scholarly journals Stand density management diagrams: modelling approaches, variants, and exemplification of their potential utility in crop planning

2021 ◽  
Vol 51 (2) ◽  
pp. 236-256 ◽  
Author(s):  
Peter F. Newton
Keyword(s):  
Decision Support ◽  
Ecological Integrity ◽  
Predictive Ability ◽  
Stand Density ◽  
Future Research ◽  
Crop Planning ◽  
Empirical Prediction ◽  
Decision Support Models ◽  
Planning Decision ◽  
Stand Density Management

The evolving shift in forest management objectives towards the collective consideration of volumetric yield, end-product quality and value, and ecosystem service outcomes, while accounting for the impacts of anthropogenic climate change, has resulted in innovative advancements in decision-support models used in stand density management. This review provides a synopsis of these efforts with respect to static, dynamic, and structural stand density management diagrams (SDMDs). More precisely, the scope of this review includes an ecology-based perspective of stand density management, summarization of the foundational quantitative relationships along with their utilization within the analytical structure of the SDMD, examination of SDMD compliance with underlying ecological constructs and empirical prediction expectations, exemplification of a climate-sensitive structural SDMD variant in boreal crop planning, and identification of outstanding analytical challenges and plausible future research directions for advancing the SDMD modelling approach and its utility in stand-level management planning. Collectively, this account of the conceptual basis, historical analytical evolution, ecological integrity, predictive ability, application diversity, and demonstrated utility of the various SDMD variants solidifies the prerequisite evidentiary foundation for the continued development and deployment of SDMD-based crop planning decision-support models.

scholarly journals Croplanner: A Stand Density Management Decision-Support Software Suite for Addressing Volumetric Yield, End-Product and Ecosystem Service Objectives When Managing Boreal Conifers

Forests ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 448
Author(s):  
Peter F. Newton
Keyword(s):  
Decision Support ◽  
Black Spruce ◽  
Stand Density ◽  
Jack Pine ◽  
Management Decision ◽  
Software Suite ◽  
Crop Planning ◽  
Pine Stands ◽  
Stand Density Management ◽  
Support Software

The objectives of this study were to develop a stand density management decision-support software suite for boreal conifers and demonstrate its potential utility in crop planning using practical deployment exemplifications. Denoted CPDSS (CroPlanner Decision-support Software Suite), the program was developed by transcribing algorithmic analogues of structural stand density management diagrams previously developed for even-aged black spruce (Picea mariana (Mill) BSP.) and jack pine (Pinus banksiana Lamb.) stand-types into an integrated software platform with shared commonalities with respect to computational structure, input requirements and generated numerical and graphical outputs. The suite included 6 stand-type-specific model variants (natural-origin monospecific upland black spruce and jack pine stands, mixed upland black spruce and jack pine stands, and monospecific lowland black spruce stands, and plantation-origin monospecific upland black spruce and jack pine stands), and 4 climate-sensitive stand-type-specific model variants (monospecific upland black spruce and jack pine natural-origin and planted stands). The underlying models which were equivalent in terms of their modular structure, parameterization analytics and geographic applicability, were enabled to address a diversity of crop planning scenarios when integrated within the software suite (e.g., basic, extensive, intensive and elite silvicultural regimes). Algorithmically, the Windows® (Microsoft Corporation, Redmond, WA, USA) based suite was developed by recoding the Fortran-based algorithmic model variants into a collection of VisualBasic.Net® (Microsoft Corporation, Redmond, WA, USA) equivalents and augmenting them with intuitive graphical user interfaces (GUIs), optional computer-intensive optimization applications for automated crop plan selection, and interactive tabular and charting reporting tools inclusive of static and dynamic stand visualization capabilities. In order to address a wide range of requirements from the end-user community and facilitate potential deployment within provincially regulated forest management planning systems, a participatory approach was used to guide software design. As exemplified, the resultant CPDSS can be used as an (1) automated crop planning searching tool in which computer-intensive methods are used to find the most appropriate precommercial thinning, commercial thinning and (or) initial espacement (spacing) regime, according to a weighted multivariate scoring metric reflective of attained mean tree size, operability status, volumetric productivity, and economic viability, and a set of treatment-related constraints (e.g., thresholds regarding intensity and timing of thinning events, and residual stocking levels), as specified by the end-user, or (2) iterative gaming-like crop planning tool where end-users simultaneously contrast density management regimes using detailed annual and rotational volumetric yield, end-product and ecological output measures, and (or) an abbreviate set of rotational-based performance metrics, from which they determine the most applicable crop plan required for attaining their specified stand-level objective(s). The participatory approach, modular computational structure and software platform used in the formulation of the CPDSS along with its exemplified utility, collectively provides the prerequisite foundation for its potential deployment in boreal crop planning.

