Short communication: Basic wood density and moisture content of 14 shrub species under two different site conditions in the Chilean Mediterranean shrubland

Keywords: wood properties, water content, shrub size, shrubland ecology, sclerophyllous vegetation


Aim of the study: The aim of this study is to provide information on species-specific basic wood density (g cm-3) and moisture content (%) in Mediterranean shrublands.

Area of study: The study covers two sites of the sclerophyllous shrubland in central Chile, Cortaderal (34°35’S 71°29’W) and Miraflores (34°08’S 70°37’W), characterized by different climatic and topographic conditions.

Material and methods: The sampling area covers 4,000 m2 over four plots at two sites. Shrub species were identified and size-related attributes such as height and crown size measured. A total of 322 shrubs were sampled at 0.3 m aboveground to determine basic wood density and moisture content. Species-specific differences and similarities were analyzed by multiple pairwise comparisons (post-hoc tests) and by ordination and hierarchical clustering.

Main results: We found high variation across species in wood density (0.46-0.77 g cm-3) and moisture content (41.6-113.1%), with many significant differences among species in wood density and among sites in moisture content. Because intraspecific variability could not be explained by shrub size and pronounced differences in wood density (0.49-0.64 g cm-3) also occurred between species of the same genus (e.g., Baccharis linearis and Baccharis macraei), our results suggested that phylogenetic affinity may be less important than adaptation to local conditions.

Research highlights: The values presented here were variable according to the type of species and environmental conditions, necessitating the determination of basic wood density (BWD) and moisture content at site – and species-specific level. The provided BWD estimates allow converting green volume to aboveground biomass in shrubland areas and are an essential source of information for estimating the carbon stocks.


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Author Biographies

Daniele Castagneri, University of Padova, Dept. Land, Environment, Agriculture and Forestry (TESAF. Via dell’Università 16, 35020 Legnaro (PD)

Department of Land, Environment, Agriculture and Forestry

Tommaso Anfodillo, University of Padova, Dept. Land, Environment, Agriculture and Forestry (TESAF. Via dell’Università 16, 35020 Legnaro (PD)

Department of Land, Environment, Agriculture and Forestry

Mark E. Olson, Universidad Nacional Autónoma de México, Instituto de Biología, Tercer Circuito s/n de Ciudad Universitaria, Ciudad de México 04510

Instituto de Biologia


Barajas Morales J, 1987. Wood specific gravity in species from two tropical forests in Mexico. IAWA J 8(2): 143-148.

Castro FX, Tudela A, Sebastià MT, 2003. Modeling moisture content in shrubs to predict fire risk in Catalonia (Spain). Agric For Meteorol 116: 49-59.

Chave J, Andalo C, Brown S, Cairns MA, Chambers JQ, Eamus D, et al., 2005. Tree allometry and improved estimation of carbon stocks and balance in tropical forests. Oecologia 145: 87-99.

Chave J, Muller-Landau HC, Baker TR, Easdale TA, Ter Steege H, Webb CO, 2006. Regional and phylogenetic variation of wood density across 2456 neotropical trees species. Ecol Appl 16(6): 2356-2367.[2356:RAPVOW]2.0.CO;2

Chave J, Coomes D, Jansen S, Lewis SL, Swenson NG, Zanne AE, 2009. Towards a worldwide wood economics spectrum. Ecol Lett 12: 351-366.

Chavent M, Kuentz V, Labenne A, Liquet B, Saracco J, 2017. PCAmixdata: Multivariate analysis of mixed data. R package version 3.1.

CIREN, 1996. Estudio agrológico de la VI Región. Descripciones de suelos, materiales y símbolos. Centro de Información de Recursos Naturales. Publicación 114. Tomos I y II. Santiago, Chile. 546 pp.

Crivellaro A, Schweingruber FH, 2013. Atlas of wood, bark and pith anatomy of the Eastern Mediterranean trees and shrubs with a special focus on Cyprus. Springer-Verlag Berlin Heidelberg. 583 pp.

Cruz P, Bascuñan A, Velozo J, Rodríguez M, 2015. Funciones alométricas de contenido de carbono para quillay, peumo, espino y litre. Bosque 36(3): 375-381.

Dinno A, 2017. Dunn.test: Dunn's test of multiple comparisons using rank sums. R package vers. 1.3.5.

Fernández-Moya J, San Miguel-Ayanz A, Cañellas I, Gea-Izquierdo G, 2011. Variability in Mediterranean annual grassland diversity driven by small-scale changes in fertility and radiation. Plant Ecol 212: 865-877.

Fick SE, Hijmans RJ, 2017. WorldClim 2: new 1km spatial resolution climate surfaces for global land areas. Int J Climatol 37(12): 4302-4315.

