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.

Yield prediction errors of a stand density management program for black spruce and consequences for model improvement

2003 ◽  
Vol 33 (3) ◽  
pp. 490-499 ◽  
Author(s):  
P F Newton
Keyword(s):  
Prediction Error ◽  
Stand Structure ◽  
Black Spruce ◽  
Initial Density ◽  
Stand Density ◽  
Management Decision ◽  
Prediction Errors ◽  
Structure Variation ◽  
Model Improvement ◽  
Stand Density Management

The objectives of this study were to (i) quantify the prediction error associated with estimating density (N (stems/ha)), quadratic mean diameter (Dq (cm)), basal area (G (m2/ha)), total volume (Vt (m3/ha)), and merchantable volume (Vm (m3/ha)) using a stand density management decision-support program (SDMDSP) developed for black spruce (Picea mariana (Mill.) BSP) plantations and (ii) given objective i, assess model adequacy by examining the relationship between prediction error and model input variables (prediction period, site index, initial density, and number of thinning treatments) by yield variate. Specifically, the SDMDSP was evaluated by comparing its yield predictions with corresponding measured values (n = 44) within 19 black spruce plantations. The resultant tolerance intervals indicated that 95% of the relative errors associated with future predictions would be within the following limits 95% of the time (minimum–maximum): (i) –27.3 to 29.7% for N, (ii) –26.1 to 14.3% for Dq, (iii) –48.3 to 26.1% for G, (iv) –64.3 to 37.7% for Vt, and (v) –87.0 to 73.0% for Vm. Graphical analysis indicated that errors for Vt and Vm were associated with the data from thinned plantations. This result is discussed within the context of residual stand structure variation and response delay from which recommendations for model improvement are derived.

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.

Stand density management diagram for managed black spruce stands

1994 ◽  
Vol 70 (1) ◽  
pp. 65-74 ◽  
Author(s):  
P. F. Newton ◽  
G. F. Weetman
Keyword(s):  
Black Spruce ◽  
Stand Density ◽  
Northern Ontario ◽  
Site Class ◽  
Permanent Sample Plots ◽  
Kalmia Angustifolia ◽  
Initial Spacing ◽  
Stand Density Management ◽  
Crown Closure ◽  
Stand Density Management Diagram

A stand density management diagram for managed black spruce (Picea mariana (Mill.) B.S.P.) stands was developed using data derived from 37 variable-size temporary and permanent sample plots, and 257 open-grown sample trees. The plots were situated within 15 plantations and 4 precommercially thinned stands located throughout central and western Newfoundland, north-western New Brunswick and northern Ontario. The basic components of the diagram included: (1) an approximate crown closure line (2) the self-thinning rule (3) expected size-density trajectories and (4) isolines for dominant height, relative density index, quadratic mean diameter and merchantability ratio. The utility of the diagram was demonstrated by deriving yields for various initial spacings by site class and subsequently evaluating various outcomes in terms of operability criteria. In addition, the potential of estimating the time of crown closure by initial spacing and site class is discussed in relation to minimizing the adverse effects of Kalmia angustifolia (L.) on black spruce growth and development. Key words: stand density management diagram, initial spacing, black spruce, operability, Kalmia angustifolia (L.)

Soil organic layer combustion in boreal black spruce and jack pine stands of the Northwest Territories, Canada

2018 ◽  
Vol 27 (2) ◽  
pp. 125 ◽  
Author(s):  
Xanthe J. Walker ◽  
Jennifer L. Baltzer ◽  
Steven G. Cumming ◽  
Nicola J. Day ◽  
Jill F. Johnstone ◽  
...  
Keyword(s):  
Northwest Territories ◽  
Boreal Forests ◽  
Black Spruce ◽  
Jack Pine ◽  
Fire Intensity ◽  
Organic Layer ◽  
Complete Combustion ◽  
Soil Organic Layer ◽  
Pine Stands ◽  
Burn Depth

