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Quantification of global forest change has been lacking despite the recognized importance of forest ecosystem services. In this study, Earth observation satellite data were used to map global forest loss (2.3 million square kilometers) and gain (0.8 million square kilometers) from 2000 to 2012 at a spatial resolution of 30 meters. The tropics were the only climate domain to exhibit a trend, with forest loss increasing by 2101 square kilometers per year. Brazil's well-documented reduction in deforestation was offset by increasing forest loss in Indonesia, Malaysia, Paraguay, Bolivia, Zambia, Angola, and elsewhere. Intensive forestry practiced within subtropical forests resulted in the highest rates of forest change globally. Boreal forest loss due largely to fire and forestry was second to that in the tropics in absolute and proportional terms. These results depict a globally consistent and locally relevant record of forest change.

Tropek et al . critique the Hansen et al . global forest loss paper in terms of its utility and accuracy. Both criticisms suffer from a miscomprehension of the definition of forest employed as well as the requirements of product validation. Utility of the product is enhanced through its integration with forest type, carbon stock, protected area status, and other ancillary data.

Tropical forests provide global climate regulation ecosystem services and their clearing is a significant source of anthropogenic greenhouse gas (GHG) emissions and resultant radiative forcing of climate change. However, consensus on pan-tropical forest carbon dynamics is lacking. We present a new estimate that employs recommended good practices to quantify gross tropical forest aboveground carbon (AGC) loss from 2000 to 2012 through the integration of Landsat-derived tree canopy cover, height, intactness and forest cover loss and GLAS-lidar derived forest biomass. An unbiased estimate of forest loss area is produced using a stratified random sample with strata derived from a wall-to-wall 30 m forest cover loss map. Our sample-based results separate the gross loss of forest AGC into losses from natural forests (0.59 PgC yr−1) and losses from managed forests (0.43 PgC yr−1) including plantations, agroforestry systems and subsistence agriculture. Latin America accounts for 43% of gross AGC loss and 54% of natural forest AGC loss, with Brazil experiencing the highest AGC loss for both categories at national scales. We estimate gross tropical forest AGC loss and natural forest loss to account for 11% and 6% of global year 2012 CO2 emissions, respectively. Given recent trends, natural forests will likely constitute an increasingly smaller proportion of tropical forest GHG emissions and of global emissions as fossil fuel consumption increases, with implications for the valuation of co-benefits in tropical forest conservation.

A novel approach for satellite-based comprehensive national tree cover change assessment was developed and applied in Bangladesh, a country where trees outside of forests play an important role in the national economy and carbon sequestration. Tree cover change area was quantified using the integration of wall-to-wall Landsat-based mapping with a higher spatial resolution sample-based assessment. The total national tree canopy cover area was estimated as 3165 500 ± 186 600 ha in the year 2000, with trees outside forests making up 54% of total canopy cover. Total tree canopy cover increased by 135 700 (± 116 600) ha (4.3%) during the 2000-2014 time interval. Bangladesh exhibits a national tree cover dynamic where net change is rather small, but gross dynamics significant and variable by forest type. Despite the overall gain in tree cover, results revealed the ongoing clearing of natural forests, especially within the Chittagong hill tracts. While forests decreased their tree cover area by 83 600 ha, the trees outside forests (including tree plantations, village woodlots, and agroforestry) increased their canopy area by 219 300 ha. Our results demonstrated method capability to quantify tree canopy cover dynamics within a fine-scale agricultural landscape. Our approach for comprehensive monitoring of tree canopy cover may be recommended for operational implementation in Bangladesh and other countries with significant tree cover outside of forests.

Agricultural intensification and forest conservation are often seen as incompatible. Agricultural interventions can help boost food security for poor rural communities but in certain cases can exacerbate deforestation, known as the rebound effect. We tested whether coupling agricultural interventions with participatory forest zoning could improve food security and promote forest conservation in the Democratic Republic of the Congo. Simple agricultural interventions led to a >60% increase in cassava yields and a spill-over effect of improved cassava variety uptake in non-intervention zones. Household surveys conducted at the end of the 8 year project implementation period revealed that households that received agricultural interventions had more favorable attitudes toward forest zoning and conservation. The surveys also showed that farmers in the intervention domain practiced less land-intensive field and fallow management strategies compared to those practiced in the non-intervention domain. However, an 18 year time series analysis of Landsat satellite data revealed that agricultural expansion persisted in areas both with and without intervention assistance, and there is risk of a rebound effect. Approximately 70% of the tree cover loss that occurred outside of the agricultural areas was located within a 3 km buffer zone surrounding the outermost edges of the agricultural areas, which suggested that the majority of tree cover loss was caused by agricultural expansion. Within that 3 km buffer, average annual tree cover loss during the post-intervention period was higher in the intervention domain compared to the non-intervention domain (0.17% yr −1 compared to 0.11% yr −1 respectively, p < 0.001), suggesting risk of a rebound effect. The disconnection between household perceptions of zoning adherence and actual behavior indicates the importance of strengthening governance structures for community-based monitoring and enforcement.

