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Modelado de la Ocupación de Fragmentos como Método para el Monitoreo de Cambios en la Florística de Bosques: Un Estudio de Caso en el Sureste de Australia
Author(s) -
PENMAN TRENT D.,
BINNS DOUG L.,
KAVANAGH RODNEY P.
Publication year - 2009
Publication title -
conservation biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.2
H-Index - 222
eISSN - 1523-1739
pISSN - 0888-8892
DOI - 10.1111/j.1523-1739.2008.01146.x
Subject(s) - occupancy , understory , biodiversity , disturbance (geology) , geography , vegetation (pathology) , forest management , scale (ratio) , environmental science , ecology , floristics , adaptive management , environmental resource management , forestry , species richness , cartography , biology , medicine , paleontology , pathology , canopy
The ability to monitor changes in biodiversity is fundamental to demonstrating sustainable management practices of natural resources. Disturbance studies generally focus on responses at the plot scale, whereas landscape‐scale responses are directly relevant to the development of sustainable forest management. Modeling changes in occupancy is one way to monitor landscape‐scale responses. We used understory vegetation data collected over 16 years from a long‐term study site in southeastern Australia. The site was subject to timber harvesting and frequent prescribed burning. We used occupancy models to examine the impacts of these disturbances on the distribution of 50 species of plants during the study. Timber harvesting influenced the distribution of 9 species, but these effects of harvesting were generally lost within 14 years. Repeated prescribed fire affected 22 species, but the heterogeneity of the burns reduced the predicted negative effects. Twenty‐two species decreased over time independent of treatment, and only 5 species increased over time. These changes probably represent a natural response to a wildfire that occurred in 1973, 13 years before the study began. Occupancy modeling is a useful and flexible technique for analyzing monitoring data and it may also be suitable for inclusion within an adaptive‐management framework for forest management.