2017
DOI: 10.1016/j.landusepol.2016.12.003
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Modeling of ecosystem services informs spatial planning in lands adjacent to the Sarvelat and Javaherdasht protected area in northern Iran

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Cited by 46 publications
(22 citation statements)
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“…A particular area of interest has been the development and improvement of predictive simulation models, such as the agent-based model (Matthews et al, 2007;Yuan et al, 2017), the cellular automata model and its evolved models based on grid neighborhood relationship analysis (Grinblat et al, 2016;Van Vliet et al, 2017), or the dynamics of land system model and state-and-transition simulation model based on analyses of changes in land system structures and spatial configuration succession (Wilson et al, 2016;Daniel et al, 2016;Najmuddin et al, 2017). Using these simulation models, it is possible to construct rational scenarios for different sustainability objectives, such as maximizing economic effects (Wu et al, 2012), minimizing pollutant emissions or environmental impacts (Bohnes et al, 2017;Degraeuwe et al, 2017), prioritizing ecological security (Brunner et al, 2017;Eitelberg et al, 2016), limiting climate change and carbon emissions (Anaya-Romero et al, 2015;Prestele et al, 2017), as well as for other sustainability scenarios, such as water resources (Proskuryakova et al, 2018), agricultural production (Chaudhary et al, 2018;Krasa et al, 2010;Van Vliet et al, 2017), or environmental protection (Najmuddin et al,2017;Zarandian et al, 2017). Obviously, most of these models are based on historical or current scenarios, and they assume consistent historical trajectories and development statuses, which can be problematic for developing countries with large-scale and disorderly land development (Fan et al, 2018).…”
Section: Introductionmentioning
confidence: 99%
“…A particular area of interest has been the development and improvement of predictive simulation models, such as the agent-based model (Matthews et al, 2007;Yuan et al, 2017), the cellular automata model and its evolved models based on grid neighborhood relationship analysis (Grinblat et al, 2016;Van Vliet et al, 2017), or the dynamics of land system model and state-and-transition simulation model based on analyses of changes in land system structures and spatial configuration succession (Wilson et al, 2016;Daniel et al, 2016;Najmuddin et al, 2017). Using these simulation models, it is possible to construct rational scenarios for different sustainability objectives, such as maximizing economic effects (Wu et al, 2012), minimizing pollutant emissions or environmental impacts (Bohnes et al, 2017;Degraeuwe et al, 2017), prioritizing ecological security (Brunner et al, 2017;Eitelberg et al, 2016), limiting climate change and carbon emissions (Anaya-Romero et al, 2015;Prestele et al, 2017), as well as for other sustainability scenarios, such as water resources (Proskuryakova et al, 2018), agricultural production (Chaudhary et al, 2018;Krasa et al, 2010;Van Vliet et al, 2017), or environmental protection (Najmuddin et al,2017;Zarandian et al, 2017). Obviously, most of these models are based on historical or current scenarios, and they assume consistent historical trajectories and development statuses, which can be problematic for developing countries with large-scale and disorderly land development (Fan et al, 2018).…”
Section: Introductionmentioning
confidence: 99%
“…In most of above models, spatial and temporal evolution rules are applied to simulate historical or current scenarios, and key development parameters are adjusted to identify the differences among various scenarios, although they are insufficient to diagnose deviation (s) caused by land development policies. However, reasonable scenarios from different dimensions can be constructed by these simulation models, such as maximizing economic effects (Wu, Peng, Zhang, Skitmore, & Song, ); minimizing pollutant emissions or environmental impacts (Bohnes, Gregg, & Laurent, ; Degraeuwe et al, ; Manuel‐Navarrete & Pelling, ); prioritizing ecological protection (Brunner, Huber, & Grêt‐Regamey, ; Eitelberg, van Vliet, Doelman, Stehfest, & Verburg, ); and constraining climate change and carbon emissions (Anaya‐Romero et al, ; Prestele et al, ) as well as sustainable scenarios for relatively singular systems such as water resource systems (Proskuryakova, Saritas, & Sivaev, ), agricultural production systems (Krasa, Dostal, Vrana, & Plocek, ; van Vliet et al, ), and ecological conservation systems (Najmuddin et al, ; Zarandian et al, ). In policy study, those scenario simulation methods could primarily be applied to analyze a single policy dimension or to compare scenarios from different dimensions, but it is difficult to use these models to determine the reasonableness of a policy and even more challenging to quantify the policy deviation.…”
Section: Introductionmentioning
confidence: 99%
“…Similar issues in other protected areas in Iran have resulted in increased conflict between local people and protected area managers (Zarandian et al, 2017). For example, Mirkarimi in his study on Golestan National Park, Iran, found that a lack of clear boundaries and natural borders resulted in unintentional land clearing of the park's land by local residents.…”
Section: Discussionmentioning
confidence: 99%
“…Development based on the protected area attractions can create an opportunity to benefit both the community and biodiversity conservation (López-Rodríguez & Rosado, 2017). It was shown in other studies in Iran that considering all stakeholders' interests can result in achieving both local community development and conservation goals (Zarandian et al, 2017). It is also argued that DOE has been more successful in solving environmental issues when involved in collaboration with other government bodies (Calabrese et al, 2008).…”
Section: Discussionmentioning
confidence: 99%
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