A multistage decision support framework to guide tree species management under climate change via habitat suitability and colonization models, and a knowledge-based scoring system

2016 ◽  
Vol 31 (9) ◽  
pp. 2187-2204 ◽  
Author(s):  
Anantha M. Prasad ◽  
Louis R. Iverson ◽  
Stephen N. Matthews ◽  
Matthew P. Peters
Keyword(s):  
Climate Change ◽  
Decision Support ◽  
Tree Species ◽  
Habitat Suitability ◽  
Scoring System ◽  
Guide Tree ◽  
Knowledge Based ◽  
Decision Support Framework ◽  
Species Management

scholarly journals Desiccation crisis of saline lakes: A new decision-support framework for building resilience to climate change

2020 ◽  
Vol 703 ◽  
pp. 134718 ◽  
Author(s):  
Amirhossein Hassani ◽  
Adisa Azapagic ◽  
Paolo D'Odorico ◽  
Amir Keshmiri ◽  
Nima Shokri
Keyword(s):  
Climate Change ◽  
Decision Support ◽  
Saline Lakes ◽  
Building Resilience ◽  
Decision Support Framework

Hotspots of change in major tree species under climate warming

2020 ◽  
Author(s):  
Flurin Babst ◽  
Richard L. Peters ◽  
Rafel O. Wüest ◽  
Margaret E.K. Evans ◽  
Ulf Büntgen ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Sensitivity ◽  
Tree Growth ◽  
Species Distribution ◽  
Tree Species ◽  
Habitat Suitability ◽  
Species Distribution Models ◽  
Sensitivity Index ◽  
Distribution Models ◽  
Bioclimatic Variables

<p>Warming alters the variability and trajectories of tree growth around the world by intensifying or alleviating energy and water limitation. This insight from regional to global-scale research emphasizes the susceptibility of forest ecosystems and resources to climate change. However, globally-derived trends are not necessarily meaningful for local nature conservation or management considerations, if they lack specific information on present or prospective tree species. This is particularly the case towards the edge of their distribution, where shifts in growth trajectories may be imminent or already occurring.</p><p>Importantly, the geographic and bioclimatic space (or “niche”) occupied by a tree species is not only constrained by climate, but often reflects biotic pressure such as competition for resources with other species. This aspect is underrepresented in many species distribution models that define the niche as a climatic envelope, which is then allowed to shift in response to changes in ambient conditions. Hence, distinguishing climatic from competitive niche boundaries becomes a central challenge to identifying areas where tree species are most susceptible to climate change.</p><p>Here we employ a novel concept to characterize each position within a species’ bioclimatic niche based on two criteria: a climate sensitivity index (CSI) and a habitat suitability index (HSI). The CSI is derived from step-wise multiple linear regression models that explain variability in annual radial tree growth as a function of monthly climate anomalies. The HSI is based on an ensemble of five species distribution models calculated from a combination of observed species occurrences and twenty-five bioclimatic variables. We calculated these two indices for 11 major tree species across the Northern Hemisphere.</p><p>The combination of climate sensitivity and habitat suitability indicated hotspots of change, where tree growth is mainly limited by competition (low HSI and low CSI), as well as areas that are particularly sensitive to climate variability (low HSI and high CSI). In the former, we expect that forest management geared towards adjusting the competitive balance between several candidate species will be most effective under changing environmental conditions. In the latter areas, selecting particularly drought-tolerant accessions of a given species may reduce forest susceptibility to the predicted warming and drying.</p>

scholarly journals Co-development of a climate change decision support framework through engagement with stakeholders

2019 ◽  
Vol 153 (4) ◽  
pp. 587-605 ◽  
Author(s):  
Anne M. Leitch ◽  
J. P. Palutikof ◽  
D. Rissik ◽  
S. L. Boulter ◽  
Fahim N. Tonmoy ◽  
...  
Keyword(s):  
Climate Change ◽  
Decision Support ◽  
Decision Support Framework

scholarly journals Spatial Pattern of Climate Change Effects on Lithuanian Forestry

