Maintenance of genetic diversity despite population fluctuations in the lesser prairie-chicken (Tympanuchus pallidicinctus)
Data files
Jan 28, 2025 version files 125.27 KB
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Lawrence_et.al_2024_Complete_Genotypes_12July2024.txt
25.67 KB
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Lawrence_et.al_2024_LekTrends.csv
9.87 KB
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Lawrence_et.al_2024_Period3_GenelandInput.txt
8.37 KB
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Lawrence_et.al_2024_Period3_Genotypes_Clusters.txt
9.68 KB
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Lawrence_et.al_2024_Period3_Genotypes_Leks.txt
9.48 KB
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Lawrence_et.al_GenePop_InputFile_AllPeriods_12July2024.txt
18.43 KB
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Lawrence_et.al_GenePop_InputFile_Period1_12July2024.txt
4.64 KB
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Lawrence_et.al_GenePop_InputFile_Period2_12July2024.txt
6.08 KB
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Lawrence_et.al_STRUCTURE_InputFile_CompleteDataset_12July2024.txt
20.69 KB
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README.md
12.38 KB
Abstract
Assessments of genetic diversity, structure, history, and effective population size (Ne) are critical for the conservation of imperiled populations. The lesser prairie-chicken (Tympanuchus pallidicinctus) has experienced declines due to habitat loss, degradation, and fragmentation in addition to substantial population fluctuations with unknown effects on genetic diversity. Our objectives were to: (i) compare genetic diversity across three temporally discrete sampling periods (2002, 2007 – 2010, and 2013 – 2014) that are characterized by low or high population abundance; (ii) examine genetic diversity at lek and lek cluster spatial scales; (ii) identify potential bottlenecks and characterize genetic structure and relatedness; and (iii) estimate the regional Ne. We analyzed 194 samples across the shinnery oak prairie region of eastern New Mexico and western Texas using 13 microsatellite loci. Mean heterozygosity, allelic richness, and inbreeding coefficient were not significantly different between discrete sampling periods, suggesting that this population has maintained its genetic diversity across the sampled population fluctuations. We did not detect genetic structure using multiple Bayesian clustering approaches. Furthermore, there was no support for recent genetic bottlenecks, and we estimated that the Ne ranged from 229.5 (Pcrit = 0.05, 95% CIs = 121.2 – 1023.1) to 349.1 (Pcrit = 0.02, 95% CIs = 176.4 – 2895.2) during our final sampling period (2013 – 2014). Although we provide evidence for gene flow within this region, continued habitat loss and fragmentation that leads to population declines and isolation could increase the risk of genetic consequences. Continued monitoring of genetic diversity and increasing available habitat that supports robust populations of lesser prairie-chickens may improve the likelihood of the species’ persistence.
README: Maintenance of genetic diversity despite population fluctuations in the lesser prairie-chicken (Tympanuchus pallidicinctus)
https://doi.org/10.5061/dryad.8931zcrxt
The following microsatellite and lesser prairie-chicken abundance datasets were used to analyze the relationship between lesser prairie-chicken population fluctuations and genetic diversity and structure.
Description of the data and file structure
Data file descriptions:
Lawrence_et.al_2024_Complete_Genotypes_12July2024.txt: file containing genotype datasets for all three sampling periods in 2002, 2007-2010, and 2013-2014.
Variable | Unit | Description |
---|---|---|
Sample ID | categorical | Unique identifies for each lesser prairie-chicken DNA sample. |
CollectionDate | date | Date of lesser prairie-chicken DNA sample collection |
Year | date | Year that sample was collected |
County | categorical | County where sample was collected. Chaves, Lea, and Roosevelt counties in New Mexico. Bailey and Cochran (abbreviated as BC), and Yoakum counties in Texas. |
Population | categorical | Population as defined by sampling period: Population 1 includes samples from 2002. Population 2 includes samples collected from 2007 - 2010. Population 3 includes samples collected from 2013 - 2014. |
Microsatellites (columns 6:18) | numeric | Allele values for lesser prairie-chicken microsatellites. Loci with missing values are coded as "0/0" |
Lawrence_et.al_2024_Period3_Genotypes_Clusters: file containing genotype dataset for sampling period 3.
Variable | Unit | Description |
---|---|---|
ID | categorical | Unique identifies for each lesser prairie-chicken DNA sample. |
LEK | categorical | Unique identifier for sampled lek. |
grouppop | categorical | Samples partitioned by discrete clusters/groups. See supplemental Figure S1 for reference groups. |
Microsatellites (columns 5:17) | numeric | Allele values for lesser prairie-chicken microsatellites. Loci with missing values are coded as "0/0" |
Lawrence_et.al_2024_Period3_Genotypes_Leks: file containing genotype dataset for sampling period 3. Samples are partitioned by the individual leks from which they were collected (see column 2, "population").
