小雨蛙鳴叫聲地理變異之成因探討與理論檢測

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(1)國立臺灣師範大學生命科學系碩士論文. 小雨蛙鳴叫聲地理變異之成因探討與理論檢測 Hypotheses testing of geographic variation in advertisement calls of Microhyla fissipes. 研究生：李閣桓 Ko-Huan Lee. 指導教授：林思民博士 Si-Min Lin. 中華民國 104 年 6 月.

(2) 致謝「明月別枝驚鵲，清風半夜鳴蟬。稻花香裡說豐年，聽取蛙聲壹片。」想起去年的夏天，蹲在野外的草叢裡，跟小雨蛙們大眼瞪小眼，比賽看誰先發出聲音就輸了的遊戲。雖然在錄音有時會感到心灰意冷，但我很感謝林思民老師對我的指導，並給我這個機會，到台灣的各個地區研究這些小動物，也感謝這些小青蛙們在我每次想要轉身離開的時候，用最熱烈的鳴叫聲把我留下來錄音。首先要感謝家人讓我可以在沒有經濟壓力的狀況下完成研究所的學業，以及在南部做實驗時給我最大的支援，尤其要感謝牧凡每次都優先讓我使用他的汽車去出差，這台車帶我去了很多樣點，也讓我可以順利完成在南部跟東部的實驗。感謝曾經跟我一起去錄音的幫手們－保羅跟京娜完成了可塑性的研究、昱宇特地從嘉義來台南幫忙、胖娘們緯毅在花蓮帶我去找點、光頭家銘連續兩年都跟我去中寮山錄音，還有在野外工作上幫了我最大忙的阿傑，除了可靠的能力之外，也讓我重新思考了人與自然之間的關係。錄音檔分析則是靠沛臻沛臻、黑貓怡潔跟 Fish 燕汝的努力，才讓我可以在做分生實驗之時，也能兼顧到資料分析。說到分生實驗，一定要感謝李昱跟芳神不厭其煩的教我這個新手，還有浥璋幫我抽 DNA，我才能這麼快就做完所有的分生實驗，以及蝸牛學長致維教我使用各種分生軟體，讓我能盡速完成後續分析。感謝展蔚在無聊之餘還能夠指點我統計分析不足的部分，還有大學長彥博在忙到不能再忙得時候，除了提供我樣點資訊外，還教我分生的知識。草魚實驗室的成員－俊文大叔、龍哥、阿平、文宣、曾威、書書、嘉偉、Hùng、晨涵、品如 RURU 老師，謝謝你們不管是在實驗或是生活上的幫助，特別是蟲子，是妳讓我在累到不能自己的時候也能打起精神繼續努力！另外也要感謝所有朋友們的幫助，彥凱、紡蓉、育純、昕凌、姿穎、允琦、創裕、茂羣、林近、會妤，雖然有的時候只是短短的聊天，但也能感覺到自己不會是一個人的充實。尤其是明緯跟博名，還要謝謝你們的家人，在我南部做實驗的那段期間願意提供我住宿，並且要感謝鳳嬬在我快要沒有自信的時候給我信心。還有中山生態實驗室的朋友們，張學文老師、瓊珍學姊、猴哥、英毅哥、爪爪、小白、阿信，給予我在高雄做實驗時的支援。最後要感謝林思民老師、關永才老師及李佩珍老師對我論文的指導，才能讓我在最後能完整呈現我的研究。在這段研究所的期間，除了往讀萬卷書更邁進之外，也藉著野外研究或是研討會的機會行了萬里路，感謝老師總是願意幫我寫推薦信去申請補助，才能讓我有這些機會出國看看別的國家、認識不同的人。在這裡要勉勵自己，這個世界還有許多很厲害的人跟你意想不到的事情值得去冒險嘗試，但不要好高騖遠，扎穩腳步前進才能走的長遠。.

(3) 目錄中文摘要........................................................................................................................ 4 Abstract .......................................................................................................................... 6 Introduction ................................................................................................................... 8 Chapter 1. Reproductive character displacement ....................................................... 13 Materials and Methods ............................................................................................. 13 Results ...................................................................................................................... 15 Discussion ................................................................................................................ 17 Chapter 2. Hypotheses test of acoustic variation ........................................................ 19 Materials and Methods ............................................................................................. 19 Results ...................................................................................................................... 22 Discussion ................................................................................................................ 25 Conclusion .................................................................................................................... 28 References ................................................................................................................... 29 List of tables and figures .............................................................................................. 34 Table 1 ...................................................................................................................... 34 Table 2 ...................................................................................................................... 34 Table 3 ...................................................................................................................... 35 Table 4 ...................................................................................................................... 36 Table 5 ...................................................................................................................... 37 Figure 1 ..................................................................................................................... 38 Figure 2 ..................................................................................................................... 39 Figure 3 ..................................................................................................................... 40 Figure 4 ..................................................................................................................... 41 Figure 5 ..................................................................................................................... 42 Figure 6 ..................................................................................................................... 43 Figure 7 ..................................................................................................................... 44 Figure 8 ..................................................................................................................... 45 Appendix ...................................................................................................................... 47.

