Putting ecosystem service models to work: conservation, management, and trade-offs

2011 ◽  
pp. 248-263 ◽  
Author(s):  
Stephen Polasky ◽  
Giorgio Caldarone ◽  
T. Ka’eo Duarte ◽  
Joshua Goldstein ◽  
Neil Hannahs ◽  
...  
2015 ◽  
Vol 53 (1) ◽  
pp. 96-105 ◽  
Author(s):  
Justine E. Cordingley ◽  
Adrian C. Newton ◽  
Robert J. Rose ◽  
Ralph T. Clarke ◽  
James M. Bullock

2021 ◽  
Author(s):  
James D. Karimi ◽  
Jim A. Harris ◽  
Ron Corstanje

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.


2017 ◽  
Vol 22 (3) ◽  
Author(s):  
Neil M. Dawson ◽  
Kenneth Grogan ◽  
Adrian Martin ◽  
Ole Mertz ◽  
Maya Pasgaard ◽  
...  

AMBIO ◽  
2018 ◽  
Vol 48 (10) ◽  
pp. 1116-1128 ◽  
Author(s):  
Marie C. Dade ◽  
Matthew G.E. Mitchell ◽  
Clive A. McAlpine ◽  
Jonathan R. Rhodes

2019 ◽  
Vol 105 ◽  
pp. 264-278 ◽  
Author(s):  
S.P. Kearney ◽  
S.J. Fonte ◽  
E. García ◽  
P. Siles ◽  
K.M.A. Chan ◽  
...  

Author(s):  
Tianwei Geng ◽  
Hai Chen ◽  
Di Liu ◽  
Qinqin Shi ◽  
Hang Zhang

Exploring and analyzing the common demands and behavioral responses of different stakeholders is important for revealing the mediating mechanisms of ecosystem service (ES) and realizing the management and sustainable supply of ES. This study took Mizhi County, a poverty-stricken area on the Loess Plateau in China, as an example. First, the main stakeholders, common demands, and behavioral responses in the food provision services were identified. Second, the relationship among stakeholders was analyzed. Finally, this study summarized three types of mediating mechanisms of food provision services and analyzed the influence of the different types of mediating mechanisms. The main conclusions are as follows: (1) Five main stakeholders in the study area were identified: government, farmers, enterprises, cooperatives, and middlemen. (2) Increasing farmers’ income is the common demand of most stakeholders in the study area, and this common demand has different effects on the behavioral responses of different stakeholders. (3) There are three types of mediating mechanisms in the study area: government + farmers mediating corn and mutton, government + enterprises mediating millet, and government + cooperatives mediating apples. On this basis, the effects of the different types of mediating mechanisms on variations in food yield, and trade-offs and synergies in typical townships, were analyzed.


2019 ◽  
Vol 650 ◽  
pp. 2325-2336 ◽  
Author(s):  
Javier Martínez-López ◽  
Kenneth J. Bagstad ◽  
Stefano Balbi ◽  
Ainhoa Magrach ◽  
Brian Voigt ◽  
...  

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