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opencc-zeroDec 2014View details →

Data from: Geographic variation in the Pine Barrens Treefrog (Hyla andersonii): concordance of genetic, morphometric, and acoustic signal data

Delimiting species is important to every subfield in biology. Templeton's cohesion species concept uses genetic and ecological exchangeability to identify sets of populations that ought to be considered as the same species, and the lack of exchangeability helps determine which populations can be grouped as evolutionarily significant units (ESU) in conservation science. However, previous work assessing genetic and ecological interchangeability among populations has been limited in scope. Here, we provide a method for assessing exchangeability that incorporates multiple, independent lines of multivariate evidence in genetic, behavioural and morphological data. We use this approach to assess exchangeability across three disjunct groups of populations of the Pine Barrens Treefrog (Hyla andersonii) from the eastern United States. This species is considered threatened by each state in which it occurs and conservation management of this taxon requires a clearer understanding of how populations in these three regions may differ from one another. We find a strikingly concordant pattern in which the first axis of variation for each of the three types of data distinguishes populations along a latitudinal gradient and the second axis distinguishes the set of populations occurring in the Carolinas from those occurring in the New Jersey and Florida/Alabama regions. We know of no comparable data set that displays such concordance among different types of data across so large a geographic range. The overlap in trait values (i.e. exchangeability) between neighbouring regions, however, is substantial in all three types of data, which supports continued consideration of this taxon as a single species.

opencc-zeroDec 2015View details →

Data from: Uncovering spatial variation in acoustic environments using sound mapping

Animals select and use habitats based on environmental features relevant to their ecology and behavior. For animals that use acoustic communication, the sound environment itself may be a critical feature, yet acoustic characteristics are not commonly measured when describing habitats and as a result, how habitats vary acoustically over space and time is poorly known. Such considerations are timely, given worldwide increases in anthropogenic noise combined with rapidly accumulating evidence that noise hampers the ability of animals to detect and interpret natural sounds. Here, we used microphone arrays to record the sound environment in three terrestrial habitats (forest, prairie, and urban) under ambient conditions and during experimental noise introductions. We mapped sound pressure levels (SPLs) over spatial scales relevant to diverse taxa to explore spatial variation in acoustic habitats and to evaluate the number of microphones needed within arrays to capture this variation under both ambient and noisy conditions. Even at small spatial scales and over relatively short time spans, SPLs varied considerably, especially in forest and urban habitats, suggesting that quantifying and mapping acoustic features could improve habitat descriptions. Subset maps based on input from 4, 8, 12 and 16 microphones differed slightly (< 2 dBA/pixel) from those based on full arrays of 24 microphones under ambient conditions across habitats. Map differences were more pronounced with noise introductions, particularly in forests; maps made from only 4-microphones differed more (> 4 dBA/pixel) from full maps than the remaining subset maps, but maps with input from eight microphones resulted in smaller differences. Thus, acoustic environments varied over small spatial scales and variation could be mapped with input from 4–8 microphones. Mapping sound in different environments will improve understanding of acoustic environments and allow us to explore the influence of spatial variation in sound on animal ecology and behavior.

FIG. 4 in Daily and seasonal variation in non-acoustic communicative behaviors of male greater short-nosed fruit bats (Cynopterus sphinx)

FIG. 4. Seasonal variation in duration and frequency of A — scent marking, B — wing flapping and C — open wing gesture behaviors. Mean ± SEM of frequency and duration varying between observed months (from January to December 2012). Mean ± SEM of number of attempts and duration was calculated from seven observation sessions for each month

FIG. 2 in Daily and seasonal variation in non-acoustic communicative behaviors of male greater short-nosed fruit bats (Cynopterus sphinx)

FIG. 2. Inter-individual variation in the mean frequency of A — scent marking, B — wing flapping and C — open wing gesture behavior between mating and non-mating seasons. Data shown as the mean of number of attempts (± SEM) made by focal bats between two mating and two non mating seasons. Each data point represents individual focal bat (Animal ID — A to F)

FIG. 3 in Daily and seasonal variation in non-acoustic communicative behaviors of male greater short-nosed fruit bats (Cynopterus sphinx)

FIG. 3. Daily variation in duration and frequency of A — scent marking, B — wing flapping and C — open wing gesture behaviors. Mean ± SEM of frequency and duration between observation sessions (one hour time interval). Mean ± SEM number of attempts and duration of each attempt were calculated for each observation session across 12 months (between January and December 2012) for all focal bats

FIG. 1 in Daily and seasonal variation in non-acoustic communicative behaviors of male greater short-nosed fruit bats (Cynopterus sphinx)

FIG. 1. Non-acoustic communicative displays of male C. sphinx. A — male bat scent marking the interior of palm leaves with its saliva during night time. Circled areas in the picture shows scent marked part of the leaf. B — Tagged male bat co-roosting with females (untagged) in the day roost and displaying open wing gesture during morning hours in the mating season

publicMay 2015View details →

Data from: Geographic variation in the Pine Barrens Treefrog (Hyla andersonii): concordance of genetic, morphometric, and acoustic signal data

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publicJul 2017View details →

