Literature DB >> 30022379

Scenario modeling for spatial-temporal change detection of carbon storage and sequestration in a forested landscape in Northern Iran.

Ardavan Zarandian1, Jalil Badamfirouz2, Roya Musazadeh2, Alireza Rahmati3, Seyedeh Bahareh Azimi3.   

Abstract

The present study was conducted, based on scenario modeling approach, in the Do-hezar and Se-hezar forested landscape in the Mazandaran Province in Northern Iran in order to detect spatial-temporal changes of carbon storage and sequestration in four different carbon pools, i.e., aboveground and belowground biomasses, dead organic matter, and organic soils. For this purpose, firstly, the changing trend of land use/land cover (LULC) was detected by analyzing and comparing remotely sensed data of the landscape during the period of 1984-2016. Then, the impacts of future LULC changes on carbon storage and sequestration were predicted and valued using the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model under two future plausible scenarios of business as usual (BAU) and balanced development (BD). According to the results of BAU scenario, continuation of the current trend will lead to a significant reduction in the carbon sequestration and a huge amount of social cost due to the loss of carbon stored in the landscape and its release to the atmosphere. The BD scenario which refers to the principled and under control development of human settlements simultaneously with forest conservational and restoration activities, could potentially reverse the downtrend of carbon sequestration service and avoid future socioeconomic costs, hence add to the economic value of the forest landscape in terms of providing a better sink for carbon storage. The results of this research can facilitate the quantitative and accurate assessment of carbon storage and sequestration relying on more precise biophysical and economic data as well as provide insight for effective land-use planning.

Entities:  

Keywords:  Carbon spatial-temporal dynamics; Ecosystem service; Hyrcanian forest; Iran

Mesh:

Substances:

Year:  2018        PMID: 30022379     DOI: 10.1007/s10661-018-6845-6

Source DB:  PubMed          Journal:  Environ Monit Assess        ISSN: 0167-6369            Impact factor:   2.513


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