Density-dependence at multiple scales in experimental and natural plant populations

The survival and reproduction of individual plants may be related to the distribution of conspecific neighbours with which they interact. We used 2 years' data from a field experiment to relate the reproduction and survival of focal Silene latifolia plants to the numbers of conspecific plants and flowers within a range of distances (0.16-150 m) from the focal plants. Thus we consider spatial scale as a continuously-varying component of population density. Because the data come from a single continuous population, we fitted regression models in two stages in order to remove spatial autocorrelation induced by environmental factors before modelling density effects. As well as single-scale models, we fitted multiple-scale models to explore interaction kernels. We statistically standardized plant size in some analyses to isolate pollination effects. Reproductive output per plant generally decreased with greater densities of plants and flowers; for example there was a negative effect of female flowers within a 70-m radius in the second year. However, at low female densities there was a positive effect of male flowers at a scale of 13 m in the first year. Seed-set per flower decreased with greater densities of flowers in the second year (at radii < 10 m). Seed predation was greater when more female flowers were present within 5-7 m. Plants' survival probability increased with density within 0.28 m for all but the smallest plants. We also collected data on the pattern and reproductive success of S. latifolia plants in a natural population nearby and applied similar methodology. Here the negative effects of female flower densities occurred at finer scales and gave way to positive effects above 2 m, contrasting with some patterns from the experiment. Synthesis. In a sessile population interacting with mobile biota, the effects of density on individual fitness may vary with the way in which density is measured. This, together with the methodological challenges for analysing spatial data from continuous populations, should be considered when designing and interpreting studies of spatial density-dependence. Taking these issues into account, we may begin to explain the spatial patterns of natural populations.