The carbon sink of secondary and degraded humid tropical forests.

The globally important carbon sink of intact, old-growth tropical humid forests is declining because of climate change, deforestation and degradation from fire and logging1-3. Recovering tropical secondary and degraded forests now cover about 10% of the tropical forest area4, but how much carbon they accumulate remains uncertain. Here we quantify the aboveground carbon (AGC) sink of recovering forests across three main continuous tropical humid regions: the Amazon, Borneo and Central Africa5,6. On the basis of satellite data products4,7, our analysis encompasses the heterogeneous spatial and temporal patterns of growth in degraded and secondary forests, influenced by key environmental and anthropogenic drivers. In the first 20 years of recovery, regrowth rates in Borneo were up to 45% and 58% higher than in Central Africa and the Amazon, respectively. This is due to variables such as temperature, water deficit and disturbance regimes. We find that regrowing degraded and secondary forests accumulated 107 Tg C year-1 (90-130 Tg C year-1) between 1984 and 2018, counterbalancing 26% (21-34%) of carbon emissions from humid tropical forest loss during the same period. Protecting old-growth forests is therefore a priority. Furthermore, we estimate that conserving recovering degraded and secondary forests can have a feasible future carbon sink potential of 53 Tg C year-1 (44-62 Tg C year-1) across the main tropical regions studied.

Declining Amazon biomass due to deforestation and subsequent degradation losses exceeding gains.

In the Amazon, deforestation and climate change lead to increased vulnerability to forest degradation, threatening its existing carbon stocks and its capacity as a carbon sink. We use satellite L-Band Vegetation Optical Depth (L-VOD) data that provide an integrated (top-down) estimate of biomass carbon to track changes over 2011-2019. Because the spatial resolution of L-VOD is coarse (0.25°), it allows limited attribution of the observed changes. We therefore combined high-resolution annual maps of forest cover and disturbances with biomass maps to model carbon losses (bottom-up) from deforestation and degradation, and gains from regrowing secondary forests. We show an increase of deforestation and associated degradation losses since 2012 which greatly outweigh secondary forest gains. Degradation accounted for 40% of gross losses. After an increase in 2011, old-growth forests show a net loss of above-ground carbon between 2012 and 2019. The sum of component carbon fluxes in our model is consistent with the total biomass change from L-VOD of 1.3 Pg C over 2012-2019. Across nine Amazon countries, we found that while Brazil contains the majority of biomass stocks (64%), its losses from disturbances were disproportionately high (79% of gross losses). Our multi-source analysis provides a pessimistic assessment of the Amazon carbon balance and highlights the urgent need to stop the recent rise of deforestation and degradation, particularly in the Brazilian Amazon.

A map of the extent and year of detection of oil palm plantations in Indonesia, Malaysia and Thailand.

In recent decades, global oil palm production has shown an abrupt increase, with almost 90% produced in Southeast Asia alone. To understand trends in oil palm plantation expansion and for landscape-level planning, accurate maps are needed. Although different oil palm maps have been produced using remote sensing in the past, here we use Sentinel 1 imagery to generate an oil palm plantation map for Indonesia, Malaysia and Thailand for the year 2017. In addition to location, the age of the oil palm plantation is critical for calculating yields. Here we have used a Landsat time series approach to determine the year in which the oil palm plantations are first detected, at which point they are 2 to 3 years of age. From this, the approximate age of the oil palm plantation in 2017 can be derived.

Persistent collapse of biomass in Amazonian forest edges following deforestation leads to unaccounted carbon losses.

Deforestation is the primary driver of carbon losses in tropical forests, but it does not operate alone. Forest fragmentation, a resulting feature of the deforestation process, promotes indirect carbon losses induced by edge effect. This process is not implicitly considered by policies for reducing carbon emissions in the tropics. Here, we used a remote sensing approach to estimate carbon losses driven by edge effect in Amazonia over the 2001 to 2015 period. We found that carbon losses associated with edge effect (947 Tg C) corresponded to one-third of losses from deforestation (2592 Tg C). Despite a notable negative trend of 7 Tg C year-1 in carbon losses from deforestation, the carbon losses from edge effect remained unchanged, with an average of 63 ± 8 Tg C year-1 Carbon losses caused by edge effect is thus an additional unquantified flux that can counteract carbon emissions avoided by reducing deforestation, compromising the Paris Agreement's bold targets.

An integrated remote sensing and GIS approach for monitoring areas affected by selective logging: A case study in northern Mato Grosso, Brazilian Amazon.

