Animal soundscapes reveal key markers of Amazon forest degradation from fire and logging.

Safeguarding tropical forest biodiversity requires solutions for monitoring ecosystem structure over time. In the Amazon, logging and fire reduce forest carbon stocks and alter habitat, but the long-term consequences for wildlife remain unclear, especially for lesser-known taxa. Here, we combined multiday acoustic surveys, airborne lidar, and satellite time series covering logged and burned forests (n = 39) in the southern Brazilian Amazon to identify acoustic markers of forest degradation. Our findings contradict expectations from the Acoustic Niche Hypothesis that animal communities in more degraded habitats occupy fewer "acoustic niches" defined by time and frequency. Instead, we found that aboveground biomass was not a consistent proxy for acoustic biodiversity due to the divergent patterns of "acoustic space occupancy" between logged and burned forests. Ecosystem soundscapes highlighted a stark, and sustained reorganization in acoustic community assembly after multiple fires; animal communication networks were quieter, more homogenous, and less acoustically integrated in forests burned multiple times than in logged or once-burned forests. These findings demonstrate strong biodiversity cobenefits from protecting burned Amazon forests from recurrent fire. By contrast, soundscape changes after logging were subtle and more consistent with acoustic community recovery than reassembly. In both logged and burned forests, insects were the dominant acoustic markers of degradation, particularly during midday and nighttime hours, which are not typically sampled by traditional biodiversity field surveys. The acoustic fingerprints of degradation history were conserved across replicate recording locations, indicating that soundscapes may offer a robust, taxonomically inclusive solution for digitally tracking changes in acoustic community composition over time.

The role of fire in global forest loss dynamics.

Fires, among other forms of natural and anthropogenic disturbance, play a central role in regulating the location, composition and biomass of forests. Understanding the role of fire in global forest loss is crucial in constraining land-use change emissions and the global carbon cycle. We analysed the relationship between forest loss and fire at 500 m resolution based on satellite-derived data for the 2003-2018 period. Satellite fire data included burned area and active fire detections, to best account for large and small fires, respectively. We found that, on average, 38 ± 9% (± range) of global forest loss was associated with fire, and this fraction remained relatively stable throughout the study period. However, the fraction of fire-related forest loss varied substantially on a regional basis, and showed statistically significant trends in key tropical forest areas. Decreases in the fraction of fire-related forest loss were found where deforestation peaked early in our study period, including the Amazon and Indonesia while increases were found for tropical forests in Africa. The inclusion of active fire detections accounted for 41%, on average, of the total fire-related forest loss, with larger contributions in small clearings in interior tropical forests and human-dominated landscapes. Comparison to higher-resolution fire data with resolutions of 375 and 20 m indicated that commission errors due to coarse resolution fire data largely balanced out omission errors due to missed small fire detections for regional to continental-scale estimates of fire-related forest loss. Besides an improved understanding of forest dynamics, these findings may help to refine and separate fire-related and non-fire-related land-use change emissions in forested ecosystems.

Remote temperature sensing by the compact thermal imager from the International Space Station.

A systematic calibration approach is presented to correlate the digital output of an infrared camera and the scene temperature. Aided by the optoelectronic properties of the camera, as few as two experimental data points are needed to establish this correlation. This approach can readily include the effects of atmospheric transmission, scene emissivity, and different background subtractions. Hence, the temperature conversion in flight can be reliably obtained from laboratory calibration. The conversion function can also be used to identify the camera's thermal sensitivity and temperature resolution, which are important information in different space missions. In applying this calibration procedure to a laboratory camera and the compact thermal imager onboard the International Space Station, its validity is confirmed.

Effect of oil palm sustainability certification on deforestation and fire in Indonesia.

