocene refugia and marine incursion hypotheses.The two methods used to test for population bottlenecks and subsequent expansions, as predicted by both the Pleistocene refugia and marine incursion hypotheses, also occasionally gave conflicting results . We inteA. cephalotes does not include the Miocene, suggesting that marine incursions are unlikely to have been responsible for forming the population structure observed today in this species. However, despite a trend toward diversification during the Pleistocene in all three species .Two disjunct sections of mitochondrial DNA, encompassing part of the Cytochrome Oxidase I (COI) and tRNA-Leucine (tRNAleu) genes, as well as the entire intergenic spacer between COI and tRNAleu were sequenced for all samples. The sequences were concatenated into a single alignment for each species that varied in length from 635 base pairs in 2, 0.04 ul of Taq polymerase, and 5.96 ul of water for a total reaction volume of 10 ul. Average PCR conditions were as follows, with slight modifications depending on the annealing temperatures of individual primer pairs: Initial denaturation at 95°C for 3 minutes was followed by 35 cycles of 95°C for 5 seconds, and an annealing temperature that increased by 0.5°C for each successive round of amplification, beginning at 45°C, for 20 seconds each round, with a final elongation step of 68°C for 15 seconds. PCR products were analyzed by running 3 ul of the product on a 1.5% agarose gel and subsequently visualized with ethidium bromide staining. For samples that successfully amplified, the remaining 7 ul of PCR product were purified by polyethylene glycol (PEG) precipitation, using a 1:1 PCR product/20% PEG mixture which was incubated for 15 min at 37°C followed by a 10-min centrifugation at 2,688×g and two washes with 80% ethanol.Total genomic DNA was extracted from one individual per colony using either the DNeasy Blood and Tissue Kit (QIAGEN) or the AccuPrep Genomic DNA Extraction Kit . Several sets of mtDNA primers  were useCycle sequencing reactions were performed for both forward and reverse sequences using the ABI BigDye Terminator Kit (version 3.1). Sephadex column purification was used to clean the cycle-sequencing product, which was then analyzed on a PRISM 3100 genetic analyzer (Applied Biosystems). Forward and reverse sequences were assembled into individual contigs using SeqMan II v.5.05 (DNASTAR) and alignments between sequences were created initially using Clustal X Estimates of the current and historical potential geographic ranges of each species were made using Maxent version 2.3 Atta, were generally not used in these analyses because they often do not contain detailed geographic coordinates indicating where the collection was made.For each species, a model was constructed for the current potential range using known collection localities (see below) and current climate conditions; the model was then projected onto a reconstruction of climate layers for the LGM to obtain a potential geographic range of each species at the LGM. Localities used as known presence records for each species of leafcutter ant  came prihttp://www.worldclim.org; version 1.4), each with a resolution of approximately 10 km. The methods used to generate these layers are described in Hijmans et al. For current environmental conditions, twenty bioclimatic layers for the entire New World were obtained from the WorldClim dataset , a commonly used measurement for comparison of model performance A. cephalotes, 90% for A. laevigata and A. sexdens) was used to build the model while the testing set was used to test the predictive ability of that model. The number of localities used for testing versus training was dependent on how many sites were available for each species. To test the predictive ability of the model, Maxent's cumulative prediction was converted to a binary (i.e. presence vs. absence) prediction. Ten different thresholds automatically generated by Maxent were used for this conversion and the extrinsic omission rate  was tested against the null hypothesis that it is no better than a random prediction  using a one-tailed binomial test Second, a separate analysis was conducted by randomly splitting the localities into two sets: training and testing. The training set  were grouped together as a single population  were made by projecting the model generated under current environmental conditions onto a reconstruction of the same environmental variables at the LGM  with a difference in log-likelihood scores between constrained and unconstrained searches greater than the empirical difference. The null hypothesis (i.e. constraint topology) was rejected when p values were less than 0.05.To determine whether these predictions were met, mitochondrial DNA gene trees were estimated, using unique haplotypes, with maximum likelihood and Bayesian inference techniques. Maximum likelihood searches were performed with a beta version of GARLI Bayesian searches were conducted in MrBayes version 3.1.2 a priori population groupings in a hierarchical framework http://cmpg.unibe.ch/software/ arlequin3/arlequin31.pdf).To determine whether populations are structured as predicted by each of the hypotheses in question , two typa priori for each species/hypothesis) was calculated in PAUP, using the model of sequence evolution selected by the AIC in ModelTest http://earthquake.usgs.gov/research/ software/#Range). Third, the presence or absence of a potential barrier between two individuals was coded as a binary character and converted to a pairwise barrier matrix. If the straight-line distance between two individuals crossed the barrier of interest (e.g. the Amazon River in the case of the riverine barrier hypothesis), then the barrier was coded as present; if not, the barrier was coded as absent.To further test for the presence of barriers to gene flow, as predicted for each hypothesis, simple and partial Mantel tests For each hypothesis/species, simple Mantel tests assessed the correlation between pairwise genetic distance matrices and the pairwise barrier matrix. Furthermore, isolation by distance was tested for by a simple Mantel test of the pairwise genetic distance and pairwise geographic distance. If both of the above tests were statistically significant, a partial Mantel test was conducted to determine whether the genetic distance between individuals was correlated with the presence of a potential barrier when the effects of geographic distance are removed. All Mantel tests were conducted with the program zt D statistic http://cmpg.unibe.ch/ software/arlequin3/arlequin31.pdf) by simulating random samples under a model of population equilibrium, where the p value is equal to the number of simulated values less than or equal to the observed value of D.Two types of analyses were performed using Arlequin 3.11 Second, pairwise nucleotide mismatch distributions were calculated for each population. A population that is at equilibrium is expected to have a multi-model mismatch distribution due to the stochastic shape of its gene tree, whereas populations that have experienced recent growth should have a unimodal mismatch distribution resulting from a star-like gene tree The refugia and marine incursion hypotheses make similar predictions about how populations should be structured see . However1 and m2) between these populations, the proportion of the ancestral population that founded each of the resulting populations (s and 1-s) and a measure of genetic diversity for the ancestral (thetaA) as well as both resulting populations  in a Bayesian framework using a Markov chain Monte Carlo method. The program assumes that the diverging populations are not exchanging migrants with any other populations To discriminate between these alternative scenarios, a coalescent dating approach was used. The results of the phylogenetic analyses for each species were used to determine where the most basal split occurred between all sampled populations. The approximate date of this split, in years before present (ybp), was estimated using the isolation-with-migration model developed by Nielsen and Wakeley max, was determined based on recent estimates for the origin of the genus Attamax for all three species in our study. All searches used the HKY model of sequence evolution (currently the most appropriate model available in IM for mtDNA evolution), a generation time of 4 years  using the equation, Tdiv = t*u, where u is the mutation rate in substitutions per site per year. The mutation rate for COI was estimated based on unpublished sequence data for the same gene from species spanning the tribe Attini and from divergence times within the Attini, as reconstructed by Schultz and Brady The estimates for t were converted into time in years since divergence Click here for additional data file.Table S2Results of gene tree topology tests. For the parametric bootstrap analyses, p values less than 0.05 indicate rejection of the null hypothesis (i.e. the constraint tree). Bpp is the Bayesian posterior probability of a given constraint topology .(0.07 MB DOC)Click here for additional data file.Table S3Results of Analyses of Molecular Variance (AMOVA). For each hypothesis, population structure was defined as predicted by each hypothesis (see text). The percentage of variance explained by each hierarchical grouping is shown, with an asterix indicating statistical significance as assessed by permutation. The “among regions” grouping is the grouping of interest for the purposes of hypothesis testing in this study .(0.07 MB DOC)Click here for additional data file.Table S4Results of simple and partial Mantel tests of matrix correlation. For each hypothesis, the correlation between corrected, pairwise genetic distance between individuals and the presence or absence of the barrier of interest was tested using a simple Mantel test (Gen Dist×Barrier). The correlation between genetic and geographic distances (Gen Dist×Geog Dist) was assessed to test for isolation by distance. If a significant correlation was found between both matrix comparisons, a partial Mantel test was conducted on all three matrices to determine whether the presence of the barrier of interest was significantly correlated with genetic distance once the effects of geographic distance are factored out . All tests used 10,000 permutations to assess statistical significance.(0.06 MB DOC)Click here for additional data file.Table S5Results of demographic analyses. Pairwise nucleotide mismatch distributions and Tajima's (1989) D tests were used to test for historical population expansion for populations defined a priori for each hypothesis.(0.08 MB DOC)Click here for additional data file.Table S6Summary of coalescent dating analyses using the program IM. Left panel: priors used for estimating Tdiv, the time since earliest population divergence for each species. Right panel: the posterior estimate for Tdiv, as well as the lower (95Lo) and upper (95Hi) 95% confidence limits for each species.(0.04 MB DOC)Click here for additional data file.Table S7List of all samples used, their geographic locations, and GenBank Accession numbers for samples used in molecular analyses. (0.44 MB DOC)Click here for additional data file.References S1(0.02 MB DOC)Click here for additional data file.


