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Digital Forestry has been proposed as "the science, technology, and art of systematically acquiring, integrating, analyzing, and applying digital information to support sustainable forests." Although rooted in traditional forestry disciplines, Digital Forestry draws from a host of other fields that, in the past few decades, have become important for implementing the concept of forest ecosystem management and the principle of sustainable forestry. Digital Forestry is a framework that links all facets of forestry information at local, national, and global levels through an organized digital network. It is anticipated that a new set of principles will be established when practicing Digital Forestry concept for the evolution of forestry education, research, and practices as the 21st century unfolds.

There are increasing evidences that recruitment of trees might be endangered through events such as climate change, enhanced seed predation or fragmentation. In addition, continuing logging in the tropics is making the conservation of remaining forests increasingly difficult In this study we assess various impacts of recruitment shortage and tree harvesting in a tropical rain forest in Sabah, Malaysia. 56 different scenarios using the process-based forest growth model Formind2.0 were assessed. Formind2.0 is based on the calculations of the carbon balance of individual trees belonging to 13 different plant functional types. Reduced recruitment led to shifts in the abundances of species, to species loss, and to forest decline and dieback.. Reduced-impact logging methods were compared with conventional logging methods.

Sixty-four different logging scenarios for an initially undisturbed forest stand at Deramakot (Malaysia) were simulated with rain forest growth model FORMIND. The scenarios differ regarding the logging cycle, logging method, cutting limit and logging intensities. We characterise the impacts with four criteria describing the yield, canopy opening and changes in species composition. Multicriteria decision analysis was used to evaluate the scenarios and identify the efficient ones. Our results plainly show that reduced-impact logging scenarios are more 'efficient' than the others, since in these scenarios forest damage is minimised without significantly reducing yield. Nevertheless there is a trade-off between yield and achieving a desired ecological state of logged forest; the ecological state of the logged forests can only be improved by reducing yields and enlarging the logging cycles. Our study also demonstrates that high cutting limits or low logging intensities cannot compensate for the high damage caused by conventional logging techniques.