Many major corporations and countries have made commitments to purchase or produce only "sustainable" palm oil, a commodity responsible for substantial tropical forest loss. Sustainability certification is the tool most used to fulfill these procurement policies, and around 20% of global palm oil production was certified by the Roundtable on Sustainable Palm Oil (RSPO) in 2017. However, the effect of certification on deforestation in oil palm plantations remains unclear. Here, we use a comprehensive dataset of RSPO-certified and noncertified oil palm plantations (∼188,000 km2) in Indonesia, the leading producer of palm oil, as well as annual remotely sensed metrics of tree cover loss and fire occurrence, to evaluate the impact of certification on deforestation and fire from 2001 to 2015. While forest loss and fire continued after RSPO certification, certified palm oil was associated with reduced deforestation. Certification lowered deforestation by 33% from a counterfactual of 9.8 to 6.6% y-1 Nevertheless, most plantations contained little residual forest when they received certification. As a result, by 2015, certified areas held less than 1% of forests remaining within Indonesian oil palm plantations. Moreover, certification had no causal impact on forest loss in peatlands or active fire detection rates. Broader adoption of certification in forested regions, strict requirements to avoid all peat, and routine monitoring of clearly defined forest cover loss in certified and RSPO member-held plantations appear necessary if the RSPO is to yield conservation and climate benefits from reductions in tropical deforestation.

Thinner bark increases sensitivity of wetter Amazonian tropical forests to fire.

Understory fires represent an accelerating threat to Amazonian tropical forests and can, during drought, affect larger areas than deforestation itself. These fires kill trees at rates varying from < 10 to c. 90% depending on fire intensity, forest disturbance history and tree functional traits. Here, we examine variation in bark thickness across the Amazon. Bark can protect trees from fires, but it is often assumed to be consistently thin across tropical forests. Here, we show that investment in bark varies, with thicker bark in dry forests and thinner in wetter forests. We also show that thinner bark translated into higher fire-driven tree mortality in wetter forests, with between 0.67 and 5.86 gigatonnes CO2 lost in Amazon understory fires between 2001 and 2010. Trait-enabled global vegetation models that explicitly include variation in bark thickness are likely to improve the predictions of fire effects on carbon cycling in tropical forests.

En los bosques tropicales de la Amazonia, los incendios de sotobosque representan una amenaza que se está acelerando. Durante la sequía, pueden afectar un área mayor que la deforestación misma. Estos incendios pueden matan árboles a tasas que varían desde <10 hasta cerca de 90% dependiendo de la intensidad del fuego, la historia de perturbaciones forestales y los rasgos funcionales de los árboles. En este estudio, examinamos la variación en el grosor de la corteza en la Amazonía. La corteza puede proteger los árboles de los incendios, pero normalmente se supone que es uniformemente delgada en los bosques tropicales. Aquí, mostramos que el grosor de la corteza varía bastante, con una corteza más gruesa en los bosques secos y más delgada en los bosques húmedos. También, mostramos que cortezas más delgadas resultan en tasas de mortalidad más altas en bosques más húmedos. En total, estimamos que los incendios en el sotobosque de la Amazonía han añadido entre 0,67 y 5,86 gigatoneladas de CO2 atmosférico entre 2001-2010. Los modelos globales de vegetación que predicen los efectos de los incendios sobre el reciclaje de carbono en los bosques tropicales deberían incluir explícitamente la variación en el grosor de la corteza.

Os incêndios rasteiros de sub-bosque representam uma ameaça cada vez maior às florestas tropicais da Amazônia. Durante secas, eles podem afetar áreas maiores do que àquelas desmatadas. Esses incêndios matam árvores a taxas que variam de <10 a c. 90%, dependendo da intensidade do fogo, da história de distúrbios florestais e das características funcionais das árvores. Neste estudo, examinamos a variação na espessura da casca na Amazônia. A casca pode proteger árvores do fogo, mas geralmente é considerada uniformemente fina para diversas florestas tropicais. Aqui, mostramos que a espessura da casca varia, com cascas mais espessas ocorrendo em florestas secas e mais finas ocorrendo em florestas mais úmidas. Mostramos também que a casca mais fina resulta em taxas de mortalidade mais altas em florestas úmidas. No total, estimamos que os incêndios de sub-bosque adicionaram entre 0,67 e 5,86 gigatoneladas de CO2 atmosférico entre 2001-2010. Os modelos globais de vegetação devem incluir explicitamente a variação na espessura da casca ao prever os efeitos do fogo no ciclo do carbono de florestas tropicais.

