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van Daalen, S.

Publications and source records attributed to van Daalen, S..

4 recordsLinked to original sources

Linking differences in personality to demography in the wandering albatross

Population dynamics are shaped by individual differences. With a good understanding of the relationships between individual differences and vital rates, population models can be improved to yield more realistic and detailed demographic projections. Personality, i.e., consistent individual differences in behaviour, is expected to shape individual differences in performance. Yet, an empirical quantification of its impact on population dynamics is currently lacking. Here, we developed and analysed a three-dimensional hyperstate population model that accounts for three sources of individual differences simultaneously in its structure: age, breeding state and boldness as a measure of personality. We parameterized our model using empirical demographic and boldness data on the wandering albatross (Diomedea exulans) population from the Crozet archipelago. We conducted sensitivity analyses to quantify the relative importance of boldness. We then simulated scenarios of increased strength of relationship between boldness and three vital rates (survival, breeding probability and breeding success) to explore conditions under which shifts in boldness distribution could be observed in the future. We showed that the sensitivity of population growth rate to changes in vital rates followed the normal distribution of boldness within the population. Indeed, population growth rate was much less sensitive to changes in the vital rates of extreme shy or bold individuals, compared to that of individuals of intermediate boldness. Overall, sensitivity of population growth rate was greater for survival than reproductive rates across all three dimensions. Our simulations showed that increasing the strength of the relationship between boldness and survival would yield the greatest shift in boldness distribution over time compared to breeding probability and breeding success. However, shifts in boldness distribution appeared constrained by the low heritability (< 0.2) value and the large variance in boldness in this population. Our study provides an important contribution to our understanding of the role of personality in shaping the population dynamics of wild species. In the face of global change, our approach offers a promising avenue to predict the potential for behavioral adaptation. More generally, our approach may help to unravel the complex interplay between individual variations in any (or many) traits and population dynamics.

ecology↗

Inequality, heterogeneity, and chance: Multiple factors and their interactions

A heterogeneous population is a mixture of groups differing in vital rates. In such a population, some of the variance in demographic outcomes (e.g., longevity, lifetime reproduction) is due to heterogeneity and some is the result of stochastic demographic processes. Many studies have partitioned variance into its between-group and within-group components, but have focused on single factors. Especially for longevity, variance due to stochasticity is far greater than that due to heterogeneity. Here we extend analysis to multiple-factor studies, making it possible to calculate the contributions to variance of each factor and each of the interactions among factors. We treat the population as a mixture and use the marginal mixing distributions to compute variance components. Examples are presented: longevity as a function of sex, race, and U.S. state of residence, lifetime reproduction among set of developed countries and as a result of resource availability and pesticide exposure.

ecology↗

Individual stochasticity in the life history strategies of animals and plants

The life histories of organisms are expressed as rates of development, reproduction, and survival. However, individuals may experience differential outcomes for the same set of rates. Such individual stochasticity generates variance around familiar mean measures of life history traits, such as life expectancy and the reproductive number R0. By writing life cycles as Markov chains, we calculate variance and other indices of variability for longevity, lifetime reproductive output (LRO), age at offspring production, and age at maturity for 83 animal and 332 plant populations from the CO_SCPLOWOMADREC_SCPLOW and CO_SCPLOWOMPADREC_SCPLOW matrix databases. We find that the magnitude within and variability between populations in variance indices in LRO, especially, are surprisingly high. We furthermore use principal components analysis to assess how the inclusion of variance indices affects life history constraints. We find that these indices, to a similar or greater degree than the mean, explain the variation in life history strategies among plants and animals.

ecology↗

When the going gets tough, the tough get going: effect of extreme climate on an Antarctic seabird’s life history

1Individuals differ in many ways. Most produce few offspring; a handful produce many. Some die early; others live to old age. It is tempting to attribute these differences in out-comes to differences in individual traits, and thus in the demographic rates experienced. However, there is more to individual variation than meets the eye of the biologist. Even among individuals sharing identical traits, life history outcomes will vary due to individual stochasticity, i.e., to chance. Quantifying the contributions of heterogeneity and chance is essential to understanding natural variability. Inter-individual differences vary across environmental conditions. Heterogeneity and stochasticity depend on environmental conditions. We show that favorable conditions increase the contributions of individual stochasticity, and reduce the contributions of heterogeneity, to variance in demographic outcomes in a seabird population. The opposite is true under poor conditions. This result has important consequence for understanding the ecology and evolution of life history strategies.

ecology↗