Invasibility of neutral communities |
| |
Authors: | Tomáš Herben |
| |
Affiliation: | 1. Key Laboratory of Reservoir Aquatic Environment, Department of Three Gorges'' Eco-Environment, Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, P.R. China;2. Landcare Research, Crown Research Institute New Zealand, Lincoln 7608, New Zealand;3. Corresponding authors. |
| |
Abstract: | Comparative data in invasion ecology show that (i) disturbance enhances community invasibility, (ii) there is a positive relationship between residence time of an invader and its success, (iii) there are broadly constant proportions of newly arrived species to those that become established and dominant (“tens rule”), and (iv) invasive species have higher growth rates in comparison with non-invasive species. I use a simple neutral model to test whether these patterns occur in communities with all species identical and no species-specific interactions. In the model, local communities are grouped into continents with immigration rates smaller between than within the continents. Species coming from the other continent are considered to be alien and their fates are recorded. In the model, disturbance predictably increases species numbers and numbers of individuals of aliens. However, the model makes different predictions on effects of disturbance on three processes involved in alien species spreading: establishment (positive effect of disturbance), naturalization (negative effect) and dominance (positive effect). The predictions do not change if variation of growth rates is incorporated into the model. The model also predicts positive relationship between residence time and abundance. Total community size had little effect on success of alien species. The broad agreement of the predictions of the neutral model with the patterns from the field suggests that some of these general patterns of community invasibility are to some degree fully independent of any specific biological assumptions and by themselves may not provide many insights on underlying biological processes. Aggregate data should therefore be used with great caution and statistical patterns must be removed by means of generating null model predictions. |
| |
Keywords: | |
本文献已被 ScienceDirect 等数据库收录! |
|