Variable | Unit | Description |
---|---|---|
ID | categorical | Unique identifies for each lesser prairie-chicken DNA sample. |
population | categorical | Unique identifier for sampled lek. |
Microsatellites (columns 4:16) | numeric | Allele values for lesser prairie-chicken microsatellites. Loci with missing values are coded as "0/0" |
Lawrence_et.al_2024_LekTrends.csv: file containing lek count data for lesser prairie-chickens in eastern New Mexico from 2000 to 2014. Data are derived from direct observations of individual birds attending leks during the spring mating season, or interpolated from nearby leks when data for a given lek were unavailable.
Variable | Unit | Description |
---|---|---|
Year | date | Reference year for lesser prairie-chicken lek count data. |
Count | numeric | Maximum number of lesser prairie-chickens observed at a particular lek during a given year. |
LekGroup | categorical | Identity of lek groups. See supplemental Figure S1 for reference groups. |
Leks | categorical | Identify of source lek for count data. |
Interpolated? | categorical | If lek counts were not available for a lek within a given year, values were interpolated with the mean counts of nearby leks. This column indicates which values were direct observations and which were interpolated. |
Lawrence_et.al_2024_GenePop_InputFile_Period1_12July2024: GENEPOP input file for sampling period 1 (2002) only. Data include unique sample identifiers (first column), and microsatellite data (subsequent columns). A descriptive header detailing the conversion of the dataset from R, microsatellite loci names, and "Pop" (required for Genepop formatting) are listed in rows 1 through 3, respectively. Loci with missing values are entered as "000000"
Lawrence_et.al_2024_GenePop_InputFile_Period2_12July2024: GENEPOP input file for sampling period 2 (2007-2010) only. Data include unique sample identifiers (first column), and microsatellite data (subsequent columns). A descriptive header detailing the conversion of the dataset from R, microsatellite loci names, and "Pop" (required for Genepop formatting) are listed in rows 1 through 3, respectively. Loci with missing values are entered as "000000"
Lawrence_et.al_2024_GenePopInputFileAllPeriods_12July2024: GENEPOP input file for all sampling periods. Data include unique sample identifiers (first column), and microsatellite data (subsequent columns). A descriptive header detailing the conversion of the dataset from R, microsatellite loci names, and "Pop" (required for Genepop formatting) are listed in rows 1 through 3, respectively. Loci with missing values are entered as "000000"
Lawrence_et.al_2024_Period3_GenelandInput.txt: input file to run Geneland structure analyses for samples collected in 2013 and 2014. The first column indicates the sample identification, and following columns provide microsatellite data. Loci with missing values are left blank.
Lawrence_et.al_STRUCTURE_InputFile_CompleteDataset_12July2024: input file to run analyses in program Structure. This file follows the format necessary to run analyses in program Structure. Microsatellite loci names are listed in the first row. Unique sample identifiers are listed in the first column, with each sample split into two paired rows. Loci with missing values are entered as "-1"
Lawrence_et.al_2024_ML_Relatedness.xlsx: This dataset contains results from the ML-Relate program (Kalinowski, Wagner, and Taper 2006), which estimates the likelihood of genetic relationships between individuals. The results file, containing tabs for each sampling period, contains the following:
Variable | Description |
---|---|
Ind1, Ind2 | IDs of the two individuals being compared. IDs for sampling period 3 refer to the lek at which samples were collected. Unique IDs for sampling periods 1 and 2 are omitted due to the sensitive nature of their locations. |
R | The hypothesized relationship being tested (e.g., FS = Full Siblings). |
LnL(R) | The natural logarithm of the likelihood value for the hypothesized relationship. More negative values indicate lower support for the hypothesis. |
U, HS, FS, PO: | Likelihood ratios comparing the tested relationship (R) to alternative relationships: U (unrelated), HS (half-sibling), FS (full-sibling), PO (parent-offspring). A value of 9999 indicates the relationship was not tested (e.g., PO in this dataset). "-" indicates no ratio is calculated for the relationship being tested (e.g., FS is not compared against itself). |
Sharing/Access information
Data was derived from the following sources:
- Lesser prairie-chicken genetic data were sequenced at the USGS Fort Collins Science Center, Fort Collins, CO, USA using the methods of Oyler-McCance et al. (2016).
- Lek count data sources include datasets from the U.S. Bureau of Land Management, Natural Heritage New Mexico, and the present study.
Code/Software
Genetic diversity metrics were measured using select packages in program R and with GENEPOP (Rousset 2008). Bayesian clustering analyses were conducted using Structure v 2.3.4 (Pritchard et al. 2000) and Geneland (Guillot and Santos 2000). The R script (file name = LEPC_genetics_Lawrence_EcoEvo_Final_Dryad.R) and supplementary tables are figures are hosted by Zenodo. Source files to analyze data are provided in these supplementary materials. Parameters for analyses outside of R are provided in the manuscript and follow the user manual for the software or user interface.