Global contemporary effective population sizes across taxonomic groups
Data files
May 03, 2024 version files 6.53 MB
Abstract
Effective population size (Ne) is a particularly useful metric for conservation as it affects genetic drift, inbreeding and adaptive potential within populations. Current guidelines recommend a minimum Ne of 50 and 500 to avoid short-term inbreeding and to preserve long-term adaptive potential, respectively. However, the extent to which wild populations reach these thresholds globally has not been investigated, nor has the relationship between Ne and human activities. Through a quantitative review, we generated a dataset with 4610 georeferenced Ne estimates from 3829 unique populations, extracted from 723 articles. These data show that certain taxonomic groups are less likely to meet 50/500 thresholds and are disproportionately impacted by human activities; plant, mammal, and amphibian populations had a <54% probability of reaching = 50 and a <9% probability of reaching = 500. Populations listed as being of conservation concern according to the IUCN Red List had a smaller median than unlisted populations, and this was consistent across all taxonomic groups. was reduced in areas with a greater Global Human Footprint, especially for amphibians, birds, and mammals, however relationships varied between taxa. We also highlight several considerations for future works, including the role that gene flow and subpopulation structure plays in the estimation of in wild populations, and the need for finer-scale taxonomic analyses. Our findings provide guidance for more specific thresholds based on Ne and help prioritize assessment of populations from taxa most at risk of failing to meet conservation thresholds.
README: Global contemporary effective population sizes across taxonomic groups
https://doi.org/10.5061/dryad.p2ngf1vzm
Through a quantitative review, we generated a dataset with 5498 georeferenced Ne and Nb estimates from 3829 unique populations, extracted from 723 articles.
Description of the data and file structure
There are two data files (.csv) associated with this dataset. The first file, 'MEC-23-0962_FullData' includes the full dataset of 5498 estimates and associated data. The second file, 'MEC-23-0962_NonReplicated' includes a subset of the data, with spatial and temporal replication removed. In both files, each row signifies a unique estimate of Ne or Nb. Details of the columns and what they contain are in the table below:
Column | Explanation |
---|---|
PaperID | A unique identifier given to each paper during the screening process. Numbers are not sequential, as papers were excluded and removed from the database during screening. |
Title | The title of the paper, extracted from Web of Science |
Authors | The authors of the paper, extracted from Web of Science |
Year Published | The year the paper was published, extracted from Web of Science |
DOI | The DOI identifier for the paper, extracted from Web of Science |
Journal | The journal the paper was published in, extracted from Web of Science |
Common Name | Common name of species, used by authors in article, all lower case. Some cells are blank, as authors did not always report a common name. |
Genus | genus (capitalized) |
Species | species (uncapitalized) |
Genus/Species | The full scientific name of the species |
IUCN_detailed | IUCN status of a species (Not evaluated, data deficient, least concern, near threatened, vulnerable, endangered, critically endangered). Only included in the full data (not in the nonreplicated data) |
IUCN | Broader groupings of IUCN status: NA (not evaluated or data deficient), nonthreatened (least concern or near threatened), threatened (vulnerable, endangered, critically endangered). Only included in the full data (not in the nonreplicated data) |
Class | freshwater fish, marine fish, diadromous fish, reptile, amphibian, mammal, bird, invertebrate, plant. If something is not listed here, or you are unsure, you can enter a comment in the column next to this. For fish that can be either resident or diadromous, use best judgement according to the authors’ descriptions of the population |
was the population reintroduced or translocated? | Did the authors mention in the paper that the population was reintroduced or translocated from a wild source? (YES/NO) |
Is the pop non-native? | Did the authors mention that this is a non-native or invasive species |
When was the pop reintroduced/translocated? | the year when pop was reintroduced or translocated |
is the population commercially harvested? | Did the authors mention that this population is commercially harvested? |
notes | notes on the reintroduction/translocation/non-native/harvesting of the population. Some cells are blank if notes were not required. |
Type of sequencing | RAD-seq, GBS, capillary electrophoresis, Sanger. Can enter a method not listed here by choosing "other" and then entering in comment column. |
Comment for type of sequencing | Response for “other” on type of sequencing. Some cells are blank. |
marker | Microsatellite, SNP, or Other |
Marker type comment | If “other” for marker above. Some cells are blank. |
