Predictability, contingency, and convergence in late succession: Slow systems and complex data-sets
Abstract:Questions: Are community dynamics in old-growth forests predictable? Convergent? Equilibrial? Are answers to these questions dependent on temporal and spatial scale? How can complex, long-term observational data be used most powerfully to address these questions?
Location: 100-ha tract of old-growth cool-temperate forest in northern Michigan, USA.
Methods: Woody stems were measured, on 243 permanent plots, several times, at varying intervals and intensity, over 70 years. A range of visualization tools and multivariate statistics were used to extract patterns and address questions posed.
Results: This ancient forest is not equilibrial; compositional trends suggest that changes are competitively driven and reflect long-lasting effects of disturbance. Predictability of community change varies across environmental gradients, with interval between samples, with spatial scale, and depending on type of predictability being assessed. Plot trajectories in species-space and changes in diversity suggest successional convergence within some habitats, but not across habitats. Dynamics are strongly structured at the scale of 'habitat-patches'.
Conclusions: Appropriate address of questions about community dynamics requires observational data of appropriate spatial and temporal scale and resolution. Powerful use of such data-sets calls for data-management and analysis tools that are robust with respect to irregularities in design and data structure. While interpretation of long-term descriptive data is challenging, appropriate analyses cast light on late successional dynamics, allowing address of models and hypotheses that are otherwise difficult to test.
Document Type: Research Article
Publication date: August 1, 2007
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