(4) 中文摘要動物行為會受到遺傳距離及環境的影響而產生差異，而亦有許多研究指出，物種間的交互作用使個體產生行為特徵上的改變。當親緣關係相近的兩種動物共域時，為了減少錯誤配對的機會，擇汰會加強牠們特徵或行為的差異，此現象稱為繁殖性狀替換（reproductive character displacement）。兩棲類的鳴叫行為直接影響到牠們的適存度，且研究指出兩棲類容易受到地理屏障的影響，因此鳴叫特徵適合用來研究動物行為在地理上的變異。當鳴叫特徵差異分別與遺傳距離及地理距離高度相關時，則鳴叫特徵的變異可能是受到基因漂變（genetic drift）的影響。然而當特徵差異只與地理距離相關時，則可能是受到文化漂變（cultural drift）的影響。除了漂變之外，自然選汰（ecological selection）也可能造成鳴叫特徵的變異，在這個理論的預測下，鳴叫特徵會與環境因子相關。本研究使用小雨蛙（Microhyla fissipes）與黑蒙西氏小雨蛙（M. heymonsi）做為研究材料，小雨蛙廣泛分布在台灣全島的低地平原，在西部的台中及花蓮以南與黑蒙西氏小雨蛙共域，這兩種小雨蛙使用相似的棲地，且發出人耳難以辨認的宣告叫聲。而在過去的調查中，我們也發現小雨蛙的鳴叫聲在各地間有些微的差異。因此本實驗欲檢測以下問題：(1)小雨蛙的鳴叫聲變異，是否是因為與黑蒙西氏小雨的蛙種間交互作用－繁殖性狀替換所造成？(2)基因漂 4.

(5) 變、文化漂變與自然選汰，何者較能解釋小雨蛙種內的鳴叫聲地理變異？我們蒐集了 13 個地點，共 233 隻動物，分析鳴叫聲特性，並與溫度及體型做回歸殘差來校正鳴叫特徵。利用粒線體的 COI 序列來進行族群結構的建立，計算遺傳分化程度及遺傳距離後，進行遺傳距離、地理距離及氣候差異鳴叫特徵差異的相關性。結果顯示，兩物種共域時並不會影響其鳴叫特徵，顯示這兩種小雨蛙間並不存在繁殖性狀替換。鳴叫特徵的差異與遺傳距離呈現顯著的正相關，與地理距離也顯著正相關，顯示鳴叫特徵的地理變異符合基因漂變的假說。另外，鳴叫特徵的差異與年均溫、年均濕度及年降雨量都沒有顯著相關，表示自然選汰並不是造成地理變異的原因。本研究的結果證實基因漂變是最有可能造成小雨蛙鳴叫聲地理變異的原因，而非文化漂變或選汰。. 關鍵字：生殖前隔離、性擇、狹口蛙科、特徵分化、繁殖群集. 5.

(6) Abstract Diversification of signals can provide insight into evolutionary processes of communication system. The forces undergo signal divergence included interaction between species, ecological force, genetic drift, or the recently proposed hypothesis of cultural drift. When closely related species are geographically overlapping, selection would favor differentiated in sexual traits through reproductive character displacement (RCD) in order to prevent from hybridization. Ecological factors such as temperature and humidity would also cause signal divergence in different selective regions. Furthermore, stochastic processes could not be excluded in the evolution of signal diversity. In this study, I tested alternative hypotheses including reproductive character displacement, ecological selection, genetic drift, and cultural drift to figure out the reason for geographic acoustic variation of Microhyla fissipes in Taiwan. I recorded calls from 13 populations, among which 8 populations are sympatrically distributed with the closely related M. heymonsi which produces advertisement calls very difficult for human to distinguish and uses almost the same niche. My results showed that there is no significant tuning of calls in sympatric populations, indicating that RCD does not occur between these two species. Population structure constructed by COI demonstrated that M. fissipes in Taiwan can be divided into four clades: northwest, southwest, south and east, while acoustic signals were significantly different among the clades. Acoustic variation was significantly correlated with both geographic distance and genetic distance. On the contrary, the correlations between acoustic distance and 6.

(7) climatic factors were not significant. I concluded that geographic variation in advertisement call of Taiwan M. fissipes was mainly caused by genetic drift instead of cultural drift. Sexual selection and ecological selection did not affect the advertisement calls of M. fissipes. My study confirmed that RCD did not occur between M. fissipes and M. heymonsi and provided a better understanding of signal evolution. Keywords: lek, Microhylidae, prezygotic isolation, sexual selection, signal divergence. 7.

(8) Introduction Acoustic signals are traits critical to sexual selection and species recognition (Claridge and de Vrijer, 1994; Ritchie, 2007). Rapid changes in. acoustic. signals,. resulted. either. by. genetic. recombination. (Vargas-Salinas and Amézquita, 2013), cultural learning (Lachlan and Servedio, 2004), or ecological adaptation (Morton, 1975; Zigler, et al., 2011), may cause population differentiation. Despite the fact that the divergence in acoustic signals can lead to speciation, whether deterministic or random force plays the major role is still under debate. The variation of acoustic signals is readily quantifiable and may rapidly respond to caller as well as receivers, which make mating calls of amphibians a good model to study the origin of geographic variation in traits. Interaction between closely related species is critical for divergent evolution in sexual traits. The first goal of this study is to test the probable reproductive character displacement (RCD) between species. To avoid from interspecific competition for signal space (Arthur, 1982; Chek et al., 2003; Amézquita et al., 2006; Grether et al., 2009) and heterospecific mating (Gerhardt, 1994; Albert et al., 2007; Moriarty and Lemmon, 2010), sexual selection will favor character displacement when closely related species get into contact (Brown and Wilson, 1956; Pfennig and Pfennig, 2012). Reproductive character displacement hypothesis proposes that traits associated with mating, such as nuptial color or advertisement call, will become more differentiated in sympatric than in allopatric zones. For example, dominant frequency of American green 8.

