Forest Management Decision Support Systems Research Articles

PRISM: A decision support system for forest planning

PRISM, a new forest management decision support system, was developed for United States national forest planning at the same time existing tools were deprecated. PRISM has a friendly graphical user interface to facilitate model development, database management, sensitivity analysis, and data visualization. It integrates SQLITE engine for database storage and exploration. It supports both classic forest planning Model I and II to schedule management activities and achieve multiple management objectives through the lifecycle of a forest plan. Multiple models may be created through the PRISM interface and solved in batch mode for convenient sensitivity analysis. Various options to visualize model outputs are available through the embedded JFREECHART library. The open-source nature of PRISM makes it free to use and allows for long-term software development and collaboration. This paper presents the architecture, core functionality, and selected applications of PRISM in the United States national forest planning.

Exploring the effects of management intensification on multiple ecosystem services in an ecosystem management context

Understanding forest dynamics under varying management intensification is a crucial step for designing and implementing sustainable forest management scenarios. One way to assess the sustainability is to evaluate the long-term supply of ecosystem services (ES) with some performance indicators. This research focuses on exploring the effects of management intensification on several ESs such as habitat for biodiversity conservation, wood production, carbon stock, cultural values, water provision and soil protection. Forest development was simulated over time with the ETCAP forest management decision support system (DSS) to investigate the effects of intensified forest management activities, representing different treatment rates, rotation periods and afforestation levels, on the selected ecosystem services. Hamidiye forest planning unit was used as a case study area with 19,009 ha forests in southeastern Turkey.The management scenarios with intensified forest interventions such as high rate of thinning and afforestation areas with medium rotation ages led to increased harvest level, carbon storage, soil protection, deadwood and forest area, and reductions in largest stand volume, understory, basal area, ground water and cultural values. The same intensified scenarios with short rotation ages, however, resulted in again higher harvest levels, yet a more regulated forest structure due mainly to the increasing afforestation areas and productivity. Extension of rotation periods, however, appear to have marginal impact on carbon storage, positive effect on soil protection and significant effect on harvest level. Scenarios with low intensified interventions only resulted in high values of biodiversity conservation and cultural values. Intensive treatments and larger afforestation areas had significant impact on the overall results. Overall, the analysis of the modeling approach with varying management scenarios led to better and wider understanding of forest development over time by allowing the assessment of the impacts of management interventions on the sustainable supply of the ecosystem services that highly depend on the afforestation level, thinning rate and rotation period.

A Compromise Programming Application to Support Forest Industrial Plantation Decision-Makers

The conflicts that arise between natural resources consumption and the desire to preserve them make the multicriteria decision theory necessary. Brazil, one of the 10 largest timber producers globally, uses optimization models that represent the growth of forests integrated with decision support systems. Brazilian forest plantation managers often face conflicts when continuously seeking efficiency gains (higher productivity at lower costs) and efficacy (higher profits with minimum social and environmental impacts). Managers of leading producing countries on timber, pulp, and fiberboard constantly interact to fine-tune industry processing demands vis-a-vis the demands of highly productive fast-growing forest plantations. The decision process in such cases seeks a compromise that accommodates short-term industry productivity optimization and long-term forestry production capacity. This paper aims to apply a forest management decision support system (FMDSS) to a case study that represents the challenges that industrial plantations in Brazil usually face. A vertically integrated pulp company situation was simulated to provide a real scenario. In this scenario, forest managers tend to shorten the rotations due to Brazil’s usually high-interest rates; meanwhile, industrial managers tend to ask for longer ones due to the positive correlation between age and wood density. Romero®, a Forest Management Decision Support System, developed by following the multi-criteria decision theory, was used to process the case study. Expressly, the hypothesis that mill managers initially have, that older ages rotation could improve mill production, was not confirmed. Moreover, mill managers lean towards changes in the short term, while the case study shows that changes in rotation size and genetic material take time, and decisions have to be made involving both interests: forest and mill managers.

