Higher absorbed solar radiation partly offset the negative effects of water stress on the photosynthesis of Amazon forests during the 2015 drought

Amazon forests play an important role in the global carbon cycle and Earth\u27s climate. The vulnerability of Amazon forests to drought remains highly controversial. Here we examine the impacts of the 2015 drought on the photosynthesis of Amazon forests to understand how solar radiation and precipitation jointly control forest photosynthesis during the severe drought. We use a variety of gridded vegetation and climate datasets, including solar-induced chlorophyll fluorescence (SIF), photosynthetic active radiation (PAR), the fraction of absorbed PAR (APAR), leaf area index (LAI), precipitation, soil moisture, cloud cover, and vapor pressure deficit (VPD) in our analysis. Satellite-derived SIF observations provide a direct diagnosis of plant photosynthesis from space. The decomposition of SIF to SIF yield (SIFyield) and APAR (the product of PAR and fPAR) reveals the relative effects of precipitation and solar radiation on photosynthesis. We found that the drought significantly reduced SIFyield, the emitted SIF per photon absorbed. The higher APAR resulting from lower cloud cover and higher LAI partly offset the negative effects of water stress on the photosynthesis of Amazon forests, leading to a smaller reduction in SIF than in SIFyield and precipitation. We further found that SIFyield anomalies were more sensitive to precipitation and VPD anomalies in the southern regions of the Amazon than in the central and northern regions. Our findings shed light on the relative and combined effects of precipitation and solar radiation on photosynthesis, and can improve our understanding of the responses of Amazon forests to drought

Forest disturbance and recovery: A general review in the context of spaceborne remote sensing of impacts on aboveground biomass and canopy structure

Abrupt forest disturbances generating gaps \u3e0.001 km2 impact roughly 0.4–0.7 million km2a−1. Fire, windstorms, logging, and shifting cultivation are dominant disturbances; minor contributors are land conversion, flooding, landslides, and avalanches. All can have substantial impacts on canopy biomass and structure. Quantifying disturbance location, extent, severity, and the fate of disturbed biomass will improve carbon budget estimates and lead to better initialization, parameterization, and/or testing of forest carbon cycle models. Spaceborne remote sensing maps large-scale forest disturbance occurrence, location, and extent, particularly with moderate- and fine-scale resolution passive optical/near-infrared (NIR) instruments. High-resolution remote sensing (e.g., ∼1 m passive optical/NIR, or small footprint lidar) can map crown geometry and gaps, but has rarely been systematically applied to study small-scale disturbance and natural mortality gap dynamics over large regions. Reducing uncertainty in disturbance and recovery impacts on global forest carbon balance requires quantification of (1) predisturbance forest biomass; (2) disturbance impact on standing biomass and its fate; and (3) rate of biomass accumulation during recovery. Active remote sensing data (e.g., lidar, radar) are more directly indicative of canopy biomass and many structural properties than passive instrument data; a new generation of instruments designed to generate global coverage/sampling of canopy biomass and structure can improve our ability to quantify the carbon balance of Earth\u27s forests. Generating a high-quality quantitative assessment of disturbance impacts on canopy biomass and structure with spaceborne remote sensing requires comprehensive, well designed, and well coordinated field programs collecting high-quality ground-based data and linkages to dynamical models that can use this information

Evaluating multiple causes of persistent low microwave backscatter from Amazon forests after the 2005 drought

Amazonia has experienced large-scale regional droughts that affect forest productivity and biomass stocks. Space-borne remote sensing provides basin-wide data on impacts of meteorological anomalies, an important complement to relatively limited ground observations across the Amazon’s vast and remote humid tropical forests. Morning overpass QuikScat Ku-band microwave backscatter from the forest canopy was anomalously low during the 2005 drought, relative to the full instrument record of 1999–2009, and low morning backscatter persisted for 2006–2009, after which the instrument failed. The persistent low backscatter has been suggested to be indicative of increased forest vulnerability to future drought. To better ascribe the cause of the low post-drought backscatter, we analyzed multiyear, gridded remote sensing data sets of precipitation, land surface temperature, forest cover and forest cover loss, and microwave backscatter over the 2005 drought region in the southwestern Amazon Basin (4°-12°S, 66°-76°W) and in adjacent 8°x10° regions to the north and east. We found moderate to weak correlations with the spatial distribution of persistent low backscatter for variables related to three groups of forest impacts: the 2005 drought itself, loss of forest cover, and warmer and drier dry seasons in the post-drought vs. the pre-drought years. However, these variables explained only about one quarter of the variability in depressed backscatter across the southwestern drought region. Our findings indicate that drought impact is a complex phenomenon and that better understanding can only come from more extensive ground data and/or analysis of frequent, spatially-comprehensive, high-resolution data or imagery before and after droughts

