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Over our study period, deforestation resulted in an additional ∼3000 km2 of edge-forest, whereas logging generated ∼20,000 km2, as it extended deep into intact forest areas.
Most indicator species identified were saproxylic and associated with unsalvaged stands, suggesting salvage logging generated the largest changes to the original ecosystem while additional effects of the silvicultural treatments were less pronounced.
Annually, deforestation and logging generated ∼32,000 and 38,000 km of new forest edge while increasing the edge-to-area ratio of remaining forest by 0.14 and 0.15, respectively.
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Illegal logging generates $10-15bn 10-15bn £7.5-11bnd the world, according to new analysis from the World Bank.
Estimates suggest that illegal logging generates approximately US$10-15 billion annually worldwide.
When logging generates net revenues, but burned pine provide a more valuable habitat (top-right quadrant), Eq. 8 will be satisfied (not satisfied) and favor choice 1 (2) when: the value of W is small (large); net revenues from logging, L − R, are large (small); and/or the survival rate advantage of burned pine over aspens is small (large).
For instance, when (L− R) is positive (i.e., logging generates enough revenue to cover all of the restoration expenses) and aspens are a more valuable habitat than burned pine, then there is no trade-off between the revenue (VAct) and the ecological (VBird) outcomes, thus favoring choice 1 (top-left quadrant).
The logs generated by such systems can therefore reveal telling details about network activity.
The log generated by the authorisation service is a great place to get an overview of which people or services had access to a given resource at a given time.
Open image in new window Fig. 7 Petrophysical logs generated for the F-sand reservoir.
Visualization could be fully leveraged to better understand via step-by-step data logs generated by learning environments.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com