Quantifying Crown Morphology of Mixed Pine-Oak Forests Using Terrestrial Laser Scanning

Sara Uzquiano,Dominik Seidel,Ignacio Barbeito,Roberto San Martín,Felipe Bravo,Martin Ehbrecht

doi:10.3390/rs13234955

Sara Uzquiano, Dominik Seidel + Show 4 more

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https://doi.org/10.3390/rs13234955

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Abstract

Mixed forests make up the majority of natural forests, and they are conducive to improving the resilience and resistance of forest ecosystems. Moreover, it is in the crown of the trees where the effect of inter- and intra-specific interaction between them is evident. However, our knowledge of changes in crown morphology caused by density, competition, and mixture of specific species is still limited. Here, we provide insight on stand structural complexity based on the study of four response crown variables (Maximum Crown Width Height, MCWH; Crown Base Height, CBH; Crown Volume, CV; and Crown Projection Area, CPA) derived from multiple terrestrial laser scans. Data were obtained from six permanent plots in Northern Spain comprising of two widespread species across Europe; Scots pine (Pinus sylvestris L.) and sessile oak (Quercus petraea (Matt.) Liebl.). A total of 193 pines and 256 oaks were extracted from the point cloud. Correlation test were conducted (ρ ≥ 0.9) and finally eleven independent variables for each target tree were calculated and categorized into size, density, competition and mixture, which was included as a continuous variable. Linear and non-linear multiple regressions were used to fit models to the four crown variables and the best models were selected according to the lowest AIC Index and biological sense. Our results provide evidence for species plasticity to diverse neighborhoods and show complementarity between pines and oaks in mixtures, where pines have higher MCWH and CBH than oaks but lower CV and CPA, contrary to oaks. The species complementarity in crown variables confirm that mixtures can be used to increase above ground structural diversity.

Highlights

Trees determine the living conditions for many other organism groups and, typically, they are the most valuable economical component for forests
Correlation Coefficients for Diameter at Breast Height (DBH) and TH were 0.98 and 0.74, respectively, confirming the distribution of Terrestrial Laser Scanning (TLS) data corresponding to the data taken in the field are consistent and have no significant differences
Descriptive statistics of all trees classified by species and pure and mix plots was performed (Table 6)

Summary

Introduction

Trees determine the living conditions for many other organism groups and, typically, they are the most valuable economical component for forests. An increase in tree species diversity can generate a variety of forest structures and interaction between the component species [7], which may lead to more resistant, resilient, and adaptable forests [2,3], and an important risk-reduction strategy [8]. For this reason, within the last two decades, to understand and manage species’ behavior in mixed conditions, many researchers have focused on the performance of mixed forests species input [2,9,10]. Considering that mixed forests dynamics vary on a small scale [15] more studies are still needed across a variety of forest types to establish a sound theoretical approach across scales

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