Amazon forests maintain consistent canopy structure and greenness during the dry season.

The seasonality of sunlight and rainfall regulates net primary production in tropical forests. Previous studies have suggested that light is more limiting than water for tropical forest productivity, consistent with greening of Amazon forests during the dry season in satellite data. We evaluated four potential mechanisms for the seasonal green-up phenomenon, including increases in leaf area or leaf reflectance, using a sophisticated radiative transfer model and independent satellite observations from lidar and optical sensors. Here we show that the apparent green up of Amazon forests in optical remote sensing data resulted from seasonal changes in near-infrared reflectance, an artefact of variations in sun-sensor geometry. Correcting this bidirectional reflectance effect eliminated seasonal changes in surface reflectance, consistent with independent lidar observations and model simulations with unchanging canopy properties. The stability of Amazon forest structure and reflectance over seasonal timescales challenges the paradigm of light-limited net primary production in Amazon forests and enhanced forest growth during drought conditions. Correcting optical remote sensing data for artefacts of sun-sensor geometry is essential to isolate the response of global vegetation to seasonal and interannual climate variability.

Spatial Factor Models for High-Dimensional and Large Spatial Data: An Application in Forest Variable Mapping.

Gathering information about forest variables is an expensive and arduous activity. As such, directly collecting the data required to produce high-resolution maps over large spatial domains is infeasible. Next generation collection initiatives of remotely sensed Light Detection and Ranging (LiDAR) data are specifically aimed at producing complete-coverage maps over large spatial domains. Given that LiDAR data and forest characteristics are often strongly correlated, it is possible to make use of the former to model, predict, and map forest variables over regions of interest. This entails dealing with the high-dimensional (~102) spatially dependent LiDAR outcomes over a large number of locations (~105-106). With this in mind, we develop the Spatial Factor Nearest Neighbor Gaussian Process (SF-NNGP) model, and embed it in a two-stage approach that connects the spatial structure found in LiDAR signals with forest variables. We provide a simulation experiment that demonstrates inferential and predictive performance of the SF-NNGP, and use the two-stage modeling strategy to generate complete-coverage maps of forest variables with associated uncertainty over a large region of boreal forests in interior Alaska.

El Niño drought increased canopy turnover in Amazon forests.

Amazon droughts, including the 2015-2016 El Niño, may reduce forest net primary productivity and increase canopy tree mortality, thereby altering both the short- and the long-term net forest carbon balance. Given the broad extent of drought impacts, inventory plots or eddy flux towers may not capture regional variability in forest response to drought. We used multi-temporal airborne Lidar data and field measurements of coarse woody debris to estimate patterns of canopy turnover and associated carbon losses in intact and fragmented forests in the central Brazilian Amazon between 2013-2014 and 2014-2016. Average annualized canopy turnover rates increased by 65% during the drought period in both intact and fragmented forests. The average size and height of turnover events was similar for both time intervals, in contrast to expectations that the 2015-2016 El Niño drought would disproportionally affect large trees. Lidar-biomass relationships between canopy turnover and field measurements of coarse woody debris were modest (R2  ≈ 0.3), given similar coarse woody debris production and Lidar-derived changes in canopy volume from single tree and multiple branch fall events. Our findings suggest that El Niño conditions accelerated canopy turnover in central Amazon forests, increasing coarse woody debris production by 62% to 1.22 Mg C ha-1  yr-1 in drought years .

Abrupt increases in Amazonian tree mortality due to drought-fire interactions.