Number of loci | number of loci (for microsatellite markers) used in estimate. |
Number of SNP | Number of SNP used in the estimate |
LociNumber | Combined the two columns of number of loci and number of SNP into a single column |
GW correction | genome-wide bias correction for LD method; YES/NO. Based on study by Waples, Larson, and Waples (2016, Heredity) |
Method (general) | LD (linkage disequilibium), SF (sibship frequency), HE (heterozygote excess), MC (molecular coancestry), Bayesian methods. If article used a different single-sample genetic estimator not listed, put "Other" and enter it into the notes column |
Method (specific) | LDNe, NeEstimator (v1 or V2), COLONY, ONeSAMP. If article used a different software not listed, put "Other" and enter it into the notes column |
Notes about method | If “other” was chosen, it is specified here. Some cells are blank if notes were not required. |
Allele freq cutoff | for LD method; common values are 0.01, 0.05, 0.1. If the article reports multiple allele cutoff values, follow this rule: For sample sizes >25 use 0.02, and <25 use 0.05. Please report whether the study included multiple allele cutoffs. |
Comment on allele cutoffs | Any comments relevant to the allele cutoff (e.g. if they reported multiple cutoffs, etc.). Some cells are blank if notes were not required. |
Sample size | the number of individuals sampled from the population |
Temporal replication? | Does this population have temporal replication YES/NO (i.e., were multiple estimates reported for the same population through time?) |
Spatial replication | Does the population have spatial replication YES/NO (i.e., were there multiple estimates reported for the same population? E.g., Ne was reported by sampling location, but multiple sampling locations make up a single population based on Fst or STRUCTURE) |
Population | name given to population; for species in bodies of water, could use the name of the lake/river, or another name used by authors in article |
Population ID | numerical identification for each population (since there can be multiple estimates for a single population). Alpha-numeric system using the article number. i.e. if article # 100 has two populations, they will be 100A and 100B. If an article only has one estimate, still include A at the end. |
Method of defining population | based off of the authors in the article and how they defined the population. E.g. using Fst values, STRUCTURE (determining # of groups), BAYESASS (measuring migration rates), IBA (individual-based-assignment; using genetic data from populations to assign individuals), etc. If there is any additional information, include it in the comment column. E.g. what their threshold Fst value was, or level of migration, etc. |
Region where population is located | can be a city/province/ etc. or multiple of these things. |
Country | The country where the population is located |
Continent/Ocean | Continent or ocean (for marine species) where the population is located |
Latitude* | Latitude of the population |
Longitude* | Longitude of the population |
How coordinate was generated* | Comment on how the coordinate was obtained (i.e. was it reported by authors, estimated from a map, converted from UTM, the midpoint from several sampling locations was estimated, etc. |
He | average He (expected heterozygosity) across loci for that population. Some cells are blank if He was not reported in the paper. |
Ho | Average Ho (observed heterozygosity) across loci for that population. Some cells are blank if Ho was not reported in the paper. |
Ar | allelic richness; average # of alleles per locus, weighted by sample size. If the authors refer to "Ar" with no mention of method, assume they are correct. If they refer to Ar as the non-weighted version, then it was categorized as MNA instead. Some cells are blank if Ar was not reported. |
MNA | mean number of alleles per locus. NOT weighted. If the authors refer to MNA but mention weighting, categorize as Ar instead. Some cells are blank if MNA was not reported. |
Inbreeding coefficient (Fis) | usually calculated from heterozygosity measures. Some cells are blank if Fis was not reported/ |
Nucleotide diversity | The nucleotide diversity reported for estimates using SNPs. Some cells are blank if nucleotide diversity was not reported. |
Ne | point estimate of Ne. Cells are blank for populations were Nb was reported instead. |
Nb | point estimate of Nb. Cells are blank for populations where Ne was reported instead. |
Year | year the samples were taken from the population. Some cells are blank if year was not reported. |
LCI | lower confidence interval for estimate |
UCI | upper confidence interval for estimate (can be "infinity" as well). |
CI method | method used to calculate CIs. E.g. jackknife vs parametric methods in LDNe program. If the method is not provided, enter as text in comments column. some cells are blank if method was not reported. |
CI comment | Comment on the CIs. Some cells are blank if notes were not required. |
