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In this page, more details are given of the areas in which submissions are
invited. If in doubt about the suitability of a submission, please contact the
Editor.
Articles are expected to be explicitly concerned with issues relating to forests or trees, processes in forests or trees, populations associated with forests or trees, the forest environment, and the social and economic impact of forests on human communities. This wide range of potential application areas is referred to below, briefly, as "forests".
There are several types of article that are welcomed. These
main types are following:
 | Articles which report original research and development of new mathematical, statistical or computing models or techniques which arise from forestry problems or contexts. |
| Articles discussing general methodological issues
that are related to use of Biometric, Modelling or Information Systems in
forestry. |
| Articles which present a meta-analysis of the models
or results of previous studies. |
However, authors who have articles that do not fall
into these types, but who think they are within the remit of FBMIS are welcome
to submit them.
The main methodological themes of FBMIS, as indicated in the title of the journal are:
| Forest Biometry, which includes
(i) Data collection methods:
Measurement, Mensuration and Remote
Sensing: theory relating to the use of instruments or the
analysis and interpretation of data resulting from the use of them.
Experiments: novel planned investigations of the
influence of controlled management treatments and environmental variables
and factors.
Sampling and Inventory: for the collection of tree or
forest data, or data relating to processes and populations that occur within
forests. New methods of design or analysis, or novel applications of
standard techniques.
(ii) Biometrics: A vast disciplinary area,
overlapping all other methodological themes of the FBMIS (and some would
argue, including them), but summarized here as the use of Statistical methods to analyze, summarize and
interpret forest data.
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| Forest Modelling, which includes use of
Mathematical, Statistical, Stochastic and Computer Software models to
represent the structure and processes occurring in the forest, and the use
of statistical methods for fitting such models to forest data. Models
need not necessarily be statistical in nature, and consequently data-fitting
of the model is not required, though of course desirable. Forest
Growth and Yield Models are a major application area, but models of animal
populations in forests, of the spread of disease or fire through a forest,
or any other forest process are welcomed. Models for the investigation
of the impact of forests on the economic and social welfare of human
communities dependent of forests, particularly in the developing world are
sought. Similarly articles with models relating to forest
Biodiversity, and its conservation and management, are invited. |
| Forest Information Sciences, which include
techniques for the storage, warehousing and archiving of data, metadata and
information, and its management for the purposes of analysis, modelling, knowledge extraction and the building of Forest Management Information and
Decision Support Systems. |
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