Interactions between climate and land-use change may drive widespread degradation of Amazonian forests. High-intensity fires associated with extreme weather events could accelerate this degradation by abruptly increasing tree mortality, but this process remains poorly understood. Here we present, to our knowledge, the first field-based evidence of a tipping point in Amazon forests due to altered fire regimes. Based on results of a large-scale, long-term experiment with annual and triennial burn regimes (B1yr and B3yr, respectively) in the Amazon, we found abrupt increases in fire-induced tree mortality (226 and 462%) during a severe drought event, when fuel loads and air temperatures were substantially higher and relative humidity was lower than long-term averages. This threshold mortality response had a cascading effect, causing sharp declines in canopy cover (23 and 31%) and aboveground live biomass (12 and 30%) and favoring widespread invasion by flammable grasses across the forest edge area (80 and 63%), where fires were most intense (e.g., 220 and 820 kW ⋅ m(-1)). During the droughts of 2007 and 2010, regional forest fires burned 12 and 5% of southeastern Amazon forests, respectively, compared with <1% in nondrought years. These results show that a few extreme drought events, coupled with forest fragmentation and anthropogenic ignition sources, are already causing widespread fire-induced tree mortality and forest degradation across southeastern Amazon forests. Future projections of vegetation responses to climate change across drier portions of the Amazon require more than simulation of global climate forcing alone and must also include interactions of extreme weather events, fire, and land-use change.

Toward an integrated monitoring framework to assess the effects of tropical forest degradation and recovery on carbon stocks and biodiversity.

Tropical forests harbor a significant portion of global biodiversity and are a critical component of the climate system. Reducing deforestation and forest degradation contributes to global climate-change mitigation efforts, yet emissions and removals from forest dynamics are still poorly quantified. We reviewed the main challenges to estimate changes in carbon stocks and biodiversity due to degradation and recovery of tropical forests, focusing on three main areas: (1) the combination of field surveys and remote sensing; (2) evaluation of biodiversity and carbon values under a unified strategy; and (3) research efforts needed to understand and quantify forest degradation and recovery. The improvement of models and estimates of changes of forest carbon can foster process-oriented monitoring of forest dynamics, including different variables and using spatially explicit algorithms that account for regional and local differences, such as variation in climate, soil, nutrient content, topography, biodiversity, disturbance history, recovery pathways, and socioeconomic factors. Generating the data for these models requires affordable large-scale remote-sensing tools associated with a robust network of field plots that can generate spatially explicit information on a range of variables through time. By combining ecosystem models, multiscale remote sensing, and networks of field plots, we will be able to evaluate forest degradation and recovery and their interactions with biodiversity and carbon cycling. Improving monitoring strategies will allow a better understanding of the role of forest dynamics in climate-change mitigation, adaptation, and carbon cycle feedbacks, thereby reducing uncertainties in models of the key processes in the carbon cycle, including their impacts on biodiversity, which are fundamental to support forest governance policies, such as Reducing Emissions from Deforestation and Forest Degradation.

Decoupling of deforestation and soy production in the southern Amazon during the late 2000s.

From 2006 to 2010, deforestation in the Amazon frontier state of Mato Grosso decreased to 30% of its historical average (1996-2005) whereas agricultural production reached an all-time high. This study combines satellite data with government deforestation and production statistics to assess land-use transitions and potential market and policy drivers associated with these trends. In the forested region of the state, increased soy production from 2001 to 2005 was entirely due to cropland expansion into previously cleared pasture areas (74%) or forests (26%). From 2006 to 2010, 78% of production increases were due to expansion (22% to yield increases), with 91% on previously cleared land. Cropland expansion fell from 10 to 2% of deforestation between the two periods, with pasture expansion accounting for most remaining deforestation. Declining deforestation coincided with a collapse of commodity markets and implementation of policy measures to reduce deforestation. Soybean profitability has since increased to pre-2006 levels whereas deforestation continued to decline, suggesting that antideforestation measures may have influenced the agricultural sector. We found little evidence of direct leakage of soy expansion into cerrado in Mato Grosso during the late 2000s, although indirect land-use changes and leakage to more distant regions are possible. This study provides evidence that reduced deforestation and increased agricultural production can occur simultaneously in tropical forest frontiers, provided that land is available and policies promote the efficient use of already-cleared lands (intensification) while restricting deforestation. It remains uncertain whether government- and industry-led policies can contain deforestation if future market conditions favor another boom in agricultural expansion.

Separating the influence of temperature, drought, and fire on interannual variability in atmospheric CO2.

