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.Peer reviewe

Comparison of Methods for Modeling Fractional Cover Using Simulated Satellite Hyperspectral Imager Spectra

Remotely sensed data can be used to model the fractional cover of green vegetation (GV), non-photosynthetic vegetation (NPV), and soil in natural and agricultural ecosystems. NPV and soil cover are difficult to estimate accurately since absorption by lignin, cellulose, and other organic molecules cannot be resolved by broadband multispectral data. A new generation of satellite hyperspectral imagers will provide contiguous narrowband coverage, enabling new, more accurate, and potentially global fractional cover products. We used six field spectroscopy datasets collected in prior experiments from sites with partial crop, grass, shrub, and low-stature resprouting tree cover to simulate satellite hyperspectral data, including sensor noise and atmospheric correction artifacts. The combined dataset was used to compare hyperspectral index-based and spectroscopic methods for estimating GV, NPV, and soil fractional cover. GV fractional cover was estimated most accurately. NPV and soil fractions were more difficult to estimate, with spectroscopic methods like partial least squares (PLS) regression, spectral feature analysis (SFA), and multiple endmember spectral mixture analysis (MESMA) typically outperforming hyperspectral indices. Using an independent validation dataset, the lowest root mean squared error (RMSE) values were 0.115 for GV using either normalized difference vegetation index (NDVI) or SFA, 0.164 for NPV using PLS, and 0.126 for soil using PLS. PLS also had the lowest RMSE averaged across all three cover types. This work highlights the need for more extensive and diverse fine spatial scale measurements of fractional cover, to improve methodologies for estimating cover in preparation for future hyperspectral global monitoring missions

Forest Fragmentation and Its Potential Implications in the Brazilian Amazon between 2001 and 2010

In recent decades, human development pressures have results in conversions of vast tracts of Amazonian tropical rain forests to agriculture and other human land uses. In addition to the loss of large forest cover, remaining forests are also fragmented into smaller habitats. Fragmented forests suffer several biological and ecological changes due to edge effects that can exacerbate regional forest degradation. The Brazilian Amazon has had greatly contrasting land cover dynamics in the past decade with the highest historical rates of deforestation (2001-2005) followed by the lowest rates of forest loss in decades, since 2006. Currently, the basin-wide status and implications of forest fragmentation on remnant forests is not well known. We performed a regional forest fragmentation analysis for seven states of the Brazilian Amazon between 2001 and 2010 using a recent deforestation data. During this period, the number of forest fragments (>2 ha) doubled, nearly 125,000 fragments were formed by human activities with more than 50% being smaller than 10 ha. Over the decade, forest edges increased by an average of 36,335 km/year. However, the rate was much greater from 2001-2005 (50,046 km/year) then 2006-2010 (25,365 km/year) when deforestation rates dropped drastically. In 2010, 55 % of basin-wide forest edges were < 10 years old due to the creation of large number of small fragments where intensive biological and ecological degradation is ongoing. Over the past decade protected areas have been expanded dramatically over the Brazilia

Dry Season Evapotranspiration Dynamics over Human-Impacted Landscapes in the Southern Amazon Using the Landsat-Based METRIC Model

Although seasonal and temporal variations in evapotranspiration (ET) in Amazonia have been studied based upon flux-tower data and coarse resolution satellite-based models, ET dynamics over human-impacted landscapes are highly uncertain in this region. In this study, we estimate ET rates from critical land cover types over highly fragmented landscapes in the southern Amazon and characterize the ET dynamics during the dry season using the METRIC (Mapping Evapotranspiration at high Resolution with Internalized Calibration) model. METRIC, a Landsat-based ET model, that generates spatially continuous ET estimates at a 30 m spatial resolution widely used for agricultural applications, was adapted to the southern Amazon by using the NDVI indexed reference ET fraction (ETrF) approach. Compared to flux tower-based ET rates, this approach showed an improved performance on the forest ET estimation over the standard METRIC approach, with R2 = 0.73 from R2 = 0.70 and RMSE reduced from 0.77 mm/day to 0.35 mm/day. We used this approach integrated into the METRIC procedure to estimate ET rates from primary, regenerated, and degraded forests and pasture in Acre, Rondônia, and Mato Grosso, all located in the southern Amazon, during the dry season in 2009. The lowest ET rates occurred in Mato Grosso, the driest region. Acre and Rondônia, both located in the southwestern Amazon, had similar ET rates for all land cover types. Dry season ET rates between primary forest and regenerated forest were similar (p > 0.05) in all sites, ranging between 2.5 and 3.4 mm/day for both forest cover types in the three sites. ET rates from degraded forest in Mato Grosso were significantly lower (p < 0.05) compared to the other forest cover types, with a value of 2.03 mm/day on average. Pasture showed the lowest ET rates during the dry season at all study sites, with the dry season average ET varying from 1.7 mm/day in Mato Grosso to 2.8 mm/day in Acre

