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© 2014 British Ecological Society. Summary: The question of the relative importance of biotic interactions versus abiotic drivers for structuring plant communities is highly debated but largely unresolved. Here, we investigate the relative importance of mean July air temperature, nitrogen (N) availability and direct plant interactions in determining the millennial-scale population dynamics through the Holocene (10 700-5200 cal. years bp) for four temperate tree taxa in the Scottish Highlands. A variety of dynamic population models were fitted to our palaeoecological time-series data to determine the mechanism(s) by which each driver affected the population biomass dynamics of Betula (birch), Pinus (pine), Alnus (alder) and Quercus (oak). Akaike information criterion weights identified the best model(s) for describing the relationship between each population and driver. The relative importance of these drivers was then assessed by the ability of each model to predict the observed population biomass dynamics. We also measured the change in goodness-of-fit of each model over time. We found that models of intra- and interspecific plant interactions described the plant population dynamics better than temperature- or N-dependent population growth models over the 5000-year study period. The best-fitting models were constant over time for pine, alder and oak. However, the plant-N availability and plant-temperature models provided a progressively better fit to the birch data when temperatures rose and N availability declined, suggesting increasing importance of these abiotic factors coincident with changing conditions. Synthesis. Multiple mechanistic models were applied to palaeoecological data to infer the most likely processes driving millennial-scale plant biomass dynamics in a woodland ecosystem. Direct plant interactions provided a better explanation for population biomass dynamics than growing season temperature or N availability over the full study period. The relative importance of all drivers we assessed here varied by species and - in the case of birch - over time in response to warming and reduced N availability. Multiple mechanistic models were applied to palaeoecological data to infer the most likely processes driving millennial-scale plant biomass dynamics in a woodland ecosystem, and how the importance of each driver changed over time. Here, importance is measured in terms of the goodness of fit of each population dynamic model for predicting the observed biomass dynamics for each of the study taxa. This is measured as the root mean square error (RMSE) between the predicted and observed pollen accumulation rates, which was calculated over a moving window of ca. 500 years. The lowest RMSE value indicates the best fitting model(s). Direct plant interactions provided a better explanation for population biomass dynamics than growing season temperature or N availability over the full study period. The relative importance of all drivers we assessed here varied by species and - in the case of birch - over time in response to warming and reduced N availability.

Original publication

DOI

10.1111/1365-2745.12365

Type

Journal article

Journal

Journal of Ecology

Publication Date

01/01/2015

Volume

103

Pages

459 - 472