(9) tree frogs (Hyla cinerea) becomes higher when sympatrically distributed with the closely related barking tree frogs (H. gratiosa) (Höbel and Gerhardt, 2003). Reproductive character displacement facilitates and further maintains pre-zygotic isolation between closely related species, and has the ability to reduce gene flow during speciation. Despite that divergence in sympatry might be a byproduct of competition, differentiation in mating call is important for female recognition on which the reproductive isolation depends. Ecological factors such as environmental temperature or perching habitats can also shape the acoustic variation through different criterions. Studies on birds revealed that the advertisement songs were changed to fit the best transmission efficiency in different vegetation types (Morton, 1975; Wiley and Richards, 1982). Anurans will also tune their acoustic signals when facing environmental heterogeneity in acoustic transmission (Witte, 2005; Vargas-Salinas and Amézquita, 2013). When natural selection occurs, we expect to find discontinuity in acoustic traits between different selective regimes and significant correlation between acoustic differences and ecological factors. Ziegler (2011) found that the temporal property of advertisement call produced by Hypsiboas pulchellus was highly influenced by habitat structure. Furthermore, they indicated that the environmental temperature would affect the dominant frequency via constraint on body size variation. Nevertheless, with only limited case of studies, whether the deterministic force or stochastic process overwhelm the geographic variation in traits is still controversial (Campbell et al., 2010; Jang et al., 2011; Sun et al. 2013). 9.

(10) In addition to deterministic force such as selection, some researches have revealed that genetic drift, consequence of stochastic process or random factor, plays an important role in shaping geographic variation in acoustic traits (Mayr, 1963; Campbell et al., 2010). Genetic drift is a random process in evolution resulted by “sampling error”, leading to random fluctuation in allele frequencies. Isolation by distance is a phenomenon caused by genetic drift when genetic divergence is positively correlated with geographic distance and the geographic barrier between two populations is too far for migrants to cross (Wright, 1943). Amphibians are known for low vagility and are easily separated by geographic barriers (Monsen and Blouin, 2004; Funk et al., 2005; Pröhl et al., 2006; Guarnizo, 2009). If positive correlation between acoustic difference with geographic and genetic distance were detected, genetic drift might be the major force underlying acoustic divergence. Study on greenish warbler (Phylloscopus trochiloides) indicated that stochastic process rather than environmental factors shaped the signal divergence in this ring species (Irwin et al., 2008). Although it is believed that natural selection is the main force contributing to phenotypic diversity, genetic drift can still trigger speciation through interacting with sexual selection (Uyeda et al., 2009). In mammals and birds, cultural transmission is another factor which can lead to geographic variation in songs. Grand and Grand (1996) found that the songs of medium ground finch (Geospiza fortis) were inherited by their paternal songs but not maternal ones, indicating that the variation in songs was not affected by genetic inheritance. Cultural drift hypothesis 10.

(11) predicts that geographic variation in signals is only correlated with geographic distance but not genetic distance. For instance, studies of greater horseshoe bats (Rhinolophus ferrumequinum) showed that variation in resting frequency of echolocation calls among regional groups are affected by selection, while the force underlying differences within groups is cultural drift (Sun et al. 2013). Almost the same pattern has been detected from the widespread Himalayan leaf-nosed bat (Hipposideros armiger), suggesting that cultural factors affect the divergence in acoustic signal as well as the selection does (Lin et al. 2014). Nevertheless, the cultural transmission theory was mostly reported from mammals or birds, while research of the learning behavior on anurans is still at its preliminary stage. Although there is no evidence that the caller would learn from the members of its lek, some species learn to adjust their aggressive behavior by recognizing their neighbor in the theory of “dear enemy” (Davis, 1987; Bee, 2003). Microhyla fissipes distributes widely throughout the low land area of Taiwan. Geographically, they overlap with their closely related congener Microhyla heymonsi in the southern two thirds of the range. In allopatric areas, these two species produce advertisement calls which are almost indistinguishable to humans (Kuramoto, 1987). Therefore, the first goal of this study is to detect the probable reproductive character displacement between these two species. This hypothesis could be supported if the differences of advertisement calls are larger in sympatric than allopatric regions. Furthermore, geographic variation among different Microhyla 11.

(12) fissipes populations is another issue of this study. In this study, I tested alternative. hypotheses. by. quantifying. geographic. variation. in. advertisement calls of Microhyla fissipes in Taiwan. The aim of this testing was to find the best hypothesis which can explain the evolutionary force shaping acoustic difference. The genetic drift hypothesis predicts a positive correlation between variation in calls with both geographic and genetic distances. In contrast, the cultural drift hypothesis predicts that the variation in calls is correlated only with geographic distance, but not genetic distance. Last, the ecological selection hypothesis predicts that the variation in calls is correlated with environmental factors. My results will provide a better understanding of anurans learning behavior in communication systems and take a further look at the importance between selection and drift in the evolution of geographically acoustic variation.. 12.

(13) Experiment 1. Reproductive character displacement. Materials and Methods Sample collection A total of 233 Microhyla samples were collected from 13 localities including seven allopatric and six sympatric sites in Taiwan during March to August, 2014 (Fig. 1). The latitude, longitude and elevation of each locality were recorded using a GPS receiver (Oregon 550t, GARMIN Ltd, Taipei, Taiwan) (Table 1). The habitats of M. fissipes contains litters, grass lands and temporary waters (Tseng, 2012) where they aggregated as leks after raining in the breeding season. Their breeding leks were highly overlapping with M. heymonsi in the sympatric zones. I captured each individual after advertisement call recording and put them into a plastic ziplock bags for morphological measurements. All individuals were weighed to nearest 0.01 g, and snout vent length (SVL) were measured to nearest 0.01 mm using a digital caliper (Mitutoyo, Kanagawa, Japan). I clipped one of the frogs’ hind leg toes for genetic analysis and preserved in 95% ethanol. Since advertisement calls of anurans may be influenced by environmental factors, temperature and humidity were recorded using a thermos-hygrometer (Lutron, Taipei, Taiwan) in the mean time when I did the acoustic records. I released the captured frog at their original localities immediately after recording and measurements.. Advertisement calls recording and analyses Advertisement calls were recorded at a rate of 44.1 kHz, 16 bit 13.

