scholarly journals The use of dynamic landscape metapopulation models for forest management: a case study of the red-backed salamander

2012 ◽  
Vol 42 (6) ◽  
pp. 1091-1106 ◽  
Author(s):  
Ascelin Gordon ◽  
Brendan A. Wintle ◽  
Sarah A. Bekessy ◽  
Jennie L. Pearce ◽  
Lisa A. Venier ◽  
...  
Keyword(s):  
Forest Management ◽  
Environmental Change ◽  
Population Size ◽  
Fire Suppression ◽  
Spatial Models ◽  
Decision Support Tool ◽  
Timber Harvesting ◽  
Management Scenarios ◽  
Support Tool ◽  
Dynamic Landscape

Spatial models of population dynamics have been proposed as a useful method for predicting the impacts of environmental change on biodiversity. Here, we demonstrate advances in dynamic landscape metapopulation modelling and its use as a decision support tool for evaluating the impacts of forest management scenarios. This novel modelling framework incorporates both landscape and metapopulation model stochasticity and allows their relative contributions to model output variance to be characterized. It includes a detailed sensitivity analysis, allowing defensible uncertainty bounds and the prioritization of future data gathering to reduce model uncertainties. We demonstrate this framework by modelling the landscape-level impacts of eight forest management scenarios on the red-backed salamander ( Plethodon cinereus (Green, 1818)) in the boreal forest of Ontario, Canada, using the RAMAS Landscape package. The 100 year forest management scenarios ranged in intensity of timber harvesting and fire suppression. All scenarios including harvesting predicted decreases in salamander population size and the current style of forest management is predicted to produce a 9%–17% decrease in expected minimum population size compared with scenarios without harvesting. This method is amenable to incorporating many forms of environmental change and allows a meaningful treatment of uncertainty.

scholarly journals Presenting MASSIMO: A Management Scenario Simulation Model to Project Growth, Harvests and Carbon Dynamics of Swiss Forests

Forests ◽  
2019 ◽  
Vol 10 (2) ◽  
pp. 94 ◽  
Author(s):  
Golo Stadelmann ◽  
Christian Temperli ◽  
Brigitte Rohner ◽  
Markus Didion ◽  
Anne Herold ◽  
...  
Keyword(s):  
Forest Management ◽  
Timber Harvesting ◽  
Reference Levels ◽  
Management Scenarios ◽  
Individual Tree ◽  
Development Models ◽  
Management Scenario ◽  
Species Mixture ◽  
The Individual ◽  
Business As Usual

Forest development models have been used to predict future harvesting potentials and forest management reference levels under the Kyoto guidelines. This contribution aims at presenting the individual-tree simulator MASSIMO and demonstrating its scope of applications with simulations of two possible forest management reference levels (base or business as usual) in an example application. MASSIMO is a suitable tool to predict timber harvesting potentials and forest management reference levels to assess future carbon budgets of Swiss forests. While the current version of MASSIMO accurately accounts for legacy effects and management scenarios, effects of climate and nitrogen deposition on growth, mortality, and regeneration are not yet included. In addition to including climate sensitivity, the software may be further improved by including effects of species mixture on tree growth and assessing ecosystem service provision based on indicators.

scholarly journals Promoting long-term forest landscape resilience in the Lake Tahoe basin

2021 ◽  
Author(s):  
Eric S Abelson ◽  
Keith M Reynolds ◽  
Angela M White ◽  
Jonathan W Long ◽  
Charles Maxwell ◽  
...  
Keyword(s):  
At Risk ◽  
Environmental Changes ◽  
Fire Suppression ◽  
Lake Tahoe ◽  
Forest Landscape ◽  
Lake Tahoe Basin ◽  
Management Scenarios ◽  
Environmental Pressures ◽  
Support Tool ◽  
Tahoe Basin

Rapid environmental changes expected in the 21st century challenge the resilience of wildlands around the world. The western portion of the Lake Tahoe basin (LTW) in California is an important ecological and cultural hotspot that is at risk of degradation from current and future environmental pressures. Historical uses, fire suppression, and a changing climate have created forest landscape conditions at risk of drought stress, destructive fire, and loss of habitat diversity. We prospectively modeled forest landscape conditions for a period of 100 years to evaluate the efficacy of five unique management scenarios in achieving desired landscape conditions across the 23,600 hectares of LTW. Management scenarios ranged from no management other than fire suppression to applying treatments consistent with historical fire frequencies and extent (i.e., regular and broadscale biomass reduction). We developed a decision support tool to evaluate environmental and social outcomes within a single framework to provide a transparent set of costs and benefits; results illuminated underlying mechanisms of forest resilience and provided actionable guidance to decision makers. Sixteen attributes were assessed in the model after assigning weights to each, derived through a survey of stakeholder priorities, so that the contribution of each attribute to evaluations of scenario performance was influenced by the combined priorities of stakeholders. We found that removing forest biomass across the landscape, particularly when accomplished using extensive fire-based removal techniques, led to highly favorable conditions for environmental quality and promoting overall landscape resilience. Environmental conditions resulting from extensive fire-based biomass removal also had nominal variation over time, in contrast with strategies that had less extensive and/or used physical removal techniques, namely thinning. Our analysis provided a transparent approach to data assessment, considering the priorities of stakeholders, to provide insights into the complexities of maintaining optimal conditions and managing landscapes to promote ecosystem resilience in a changing world.