was the original estimate negative or infinite? | For populations with no point estimate (I.e., the estimate was negative or infinite), and we used the LCI as a proxy of the point estimate. This column indicates whether the original estimate was negative or infinite. Cells are blank for estimates that were not negative or infinite. |
Fifty | A binary response indicating whether the population meets the threshold of fifty Ne. 0 = below fifty, 1 = equal or greater than fifty. |
fivehundred | A binary response indicating whether the population meets the threshold of five hundred Ne. 0 = below five hundred, 1 = equal or greater than five hundred. |
Did they sample individuals across different cohorts? | yes/no/unsure. Did the authors sample from multiple cohorts within a population? |
Did they report Ne for sampling sites? | If the authors defined a population as a group of sampling sites, but only reported Ne for the sites (rather than for the population as a whole), this column was marked "YES", and each sampling site was entered on a unique row, with the SAME POPULATION ID. If Ne is reported for both the sampling sites, and overall population, the population-level Ne was used, and this column was marked as “NO”. |
Did they pool samples from multiple years? | yes/no/unsure. Did the authors pool samples from the same population over multiple years? |
Notes | any other notes on the validity of the Ne estimate (e.g. all samples came from a single breeding site and may not be representative of the population). Some cells are blank if notes were not required. |
Nc estimate | point estimate of Nc. Some cells are blank if Nc was not reported. |
Nc LCI | Lower confidence interval of Nc (if reported). Some cells are blank if Nc was not reported. |
Nc UCI | Upper confidence interval of Nc (if reported). Some cells are blank if Nc was not reported. |
Nc method | mark-recapture, complete count, incomplete count (e.g. quadrat study with extrapolation), or "other". Some cells are blank if Nc was not reported. |
Nc method comment | Any other relevant information about the method of estimating Nc. Some cells are blank if Nc was not reported. |
Year Nc taken | The year that the Nc estimate was taken. Some cells are blank if Nc was not reported. |
comment | Any relevant information about the year that Nc was taken. Some cells are blank if Nc was not reported. |
ratio | The ratio of Ne/Nc or Nb/Nc. Some cells are blank if Nc was not reported. |
Ratio type | “Ne” or “Nb”, i.e. is the ratio between Ne and Nc, or between Nb and Nc. Some cells are blank if Nc was not reported. |
Notes | Overall notes on the paper/methods/estimates, etc. Some cells are blank where notes were not required. |
HFI | The human footprint index, extracted using the lat/long coordinates in QGIS. Only included in the full data (not in the nonreplicated data). Some cells are blank where no HFI value was associated with the GPS location. |
*Information on Latitude and Longitude are not included in the publicly accessible document, to protect locations of at-risk populations. Please contact the authors to receive the coordinate information for the dataset.
Sharing/Access information
Data were derived from peer reviewed articles, the details of which can be found in the data file under the columns titled 'Title', 'Authors', 'Year Published', 'DOI', and 'Journal'.
Code/Software
The R script associated with this dataset, titled 'MEC-23-0962_Code.R' was run in R Statistical Software (Version 4.2.2) and RStudio (Version 2022.12.0+353). The packages included in the script are: glmmTMB (v. 1.1.5), ggplot2 (v. 3.4.1), dplyr (v. 1.1.0), emmeans (v. 1.8.4-1), lme4 (v. 1.1-31), and nlme (v. 3.1-160)
Methods
Literature search, screening, and data extraction
A primary literature search was conducted using ISI Web of Science Core Collection and any articles that referenced two popular single-sample Ne estimation software packages: LDNe (Waples & Do, 2008), and NeEstimator v2 (Do et al., 2014). The initial search included 4513 articles published up to the search date of May 26, 2020. Articles were screened for relevance in two steps, first based on title and abstract, and then based on the full text. For each step, a consistency check was performed using 100 articles to ensure they were screened consistently between reviewers (n = 6). We required a kappa score (Collaboration for Environmental Evidence, 2020) of ³ 0.6 in order to proceed with screening of the remaining articles. Articles were screened based on three criteria: (1) Is an estimate of Ne or Nb reported; (2) for a wild animal or plant population; (3) using a single-sample genetic estimation method. Further details on the literature search and article screening are found in the Supplementary Material (Fig. S1).
We extracted data from all studies retained after both screening steps (title and abstract; full text). Each line of data entered in the database represents a single estimate from a population. Some populations had multiple estimates over several years, or from different estimation methods (see Table S1), and each of these was entered on a unique row in the database. Data on N̂e, N̂b, or N̂c were extracted from tables and figures using WebPlotDigitizer software version 4.3 (Rohatgi, 2020). A full list of data extracted is found in Table S2.