Forest cover disturbances due to processes such as logging and forest fires are a widespread issue especially in the tropics, and have heavily affected forest biomass and functioning in the Brazilian Amazon in the past decades. Satellite remote sensing has played a key role for assessing logging activities in this region; however, there are still remaining challenges regarding the quantification and monitoring of these processes affecting forested lands. In this study, we propose a new method for monitoring areas affected by selective logging in one of the hotspots of Mato Grosso state in the Brazilian Amazon, based on a combination of object-based and pixel-based classification approaches applied on remote sensing data. Logging intensity and changes over time are assessed within grid cells of 300 m × 300 m spatial resolution. Our method encompassed three main steps: (1) mapping forest/non-forest areas through an object-based classification approach applied to a temporal series of Landsat images during the period 2000-2015, (2) mapping yearly logging activities from soil fraction images on the same Landsat data series, and (3) integrating information from previous steps within a regular grid-cell of 300 m × 300 m in order to monitor disturbance intensities over this 15-years period. The overall accuracy of the baseline forest/non-forest mask (year 2000) and of the undisturbed vs disturbed forest (for selected years) were 93% and 84% respectively. Our results indicate that annual forest disturbance rates, mainly due to logging activities, were higher than annual deforestation rates during the whole period of study. The deforested areas correspond to circa 25% of the areas affected by forest disturbances. Deforestation rates were highest from 2001 to 2005 and then decreased considerably after 2006. In contrast, the annual forest disturbance rates show high temporal variability with a slow decrease over the 15-year period, resulting in a significant increase of the ratio between disturbed and deforested areas. Although the majority of the areas, which have been affected by selective logging during the period 2000-2014, were not deforested by 2015, more than 70% of the deforested areas in 2015 had been at least once identified as disturbed forest during that period.

Determination of tropical deforestation rates and related carbon losses from 1990 to 2010.

We estimate changes in forest cover (deforestation and forest regrowth) in the tropics for the two last decades (1990-2000 and 2000-2010) based on a sample of 4000 units of 10 ×10 km size. Forest cover is interpreted from satellite imagery at 30 × 30 m resolution. Forest cover changes are then combined with pan-tropical biomass maps to estimate carbon losses. We show that there was a gross loss of tropical forests of 8.0 million ha yr(-1) in the 1990s and 7.6 million ha yr(-1) in the 2000s (0.49% annual rate), with no statistically significant difference. Humid forests account for 64% of the total forest cover in 2010 and 54% of the net forest loss during second study decade. Losses of forest cover and Other Wooded Land (OWL) cover result in estimates of carbon losses which are similar for 1990s and 2000s at 887 MtC yr(-1) (range: 646-1238) and 880 MtC yr(-1) (range: 602-1237) respectively, with humid regions contributing two-thirds. The estimates of forest area changes have small statistical standard errors due to large sample size. We also reduce uncertainties of previous estimates of carbon losses and removals. Our estimates of forest area change are significantly lower as compared to national survey data. We reconcile recent low estimates of carbon emissions from tropical deforestation for early 2000s and show that carbon loss rates did not change between the two last decades. Carbon losses from deforestation represent circa 10% of Carbon emissions from fossil fuel combustion and cement production during the last decade (2000-2010). Our estimates of annual removals of carbon from forest regrowth at 115 MtC yr(-1) (range: 61-168) and 97 MtC yr(-1) (53-141) for the 1990s and 2000s respectively are five to fifteen times lower than earlier published estimates.

Continental estimates of forest cover and forest cover changes in the dry ecosystems of Africa between 1990 and 2000.

AIM: This study provides regional estimates of forest cover in dry African ecoregions and the changes in forest cover that occurred there between 1990 and 2000, using a systematic sample of medium-resolution satellite imagery which was processed consistently across the continent. LOCATION: The study area corresponds to the dry forests and woodlands of Africa between the humid forests and the semi-arid regions. This area covers the Sudanian and Zambezian ecoregions. METHODS: A systematic sample of 1600 Landsat satellite imagery subsets, each 20 km × 20 km in size, were analysed for two reference years: 1990 and 2000. At each sample site and for both years, dense tree cover, open tree cover, other wooded land and other vegetation cover were identified from the analysis of satellite imagery, which comprised multidate segmentation and automatic classification steps followed by visual control by national forestry experts. RESULTS: Land cover and land-cover changes were estimated at continental and ecoregion scales and compared with existing pan-continental, regional and local studies. The overall accuracy of our land-cover maps was estimated at 87%. Between 1990 and 2000, 3.3 million hectares (Mha) of dense tree cover, 5.8 Mha of open tree cover and 8.9 Mha of other wooded land were lost, with a further 3.9 Mha degraded from dense to open tree cover. These results are substantially lower than the 34 Mha of forest loss reported in the FAO's 2010 Global Forest Resources Assessment for the same period and area. MAIN CONCLUSIONS: Our method generates the first consistent and robust estimates of forest cover and change in dry Africa with known statistical precision at continental and ecoregion scales. These results reduce the uncertainty regarding vegetation cover and its dynamics in these previously poorly studied ecosystems and provide crucial information for both science and environmental policies.

State and evolution of the African rainforests between 1990 and 2010.