(14) resolution using digital recorder (Sony PCM-M10) with a shotgun microphone (Sony ECM-CG50), which was placed as close to the calling male as possible. I recorded at least 20 consecutive calls from each individual, then used Raven pro v1.4 (Cornell Lab of Ornithology, Ithaca, NY, USA) to measure the acoustic traits. The calling patterns of M. fissipes and M. heymonsi were composed of a series of calls. Each call is constituted by numerous pulses. For the temporal properties, I measured call duration, call interval, call rate, call rise time and fall time. I also counted the number of pulse inside a call as pulse number. For the spectral properties, I measure the greatest peak on the power spectrum (FFT = 1024 points, Hanning window) as dominant frequency, and the frequencies which divide the call into 25% and 75% of the energy on the spectrogram. Individual call parameters were obtained by averaging 20 calls from the same frog.. Removal of environmental effects Before removing environmental effects, I reduced redundant characters by principal components analysis on which duplicated variables over datasets were identified and combined into principal components. Then I conducted Pearson correlation test to test the correlation between the highest two principal components with environmental temperature and body condition. The body condition was standardized from snout-vent length and body weight by scaled mass index (SMI), which performed better than other body condition index in predicting the fat and other body components (Peig and Green, 2009; 14.

(15) 2010). I took linear regression residuals of the significant factors with the principal components as new environmental independent acoustic traits to do the subsequent statistical analyses. The SMI was calculated using R version 3.11 (R Foundation for Statistical Computing), the others were conducted using JMP 11.0 (SAS Institute Inc., Cary, NC).. Test of reproductive character displacement Because the data didn’t fit the assumptions of the parametric method, I used the nonparametric method, Mann-Whitney test, to compare the differences of acoustic signals between M. fissipes and M. heymonsi. I examined whether the differences of acoustic signals were enhanced in sympatric areas by conducting Krustkal-Wallis test where I divided the M. fissipe into western and eastern groups. Then a post-hoc Steel-Dwass all pairs test was conducted to compare the acoustic differences of M. fissipes between groups in which the M. heymonsi was present or absent. All the statistical tests above were conducted using JMP 11.0 (SAS Institute Inc., Cary, NC).. Results Analysis of acoustic plasticity I classified the acoustic traits of M. fissipes into temporal properties (PC1) and spectral properties (PC2) based on the result of PCA (Fig. 3). Both of these two acoustic properties are significantly correlated with air temperature, while SMI and the interaction between these two factors were not significant (Table 2). Therefore, the linear regression residuals 15.

(16) were calculated from the correlation between acoustic traits and air temperature.. Acoustic difference between M. fissipes and M. heymonsi All the acoustic traits (call duration, call interval, call rate, call rise time, call fall time, pulse number, dominant frequency, 1st quartile frequency, 3rd quartile frequency and IQR bandwidth of frequency) were significantly different between M. fissipes and M. heymonsi before the adjustment with environmental effect. I summarized these acoustic traits by PCA which showed that these two species could be distinguished into two. groups. mainly. by. temporal. properties. (PC1). (Table. 3).. Mann-Whitney test also indicated that these two species are similar in spectral properties (p=0.5320) but were significantly different in temporal properties (p<0.0001). After removing the effect of air temperature, the difference of temporal properties between M. fissipes and M. heymonsi was still significant (p<0.0001). Compared to M. heymonsi, M. fissipes produced shorter advertisement call, higher call rate, higher pulse number, and lower spectral frequency (Table 4). In Kruskal-Wallis test, I compared the acoustic traits of these two Microhyla between allopatric and sympatric zones, and I found that the differences in both temporal properties (PC1) and spectral properties (PC2) of M. fissipes between allopatric and sympatric zones were not significant (p=0.5145). This result indicated that interaction between these two microhylids is not a critical factor resulting acoustic variation.. 16.

(17) Discussion In this chapter I solved whether reproductive character displacement occurs between M. fissipes and M. heymonsi. The results showed that acoustic signal of M. fissipes was not affected by M. heymonsi and did not support the reproductive character displacement hypothesis. Advertisement calls from M. fissipes and M. heymonsi are so similar that most people are difficult to distinguish between the two. My results showed that the advertisement call is significantly different between M. fissipes and M. heymonsi in temporal properties (fast versus slow tempos), but not for the spectral properties (low versus high frequencies). This might be the reason why their mating call is hard to be distinguished by human. Hybrids between the two species have never been reported in the wild; my study and Lin (2009) both showed the congruence between mitochondrial and morphological identifications, thus also rejected the probability of hybrids between these two species. Although the temporal properties between these two frogs are significantly different, the distributions of the traits are highly overlapping (Table 4). Without reproductive character displacement in the sympatric zones between the two frogs, how their females recognize their mates is still unknown. I doubt that the differences in temporal properties might be adequate for females to identify conspecific males, although I have not yet designed experiments to test this prediction. Gerhardt (1994) indicated that females might be under more severe impact from heterospecific mating, which will promote reinforcement on mate discrimination (Sæ tre, 1997; Höbel and Gerhardt, 2003). Although I failed to detect RCD on male 17.

(18) advertisement calls, I suppose that RCD might occur on visual cues because these two Microhyla are more diverted on morphology than acoustic traits. There are usually ornate dark or brown lines on the back of M. fissipes and a grey stripe from their eye to hind leg. On the other hand, there are usually two arcuate black lines beside the dorsal line and a dark stripe running on their body side. In some cases, visual cues for female choice have been proved to be as important as acoustic ones in frogs (Candolin, 2003; Gomez et al., 2009). Anurans remain high sensitivity to visual signals for predation, communication and mate choice even in low luminous environment (Aho et al., 1988; 1993; Cummings et al., 2008; Preininger et al., 2013). In my case, advertisement calls may be an aggregation signal for females to locate the leks, while visual cues were further used to distinguish the mates.. 18.