Pocillopora damicornis from 26 reefs in Kenya and Tanzania.Studies of population genetic structures provide an indication of direction and magnitude of larval transport and hence are an important component in the assessment of the ability of reefs to recover from severe disturbance. This paper reports data on population genetic structures in the coral FST = 0.023 ± 0.004 SE; p < 0.001), however, only 34% of all pairwise population comparisons showed significant differentiation. Panmixia could not be rejected between reefs separated by as much as 697 km, while other sites, separated by only a single kilometre, were found to be significantly differentiated. An analysis of molecular variance indicated that population genetic differentiation was significant only at the smaller spatial scale (< 10 km), whereas panmixia could not be rejected between groups of samples separated by over 100 km. Estimates of contemporary gene flow showed similar results, with numbers of first generation migrants within each population ranging from 0 to 4  and likely dispersal distances ranging between 5 and 500 km.Gene flow among reefs was found to be variable, with a significant overall genetic subdivision (P. damicornis varied over spatial scales and that this variability occurred at both evolutionary and ecological time scales. This paradox is discussed in light of stochastic recruitment and small scale population structures found in other species of coral. The study also identifies potential source reefs, such as those within Mnemba Conservation area near Zanzibar and genetically isolated reefs such as those within Malindi Marine National Park and Reserve in northern Kenya.This study showed that population differentiation in  Current threats to coral reefs, such as elevated sea water temperatures, coral disease, pollution and destructive and unsustainable fishing methods, have depleted or degraded more than half of the world's coral reefs -4. The pTo date, the processes underlying the highly variable population genetic structures in corals remain poorly understood -14. ManyPocillopora damicornis is a common scleractinian coral, found on tropical coral reefs throughout the Indo-Pacific region [Seriatorpora hystrix [P. damicornis indicate that populations that are influenced by asexual reproduction are less panmictic [c region . It has  hystrix  its morp hystrix -28. Sexu hystrix . Its ase hystrix . Populatanmictic -32 than anmictic . Howeveranmictic  and at Lanmictic . In geneanmictic , whereasanmictic . Interesanmictic ,35,36. HP. damicornis exhibits low tolerance to elevated sea surface temperatures [Like most pocilloporid corals, eratures ,38 and oeratures ,40. Howeeratures ,42 and neratures . As an eThe coast of East Africa displays a mixture of fringing-, rock island- and patch-reefs. From Malindi to Kisite in Kenya, the coast is lined by an almost unbroken fringing reef, behind which extensive lagoonal reefs are found . FurtherP. damicornis at different spatial scales along the coast of East Africa. Levels of connectivity were inferred at evolutionary and contemporary time scales and related to geographic distance among and between reefs as well as the physical location and habitat of the sampled populations. Due to the lack of basic ecological data relating to the reefs included in this study, the underlying project was of an exploratory nature and not hypothesis driven. As a result the discussion is organised around results rather than addressing specific issues or hypothesis.This study was implemented with the aim of examining population genetic patterns in the NF-type of FST outlier tests revealed a signature of positive selection in locus Pd3_002 (probability that simulated FST < sample FST = 0.999). However, all significance tests for the F-statistics were done by bootstrapping over loci and the exclusion of locus Pd3_002 from the analysis did not alter the results. As a result, Pd3_002 was included in the study to maximise the power of the analyses. The ratio of unique multi locus genotypes to sampled colonies equalled 1.0 within all sampled populations but an identical multi-locus genotype was shared between DT 2 and MTW3 (see table FST) and a significant deficit of heterozygotes (except Pd3_005)   than among groups , with no significant deviation from HWE found at the larger spatial scale , nor among sites within any of the seven groups . This remained the case also after excluding highly divergent sites such as Malindi, MMP 1, ZE 1 and ZW 2 .Between population differentiation accounted for 2.3% of the overall deviation from HWE  had a probability of less than 0.01 of being derived from within the site at which they were sampled . Out of these, 14 colonies had a probability of being derived from a genetically divergent, sampled site of > 0.05. Six populations  showed no signs of recent immigration and Mnemba Conservation Area near Zanzibar (ZE 1) was found to be the most likely source population for six colonies sampled across the entire geographic range of the study  showed no consistent pattern or correlation to any obvious difference in habitat and the proportion of the F-types sampled at each site varied from 0 15 sites) to 100% (Kanamai)  results in a coefficient of variation of < 0.25, suggesting that the power of the statistics employed herein with is sufficient.It is important to emphasise that although a very small amount of migration is enough to counteract genetic drift, not rejecting panmixia does not equate to open populations that are capable of seeding degraded neighbouring or distant reefs. In fact, replenishing severely depleted populations requires hundreds or thousands of successful migrants per generation . ConversFST values from previous spatial genetic studies is inappropriate [Seriatopora hystrix [Due to the difference in polymorphism between allozymes and microsatellites, a direct comparison between reported ropriate . Howeverropriate ,47) and ropriate -51. Smalropriate ,34,52 an hystrix ,54 and cF-statistics. Exclusion tests further increased the number of potentially isolated reefs by showing that six reefs show no signs of first generation migrants. MMP 1 was the only site that showed consistent genetic isolation at both evolutionary and contemporary time scales. MMP 1, which is a reef slope site off Bamburi Beach, was isolated from nearby lagoonal populations, corroborating previous results for the massive coral Platygyra daedalea [P. daedalea [For the purpose of managing coral reef ecosystems, processes at ecological time scales need to be separated from those at evolutionary time scales . This cadaedalea . Furtherdaedalea , MMP 1 wdaedalea  who propdaedalea . Such a P. daedalea [A lack of successful dispersal from southerly reefs may explain the divergence of Malindi from other sampled populations. Malindi was found to be genetically isolated from the southerly lagoonal reefs, (with the exception of Kanamai), also in daedalea . Studiesdaedalea -61. AlonMnemba conservation area on the northeast tip of Unguja Island, Zanzibar (ZE 1) is genetically differentiated from all sites except DAR 3 and MAF 1, yet is the most likely source population for 6 of the 31 detected first generation migrants in the data set. This population has the highest genetic diversity, and hence has an increased likelihood of being perceived as the source population of colonies harbouring alleles that are rare or absent in other populations. Another population on Zanzibar (ZW 1) is equally isolated, indicating that these two sites, along with MMP 1, harbour predominantly self seeding populations.Surveys conducted after the 1998 coral bleaching event showed that reefs off the coast of Dar es Salaam were not significantly affected by the bleaching; in fact, hard coral cover increased between 1997 and 1999 . DespiteAll four sites from Mafia are sampled within Chole Bay and within a kilometre of each other. No pairwise comparisons within the group showed significant differentiation, nor are they significantly differentiated to other sampled sites with the exception of the six isolated sites discussed earlier. No comparative data from before and after the 1998 coral bleaching event is available for Chole Bay on Mafia. However, hard coral cover was reported to be 30% in 1999, which would suggest that bleaching had not significantly affected these reefs .Balanophyllia elegans [Seriatopora hystrix [Despite the relatively large geographic distance between the sites at Mtwara and the other reefs, significant differentiation was only found between these sites and the isolated sites of Malindi, MMP 1, ZE 1 and ZW 1 as well as DT 2. Hence, sufficient gene flow to counteract the effects of random genetic drift seemingly occurs at spatial scales of up to 697 km . The exclusion test further reveals that first generation migrants are likely to have dispersed from Mtwara to Zanzibar, a distance of over 500 km. If dispersal occurs primarily through a stepping stone model, a significant isolation by distance should, in theory, be apparent. However, this was not found to be the case for this dataset. Significant isolation by distance has been detected at spatial scales similar to those between sites within groups (1 – 50 km) for the brooding corals  elegans  and Seri hystrix . The res hystrix . Indeed, hystrix . Further hystrix ,65. Howe hystrix ,66 and i hystrix ,67-69. T hystrix ) may welP. damicornis were genetically characterised at one nuclear and two mitochondrial sequence markers and six microsatellite loci. Both genomes support the existence of two reciprocally monophyletic clusters of WIO origin indicative of two reproductively isolated species within P. damicornis. Some interesting observations regarding the 154 colonies that were found to belong to the F-types and hence excluded from the population genetic statistics are worth reporting here. The most striking difference related to the prevalence of asexual reproduction, which would suggest that the two types differ in their preferred, or most commonly utilised, reproductive mode. Among the F-types, 105 colonies out of 154 were found to belong to 14 clonal lineages . Without a doubt, the incorporation of ecological, hydrodynamic and