scholarly journals The Human Dimensions of Spatial, Pre-Wildfire Planning Decision Support Systems: A Review of Barriers, Facilitators, and Recommendations

Forests ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 483
Author(s):  
Melanie Colavito
Keyword(s):  
Risk Assessment ◽  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
The United States ◽  
Human Dimensions ◽  
Wildfire Risk ◽  
Forest Fuels ◽  
Fuels Treatment ◽  
Wildfire Planning

Decision support systems (DSSs) are increasingly common in forest and wildfire planning and management in the United States. Recent policy direction and frameworks call for collaborative assessment of wildfire risk to inform fuels treatment prioritization using the best available science. There are numerous DSSs applicable to forest and wildfire planning, which can support timely and relevant information for decision making, but the use and adoption of these systems is inconsistent. There is a need to elucidate the use of DSSs, specifically those that support pre-wildfire, spatial planning, such as wildfire risk assessment and forest fuels treatment prioritization. It is important to understand what DSSs are in use, barriers and facilitators to their use, and recommendations for improving their use. Semi-structured interviews with key informants were used to assess these questions. Respondents identified numerous barriers, as well as recommendations for improving DSS development and integration, specifically with respect to capacity, communication, implementation, question identification, testing, education and training, and policy, guidance, and authorities. These recommendations can inform DSS use for wildfire risk assessment and treatment prioritization to meet the goals of national policies and frameworks. Lastly, a framework for organizing spatial, pre-wildfire planning DSSs to support end-user understanding and use is provided.

scholarly journals Feasibility of using existing web services for on-demand data access within distributed environmental decision support systems

2017 ◽  
Vol 20 (2) ◽  
pp. 263-280
Author(s):  
Stuart F. Sheffield ◽  
Jonathan L. Goodall ◽  
Mohamed M. Morsy ◽  
Alexander B. Chen
Keyword(s):  
Decision Support ◽  
Web Services ◽  
Decision Support Systems ◽  
Support Systems ◽  
Response Times ◽  
Data Access ◽  
The United States ◽  
Environmental Data ◽  
Project Area ◽  
On Demand

Abstract Web services providing machine-accessible interfaces to environmental data are now commonplace. Building on this, a current trend is to expand these web services to provide on-demand access to model and analysis services. This progression suggests the future possibility of cloud-based decision support systems (DSSs) integrating distributed data and analysis services delivered through a host of providers. Such distributed environmental DSSs have many potential benefits, but would require highly scalable and responsive web services. The objective of this study is to assess the current feasibility of building distributed environmental DSSs from existing web services in the United States. Results show that, of the many available web services providing information about soils, river network topology, watersheds, streamflow, etc., response times are often only a few seconds for a small project area, but can grow exponentially as the project area increases. On-demand watershed delineation remains a slow-to-respond service relative to the other services tested. Also, the results suggest the need to better co-locate servers near client applications to speed up response times. Collectively, these results provide specific areas where future research is needed in order to achieve the vision of on-demand distributed environmental DSSs.

Historical Overview of Decision Support Systems (DSS)

2011 ◽  
pp. 1753-1758 ◽  
Author(s):  
Udo Richard Averweg
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
United States Of America ◽  
Support Systems ◽  
The United States ◽  
Future Trends ◽  
Historical Overview ◽  
Essential Information ◽  
Organizational Perspective ◽  
The Subject

During the late 1970s the term “decision support systems” was first coined by P. G. W. Keen, a British Academic then working in the United States of America. In 1978, Keen and Scott Morton published a book entitled, Decision Support Systems: An Organizational Perspective (Keen & Scott Morton, 1978), wherein they defined the subject title as computer systems having an impact on decisions where computer and analytical aids can be of value but where the manager’s judgment is essential. Information systems (IS) researchers and technologists have developed and investigated decision support systems (DSS) for more than 35 years (Power, 2003b). The structure of this article is as follows: The background to DSS will be given. Some DSS definitions, a discussion of DSS evolution, development of the DSS field and frameworks are then presented. Some future trends for DSS are then suggested.

