scholarly journals Assessing ecosystem services from multifunctional trees in pastures using Bayesian belief networks

2016 ◽  
Vol 18 ◽  
pp. 165-174 ◽  
Author(s):  
David N. Barton ◽  
Tamara Benjamin ◽  
Carlos R. Cerdán ◽  
Fabrice DeClerck ◽  
Anders L. Madsen ◽  
...  
Keyword(s):  
Ecosystem Services ◽  
Bayesian Belief Networks ◽  
Belief Networks

Exploring ecosystem service issues across diverse knowledge domains using Bayesian Belief Networks

2011 ◽  
Vol 35 (5) ◽  
pp. 681-699 ◽  
Author(s):  
Roy Haines-Young
Keyword(s):  
Ecosystem Services ◽  
Social Values ◽  
Early Stage ◽  
Bayesian Belief Networks ◽  
Decision Makers ◽  
Belief Networks ◽  
Knowledge Domains ◽  
Study Materials ◽  
Shared Social Values

The analysis of the relationships between people and nature is complex, because it involves bringing together insights from a range of disciplines, and, when stakeholders are involved, the perspectives and values of different interest groups. Although it has been suggested that analytical-deliberate approaches may be useful in dealing with some of this complexity, the development of methods is still at an early stage. This is particularly so in relation to debates around the concept of ecosystem services where biophysical, social and economic insights need to be integrated in ways that can be accessed by decision-makers. The paper draws on case studies to examine the use of Bayesian Belief Networks (BBNs) as a means of implementing analytical-deliberative approaches in relation to mapping ecosystem services and modelling scenario outcomes. It also explores their use as a tool for representing individual and group values. It is argued that when linked with GIS techniques BBNs allow mapping and modelling approaches rapidly to be developed and tested in an efficient and transparent way, and that they are a valuable scenario-building tool. The case-study materials also show that BBNs can support multicriteria forms of deliberative analysis that can be used to capture stakeholder opinions so that different perspectives can be compared and shared social values identified.

scholarly journals Operationalizing an ecosystem services-based approach using Bayesian Belief Networks: An application to riparian buffer strips

2015 ◽  
Vol 110 ◽  
pp. 15-27 ◽  
Author(s):  
Alistair McVittie ◽  
Lisa Norton ◽  
Julia Martin-Ortega ◽  
Ioanna Siameti ◽  
Klaus Glenk ◽  
...  
Keyword(s):  
Ecosystem Services ◽  
Bayesian Belief Networks ◽  
Riparian Buffer ◽  
Belief Networks ◽  
Buffer Strips ◽  
Riparian Buffer Strips

scholarly journals Integrating mixed-cell CA model and Bayesian belief networks to optimize ecosystem services for ecological restoration and conservation

2021 ◽  
Author(s):  
Shuang Zhou ◽  
Li Peng
Keyword(s):  
Land Use ◽  
Ecosystem Services ◽  
Ecological Restoration ◽  
Land Development ◽  
Bayesian Belief Networks ◽  
The State ◽  
Belief Networks ◽  
Mixed Cell ◽  
Development Scenarios ◽  
Ca Model

The complexity and uncertainty of land use and environmental factors pose challenges to the management decisions of ecological restoration and conservation.We integrated the mixed-cell CA model and Bayesian belief networks to develop an innovative method for optimizing ecosystem services under different land development scenarios, including consideration of the uncertainty and variability of factors.The southern region of Sichuan Province, China, was selected as an example.We first established three development scenarios between 2015 and 2035, namely, natural development scenario (NDS), ecological protection scenario (EPS), and cultivated land protection scenario (CLPS).The MCCA model was utilized to simulate the land use pattern in 2035 under different scenarios.We then construced a BBN-based model to investigate the carbon sequestration, grain supply, soil conservation, habitat quality, and water yield in 2035 under uncertain scenarios.After the sensitivity analysis and evaluation of the model, we determined the state combination of influential factors at various ecosystem service levels and the ecological restoration and conservation key areas.The obtained result showed that the key influencing factors impacting the ecosystem services level included NPP, Slope, forestland and ET, and the state combination corresponding to the highest level of ecosystem services was predominantly distributed in regions with the highest NPP, the highest Slope, the highest forestland area and low ET.Based on this finding, we proposed some suggestions for ecological restoration and conservation of key areas.This model considers uncertainties and is capable of providing scientific recommendations on restoration and conservation; therefore, it can serve as an effective tool to assist stakeholders in making decisions.