The response of the carbon cycle in prognostic Earth system models (ESMs) contributes significant uncertainty to projections of global climate change. Quantifying contributions of known drivers of interannual variability in the growth rate of atmospheric carbon dioxide (CO2) is important for improving the representation of terrestrial ecosystem processes in these ESMs. Several recent studies have identified the temperature dependence of tropical net ecosystem exchange (NEE) as a primary driver of this variability by analyzing a single, globally averaged time series of CO2 anomalies. Here we examined how the temporal evolution of CO2 in different latitude bands may be used to separate contributions from temperature stress, drought stress, and fire emissions to CO2 variability. We developed atmospheric CO2 patterns from each of these mechanisms during 1997-2011 using an atmospheric transport model. NEE responses to temperature, NEE responses to drought, and fire emissions all contributed significantly to CO2 variability in each latitude band, suggesting that no single mechanism was the dominant driver. We found that the sum of drought and fire contributions to CO2 variability exceeded direct NEE responses to temperature in both the Northern and Southern Hemispheres. Additional sensitivity tests revealed that these contributions are masked by temporal and spatial smoothing of CO2 observations. Accounting for fires, the sensitivity of tropical NEE to temperature stress decreased by 25% to 2.9 ± 0.4 Pg C yr-1 K-1. These results underscore the need for accurate attribution of the drivers of CO2 variability prior to using contemporary observations to constrain long-term ESM responses.

20th-Century hurricanes leave long-lasting legacies on tropical forest height and the abundance of a dominant wind-resistant palm.

Projected increases in hurricane intensity under a warming climate will have profound effects on many forest ecosystems. One key challenge is to disentangle the effects of wind damage from the myriad factors that influence forest structure and species distributions over large spatial scales. Here, we employ a novel machine learning framework with high-resolution aerial photos, and LiDAR collected over 115 km2 of El Yunque National Forest in Puerto Rico to examine the effects of topographic exposure to two hurricanes, Hugo (1989) and Georges (1998), and several landscape-scale environmental factors on the current forest height and abundance of a dominant, wind-resistant species, the palm Prestoea acuminata var. montana. Model predictions show that the average density of the palm was 32% greater while the canopy height was 20% shorter in forests exposed to the two storms relative to unexposed areas. Our results demonstrate that hurricanes have lasting effects on forest canopy height and composition, suggesting the expected increase in hurricane severity with a warming climate will alter coastal forests in the North Atlantic.

The Mg isotopic systematics of granitoids in continental arcs and implications for the role of chemical weathering in crust formation.

Continental crust is too Si-rich and Mg-poor to derive directly from mantle melting, which generates basaltic rather than felsic magmas. Converting basalt to more felsic compositions requires a second step involving Mg loss, which is thought to be dominated by internal igneous differentiation. However, igneous differentiation alone may not be able to generate granites, the most silicic endmember making up the upper continental crust. Here, we show that granites from the eastern Peninsular Ranges Batholith (PRB) in southern California are isotopically heavy in Mg compared with PRB granodiorites and canonical mantle. Specifically, Mg isotopes correlate positively with Si content and O, Sr, and Pb isotopes and negatively with Mg content. The elevated Sr and Pb isotopes require that a component in the source of the granitic magmas to be ancient preexisting crust making up the prebatholithic crustal basement, but the accompanying O and Mg isotope fractionations suggest that this prebatholithic crust preserved a signature of low-temperature alteration. The protolith of this basement rock may have been the residue of chemical weathering, which progressively leached Mg from the residue, leaving the remaining Mg highly fractionated in terms of its isotopic signature. Our observations indicate that ancient continental crust preserves the isotopic signature of compositional modification by chemical weathering.

Deforestation-induced climate change reduces carbon storage in remaining tropical forests.

Biophysical effects from deforestation have the potential to amplify carbon losses but are often neglected in carbon accounting systems. Here we use both Earth system model simulations and satellite-derived estimates of aboveground biomass to assess losses of vegetation carbon caused by the influence of tropical deforestation on regional climate across different continents. In the Amazon, warming and drying arising from deforestation result in an additional 5.1 ± 3.7% loss of aboveground biomass. Biophysical effects also amplify carbon losses in the Congo (3.8 ± 2.5%) but do not lead to significant additional carbon losses in tropical Asia due to its high levels of annual mean precipitation. These findings indicate that tropical forests may be undervalued in carbon accounting systems that neglect climate feedbacks from surface biophysical changes and that the positive carbon-climate feedback from deforestation-driven climate change is higher than the feedback originating from fossil fuel emissions.