scholarly journals Black rhinoceros avoidance of tourist infrastructure and activity: planning and managing for coexistence

Oryx ◽  
2019 ◽  
pp. 1-10 ◽  
Author(s):  
Jeff R. Muntifering ◽  
Wayne L. Linklater ◽  
Robin Naidoo ◽  
Simson !Uri-≠Khob ◽  
Pierre du Preez ◽  
...  
Keyword(s):  
Spatial Data ◽  
Wildlife Conservation ◽  
Species Conservation ◽  
Decision Support Tool ◽  
Management Scenarios ◽  
Case Scenario ◽  
High Quality ◽  
Worst Case ◽  
Support Tool ◽  
Black Rhinoceros

AbstractWildlife-based tourism poses opportunities and challenges for species conservation. Minimizing potential negative impacts of tourism is critical to ensure business and conservation enterprises can coexist. In north-western Namibia tourism is used as a conservation tool for the Critically Endangered black rhinoceros Diceros bicornis. However, black rhinoceroses are susceptible to human disturbance and may become displaced by tourist activities, which threatens not only the security and health of the rhinoceros population but also the sustainability of the business. We examined areas avoided by black rhinoceroses to understand how they respond to the type and extent of tourism development, and to evaluate management alternatives. We used spatial data on use of water sources by rhinoceroses to create a series of a priori candidate models that described the negative influences of tourist activities on rhinoceros habitat use. A model selection approach strongly supported a cumulative zones of influence model comprised of a 6 km buffer around the airstrip combined with a 1 km buffer around roads used daily. We compared alternative management scenarios using the best-performing model and found that an optimal road-use policy combined with airstrip relocation could minimize the total area avoided by the black rhinoceros to 7.1% and loss of high quality habitat to 20.7%. Under the worst-case scenario the area avoided and loss of high quality habitat were 153 and 85% greater, respectively, than under the scenario with optimal management. Our findings provide a novel framework and a practical, policy-relevant decision support tool to improve the contribution of tourism to wildlife conservation.

scholarly journals A Decision Support Tool for Assessing the Impact of Climate Change on Multiple Ecosystem Services

Forests ◽  
2019 ◽  
Vol 10 (5) ◽  
pp. 440 ◽  
Author(s):  
Irina Cristal ◽  
Aitor Ameztegui ◽  
Jose Ramon González-Olabarria ◽  
Jordi Garcia-Gonzalo
Keyword(s):  
Climate Change ◽  
Decision Support ◽  
Ecosystem Services ◽  
Forest Management ◽  
Decision Support Tool ◽  
Tree Level ◽  
Support Tool ◽  
Simulation Engine ◽  
User Centric ◽  
The Impact

In the climate change era, forest managers are challenged to use innovative tools to encourage a sustained provision of goods and services. Many decision support tools (DSTs), developed to address global changes in forest management practices, reflect the complexity of the scientific knowledge produced, a fact that could make it difficult for practitioners to understand and adopt them. Acknowledging the importance of knowledge transfer to forestry practitioners, this study describes a user-centric decision support software tool, aiming to assess forest management and climate change impacts on multiple ecosystem services (ESs) at a stand level. SORTIE-ND, a spatially explicit tree-level simulator for projecting stand dynamics that is sensitive to climate change, is encapsulated into the decision support tool and used as the simulation engine for stand development. Linking functions are implemented to evaluate ecosystem services and potential risks, and decision support is provided in form of interactive 2D and 3D visualizations. Five main components were identified to delineate the workflow and to shape the decision support tool: the information base, the alternative generator, the forest simulator, the ecosystem services calculator, and the visualization component. In order to improve the interaction design and general user satisfaction, the usability of the system was tested at an early stage of the development. While we have specifically focused on a management-oriented approach through user-centric interface design, the utilization of the product is likely to be of importance in facilitating education in the field of forest management.

scholarly journals HeProMo: A decision support tool to estimate wood harvesting productivities