The need for an understory decision support system for temperate deciduous forest management

Numerous decision-makers have an interest in how forest biodiversity and functioning will alter under environmental change. These decision-makers may have varied motivations underlying their management response to environmental change by focusing on contrasting management challenges and targets. Decision-makers may use different tools to aid their decision-making when facing uncertainty. We specifically investigate whether decision-makers in forest management across Europe consider the understory (i.e. herbaceous layer) in decision making, as this component constitutes the vast majority of floral biodiversity in temperate forests, and has an important functional role. To address this question, we distributed an online questionnaire to more than 800 forest management decision-makers across Europe, and received 100 completed responses. We assess what objectives drive management decisions, and whether these are consistent depending on respondents’ occupations. Interestingly, regardless of respondent profile, biodiversity loss and climate change are expected to permeate management decisions in the coming decades, motivated primarily by a sense of environmental protection. Priority management targets did not vary across respondent profiles (i.e. occupation) either, and focused on biodiversity values, adaptation and mitigation to climate change, and forest regeneration. The majority of respondents identified the understory as an “Important” target for forest management decisions. Respondents used a mix of personal experience and literature sources to base management decisions on, while infrequently using recognised decision support systems (DSS). No utilised system considered the understory at the moment. Indeed, our review of available forest management DSS, conducted in parallel to the questionnaire, shows that an understory DSS tool, especially one that can consider changing socio-environmental conditions, is lacking for decision-makers. Based on (1) forest management decision-makers’ wide concern around biodiversity loss, climate change and forest regeneration, (2) the known functional role of temperate forest understories, and (3) an apparent lack of existing DSS with an understory component, we identify the requirement for an agile tool that accounts for understory dynamics. Such a tool, especially when integrated into existing DSS, will strongly support decision-makers in their quest to attain more biodiverse, functional and resilient forests for the future.

Evaluation of Forest Industry Scenarios to Increase Sustainable Forest Mobilization in Regions of Low Biomass Demand

There is an increasing interest in forest biomass for energy throughout Europe, which is seen as a way of promoting forest mobilization and economic development locally, in particular in regions where forest biomass is available but its use is limited by lack of demand. This study was conducted to define, evaluate and select viable forest industry scenarios to increasing forest mobilisation in the North of Portugal using AppTitude®, a Forest Management Decision Support Systems (FMDSS) considering spatially explicitly supply (biomass growth and yield), demand (industry), and supply–demand interactions (markets). The protocol followed combined a set of indicators of sustainable forest management to guide the selection of the best industry solutions in terms of location, dimension, forest biomass and other variables defined as objectives. The simulations allowed the selection of a small set of industry scenarios compatible with an existing plant outside the study area, increasing wood mobilization, preventing overexploitation and competition among industries but increasing value and price of forest biomass. The results of the application of this FMDSS showed that introducing new biomass plants in the region will increase sustainable forest mobilization and related local development. AppTitude® revealed to be a powerful and reliable tool to assist forest planning.

Evaluating the Impact of Future Global Climate Change and Bioeconomy Scenarios on Ecosystem Services Using a Strategic Forest Management Decision Support System