Data Filtering
After the initial data collation, correction, and organization, there was a total of 8971 Ne estimates (Fig. S1). We used regression analyses to compare Ne estimates on the same populations, using different estimation methods (LD, Sibship, and Bayesian), and found that the R2 values were very low (R2 values of <0.1; Fig. S2 and Fig. S3). Given this inconsistency, and the fact that LD is the most frequently used method in the literature (74% of our database), we proceeded with only using the LD estimates for our analyses. We further filtered the data to remove estimates where no sample size was reported or no bias correction (Waples, 2006) was applied (see Fig. S6 for more details).
Ne is sometimes estimated to be infinity or negative within a population, which may reflect that a population is very large (i.e., where the drift signal-to-noise ratio is very low), and/or that there is low precision with the data due to small sample size or limited genetic marker resolution (Gilbert & Whitlock, 2015; Waples & Do, 2008; Waples & Do, 2010) We retained infinite and negative estimates only if they reported a positive lower confidence interval (LCI), and we used the LCI in place of a point estimate of Ne or Nb. We chose to use the LCI as a conservative proxy for in cases where a point estimate could not be generated, given its relevance for conservation (Fraser et al., 2007; Hare et al., 2011; Waples & Do 2008; Waples 2023). We also compared results using the LCI to a dataset where infinite or negative values were all assumed to reflect very large populations and replaced the estimate with an arbitrary large value of 9,999 (for reference in the LCI dataset only 51 estimates, or 0.9%, had an or > 9999). Using this 9999 dataset, we found that the main conclusions from the analyses remained the same as when using the LCI dataset, with the exception of the HFI analysis (see discussion in supplementary material; Table S3, Table S4 Fig. S4, S5). We also note that point estimates with an upper confidence interval of infinity (n = 1358) were larger on average (mean = 1380.82, compared to 689.44 and 571.64, for estimates with no CIs or with an upper boundary, respectively). Nevertheless, we chose to retain point estimates with an upper confidence interval of infinity because accounting for them in the analyses did not alter the main conclusions of our study and would have significantly decreased our sample size (Fig. S7, Table S5).
We also retained estimates from populations that were reintroduced or translocated from a wild source (n = 309), whereas those from captive sources were excluded during article screening (see above). In exploratory analyses, the removal of these data did not influence our results, and many of these populations are relevant to real-world conservation efforts, as reintroductions and translocations are used to re-establish or support small, at-risk populations.
We removed estimates based on duplication of markers (keeping estimates generated from SNPs when studies used both SNPs and microsatellites), and duplication of software (keeping estimates from NeEstimator v2 when studies used it alongside LDNe). Spatial and temporal replication were addressed with two separate datasets (see Table S6 for more information): the full dataset included spatially and temporally replicated samples, while these two types of replication were removed from the non-replicated dataset. Finally, for all populations included in our final datasets, we manually extracted their protection status according to the IUCN Red List of Threatened Species. Taxa were categorized as “Threatened” (Vulnerable, Endangered, Critically Endangered), “Nonthreatened” (Least Concern, Near Threatened), or “N/A” (Data Deficient, Not Evaluated).
Mapping and Human Footprint Index (HFI)
All populations were mapped in QGIS using the coordinates extracted from articles. The maps were created using a World Behrmann equal area projection. For the summary maps, estimates were grouped into grid cells with an area of 250,000 km2 (roughly 500 km x 500 km, but the dimensions of each cell vary due to distortions from the projection). Within each cell, we generated the count and median of Ne. We used the Global Human Footprint dataset (WCS & CIESIN, 2005) to generate a value of human influence (HFI) for each population at its geographic coordinates. The footprint ranges from zero (no human influence) to 100 (maximum human influence). Values were available in 1 km x 1 km grid cell size and were projected over the point estimates to assign a value of human footprint to each population. The human footprint values were extracted from the map into a spreadsheet to be used for statistical analyses. Not all geographic coordinates had a human footprint value associated with them (i.e., in the oceans and other large bodies of water), therefore marine fishes were not included in our HFI analysis. Overall, 3610 Ne estimates in our final dataset had an associated footprint value.