(19) Experiment 2. Hypotheses test of acoustic variation. Materials and Methods Sample collection A total of 233 Microhyla samples were collected from 13 localities in Taiwan during March to August, 2014 (Fig. 1). The latitude, longitude and elevation of each locality were recorded using a GPS receiver (Oregon 550t, GARMIN Ltd, Taipei, Taiwan) (Table 1). The habitats of M. fissipes contains litters, grass lands and temporary waters (Tseng, 2012) where they aggregated as leks after raining in the breeding season. I captured each individual after advertisement call recording and put them into a plastic ziplock bags for morphological measurements. All individuals were weighed to nearest 0.01 g, and snout vent length (SVL) were measured to nearest 0.01 mm using a digital caliper (Mitutoyo, Kanagawa, Japan). I clipped one of the frogs’ hind leg toes for genetic analysis and preserved in 95% ethanol. Since advertisement calls of anurans may be influenced by environmental factors, temperature and humidity were recorded using a thermos-hygrometer (Lutron, Taipei, Taiwan) in the mean time when I did the acoustic records. I released the captured frog at their original localities immediately after recording and measurements.. Advertisement calls recording and analyses Advertisement calls were recorded at a rate of 44.1 kHz, 16 bit resolution using digital recorder (Sony PCM-M10) with a shotgun 19.

(20) microphone (Sony ECM-CG50), which was placed as close to the calling male as possible. I recorded at least 20 consecutive calls from each individual, then used Raven pro v1.4 (Cornell Lab of Ornithology, Ithaca, NY, USA) to measure the acoustic traits. The calling patterns of M. fissipes and M. heymonsi were composed of a series of calls. Each call is constituted by numerous pulses. For the temporal properties, I measured call duration, call interval, call rate, call rise time and fall time. I also counted the number of pulse inside a call as pulse number. For the spectral properties, I measure the greatest peak on the power spectrum (FFT = 1024 points, Hanning window) as dominant frequency, and the frequencies which divide the call into 25% and 75% of the energy on the spectrogram. Individual call parameters were obtained by averaging 20 calls from the same frog.. Sequencing and analyses of mitochondrial DNA I extracted the DNA from the toes by using the EasyPure™ Gel/PCR DNA Fragments Extraction Kit (Bioman Scientific Co., Ltd). The COI sequence was amplified using primer LCO020 (5’ TTT CAA CCA ACC ACA AAG ACA TGG G 3’) and HCO710 (5’ TAT ACT TCA GGG TGG CCA AAR AAT CA 3’) via polymerase chain reactions (PCR). I performed double-stranded polymerase chain reactions in 20 μl volume with the following steps: 1 cycle denaturation at 94°C for 3 minutes, followed by 35 cycles at 94°C for 30 seconds, annealing at 50°C for 40 seconds, and 72°C for 60 seconds, with final elongation at 72°C for 10 minutes by iCycler Thermal Cycler (Bio-Rad). PCR products were run on 20.

(21) 1.2% agarose gels in 1X TBE buffer to confirm that the lengths of the particular fragments were correctly amplified. Automated PCR products were carried out with the same primers for both directions on ABI 3730 by Genomics BioSci & Tech Corp. (Taipei, Taiwan). Sequences were edited by Sequencher v4.9 (GeneCode, Boston, MA, USA) and aligned by ClustalX (Jeanmougin et al., 1998). I used MEGA v6.0 (Kumar et al., 2004) to estimate the best-fit model for evaluating phylogenetic relationship and calculated the pairwise genetic distance between populations. Genetic differentiation (Fst) among populations were calculated by using DnaSP v5.1 (Librado, Rozas, 2009). I constructed haplotype neighbor-joining network using Network v4.6.. Test of genetic drift and cultural drift The correlation between acoustic differences with geographic and genetic distances was accessed using Mantel test, which was analyzed in R version 3.11. First, I calculated the dissimilarity matrices of acoustic differences between each locality pairing by conduction a post-hoc Steel-Dwass all pairs test on residual PCA scores. The geographic distance was calculated as the shortest distance between GPS coordinates of two localities. Then, I conducted Mantel test with 1,000 permutations to correlate acoustic differences to geographic distances and genetic distances, respectively.. Test of ecological selection The climate data covering 1981-2010 were collected from Central 21.

(22) Weather Bureau (Taipei, Taiwan). Because the acoustic traits and transmission abilities were reported to be affected by temperature, humidity and precipitation (Gerhardt and Huber, 2002; Ziegler, 2011), I extracted annual mean temperature, annual mean relative humidity and annual precipitation for each locality. Pairwise correlation between these three climates variables and acoustic differences were performed on Mantel test using R version 3.11. I tested the correlation between acoustic distances and climatic variables after removing the effects of geographic or genetic distances by partial Mantel test. If the correlation between acoustic differences with genetic and geographic distances was significant, I would correlate the residual of acoustic differences to climate data to investigate the effect of ecological selection on acoustic variation.. Results Genetic analysis I amplified mitochondrial COI sequence (674 base pairs) and recovered 24 haplotypes with haplotype diversity (h) 0.8804 in M. fissipes from 13 localities in Taiwan. Population differentiation (Fst) ranged from 0 to 0.999 among M. fissipes (Table 5). Genetic distance estimated by K2 model ranged from 0 to 0.00657 (Table 5). There is highly significant correlation between K2P genetic distances and geographic distances (r=0.6421, p=0.0010), showing a pattern of isolation by distance in M. fissipes. The population of M. fissipes can be diverged into four major clades: North-West (NW, from 2 populations), 22.