Data from: Uncovering spatial variation in acoustic environments using sound mapping

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dryad28/100

Data from: Phenotypic variation and covariation indicate high evolvability of acoustic communication in crickets

Studying the genetic architecture of sexual traits provides insight into the rate and direction at which traits can respond to selection. Traits associated with few loci and limited genetic and phenotypic constraints tend to evolve at high rates typically observed for secondary sexual characters. Here, we examined the genetic architecture of song traits and female song preferences in the field crickets Gryllus rubens and G. texensis. Song and preference data were collected from both species and interspecific F1 and F2 hybrids. We first analysed phenotypic variation to examine interspecific differentiation and trait distributions in parental and hybrid generations. Then, the relative contribution of additive and additive-dominance variation was estimated. Finally, phenotypic variance-covariance (P) matrices were estimated to evaluate the multivariate phenotype available for selection. Song traits and preferences had unimodal trait distributions and hybrid offspring were intermediate with respect to the parents. We uncovered additive and dominance variation in song traits and preferences. For two song traits we found evidence for X-linked inheritance. On one hand, the observed genetic architecture does not suggest rapid divergence, although sex-linkage may have allowed for somewhat higher evolutionary rates. On the other hand, P matrices revealed that multivariate variation in song traits aligned with major dimensions in song preferences, suggesting a strong selection response. We also found strong covariance between the main traits that are sexually selected and traits that are not directly selected by females, providing an explanation for the striking multivariate divergence in male calling songs despite limited divergence in female preferences.

opencc-zeroDec 2014View details →

Figure 4 from: Zhang X, Wen M, Li J, Zhu H, Wang Y, Ren B (2015) Acoustic, genetic and morphological variations within the katydid Gampsocleis sedakovii (Orthoptera, Tettigonioidea). ZooKeys 529: 105-121. https://doi.org/10.3897/zookeys.529.6043

Figure 4 - Power spectral density of the calling songs of Gampsocleis sedakovii from six geographic populations (A–F: CES, BYCG, JDM, WCG, SMJ and ELC).

Figure 3 from: Zhang X, Wen M, Li J, Zhu H, Wang Y, Ren B (2015) Acoustic, genetic and morphological variations within the katydid Gampsocleis sedakovii (Orthoptera, Tettigonioidea). ZooKeys 529: 105-121. https://doi.org/10.3897/zookeys.529.6043

Figure 3 - Presentation of one syllable of calling songs showed in Fig. 2 (A-F: CES, BYCG, JDM, WCG, SMJ and ELC).

Figure 6 from: Zhang X, Wen M, Li J, Zhu H, Wang Y, Ren B (2015) Acoustic, genetic and morphological variations within the katydid Gampsocleis sedakovii (Orthoptera, Tettigonioidea). ZooKeys 529: 105-121. https://doi.org/10.3897/zookeys.529.6043

Figure 6 - Neighbour-Joining (NJ) tree based on COI sequence from 18 individuals of Gampsocleis sedakovii collected from six sampling sites (CES, BYCG, JDM, WCG, SMJ, and ELC).

Figure 2 from: Zhang X, Wen M, Li J, Zhu H, Wang Y, Ren B (2015) Acoustic, genetic and morphological variations within the katydid Gampsocleis sedakovii (Orthoptera, Tettigonioidea). ZooKeys 529: 105-121. https://doi.org/10.3897/zookeys.529.6043

Figure 2 - The oscillograms of calling songs of Gampsocleis sedakovii collected from six locations at different speeds (A-F: CES, BYCG, JDM, WCG, SMJ and ELC).

Figure 1 from: Zhang X, Wen M, Li J, Zhu H, Wang Y, Ren B (2015) Acoustic, genetic and morphological variations within the katydid Gampsocleis sedakovii (Orthoptera, Tettigonioidea). ZooKeys 529: 105-121. https://doi.org/10.3897/zookeys.529.6043

Figure 1 - Locations of the six sampling sites in Inn Mongolia, China. Each point signifies a sampling site. Abbreviation: CES, Chaersen; BYCG, Bayancuogang; JDM, Jiaodaomu; WCG, Wuchagou; SMJ, Samajie; ELC, Elunchun.

publicJul 2015View details →

dryad28/100

Data from: Phenotypic variation and covariation indicate high evolvability of acoustic communication in crickets

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zenodo24/100

Figure 8 from: Zhang X, Wen M, Li J, Zhu H, Wang Y, Ren B (2015) Acoustic, genetic and morphological variations within the katydid Gampsocleis sedakovii (Orthoptera, Tettigonioidea). ZooKeys 529: 105-121. https://doi.org/10.3897/zookeys.529.6043

Figure 8 - Dendrogram generated by cluster analysis based on morphological traits.

zenodo24/100

Figure 7 from: Zhang X, Wen M, Li J, Zhu H, Wang Y, Ren B (2015) Acoustic, genetic and morphological variations within the katydid Gampsocleis sedakovii (Orthoptera, Tettigonioidea). ZooKeys 529: 105-121. https://doi.org/10.3897/zookeys.529.6043

Figure 7 - Dendrogram generated by cluster analysis based on acoustic characteristics.