Challenges and opportunities in developing decision support systems for risk assessment and management of forest invasive alien species

2020 ◽  
Vol 28 (3) ◽  
pp. 218-245 ◽  
Author(s):  
Valentine Lafond ◽  
Federico Lingua ◽  
Stefanie Lumnitz ◽  
Gregory Paradis ◽  
Vivek Srivastava ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Decision Making ◽  
Invasive Species ◽  
Decision Support ◽  
Decision Support Systems ◽  
Alien Species ◽  
Invasive Alien Species ◽  
Support Systems ◽  
Challenges And Opportunities ◽  
Risk Assessment And Management

Biological invasions represent an increasing threat to ecosystems worldwide, with negative ecological and socio-economic impacts, whereas risk assessment and management remain challenging. The development of decision support systems (DSS) has the potential to help decision-makers and managers mitigate invasive species, but few DSS exist for forest invasive alien species (FIAS). The use of DSS in forestry is not new but they represent an asset in decision making in times of increasing complexity of issues foresters face and factors to consider. Yet, few forest DSS address the problem of FIAS. In this review, we identify key elements of the FIAS risk-assessment and management decision-making process, discuss these elements with a model-based DSS development perspective, and summarize outstanding challenges and opportunities for FIAS DSS development. FIAS DSS should not only estimate the probability of FIAS invasion but also consider forest vulnerability and quantify exposure (i.e., value at risk), while allowing different threat scenarios and possible solutions to be compared. Such a complete risk assessment and management calls for integrative modelling approaches that explicitly link different components of FIAS invasion, management, and impact assessment into a DSS. Such integrative modelling is challenging and may require collaboration among experts of different domains. International collaboration is also needed to facilitate data exchange, as the lack of data is one of the main challenges. In many cases, data and ecological knowledge of invasive species are too limited (in quantity or quality) to constitute useful input to DSS or their components (e.g., species distribution model). Another challenge is to better consider the multiple sources of uncertainties inherent to modelling invasions (e.g., host preferences and behavior, forest vulnerability, potential impacts, and cost and benefits of mitigation actions) when assessing FIAS risk and communicating results from risk assessment. Communication with stakeholders and DSS end-users, in fact, appears as one of the keys to successful DSS development and appropriation, not only to ensure that they correspond to end-users’ needs but also to ensure ease of use, functionality, and good visualization of DSS outputs.

scholarly journals An interactive online database for the selection of woody ornamental plants

2003 ◽  
Vol 13 (3) ◽  
pp. 562-568
Author(s):  
Jonathan M. Lehrer ◽  
Mark H. Brand
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Survey Data ◽  
Web Site ◽  
Support Systems ◽  
Ornamental Plants ◽  
The United States ◽  
Online Questionnaire ◽  
Woody Ornamental ◽  
Strongly Agree

Web sites such as the University of Connecticut (UConn) Plant Database allow large volumes of information and images to be stored, published and accessed by users for the purpose of informed decision-making. Sorting information on the World Wide Web (Web) can be difficult, especially for novice users and those interested in quick results. The advent of Internet search and retrieval software fosters the creation of interactive decision support systems. The Plant Selector was designed to complement the UConn Plant Database plant encyclopedia by allowing Web site users to generate lists of woody ornamental plants that match specific criteria. On completion of an HTML-based search form by users, a Web-enabled database is searched and lists of matching plants are presented for review. To facilitate analysis of the Plant Selector's efficacy, an online questionnaire was implemented to solicit user feedback. Survey data from 426 responses to the online evaluation tool were analyzed both to understand user demographics and gauge satisfaction with the Plant Selector module. Survey data revealed that most Plant Selector users are between 40 to 65 years of age and homeowners with minimal horticultural experience. A large percentage of Web site visitors (68%) is located across the United States beyond Connecticut and the New England region. The great majority of survey respondents (65%) use this tool to select plants for the home landscape. Most (77%) either agree or strongly agree that the Plant Selector is easy to use and delivers results that are useful (66%), while 70% agree or strongly agree that the categories used by the Plant Selector are sufficient. The survey results in general suggest that Web-based decision support systems may serve useful roles in the field of horticulture education.

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