PLoS ONE ◽  
2020 ◽  
Vol 15 (12) ◽  
pp. e0244289
Author(s):  
Stefan Holm ◽  
Fritz Frutig ◽  
Renato Lemm ◽  
Oliver Thees ◽  
Janine Schweier
Keyword(s):  
Decision Support ◽  
Forest Management ◽  
Decision Support Tool ◽  
Operating Conditions ◽  
Production Costs ◽  
Forest Operations ◽  
Support Tool ◽  
Central European ◽  
Wood Harvesting ◽  
Input Variables

In the field of forestry, one of the most economically important ecosystem service is the provision of timber. The need to calculate the economic effects of forest management in the short, medium, and long term is increasing. Forest operations or timber harvesting, which comprises felling, processing, and transport of trees or timber, are responsible for a large part of the costs and environmental impacts associated to forest management or enterprises. From a decision maker’s perspective, it is essential to estimate working productivity and production costs under given operating conditions before any operation is conducted. This work addresses the lack of a valid collection of models that allows estimating time, productivities, and costs of labor and machinery for the most important forest operations in forest stands under Central European conditions. To create such models, we used data from forest enterprises, manual time studies, and the literature. This work presents a decision support tool that estimates the wood harvesting productivities of 12 different kinds of forest operations under Central European conditions. It includes forest operations using chainsaws, harvesters, skidders, forwarders, chippers, cable and tower yarders, and helicopters. In addition, the tool covers three models for wood volume estimation. The tool is written in Java and available open-source under the Apache License. This work shows how the tool can be used by describing its graphical user interface (GUI) and its application programming interface (API) that facilitates bulk processing of scientific data. Carefully selected default values allow estimations without knowing all input variables in detail. Each model is accompanied by an in-depth documentation where the forest operation, input variables, formulas, and statistical background are given. We conclude that HeProMo is a very useful tool for applications in forest practice, research, and teaching.

scholarly journals A detrimental soil disturbance prediction model for ground-based timber harvesting

2012 ◽  
Vol 42 (5) ◽  
pp. 821-830 ◽  
Author(s):  
Derrick A. Reeves ◽  
Matthew C. Reeves ◽  
Ann M. Abbott ◽  
Deborah S. Page-Dumroese ◽  
Mark D. Coleman
Keyword(s):  
Soil Properties ◽  
Predictive Model ◽  
Decision Support Tool ◽  
Timber Harvesting ◽  
Soil Disturbance ◽  
Slope Aspect ◽  
Areal Extent ◽  
Support Tool ◽  
Topographic Features ◽  
Site Characteristics

Soil properties and forest productivity can be affected during ground-based harvest operations and site preparation. The degree of impact varies widely depending on topographic features and soil properties. Forest managers who understand site-specific limits to ground-based harvesting can alter harvest method or season to limit soil disturbance. To determine the potential areal extent of detrimental (potentially plant growth limiting) soil disturbance based on site characteristics and season of harvest, we developed a predictive model based on soil monitoring data collected from 167 ground-based harvest units. Data collected included dominant site parameters (e.g., slope, aspect, soil texture, and landtype), harvest season, harvest type (intermediate or regeneration), and the machine(s) used during ground-based harvest operations. Aspect (p = 0.0217), slope (p = 0.0738), landtype (p = 0.0002), and the interaction of harvest season × landtype (p = 0.0002) were the key variables controlling the areal extent and magnitude of detrimental soil disturbance. For example, harvesting during non-winter months on gently rolling topography resulted in greater soil disturbance than similar harvest operations on landscapes that are highly dissected. This is likely due to the ease with which equipment can move off designated trails. A geospatially explicit predictive model was developed using general linear model variables found to significantly influence the areal extent of detrimental soil disturbance on nine defined landtypes. This tool provides a framework that, with local calibration, can be used on other forest lands as a decision support tool to geospatially depict landtypes susceptible to detrimental soil disturbance during ground-based harvest operations.

Warehouse management system customization and information availability in 3pl companies

2019 ◽  
Vol 119 (2) ◽  
pp. 251-273 ◽  
Author(s):  
Giulia Baruffaldi ◽  
Riccardo Accorsi ◽  
Riccardo Manzini
Keyword(s):  
Management System ◽  
Decision Support Tool ◽  
Optimization Techniques ◽  
Warehouse Management ◽  
Management Scenarios ◽  
Content Type ◽  
Support Tool ◽  
Information Availability ◽  
Digital Twin ◽  
Warehouse Management System

