Structural diversity underpins carbon storage in Australian temperate forests

• Published in: Global ecology and biogeography Vol. 29; no. 5; pp. 789 - 802
• Main Authors: Aponte, Cristina, Kasel, Sabine, Nitschke, Craig R., Tanase, Mihai A., Vickers, Helen, Parker, Linda, Fedrigo, Melissa, Kohout, Michele, Ruiz‐Benito, Paloma, Zavala, Miguel A., Bennett, Lauren T., Hickler, Thomas
• Format: Journal Article
• Language: English
• Published: Oxford Wiley Subscription Services, Inc 01.05.2020
• Subjects: Abiotic factors; Agglomeration; Australia; Biodiversity; Biotic factors; Carbon; Carbon sequestration; climate; Data management; Diversity indices; environmental factors; fire; fire history; forest carbon; forest inventory; Forest management; forest trees; forest types; Forests; functional diversity; functional identity; mass‐ratio; Multivariate statistical analysis; niche‐complementarity; Plant diversity; soil; Soils; Species diversity; Species richness; structural diversity; structural equation model; Structural equation modeling; Temperate forests; wood density; Australia
• ISSN: 1466-822X; 1466-8238
• DOI: 10.1111/geb.13038

Aim Forest carbon storage is the result of a multitude of interactions among biotic and abiotic factors. Our aim was to use an integrative approach to elucidate mechanistic relationships of carbon storage with biotic and abiotic factors in the natural forests of temperate Australia, a region that has been overlooked in global analyses of carbon‐biodiversity relations. Location South‐eastern Australia. Time period 2010–2015. Major taxa studied Forest trees in 732 plots. Methods We used the most comprehensive forest inventory database available for south‐eastern Australia and structural equation models to assess carbon‐storage relationships with biotic factors (species or functional diversity, community‐weighted mean (CWM) trait values, structural diversity) and abiotic factors (climate, soil, fire history). To assess the consistency of relationships at different environmental scales, our analyses involved three levels of data aggregation: six forest types, two forest groups (representing different growth environments), and all forests combined. Results Structural diversity was consistently the strongest independent predictor of carbon storage at all levels of data aggregation, whereas relationships with species‐ and functional‐diversity indices were comparatively weak. CWMs of maximum height and wood density were also significant independent predictors of carbon storage in most cases. In comparison, climate, soil, and fire history had only minor and mainly indirect effects via biotic factors on carbon storage. Main conclusions Our results indicate that carbon storage in our temperate forests was underpinned by tree structural diversity (representing efficient utilisation of space) and by CWM trait values (representing selection effects) more so than by tree species richness or functional diversity. Abiotic effects were comparatively weak and mostly indirect via biotic factors irrespective of the environmental range. Our study highlights the importance of managing forests for functionally important species and to maintain and enhance their structural complexity in order to support carbon storage.