temporal data into the spatial genetic studies would provide a more comprehensive picture of reef connectivity in this region and improve management decisions and conservation efforts. Unfortunately, such data is yet largely unavailable for most of the reefs in the WIO region despite the vital role these ecosystems play both as biodiversity hot spots as well as by providing essential goods and services for rapidly growing coastal towns and communities.In summary, the spatial genetic patterns reported in this study indicate a variable degree of isolation of populations at both ecological and evolutionary time scales, with certain sites showing a high degree of connectivity and others relying mostly on self seeding. The results highlight the importance of identifying and protecting reefs that harbour high levels of genetic biodiversity and that act as potential source reefs, such as Mnemba conservation area on Zanzibar. It also provided further evidence that certain reef slope sites are unique, such as MMP 1, which was shown to be isolated from closely positioned lagoonal populations in the Mombasa marine national park and reserve in both the present study as well as previous studies of another species of coral  to Mtwara marine national park , spanning a distance of approximately 860 km  was cut off a central branch of 19 – 35 colonies at each site, making a total of 825 samples. Samples were collected at least five metres from their nearest sampled neighbour to minimise the inclusion of clones that were a result of fragmentation, and were kept at ambient temperature in 70% ethanol until further processing.® DNEasy kit according to a modified protocol for rodent tails (fragments were placed directly into lysis buffer and Proteniase K and kept in a water bath at 56°C over night). A polymerase chain reaction (PCR) was carried out using six fluorescently labelled microsatellite primers developed for Pocillopora spp.: PV 6 and PV 7 , and Pd3_002, Pd3_004, Pd2_006, and Pd3_005 . The PCR was conducted in 10 μl reactions using 25 ng of DNA, 0.25 U AmpliTaq© (Applied Biosystems), and a concentration of 0.25 mM of each dNTP, 0.1 mM of MgCl2 and 0.4 mM of each primer. The thermal cycling protocol was initiated with 5 minutes at 95°C followed by 30 ×  or 58°C  and 1 min at 72°C) and ended with a 10 minute extension at 72°C. Non amplifying samples were re-run at a 5°C lower annealing temperature than those stated above. PCR products as well as positive and negative controls were visualised on an ABI Prism 3700 DNA Analyzer  together with a GeneScan 500-Rox ladder and genotyped automatically and verified manually using GeneMapper© version 4.0-software .DNA was extracted using the QiagenDue to the prevalence of two genetically distinct but morphologically similar types (F and NF) being present on reefs in East Africa , the population genetic statistics presented in this study are based only on the NF-type, which was found in sufficient numbers on 26 out of the 29 sampled reefs. All downstream calculations are based on 661 NF-type individuals from 26 populations. The sample from Kanamai was entirely made up of F-types and only 3 and 6 individuals from DT 3 and DAR 2 respectively were of the NF-type, hence those three sites were excluded from further analysis.FST-values to 10,000 simulated FST-values according to the FST-outlier method using the Selection Workbench [Resulting genotypes were checked for scoring errors and potential null alleles using Micro-Checker . Loci weorkbench .HO) and expected levels of heterozygosity (HE), according to Nei [To avoid over-estimating genetic divergence between populations, the microsatellite Excel toolkit  was usedg to Nei  and averFIS), sites within total (FST), and individuals within total (FIT), according to Weir and Cockerham [FSG) and between (> 100 km) (FGT) four groups of samples was done using the Arlequin software  regression. Significance values were obtained through a Mantel test using 1000 randomisations. This test was conducted twice, once including all samples and once excluding the most divergent sites .The isolation by distance web service (IBDWS)  was usedThe project was conceptualised by PS, who acquired the funding in collaboration with MG. Collections and laboratory work were done by PS, OH and NO. OH implemented an initial pilot study for this project as his undergraduate thesis work under the supervision of PS and MG. Interpretation of the data and writing of the manuscript was done by PS. MG supervised PS during her PhD work and revised earlier versions of the manuscript.Table of genetic and geographic distances.Click here for fileTable of migrants.Click here for file


M. murinus), in order to investigate such phylogeographic processes on a large tropical island. We also evaluated the effects of anthropogenic pressures (fragmentation/deforestation) and natural features  on genetic structure in order to complement our understanding of past and present processes of genetic differentiation.Pleistocene events have shaped the phylogeography of many taxa worldwide. Their genetic signatures in tropical species have been much less explored than in those living in temperate regions. We analysed the genetic structure of a Malagasy primate species, a mouse lemur with a wide distribution  from two adjacent Inter-River-Systems (IRSs) revealed that forest fragmentation and the river restrict gene flow, thereby leading to an increased genetic differentiation between populations beyond the effect of isolation-by-distance. Demographic simulations detected signals of two successive spatial expansions that could be preliminarily dated to the late Pleistocene and early Holocene. The haplotype network revealed geographic structure and showed deep molecular divergences within and between the IRSs that would be congruent with a two-step colonization scenario.This study supports the hypothesis of a relatively recent spatial expansion of the grey mouse lemur in northwestern Madagascar, which may also explain why this taxon, in contrast to its congeners, has not yet undergone allopatric speciation in the studied area and possibly across its presently wide range. Pleistocene events have shaped the phylogeography of many taxa worldwide . ParticuOne model region for the study of the combined effects of ancient and recent factors is Madagascar. This island has been isolated from all other landmasses during the last 80 million years (My) and different vertebrate groups have undergone complex phylogeographic histories . MoreoveMicrocebus spp.) form an exceptionally diverse genus. The number of described Microcebus species has increased from four to 18 in recent years  due rview in  for a reThe high species diversity of lemurs in general and of mouse lemurs in particular has been explained as a joint effect of topographic barriers  and/or Pleistocene climatic and vegetation changes -19. ReceM. murinus) has a wide distribution as it inhabits the dry deciduous forests from southern to northwestern Madagascar [i) In a recent study Kappeler et al. [M. murinus clade to about 1.4 My, which sets an upper Pleistocene limit for its expansion; ii) M. murinus possesses an ecological preference for dry habitats [iii) M. murinus is the closest relative of M. griseorufus from southern Madagascar [In contrast to most other lemur species, the grey mouse lemur  and with the Bongolava mouse lemur (M. bongolavensis) in two adjacent IRSs at their northern distribution limit , and natural features  on the genetic structure of the grey mouse lemur at its northern distribution edge. Populations in this area are predicted to show signs of a Pleistocene spatial expansion from the likely southern origin towards the northwestern IRSs. Spatial simulations were used to identify the expansion model which fitted best to the patterns of molecular diversity observed in extant A total of 367 monomorphic (81.9%) and 81 polymorphic positions (18.1%) were identified in the D-loop sequences (455 bp) of the 195 individuals. A total of 47 different haplotypes were found which differed in 1-37 positions in pairwise comparisons.2 = 0.104, F = 1.507, n.s.; haplotype diversity: R2 = 0.002, F = 0.028, n.s.).The genetic diversity of sites varied in the ANP, as well as among the isolated forest fragments Table . Three sn > 5). The four samples with most haplotypes (n = 7) were located within the ANP. The three ANP samples with only one or two haplotypes were also the smallest samples with three or five individuals, respectively. Among the isolated fragments, Tanambao possessed the highest number of haplotypes (n = 6), while the other sites were less diverse. When comparing haplotype diversity, allelic richness or nucleotide diversity statistically between the sites in the ANP and the isolated forest fragments, however, no significant difference could be revealed : U = 14.5, n1 = 8, n2 = 5, n.s.; Nd: U = 17; n1 = 10, n2 = 5, n.s.). This lack of statistical evidence could be due to a lack of power given the small overall number of study sites and some variability among fragments and among ANP sites.In general, the ANP samples showed the highest genetic diversity, in particular sites with larger sample sizes , while none of the populations showed significantly positive D values. Similarly, no Fu's Fs values were significant  for any of the samples , either the first and the second or the first and the third . As no specific statistical test is available to determine if a mismatch distribution fits the Model 2, we tested this hypothesis using simulations.The es Table . The viss Figure . The pres Figure . The firs Figure . The secS and C). S is characterized by a series of recent coalescent events which correspond to individuals in the sample that are related . The two older phases (C1 and C2) correspond to the "collecting phases" which occur at the level of the metapopulation, and in our case during the spatial contraction (going backward in time). They correspond to the alleles whose common ancestor can be traced to the time of the range expansion (going forward in time). In a widely distributed but randomly mating population, coalescent events are rare and randomly distributed in time , but during a range