Increased fire frequency, extent and severity are expected to strongly affect the structure and function of boreal forest ecosystems. In this study, we examined 213 plots in boreal forests dominated by black spruce (Picea mariana) or jack pine (Pinus banksiana) of the Northwest Territories, Canada, after an unprecedentedly large area burned in 2014. Large fire size is associated with high fire intensity and severity, which would manifest as areas with deep burning of the soil organic layer (SOL). Our primary objectives were to estimate burn depth in these fires and then to characterise landscapes vulnerable to deep burning throughout this region. Here we quantify burn depth in black spruce stands using the position of adventitious roots within the soil column, and in jack pine stands using measurements of burned and unburned SOL depths. Using these estimates, we then evaluate how burn depth and the proportion of SOL combusted varies among forest type, ecozone, plot-level moisture and stand density. Our results suggest that most of the SOL was combusted in jack pine stands regardless of plot moisture class, but that black spruce forests experience complete combustion of the SOL only in dry and moderately well-drained landscape positions. The models and calibrations we present in this study should allow future research to more accurately estimate burn depth in Canadian boreal forests.

Algorithmic versions of black spruce stand density management diagrams

1997 ◽  
Vol 73 (2) ◽  
pp. 257-265 ◽  
Author(s):  
P. F. Newton
Keyword(s):  
Black Spruce ◽  
Initial Density ◽  
Basal Area ◽  
Stand Density ◽  
File Transfer ◽  
Quadratic Mean ◽  
Dominant Height ◽  
Yield Production ◽  
Quadratic Mean Diameter ◽  
Stand Density Management

Algorithmic versions of stand density management diagrams (SDMDs) were developed for natural and managed black spruce (Picea mariana (Mill.) B.S.P.) stands. Specifically, the IBM-compatible PC-based algorithms (1) graphically illustrate site-specific size-density trajectories for eight user-specified initial density regimes, (2) given (1), calculate and subsequent tabulate periodic yield estimates (mean dominant height, density, mean volume, total volume, total merchantable volume, quadratic mean diameter, and basal area), and (3) given (2), graphically illustrate empirically-derived yield production curves for total merchantable volume ha−1 and stems m−3 with user-specified operability criteria superimposed. Instructions on acquiring the executable algorithmic versions including the required graphical subroutines via the Internet are described. Currently, the algorithms are restricted in applicability to central insular Newfoundland. Key words: stand density management diagrams, black spruce, algorithms, microcomputer, World-Wide Web (WWW), hypertext browser, file transfer protocol (FTP).

What influences the acceptance of emergency management decision-support software? A study of county emergency management officials

2016 ◽  
Vol 13 (6) ◽  
pp. 539
Author(s):  
Eliot A. Jennings, PhD ◽  
Sudha Arlikatti, PhD
Keyword(s):  
Decision Support ◽  
Emergency Management ◽  
Disaster Response ◽  
Secondary Data ◽  
Positive Influence ◽  
Management Decision ◽  
Time Data ◽  
Emergency Managers ◽  
Support Software ◽  
Management Decision Support

Objective: While the benefits of emergency management decision-support software (EMDSS) have been touted for helping reduce time in decision making, increasing interoperability, and real-time data management for effective disaster response, little is understood regarding the factors that influence the acceptance of these technologies by emergency management officials. This study aims to fill this gap and contribute to theory on user acceptance of EMDSS in the public sector and highlight practical constraints and solutions for emergency managers. Design: This research uses secondary data available from the 2006 survey of county emergency management agencies conducted by the National Center for the Study of Counties.Results: Having a lead county emergency management official with higher qualifications and an in-house geographic information system division, both have a positive influence on the acceptance of EMDSS by that agency.Conclusions: Contrary to expectations, the level of local collaborative planning efforts, the perceived level of threat, and number of disaster declarations for the county did not influence the use of these sophisticated EMDSS. To ensure use of such technology for effective emergency management, more funding to offer specialized training in the use of DSS is required in those agencies that do not have in-house GIS specialists.

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