Effects of sampling effort on estimates of the structure of replacement networks

Aims Important aspects of plant community dynamics depend on interactions between plant species which affect the processes of recruitment and the replacement of dead individuals by new ones. These interactions blend in the replacement network of the community. The qualitative and functional structure of replacement networks can provide insights on community stability properties. The goal of this study was analysing how sampling effort affects estimates of different descriptors of replacement networks. Location Mixed Pine-Oak forests in Southern Spain. Methods We sampled the replacement networks of nine forest patches. In each forest we surveyed 16 plots of 25 x 25m, locating all the saplings of woody species and noting whether they were recruiting under the canopy of some plant species or in open interspaces. Using the replacement networks from the plots of each forest we constructed curves relating network descriptor estimates to sampling effort. Additionally we calculated the completeness of basic network elements (number of species and interactions) using rarefaction and extrapolation techniques. Results Number of species (S) and connectance (C) stabilized within our range of sampling effort. The estimates of S reached completeness values above 97%. However, the number of interactions in the network (L) and the mean number or interactions per species (k) did not stabilise although the estimates of L reached completeness values above 86%. With few exceptions, the parameters describing the functional structure of the network and those related to community stability stabilized within our range of sampling effort. Conclusions Our results suggest that most replacement networks descriptors in the studied forests can be reliably estimated from samples of around 1 ha. Since plots used in forest ecology are commonly around that size, replacement network monitoring can be easily incorporated in forest ecology studies as a highly cost-effective tool to explore community dynamics. The reliability of replacement network estimates will allow both a solid foundation for further developments and also a straightforward comparison of results obtained from multiple communities. This article is protected by copyright. All rights reserved.