expansion from one region, many coalescent events occur around the time of the expansion because individuals are restricted to a smaller geographic area. In the simulated Model 2, the three main periods of coalescence translate into three modes in the mismatch distribution. In the gene genealogy  were above 0.2 and only seven were not significant  and geographic distances (km) were significantly and positively correlated in the IRS1  suggesting the existence of isolation-by-distance within IRS1.Pairwise ΦST values across the Mahajamba river were significantly higher than those between samples from the same side of the river , but we note that some pairwise ΦST values between populations from the same side of the river were also very high .The importance of the Mahajamba River as a barrier to gene flow between IRS1 and IRS2 was tested with an AMOVA and with permutation tests. All variance components and fixation indices were large and significantly different from zero. The highest proportion of the molecular variance (41.2%) was explained by the variations between sites within each IRS while 32.8% is explained by the river (the remaining 26.0% of the molecular variance is explained by the variation within sites). These values should be interpreted with care, however, since we only had two samples in IRS2 which are almost fixed for very different haplotypes. The permutation tests showed that average ΦST values were significantly higher between populations separated by a savannah (n = 21) than between populations separated by a "continuous" forest habitat  were shared among several sites Figure . These ste Marie and Tanambao. Finally, cluster 4 which consists of one haplotype, was only present in the northernmost fragment Tanambao.The network analysis revealed three distinct sets of haplotypes which were separated by more than 23 mutation steps from each other Figure . The firM. murinus in northwestern Madagascar (see below) but could also demonstrate some effects of forest fragmentation, geographic distance and the large river Mahajamba on the genetic structure of this widely distributed mouse lemur species. These anthropogenic and environmental effects shall be discussed first, before we move to the phylogeographic processes.This study provides evidence for two successive spatial expansions of M. murinus. When compared to the sympatric M. ravelobensis, the number of haplotypes and the haplotype diversity per site were not significantly different  would be required to draw stronger conclusions about the effect of forest fragmentation on the diversity of 0-0.656, , four coST values between sites isolated by savannah were significantly higher than those between sites from the ANP (i.e. continuous forest) despite comparable geographic distances. Furthermore, haplotype sharing was typically not observed between isolated fragments but only between sites in the ANP. The only exception was Ste Marie that shared its four haplotypes with different Park populations. It must be emphasized, though, that Ste Marie is separated from the ANP only by a 3 km stretch of savannah. Surprisingly, a previous study on M. ravelobensis in Ste Marie did not find haplotype sharing with ANP populations [Besides affecting the genetic diversity within populations, fragmentation also increased the genetic differentiation between them beyond the effects of isolation-by-distance which was also detected. The average Φulations . These dM murinus. Note that at that time M. ravelobensis and M. bongolavensis specimen were still believed to form two clades within the same species. D-loop haplotypes from the western or eastern side of the river Mahajamba differed in more than 59 base pairs [M. murinus. A later study showed that the two reddish clades had already diverged into two separate species and that the river had probably promoted this speciation event [M. murinus or that M. murinus possesses larger migratory abilities that sustain gene flow between the IRSs (around the headwaters of the large rivers), counteracting genetic drift on both sides of the river. The latter explanation seems to be less likely, since the haplotypes of either side of the river have diverged completely, indicating that the river effectively prevents gene flow between the IRSs. A later arrival of M. murinus in the northwest compared to the ancestors of M. ravelobensis and M. bongolavensis would also explain why the grey mouse lemur clade did not yet undergo speciation in these two IRSs. Ultimately, this barrier function of the river may be sufficient so that populations in the two IRSs may eventually diverge into distinct species.Our study provides evidence for a significant influence of the Mahajamba River on genetic differentiation but not as high as in their reddish sister species. Guschanski et al.  found thse pairs , compareon event . This coM. murinus within IRS1 and IRS2 reached levels comparable to the ones existing between the IRSs. This may indicate that the genetic lineages within the IRSs have diverged very early during the colonization process or that they result from several colonization events. These hypotheses are discussed in the next section.Taken together, the AMOVA and the network analyses suggest that the genetic differentiation in Model 1). Surprisingly, most samples pointed to only one of the two different periods of expansion. Our modelling approach (Model 2) showed that two successive spatial expansions in small-sized populations generate a trimodal distribution similar to the observed distributions. It may be surprising that Model 1 is not significantly rejected even when there are three modes in the mismatch distribution. This can be explained by the fact that the test is always picking up the bigger of the two last modes as a signal of spatial expansion, without considering the smaller one  as demonstrated theoretically [D and Fu's Fs were negative and only 3.7% and 0.0% of those values were significant. Furthermore, a very recent simulation study by Städler et al. [D can exhibit positive values (apparently indicating a bottleneck). Finally, these tests may also be affected by the recent fragmentation as noted above. Altogether, these analyses show the limitations of single statistics such as Tajima's D and Fu's Fs to detect demographic events when more than one such event has taken place [Assuming a Pleistocene colonization scenario which is suggested by its recent date of divergence (about 1.4 Mya) from its southern sister species , we predch Model  showed tch Model  showed tetically  and empietically . This isr et al.  confirmeen place ,32.mismatch analyses suggests that they took place relatively recently. It has already been suggested that the Malagasy forest habitats underwent severe changes during the Pleistocene due to climatic changes associated with the glacial and interglacial periods [M. murinus [M. murinus may have colonized the IRSs at its northern distribution range in the second half of the Pleistocene.The fact that we pick up the signals of spatial expansions in the  periods ,18. Toge murinus , it seemmismatch distributions expected under a spatial expansion model, it is possible to calculate rough estimates for the dates of these two successive spatial expansions. Assuming a constant mutation rate of 10-6 per site per generation (one estimate used for a closely related lemur species [mu), where tau* is the mode of the mismatch distribution and mu is the mutation rate for the whole sequence. The first expansion was thereby estimated to have occurred between 26,500 to 33,500 years ago  and usiM. murinus is proposed: One ancestral population of M. murinus colonized the IRS1 probably before the last glacial maximum (LGM). M. murinus may then have retreated when forests contracted during the dry period associated with the LGM towards the persisting riverine forests along the Mahajamba and Betsiboka. It subsequently re-colonized the area (second wave of expansion) in a period of recent forest expansion following the LGM. This second spatial expansion is supported by the detection of a contact zone with high haplotype diversity, which parallels the events that were described in several other species as a result of postglacial expansions with subsequent admixture [-7 [Given the results of this study, the following scenario for the colonization of IRS1 by dmixture ,35. Thisture [-7 , for exature [-7 -38. Thiste Marie, Tanambao and Mangatelo. IRS2 contains the fragments Tsinjomitondraka and Maroakata. The ANP  is one of the largest remaining forest areas in western Madagascar [The study sites are located in northwestern Madagascar between two major rivers, the Betsiboka in the south and the Sofia in the north. The Mahajamba River divides this area into two IRSs  and were isolated from each other and the ANP by variable stretches of savannah. Euclidean distances between study sites ranged from 13 to 109 km with a maximum distance of 68 km between sites within the ANP. A total of 195 individual samples , collected between the years 2000-2004, were available for this study. The number of individuals per site varied between 3 and 27 (Tab. 2) after capturing mouse lemurs systematically with Sherman Live traps as described in Olivieri et al. [The forest fragments differed largely in size (2 km® Spin PCRapace) following the manufacturer's protocol. Sequencing was carried out by the company Macrogen . Sequences were analyzed with SeqMan II 6.00 (© 1989-2004 DNASTAR) and subsequently cut to a uniform length of 455 bp. The alignment of all sequences was constructed with the program Mega 4.0.DNA was isolated from the ear biopsies using a standard phenol/chloroform extraction . A speciNd, [AR(r)), corrected for sample size variations, was calculated for each population with a sample size >3 from haplotype frequencies using the rarefaction method proposed by Petit et al. [RAREFAC. We used a simple regression  to test whether the number of haplotypes or haplotype diversity could be explained by sample size. Furthermore, a Mann-Whitney U-Test was used to determine if there was a difference in genetic diversity  and Nd) between the ANP samples and the samples from isolated forest fragments. All tests were