Climate Impacts on Sustainable Natural Resource Management. Группа авторов
under two different scenarios were calculated. Annual time‐series of land cover maps (2000–2016) and carbon stock reference were used to calculate GHG emissions. The results showed that deforestation was the major contributor to GHG emissions in the study area. Also, REDD+ commitment from the local government proved to be a good step forward in reducing GHG emissions in the area. However, the projected reduction in GHG emissions under the REDD+ scenario was smaller than the target written in the local action plan of REDD+. Thus, the provincial government needs to accelerate the strategies for reducing GHG emissions by restoring degraded forest landscapes, avoiding further deforestation and forest degradation, and making appropriate decisions for the socio‐economic development program. Furthermore, the spatial information of the largest GHG emitters in East Kalimantan, which were caused by forest cover changes, could assist the provincial government in locating planned forest restoration action on the same forest landscapes where deforestation and forest degradation occurred. Some illustrations of GHG emission targets resulting from various decisions were also demonstrated in this study.
Acknowledgement
We would like to thank to the reviewers for improving this manuscript.
Author Contribution
Kiswanto, Martiwi Diah Setiawati and Satoshi Tsuyuki conceptualized the research. Kiswanto as the first author performed the data analysis and wrote the draft paper while Martiwi Diah Setiawati performed a literature review and edited the manuscript. Kiswanto and Martiwi Diah Setiawati contributed equally.
List of Appendix
1.A Sample of transition matrix for calculating the total area of land cover changes in each period.
| t1 | Total (ha) | ||||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| PMF | PSF | SDF | SMF | SSF | PF | ECL | PDA | MDA | DSL | WSL | PRF | SA | TA | PH | OS | FPA | BG | MA | OW | ||||
| t2 | 249.62 | — | — | 1.19 | — | — | — | — | — | — | 0.00 | — | — | — | — | — | — | — | — | — | 250.80 | 250.80 | |
| PMF | — | 5.66 | — | — | 0.01 | — | — | — | — | — | — | 0.03 | — | — | — | — | — | 0.01 | — | — | 5.71 | 5.71 | |
| PSF | — | — | 2.61 | — | — | 0.08 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 2.68 | 2.68 | |
| SDF | — | — | — | 477.85 | — | — | 0.35 | 0.31 | — | 0.06 | 1.59 | — | — | 0.01 | — | — | — | — | 0.03 | 0.06 | 480.26 | 480.26 | |
| SMF | — | — | — | — | 18.50 | — | — | — | — | — | — | 0.08 | — | — | — | — | — | 0.17 | — | — | 18.74 | 18.74 | |
| SSF | — | — | — | — | — | 12.78 | — | — |
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