Primary forest extent, loss and degradation within the Democratic Republic of the Congo (DRC) were quantified from 2000 to 2010 by combining directly mapped forest cover extent and loss data (CARPE) with indirectly mapped forest degradation data (intact forest landscapes, IFL). Landsat data were used to derive both map inputs, and data from the GLAS (Geoscience Laser Altimetry System) sensor were employed to validate the discrimination of primary intact and primary degraded forests. In the year 2000, primary humid tropical forests occupied 104 455 kha of the country, with 61% of these forests classified as intact. From 2000 to 2010, 1.02% of primary forest cover was lost due to clearing, and almost 2% of intact primary forests were degraded due to alteration and fragmentation. While primary forest clearing increased by a factor of two between 2000-2005 and 2005-2010, the degradation of intact forests slightly decreased. Fragmentation and selective logging were the leading causes of intact forest degradation, accounting for 91% of IFL area change. The 10 year forest degradation rate within designated logging permit areas was 3.8 times higher compared to other primary forest areas. Within protected areas the forest degradation rate was 3.7 times lower than in other primary forest areas. Forest degradation rates were high in the vicinity of major urban areas. Given the observed forest degradation rates, we infer that the degradation of intact forests could increase up to two-fold over the next decade.

Recent advances in remote sensing enable the mapping and monitoring of carbon stocks without relying on extensive in situ measurements. The Democratic Republic of the Congo (DRC) is among the countries where national forest inventories (NFI) are either non-existent or out of date. Here we demonstrate a method for estimating national-scale gross forest aboveground carbon (AGC) loss and associated uncertainties using remotely sensed-derived forest cover loss and biomass carbon density data. Lidar data were used as a surrogate for NFI plot measurements to estimate carbon stocks and AGC loss based on forest type and activity data derived using time-series multispectral imagery. Specifically, DRC forest type and loss from the FACET (Forêts d'Afrique Centrale Evaluées par Télédétection) product, created using Landsat data, were related to carbon data derived from the Geoscience Laser Altimeter System (GLAS). Validation data for FACET forest area loss were created at a 30-m spatial resolution and compared to the 60-m spatial resolution FACET map. We produced two gross AGC loss estimates for the DRC for the last decade (2000-2010): a map-scale estimate (53.3 ± 9.8 Tg C yr−1) accounting for whole-pixel classification errors in the 60-m resolution FACET forest cover change product, and a sub-grid estimate (72.1 ± 12.7 Tg C yr−1) that took into account 60-m cells that experienced partial forest loss. Our sub-grid forest cover and AGC loss estimates, which included smaller-scale forest disturbances, exceed published assessments. Results raise the issue of scale in forest cover change mapping and validation, and subsequent impacts on remotely sensed carbon stock change estimation, particularly for smallholder dominated systems such as the DRC.

Dramatic political and economic changes in Eastern European countries following the dissolution of the “Eastern Bloc” and the collapse of the Soviet Union greatly affected land-cover and land-use trends. In particular, changes in forest cover dynamics may be attributed to the collapse of the planned economy, agricultural land abandonment, economy liberalization, and market conditions. However, changes in forest cover are hard to quantify given inconsistent forest statistics collected by different countries over the last 30 years. The objective of our research was to consistently quantify forest cover change across Eastern Europe from 1985 until 2012 using the complete Landsat data archive. We developed an algorithm for processing imagery from different Landsat platforms and sensors (TM and ETM+), aggregating these images into a common set of multi-temporal metrics, and mapping annual gross forest cover loss and decadal gross forest cover gain. Our results show that forest cover area increased from 1985 to 2012 by 4.7% across the region. Average annual gross forest cover loss was 0.41% of total forest cover area, with a statistically significant increase from 1985 to 2012. Most forest disturbance recovered fast, with only 12% of the areas of forest loss prior to 1995 not being recovered by 2012. Timber harvesting was the main cause of forest loss. Logging area declined after the collapse of socialism in the late 1980s, increased in the early 2000s, and decreased in most countries after 2007 due to the global economic crisis. By 2012, Central and Baltic Eastern European countries showed higher logging rates compared to their Western neighbours. Comparing our results with official forest cover and change estimates showed agreement in total forest area for year 2010, but with substantial disagreement between Landsat-based and official net forest cover area change. Landsat-based logging areas exhibit strong relationship with reported roundwood production at national scale. Our results allow national and sub-national level analysis of forest cover extent, change, and logging intensity and are available on-line as a baseline for further analyses of forest dynamics and its drivers.

Protection of large natural forest landscapes is a highly important task to help fulfill different international strategic initiatives to protect forest biodiversity, to reduce carbon emissions from deforestation and forest degradation, and to stimulate sustainable forest management practices. This paper introduces a new approach for mapping large intact forest landscapes (IFL), defined as an unbroken expanse of natural ecosystems within areas of current forest extent, without signs of significant human activity, and having an area of at least 500 km2. We have created a global IFL map using existing fine-scale maps and a global coverage of high spatial resolution satellite imagery. We estimate the global area of IFL within the current extent of forest ecosystems (forest zone) to be 13.1 million km² or 23.5% of the forest zone. The vast majority of IFL are found in two biomes: Dense Tropical and Subtropical Forests (45.3%) and Boreal Forests (43.8%). The lowest proportion of IFL is found in Temperate Broadleaf and Mixed Forests. The IFL exist in 66 of the 149 countries that together make up the forest zone. Three of them—Canada, Russia, and Brazil—contain 63.8% of the total IFL area. Of the world’s IFL area, 18.9% has some form of protection, but only 9.7% is strictly protected, i.e., belongs to IUCN protected areas categories I–III. The world IFL map presented here is intended to underpin the development of a general strategy for nature conservation at the global and regional scales. It also defines a baseline for monitoring deforestation and forest degradation that is well suited for use with operational and cost-effective satellite data. All project results and IFL maps are available on a dedicated web site (http://www.intactforests.org).