Using stand-scale forest models for estimating indicators of sustainable forest management
Mäkelä, Annikki; Rio, Miren del; Hynynen, Jari; Hawkins, Michael J.; Reyer, Christopher; Soares, Paula; van Oijen, Marcel; Tomé, Margarida. 2012 Using stand-scale forest models for estimating indicators of sustainable forest management. Forest Ecology and Management, 285. 164-178. 10.1016/j.foreco.2012.07.041Before downloading, please read NORA policies.
N019589PP.pdf - Accepted Version
Restricted to NORA staff only until 1 January 2015.
Criteria and indicators (C & I) to evaluate the sustainability of forest management have been proposed by the Ministerial Conference on the Protection of Forests in Europe. Although primarily defined at the national scale, these C & I also have implications at scales ranging from forest stands to the forest management unit. In this paper, we review existing forest growth and ecosystem models from the point of view of applicability to prediction of indicators of sustainable management, focusing on stand scale models and management. To do this, we first present a conceptual framework for understanding the role of models in assessing forest management at the stand level in the context of sustainability criteria and indicators. We classify the criteria into those predictable using models operating at the stand scale, and those derivable either through scaling up or as solutions of a multi-objective management optimisation problem. We conclude that to date, no comprehensive models exist that could be used to predict all the indicators simultaneously. The most promising approach seems to be a modular system where different models are combined and run simultaneously, with shared inputs and well defined mutual links. More modelling efforts are needed especially regarding the state of the soil, including carbon, nitrogen and water balances and physical effects. Models also need development in their ability to deal with heterogeneous stand structures and with non-woody forest products such as berries, mushrooms or cork. The outputs of the models need to be developed in a direction where they can be interpreted in terms of the recreational or biodiversity value of the forest. Data requirements are most pronounced on the same issues as the gaps in model availability. It would be important to consider amending the national forest inventories and other similar standard data collection protocols with variables required for sustainability assessment. Importantly, combining different models in a modular system and with variable data sources requires advanced model parameterisation and evaluation methods and assessment of parameter and model uncertainty. The probabilistic, Bayesian approaches hold a lot of promise in this respect. Predictions using several different models or model systems, with systematic analysis of e.g. inter-model variability, could also be considered.
|Item Type:||Publication - Article|
|Digital Object Identifier (DOI):||10.1016/j.foreco.2012.07.041|
|Programmes:||CEH Topics & Objectives 2009 onwards > Biogeochemistry > BGC Topic 2 - Biogeochemistry and Climate System Processes > BGC - 2.4 - Develop model frameworks to predict future impact of environmental drivers ...|
|Additional Information. Not used in RCUK Gateway to Research.:||This document is the author’s version of a work that was accepted for publication in Forest Ecology and Management. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Forest Ecology and Management, 285. 164-178. 10.1016/j.foreco.2012.07.041 www.elsevier.com/|
|Additional Keywords:||sustainable forest management, criteria and indicators, growth model, forest ecosystem model, model types, data requirements|
|NORA Subject Terms:||Ecology and Environment|
|Date made live:||14 Sep 2012 12:52|
Actions (login required)