done using the STATISTICA 5.5 software.The number of haplotypes and the haplotype and nucleotide diversities  were cat et al.  with theD [Fs [Fs-statistic was regarded as significant with a p-value lower than 0.02 instead of 0.05. Negative values of both statistics point towards population growth and/or positive selection, whereas positive Tajima's D values indicate bottlenecks and/or balancing selection.Tajima's D  und Fu'sD [Fs  are knowD [Fs . Followimismatch distributions were constructed for polymorphic samples with a sample size of at least 10 individuals. A mismatch distribution is the distribution of the number of nucleotide mismatches between all pairs of DNA sequences belonging to a population sample. The shape of the mismatch distribution has been shown to be influenced by past demographic events such as expansions and bottlenecks. The distribution is usually bell-shape in populations having increased demographically in the past [In addition to these tests, the past , while ithe past .mismatch distribution rejects statistically the null hypothesis of one spatial expansion, which we call Model 1 hereafter. In this model it is assumed that a population expanded spatially from one deme into a larger area divided in same-sized demes interconnected by gene flow. We estimated also estimated Tau, the time of the expansion .Using the software Arlequin v.3, it is possible to formally test if a mismatch distribution of all the samples from IRS 1 taken together shows three different modes, which is unexpected under Model 1, we investigated a second model (Model 2), which consists of two successive spatial range expansions interrupted by a (moderate) bottleneck (see below). Since no formalized test is currently available for this model, we simulated data according to Model 2 and visually compared the mismatch distributions generated to those observed. Simulations were carried out using the modified version of the SPLATCHE software [M. murinus dataset and also because the IRSs studied here are more likely to represent the periphery than the centre of the expansion. This procedure allows us to simulate the genetic diversity of mitochondrial sequences that underwent an old spatial expansion, then passed through a bottleneck, corresponding to the reduction in size of viable habitat and finally through a more recent spatial expansion into an empty territory. Parameters which correspond approximately to those estimated from our samples were chosen: the older expansion occurring about 30 mutational units of time in the past and the more recent one 10 mutational units of time ago (see the mismatch distribution results). We used a mutation rate of 10-6 per site and per generation [K equal to 50 for all demes, a growth rate of 0.2 and a generation time of one year. Using a migration rate of 0.1, the effective number of migrants exchanged between demes at equilibrium (Nm) is equal to 5.Because the software  describesoftware . Basicalsoftware . Insteadsoftware . The firneration , a carryST. The model of Tamura & Nei [ST-values). The statistical significance was determined by means of 10,000 permutations.Genetic differentiation between populations was measured using Φra & Nei  was chosra & Nei  on the bra & Nei  was perfn < 5: Bealana, Komandria) were excluded from this analysis.An Analysis of Molecular Variance (AMOVA) was carried out in order to detect genetic structure generated by the river Mahajamba, separating the two IRSs. For this analysis, samples were divided into two groups corresponding to IRS1 und IRS2, which makes the results directly comparable to study of Guschanski et al.  on the oST values obtained between populations separated by stretches of savannah (ANP group vs. fragments and between fragments) and those obtained for pairs of populations separated by a "continuous" forest habitat, i.e. within the ANP group including Beronono and Bealana. Since geographic distance is a confounding factor that may inflate "savannah" distances, we only compared pairwise ΦST values for geographic distances lower than the highest one found within the ANP. Consequently, of the three fragments available, Tanambao was excluded from the analysis due to its large distance from the ANP. We regressed ΦST values against geographical distances within the ANP and then compared the residuals obtained with those corresponding to pairs involving a savannah crossing. If the savannah generated an increase in genetic differentiation we expect that the savannah residuals should be more positive than the ANP residuals . The difference between the two sets of residuals was tested using a permutation approach . We also tested for a correlation between the residuals and geographical distances. These computations were performed with R [The influence of the forest fragmentation on genetic differentiation was tested for the populations in IRS1 by comparing the pairwise Φd with R  partly wFinally, for the analysis of genetic structure and haplotype sharing, a haplotype network was constructed with the programme TCS 1.21 . ClusterNS sequenced the samples, performed the alignment, contributed to some analyses and was involved in drafting the manuscript. LC participated in the design of the study, contributed some statistical analyses and was involved in the interpretation and drafting of the manuscript. MC contributed some statistical analyses and was involved in the interpretation and drafting of the manuscript. UR conceived of the study, participated in its design and in data interpretation and drafted the manuscript. All authors read and approved the final manuscript.NS was an undergraduate Biology student in the lab of UR when conducting this population genetics study. LC is interested in understanding how genetic data can be used to reconstruct the demographic history of species with an emphasis on endangered species and on humans. MC leads a research program on population genetics, with a focus on the genetic consequences of past demographic events and natural selection. UR is co-leading a long-term project on the evolution and behavioral ecology of nocturnal lemurs in northwestern Madagascar which is conducted by members of the Institute of Zoology, University of Veterinary Medicine Hannover.ST-values between all study sites  and their significance Table S1 - Pairwise Θ. ANP: sites in the Ankarafantsika National Park, IFFs: Isolated forest fragments, ****: p < 0.0001, **: p < 0.01, *: p < 0.05, n.s.: not significant. For abbreviations of study sites see Table Click here for file


The combination of optimized contribution dynamic selection and various mating schemes was investigated over seven generations for a typical tree breeding scenario. The allocation of mates was optimized using a simulated annealing algorithm for various object functions including random mating (RM), positive assortative mating (PAM) and minimization of pair-wise coancestry between mates (MCM) all combined with minimization of variance in family size and coancestry. The present study considered two levels of heritability (0.05 and 0.25), two restrictions on relatedness  and two maximum permissible numbers of crosses in each generation (100 and 400). The infinitesimal genetic model was used to simulate the genetic architecture of the trait that was the subject of selection. A framework of the long term genetic contribution of ancestors was used to examine the impacts of the mating schemes on population parameters.MCM schemes produced on average, an increased rate of genetic gain in the breeding population, although the difference between schemes was small but significant after seven generations (up to 7.1% more than obtained with RM). In addition, MCM reduced the level of inbreeding by as much as 37% compared with RM, although the rate of inbreeding was similar after three generations of selection. PAM schemes yielded levels of genetic gain similar to those produced by RM, but the increase in the level of inbreeding was substantial (up to 43%).The main reason why MCM schemes yielded higher genetic gains was the improvement in managing the long term genetic contribution of founders in the population; this was achieved by connecting unrelated families. In addition, the accumulation of inbreeding was reduced by MCM schemes since the variance in long term genetic contributions of founders was smaller than in the other schemes. Consequently, by combining an MCM scheme with an algorithm that optimizes contributions of the selected individuals, a higher long term response is obtained while reducing the risk within the breeding program. Eucalyptus globulus, whilst 12] foundIn forest tree breeding, most studies on the effect of mating schemes have compared positive assortative mating (PAM) and RM e.g. -19). The. The19])Recently, it has been demonstrated that, when using quadratic optimization methods like the OC algorithm, the selective advantage is a function of the Mendelian sampling terms rather than the EBVs ,23. The The goal of the current study was to investigate how different mating strategies influence selection response and the accumulation of inbreeding when using OC selection within a typical forest tree breeding scenario. Comparisons were made between simulated populations over seven generations of selection. The simulated pedigrees were typical of those in tree breeding and the trees were assumed to be monoecious. The mating schemes were derived using a simulated annealing algorithm and objective functions were tested. The following mating strategies were evaluated: (1) RM with no constraints on mating relatives; (2) PAM with no constraints on mating of relatives but controls on the full-sib family size; (3) PAMCM: PAM combined with minimum variance in coancestry; (4) MCM1: regular MCM with no additional constraints; (5) MCM2: MCM combined with minimizing variance in family size; (6) MCM3: MCM combined with minimizing family size and finally; (7) MCM4: a combination of minimizing the variances in both coancestry and family size. We used stochastic Monte Carlo simulation procedures to obtain parameter estimates and genetic evaluations are performed using the individual tree model in a restricted maximum likelihood (REML) framework. Moreover, the theory of long term genetic contribution (i.e. based on regression of Mendelian sampling terms over generations) was used to predict any departure from the theoretical maximum limit of genetic gain.2 = 0.05; 0.25) for a maximum of 100 permissible crosses. The data in Table All mating schemes resulted in similar levels of group coancestry for each generation, and these were slightly lower than the pre-defined levels. Tables 7), in comparison with scenarios with very stringent restrictions . The greatest impact of non random mating on G7 was for ΔC = 2% and h2 = 0.05, resulting in 6.2% and 7.1% increased merit for MCM3 and MCM4, respectively. MCM1 always produced less gain than that achieved by MCM2-4, suggesting that the latter schemes produce a better population structure (i.e. they connect more families). This finding is supported by the average number of crosses for each scheme; MCM 2, 3 and 4 produced highest number of crosses in all scenarios . PAM produced a somewhat higher G7 when ΔC = 2%, although the difference was not large.Both PAM and PAMCM resulted in similar levels of Gmax) increased from 100 to 400 . This suggests that MCM2 would increase genetic gain more than RM for selection schemes continuing beyond seven generations.The level of genetic merit increased for all schemes when the maximum number of permissible matings (N2 = 0.05 than for h2 = 0.25 (Table 2 is 0.05. MCM schemes were more efficient in reducing F7 in comparison with RM when ΔC was lower (i.e. more with rigid constraints). MCM1 yielded the lowest F7 of all schemes, reducing F7 by 26-37% in comparison with corresponding levels produced by RM. F7 was always lower for MCM1 than for MCM2, probably as a result of the extra restriction on variation in family size in MCM2, thus allocating mates that were least related. Moreover, compared with RM, MCM schemes always gave a lower sum of squared long term genetic contributions of the founders, suggesting better management of the founder contributions to descendants.In general, the level of inbreeding was slightly higher for h25 Table . One pos7 level was between 26 and 43% higher than corresponding levels obtained by RM. The most likely cause for this phenomenon may be a higher frequency of matings between related trees (i.e. more full-sib matings), particularly at low levels of h2. The high variance in the long term genetic contribution of founder trees and the strong positive deviation from ideal α7 is in accord with the high levels of inbreeding for PAM.There was a two generation delay in inbreeding in MCM1 in comparison with RM and PAM Figure . The rea7, between 27-42% more than corresponding levels for RM (Tables α7) compared to all the other schemes (except PAM). It seems probable that more crosses between half-sibs are allocated using PAMCM, due to the correlation in EBV between half-sibs combined with the relatively high number of crosses performed. As a result, more half-sibs (or other similar levels of relatedness) are crossed, particularly at low h2, because crosses between full-sibs are avoided  in the breeding population over seven generations of selection. We only show the additive genetic variance because non-additive genetic variance was assumed to be absent. No general difference in the trajectories of VA was detectable between mating schemes, apart from a slight reduction in most schemes that could be a result of either the Bulmer effect [A, sometimes even an increased VA was observed after seven generations of selection. Moreover, when h2 was low, more trees were selected on average, thus slowing down the reduction in VA.Table r effect  or the bmax to 400 is shown in Table A was reduced more when Nmax = 400 in comparison with Nmax = 100. This may be because of the increased sum of squared long term genetic contributions or the increased level of inbreeding, reducing the within-family additive variance component more compared to Nmax = 100  over replicates (MC iterations) of estimated variance components varied between mating schemes. For Vaest), at generation 7, on the long term genetic contribution (r) of the founders. Table r displayed non-zero variation over selection candidates at generation seven  > 0, where N is the number of selection candidates in generation 7) in all scenarios, which could indicate a lack of convergence. Nevertheless, the results provide information on the efficiency of the different mating schemes (i.e. in managing the contribution of the founders). We have chosen to present the three most interesting schemes in terms of accumulated genetic merit, namely RM, PAMCM and MCM2. Clearly, the difference in residual variance , this is particularly clear in Figure r values are distributed much more evenly around the line in comparison with their distribution in Figure r clearly depends on the level of the heritability (Table bra) of all schemes. This result implies that the contribution of selected trees became more variable for PAMCM compared with the other schemes and that a few trees make a very high contribution  and lower level of inbreeding (F7) after seven generations of selection compared to equivalent results achieved by RM. Up to 7.1% increase in genetic merit was achieved by MCM2, MCM3, and MCM4 in comparison with corresponding results obtained by RM. On the other hand, MCM1 yielded the lowest level of accumulated inbreeding, with a maximum decrease in F7 of 37% compared with the equivalent estimate obtained through RM. The two mating schemes that used positive assortative mating combined with restrictions on variance in either family size or coancestry  resulted in similar levels of accumulated genetic merit but higher levels of inbreeding compared with RM. In addition, regressions of the long term genetic contribution (r) of founders on estimated Mendelian sampling terms (aest) showed that the minimum coancestry schemes resulted in lower residual variance and, therefore, less deviation from the ideal level of genetic gain. We also demonstrated that the MCM schemes resulted in lower sums of squared r for founders, suggesting that these schemes produce the lowest rate of inbreeding (ΔF) in the population. For estimates of r, we used a robust, deterministic approach that can handle large, complex pedigrees, as suggested by [Here we have demonstrated that different strategies for mate allocation result in different genetic parameters in a tree breeding scenario when optimized contribution selection (OC) was applied over seven generations. In the scenarios considered, the rate of increase in coancestry (ΔC) was restricted to either 1 or 2% for two different levels of heritability (0.05 and 0.25). We found that, in general, the minimum coancestry mating (MCM) schemes produced a higher level of genetic merit  of long term genetic contributions by founders when selecting trees and their mating proportions for each generation of selection. Hence, a more even contribution of trees and avoidance of mating between close relatives caused unrelated families to be connected to a greater extent, thus the OC algorithm can increase the selection differential. Third, a lower level of inbreeding in MCM schemes resulted in a lower reduction in Mendelian sampling variance (less within-family additive variance). Therefore, the level of within-family selection response will be diminished according to When the maximum number of created families in each generation was increased from 100 to 400, in general, increased levels of genetic merit were obtained. However, the relative differences in genetic merit between the mating schemes were reduced. The most likely reason is that management of the long term contribution of ancestors is more important in schemes where fewer full-sib families are created in each generation, since the OC algorithm provides a better opportunity for increasing the between-family selection intensity if the relationships between families are more equal. Consequently, if suitable mating strategies are utilized, such as the MCM schemes, the level of genetic gain will be enhanced in schemes where the number of crosses is few.A simulation study of animal breeding programs  found thWhen PAM has been combined with static selection methods, little improvement in response to selection in the breeding population has resulted, compared with RM, i.e. ,19. As aThe level of coancestry will inevitably rise when directional selection is applied to a closed breeding population. Consequently, inbreeding will also accumulate. By using MCM, the level of inbreeding can be delayed, but will eventually reach the same level as RM. The reason why MCM and RM will generate similar levels of inbreeding in the long term is that all MCM schemes produce greater negative deviation from Hardy-Weinberg equilibrium (see Results). Hence, the asymptotic level of inbreeding will be equal even though the level of inbreeding is lower in the short and medium terms considered here.  comparedr on aest, corresponding to the part of r that does not contribute to the overall genetic gain in the breeding population [r and a), the contribution of each generation proposed by OC will also change . Since see also ,27. HoweA) of the breeding population into consideration since a higher level of VA could be exploited [A for the different mating schemes, although PAM and PAMCM yielded less reduction and sometimes even a slight increase in VA compared with the other schemes. On the other hand, PAM and PAMCM increased the level of inbreeding by up to 44% in comparison with RM and even more in comparison with the MCM schemes; this is not desirable in production populations. This difference between the mating schemes is important to remember. suggestexploited . We founThe levels of heritability (0.05 and 0.25) used in the current study were based on levels reported in , which aIt should be pointed out that the SA algorithm, for some of the mating schemes, was assigned to minimize an object function containing two separate terms or objectives  of the OC algorithm is obtained by introducing LaGrangian multipliers, λ0 and λ1, combined with the constraints on relatedness and on total contribution presentect is a vector containing the mating