Density-dependent processes fluctuate over 50 years in an ecotone forest

Oecologia. 2019 Dec;191(4):909-918. doi: 10.1007/s00442-019-04534-6. Epub 2019 Oct 17.

Abstract

Spatial patterns can inform us of forest recruitment, mortality, and tree interactions through time and disturbance. Specifically, successional trajectories of self-thinning and heterospecific negative density dependence can be interpreted from the spatial arrangement of forest stems. We conducted a 50-year spatial analysis of a forest undergoing succession at the ecotone of the southwestern Canadian boreal forest. The forest progressed from early to late sere and experienced repeated severe droughts, forest tent caterpillar outbreaks (Malacosoma disstria), as well as the outbreak of bark beetles. Cumulatively, the forest lost 70% of stems due to natural succession and a combination of disturbance events. Here, we describe spatial patterns displaying signals of successional self-thinning, responses to disturbance, and changes in patterns of density dependence across 50 years. Forest succession and disturbance events resulted in fluctuating patterns of density-dependent mortality and recruitment that persisted into late seral stages. The combined effects of conspecific and heterospecific density-dependent effects on mortality and recruitment resulted in near-spatial equilibrium over the study period. However, the strength and direction of these demographic and spatial processes varied in response with time and disturbance severity. The outbreak of forest tent caterpillar, pronounced drought, and bark beetles combined to reduce stand aggregation and promote a spatial equilibrium. Density-dependent processes of competition and facilitation changed in strength and direction with succession of the plot and in combination with disturbance. Together these results reinforce the importance of successional stage and disturbance to spatial patterns.

Keywords: Aspen; Density dependence; Ecotone; Spruce.

MeSH terms

  • Canada
  • Droughts
  • Forests*
  • Spatial Analysis
  • Trees*