Forests ◽  
2019 ◽  
Vol 10 (9) ◽  
pp. 809 ◽  
Author(s):  
Gintautas Mozgeris ◽  
Vilis Brukas ◽  
Nerijus Pivoriūnas ◽  
Gintautas Činga ◽  
Ekaterina Makrickienė ◽  
...  
Keyword(s):  
Climate Change ◽  
Decision Support ◽  
Ecosystem Services ◽  
Forest Management ◽  
Decision Support Systems ◽  
Tree Species ◽  
Support Systems ◽  
Forest Growth ◽  
Climate Change Scenarios ◽  
Climate Change Effects

Research Highlights: Validating modelling approach which combines global framework conditions in the form of climate and policy scenarios with the use of forest decision support system to assess climate change impacts on the sustainability of forest management. Background and Objectives: Forests and forestry have been confirmed to be sensitive to climate. On the other hand, human efforts to mitigate climate change influence forests and forest management. To facilitate the evaluation of future sustainability of forest management, decision support systems are applied. Our aims are to: (1) Adopt and validate decision support tool to incorporate climate change and its mitigation impacts on forest growth, global timber demands and prices for simulating future trends of forest ecosystem services in Lithuania, (2) determine the magnitude and spatial patterns of climate change effects on Lithuanian forests and forest management in the future, supposing that current forestry practices are continued. Materials and Methods: Upgraded version of Lithuanian forestry simulator Kupolis was used to model the development of all forests in the country until 2120 under management conditions of three climate change scenarios. Selected stand-level forest and forest management characteristics were aggregated to the level of regional branches of the State Forest Enterprise and analyzed for the spatial and temporal patterns of climate change effects. Results: Increased forest growth under a warmer future climate resulted in larger tree dimensions, volumes of growing stock, naturally dying trees, harvested assortments, and also higher profits from forestry activities. Negative impacts were detected for the share of broadleaved tree species in the standing volume and the tree species diversity. Climate change effects resulted in spatially clustered patterns—increasing stand productivity, and amounts of harvested timber were concentrated in the regions with dominating coniferous species, while the same areas were exposed to negative dynamics of biodiversity-related forest attributes. Current forest characteristics explained 70% or more of the variance of climate change effects on key forest and forest management attributes. Conclusions: Using forest decision support systems, climate change scenarios and considering the balance of delivered ecosystem services is suggested as a methodological framework for validating forest management alternatives aiming for more adaptiveness in Lithuanian forestry.

scholarly journals Facilitating Adaptive Forest Management under Climate Change: A Spatially Specific Synthesis of 125 Species for Habitat Changes and Assisted Migration over the Eastern United States

Forests ◽  
2019 ◽  
Vol 10 (11) ◽  
pp. 989 ◽  
Author(s):  
Louis R. Iverson ◽  
Anantha M. Prasad ◽  
Matthew P. Peters ◽  
Stephen N. Matthews
Keyword(s):  
Climate Change ◽  
United States ◽  
Tree Species ◽  
Habitat Suitability ◽  
Analysis Data ◽  
Suitable Habitat ◽  
Eastern United States ◽  
Data Set ◽  
The Face ◽  
Suitable Habitats

We modeled and combined outputs for 125 tree species for the eastern United States, using habitat suitability and colonization potential models along with an evaluation of adaptation traits. These outputs allowed, for the first time, the compilation of tree species’ current and future potential for each unit of 55 national forests and grasslands and 469 1 × 1 degree grids across the eastern United States. A habitat suitability model, a migration simulation model, and an assessment based on biological and disturbance factors were used with United States Forest Service Forest Inventory and Analysis data to evaluate species potential to migrate or infill naturally into suitable habitats over the next 100 years. We describe a suite of variables, by species, for each unique geographic unit, packaged as summary tables describing current abundance, potential future change in suitable habitat, adaptability, and capability to cope with the changing climate, and colonization likelihood over 100 years. This resulting synthesis and summation effort, culminating over two decades of work, provides a detailed data set that incorporates habitat quality, land cover, and dispersal potential, spatially constrained, for nearly all the tree species of the eastern United States. These tables and maps provide an estimate of potential species trends out 100 years, intended to deliver managers and publics with practical tools to reduce the vast set of decisions before them as they proactively manage tree species in the face of climate change.

