Table 1.
Key terminology used in the study.
Fig 1.
Aggregated (A-B) and converted (C-D) datasets used for the forest loss analyses.
A) Forest extent in percentage of grid area at 1 km resolution, based on Global Forest Change (GFC) data [5]; B) Forest loss in percentage of grid area at 1 km resolution, based on GCF data [5]; C) Protected areas based on World Database of Protected Areas (WDPA) [30], converted to 1 km resolution; and D) Large Intact Forest Landscapes (IFLs) based on dataset by Potapov et al [20], converted to 1 km resolution.
Table 2.
A description of the datasets used in this study.
GFC stands for Global Forest Change dataset.
Table 3.
The socio-economic indicators used in the regression analysis.
The indicators were used as independent variables in the assessment of the forest loss drivers with Weighted Least-Squares (WLS) regression analysis.
Table 4.
Forest extent in 2000 and its loss over the period of 2000–2012.
The forest extent and loss are calculated for geographical regions in absolute [103 km2] and relative values [%].
Fig 2.
Absolute and relative forest extent by country in year 2000.
Absolute forest extents (left column) are presented in km2 and relative forest extents (right column) are in %. A and B) Total forest extent; C and D) Protected forest extent; E and F) Intact forest extent; G and H) Protected intact forest extent.
Fig 3.
Absolute and relative forest losses by country between 2000 and 2012.
Absolute forest losses (left column) are presented in km2 and relative forest losses (right column) are in %. A and B) Total forest loss; C and D) Loss in protected forests; E and F) Loss in intact forest; G and H) Loss in protected intact forests.
Fig 4.
Clustering of countries by their forest loss patterns.
A) country clusters based on absolute and relative losses in total and protected forest; and B) country clusters based on intact and protected intact forest. The cluster characteristics are illustrated by radar charts, of which radii represent the variables used in the clustering. The absolute range in each variable is given next to the variables. The cluster centroids on each variable are plotted on the radii, and these centroids are connected with lines. The countries within each cluster are mapped above the corresponding radar chart and the colours both, in the radar charts and their corresponding maps, indicate the cluster in question.
Fig 5.
Comparison of forest loss between different forest types: A) Anomaly ratio for loss in protected forest and loss in non-protected forest; B) Anomaly ratio for loss in intact forest and loss in non-intact forest; C) Anomaly ratio for loss in protected intact forest and loss of non-protected intact forest (anomaly ratio <0 (>0) indicates that forest loss is lower (higher) in the protected forest type than in the non-protected forest type).
Note: all the anomalies were calculated with relative losses.
Table 5.
The associations of common socio-economic parameters to forest loss between 2000–2012.
The four WLS regression models have each a different dependent variable: (a) relative total forest loss, (b) relative loss in protected forest, (c) relative loss in intact forest, and (d) relative loss in protected intact forest. The weight used in the regression for the forest loss measures was the total forest extent in question. Standardised beta coefficient (B) is given for each independent variable included in each of the four models. The independent variables are explained in Table 3. The country specific data are given in S1 Table and S2 Table of the supplementary.