scholarly journals Development of a frugal crop planning decision support system for subsistence farmers

2016 ◽  
Author(s):  
◽  
Adam Friedland
Keyword(s):  
Information System ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Structural Testing ◽  
Strategic Decisions ◽  
Subsistence Farmers ◽  
Crop Planning ◽  
Support Tool ◽  
Planning Decision

This dissertation reports on the original study that undertakes the development of a frugal information system to support subsistence farmers through the use of the Agricultural Production Systems Simulator (APSIM) as a support tool to assist them in optimal strategic decisions making. The field of agriculture is vast and in-depth and a number of critical factors like soil type, rainfall and temperature are involved that farmers have to take into account. Farmers persistently face the challenges of increasing and sustaining yields to meet with the populaces demand with often limited resources, which makes strategic decisions on what to plant, when to plant, where to plant and how to plant in a particular season imperative. The way in which this study attempts to solve this agricultural decision making problem is with the use of the APSIM. This technology platform provides an advanced simulation of agricultural systems that can enable subsistence farmers to simulate a number of variables ranging from plant types, soil, climate and even management interactions. This research presents a frugal web-based crop planning decision support system that subsistence farmers can take advantage with the use of the APSIM. The APSIM platform was used to run simulations for various regions with the results containing the expected level of success along with other useful information for a specified crop in the vicinity, using state of the art software platforms and tools ranging from Google Maps application programming interfaces, Microsoft’s model view controller framework, JavaScript and others. The validity of this system was tested through a number of design science methods including structural testing and illustrative scenarios, show capability of the information system. The results obtained from this evaluation show a small but powerful tool that has the capability of servicing a multitude of farmers with crop management decisions.

scholarly journals Stand density management diagrams and their development and utility in black spruce management

1993 ◽  
Vol 69 (4) ◽  
pp. 421-430 ◽  
Author(s):  
P. F. Newton ◽  
G. F. Weetman
Keyword(s):  
Black Spruce ◽  
Basal Area ◽  
Stand Density ◽  
Future Research ◽  
Permanent Sample Plots ◽  
Quadratic Mean Diameter ◽  
Using Data ◽  
Stand Density Management ◽  
Natural Stands ◽  
Stand Density Management Diagram

A stand density management diagram for black spruce (Picea mariana (Mill.) B.S.P.) was developed using data derived from 49 0.081-ha permanent sample plots and 257 open-grown sample trees located throughout central insular Newfoundland. The diagram illustrated the reciprocal equation of the competition-density effect, self-thinning rule, approximate crown closure line, zone of imminent competition-mortality, and isolines for relative density, quadratic mean diameter and merchantability ratio. Mean prediction error for natural stand trajectories over a 30-projection period were 2.5 dm3 for mean volume, 306 stems/ha for density, 16.1 m3/ha for merchantable volume, 14.3 m3/ha for total volume, and 1.9 m2/ha for basal area. Implementation procedures using a combination of monoareal and polyareal sampling methods were described and the potential application of the diagram for evaluating thinning alternatives was demonstrated. Limitations of the diagram and future research directions were identified. Key words: stand density management diagram, black spruce, natural stands, central Newfoundland

Models of decision support in socio-cyber-physical systems

2019 ◽  
pp. 55-70 ◽  
Author(s):  
A. V. Smirnov ◽  
T. V. Levashova
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Situation Awareness ◽  
Cyber Physical Systems ◽  
Emergent Behavior ◽  
Emergent Properties ◽  
Decision Making Process ◽  
Physical Systems ◽  
Decision Support Models ◽  
Common Goals