scholarly journals Online Class Scheduling and Faculty Loading System within a Decision Support Framework

2015 ◽  
Vol 6 (1) ◽  
Author(s):  
Eric Perez Ortega ◽  
Moma Dela Torre Ortega ◽  
Darlyne Iligan Brigoli
Keyword(s):  
Decision Support ◽  
Department Heads ◽  
Knowledge Based ◽  
Course Scheduling ◽  
Faculty Teaching ◽  
Decision Support Framework ◽  
Loading System ◽  
Rule Sets ◽  
Class Scheduling ◽  
Time Required

Developing course schedules to accommodate student enrollment needs has been a recurring and complicated task of the department heads each school term. To develop a course schedule connotes an assignment of time intervals for each course offering and optimization of available resources such as classrooms and computer laboratories and subsequently maximize the department faculty inventory and preferences. The study aimed to create a class scheduling and loading system which tackles academic department heads’ responsibilities of establishing well-defined faculty teaching loads. A descriptive-developmental design was utilized using a researcher-made questionnaire and interview. The scheduling and loading system is articulated to allow the defining of teaching assignments to the time slot system by applying knowledge-based approach, appropriate heuristic functions and rule sets to load correct courses to faculty; and allow a search for the best slot on multiple viable slots within the decision-support framework.  Decision support framework facilitates administrative priorities to resolve conflicts on slots representing deviations from the assignment criteria. The result of the study indicated the reduction of time required for course scheduling and the results are more acceptable to faculty loads for the teachers. The study recommends embedding other parameters into the system and continuous improvement and maintenance should be done for the system, adding new constraints and requirements. 

scholarly journals A robust multiple-objective decision-making paradigm based on the water–energy–food security nexus under changing climate uncertainties

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Maedeh Enayati ◽  
Omid Bozorg-Haddad ◽  
Elahe Fallah-Mehdipour ◽  
Babak Zolghadr-Asli ◽  
Xuefeng Chu
Keyword(s):  
Climate Change ◽  
Decision Making ◽  
Food Security ◽  
Decision Support ◽  
Multiple Objective ◽  
Decision Making Process ◽  
Climate Change Projections ◽  
Decision Support Framework ◽  
The Impact

AbstractFrom the perspective of the water–energy–food (WEF) security nexus, sustainable water-related infrastructure may hinge on multi-dimensional decision-making, which is subject to some level of uncertainties imposed by internal or external sources such as climate change. It is important to note that the impact of this phenomenon is not solely limited to the changing behavior patterns of hydro-climatic variables since it can also affect the other pillars of the WEF nexus both directly and indirectly. Failing to address these issues can be costly, especially for those projects with long-lasting economic lifetimes such as hydropower systems. Ideally, a robust plan can tolerate these projected changes in climatic behavior and their associated impacts on other sectors, while maintaining an acceptable performance concerning environmental, socio-economic, and technical factors. This study, thus, aims to develop a robust multiple-objective decision-support framework to address these concerns. In principle, while this framework is sensitive to the uncertainties associated with the climate change projections, it can account for the intricacies that are commonly associated with the WEF security network. To demonstrate the applicability of this new framework, the Karkheh River basin in Iran was selected as a case study due to its critical role in ensuring water, energy, and food security of the region. In addition to the status quo, a series of climate change projections (i.e., RCP 2.6, RCP 4.5, and RCP 8.5) were integrated into the proposed decision support framework as well. Resultantly, the mega decision matrix for this problem was composed of 56 evaluation criteria and 27 feasible alternatives. A TOPSIS/Entropy method was used to select the most robust renovation plan for a hydropower system in the basin by creating a robust and objective weighting mechanism to quantify the role of each sector in the decision-making process. Accordingly, in this case, the energy, food, and environment sectors are objectively more involved in the decision-making process. The results revealed that the role of the social aspect is practically negligible. The results also unveiled that while increasing the power plant capacity or the plant factor would be, seemingly, in favor of the energy sector, if all relevant factors are to be considered, the overall performance of the system might resultantly become sub-optimal, jeopardizing the security of other aspects of the water–energy–food nexus.

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