scholarly journals Using Decision Analysis to Integrate Habitat and Community Values for Coastal Resilience Planning

Author(s):  
David M. Martin ◽  
Jackie A. Specht ◽  
Michelle R. Canick ◽  
Kelly L. Leo ◽  
Kathleen Freeman

AbstractDecision analysis is applied to habitat and community resilience planning in Maryland, USA. Sea level rise is causing wetland loss and increased flooding in coastal areas. A team at The Nature Conservancy analyzed a decision to identify high-value conservation planning units across Maryland’s Lower Eastern Shore. The team selected two fundamental objectives: minimize habitat loss and minimize community flood impacts. Sub-objectives included habitat function, habitat migration potential, critical infrastructure, and social vulnerability. Spatial attributes were selected based on ecological knowledge about habitat and socio-economic knowledge about sustaining populations in flood-prone areas. Seven planning units were developed across the Lower Eastern Shore. Single-attribute value functions determined the overall value of each unit per attribute, whereas multi-attribute value functions determined the overall value of each unit for all fundamental objectives. Sensitivity analysis incorporated data adjustments based on different flood scenarios and unit sizes, and variation in attribute weights associated with the multi-attribute value function. The Pareto efficiency principle revealed tradeoffs between units for habitat protection and management and community engagement and adaptation. Results indicate that four units are Pareto efficient under different sensitivity iterations and they trade off value in the fundamental objectives, whereas one unit provides the highest combined habitat and community value. This research guided thinking about equity in decision making and targeting conservation actions at local scales. The approach and methods can be used to inform conservation decisions in other similar contexts.

Omega ◽  
2019 ◽  
Vol 85 ◽  
pp. 49-67 ◽  
Author(s):  
Fridolin Haag ◽  
Judit Lienert ◽  
Nele Schuwirth ◽  
Peter Reichert

2014 ◽  
Vol 234 (1) ◽  
pp. 221-230 ◽  
Author(s):  
Rudolf Vetschera ◽  
Wolfgang Weitzl ◽  
Elisabeth Wolfsteiner

Water ◽  
2019 ◽  
Vol 11 (3) ◽  
pp. 517 ◽  
Author(s):  
Karin M. de Bruijn ◽  
Carolina Maran ◽  
Mike Zygnerski ◽  
Jennifer Jurado ◽  
Andreas Burzel ◽  
...  

In order to increase the flood resilience of cities (i.e., the ability to cope with flood hazards), it is also crucial to make critical infrastructure functions resilient, since these are essential for urban society. Cities are complex systems with many actors of different disciplines and many interdependent critical infrastructure networks and functions. Common flood risk analysis techniques provide useful information but are not sufficient to obtain a complete overview of the effects of flooding and potential measures to increase flood resilience related to critical infrastructure networks. Therefore, a more comprehensive approach is needed which helps accessing knowledge of actors in a structured way. Fort Lauderdale, Florida, United States has suffered from flood impacts, especially from disruptions in critical infrastructure. This paper shows how shared insight among different sectors and stakeholders into critical infrastructure resilience and potential resilience-enhancing measures was obtained using input from these actors. It also provides a first quantitative indication of resilience, indicated by the potential disruption due to floods and the effect of measures on resilience. The paper contributes to the existing literature on resilience specifically by considering the duration of disruption, the inclusion of critical infrastructure disruption in flood impact analysis, and the step from resilience quantification to measures.


2018 ◽  
Vol 21 ◽  
pp. S220
Author(s):  
C Schey ◽  
M Connolly ◽  
A Volovyk ◽  
O Topachevskyi ◽  
N Kotsopoulos

2018 ◽  
Vol 52 (2 (246)) ◽  
pp. 140-143
Author(s):  
A.A. Gevorgyan ◽  
H.S. Avagyan

This work presents development of a method for multi-criteria decision making under uncertainty conditions based on single-attribute value functions and probabilistic distributions. The values of different criteria are modeled using normal distributions, i.e. the value of the $ i $-th criteria of the $ j $-th option is given by $ x^j_i \sim \mathcal{N} ({\mu}^j_i, {\sigma}^j_i) $ distribution. The method is evaluated and the results are analyzed on a simple example.


Mathematics ◽  
2019 ◽  
Vol 7 (8) ◽  
pp. 661 ◽  
Author(s):  
Shahzaib Ashraf ◽  
Saleem Abdullah ◽  
Lazim Abdullah

This paper aims to resolve the issue of the ranking of the fuzzy numbers in decision analysis, artificial intelligence, and optimization. In the literature, many ideas have been established for the ranking of the fuzzy numbers, and those ideas have some restrictions and limitations. We propose a method based on spherical fuzzy numbers (SFNs) for ranking to overcome the existing restrictions. Further, we investigate the basic properties of SFNs, compare the idea of spherical fuzzy set with the picture fuzzy set, and establish some distance operators, namely spherical fuzzy distance-weighted averaging (SFDWA), spherical fuzzy distance order-weighted averaging (SFDOWA), and spherical fuzzy distance order-weighted average weighted averaging (SFDOWA WA) operators with the attribute weights’ information incompletely described. Further, we design an algorithm to solve decision analysis problems. Finally, to validate the usage and applicability of the established procedure, we assume the child development influence environmental factors problem as a practical application.


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