Short communication: Variation of deadwood density by decay class in Douglas fir (Pseudotsuga menziesii (Mirbel) Franco) stands in Italy
Abstract
Aim of the study: To estimate fresh and basic density values of Douglas fir deadwood for the five decay classes used in the National Forest Inventories (NFIs).
Area of study: Rincine forest in Tuscany region (Italy).
Material and methods: 140 samples of Douglas fir deadwood (28 for each decay class; 14 of which were collected in summer and 14 in winter) were collected and analysed in the laboratory. The samples were weighed fresh, then placed in the oven for 3 days at 60°C. Afterwards the samples were weighed dried. The laboratory data were used to estimate moisture content (%), fresh and basic density by decay class.
Main results: The results showed that the trend of basal density decreased from 1st to 5th decay class (0.43 g cm-3, 0.39 g cm-3, 0.37 g cm-3, 0.29 g cm-3 and 0.20 g cm-3). An average basic density of 0.34 g cm-3 could be used in future studies concerning the estimation of C-stock in Douglas fir deadwood.
Research highlights: The moisture content of all decay classes of lying deadwood is influenced by the season (winter vs. summer) and consistent with the local climate regime.
Downloads
References
Bayraktar S, Paletto A, Floris A, 2020. Deadwood volume and quality in recreational forests: The case study of the Belgrade forest (Turkey). For Syst 29: e008. https://doi.org/10.5424/fs/2020292-16560
Bell G, Kerr A, McNickle D, Woollons R, 1996. Accuracy of the line intersect method of post-logging sampling under orientation bias. For Ecol Manag 84: 23-28. https://doi.org/10.1016/0378-1127(96)03773-5
Brin A, Bouget C, Brustel H, Jactel H, 2011. Diameter of downed woody debris does matter for saproxylic beetle assemblages in temperate oak and pine forests. J Insect Conserv 15(5): 653-669. https://doi.org/10.1007/s10841-010-9364-5
Brockerhoff EG, Jactel H, Parrotta JA, Ferraz SF, 2013. Role of eucalypt and other planted forests in biodiversity conservation and the provision of biodiversity-related ecosystem services. For Ecol Manag 301: 653-669. https://doi.org/10.1016/j.foreco.2012.09.018
Brown S, 2002. Measuring carbon in forests: current status and future challenges. Environ Pollut 116: 363-372. https://doi.org/10.1016/S0269-7491(01)00212-3
Castaldi C, Vacchiano G, Marchi M, Corona P, 2017. Projecting nonnative Douglas fir plantations in southern Europe with the forest vegetation simulator. For Sci 63: 101-110. https://doi.org/10.5849/forsci.16-048
De Meo I, Angelli EA, Graziani A, Kitikidou K, Lagomarsino A, Milios E, et al., 2017. Deadwood volume assessment in Calabrian pine (Pinus brutia Ten.) peri-urban forests: Comparison between two sampling methods. J Sust For 36: 666-686. https://doi.org/10.1080/10549811.2017.1345685
De Meo I, Lagomarsino A, Agnelli AE, Paletto A, 2018. Direct and indirect assessment of carbon stock in deadwood: comparison in Calabrian pine (Pinus brutia Ten. subsp. brutia) forests in Italy. For Sci 65: 460-468. https://doi.org/10.1093/forsci/fxy051
Di Cosmo L, Gasparini P, Paletto A, Nocetti M, 2013. Deadwood basic density values for national-level carbon stock estimates in Italy. For Ecol Manag 295: 51-58. https://doi.org/10.1016/j.foreco.2013.01.010
Harmon ME, Sexton J, 1996. Guidelines for measurements of woody detritus in forest ecosystems. Publication No. 20, US LTER Network Office, University of Washington, Seattle.
Herrero C, Monleon VJ, Gómez N, Bravo F, 2016. Distribution of dead wood volume and mass in Mediterranean Fagus sylvatica L. forests in Northern Iberian Peninsula. Implications for field sampling inventory. For Syst 25(3): e069. https://doi.org/10.5424/fs/2016253-09009
Næsset E, 1999. Relationship between relative wood density of Picea abies logs and simple classification systems of decayed coarse woody debris. Can J For Res 14: 454-461. https://doi.org/10.1080/02827589950154159
Norman G, 2010. Likert scales, levels of measurement and the "laws" of statistics. Adv Health Sci Educ 15: 625-632. https://doi.org/10.1007/s10459-010-9222-y
Paletto A, Tosi V, 2010. Deadwood density variation with decay class in seven tree species of the Italian Alps. Scand J Forest Res 25: 164-173. https://doi.org/10.1080/02827581003730773
Paletto A, De Meo I, Cantiani P, Ferretti F, 2014. Effects of forest management on the amount of deadwood in Mediterranean oak ecosystems. Ann Forest Sci 71: 791-800. https://doi.org/10.1007/s13595-014-0377-1
Pan Y, Birdsey RA, Fang J, Houghton R, Kauppi PE, Kurz WA et al., 2011. A large and persistent carbon sink in the world's forests. Science 333: 988-993. https://doi.org/10.1126/science.1201609
QGIS Development Team, 2017. QGIS Geographic Information System. Open Source Geospatial Foundation Project. http://qgis.osgeo.org.
Regional Forest Inventory of Tuscany, 1998. L'inventario forestale. Firenze, Regione Toscana.
Tabacchi G, Di Cosmo L, Gasparini P, Morelli S, 2011. Stima del volume e della fitomassa delle principali specie forestali italiane. Equazioni di previsione, tavole del volume della fitomassa arborea epigea. CREA, Trento, 412 p.
Takahashi M, Ishizuka S, Ugawa S, Sakai Y, Sakai H, Ono K et al., 2015. Carbon stock in litter, deadwood and soil in Japan's forest sector and its comparison with carbon stock in agricultural soils. Soil Sci Plant Nutr 56: 19-30. https://doi.org/10.1111/j.1747-0765.2009.00425.x
Teodosiu M, Bouriaud OB, 2012. Deadwood specific density and its influential factors: A case study from a pure Norway spruce old-growth forest in the Eastern Carpathians. For Ecol Manag 283: 77-85. https://doi.org/10.1016/j.foreco.2012.06.050
Van Wagner CE, 1968. The line intersect method for forest fuel sampling. Forest Sci 14: 20-26.
Warren WG, Olsen PF, 1964. A line-intersect technique for assessing logging waste. For Sci 10: 267-276.
Weggler K, Dobbertin M, Jüngling E, Kaufmann E, Thürig E, 2012. Dead wood volume to dead wood carbon: the issue of conversion factors. Eur J Forest Res 131: 1423-1438. https://doi.org/10.1007/s10342-012-0610-0
Copyright (c) 2022 CSIC_INIA
This work is licensed under a Creative Commons Attribution 4.0 International License.
© CSIC. Manuscripts published in both the printed and online versions of this Journal are the property of Consejo Superior de Investigaciones Científicas, and quoting this source is a requirement for any partial or full reproduction.
All contents of this electronic edition, except where otherwise noted, are distributed under a “Creative Commons Attribution 4.0 International” (CC BY 4.0) License. You may read here the basic information and the legal text of the license. The indication of the CC BY 4.0 License must be expressly stated in this way when necessary.
Self-archiving in repositories, personal webpages or similar, of any version other than the published by the Editor, is not allowed.
