Modelling branch surface area of Picea abies [L.] Karst

ABSTRACTAllometric models based on limited sub-samples are widely used for predicting forest-scale information. Here, we develop allometric models for the branch surface area of the widespread conifer species Picea abies [L.] Karst. Branch surface area is a proxy for the capacity of tree branches to intercept and store water and air pollutants. Based on “probability proportional to size” sampling, we measured the surface area for 285 branches and then calculated the branch surface area of 30 trees (and their 3298 branches). We developed allometric models to estimate the total surface area of branches, as well as their number and diameters, for trees across a range of diameters (DBH), heights, and crown ratios (CR). We show that DBH and CR play significant roles in branch characteristics. The branch surface area was linearly related to the stand basal area. Reducing stand density will proportionally reduce interception capacity. The approach outlined here may help stimulate further studies (more species, regions, and management practices) required to optimize stand density for ecosystem services related to crown characteristics, such as hydrology, forage quality, and quantity or capacity for air pollutants.KEYWORDS: Precipitation interceptionwater capacitybarkNorway sprucehydrology-oriented silviculturePPS sampling AcknowledgementsBranch and tree data were sampled on long-term research plots (LTRP) of the Department of Forest Growth, Silviculture and Genetics of the Austrian Research Centre for Forests (BFW). The maintenance of such LTRP is one of the core tasks of BFW and is financed through the base funding of BFW provided by the Austrian Federal Ministry of Agriculture, Forestry, Regions, and Water Management. The authors are grateful for this support. Moreover, the authors want to thank Gerald Schnabel for the preparation of Figure 2. The analysis was partly funded by the European Union Horizon Europe programme as part of the project ‘OPTimising FORest management decisions for a low-carbon, climate resilient future in Europe’ (OptFor-EU), under Grant agreement n°101060554. Views and opinions expressed are however those of the authors only and do not necessarily reflect those of the European Union or REA. Neither the European Union nor the granting authority can be held responsible for them.Disclosure statementNo potential conflict of interest was reported by the authors.Data availability statementThe data used in this study will be made available upon request.