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Investigating the effect of selective logging on tree biodiversity and structure of the tropical forests of Papua New Guinea

Riccardo Testolin (1)   , Simon Saulei (2), Alessio Farcomeni (3), Giorgio Grussu (1-4), Cossey Yosi (2), Michele De Sanctis (4), Fabio Attorre (4)

iForest - Biogeosciences and Forestry, Volume 9, Issue 3, Pages 475-482 (2016)
doi: https://doi.org/10.3832/ifor1732-008
Published: Jan 25, 2016 - Copyright © 2016 SISEF

Research Articles


Unsustainable exploitation of tropical forest resources is raising worldwide concern. In Papua New Guinea (PNG) timber harvesting has been identified as a major contributor to deforestation and forest degradation but its impact on biodiversity is still poorly understood. In this study we investigated the effect of selective logging on tree taxonomic composition, structure and diversity of PNG forests. We used data from 101 one-hectare permanent sample plots (PSPs) belonging to two vegetation types: low altitude forests on plains and fans (type P) and low altitude forests on uplands (type H). We used multivariate techniques to test for significant differences in species composition between plots of different vegetation types and disturbance regimes, identifying the tree taxa to which these differences could be ascribed. ANOVA was used to test for differences between logged-over and unlogged forest PSPs with respect to biodiversity (richness, Shannon’s diversity, Pielou’s evenness) and stand structure (stem density, basal area - BA). Temporal trends of forest features were analyzed using linear regression. Significant differences in taxonomic composition were found between logged-over and unlogged plots of the H type (p = 0.04). No differences were found in richness, diversity and evenness between logged-over and unlogged forest plots, while stem density was higher in the latter (421 ± 153 stems ha-1). Greater BA was found in unlogged forests (30.28 ± 4.45 m2 ha-1) of the H type when compared to the logged-over stands (15.52 ± 4.04 m2 ha-1). We detected positive trends in richness (0.55 ± 0.19 taxa ha-1 yr-1) and diversity after logging. Furthermore, H type forest exhibited positive trends in stem density (9 ± 1 stems ha-1 yr-1) and BA (0.42 ± 0.06 m2 ha-1 yr-1) with elapsed time since harvesting. Our analysis highlights some significant effects of logging activities on biodiversity and structure of PNG forests. Additionally, forests exhibited a significant recovery with respect to richness, diversity and stand structure. These preliminary results will be compared with data collected by the forthcoming National Forest Inventory in order to assess and monitor the effects of human activities and ecological factors on PNG forest biodiversity and develop appropriate conservation measures and sustainable management strategies.

  Keywords


Selective Logging, Biodiversity, Basal Area, Papua New Guinea, Multivariate Analysis, National Forest Inventory, Permanent Sample Plots, REDD+

Authors’ address

(1)
Riccardo Testolin
Giorgio Grussu
Food and Agriculture Organization of the United Nations, v.le delle Terme di Caracalla, I-00153, Roma (Italy)
(2)
Simon Saulei
Cossey Yosi
Papua New Guinea Forest Research Institute, P.O. Box 314, Lae 411, Morobe Province, Papua (New Guinea)
(3)
Alessio Farcomeni
Department of Public Health and Infectious Diseases, “Sapienza” University of Rome, p.le Aldo Moro 5, I-00185 Roma (Italy)
(4)
Giorgio Grussu
Michele De Sanctis
Fabio Attorre
Department of Environmental Biology, “Sapienza” University of Rome, p.le Aldo Moro 5, I-00185 Roma (Italy)

Corresponding author

 
Riccardo Testolin
riccardo.testolin@gmail.com

Citation

Testolin R, Saulei S, Farcomeni A, Grussu G, Yosi C, De Sanctis M, Attorre F (2016). Investigating the effect of selective logging on tree biodiversity and structure of the tropical forests of Papua New Guinea. iForest 9: 475-482. - doi: 10.3832/ifor1732-008

Academic Editor

Gianluca Piovesan

Paper history

Received: Jun 05, 2015
Accepted: Nov 01, 2015

First online: Jan 25, 2016
Publication Date: Jun 01, 2016
Publication Time: 2.83 months

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