| Literature DB >> 26679703 |
Eulalia Moreno1, Javier Pérez-González2,3, Juan Carranza2, Jordi Moya-Laraño1.
Abstract
Captive breeding of endangered species often aims at preserving genetic diversity and to avoid the harmful effects of inbreeding. However, deleterious alleles causing inbreeding depression can be purged when inbreeding persists over several generations. Despite its great importance both for evolutionary biology and for captive breeding programmes, few studies have addressed whether and to which extent purging may occur. Here we undertake a longitudinal study with the largest captive population of Cuvier's gazelle managed under a European Endangered Species Programme since 1975. Previous results in this population have shown that highly inbred mothers tend to produce more daughters, and this fact was used in 2006 to reach a more appropriate sex-ratio in this polygynous species by changing the pairing strategy (i.e., pairing some inbred females instead of keeping them as surplus individuals in the population). Here, by using studbook data we explore whether purging has occurred in the population by investigating whether after the change in pairing strategy a) inbreeding and homozygosity increased at the population level, b) fitness (survival) increased, and c) the relationship between inbreeding and juvenile survival, was positive. Consistent with the existence of purging, we found an increase in inbreeding coefficients, homozygosity and juvenile survival. In addition, we showed that in the course of the breeding programme the relationship between inbreeding and juvenile survival was not uniform but rather changed over time: it was negative in the early years, flat in the middle years and positive after the change in pairing strategy. We highlight that by allowing inbred individuals to mate in captive stocks we may favour sex-ratio bias towards females, a desirable managing strategy to reduce the surplus of males that force most zoos to use ethical culling and euthanizing management tools. We discuss these possibilities but also acknowledge that many other effects should be considered before implementing inbreeding and purging as elements in management decisions.Entities:
Mesh:
Year: 2015 PMID: 26679703 PMCID: PMC4682998 DOI: 10.1371/journal.pone.0145111
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Fig 1Differences in inbreeding.
Inbreeding before and after the pairing strategy change occurred in 2006. Figure shows means and standard errors.
Fig 2Differences in juvenile survival.
Juvenile survival before and after the pairing strategy change. Juvenile survival is a dichotomous variable in which 0 indicates dead individuals and 1 indicates surviving individuals. Figure shows mean and standard error.
GLMM model using the library “lme4”.
| estimate | se | z | P | |
|---|---|---|---|---|
| Intercept | 6.381 | 2.247 | 2.840 | 0.0045 |
| Birth Year | -0.451 | 0.219 | -2.059 | 0.0395 |
| Inbreeding 1 | -10.91 | 4.839 | -2.254 | 0.0242 |
| Inbreeding 2 | -1.299 | 2.730 | -0.476 | 0.6341 |
| Inbreeding 3 | -7.735 | 3.173 | -2.438 | 0.0148 |
| Birth Year * Inbreeding 1 | 1.035 | 0.446 | 2.323 | 0.0202 |
| Birth Year * Inbreeding 2 | 0.042 | 0.179 | 0.235 | 0.8145 |
| Birth Year * Inbreeding 3 | 0.695 | 0.282 | 2.468 | 0.0136 |
Fixed effects of the GLMM model after using cubic spline with linear, quadratic and cubic. See also “Fig 3”.
Fig 3Evolution of juvenile survival through time.
Relationship between inbreeding and juvenile survival through time. Juvenile survival is a dichotomous variable in which 0 indicates dead individuals and 1 indicates surviving individuals. Figure shows predicted values and 95% confidence bands. Time progresses from left to right, so the left graph shows the relationship between inbreeding and juvenile survival centred in year 1981, while the right graph shows this relationship centred in year 2006 when a major change in pairing management occurred. Graphs were produced with library “effects” [68], which uses the estimates of the effects from GLMMs to predict the values across the entire expand of the explanatory variables. Confidence bands are calculated from standard errors estimated at each of three levels of inbreeding (0.0625, 0.2451 and 0.4277) within each of the time periods.