Forest Inventory Data

Forest inventory was conducted in Acre, the southwestern Amazon, in July-August in 2014. Field data was collected in four fragmented forest areas. In addition, this forest inventory includes data in forest areas burned in 2005 and 2010 and unburned forest areas. Forest inventory includes information on vegetation species and stem diameter at breast height (DBH) at each plot of 25m x 25m. All trees with DBH ≥ 10cm were measured at 25m x 25m plots and those with DBH\u3c 10cm and lianas were measured at 10m x 10m and 5m x 5m subplots within each 25m x 25m plot

Evaluation of Landsat-Based METRIC Modeling to Provide High-Spatial Resolution Evapotranspiration Estimates for Amazonian Forests

While forest evapotranspiration (ET) dynamics in the Amazon have been studied both as point estimates using flux towers, as well as spatially coarse surfaces using satellite data, higher resolution (e.g., 30 m resolution) ET estimates are necessary to address finer spatial variability associated with forest biophysical characteristics and their changes by natural and human impacts. The objective of this study is to evaluate the potential of the Landsat-based METRIC (Mapping Evapotranspiration at high Resolution with Internalized Calibration) model to estimate high-resolution (30 m) forest ET by comparing to flux tower ET (FT ET) data collected over seasonally dry tropical forests in Rondônia, the southwestern region of the Amazon. Analyses were conducted at daily, monthly and seasonal scales for the dry seasons (June–September for Rondônia) of 2000–2002. Overall daily ET comparison between FT ET and METRIC ET across the study site showed r2 = 0.67 with RMSE = 0.81 mm. For seasonal ET comparison, METRIC-derived ET estimates showed an agreement with FT ET measurements during the dry season of r2 >0.70 and %MAE <15%. We also discuss some challenges and potential applications of METRIC for Amazonian forests

Deforestation, plantation-related land cover dynamics and oil palm age-structure change during 1990–2020 in Riau Province, Indonesia

The expansion of plantations, such as oil palm, in Indonesia has caused large-scale deforestation. Loss of tropical forest, in particular peatland forest, is a major ecological and environmental threat as well as a source of atmospheric carbon emissions. Understanding the spatio-temporal dynamics of plantation expansion may illuminate pathways to reduce deforestation while maintaining high yields in existing plantations. Beyond mapping forest conversion to plantations, it is also important to understand post-conversion plantation success and crop age. In the case of oil palm, the typical productive lifespan is 25–30 years before replanting or conversion to other land use becomes necessary. Knowledge about the extent of oil palm in different productive growth stages is important for yield estimation and improving management strategies. This study characterizes the land-cover and land-use changes inherent to oil palm plantation expansion and age-structured oil palm dynamics across Riau, the province with the greatest production of oil palm in Indonesia, using a 30 year time-series of Landsat satellite imagery. From 1990 to 2020, Riau lost 4.63 M ha of forest, while oil palm extent grew six-fold, reaching an estimated 3.52 M ha in 2020. Rapid expansion of oil palm plantations in Riau resulted in the predominance of younger age classes (<10 yr-old) and rapidly increasing yields during 2010–2020. Conversion dynamics changed over time such that, after 2014, the <10 yr age class declined by 14%, whereas the 10–20 yr-old (peak yield stage) and ⩾20 yr-old (decline stage) age classes increased by 11% and 3%, respectively. In 28 years of observation (1992–2020), 41% of oil palm planted between 1990 and 1992 underwent at least one cycle of replanting in Riau

Historical trends of degradation, loss, and recovery in the tropical forest reserves of Ghana

The Upper Guinean Forest region of West Africa, a globally significant biodiversity hotspot, is among the driest and most human-impacted tropical ecosystems. We used Landsat to study forest degradation, loss, and recovery in the forest reserves of Ghana from 2003 to 2019. Annual canopy cover maps were generated using random forests and results were temporally segmented using the LandTrendr algorithm. Canopy cover was predicted with a predicted-observed r2 of 0.76, mean absolute error of 12.8%, and mean error of 1.3%. Forest degradation, loss, and recovery were identified as transitions between closed (>60% cover), open (15–60% cover) and low tree cover (< 15% cover) classes. Change was relatively slow from 2003 to 2015, but there was more disturbance than recovery resulting in a gradual decline in closed canopy forests. In 2016, widespread fires associated with El Niño drought caused forest loss and degradation across more than 12% of the moist semi-deciduous and upland evergreen forest types. The workflow was implemented in Google Earth Engine, allowing stakeholders to visualize the results and download summaries. Information about historical disturbances will help to prioritize locations for future studies and target forest protection and restoration activities aimed at increasing resilience