How to Define Spacing Among Forest Trees to Mitigate Competition: A Technical Note

Establishing an optimum range of inter-species spacing that reduces competition among trees and mitigates the effects of drought is a critical yet complex challenge in forest management. Stand density plays a crucial role in forest functioning by regulating resource allocation within individual trees. Higher stand densities have been shown to reduce sap velocities, indicating intensified competition for water and other resources. However, determining the precise spacing that minimizes competition while maintaining ecosystem balance remains unclear. In this study, conducted in temperate Norway spruce forests at an altitude range of 400-500 m in the Czech Republic, we propose a novel technique to define tree spacing that reduces competitive interactions. We used xylem sap flow residuals of an ordinary least square (OLS) regression model to filter out the effects of elevation and diameter at breast height (DBH) on field-measured sap flow for 101 planted Norway spruce trees with a DBH range of 40 ± 5 cm (≈90-100 years old). The model residuals allowed us to account for the most important driver of sap flow variability: tree density and its underlying effects on individual tree traits. To minimize the confounding effects of temporal and spatial variability, we used twelve consecutive daily measurements of sap flow (6 a.m. to 6 p.m.) taken at the start of the growing season. By constructing an experimental variogram, we quantified sap flow variability as a function of tree spacing. The results showed a steady sap flow pattern at tree densities of 12, 11, and 10 trees per 314 m<sup>2</sup> (equivalent to 350 ± 32 trees per hectare), corresponding to inter-tree spacing measurements of 5.12 m, 5.34 m, and 5.60 m, respectively. These findings suggest that when the <i>N</i> number of trees (median) per unit area (<i>A</i>) is in equilibrium with resource availability, increasing or decreasing the <i>n</i> number of trees may not significantly change competition levels (<i>A; f(A) = N ± n</i>). The size or deviation of <i>n</i> depends on the area to define the minimum and maximum thresholds or tolerance capacity for the number of trees allowed to be in the area. This technique-using a variogram of sap flow residuals to determine tree spacing-can be periodically applied, such as every 10-15 years, and adapted for different elevation gradients (e.g., within 100 m intervals). It offers a practical tool for forest managers and policymakers, guiding thinning and planting strategies to enhance forest resilience in the face of water-stress conditions.

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Journal
Biology
Published
2025-03-15
DOI
https://doi.org/10.3390/biology14030296
Citations
3
Primary Topic
Plant Water Relations and Carbon Dynamics
Type
article
Field-Weighted Citation Impact
3.32
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article

How to Define Spacing Among Forest Trees to Mitigate Competition: A Technical Note

Nataliya Korolyova, Khodabakhsh Zabihi, Vivek Vikram Singh, Rastislav Jakuš et al.
3 citations
Biology
Plant Water Relations and Carbon Dynamics
3.32
article

How to Define Spacing Among Forest Trees to Mitigate Competition: A Technical Note

Nataliya Korolyova, Khodabakhsh Zabihi, Vivek Vikram Singh, Rastislav Jakuš, Aleksei Trubin
article en
3 citations

Abstract

Establishing an optimum range of inter-species spacing that reduces competition among trees and mitigates the effects of drought is a critical yet complex challenge in forest management. Stand density plays a crucial role in forest functioning by regulating resource allocation within individual trees. Higher stand densities have been shown to reduce sap velocities, indicating intensified competition for water and other resources. However, determining the precise spacing that minimizes competition while maintaining ecosystem balance remains unclear. In this study, conducted in temperate Norway spruce forests at an altitude range of 400-500 m in the Czech Republic, we propose a novel technique to define tree spacing that reduces competitive interactions. We used xylem sap flow residuals of an ordinary least square (OLS) regression model to filter out the effects of elevation and diameter at breast height (DBH) on field-measured sap flow for 101 planted Norway spruce trees with a DBH range of 40 ± 5 cm (≈90-100 years old). The model residuals allowed us to account for the most important driver of sap flow variability: tree density and its underlying effects on individual tree traits. To minimize the confounding effects of temporal and spatial variability, we used twelve consecutive daily measurements of sap flow (6 a.m. to 6 p.m.) taken at the start of the growing season. By constructing an experimental variogram, we quantified sap flow variability as a function of tree spacing. The results showed a steady sap flow pattern at tree densities of 12, 11, and 10 trees per 314 m<sup>2</sup> (equivalent to 350 ± 32 trees per hectare), corresponding to inter-tree spacing measurements of 5.12 m, 5.34 m, and 5.60 m, respectively. These findings suggest that when the <i>N</i> number of trees (median) per unit area (<i>A</i>) is in equilibrium with resource availability, increasing or decreasing the <i>n</i> number of trees may not significantly change competition levels (<i>A; f(A) = N ± n</i>). The size or deviation of <i>n</i> depends on the area to define the minimum and maximum thresholds or tolerance capacity for the number of trees allowed to be in the area. This technique-using a variogram of sap flow residuals to determine tree spacing-can be periodically applied, such as every 10-15 years, and adapted for different elevation gradients (e.g., within 100 m intervals). It offers a practical tool for forest managers and policymakers, guiding thinning and planting strategies to enhance forest resilience in the face of water-stress conditions.

BiologyVol. 14(3)
Czech University of Life Sciences Prague (CZ), Slovak Academy of Sciences (SK), Institute of Forest Ecology of the Slovak Academy of Sciences (SK)
Clean water and sanitation
Openalex Percentile: Top 9%
Plant Water Relations and Carbon Dynamics
3.32
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