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Key processes of the forest model are mortality, productivity and regeneration.
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Multi-layer perception neural network (MPNN) models were adopted to evaluate the influence of independent variables in the process of the forest transition.
Thus, the importance of including this group of people in the process of the forest restoration that will occur in the region is emphasized because they possess information about the past vegetation changes and their causes.
A simultaneous equations model was established and the significance ranking of various factors was obtained in order to analyze the driving mechanism of the spatial-temporal process of the forest land.
However, the feasibility of such a drying process for the forest industry also depends on the cost of building and operating appropriate drying facilities.
Comparing the phylogeographical patterns of two types of phytophagous insects (i.e., a generalist seed predator living in both the cool and warm temperate zones and the host-specific seed predator living only in the warm temperate zone) and of several plant species growing in these temperate zones of Japan enabled us to specify the historical processes of these forests more precisely.
GEMS automates the processes of downscaling forest ages from the USDA Forest Inventory and Analysis data (FIA), crop compositions from the Agricultural Census, grass cover distribution and temporal changes from the remotely sensed imagery interpretation.
This break-up of Fe contiguous films into nanoparticles is suppressed by other effects such as Ostwald ripening processes at the forest growth temperature of 780 °C.
The resulting maps of vegetation structure at five time periods from 1945 to present gave new insights into the ecological processes of secondary forest succession.
Remotely sensed information on the spatial extent and intensity of forest disturbance would be extremely useful for managers and ecologists in attempts to develop a mechanistic understanding of forest degradation and the processes of forest disturbance [7, 8].
Remotely sensed information on the spatial extent and intensity of forest disturbance would be extremely useful for managers and ecologists in attempts to develop a mechanistic understanding of forest degradation and the processes of forest disturbance [ 7, 8].
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