(23) South-West (SW, from 5 populations), East (E, from 5 populations), and South (S, from only 1 population occurred with a few individuals from the SW and the E clades) (Fig. 5). The result of minimum spanning network showed congruent pattern to phylogenetic tree, NW was differed from SW, KT and East by 2, 3, 2 mutational steps (Fig. 6).. Geographic variation in advertisement calls The result of Kruskal-Wallis test showed that the residual PC1 and residual PC2 were both significantly different among localities (p<0.0001). In Steel-Dwass all pairs test, I found that residual PC1 of Wulai population was significantly different from those of Emei population (p=0.0487), south-western group (Wusanto: p=0.0183 and Neipu: p=0.0003), southern group (Kenting: p=0.0005), and eastern group (Shanli: p=0.0008, Changbin: p=0.0266, Mataian: p=0.0003 and Mijian: p=0.0024). Besides those of Wulai population, Residual PC1 of Emei population is significantly different from those of south-western group (Wusanto: p=0.0002, Chungliao mountain: p=0.0226 and Neipu: p=0.0002), southern group (Kenting: p=0.0003) and eastern group (Shanli: p=0.0002, Changbin: p=0.0266, Mataian: p=0.0001 and Mijain: p=0.0013). Residual PC1 of Wusanto population was also significantly different from those of Mataian population(p=0.0064). Residual PC1 of Chungliao mountain poulation was significantly different from those of Kenting population (p=0.0335) and Mataian population (p=0.0070). In summary, the residual PC1 is significantly different between each group pairs (p<0.0001 for all), with partial difference among populations (Fig. 23.

(24) 7). The significant difference in spectral properties (PC2) was resulted by Mataian population, it was significantly different from Hsinchu, Shanli and Taipei population. The result would be insignificant if I withdraw Mataian population. The acoustic signal could be divided into north-western. population,. south-western. population,. and. eastern. population, since I only have one sampling locality which was Kenting in the South group, it was excluded of acoustic groups.. Correlation of acoustic variation In mantel test, there was significantly positive correlation between pairwise residual PC1 differences and geographic distance (r=0.3981, p=0.017982) (Fig. 8a). Furthermore, the correlation between pairwise residual PC1 differences and genetic distance was also significantly positive (r=0.3238, p=0.037962) (Fig. 8b). On the contrary, the ecological factors, annual temperature (r=0.2003, p=0.10889), annual relative humidity (r=0.03581, p=0.33666) and annual precipitation (r=0.1009, p=0.13686), were insignificantly correlated with pairwise residual PC1 differences (Fig. 9). Even after I removed the contribution of either geographic distance (annual temperature: r= − 0.08491, p=0.63736; annual relative humidity: r=−0.1897, p=0.9001; annual precipitation: r= − 0.07927, p=0.59441) or genetic distance (annual temperature: r=0.03584, p=0.33367; annual relative humidity: r=−0.1587, p=0.84515; annual precipitation: r=−0.07633, p=0.61538) by partial Mantel test, the correlation between climatic distances and acoustic distance remained insignificant. This result showed that ecological factors did not affect the 24.

(25) acoustic variation.. Discussion In this experiment I aimed to select a hypothesis which could best explain the geographic variation in advertisement calls. The insignificant correlation between acoustic traits and environmental factors indicated that selection from these factors did not shape the geographic variation in calls. My data supported that the pattern of acoustic variation in advertisement call fits the prediction of genetic drift hypothesis, which might play a major role in acoustic variation more than cultural drift and selection in M. fissipes.. Selection hypothesis was not supported There are evidences that environmental factors such as temperature and humidity could cause variation in sound transmission (Ryan, 1990; Snell-Rood, 2012; Luo et al., 2014). I tested the effect of temperature, humidity and precipitation, but all these climatic factors had no impact on temporal differences. Although spectral properties might be sensitive to microhabitats in some cases (Bosch, 2004; Vargas-Salinas and Amézquita, 2013), I did not detect any variation in the spectral properties of M. fissipes except for the Mataian population. In addition to climatic factors, some studies indicated that the composition of habitat would stand for either barriers or amplificatory to acoustic signals (Ryan et al., 1990; Wilkins et al., 2013; Tan et al., 2014). Since M. fissipes prefers perching on grassland or open ground (Tseng, 2012), I propose that habitat 25.

(26) structures are not an important element leading to acoustic variation in this frog. Background or anthropogenic noise might be another environmental factor causing the acoustic variation. Anurans were found to modulate their advertisement calls with the traffic noise and mix-species assemblage (Witte et al., 2005; Phelps et al., 2007; Kaiser and Hammers, 2009). Reichert and Gerhardt (2013) indicated that Hyla versicolor is able to mediate their call timing in the chorus, which mean that lek size might have influence on temporal properties. In a recent study, I also found that the call rates would be significantly decreased when lek size exceeds 200 individuals (Lee et al., unpublished data). The lek size where I recorded the advertisement calls of M. fissipes or M. heymonsi was always lower than 200 individuals, which helped to rule out this affect.. Genetic drift hypothesis explains acoustic variation It is believed that calling behavior can be parental transmitted or horizontal transmitted. Since parental care does not occur in M. fissipes, cultural transmission for this frog is less probable. Some research on avian and mammals indicated that social learning from congeners in the same group plays an important role in shaping acoustic signals (Tyack, 2008; Sewall, 2009). Yet, I failed to find any evidence whether the advertisement calls of M. fissipes could result from social learning or being constrained by anatomy. Genetic drift hypothesis predicts that the acoustic difference would be positively correlated with genetic and geographic distance. On the 26.

(27) other hand, cultural drift hypothesis predicts that the acoustic difference would be only correlated with geographic distance, but not genetic distance. The pattern of acoustic variation in this study supports the prediction of genetic drift. It has been reported that stochastic process is a major force shaping acoustic variation in some animals (Irwin et al., 2008; Ohmer et al., 2009; Campbell et al., 2010). Since the correlation between genetic distance and acoustic differences is nearly insignificant, genomic data might help to provide a better understanding of population differentiation. However, considering the phylogeny tree and haplotype network are coordinate with the former research of population differentiation in other Taiwanese anurans (Lin, 2009; Lin et al., 2012), the result would not be altered even if I additionally use the faster evolving nuclear marker such as microsatellites. Genetic drift showed that populations of M. fissipes from different clades randomly obtain beneficial mutations to adapt to similar environments. Acoustic divergence due to genetic drift could be the beginning of speciation. My research demonstrated that acoustic divergence of M. fissipes was mostly resulted by genetic drift with no effect of selection. However, speciation through acoustic divergence by genetic drift should contain assortative mating between different populations. Further research on female preference is still needed to answer whether genetic drift could lead to greater divergence in different clades of M. fissipes.. 27.

