Structural heterogeneity and spatial autocorrelation in a natural mature Pinus sylvestris dominated forest

Abstract

The tree species composition, vertical stratification and patterns of spatial autocorrelation at the tree and quadrate (25 × 25 m) scales were studied in a natural mature PinuS sylvestris dominated forest in eastern Finland. For the analyses we mapped the locations and dimensions of trees taller than 10 m in a 9 ha (300 × 300 m) area, and within this area we mapped all trees taller than 0.3 m on a core plot of 4 ha (200 × 200 m). The overall tree size distribution was bimodal. the dominant layer and the understory forming the peak frequencies. Pinus sylvestris dominated the main canopy, together with scattered Betula pendula and Picea abies. Alnus incana, Populus tremula, Salix caprea, Sorbus aucuparia and Juniperus communis occurred only in the under‐ and middlestories. Autocorrelation analysis (semivarianee) of tree size variation revealed spatial patterns, which were strongly dependent on the size of trees included in the analysis. When all living trees, including the understory regeneration, were taken into account, the autocorrelation pattern ranged up to 35 m inter‐tree distances, reflecting the spatial scale of understory regeneration patches. Competitive interaction among middle‐ and upperstory trees (height>10 m) had contrasting effects on autocorrelation pattern depending on spatial scale. At the fine scale, dominant trees suppressed their smaller close neighbors (asymmetric competition), which was shown as increased tree size variation at small inter‐tree distances (<2 m). At slightly larger inter‐tree distances, specifically among large trees of similar size, competition was more symmetrical, which resulted in decreased tree size variation at these inter‐tree distances (3–4 m). This effect was seen most clearly in the dominant trees, there being a clear autocorrelation pattern in tree size up to inter‐tree distances of ∼4 m. At the quadrate scale (25 × 25 m) the analysis revealed high local variation in structural characteristics such as tree height diversity (THD), tree species diversity (H) and autocorrelation of tree height. The analysis suggests that naturally developed P. sylvestris forests exhibit complex small‐scale patterns of structural heterogeneity and spatial autocorrelation in tree size. These patterns may be important for stand‐scale habitat diversity and can have aggregated effects on ecosystem dynamics at larger spatial scales though their influence on the spread of disturbance and regeneration after disturbance.

Post-fire effects and short-term regeneration dynamics following high-severity crown fires in a Mediterranean forest

“…Following Kuuluvainen et al (1998), we used the distribution of tree heights to represent the vertical structure of the forest. The tree height diversity (THD) index was computed for living stems and snags (Kuuluvainen et al 1996), adopting 2.5-m-deep horizontal layers.…”

Spatial surface-pattern analyses and boundary detection techniques applied in forest ecology

“…Como se ha señalado, a pesar de ser los árboles objetos discretos en el espacio, algunas de las variables que los caracterizan (tamaño, genotipo, edad) pueden considerarse consecuencia de factores ambientales continuos tales como la radiación, el régimen de viento, el agua y los nutrientes disponibles en el suelo (Biondi et al, 1994;Kuuluvainen et al, 1993Kuuluvainen et al, , 1996Kuuluvainen et al, , 1998. Una variable z se dice regionalizada (o autocorrelacionada) cuando se pueden predecir los valores de esta variable en algunos puntos del espacio a partir de valores conocidos en otros puntos de muestreo cuyas posiciones espaciales son conocidas.…”

Methods and applications for improving parameter prediction models for stand structures in Finland

“…Pine-dominated old-growth forests typically consist of different age and species cohorts, which form a patchy and multi-layered canopy structure (Kuuluvainen 2002, Lähde et al 1994ab, Rouvinen and Kuuluvainen 2005. Thus, diameter distributions in natural or semi-natural old-growth forests are often bimodal or multimodal (e.g., Kuuluvainen et al 1998a, Linder et al 1997. If the different tree species are examined separately, the distributions seemed unimodal in most cases examined (Siipilehto 2001b, Rouvinen andKuuluvainen 2005; see also Merganič and Sterba 2006 concerning virgin forests in Slovakia).…”