| Literature DB >> 23398653 |
Elodie Vercken1, Flora Vincent, Ludovic Mailleret, Nicolas Ris, Elisabeth Tabone, Xavier Fauvergue.
Abstract
1. Propagule pressure, i.e. the number of individuals introduced, is thought to be a major predictor of the establishment success of introduced populations in the field. Its influence in laboratory experimental systems has however been questioned. In fact, other factors involved in long-term population persistence, like habitat size, were usually found to explain most of the dynamics of experimental populations. 2. To better understand the respective influence of short- and long-term factors and their potential interaction on extinction dynamics in experimental systems, we investigated the influence of propagule pressure, habitat size and genetic background on the early dynamics of laboratory-based populations of a hymenopteran parasitoid. 3. The amount of demographic variance differed between establishment and persistence phase and was influenced by habitat size and genetic background (geographic strain), but independent of propagule pressure. In contrast, the probability of extinction within five generations depended on the genetic background and on the interaction between propagule pressure and habitat size. Vulnerability to extinction in small size habitats was increased when populations were founded with a small number of individuals, but this effect was delayed until the third to fifth generations. 4. These results indicate that demographic stochasticity is influential during population establishment, but is not affected by the genetic variability of propagules. On the other hand, extinction might be influenced by a genetic Allee effect triggered by the combination of low propagule pressure and genetic drift. Finally, we documented consistent differences between genetic backgrounds in both deterministic and stochastic population dynamics patterns, with major consequences on extinction risk and ultimately population establishment.Entities:
Keywords: Theta‐Ricker model; Trichogramma; adaptation; extinction debt; inbreeding depression; inoculum size; negative density dependence; propagule size
Mesh:
Year: 2013 PMID: 23398653 PMCID: PMC3708108 DOI: 10.1111/1365-2656.12051
Source DB: PubMed Journal: J Anim Ecol ISSN: 0021-8790 Impact factor: 5.091
Models of population dynamics tested to describe experimental variations in population size
| Model | Recurrence equation | Parameters | Processes described |
|---|---|---|---|
| Geometric | Unlimited growth of the population: constant per capita growth rate | ||
| Ricker (Ricker | Negative density dependence: the natural logarithm of the per capita growth rate decreases linearly with population size | ||
| Theta-Ricker (Gilpin & Ayala | Negative density-dependence: the natural logarithm of the per capita growth rate decreases nonlinearly with population size | ||
| Classical Allee effect (Lewis & Kareiva | Positive and negative density dependence: the relationship between population size and per capita growth rate is hump-shaped. If A > 0, the Allee effect is strong. If A < 0, the Allee effect is weak. | ||
| Allee-Ricker (Avilés | Positive and negative density dependence: the relationship between population size and per capita growth rate is hump-shaped. The Allee effect is always strong. | ||
| Allee- Theta-Ricker (Avilés | Positive and negative density dependence: the relationship between population size and per capita growth rate is hump-shaped. The Allee effect is always strong. |
Fig. 1Projection of the natural logarithm of the ratio of population sizes between two consecutive generations in function of population size. Under this transformation, simple negative density dependence (Ricker model) appears as a straight, decreasing line, while nonlinear density dependence (Theta-Ricker model) is either a decreasing concave function (θ > 1) or a decreasing convex function (θ < 1). A Theta-Ricker model with θ < 1 was fitted for all combinations of strain and habitat size (model fit is drawn in red). The scale of the left panel is represented by a dashed line on the right panel to highlight the stronger density dependence regulation exerted in the small habitats.
Fig. 2Mean rescaled squared residuals between predicted and observed dynamics along the five generations: (left) during establishment or persistence phase; (middle) in small and large habitats; and (right) in populations of the three geographic strains (R: Reunion, T: Taiwan, V: Vietnam). Error bars are 95% confidence intervals.
Fig. 4Cumulative probability of extinction along the five generations in small (dashed lines) and large habitats (full lines) for the three geographic strains.
Fig. 3Cumulative probability of extinction at the fifth generation in small (left) and large habitats (right) in function of the number of founding females. Symbols: experimental observations averaged over all replicates. Lines: model fits including the interaction between habitat size and propagule pressure.