scholarly journals Implementing Climate Change and Associated Future Timber Price Trends in a Decision Support System Designed for Irish Forest Management and Applied to Ireland’s Western Peatland Forests

Forests ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 270 ◽  
Author(s):  
Anders Lundholm ◽  
Edwin Corrigan ◽  
Maarten Nieuwenhuis

Research Highlights: Predicting impacts on forest management of Climate Change (CC) and dynamic timber prices by incorporating these external factors in a Forest Management Decision Support System (FMDSS). Background and Objectives: Forest managers must comply with Sustainable Forest Management (SFM) practices, including considering the long-term impacts that CC and the bioeconomy may have on their forests and their management. The aims of this study are: (1) incorporate the effects of CC and Dynamic Prices (DP) in a FMDSS that was developed for Ireland’s peatland forests, (2) analyse the impact of global climate and market scenarios on forest management and forest composition at the landscape level. Materials and Methods: Remsoft Woodstock is a strategic planning decision support system that is widely used for forest management around the world. A linear programming model was developed for Ireland’s Western Peatland forests while using Woodstock. Data from Climadapt, which is an expert-based decision support system that was developed in Ireland, were used to include CC effects on forest productivity and species suitability. Dynamic market prices were also included to reflect the changing demands for wood fibre as part of the European Union (EU) and global effort to mitigate CC. Results: DP will likely have more impact on harvest patterns, volumes, and net present value than CC. Higher assortment prices, especially for pulpwood, stimulate the harvesting of forests on marginal sites and off-set some of the negative CC growth impacts on forest profitability. Conclusions: Incorporating CC and bioeconomy prices in a forest decision support system is feasible and recommendable. Foresters should incorporate the expected global changes in their long-term management planning to mitigate the negative effects that un-informed management decisions can have on the sustainability of their forests.

2020 ◽  
Vol 10 (4) ◽  
pp. 612-619
Author(s):  
P.E. Shumilin ◽  
◽  
V.A. Eremenko ◽  

The digital development of the economy opens up new horizons for accounting. On the one hand, dissolution of accounting in corporate management systems takes place, on the other hand, the accounting functions for managing economic information remain relevant. This article uses the accounting modeling method. We offer a five-blocks accounting model of the decision support system. The model is formed by such blocks as the interface for collecting primary data on company transactions in the context of the formation of financial, managerial, strategic accounting accounts, ETL (extract, transform, loading) of processes for combining credentials from various sources within the framework of a structured work plan of accounts; predicted accounting iterations, having a synergistic, reorganization, reorganization, immunization, hedging and other areas; express audit of the management decision, which consists in assessing the impact of the management decision on the effectiveness of the company, which includes such elements as tax and legal expertise; SWOT analysis; reporting visualization tools that allow you to generate different types of reporting: financial, managerial, statistical, not just in tabular form, but using digital visualization methods; accounting and analytical indicators of managerial decisions, which can be described as a system of indicators reflecting the financial and economic situation of the enterprise under the influence of managerial decisions; the state of its financial stability, profitability, solvency, liquidity; the size of the property of the founders. The introduction and use of this model will allow generating relevant accounting information based on the needs of management, supporting the adoption of management decisions at a scientifically sound level that meets the criteria of business efficiency and protect the interests of owners.


2020 ◽  
Vol 55 (11) ◽  
pp. 1267-1282
Author(s):  
Ramiro Meza-Palacios ◽  
Alberto A. Aguilar-Lasserre ◽  
Luis F. Morales-Mendoza ◽  
José O. Rico-Contreras ◽  
Luis H. Sánchez-Medel ◽  
...  