Satellite remote sensing of vegetation dynamics in the context of climate change

Vegetation is a key component of the Earth's climate system. Understanding vegetation dynamics in a changing climate requires both in situ and remote sensing data. Satellite remote sensing is especially indispensible for continuous monitoring of vegetation over large areas. This dissertation is focused on investigation of vegetation dynamics in the broader context of climate change using satellite data over two critical regions: the arctic-boreal area in the northern high latitudes and Amazonia in South America. The northern high latitudes have experienced amplified warming. We found the response of the arctic-boreal vegetation to this warming to be different between North America and Eurasia during a 30-year period since 1982: the relationship between vegetation green-up and temperature rise was stable over Eurasia, but in North America, the amount of vegetation green-up per unit amount of warming has decreased since the beginning of 21st century. This could partly be explained by the unmatched northward movements of temperature and precipitation patterns in North America. The Amazonian rainforests have highly dense canopies of green leaves. In such dense media, reflection of solar radiation tends to saturate. Thus, the satellite measurements are weakly sensitive to vegetation changes. At the same time, the data are strongly influenced by changing sun-sensor geometry. This makes it difficult to discriminate between vegetation changes and sun-sensor geometry effects. We developed a new physically based approach to detect changes in dense forests. Analyses of several years of data from three sensors on two satellites under a range of sun-sensor geometries provide robust evidence for a sunlight driven seasonal cycle in structure and greenness of Amazonian rainforests. The 2005 and 2010 dry-season droughts decreased the photosynthetic activity of Amazonian rainforests. We demonstrate that satellite data capture such decreases. Furthermore, we show that in 2004 and 2007, when there was lower wet-season water abundance compared to normal years, the photosynthetic activity of Amazonian forests also decreased. Potentially frequent water deficits over Amazon in the future, irrespective of whether they occur in the dry or wet season, will decrease the photosynthetic activity of Amazonian forests, and provide a positive feedback to global warming

Post-drought decline of the Amazon carbon sink

Amazon forests have experienced frequent and severe droughts in the past two decades. However, little is known about the large-scale legacy of droughts on carbon stocks and dynamics of forests. Using systematic sampling of forest structure measured by LiDAR waveforms from 2003 to 2008, here we show a significant loss of carbon over the entire Amazon basin at a rate of 0.3 ± 0.2 (95% CI) PgC yr−1 after the 2005 mega-drought, which continued persistently over the next 3 years (2005–2008). The changes in forest structure, captured by average LiDAR forest height and converted to above ground biomass carbon density, show an average loss of 2.35 ± 1.80 MgC ha−1 a year after (2006) in the epicenter of the drought. With more frequent droughts expected in future, forests of Amazon may lose their role as a robust sink of carbon, leading to a significant positive climate feedback and exacerbating warming trends.The research was partially supported by NASA Terrestrial Ecology grant at the Jet Propulsion Laboratory, California Institute of Technology and partial funding to the UCLA Institute of Environment and Sustainability from previous National Aeronautics and Space Administration and National Science Foundation grants. The authors thank NSIDC, BYU, USGS, and NASA Land Processes Distributed Active Archive Center (LP DAAC) for making their data available. (NASA Terrestrial Ecology grant at the Jet Propulsion Laboratory, California Institute of Technology)Published versio

The 2010 spring drought reduced primary productivity in southwestern China

Many parts of the world experience frequent and severe droughts. Summer drought can significantly reduce primary productivity and carbon sequestration capacity. The impacts of spring droughts, however, have received much less attention. A severe and sustained spring drought occurred in southwestern China in 2010. Here we examine the influence of this spring drought on the primary productivity of terrestrial ecosystems using data on climate, vegetation greenness and productivity. We first assess the spatial extent, duration and severity of the drought using precipitation data and the Palmer drought severity index. We then examine the impacts of the drought on terrestrial ecosystems using satellite data for the period 2000–2010. Our results show that the spring drought substantially reduced the enhanced vegetation index (EVI) and gross primary productivity (GPP) during spring 2010 (March–May). Both EVI and GPP also substantially declined in the summer and did not fully recover from the drought stress until August. The drought reduced regional annual GPP and net primary productivity (NPP) in 2010 by 65 and 46 Tg C yr−1, respectively. Both annual GPP and NPP in 2010 were the lowest over the period 2000–2010. The negative effects of the drought on annual primary productivity were partly offset by the remarkably high productivity in August and September caused by the exceptionally wet conditions in late summer and early fall and the farming practices adopted to mitigate drought effects. Our results show that, like summer droughts, spring droughts can also have significant impacts on vegetation productivity and terrestrial carbon cycling