Sustainable Forest Management (SFM) has become an important pillar of modern forest management, and one way to evaluate the sustainability of forestry is to assess long-term supply of ecosystem services (ESs) indicators. The concept of sustainability also has come to include adapting to climate change and the associated dynamic timber markets. This study aims to: 1) incorporate several ESs indicators in a Forest Management Decision Support System (FMDSS) that can deal with climate change and dynamic timber markets; and 2) analyse the impact that intensified forest management, resulting from global change scenarios that represent different levels of climate change mitigation efforts, will have on forest ES indicators in the west of Ireland. A linear programming model that optimized Net Present Value (NPV) from mill-gate sales was previously developed in Remsoft Woodstock, a DSS framework used for strategic forest planning around the world. This Woodstock model was modified to include the effects of global scenarios that include climate change and dynamic timber prices. This model was further developed to include indicators for five ESs (carbon storage in the forest as well as in harvested wood products and carbon substitution, windthrow risk, biodiversity, water quality, and cultural values), to assess the impacts of these global scenarios on the forest landscape and the sustainability of forest management. The ES indicator values were mainly linked to forest age, forest type, and yield tables, and their inclusion in the FMDSS had almost no impact on total model run times. Intensified forest clearfelling, as a result of increasing timber prices associated with most global scenarios, led to increased phosphor emissions to waterbodies, and reductions in windthrow risk and carbon storage. The global scenarios only resulted in minor differences in the indicator values for biodiversity and cultural values. Besides the global scenarios, recent forest policy development and the poor soil conditions in the study area impacted on the results. The developed system, with its innovative method to incorporate climate change and associated market dynamics, could be applied to other forest landscapes in Ireland and Europe, or indeed by any forest company or organisation that uses Remsoft Woodstock.

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

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.

Decision Support Approaches in Adaptive Forest Management

Climate and social changes place strong demands on forest managers. Forest managers need powerful approaches and tools, which could help them to be able to react to the rapidly changing conditions. However, the complexity of quantifying forest ecosystems services as well as the complexity of current decision theories, technologies and operation research methods, complicate the creation of one general tool. The continuous research and development in this area is an indispensable part of the success of adaptive management as well as the sharing of knowledge and information between research teams around the world. The Community of Practice of Forest Management Decision Support Systems provides a platform for broad discussion among scientists, researchers as well as forest professionals. This special issue provides papers which resulted from a conference session of the International Union of Forest Research Organizations’ (IUFRO) 125th Anniversary Congress in Freiburg, Germany in 2017. The joint sessions and other meetings (and resulting publications) are appropriate opportunities for knowledge sharing on these important methods and systems for protecting and managing forest ecosystems in the future.

Research and construction of web crawler based forest management knowledge collection system.

Accurate Internet access to forest management information can be obtained through the construction of a data collection system for forest management. Based on an analysis of the data collection, system process, system module and database were designed, rules governing web crawlers were improved and delimited, and workflow and algorithm of web crawlers were explored. This system summarized and analyzed the characteristics observed from webpages featuring forest management, and served to identify those collected data contents with an eigenvector of forest management. Information about forest management was also denoised by this system; information was extracted through intelligence match, and repeated information about forest management was eliminated through fingerprint recognition by Euclidean distance. The experiment results indicated that this data collection system for forest management featured high subject relevance, high accuracy, and low repetition rate. Therefore, it can satisfy the need of the forest management decision support system.

Explicating behavioral assumptions in forest scenario modelling – the behavioral matrix approach

Forest landscapes are too complex systems for the actors involved in policy making, including experts, to predict the consequences of different management options and policy measures without the aid of modelling tools. Forest sector models and forest management Decision Support Systems (DSS) are two major types of modelling tools that can be used for providing model-based support to forest policy development. Regardless of the modelling tool, policy makers and other concerned actors need to be aware of the behavioral assumptions, or implications, of a scenario in order to proceed to an assessment of what it takes to achieve, alternatively avoid it. A unified method or even a unified understanding of this problem is as yet lacking among forest scenario analysts. This paper presents an approach to facilitate the definition and communication of behavioral assumptions, primarily in DSS-based forest scenario modelling. At the core of the approach is the Behavioral Matrix (BM), a way of structuring forest management specifications. A case study in southern Sweden is presented as an example.