1991 ◽  
Vol 67 (6) ◽  
pp. 622-628 ◽  
Author(s):  
Dan Bulger ◽  
Harold Hunt

The focus of a decision support system is much different from Management Information Systems (MIS) and data-based "decision support systems". Decision support systems, as defined by the authors, focus on decisions and decision makers, and on information. Technology is treated as a tool and data as the raw material. In many traditional systems the focus is on the technology, and the data is the "information", while decision makers are, to some extent, externalized.The purpose of the Forest Management Decision Support System (FMDSS) project is to develop a set of software tools for creating forest management decision support systems. This set of tools will be used to implement a prototype forest management decision support system for the Plonski forest, near Kirkland Lake, Ontario.There are three critical ingredients in building the FMDSS, these are: (1) knowledge of the decision making process, (2) knowledge of the forest, and (3) the functionality of underlying support technology. The growing maturity of the underlying technology provides a tremendous opportunity to develop decision support tools. However, a significant obstacle to building FMDSS has been the diffuse nature of knowledge about forest management decision making processes, and about the forest ecosystem itself. Often this knowledge is spread widely among foresters, technicians, policy makers, and scientists, or is in a form that is not easily amenable to the decision support process. This has created a heavy burden on the project team to gather and collate the knowledge so that it could be incorporated into the function and design of the system. It will be difficult to gauge the success of this exercise until users obtain the software and begin to experiment with its use.


2020 ◽  
Vol 3 (1) ◽  
pp. 83
Author(s):  
Timothy Thrippleton ◽  
Clemens Blattert ◽  
Reinhard Mey ◽  
Jürgen Zell ◽  
Esther Thürig ◽  
...  

Forest management is becoming increasingly complex due to increasing demands in ecosystem service provisioning and future climate change impacts. For a sustainable forest management, scientifically well-founded decision support is therefore urgently required. Within the project SessFor, a decision support system for strategic planning at the forest enterprise level is being developed, based on the climate sensitive forest model SwissStandSim and initialized from forest inventory data. The system is currently applied to the forest enterprise Wagenrain (440 ha), located in the Swiss Plateau region. Indicators for biodiversity and ecosystem service provisioning (timber production, recreation value and carbon sequestration) are calculated for different management strategies and evaluated using a multi-criteria decision analysis. Preliminary results demonstrate the suitability of the system to evaluate ecosystem service provisioning under different management strategies and to identify the best management strategy, based on criteria defined by the forest manager. Furthermore, results show how the system can be used to assess developments for time-scales of 50–100 years under different climate change scenarios. In the ongoing project, the system will be applied to other case study regions, including mountain forests, which are of key importance in Switzerland and other alpine areas.


2008 ◽  
Vol 84 (5) ◽  
pp. 718-730 ◽  
Author(s):  
Dan Rouillard ◽  
Tom Moore

We describe a pilot project on the Romeo Malette Forest in northeastern Ontario that used a spatially explicit strategic model as an element of the hierarchical modelling process used in forest management planning. We integrated 2 different and slightly overlapping modelling tools, the traditional aspatial Strategic Forest Management Model (SFMM) and the newer spatial Patchworks model, to form a comprehensive decision support system for planning. Results from the conventional modelling approach using only SFMM served as comparison. The pilot project’s goals included satisfying Ontario’s rigorous planning and public consultation requirements, addressing technical issues associated with using 2 separate models, and engaging planning team members in the decision-making process. Implementation of a new technology (spatial modelling) into a highly regulated organizational process presented the planning team with a series of challenges. For example, the higher resolution of the data used for the Patchworks model and changes in conventional concepts and procedures required that the planning team adjust and adapt its approach. One clear advantage of the combined approach was that the long-term effects of spatial and operational adjustments, such as landscape-level policies or harvest block deferrals, were evaluated comprehensively and immediately, leading to greater confidence that the forecast outcomes are sustainable. The hierarchical-spatial modelling process used in this pilot provides a significant improvement to forest management planning and results in improved confidence in the overall sustainability of the long-term management direction. The lessons learned have provided a base for future planning teams to take advantage of the many benefits of a decision support system that includes spatial modelling. Key words: forest management planning, spatial modelling, decision support, Patchworks


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