Data from: The influence of weather conditions during gestation on life histories in a wild Arctic ungulate ...
The internal predictive adaptive response (internal PAR) hypothesis predicts that individuals born in poor conditions should start to reproduce earlier if they are likely to have reduced performance in later life. However, whether this is the case remains unexplored in wild populations. Here, we use...
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Dataset |
| Language: | English |
| Published: |
Dryad
2016
|
| Subjects: | |
| Online Access: | https://dx.doi.org/10.5061/dryad.fp505 https://datadryad.org/stash/dataset/doi:10.5061/dryad.fp505 |
| Summary: | The internal predictive adaptive response (internal PAR) hypothesis predicts that individuals born in poor conditions should start to reproduce earlier if they are likely to have reduced performance in later life. However, whether this is the case remains unexplored in wild populations. Here, we use longitudinal data from a long-term study of Svalbard reindeer to examine age-related changes in adult female life-history responses to environmental conditions experienced in utero as indexed by rain-on-snow (ROSutero). We show that females experiencing high ROSutero had reduced reproductive success only from 7 years of age, independent of early reproduction. These individuals were able to maintain the same annual reproductive success between 2 and 6 years as phenotypically superior conspecifics that experienced low ROSutero. Young females born after high ROSutero engage in reproductive events at lower body mass (about 2.5 kg less) than those born after low ROSutero. The mean fitness of females that experienced ... : Data supporting the paperData1 is a dataframe with 7 variables: 1) id = female identity, 2) RS = annual reproductive success of females aged 7 years and over (0 = failed, 1 = success), 3) year, 4) ROSutero = rain on-snow events experienced in utero (0 = high, 1 = low), 5) alo = age at last observation, 6) ROScurrent = rain-on-snow experienced in current year, 7) age. Data2 is a dataframe with 7 variables: 1) id = female identity, 2) RS = annual reproductive success of females aged 2-6 years (0 = failed, 1 = success), 3) year, 4) ROSutero = rain on-snow events experienced in utero (0 = high, 1 = low), 5) alo = age at last observation between 2 and 6 years, 6) ROScurrent = rain-on-snow experienced in current year, 7) age . Data3 is a dataframe with 5 variables: 1) id = female identity, 2) year, 3) preg = annual pregnancy probability of females aged 2-6 years, 4) ROSutero = rain on-snow events experienced in utero (0 = high, 1 = low), 5) BM = body mass. All continuous variables have been centered and divided by ... |
|---|