New generation geostationary satellite observations support seasonality in greenness of the Amazon evergreen forests

Assessing the seasonal patterns of the Amazon rainforests has been difficult because of the paucity of ground observations and persistent cloud cover over these forests obscuring optical remote sensing observations. Here, we use data from a new generation of geostationary satellites that carry the Advanced Baseline Imager (ABI) to study the Amazon canopy. ABI is similar to the widely used polar orbiting sensor, the Moderate Resolution Imaging Spectroradiometer (MODIS), but provides observations every 10–15 min. Our analysis of NDVI data collected over the Amazon during 2018–19 shows that ABI provides 21–35 times more cloud-free observations in a month than MODIS. The analyses show statistically significant changes in seasonality over 85% of Amazon forest pixels, an area about three times greater than previously reported using MODIS data. Though additional work is needed in converting the observed changes in seasonality into meaningful changes in canopy dynamics, our results highlight the potential of the new generation geostationary satellites to help us better understand tropical ecosystems, which has been a challenge with only polar orbiting satellites

A Novel Diffuse Fraction-Based Two-Leaf Light Use Efficiency Model: An Application Quantifying Photosynthetic Seasonality Across 20 AmeriFlux Flux Tower Sites

. Diffuse radiation can increase canopy light use efficiency (LUE). This creates the need to differentiate the effects of direct and diffuse radiation when simulating terrestrial gross primary production (GPP). Here, we present a novel GPP model, the diffuse-fraction-based two-leaf model (DTEC), which includes the leaf response to direct and diffuse radiation, and treats maximum LUE for shaded leaves (εmsh defined as a power function of the diffuse fraction (Df)) and sunlit leaves (εmsu defined as a constant) separately. An Amazonian rainforest site (KM67) was used to calibrate the model by simulating the linear relationship between monthly canopy LUE and Df. This showed a positive response of forest GPP to atmospheric diffuse radiation, and suggested that diffuse radiation was more limiting than global radiation and water availability for Amazon rainforest GPP on a monthly scale. Further evaluation at 20 independent AmeriFlux sites showed that the DTEC model, when driven by monthly meteorological data and MODIS leaf area index (LAI) products, explained 70% of the variability observed in monthly flux tower GPP. This exceeded the 51% accounted for by the MODIS 17A2 big-leaf GPP product. The DTEC model’s explicit accounting for the impacts of diffuse radiation and soil water stress along with its parameterization for C4 and C3 plants was responsible for this difference. The evaluation of DTEC at Amazon rainforest sites demonstrated its potential to capture the unique seasonality of higher GPP during the diffuse radiation-dominated wet season. Our results highlight the importance of diffuse radiation in seasonal GPP simulation

A comparison of plot-based satellite and Earth system model estimates of tropical forest net primary production

Net primary production (NPP) by plants represents the largest annual flux of carbon dioxide (CO2) from the atmosphere to the terrestrial biosphere, playing a critical role in the global carbon (C) cycle and the Earth’s climate. Rates of NPP in tropical forests are thought to be among the highest on Earth, but debates about the magnitude, patterns, and controls of NPP in the tropics highlight uncertainty in our understanding of how tropical forests may respond to environmental change. Here, we compared tropical NPP estimates generated using three common approaches: (1) field-based methods scaled from plot-level measurements of plant biomass, (2) radiation-based methods that model NPP from satellite-derived radiation absorption by plants, (3) and biogeochemical model-based methods. For undisturbed tropical forests as a whole, the three methods produced similar NPP estimates (i.e. about 10 Pg C yr1). However, the three different approaches produced vastly different patterns of NPP both in space and through time, suggesting that our understanding of tropical NPP is poor and that our ability to predict the response of NPP in the tropics to environmental change is limited. To address this shortcoming, we suggest the development of an expanded, high-density, permanent network of sites where NPP is continuously evaluated using multiple approaches. Well-designed NPP megatransects that include a high-density plot network would significantly increase the accuracy and certainty in the observed rates and patterns of tropical NPP and improve the reliability of Earth system models used to predict NPP–carbon cycle–climate interactions into the futur