Introduction: Socio-cyber-physical systems are complex non-linear systems. Such systems display emergent properties. Involvement of humans, as a part of these systems, in the decision-making process contributes to overcoming the consequences of the emergent system behavior, since people can use their experience and intuition, not just the programmed rules and procedures.Purpose: Development of models for decision support in socio-cyber-physical systems.Results: A scheme of decision making in socio-cyber-physical systems, a conceptual framework of decision support in these systems, and stepwise decision support models have been developed. The decision-making scheme is that cybernetic components make their decisions first, and if they cannot do this, they ask humans for help. The stepwise models support the decisions made by components of socio-cyber-physical systems at the conventional stages of the decision-making process: situation awareness, problem identification, development of alternatives, choice of a preferred alternative, and decision implementation. The application of the developed models is illustrated through a scenario for planning the execution of a common task for robots.Practical relevance: The developed models enable you to design plans on solving tasks common for system components or on achievement of common goals, and to implement these plans. The models contribute to overcoming the consequences of the emergent behavior of socio-cyber-physical systems, and to the research on machine learning and mobile robot control.

Decision support tools for oil spill response (OSR-DSTs): Approaches, challenges, and future research perspectives

2021 ◽  
Vol 167 ◽  
pp. 112313
Author(s):  
Zhaoyang Yang ◽  
Zhi Chen ◽  
Kenneth Lee ◽  
Edward Owens ◽  
Michel C. Boufadel ◽  
...  
Keyword(s):  
Decision Support ◽  
Oil Spill ◽  
Future Research ◽  
Decision Support Tools ◽  
Research Perspectives ◽  
Support Tools ◽  
Oil Spill Response

Influences of Stress on Interactions with Decision Support

2020 ◽  
Vol 64 (1) ◽  
pp. 1886-1890
Author(s):  
Kylie Litaker ◽  
Christopher B. Mayhorn
Keyword(s):  
Decision Support ◽  
Information Source ◽  
Negative Influence ◽  
Future Research ◽  
Physiological Measures ◽  
Task Motivation ◽  
Situational Stress ◽  
Before And After ◽  
Scanning Task ◽  
Source Of Information

People regularly interact with automation to make decisions. Research shows that reliance on recommendations can depend on user trust in the decision support system (DSS), the source of information (i.e. human or automation), and situational stress. This study explored how information source and stress affect trust and reliance on a DSS used in a baggage scanning task. A preliminary sample of sixty-one participants were given descriptions for a DSS and reported trust before and after interaction. The DSS gave explicit recommendations when activated and participants could choose to rely or reject the choice. Results revealed a bias towards self-reliance and a negative influence of stress on trust, particularly for participants receiving help from automation. Controlling for perceived reliability may have eliminated trust biases prior to interaction, while stress may have influenced trust during the task. Future research should address potential differences in task motivation and include physiological measures of stress.

scholarly journals Bridging Science and Practice-Importance of Stakeholders in the Development of Decision Support: Lessons Learned

2021 ◽  
Vol 13 (10) ◽  
pp. 5744
Author(s):  
Innocent K. Tumwebaze ◽  
Joan B. Rose ◽  
Nynke Hofstra ◽  
Matthew E. Verbyla ◽  
Daniel A. Okaali ◽  
...  
Keyword(s):  
Decision Support ◽  
Stakeholder Participation ◽  
Scientific Data ◽  
Lessons Learned ◽  
Future Research ◽  
Decision Support Tools ◽  
Local Data ◽  
Funding Sources ◽  
Sanitation And Hygiene ◽  
Support Tools

User-friendly, evidence-based scientific tools to support sanitation decisions are still limited in the water, sanitation and hygiene (WASH) sector. This commentary provides lessons learned from the development of two sanitation decision support tools developed in collaboration with stakeholders in Uganda. We engaged with stakeholders in a variety of ways to effectively obtain their input in the development of the decision support tools. Key lessons learned included: tailoring tools to stakeholder decision-making needs; simplifying the tools as much as possible for ease of application and use; creating an enabling environment that allows active stakeholder participation; having a dedicated and responsive team to plan and execute stakeholder engagement activities; involving stakeholders early in the process; having funding sources that are flexible and long-term; and including resources for the acquisition of local data. This reflection provides benchmarks for future research and the development of tools that utilize scientific data and emphasizes the importance of engaging with stakeholders in the development process.

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