proportion of the candidate trees in the breeding population at round t (' denotes the transpose of the vector), At is the additive relationship matrix between candidate trees, bt is a vector containing the EBV of the candidate trees, 1 is a vector of ones in all entries and Ct+1 is the constraint on group coancestry in the population at generation t+1. The restriction on group coancestry holds if the increase between generations is small [ct needs to be transformed into integer values; these are called contribution units (ζt) [ζt specify how many potential crosses (matings) each tree can participate in. Furthermore, the limit of the allowed maximum number of crosses each generation is set to Nmax = ∑iζt, i/2. Depending on the outcome of the mate allocation procedure (described in next section), the actual number of crosses performed (Ncro) could then be less or equal to the allowed maximum number of crosses Nmax. Each cross between two parents resulted in one family where the size of the family (i.e. the number of full-sibs) was computed as dividing the total number of plants available each generation (5000) with Ncro. Here, we used the following procedure to convert ct into ζtwhere is small ,13. Howeis small ). In addits (ζt) . ζt specmaxct1. multiply the contribution vector by twice the maximum number of crosses: 2 Nmax ct = ζtmp to the nearest integer below the actual value for each tree i, to obtain the temporary number of crosses summed over all trees ∑iζtmp, i/2 = Ntmp 2. round down 2 Ntmp3. count the total number of families produced so far, Ntmp < Nmaxa. if Nζtmp, i = ζtmp, i + 1) and consequently increase Ntmp by onei. increase the number of matings for the tree i with the highest deviation between the real and integer numbers by one  = 0 indicates that trees i and j are not mated and consequently, if X > 0, trees i and j are mated. In addition, the number of non-zero elements in X is the actual number of crosses Ncro while the sum of all non-zero elements in X is the maximum number of crosses Nmax  = Nmax). The SA algorithm is a stochastic search algorithm that tries to locate a global minimum of a loss function [X), then two randomly chosen matings are rearranged using uniform random numbers  and  are randomly chosen and are permuted into  and  so that X is permuted into X'). A new loss function, L(X'), is computed and compared with L(X). If L(X') < L(X), the new configuration is kept.Optimization of the mating proportions selected individuals in each generation was performed using the simulated annealing (SA) approach of . In eachfunction . The maiX') > L(X), there is still a chance that the new configuration will be accepted, depending on the "temperature" of the system. As the number of iterations increases, the temperature decreases (i.e. the system cools down) and the probability of accepting a new configuration if L(X') > L(X) decreases. The probability of accepting a new state (pk) if L(X') > L(X) isHowever, if L(cb is the Bolzmanns constant and Tk is the temperature of the system [cb is set to 1. The temperature decays according to Tk + 1 = Tk (1 - α) where α is chosen according to the size and complexity of the optimization problem. In the current study, α was set to 0.01 and T0 to 1. Eventually, as the iterations proceed, Tk becomes very low and no further changes occur; at this point, we obtain one solution to our optimization problem. The initial X was obtained by first ranking all trees according to their contribution and then assigning as many contribution units between the top ranked and the second ranked tree as possible, i.e. X = ζt, 2, since ζt, 2 ≤ ζt, 1. Then the first and third ranked trees are assigned contribution units and so on until all contribution units of the best ranked tree are assigned. By continuing this procedure, all contribution units are allocated between all selected trees, even though it might require adding an extra unit to ζi of the penultimate ranked tree. This approximation will most probably have very little influence on the outcome of the simulation process. The SA algorithm has been used extensively for calculating optimal mating schemes in various breeding situations, e.g. [where e system . Furtherns, e.g. ,15,30.The following mating strategies were compared:X) was set to a constant which was kept throughout the iteration procedure, leading to all suggested mating changes being accepted. The total number of changes  was set to 30 000.RM - random mating with no constraints on the mating of relatives. L(X) consisted of two terms: one computed the difference in EBV between mating pairs while the other computed the variance in allocation of contribution units between trees. A strict PAM scheme with no constraints on the mating of relatives was implemented first (i.e. only the rank of parents was used), but this lead to very large family sizes, which severely restricted the OC algorithm.PAM - positive assortative mating based on EBV combined with minimization of variance in family size. Hence, L(2 = 0.05). As a result, full-sibs will be mated more often in PAM than in a RM scenario; this could severely restrict the OC algorithm when selecting from all available candidate trees. Therefore, a combination of PAM and minimization of coancestry variance should lead to a more appropriate population structure, and resulting in an improved outcome for the OC algorithm in comparison with strict PAM. Here, L(X) contained the same term as in the PAM scheme  but also minimizing variance in pairwise coancestry between mates.PAMCM - PAM combined with minimization of coancestry variance (scheme MCM4), because it is very likely that close relatives will be mated in a strict PAM scheme. Estimated EBVs tend to be similar within families and therefore full-sibs are likely to be adjacent to each other, particularly at the lower level of heritability considered here (hMCM1 - standard minimum coancestry mating (MCM), which assigns mating pairs based on the lowest possible pairwise coancestry with no additional constraints. Hence, inbreeding in the offspring generation is minimized. Theoretically, this option should produce the lowest variance in long term contributions in comparison with all other schemes since the only aim of the scheme is to minimize pairwise coancestry between mates. Consequently, the increase in inbreeding of the population will be minimized .X) comprised of one term minimizing coancestry between mates (see MCM1) and one term minimizing variance in family size (see PAM).MCM2 - To achieve a more even population structure, MCM was combined with minimization of variance in family size. By adding this feature to the standard MCM, the genetic merit of the breeding population should be enhanced when using a quadratic selection procedure, as demonstrated by . L(X) coX) contained one term minimizing coancestry between mates (see MCM1) and one term minimizing the family size so that as many half-sib families were created as possible.MCM3 - MCM combined with minimizing family size, which would behave in a similar manner to a factorial mating scheme. It has been predicted that this mating scheme will decrease inbreeding in animal breeding situations  and reduX) contained terms that minimized variance in both pairwise coancestry between mates (e.g. PAMCM) and in full-sib family size (e.g. PAM).MCM4 - here, minimal variance in coancestry was used, since this option should avoid extreme matings (i.e. full-sib matings) and therefore, produce a better population structure. To improve the population structure further, we added minimization of variance in family size. Consequently, L(X. In one case (i.e. RM), simpler algorithms for computing the mating scheme may have been more convenient. Nonetheless, since we already had the SA algorithm implemented in the simulation program, we choose to utilize it as much as possible. This also facilitated comparison between mating schemes because they were all based on the same algorithm. Mathematical descriptions of the loss functions that define the mating schemes are presented in Additional file We ran the SA algorithm with different numbers of iterations and different decreases in temperature, depending on the ratio of accepted/non-accepted proposals for ri, which is the proportion of genes, inherited from ancestor i by a defined generation of descendants. For a non-random mating population, [F, is a function of the sum of squared long term genetic contributions from ancestors to descendants, α is the departure from complete random mating (i.e. deviation from the Hardy-Weinberg equilibrium). Hence, to minimize the rate of inbreeding in the population, the sum of squared long term genetic contributions should be minimized. To estimate ri for all ancestors i, we used the deterministic approach proposed by [ri over different descendants (i.e. the long term genetic contribution of founders did not converge), we used rij is the long term contribution of ancestor i to a particular descendent j and N is the total number of offspring in the last generation . Here, we chose the founder population as ancestors when estimating  introduculation,  proved tposed by . Since wa)In selection algorithms using quadratic indices,  defined ri), which is not apparent with the standard quantitative genetic formula for gain , which [a. We used the following linear regression to determine the impact of the mating scheme on the allocation of r on a at generation 7:Hence, (3) indicates that accumulated genetic gain in the breeding population depends on utilization of the Mendelian sampling term, which corresponds to each individuals' unique contribution to the gene pool. Another important property of (3) is that the rate of gain in the population is related to the pedigree (by means of equation ). A convoreover,  demonstr), which  used to bra corresponds to the regression coefficient, aest is the estimated Mendelian sampling term, c is the intercept and ei ~N is the residual effect. Only trees having a positive contribution  were included in the regression analysis. High values of bra indicate a less equal contribution (utilization) of the selected individuals [bra depends on the restrictions placed on relatedness and how the population structure is improved by the mating scheme.where i ~N0, σe is the ri was generated from N over replicates.Click here for fileObject functions for the various mating schemes. This section contains a full list of object functions used throughout the study.Click here for file