The Use of Decision Support Systems in Forest Management: Analysis of FORSYS Country Reports

From 2009 to 2013, a group of more than 100 researchers from 26 countries, under a COST-Action project named FORSYS, worked on a review of the use of forest management decision support systems (FMDSS). Guided by a template, local researchers conducted assessments of FMDSS use in their countries; their results were documented in Country Reports. In this study, we have used the Country Reports to construct a summary of FMDSS use. For the purposes of our analysis, we conducted a two-round categorisation of the main themes to describe the most relevant aspects of FMDSS use. The material produced was used to generate quantitative summaries of (i) the types of problem where FMDSS are used, (ii) models and methods used to solve these problems, (iii) knowledge management techniques, and (iv) participatory planning techniques. Beyond this, a qualitative analysis identified and summarised the local researchers’ primary concerns, recorded in the conclusions to the Country Reports; we designated these “lessons learned”. Results from the quantitative analysis suggested that most of the participant countries were making use of latest generation FMDSS. A few did not have practical problems that justified the use of such technology or they were still at the beginning of the process of building models to solve their own forest problems.

Decision Support for the Provision of Ecosystem Services under Climate Change: An Editorial

The Special Issue “Providing Ecosystem Services under Climate Change: Community of Practice of Forest Decision Support Systems” is based on the presentations given at the 24th World Congress of the International Union of Forest Research Organizations and provides an overview on Forest Management Decision Support Systems currently designed and applied for the sustained provision of ecosystem services within the context of climate change. The contributions provide an overview on models, methods, techniques used in decision support and the proposed frameworks to support decision making. With populations and economies growing worldwide, the demands on forest resources increase, and sustaining the supply of ecosystem services becomes crucial. Through growing public participation in decisions regarding the management of natural resources, new demands have emerged for tools that support our understanding of environmental issues, and for the development and evaluation of alternative management options; there is a desire to project the consequences of different courses of action. Decision Support Systems (DSS) have been proven to solve such ill-structured decision problems by integrating database management systems with analytical and operational research models, thus providing various reporting capabilities. Several case studies focus on decision problems, the development and evaluation of alternative management options, and on projecting the consequences of different courses of action in the provision of ecosystem services. Conclusions on the state-of-the-art in decision support and the needed advances in research are drawn.

A Review of Recent Forest and Wildland Fire Management Decision Support Systems Research

This is a review of recent efforts to develop and implement forest and wildland fire management decision support systems (FMDSS) that fire managers can use to enhance their management of their fire suppression activities. Fire managers need to resolve complex decisions associated with fuel management, fire prevention, detection, the suppression of potentially destructive wildfires and the use of prescribed fire to achieve an appropriate balance between the beneficial and detrimental social, economic and ecological impacts of fire on flammable landscapes, often under considerable uncertainty. This review focuses on the use of operational research and management science (OR/MS) methods to address their suppression resource management decision support needs.

Outlook for the Next Generation’s Precision Forestry in Finland

During the past decade in forest mapping and monitoring applications, the ability to acquire spatially accurate, 3D remote-sensing information by means of laser scanning, digital stereo imagery and radar imagery has been a major turning point. These 3D data sets that use single- or multi-temporal point clouds enable a wide range of applications when combined with other geoinformation and logging machine-measured data. New technologies enable precision forestry, which can be defined as a method to accurately determine characteristics of forests and treatments at stand, sub-stand or individual tree level. In precision forestry, even individual tree-level assessments can be used for simulation and optimization models of the forest management decision support system. At the moment, the forest industry in Finland is looking forward to next generation’s forest inventory techniques to improve the current wood procurement practices. Our vision is that in the future, the data solution for detailed forest management and wood procurement will be to use multi-source and -sensor information. In this communication, we review our recent findings and describe our future vision in precision forestry research in Finland.

Studying the use of forest management decision support systems: an initial synthesis of lessons learned from case studies compiled using a semantic wiki

In order to share information on the development and use of forest management decision support systems (FMDSS), a European-initiated network has established a wiki website as part of its activities. Case studies and associated lessons learned were solicited from the network using semantic structures built on the wiki. A total of 31 cases from 10 different countries and 80 associated lessons were entered into the wiki. The resulting lessons were categorized (non-exclusively) using four major themes: (1) decision support system architecture and design (40 lessons), (2) methods and models (26), (3) knowledge management processes (34) and (4) participatory processes (32). The semantic wiki proved useful for gathering case information and relating it to other information objects, such as FMDSS software descriptions; however, it was not as well suited to the task of analysis and synthesis as commercial qualitative analysis software packages. Future development possibilities for the semantic structures are suggested, and more cases are solicited from the FMDSS community.

