Rapidly Accelerating Deforestation in Cambodia’s Mekong River Basin: A Comparative Analysis of Spatial Patterns and Drivers
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Mapping Tree Cover and Deforestation from 1992–2017
2.3. Statistical Model to Predict Drivers of Deforestation
2.3.1. Data Variables
2.3.2. Statistical Modeling of Drivers of Deforestation
3. Results
3.1. Mapping Tree Cover from 1992–2017
3.2. Deforestation Mapping (1993–2017)
3.3. Statistical Modeling of Deforestation
4. Discussion
4.1. Deforestation Patterns over Time
4.2. Forest Loss in Protected Areas and Community Forests
4.3. Forest Loss in Floodplains
4.4. Spatial Drivers of Deforestation
5. Conclusions
Author Contributions
Funding
Conflicts of Interest
Appendix A
References
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Variable Group | Variable Name | Variable Description | Data Source |
---|---|---|---|
Socio-economic | Population density | Total number of people per grid-cell (worldpop) | Worldpop data after 2000, and SEDAC data for the 1990s |
Roads | Euclidean Distance to roads | Open Development Cambodia (ODC) | |
Roads-density | |||
Land cover | Urban | SERVIR Mekong | |
Agricultural Land | SERVIR Mekong | ||
Protected Areas | ODC | ||
Topo-edaphic | Topography | Slope | DEM derived from shuttle radar topography mission (SRTM) at approximately 90-m resolution |
Aspect | |||
Soil | Clay (0–2 micrometer mass fraction in % at 1 m depth 1 m) | [67] | |
Sand (0–2 micrometer mass fraction in % at 1 m depth) | [67] | ||
Climatic | Bioclimatic variables | Annual mean temperature | Global Climate Data |
Mean Diurnal range | Global Climate Data | ||
Isothermality | Global Climate Data | ||
Temperature seasonality | Global Climate Data | ||
Maximum temperature of warmest month | Global Climate Data | ||
Minimum temperature of coldest month | Global Climate Data | ||
Temperature annual range | Global Climate Data | ||
Annual precipitation | Global Climate Data | ||
Precipitation of wettest month | Global Climate Data | ||
Precipitation of driest month | Global Climate Data | ||
Precipitation seasonality | Global Climate Data | ||
Hydropower Development | Hydropower Dams | Euclidean Distance to dams | ODC & [23] |
Inundation layer | Inundation (Yes/No) | Global Surface water website | |
Fragmentation | Landscape metrics | Percentage of landscapes (PLAND) | FRAGSTATS |
Perimeter-area fractal dimension (PAFRAC) | FRAGSTATS | ||
Edge density (ED) | FRAGSTATS | ||
Euclidean nearest neighbor distance (ENN_MN) | FRAGSTATS | ||
Patch density (PD) | FRAGSTATS | ||
Interspersion juxtaposition index (IJI) | FRAGSTATS | ||
Proportion of like adjacencies (PLADJ) | FRAGSTATS | ||
Aggregation index (AI) | FRAGSTATS | ||
Clumpiness (CLUMPY) | FRAGSTATS |
Statistic | 50% Withheld Data | 2005 | 2010 | 2015 |
---|---|---|---|---|
Root Mean Square Error (RMSE in %) | 18.29 | 27.83 | 20.06 | 26.12 |
Percent Bias (PBIAS) | 1.10 | −11.30 | −13.4 | −5.5 |
Pearson Correlation (r) | 0.90 | 0.75 | 0.88 | 0.78 |
R-squared | 0.80 | 0.56 | 0.77 | 0.61 |
Slope of the linear model | 0.81 | 0.66 | 0.79 | 0.72 |
Metrics | Cambodia 3S Basin | Cambodia Only | 3S Basin Only | Tonle Sap Only |
---|---|---|---|---|
Accuracy (%) | 71 | 72 | 70 | 78 |
Kappa value | 0.36 | 0.40 | 0.34 | 0.58 |
Sensitivity | 0.81 | 0.79 | 0.81 | 0.75 |
Specificity | 0.54 | 0.60 | 0.53 | 0.82 |
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Lohani, S.; Dilts, T.E.; Weisberg, P.J.; Null, S.E.; Hogan, Z.S. Rapidly Accelerating Deforestation in Cambodia’s Mekong River Basin: A Comparative Analysis of Spatial Patterns and Drivers. Water 2020, 12, 2191. https://doi.org/10.3390/w12082191
Lohani S, Dilts TE, Weisberg PJ, Null SE, Hogan ZS. Rapidly Accelerating Deforestation in Cambodia’s Mekong River Basin: A Comparative Analysis of Spatial Patterns and Drivers. Water. 2020; 12(8):2191. https://doi.org/10.3390/w12082191
Chicago/Turabian StyleLohani, Sapana, Thomas E. Dilts, Peter J. Weisberg, Sarah E. Null, and Zeb S. Hogan. 2020. "Rapidly Accelerating Deforestation in Cambodia’s Mekong River Basin: A Comparative Analysis of Spatial Patterns and Drivers" Water 12, no. 8: 2191. https://doi.org/10.3390/w12082191