You have full text access to this OnlineOpen article
Identifying when weather influences life-history traits of grazing herbivores
Article first published online: 19 JUN 2007
DOI: 10.1111/j.1365-2656.2007.01251.x
Additional Information
How to Cite
SIMS, M., ELSTON, D. A., LARKHAM, A., NUSSEY, D. H. and ALBON, S. D. (2007), Identifying when weather influences life-history traits of grazing herbivores. Journal of Animal Ecology, 76: 761–770. doi: 10.1111/j.1365-2656.2007.01251.x
Publication History
- Issue published online: 19 JUN 2007
- Article first published online: 19 JUN 2007
- Received 21 July 2006; accepted 27 March 2007
Keywords:
- birth weight;
- mixed model;
- multicollinearity;
- random coefficient;
- smoothing
Summary
- 1There is increasing evidence that density-independent weather effects influence life-history traits and hence the dynamics of populations of animals. Here, we present a novel statistical approach to estimate when such influences are strongest. The method is demonstrated by analyses investigating the timing of the influence of weather on the birth weight of sheep and deer.
- 2The statistical technique allowed for the pattern of temporal correlation in the weather data enabling the effects of weather in many fine-scale time intervals to be investigated simultaneously. Thus, while previous studies have typically considered weather averaged across a single broad time interval during pregnancy, our approach enabled examination simultaneously of the relationships with weekly and fortnightly averages throughout the whole of pregnancy.
- 3We detected a positive effect of temperature on the birth weight of deer, which is strongest in late pregnancy (mid-March to mid-April), and a negative effect of rainfall on the birthweight of sheep, which is strongest during mid-pregnancy (late January to early February). The possible mechanisms underlying these weather–birth weight relationships are discussed.
- 4This study enhances our insight into the pattern of the timing of influence of weather on early development. The method is of much more general application and could provide valuable insights in other areas of ecology in which sequences of intercorrelated explanatory variables have been collected in space or in time.

1365-2656/asset/olbannerleft.gif?v=1&s=4f0919eca9042f833d018453e8f48b1e3e3123ec)
1365-2656/asset/olbannerright.gif?v=1&s=92164cf20561f2dc5785bff8431569e5b40f87aa)