Challenges in developing and implementing a decision support systems (ETÇAP) in forest management planning: a case study in Honaz and Ibradı, Turkey

Decision support systems (DSSs) are indispensable tools in preparing a forest management plan for a better combination of multiple forest values. This study attempted to develop and explain a stand-based forest management DSS (Ecosystem-based multiple-use forest planning [ETÇAP]) comprising a traditional simulation, linear programming (LP), metaheuristics and geographic information system. The model consists of five submodels; traditional management approach to handle inventory data, an empirical growth and yield model, a simulation to conceptualize management actions, a LP technique to optimize resource allocation and a simulated annealing approach to directly create a spatially feasible harvest schedule. The ETÇAP model has been implemented in a comparative two case study areas; Denizli–Honaz and Akseki–Ibradı. Both simulation and optimization models outperformed to the traditional management plan. The periodical change of growing stock, allowable cuts, carbon sequestration and water production are used as performance indicators. The results showed that more amount of wood could be harvested over time compared to traditional level of harvesting. It could be concluded that various management strategies allowed managers to stimulate more decision options for better outputs through intertemporal trade-offs of management interventions as the model provided tools to quantify forest dynamics over time and space. Challenges exist to establish the functional relationships between forest structure and values for better quantification and integration into the management plans.

Review. A brief overview of forest management decision support systems (FMDSS) listed in the FORSYS wiki

Aim of study. The aim of the study was to overview forest management decision support systems (FMDSS) listed in the FORSYS wiki in terms of software design and architecture.Area of study. A total of 62 FMDSS from 23 countries were included into the study.Material and methods. First, all FMDSS listed in the FORSYS wiki were described in terms of functionalities, typologies and elements of architecture. Thereafter, the findings were compared with the desired architectural features of FMDSS to identify success or potential gaps. Finally, some measures were suggested to improve knowledge transfer and smooth integration of system components.Main results. Most of the systems listed in the FORSYS wiki originate from research projects and are either knowledge- or model-driven. There are only few compound systems or tools that can be used as sub-components in integrated systems.Research highlights. There is a lack of generic platforms or DSS generators that would facilitate construction of integrated systems. Further efforts are needed to study the potential of cloud services. Keywords: forest management; decision support systems; software architecture; typologies.

Empirical guidelines for forest management decision support systems based on the past experiences of the expert's community

Aim of the study: Decision support systems for forest management (FMDSS) have been developed world wide to account for a broad range of forest ecosystems, management goals and organizational frameworks (e.g. the wiki page of the FORSYS project reports 62 existing FMDSSs from 23 countries). The need to enhance the collaboration among this diverse community of developers and users fostered the rise of new group communication processes that could capture useful knowledge from past experiences in order to efficiently provide it to new FMDSS development efforts.Material and methods: This paper presents and tests an exploratory process aiming to identify the empirical guidelines assisting developers and users of FMDSS. This process encompasses aDelphi survey built upon the consolidation of the lessons-learned statements that summarize the past experiences of the experts involved in the FORSYS project. The experts come from 34 countries and have diverse interests, ranging from forest planners, IT developers, social scientists studying participatory planning, and researchers with interests in knowledge management and in quantitative models for forest planning.Main results: The proposed 37 empirical guidelines that group 102 lessons-learned cover a broad range of issues including the DSS development cycle, involvement of the stakeholders, methods, models and knowledge-based techniques in use.Research highlights: These results may be used for improving new FMDSS development processes, teaching and training and further suggest new features of FMDSS and future research topics. Furthermore, the guidelines may constitute a knowledge repository that may be continuously improved by a community of practice.Keywords: Forest management; guidelines; guidelines definition process; lessons learned; decision support systems; system architecture; knowledge management; participatory planning; Delphi.