PurposeThe purpose of this paper is to illustrate an original decision-support tool (DST) that aids 3PL managers to decide on the proper warehouse management system (WMS) customization. The aim of this tool is to address to the three main issues affecting such decision: the cost of the information sharing, the scarce visibility of the client’s data and the uncertainty of quantifying the return from investing into a WMS feature.Design/methodology/approachThe tool behaves as a digital twin of a WMS. In addition, it incorporates a set of WMS’s features based both on heuristics and optimization techniques and uses simulation to perform what-if multi-scenario analyses of alternative management scenarios. In order to validate the effectiveness of the tool, its application to a real-world 3PL warehouse operating in the sector of biomedical products is illustrated.FindingsThe results of a simulation campaign along an observation horizon of ten months demonstrate how the tool supports the comparison of alternative scenarios with theas-is, thereby suggesting the most suitable WMS customization to adopt.Practical implicationsThe tool supports 3PL managers in enhancing the efficiency of the operations and the fulfilling of the required service level, which is increasingly challenging given the large inventory mix and the variable clients portfolio that 3PLs have to manage. Particularly, the choice of the WMS customization that better perform with each business can be problematic, given the scarce information visibility of the provider on the client’s processes.Originality/valueTo the author’s knowledge, this paper is among the first to address a still uncovered gap of the warehousing literature by illustrating a DST that exploits optimization and simulation techniques to quantify the impacts of the information availability on the warehousing operations performance. As a second novel contribution, this tool enables to create a digital twin of a WMS and foresee the evolution of the warehouse’s performance over time.

scholarly journals An ecosystem service perspective on urban nature, physical activity, and health

2021 ◽  
Vol 118 (22) ◽  
pp. e2018472118
Author(s):  
Roy P. Remme ◽  
Howard Frumkin ◽  
Anne D. Guerry ◽  
Abby C. King ◽  
Lisa Mandle ◽  
...  
Keyword(s):  
Physical Activity ◽  
Current Knowledge ◽  
Health Benefits ◽  
Spatial Models ◽  
Decision Support Tool ◽  
Well Being ◽  
Potential Contribution ◽  
Urban Nature ◽  
Model Framework ◽  
Support Tool

Nature underpins human well-being in critical ways, especially in health. Nature provides pollination of nutritious crops, purification of drinking water, protection from floods, and climate security, among other well-studied health benefits. A crucial, yet challenging, research frontier is clarifying how nature promotes physical activity for its many mental and physical health benefits, particularly in densely populated cities with scarce and dwindling access to nature. Here we frame this frontier by conceptually developing a spatial decision-support tool that shows where, how, and for whom urban nature promotes physical activity, to inform urban greening efforts and broader health assessments. We synthesize what is known, present a model framework, and detail the model steps and data needs that can yield generalizable spatial models and an effective tool for assessing the urban nature–physical activity relationship. Current knowledge supports an initial model that can distinguish broad trends and enrich urban planning, spatial policy, and public health decisions. New, iterative research and application will reveal the importance of different types of urban nature, the different subpopulations who will benefit from it, and nature’s potential contribution to creating more equitable, green, livable cities with active inhabitants.

scholarly journals An Evaluation of Woody Biomass and Pulpwood Market Competition within a Range of Procurement Distances

2021 ◽  
Vol 71 (4) ◽  
pp. 407-418
Author(s):  
Manisha Parajuli ◽  
Patrick Hiesl ◽  
Mathew Smidt ◽  
Dana Mitchell
Keyword(s):  
Decision Support ◽  
Loblolly Pine ◽  
Market Competition ◽  
Forest Biomass ◽  
Decision Support Tool ◽  
Timber Harvesting ◽  
Wood Chips ◽  
Cube Root ◽  
Support Tool ◽  
Harvesting Systems

Abstract In the Southern United States, a rising number of biomass facilities have created new market opportunities for forest landowners, consulting foresters, and loggers, which could increase the competition between the biomass market and pulpwood market for forest biomass. Thus, comparing the profits from conventional roundwood harvesting and biomass harvesting within a range of procurement distances could be crucial to make a harvest decision. In this study, we considered two harvesting systems: conventional and biomass. We developed a decision support tool to predict and compare the final stumpage value from both harvesting systems based on the stand and site conditions, market conditions, and distance to the nearest market. We grew (simulated) loblolly pine (Pinus taeda) plantations to six different thinning ages (12, 14, 16, 18, 20, and 22 yr) at five different site indices (17, 20, 23, 26, and 29 m at a base age of 25 yr) using the PTAEDA4.0 software. Different models were fitted and evaluated for certain training and validating criteria. In both harvesting systems, we select the cube root-transformed model as the best model. Using the models, we predict that the utilization of logging residues and pulpwood as wood chips may yield a higher return to the landowner when the delivered price of the wood chips is comparable to the delivered price of the pulpwood and within the same procurement distance. The selected models thus serve as a decision support tool to inform stakeholders to further maximize their economic return from timber harvesting operations by selecting the most profitable option.

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