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Forest disturbance and regeneration: a mosaic of discrete gap dynamics and open matrix regimes?

Research output: Contribution to journalJournal article

<mark>Journal publication date</mark>11/2014
<mark>Journal</mark>Journal of Vegetation Science
Issue number6
Number of pages14
Pages (from-to)1341-1354
Early online date27/05/14
<mark>Original language</mark>English


Recent research in boreal forest suggests that an ‘open matrix’ model may be more appropriate than the traditional model of spatially discrete gap dynamics for describing forest disturbance and regeneration, but what is the evidence from temperate broad-leaved deciduous forests concerning the prevalence of these alternative models?

Semi-natural temperate broad-leaved deciduous forest in southern England.

Multi-temporal LiDAR data were used to monitor the changes in tree canopy height and canopy gaps over a 10-yr period for a 130-ha area of forest. Gap dynamics were characterized by quantifying gap creation, expansion, contraction and closure. By identifying the types and rates of canopy height transitions, areas of gap contraction and closure were attributed to the processes of lateral crown growth or vertical regeneration.

Across the study site there was a zonation in canopy and gap properties and their dynamics. Many areas of the forest had the characteristics of open wood-pasture dominated by large, complex gaps being maintained under a regime of chronic disturbance. In these areas, several characteristics of the gap dynamics indicated that regeneration was restricted and this may be attributable to spatially-focused overgrazing by large herbivores. In contrast, other areas were characterized by high, closed canopy forest with small, discrete gaps where gap creation and infill were balanced.

At the landscape-scale broad-leaved deciduous forests contain a spatial mosaic of zones, which conform to different models of disturbance and regeneration dynamics; discrete gap dynamics and open matrix regimes are juxtaposed. It is now important to elucidate the abiotic factors and biotic interactions that determine the spatio-temporal distribution of the different regimes and to examine whether such a ‘regime mosaic’ model is applicable in other forest types.