Formulating a general statistical model for Betula spp. invasion of lowland heath ecosystems
P. Manning, NERC Centre for Population Biology, Imperial College London, Silwood Park Campus, Ascot, Berkshire SL5 0NE, UK (fax +44 1344 873173; e-mail firstname.lastname@example.org).
- 1Numerous studies describe thresholds at which transitions between alternate ecosystem states occur but few quantitatively delimit these conditions and present them in simple frameworks that are of use in ecosystem management. Previous research on heathland ecosystems has provided a site-specific statistical model that describes the determinants of the threshold point in heath–scrub vegetation transition, but the wider applicability, and thus utility, of this model was unknown.
- 2Multi-site experimental manipulations were conducted to assess whether a consistent set of factors limited the recruitment of Betula species into heathland vegetation. Data were pooled and used to fit a single general statistical model. The applicability of this model to a wider range of environments was tested using two independent data sets.
- 3The identity of the factors controlling Betula colonization, which include Betula seed bank density, phosphorus (P) availability and disturbance effects, were broadly similar between sites, but the strength of their effect varied widely.
- 4The general model (explained deviance 59·8%) described Betula seedling densities as a function of biomass and necromass density, vegetation height, Betula seed bank density, P availability and soil water content. These relationships were complex, with numerous interaction and polynomial terms.
- 5Although the model was derived from data from a single community type it was reasonably accurate in the prediction of seedling densities over a wider range of heath conditions. However, data capable of validating predictions of high seedling densities were not available.
- 6Synthesis and applications. The apparent success of the general statistical model suggests that an approach incorporating multi-site experiments and statistical modelling can facilitate our understanding of ecosystem state transitions and inform the management of invasive species. By describing Betula invasion as a function of variables that are simple, general descriptions of the environment, the model can potentially inform management in a wide range of conditions. The results suggest that heaths close to seed sources and in the degenerate state of the dwarf shrub cycle are the most vulnerable to invasion, and management should target such sites as a priority. At regional scales, these conditions are probably most common in high soil phosphorus sorption capacity areas, where management should be prioritized.