Ailuropoda melanoleuca) living in four isolated patches of the Xiaoxiangling and Daxiangling Mountains. Three geographic distance definitions were used with the "isolation by distance theory": Euclidean distance (EUD), least-cost path distance (LCD) defined by food resources, and LCD defined by habitat suitability.Gene flow maintains genetic diversity within a species and is influenced by individual behavior and the geographical features of the species' habitat. Here, we have characterized the geographical distribution of genetic patterns in giant pandas (A total of 136 genotypes were obtained from 192 fecal samples and one blood sample, corresponding to 53 unique genotypes. Geographical maps plotted at high resolution using smaller neighborhood radius definitions produced large cost distances, because smaller radii include a finer level of detail in considering each pixel. Mantel tests showed that most correlation indices, particularly bamboo resources defined for different sizes of raster cell, were slightly larger than the correlations calculated for the Euclidean distance, with the exception of Patch C. We found that natural barriers might have decreased gene flow between the Xiaoxiangling and Daxiangling regions.Landscape features were found to partially influence gene flow in the giant panda population. This result is closely linked to the biological character and behavior of giant pandas because, as bamboo feeders, individuals spend most of their lives eating bamboo or moving within the bamboo forest. Landscape-based genetic analysis suggests that gene flow will be enhanced if the connectivity between currently fragmented bamboo forests is increased. Capreolus capreolus) [Lagidium viscacia) [Gene flow, in the form of effective individual gene movement within and between populations, is one of the most important factors for maintaining genetic diversity within a species and counteracting the negative effects of habitat fragmentation ,2. Landspreolus) , or mouniscacia) ). Therefiscacia) ), isolatiscacia) .The most common methodology adopted for landscape genetics studies has been the comparison of geographic and genetic distance matrices to describe the geographical structure of genetic variability, at a fine spatial scale, within a population. The Euclidean distance (EUD) was the first metric used for these correlation matrices, and is currently the most frequently used metric for quantifying geographic distance between individuals -13. The Ailuropoda melanoleuca) is often cited as one of the most endangered mammals in the world [2, where it spends most of its time. Females tend to forage only within their home range [The giant panda , generating slightly negative Fis values . The Ho values were higher than the He values, in agreement with results from a previous study of the same region [A total of 136 genotypes were obtained from 192 fecal samples and one blood sample, yielding 53 unique individual genotypes. The consistency between genotypes was checked according to standard replication criteria. Using the formulae , the meae region . No evidIn XXL, there were two individuals living in Luding county. The mean distance to Patch A or B was greater than 70 km. Therefore, because the sample size was small and the mantel test biased, we excluded these individuals in the following analysis.The numerical model was affected by the choice of radius (from 1200 to 1800 m). Small radii tended to yield larger cost distances  [P > 0.05) for a radius of 1500 m.The correlation indices between genetic and pairwise least-cost paths were different for different raster cell sizes because LCD paths, computed using friction maps of different resolutions, appeared to differ in shape and length. The permeability of the local landscape structures depended on the resolution of the friction maps used, which has been observed in studies of the American marten (ericana) . GeneralThe range of power for our test is 0.08-0.34  were enhanced by the presence of habitat types preferred by the species, in agreement with other studies. For example, the mobility of forest species is favored by wooded landscapes, and correlation coefficients between dispersal data and the LCD measures were slightly stronger than with Euclidean distance measures . The effects of habitat suitability depended more strongly on raster cell size and yielded larger SDs (standard deviation) between correlation indices than the effects of bamboo resources. No significant changes were observed in the Mantel test after using LCD  might have played an important role in shaping boundaries of groups in giant panda, notably the significant two genetic clusters, XXL and DXL Figure . MoreoveBashania spanostachya Yi. The forest and food (bamboo) resource fragmentation is the most serious threat to habitat, and has limited the panda's distribution to within three major ditches, the Niuchang, the Dayang, and the Caimagu ditches. Thus, limited food resources may lead to a non-random distribution of individuals. In addition, there was no significant pattern found in the DXL region (Table Yushania lineolata Yi and Bashania spanostachya Yi). Thus, they are able to move freely about the landscape, reflecting the partial random distribution.We found a significant IBD pattern in the XXL region, especially in Patch A Table  and 3. AHere we found that landscape features might influence gene flow of giant pandas across two scales. First, within patches, the use of an LCD measure improves the model for individual movement and gene flow by broadening the geographic measurements that are integrated into one or more important ecogeographical variables, such as food resources (bamboo). However, some uncertainty was introduced by the size of the neighborhood radius defined in the numerical model and by the raster cell size. Although use of a complicated model or several parameters to describe landscape ecology increases uncertainty in the current model implementations, improvements can be made by integrating additional ecological factors, including intra-specific interactions and kin and resource competition. Giant panda research has yet characterized larger populations, which would decrease the bias inherent in small population sizes. If using LCD methods, the effects of neighborhood radius and raster cell size on least-cost path approaches should be rigorously investigated. Second, at a broader inter-patch scale, natural barriers and human activity along the river might have further decreased gene flow and led to habitat fragmentation and subsequent population differentiation of giant pandas in these regions. Therefore, the landscape genetic analysis presented here suggests that it is vital to connect currently fragmented habitats and increase the connectivity of bamboo resources within a habitat to restore population viability of the giant panda in these regions. For these small isolated populations reintroductions will be an effective strategy.In total, 192 fecal samples and one blood sample were collected in each of the four patches of the DXL and XXL mountains Figure  between Ame-05, Ame-10, Ame-13, Ame-15, Ame-16, Ame-26, Ame-22, AFAY161179, and AY161195) were selected for this study on the basis of PCR efficiency, polymorphisms, and yield. To obtain reliable genotypes, a modified multi-tube approach [Tm, and fluorescent dye , using the QIAGEN Mutliplex PCR kit according to the manufacturer's protocol at optimized annealing temperatures. Products were resolved using an ABI 377 prism automated sequencer, and analyzed using GeneScan v3.1.2 and Genotyper 2.5 (Applied Biosystems). Sex identification was carried out according to previously described methods [DNA was extracted from feces with standard controls . Eighteeapproach  was used methods . A speci(ID) and P(ID-sibs)) to quantify the efficacy in discriminating the nine loci in combination.Genotyping errors are frequently encountered in noninvasive genetic analysis using fecal samples ,41, and A), observed heterozygosity (OH), and expected heterozygosity (EH) [F statistics were estimated [ra, were defined [Genetic diversity was measured as the mean number of alleles per locus (ity (HE) . Wright'stimated . We alsostimated . Genetic defined  and comp defined .The Euclidean distance, as the traditional predictor of genetic difference between populations, was calculated using geographic straight-line distances between each pair of individuals using the ArcGIS 9.0 software Figure .2) [The map of the bamboo distribution was imported from a previous study  and our 2) ,29. Diff2)  in ArcviThe Ecological Niche Factor Analysis  model iP values were obtained using a permutation procedure .To test the effects of landscape features on gene flow within the giant panda population, we compared the matrix of pairwise genetic distances with four matrices of geographical distances. The resulting correlations were evaluated by Mantel tests implemented in GENALEX 6.2 . P valuehttp://gpower.software.informer.com/3.1/ to determine the power of the test. In addition, IBDsim [-4 mutation rate was chosen. We conducted 100 simulations with small population size .In order to evaluate the effect using a low number of individuals in our IBD analyses, we used Gpower 3.1 , IBDsim  was usedGeneland is a computer package that allows to make use of georeferenced individual multilocus genotypes to infer the number of populations and the spatial location of genetic discontinuities between populations . We ran XXL: The Xiaoxiangling Mountains; DXL: The Daxiangling Mountains; EUD: The Euclidean distance; LCD: Least-cost path distance; ENFA: Ecological Niche Factor Analysis.FW designed the research. LZ conducted the lab work. LZ, XZ, TM, SZ and FW analyzed the data. LZ and TM conducted the fieldwork. LZ, FW, XZ wrote the paper. All authors discussed the results and commented on the manuscript. All authors read and approved the manuscript.