(28) Conclusion This study demonstrated that reproductive character displacement in advertisement call does not occur between Microhyla fissipes and M. heymonsi. Although these two microhylids produce similar calls in spectral properties, they can be discriminated by their temporal properties. The significantly positive correlation between acoustic difference with genetic and geographic distance indicated that the force underlying geographic variation in advertisement call of M. fissipes might be genetic drift. This conclusion consists with other studies (Campbell et al., 2010; Jang et al., 2011) in advocating that genetic drift might be the main force shaping geographically acoustic variation, while discords with other studies (Sun et al., 2013; Lin et al., 2014) in suggesting that there is no contribution from neither direct nor indirect selection.. 28.

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(34) List of tables and figures Table 1. Specific sampling localities of Microhyla fissipes and M. heymonsi. Abbreviation of each localities were shown in the bracket. Locality. Latitude. Longitude. Wulai (WL). 24.8898. 121.5672. Emei (EM). 24.68715. 121.0135. Dakeng (DK). 23.7266. 120.6212. Wusanto (WS). 23.2383. 120.3753. Chungliao mountain (CL). 22.8090. 120.4102. Neipu (NP). 22.6393. 120.6025. Kenting (KT). 21.9548. 120.8197. Shanli (SL). 22.8525. 121.1504. Changbin (CB). 23.3053. 121.4236. Mataian (MT). 23.6589. 121.4130. Mijian (MJ). 23.847. 121.5421. Table 2. Effect of air temperature, body condition (SMI) and interaction between them on the acoustic characters of Microhyla fissipes.. Temporal properties. Spectral properties. GLM. df. Estimate. SE. F. p. Air temp.. 232. -0.352. 0.033. 115.151. <0.0001. SMI. 232. 0.559. 0.445. 2.380. 0.211. Air temp. × SMI. 211. 0.103. 0.138. 36.375. 0.456. Air temp.. 232. 0.154. 0.058. 7.009. 0.009. SMI. 232. -0.395. 0.607. 0.423. 0.516. Air temp. × SMI. 211. 0.350. 0.243. 2.937. 0.152. 34.

(35) Table 3. Loadings of the first two principal components summarizing variation in advertisement calls of Microhyla fissipes and M. heymonsi Principal component Call variables. PC1. PC2. Duration (s). 0.96677*. 0.052593. Rise time (s). 0.889234. 0.220503. Fall time (s). 0.831445. -0.23667. Interval (s). 0.734177. 0.152155. Call rate. -0.91824. -0.07786. Pulse number. 0.432403. -0.08165. Dominant frequency (Hz). -0.06375. 0.899683. Q1 frequency (Hz). -0.0536. 0.929585*. Q2 frequency (Hz). -0.14828. 0.817934. IQR BW of frequency (Hz). -0.07939. -0.38317. Percent of variance explained. 40.2. 26.3. * the highest loading of each principal component.. 35.

(36) Table 4. The acoustic difference between Microhyla fissipes and Microhyla heymonsi. All the acoustic traits were significantly identical but highly overlapped.. 36.

(37) Table 5. Genetic differentiation (Fst, upper-right) and pairwise genetic distance (Kimura-2-parameter, lower-left) among populations of M. fissipes. Abbreviation of sample localities refers to table 1. WL. EM. DK. WS. CL. NP. KT. WL. -. 0.167. EM. 0.00244. DK. CB. MT. MJ. 0.686. 0.514. 0.654. 0.639. 0.409. 0.608. 0.598. 0.758. 0.758. -. 0.870. 0.601. 0.811. 0.784. 0.442. 0.724. 0.714. 0.909. 0.909. 0.00507. 0.00342. -. 0.122. 0.000. 0.000. 0.424. 0.808. 0.800. 0.999. 0.999. WS. 0.00563. 0.00398. 0.00130. -. 0.103. 0.095. 0.232. 0.488. 0.466. 0.733. 0.733. CL. 0.00532. 0.00367. 0.00025. 0.00155. -. 0.000. 0.400. 0.759. 0.750. 0.947. 0.947. NP. 0.00544. 0.00380. 0.00037. 0.00168. 0.00062. -. 0.389. 0.737. 0.727. 0.923. 0.923. KT. 0.00682. 0.00517. 0.00422. 0.00466. 0.00447. 0.00460. -. 0.312. 0.289. 0.533. 0.533. SL. 0.00597. 0.00432. 0.00387. 0.00369. 0.00412. 0.00425. 0.00164. -. 0.091. 0.688. 0.688. CB. 0.00582. 0.00417. 0.00372. 0.00354. 0.00397. 0.00410. 0.00238. 0.00463. -. 0.667. 0.667. MT. 0.00657. 0.00492. 0.00447. 0.00428. 0.00472. 0.00485. 0.00238. 0.00448. 0.00223. -. MJ. 0.00657. 0.00492. 0.00447. 0.00428. 0.00472. 0.00485. 0.00164. 0.00523. 0.00223. 0.00000. 37. SL. 0.000 -.

(38) Figure 1. Sample localities of Microhyla fissipes (gray) and M. heymonsi (stripe), including 7 allopatric and 6 sympatric localities. Pie graph represents acoustic records of the two microhylids from each locality.. 38.

(39) Figure 2. Temporal and spectral properties used in acoustic analysis. A-d show the waveforms of advertisement calls in different parameters. (a) 15 consecutive calls from one individual, where the number of calls within a period is defined as call rate; (b) each call is composed by a series of pulses, where the number of pulses in a call is defined as pulse number; (c) amplification of a pulse; (d) the power spectrum of a single call. 39.

