Characterizing spatial structure of Abies marocana forest through point pattern analysis

Abstract

Aim of study: Understanding small-scale patterns caused by stochastic factors or community interactions driving forest structure and diversity of Moroccan fir Abies marocana Trab.Area of study: Talassemtane fir forest, Talassemtane National Park, Rif Mountains, northern Morocco.Material and methods: Eight plots representative of the structural variability of A. marocana forests were selected, and all tree individuals with diameter at breast height (dbh) ≥2 cm were mapped and measured. We performed four types of spatial point pattern analyses: (1) Univariate analyses to explore the overall trees spatial pattern, (2) bivariate analyses to assess the spatial relationship between juveniles and A. marocana adults, (3) correlation between tree sizes (dbh) and distance between points pairs using the univariate mark correlation function, and (4) random labeling analyses between dominant and suppressed Moroccan fir individuals to assess competition patterns.Main results: We found a strong spatial aggregation of fir individuals and a positive intraspecific association between juveniles and adult trees. However, there were weak but significant distance-dependent effect on tree size and density-dependent effect on suppression pattern.Research highlights: Shade-tolerance, seed dispersal and/or microsite heterogeneity might play important roles in the observed fir patterns. Our results provide a basic knowledge on within-stand Moroccan fir spatial distribution, with implications for adaptive management of these relic forests, and prompting to further research to test advanced hypotheses.Additional key words: Moroccan fir; Talassemtane National Park; Rif forest; Spatial analysis; summary statistics; facilitation; aggregation.Abbreviations used: MF (Moroccan fir); Talassemtane National Park (TNP); dbh (diameter at breast height); Univariate pair-correlation function (g(r)); Heterogeneous Poisson (HP); Bivariate pair-correlation function (g12(r)); Univariate mark correlation function (kmm(r)), Mark connection function (p12(r)).