Tree Architecture and Structural Complexity in Mountain Forests of the Annapurna Region, Himalaya

• Published in: Ecology and evolution Vol. 15; no. 4; pp. e71341 - n/a
• Main Authors: Das, Smita, Basnet, Prakash, Seidel, Dominik, Röll, Alexander, Ehbrecht, Martin, Hölscher, Dirk
• Format: Journal Article
• Language: English
• Published: England John Wiley & Sons, Inc 01.04.2025; John Wiley and Sons Inc; Wiley
• Subjects: Annual precipitation; Biodiversity; box‐dimension; Climate change; Complexity; Elevation; Environmental conditions; Environmental factors; Flowers & plants; Forests; Height; Mountain forests; Mountains; Pine needles; Plant diversity; Precipitation; Stand structure; structural complexity; tree architecture; Trees; Variables; Variation; Nepal; elevation; box‐dimension; structural complexity; precipitation; tree architecture
• ISSN: 2045-7758; 2045-7758
• DOI: 10.1002/ece3.71341

ABSTRACT Mountain ranges comprise heterogeneous environments and high plant diversity, but little is known about the architecture and structural complexity of trees in mountain forests. We studied the relationship between tree architecture, environmental conditions, and tree structural complexity in forests of the Annapurna region in the Himalaya. We further asked whether and how tree structural complexity translates into forest stand structural complexity. The study covers 546 trees on 14 undisturbed study plots across wide ranges of elevation (1300 to 3400 m asl.) and annual precipitation (1180 to 3600 mm yr.−1). They were assessed by ground‐based mobile laser scanning. We found that tree structural complexity, expressed as box‐dimension (Db), was lowest for the needle‐leaved Pinus wallichiana and highest for the broad‐leaved Daphniphyllum himalense. A high share of the variation in Db was explained by tree architecture. In multivariate models, tree height, crown radius, and crown length explained more than 60% of the observed variation in Db. Stem density of the plot accounted for 19% of the variation in Db, and there was no influence of tree diversity. Precipitation explained l3% of the observed variation in tree Db, but elevation and slope did not have significant influences. As expected, tree height decreased with increasing elevation, but small trees often had relatively high Db values. The standard deviation of tree‐level Db within a plot explained 47% of the variation in stand‐level structural complexity among plots, surpassing the maximum tree‐level Db. This suggests that both the sole removal of small or large trees would reduce the stand‐level complexity by 36%. We conclude that in the Himalayan forests, species identity and tree architecture play a significant role in determining tree structural complexity, while environmental factors have a smaller role. Furthermore, structural variation among the trees within a plot plays a crucial role for the structural complexity at the stand level. Tree architecture and structural complexity were studied in mountain forests of the Himalaya. We assessed 546 trees belonging to six species by mobile laser scanning. The change in tree structural complexity with elevation was less pronounced than the decline in tree height. Species identity and tree architecture played a significant role in determining tree structural complexity. Structural variation among the trees determines the structural complexity at the stand level.