This paper presents a map of Africa's rainforests for 2005. Derived from moderate resolution imaging spectroradiometer data at a spatial resolution of 250 m and with an overall accuracy of 84%, this map provides new levels of spatial and thematic detail. The map is accompanied by measurements of deforestation between 1990, 2000 and 2010 for West Africa, Central Africa and Madagascar derived from a systematic sample of Landsat images-imagery from equivalent platforms is used to fill gaps in the Landsat record. Net deforestation is estimated at 0.28% yr(-1) for the period 1990-2000 and 0.14% yr(-1) for the period 2000-2010. West Africa and Madagascar exhibit a much higher deforestation rate than the Congo Basin, for example, three times higher for West Africa and nine times higher for Madagascar. Analysis of variance over the Congo Basin is then used to show that expanding agriculture and increasing fuelwood demands are key drivers of deforestation in the region, whereas well-controlled timber exploitation programmes have little or no direct influence on forest-cover reduction at present. Rural and urban population concentrations and fluxes are also identified as strong underlying causes of deforestation in this study.

The effect of climate anomalies and human ignition factor on wildfires in Russian boreal forests.

Over the last few years anomalies in temperature and precipitation in northern Russia have been regarded as manifestations of climate change. During the same period exceptional forest fire seasons have been reported, prompting many authors to suggest that these in turn are due to climate change. In this paper, we examine the number and areal extent of forest fires across boreal Russia for the period 2002-2005 within two forest categories: 'intact forests' and 'non-intact forests'. Results show a far lower density of fire events in intact forests (5-14 times less) and that those events tend to be in the first 10 km buffer zone inside intact forest areas. Results also show that, during exceptional climatic years (2002 and 2003), fire event density is twice that found during normal years (2004 and 2005) and average areal extent of fire events (burned area) in intact forests is 2.5 times larger than normal. These results suggest that a majority of the fire events in boreal Russia are of human origin and a maximum of one-third of their impact (areal extension) can be attributed to climate anomalies alone, the rest being due to the combined effect of human disturbances and climate anomalies.

Ecology: human role in Russian wild fires.

Anomalies in temperature and precipitation in northern Russia over the past few years have been viewed as manifestations of anthropogenic climate change, prompting suggestions that this may also account for exceptional forest fires in the region. Here we examine the number of forest-fire events across the boreal Russian Federation for the period 2002 to 2005 in 'intact' forests, where human influence is limited, and in 'non-intact' forests, which have been shaped by human activity. Our results show that there were more fires in years during which the weather was anomalous, but that more than 87% of fires in boreal Russia were started by people.

Tropical forest cover change in the 1990s and options for future monitoring.

Despite the importance of the world's humid tropical forests, our knowledge concerning their rates of change remains limited. Two recent programmes (FAO 2000 Forest Resources Assessment and TREES II), exploiting the global imaging capabilities of Earth observing satellites, have recently been completed to provide information on the dynamics of tropical forest cover. The results from these independent studies show a high degree of conformity and provide a good understanding of trends at the pan-tropical level. In 1990 there were some 1150 million ha of tropical rain forest with the area of the humid tropics deforested annually estimated at 5.8 million ha (approximately twice the size of Belgium). A further 2.3 million ha of humid forest is apparently degraded annually through fragmentation, logging and/or fires. In the sub-humid and dry tropics, annual deforestation of tropical moist deciduous and tropical dry forests comes to 2.2 and 0.7 million ha, respectively. Southeast Asia is the region where forests are under the highest pressure with an annual change rate of -0.8 to -0.9%. The annual area deforested in Latin America is large, but the relative rate (-0.4 to -0.5%) is lower, owing to the vast area covered by the remaining Amazonian forests. The humid forests of Africa are being converted at a similar rate to those of Latin America (-0.4 to -0.5% per year). During this period, secondary forests have also been established, through re-growth on abandoned land and forest plantations, but with different ecological, biophysical and economic characteristics compared with primary forests. These trends are significant in all regions, but the extent of new forest cover has proven difficult to establish. These results, as well as the lack of more detailed knowledge, clearly demonstrate the need to improve sound scientific evidence to support policy. The two projects provide useful guidance for future monitoring efforts in the context of multilateral environmental agreements and of international aid, trade and development partnerships. Methodologically, the use of high-resolution remote sensing in representative samples has been shown to be cost-effective. Close collaboration between tropical institutions and inter-governmental organizations proved to be a fruitful arrangement in the different projects. To properly assist decision-making, monitoring and assessments should primarily be addressed at the national level, which also corresponds to the ratification level of the multilateral environmental agreements. The Forest Resources Assessment 2000 deforestation statistics from countries are consistent with the satellite-based estimates in Asia and America, but are significantly different in Africa, highlighting the particular need for long-term capacity-building activities in this continent.

Determination of deforestation rates of the world's humid tropical forests.

A recently completed research program (TREES) employing the global imaging capabilities of Earth-observing satellites provides updated information on the status of the world's humid tropical forest cover. Between 1990 and 1997, 5.8 +/- 1.4 million hectares of humid tropical forest were lost each year, with a further 2.3 +/- 0.7 million hectares of forest visibly degraded. These figures indicate that the global net rate of change in forest cover for the humid tropics is 23% lower than the generally accepted rate. This result affects the calculation of carbon fluxes in the global budget and means that the terrestrial sink is smaller than previously inferred.