Fromm JH, Sautter I, Matthies D, Kremer J, Schumacher P, Ganter C, 2001. Xylem water content and wood density in spruce and oak trees detected by high-resolution computed tomography. Plant Physiol 127: 416-425.

Gayoso J, Guerra J, Alarcón D, 2002. Contenido de carbono y funciones de biomasa en especies nativas y exóticas. Medición de la capacidad de captura de carbono en bosques de Chile y su promoción en el mercado mundial. Informe técnico FONDEF D98I1076. Instituto Forestal y Universidad Austral de Chile. Valdivia. 53 pp.

Henry M, Bombelli A, Trotta C, Alessandrini A, Birigazzi L, Sola G, et al., 2013. GlobAllomeTree: international platform for tree allometric equations to support volume, biomass and carbon assessment. iForest 6: 326-330.

INFOR, 2020. Chilean forestry sector 2020. Instituto Forestal. Santiago, Chile. 49 pp.

Kenzo T, Sano M, Yoneda R, Chann S, 2017. Comparison of wood density and water content between dry evergreen and dry deciduous forest trees in Central Cambodia. Jpn Agric Res Q 54(4): 363-374.

Longuetaud F, Mothe F, Fournier M, Dlouha J, Santenoise P, Deleuze C, 2016. Within-stem maps of wood density and water content for characterization of species: a case study on three hardwood and two softwood species. Ann For Sci 73: 601-614.

Maechler M, Rousseeuw P, Struyf A, Hubert M, Hornik K, 2021. cluster: Cluster Analysis Basics and Extensions. R package version 2.1.2.

Martínez-Cabrera HI, Jones CS, Espino S, Schenk HJ, 2009. Wood anatomy and wood density in shrubs: Responses to varying aridity along transcontinental transects. Am J Bot 96(8): 1388-1398

Martínez-Cabrera HI, Schenk HJ, Cevallos-Ferriz SRS, Jones CS, 2011. Integration of vassel traits, wood density, and height in angiosperm shrubs and trees. Am J Bot 98(5): 915-922.

McFerrin L, 2013. HDMD: Statistical analysis tools for high dimension molecular data (HDMD). R package vers. 1.2.

Muller-Landau HC, 2004. Interspecific and inter-site variation in wood specific gravity of tropical trees. Biotropica 36: 20-32.

Preston KA, Cornwell WK, DeNoyer JL, 2006. Wood density and vessel traits as distinct correlates of ecological strategy in 51 California coast range angiosperms. New Phytol 170: 807-818.

R Core Team, 2021. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. R version 4.0.4.

Revelle W, 2021. Psych: Procedures for personality and psychological research, Northwestern University, Evanston, ILL, USA. Version = 2.1.6.

Ruiz-Peinado R, Bravo-Oviedo A, López-Senespleda E, Bravo F, del Rio M, 2017. Forest management and carbon sequestration in the Mediterranean region: A review. Forest Syst 26(2): eR04S.

Schulz JJ, Cayuela L, Echeverria C, Salas J, Rey-Benayas JM, 2010. Monitoring land cover change of the dryland forest landscape of Central Chile (1975-2008). Appl Geogr 30: 436-447.

Schulz JJ, Cayuela L, Rey-Benayas JM, Schröder B, 2011. Factors influencing vegetation cover change in Mediterranean Central Chile (1975-2008). Appl Veg Sci 14: 571-582.

Segura G, Balvanera P, Durán E, Pérez A, 2003. Tree community structure and stem mortality along a water availability gradient in a Mexican tropical dry forest. Plant Ecol 169: 259-271.

Ter Steege H, Hammond DS, 2001. Character convergence, diversity, and disturbance in tropical rain forest in Guyana. Ecology 82: 3197-3212.[3197:CCDADI]2.0.CO;2

Wickham H, 2016. ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag, NY. 213 pp.

Zanne AE, López-González G, Coomes DA, Ilic J, Jansen S, Lewis SL, et al., 2009. Global wood density database. Dryad.

Zwanzig M, Schlicht R, Frischbier N, Berger U, 2020. Primary steps in analyzing data: Tasks and tools for a systematic data exploration. In: Forest-water interactions. Ecological studies (analysis and synthesis), vol 240; Leiva DF et al. (eds). Springer, Cham.

How to Cite
KutcharttE., GayosoJ., GuerraJ., PirottiF., CastagneriD., AnfodilloT., RojasY., OlsonM. E., & ZwanzigM. (2022). Short communication: Basic wood density and moisture content of 14 shrub species under two different site conditions in the Chilean Mediterranean shrubland. Forest Systems, 31(1), eSC01.
Short communications