Distribution modelling of Japanese honeysuckle ( Lonicera japonica) invasion in the Cumberland Plateau and Mountain Region, USA

Predicting the potential distribution of invasive plants within a specific region is pivotal to planning effective management but is challenged by attempting to model expanding populations that are rarely at equilibrium with their environment. We adopt an ensemble modelling approach to assess the potential distribution of Japanese honeysuckle ( Lonicera japonica), a vine invasive to forests of the Cumberland Plateau and Mountain Region in the southeast of USA. The influence of disturbance, spatial and temporal heterogeneity and other landscape characteristics were assessed by creating regional level models based on occurrence records from the United States Department of Agriculture, Forest Service, Forest Inventory and Analysis (FIA) database. Logistic regression and maximum entropy (MaxEnt) models were assessed independently and evaluated as predictive tools to test the value of presence/absence and presence only data in predicting species distributions. Ensemble models were also developed that combined the predictions of the two modelling approaches to obtain a more robust prediction. While logistic and MaxEnt models were similar in their predictive ability and dominant input variables, the ensemble approach derived the best fitting model overall. The regional distribution of Japanese honeysuckle was influenced greatly by environmental conditions such as elevation, slope, and temperature with anthropogenic activity having significant, though lesser, influence. The ensemble models predict that Japanese honeysuckle has nearly reached its potential distribution. However, given the critical role of minimum temperature on Japanese honeysuckle distribution, future occupancy at higher elevations is likely to increase since January temperatures for this region are predicted to rise by 1–4 °C over the next 100 years. The models also give some indication of the likely effect of land cover change on its distribution. Japanese honeysuckle tended to be associated with a high component of farming or low component of forest within the local neighbourhood. This suggests disturbed forest and/or high fragmentation has a higher invasion potential and given past trends and expected continued population growth this disturbance and fragmentation will only increase. The models can be integrated into forest management decision support systems and assist in the development of long term management plans, integrating the impact of potential climate and land cover change scenarios.

Biophysical sustainability, process-based monitoring and forest ecosystem management decision support systems

Sustainability is a key concept in resource management and environmental issues, but implementation is fraught with difficulty due to lack of agreement as to what it means. Because of the ubiquity of disturbance, ecosystem sustainability inevitably involves change. We define stand-level biophysical sustainability as non-declining patterns of change over at least three cycles of disturbance, and landscape-level sustainability as a shifting mosaic of non-declining stand change, the overall character of which remains within acceptable limits over time. Simple empirical assessment (i.e., monitoring) of this concept of sustainability is generally not practical in forestry because of the long time and large spatial scales involved. Adaptive management (AM), another key resource management concept, involves monitoring to assess the consequences of management actions. It requires forecasts of expected change in sustainably managed, post-disturbance ecosystems against which to assess monitoring data. Without these forecasts, which constitute temporal fingerprints of sustainable change, short-term monitoring data cannot be used reliably as a basis from which to assess longer-term sustainability. A comprehensive monitoring system to address biophysical sustainability locally and at the landscape scale for a large management unit over a rotation-length time scale would involve the key elements of ecosystem structure and function and the effects thereon of management and climate change. This would be prohibitively expensive and demanding of human resources and the results would not be available until the end of the rotation. A strategy that honours the intent of AM is an intimate linkage between predictive monitoring and process-based ecosystem management decision support systems—ecosystem process-based monitoring—the emphasis of which is on temporal patterns of indicator change rather than comparisons between static indicators and audits of current ecosystem conditions (the certification approach). It involves a combination of monitoring and ecosystem management modeling that reduces the long-term cost of monitoring and increases the utility of the data collected for the assessment of sustainability and for the design of policy and adaptive practice in forestry. Key words: prediction, process-based monitoring, sustainability, forest ecosystems, biophysical indicators, temporal fingerprints, adaptive management, ecosystem management models