Tracking and classifying Amazon fire events in near real time.

Exceptional fire activity in 2019 sparked concern about Amazon forest conservation. However, the inability to rapidly separate satellite fire detections by fire type hampered fire suppression and assessment of ecosystem and air quality impacts. Here, we describe the development of a near-real-time approach for tracking contributions from deforestation, forest, agricultural, and savanna fires to burned area and emissions and apply the approach to the 2019 fire season in South America. Across the southern Amazon, 19,700 deforestation fire events accounted for 39% of all satellite active fire detections and the majority of fire carbon emissions (63%; 69 Tg C). Multiday fires accounted for 81% of burned area and 92% of carbon emissions from the Amazon, with many forest fires burning uncontrolled for weeks. Most fire detections from deforestation fires were correctly identified within 2 days (67%), highlighting the potential to improve situational awareness and management outcomes during fire emergencies.

California wildfire spread derived using VIIRS satellite observations and an object-based tracking system.

Changing wildfire regimes in the western US and other fire-prone regions pose considerable risks to human health and ecosystem function. However, our understanding of wildfire behavior is still limited by a lack of data products that systematically quantify fire spread, behavior and impacts. Here we develop a novel object-based system for tracking the progression of individual fires using 375 m Visible Infrared Imaging Radiometer Suite active fire detections. At each half-daily time step, fire pixels are clustered according to their spatial proximity, and are either appended to an existing active fire object or are assigned to a new object. This automatic system allows us to update the attributes of each fire event, delineate the fire perimeter, and identify the active fire front shortly after satellite data acquisition. Using this system, we mapped the history of California fires during 2012-2020. Our approach and data stream may be useful for calibration and evaluation of fire spread models, estimation of near-real-time wildfire emissions, and as means for prescribing initial conditions in fire forecast models.

Regulating continent growth and composition by chemical weathering.

Continents ride high above the ocean floor because they are underlain by thick, low-density, Si-rich, and Mg-poor crust. However, the parental magmas of continents were basaltic, which means they must have lost Mg relative to Si during their maturation into continents. Igneous differentiation followed by lower crustal delamination and chemical weathering followed by subduction recycling are possible solutions, but the relative magnitudes of each process have never been quantitatively constrained because of the lack of appropriate data. Here, we show that the relative contributions of these processes can be obtained by simultaneous examination of Mg and Li (an analog for Mg) on the regional and global scales in arcs, delaminated lower crust, and river waters. At least 20% of Mg is lost from continents by weathering, which translates into >20% of continental mass lost by weathering (40% by delamination). Chemical weathering leaves behind a more Si-rich and Mg-poor crust, which is less dense and hence decreases the probability of crustal recycling by subduction. Net continental growth is thus modulated by chemical weathering and likely influenced by secular changes in weathering mechanisms.

Storm surge and ponding explain mangrove dieback in southwest Florida following Hurricane Irma.

Mangroves buffer inland ecosystems from hurricane winds and storm surge. However, their ability to withstand harsh cyclone conditions depends on plant resilience traits and geomorphology. Using airborne lidar and satellite imagery collected before and after Hurricane Irma, we estimated that 62% of mangroves in southwest Florida suffered canopy damage, with largest impacts in tall forests (>10 m). Mangroves on well-drained sites (83%) resprouted new leaves within one year after the storm. By contrast, in poorly-drained inland sites, we detected one of the largest mangrove diebacks on record (10,760 ha), triggered by Irma. We found evidence that the combination of low elevation (median = 9.4 cm asl), storm surge water levels (>1.4 m above the ground surface), and hydrologic isolation drove coastal forest vulnerability and were independent of tree height or wind exposure. Our results indicated that storm surge and ponding caused dieback, not wind. Tidal restoration and hydrologic management in these vulnerable, low-lying coastal areas can reduce mangrove mortality and improve resilience to future cyclones.