(40) M. fissipes M. heymonsi. Figure 3. Variation in advertisement calls between Microhyla fissipes (blue) and M. heymonsi (red) represented by principal component plots. PC1 explains 42.3% of the total variance in acoustic signals, while PC2 explains 23.5%.. 40.

(41) 8 Microhyla fissipes 6. Microhyla heymonsi. Residual PC1. 4. 2. 0. -2. -4. -6 allopatry. sympatry. sympatry. allopatry. Figure 4. Acoustic differences of these two microhylids between allopatric and sympatric populations. The presence or absence of heterospecies doesn’t affect the acoustic signals. The lines of each box represent first, second and third quantile. The extended whiskers represent the lower adjacent and upper adjacent values, respectively.. 41.

(42) TP5 TP10. TP3 TP2. TP1 TP4. TP8 XC11. TP6 TP7. XC10 XC2. North-West. XC7 XC9. XC8 TP9. XC1 XC4. XC12 XC6. KMf1 KMf2. WSf58 DKF1. DKf5 DKf3. DKf4 DKf6. JLf2 JLf57. WSf37 WSf57 WSf44. South-West. WSf38 DKf2 PKf23 PKf32 KMf4 KMf3 JLf53 PKf31 JLf3 JLf4 JLf5 SDf5 PKf25 WSf36 SKf2 SDf3 SDf4 SKf4. South. SKf3 SKf1 SDf1 JHf4 JHf1 MTf1 MTf5 MJf5 MTf4 MJf2 MJf1 MJf4 MJf3 MTf3 MTf2 JHf6. East. WSf39 WSf55 SLf4 SKf5 SLf1 SLf3. JHf5 SLf5. JHf2 JHf3. SDf2 SDf6. SLf2. M. okinavensis IM1. IM2. Figure 5. The phylogenic tree for 24 haplotypes of mitochondrial COI among 82 individuals from 13 localities in Taiwan. The yellow, green, orange and purple shades represent the northern, the western, Kenting peninsular, and the eastern groups.. 42.

(43) South. North-West. South-West East Figure 6. The minimum spanning network for 24 haplotypes of mitochondrial COI among 82 individuals from 13 localities in Taiwan. The yellow, green, orange and purple shades represent the northern, the western, Kenting peninsular, and the eastern groups. The size of the circle represents the frequency of haplotype.. 43.

(44) 6. 4. 2. 0. Residual PC1. -2. -4 North. West. East. 6. 4. 2. 0. -2. -4 WL. EM. DK. WS. CL. NP. KT. SL. CB. MT. MJ. Localities Figure 7. Geographic variation in advertisement calls of Microhyla fissipes in Taiwan. The boxplots show the acoustic differences (a) between groups and (b) among populations. The environmental independent principal component scores which summarize the co-variation in origin calls are represented by the boxplots.. 44.

(45) Figure 8. The correlation between acoustic difference with geographic distance and genetic distance. Genetic distance is estimated from COI sequence by K2 model. Geographic distance is calculated from GPS by linear distance in kilometers. (a) The relationship between difference in temporal properties and geographic distance is significantly positive (p=0.017). (b) The correlation with genetic distance is significantly positive (P=0.030). The mantel test was calculated under the replication of 1000 times.. 45.

(46) Figure 9. The ecological factors are all insignificantly correlated to temporal properties. The relationship between difference in temporal properties with (a) annual temperature, (b) relative humidity and (c) annual precipitation.. 46.

(47) Appendix 2.5. 0.25. *. Microhyla fissipes. 80 Microhyla fissipes. 0.20. 2.0. Microhyla heymonsi. Microhyla fissipes 60. Microhyla heymonsi. 0.10 0.05 0.00 -0.05. 1.0. 0.5. 0.0. -0.5. -0.10 -0.15 allopatry. sympatry. sympatry. allopatry. sympatry. sympatry. 0. -20. allopatry. sympatry. sympatry. 0.00. -0.05. Microhyla fissipes. Microhyla heymonsi. 0.05. 0.00. -0.05. -0.10 allopatry. Microhyla heymonsi. 4. 2. 0. -2. -0.10 sympatry. allopatry. 6. Residual Pulse number (N). Residual Fall time (s). 0.10. 0.05. sympatry. 20. Microhyla fissipes. Microhyla heymonsi. allopatry. 40. -60. allopatry. 0.15 Microhyla fissipes. 0.10. Microhyla heymonsi. -40. -1.0. allopatry. 0.15. Residual Rise time (s). Residual Call rate (N/m). 1.5. Residual Interval (s). Residual Duration (s). 0.15. -4 allopatry. sympatry. 47. sympatry. allopatry. allopatry. sympatry. sympatry. allopatry.

(48) 3500. 1000. Appendix 1. Acoustic interaction between Microhyla fissipes and M. heymonsi of each character. Only the call duration of M. heymonsi significantly shifted in sympatric area. The rest of these characters remain constant, indicating that. 500. 3000. 0. -500. -1000 Microhyla fissipes. 1st quartile frequency (Hz). Residual Dominant frequency (Hz). Microhyla fissipes Microhyla heymonsi. 2500. 2000. reproductive character displacement did not occur.. 1500. -1500 Microhyla heymonsi 1000. -2000 allopatry. sympatry. sympatry. allopatry. allopatry. sympatry. sympatry. allopatry. sympatry. allopatry. 1200. 1000. 500. 0. -500. Microhyla fissipes. -1000. Microhyla heymonsi -1500. Residual IQR bandwidth frequency (Hz). Residual 3rd quartile frequency (Hz). Microhyla fissipes 1000 Microhyla heymonsi 800 600 400 200 0 -200 -400 allopatry. sympatry. sympatry. allopatry. allopatry. 48. sympatry.

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