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Selective logging: do rates of forest turnover in stems, species composition and functional traits decrease with time since disturbance? - A 45 year perspective.
Osazuwa-Peters, Oyomoare L; Jiménez, Iván; Oberle, Brad; Chapman, Colin A; Zanne, Amy E.
Afiliação
  • Osazuwa-Peters OL; Department of Biology, One University Boulevard, University of Missouri Saint Louis, Saint Louis, Missouri, 63121, USA.
  • Jiménez I; Center for Conservation and Sustainable Development, Missouri Botanical Garden, P.O. Box 299 St. Louis, MO 63166.
  • Oberle B; Department of Biological Sciences, 2023 G St. NW, The George Washington University, Washington DC, 20052, USA.
  • Chapman CA; Department of Anthropology and School of Environment, McGill University, Montreal, Quebec, H3A 2T7, Canada, and Wildlife Conservation Society, 2300 Southern Boulevard, Bronx, New York, USA 10460.
  • Zanne AE; Center for Conservation and Sustainable Development, Missouri Botanical Garden, P.O. Box 299 St. Louis, MO 63166 ; Department of Biological Sciences, 2023 G St. NW, The George Washington University, Washington DC, 20052, USA.
For Ecol Manage ; 357: 10-21, 2015 Dec 01.
Article em En | MEDLINE | ID: mdl-26339115
Selective logging, the targeted harvesting of timber trees in a single cutting cycle, is globally rising in extent and intensity. Short-term impacts of selective logging on tropical forests have been widely investigated, but long-term effects on temporal dynamics of forest structure and composition are largely unknown. Understanding these long-term dynamics will help determine whether tropical forests are resilient to selective logging and inform choices between competing demands of anthropogenic use versus conservation of tropical forests. Forest dynamics can be studied within the framework of succession theory, which predicts that temporal turnover rates should decline with time since disturbance. Here, we investigated the temporal dynamics of a tropical forest in Kibale National Park, Uganda over 45 years following selective logging. We estimated turnover rates in stems, species composition, and functional traits (wood density and diameter at breast height), using observations from four censuses in 1989, 1999, 2006, and 2013, of stems ≥ 10 cm diameter within 17 unlogged and 9 logged 200 × 10 m vegetation plots. We used null models to account for interdependencies among turnover rates in stems, species composition, and functional traits. We tested predictions that turnover rates should be higher and decrease with increasing time since the selective logging event in logged forest, but should be less temporally variable in unlogged forest. Overall, we found higher turnover rates in logged forest for all three attributes, but turnover rates did not decline through time in logged forest and was not less temporally variable in unlogged forest. These results indicate that successional models that assume recovery to pre-disturbance conditions are inadequate for predicting the effects of selective logging on the dynamics of the tropical forest in Kibale. Selective logging resulted in persistently higher turnover rates, which may compromise the carbon storage capacity of Kibale's forest. Selective logging effects may also interact with effects from other global trends, potentially causing major long-term shifts in the dynamics of tropical forests. Similar studies in tropical forests elsewhere will help determine the generality of these conclusions. Ultimately, the view that selective logging is a benign approach to the management of tropical forests should be reconsidered in the light of studies of the effects of this practice on long-term forest dynamics.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: For Ecol Manage Ano de publicação: 2015 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: For Ecol Manage Ano de publicação: 2015 Tipo de documento: Article País de afiliação: Estados Unidos