A climate change adaptive dynamic programming approach to optimize eucalypt stand management scheduling: a Portuguese application

Ferreira, Liliana; Constantino, Miguel; Borges, José G.; García-Gonzalo, Jordi; Barreiro, Susana

doi:10.1139/cjfr-2015-0329

Cited by 12 publications

(9 citation statements)

References 23 publications

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“…Research distribution among journals is decentralized according to the focus of the study in question. This occurred due to the wide employability of PBMs in forest studies, which can be used in ecological and environmental research (Sanchez-Salguero et al, 2018;Xu et al, 2019), with emphasis on forest production (Oliveira et al, 2018;Thomas et al, 2018) or on the optimization and management of forest resources (Ferreira et al, 2016;Venturas et al, 2018).…”

Section: Distribution Of Journalsmentioning

confidence: 99%

Use of the process-based models in forest research: a bibliometric review

Gonçalves

Santos

França

et al. 2021

CERNE

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Background: Process-based modeling is made to simulate the interactions of the soil-plantatmosphere system providing information and estimates for forest management and services. Through bibliometric evaluation we identify the quantitative state of the art on the use of Process-Based Models (PBMs) applied in forestry studies, contextualizing research fronts, and analyzing the main topics and emerging themes. Data from the Web of Science and Scopus were used for the bibliometric survey of 533 scientific records. Results:We verified that (i) the number of publications related to the PBMs was boosted in the year 2000, and is growing; (ii) Forest Ecology and Management (74 publications) is the journal that most publishes on the subject; (iii) Annikki Mäkelä is the most productive researcher (20 publications) and most cited (h-index: 12); (iv) The USA (131 records) is the country with the highest number of research; (v) there are eight collaborative networks between the authors, three workings together, and five producing in isolation; (vi) the keywords are grouped into five clusters: (a) the effect of climate change on forests; (b) carbon studies; (c) physiology of trees; (d) silvicultural practices and; (e) analysis of model uncertainties. The separation of themes showed that the new search hotspots are the PBMs using of remote detection tools. Conclusion:The results presented can be a fundamental theoretical tool for understanding the trends and development perspectives of this research line in future studies.

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Section: Distribution Of Journalsmentioning

confidence: 99%

Use of the process-based models in forest research: a bibliometric review

Gonçalves

Santos

França

et al. 2021

CERNE

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“…stands (Ferreira et al 2012) and short-rotation coppice systems (Ferreira et al 2012) under fire risk, both in Portugal. Ferreira et al (2016) developed a dynamic programming approach to define stand-level adaptive management strategies in a context of climate change. The development of landscape-level adaptive management strategies may be facilitated by other quantitative techniques, e.g., integer and mixed integer spatially explicit models, stochastic optimization models, and heuristic approaches ).…”

Section: Optimization Techniques and Trade-offs Among Objectivesmentioning

confidence: 99%

A framework for modeling adaptive forest management and decision making under climate change

Yousefpour¹,

Temperli²,

Jacobsen³

et al. 2017

E&S

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Hanewinkel. 2017. A framework for modeling adaptive forest management and decision making under climate change. ABSTRACT. Adapting the management of forest resources to climate change involves addressing several crucial aspects to provide a valid basis for decision making. These include the knowledge and belief of decision makers, the mapping of management options for the current as well as anticipated future bioclimatic and socioeconomic conditions, and the ways decisions are evaluated and made. We investigate the adaptive management process and develop a framework including these three aspects, thus providing a structured way to analyze the challenges and opportunities of managing forests in the face of climate change. We apply the framework for a range of case studies that differ in the way climate and its impacts are projected to change, the available management options, and how decision makers develop, update, and use their beliefs about climate change scenarios to select among adaptation options, each being optimal for a certain climate change scenario. We describe four stylized types of decision-making processes that differ in how they (1) take into account uncertainty and new information on the state and development of the climate and (2) evaluate alternative management decisions: the "no-change," the "reactive," the "trend-adaptive," and the "forward-looking adaptive" decision-making types. Accordingly, we evaluate the experiences with alternative management strategies and recent publications on using Bayesian optimization methods that account for different simulated learning schemes based on varying knowledge, belief, and information. Finally, our proposed framework for identifying adaptation strategies provides solutions for enhancing forest structure and diversity, biomass and timber production, and reducing climate change-induced damages. They are spatially heterogeneous, reflecting the diversity in growing conditions and socioeconomic settings within Europe.

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“…Certain authors (Ferreira et al, 2016) propose a stochastic approach based on dynamic programming to mitigate adverse climate change impacts and to increase the adaptive capacity of forest stands. This approach is the more innovative as it fully integrates a stochastic dynamic approach with a process-based model that is sensitive to climate parameters.…”

Section: Literature Reviewmentioning

confidence: 99%

Application of Dynamic Programming in Planning Costs of Telecommunication Security Operations to Provide Aid to Civilian Authorities

et al. 2016

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Management 2016/81 The problem in planning costs of an operation, i.e., the problem of determining an optimal capacity of units used in time is a highly complex problem whose solution can be obtained in different ways, depending on what is taken as an optimality criterion and the types of limiting factors that are present during an operation's realization. The main goal of this paper is to show the practical application of dynamic programming with the aim of improving planning and organizing forces and costs during the realization of the Serbian army's third mission. Data on the use of Serbian Military's units after the earthquake in the area of Kraljevo in 2010 were analysed. The paper covers the use of dynamic programming, namely, the complex optimization problem of using military units, which depends on a large number of variables and can be extremely difficult to solve, is disassembled into several smaller partial problems that depend on one variable and are simpler to solve. The model of using the military is based on mission usage and represented as one of possible scenarios of natural disasters that engulfed a part of the Serbian territory.

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A climate change adaptive dynamic programming approach to optimize eucalypt stand management scheduling: a Portuguese application

Cited by 12 publications

References 23 publications

Use of the process-based models in forest research: a bibliometric review

Use of the process-based models in forest research: a bibliometric review

A framework for modeling adaptive forest management and decision making under climate change

Application of Dynamic Programming in Planning Costs of Telecommunication Security Operations to Provide Aid to Civilian Authorities

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