Using Bayesian network models to incorporate uncertainty in the economic analysis of pollution abatement measures under the water framework directive

2005 ◽  
Vol 5 (6) ◽  
pp. 95-104 ◽  
Author(s):  
D.N. Barton ◽  
T. Saloranta ◽  
T.H. Bakken ◽  
A. Lyche Solheim ◽  
J. Moe ◽  
...  
Keyword(s):  
Water Quality ◽  
At Risk ◽  
Economic Valuation ◽  
Pollution Abatement ◽  
Network Models ◽  
Cost Effective ◽  
Bayesian Belief Networks ◽  
Probabilistic Interpretation ◽  
Belief Networks ◽  
Benefit Cost Analysis

The evaluation of water bodies “at risk” of not achieving the Water Framework Directive's (WFD) goal of “good status” begs the question of how big a risk is acceptable before a programme of measures should be implemented. Documentation of expert judgement and statistical uncertainty in pollution budgets and water quality modelling, combined with Monte Carlo simulation and Bayesian belief networks, make it possible to give a probabilistic interpretation of “at risk”. Combined with information on abatement costs, a cost-effective ranking of measures based on expected costs and effect can be undertaken. Combined with economic valuation of water quality, the definition of “disproportionate cost” of abatement measures compared to benefits of achieving “good status” can also be given a probabilistic interpretation. Explicit modelling of uncertainty helps visualize where research and consulting efforts are most critical for reducing uncertainty. Based on data from the Morsa catchment in South-Eastern Norway, this paper discusses the relative merits of using Bayesian belief networks when integrating biophysical modelling results in the benefit-cost analysis of derogations and cost-effectiveness ranking of abatement measures under the WFD.

scholarly journals Using Bayesian Belief Networks to assess the influence of landscape connectivity on ecosystem service trade-offs and synergies in urban landscapes in the UK

2021 ◽  
Author(s):  
James D. Karimi ◽  
Jim A. Harris ◽  
Ron Corstanje
Keyword(s):  
Functional Connectivity ◽  
Ecosystem Service ◽  
Urban Areas ◽  
Landscape Connectivity ◽  
Structural Characteristics ◽  
Bird Species ◽  
Bayesian Belief Networks ◽  
Belief Networks ◽  
Patch Area ◽  
Trade Offs

Abstract Context Landscape connectivity is assumed to influence ecosystem service (ES) trade-offs and synergies. However, empirical studies of the effect of landscape connectivity on ES trade-offs and synergies are limited, especially in urban areas where the interactions between patterns and processes are complex. Objectives The objectives of this study were to use a Bayesian Belief Network approach to (1) assess whether functional connectivity drives ES trade-offs and synergies in urban areas and (2) assess the influence of connectivity on the supply of ESs. Methods We used circuit theory to model urban bird flow of P. major and C. caeruleus at a 2 m spatial resolution in Bedford, Luton and Milton Keynes, UK, and Bayesian Belief Networks (BBNs) to assess the sensitivity of ES trade-offs and synergies model outputs to landscape and patch structural characteristics (patch area, connectivity and bird species abundance). Results We found that functional connectivity was the most influential variable in determining two of three ES trade-offs and synergies. Patch area and connectivity exerted a strong influence on ES trade-offs and synergies. Low patch area and low to moderately low connectivity were associated with high levels of ES trade-offs and synergies. Conclusions This study demonstrates that landscape connectivity is an influential determinant of ES trade-offs and synergies and supports the conviction that larger and better-connected habitat patches increase ES provision. A BBN approach is proposed as a feasible method of ES trade-off and synergy prediction in complex landscapes. Our findings can prove to be informative for urban ES management.

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