Small anomalies in dry-season greenness and chlorophyll fluorescence for Amazon moist tropical forests during El Niño and La Niña

https://doi.org/10.1016/j.rse.2020.112196Get rights and content

Highlights

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    Dry-season greenness, fluorescence, photosynthesis anomaly in 2015/16 El Niño mixed

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    Above normal dry-season greenness, fluorescence, photosynthesis in 2009/10 El Niño

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    Below normal dry-season greenness, fluorescence, photosynthesis in two La Niñas

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    Anomalies were larger in September than the entire dry season.

Abstract

The Amazon Basin, a major driver of atmospheric CO2 fluxes, is composed of moist tropical forest (> 2000 mm mean annual precipitation), seasonally moist tropical forests (< 2000 mm mean annual precipitation), croplands, and pastures. It is debated whether there is a dry-season increase in photosynthesis for moist forest and a large reduction in photosynthesis of tropical South America was recently cited as a major driver of the historically high atmospheric CO2 growth rate during the 2015/2016 El Niño. To address this debate and to gain insight into changes in dry-season greenness, SIF, and photosynthesis during El Niño-Southern Oscillation (ENSO) events, here we investigate (1) dry-season changes in satellite-based greenness, solar-induced chlorophyll fluorescence (SIF), and photosynthesis during 2007–2017 and (2) anomalies of satellite-based dry-season greenness, SIF, and photosynthesis for two El Niño events (2009/2010 and 2015/2016) and two La Niña events (2007/2008 and 2010/2011). We hypothesize that satellite-based greenness, SIF, and photosynthesis of moist tropical forests should increase during the dry season, and find this to be the case using two MODIS BRDF-adjusted vegetation indices (EVI and NDVI), GOME-2 SIF data, and the Vegetation Photosynthesis Model (VPM). We also hypothesize that dry-season greenness, SIF, and photosynthesis should be anomalously high during the El Niños, due to anomalously high photosynthetically active radiation (PAR) and a relatively normal preceding wet season, and anomalously low during the La Niñas because these dry seasons were preceded by anomalously low amounts of wet-season precipitation. For this hypothesis, we present results for moist tropical forest and at the basin scale to determine if and by how much their anomalies differ. We find dry-season greenness, SIF, and photosynthesis of moist tropical forest and at the basin scale were statistically significantly lower than normal during the La Niñas, significantly higher than normal during the 2009/2010 El Niño, and were mixed for the 2015/2016 El Niño. Although statistically significant, the magnitudes of the dry-season anomalies were not substantial. Our findings provide additional evidence that photosynthesis of moist tropical Amazon forest increases during the dry season and narrows the potential drivers of perturbations to the atmospheric CO2 growth rate during the last four ENSO events, as anomalies in dry-season greenness, SIF, and photosynthesis during these ENSO events were minute.

Introduction

The seasonal dynamics of forest canopy structure and function in the Amazon are critically important to the local, regional, and global carbon and water cycles, but the dynamics of photosynthesis in moist tropical Amazon forest have been the subject of intense debates over the last two decades (Doughty et al., 2019; Galvão et al., 2011; Huete et al., 2006; Lee et al., 2013; Morton et al., 2014; Saleska et al., 2016; Saleska et al., 2007; Samanta et al., 2010; Xiao et al., 2006; Xiao et al., 2005). A limited number of field studies at the leaf and canopy (Albert et al., 2018; Wu et al., 2018) and landscape (Restrepo-Coupe et al., 2013; Saleska et al., 2003) levels have assessed the seasonal dynamics of forest canopy structure and function, and have concluded that canopy photosynthetic capacity (greenness) and photosynthesis, or gross primary production (GPP), increased during in the dry season. Several satellite-based studies have concluded that dry-season increases in canopy greenness remained after adjusting surface reflectance data to account for the effect of viewing and illumination geometry on vegetation indices (Guan et al., 2015; Maeda et al., 2014; Saleska et al., 2016). A recent field study provided in situ video evidence of forest canopy dynamics of mixed age leaves and new leaf flush during the dry season (Gonçalves et al., 2020). In our previous study, we documented significant dry-season increases in solar-induced chlorophyll fluorescence (SIF), which is a small amount of energy emitted by plants after chlorophyll absorbs photosynthetically active radiation (PAR), that could not be explained alone by changes in sun-sensor geometry, cloud cover, or sunlight entering the canopy (Doughty et al., 2019).

It has also been debated whether severe meteorological drought associated with El Niño further increases dry-season photosynthesis of moist tropical forests in the Amazon or suppresses it (Asner and Alencar, 2010; Brando et al., 2010; Gatti et al., 2014; Huete et al., 2006; Liu et al., 2017; Samanta et al., 2010; Xu et al., 2011). The atmospheric CO2 growth rate was historically high during the 2015/2016 El Niño (Betts et al., 2016), and two studies partially attributed the high rate to a large reduction in photosynthesis of tropical South America (Gloor et al., 2018; Liu et al., 2017). Another study reported seemingly conflicting results in that GOME-2 SIF decreased but greenness increased during the 2015/2016 El Niño (Yang et al., 2018b), and another study found that the 2015/2016 El Niño suppressed SIF after a multi-step correction of the GOME-2A data (Koren et al., 2018), which suffers from sensor degradation (Zhang et al., 2018).

Our limited understanding on the effects of ENSO events on moist tropical forests not only have significant implications for dynamic global vegetation models (DGVMs), some of which have poorly represented the seasonal dynamics of photosynthesis in the Amazon (Restrepo-Coupe et al., 2017), but also have important implications for identifying the factors that drive changes in net carbon fluxes as estimated by atmospheric inversions. The net carbon fluxes in the Amazon is the difference between photosynthesis and respiration. Thus, we must discern what drives changes in photosynthesis in the Amazon to understand to what degree and why net carbon exchange has changed and how it may change in the future. Satellite-based observations and data are the only resources that allow us to investigate the Amazon at the basin scale to assess whether what we observe in situ at experimental sites is occurring in other parts of the basin.

Here, we used monthly MODIS-based vegetation indices, SIF data from GOME-2 and OCO-2, and photosynthesis estimates from the Vegetation Photosynthesis Model (GPPVPM) for 2007–2017 to investigate (1) if there were dry-season increases in greenness, SIF, and photosynthesis for moist tropical forests, and (2) whether dry-season greenness, SIF, and photosynthesis during the strong El Niños (2009/2010 and 2015/2016) and La Niñas (2007/2008 and 2010/2011) were anomalously high or low for moist tropical forest and the entire Amazon Basin.

We hypothesized that (1) greenness, SIF, and photosynthesis of moist tropical forests increase during the dry season, and (2) dry-season greenness, SIF, and photosynthesis were higher than normal during the El Niños and lower than normal during the La Niñas. We expected these two El Niños to enhance dry-season greenness, SIF, and photosynthesis in moist tropical forest (>2000 mm mean annual precipitation) because these forests are generally radiation limited rather than water limited (Guan et al., 2015) and these two El Niños were preceded by relatively normal amounts of wet season precipitation (Fig. 1), and thus increased radiation should increase greenness, SIF, and photosynthesis (Saleska et al., 2007; Wagner et al., 2017). Conversely, we expected dry-season greenness, SIF, and photosynthesis to be anomalously low during the 2007/2008 and 2010/2011 La Niñas due to the anomalously low amounts of precipitation preceding the dry season of both La Niñas (Fig. 1).

Section snippets

Study sites

We investigated changes in satellite-based vegetation indices, SIF, and photosynthesis at the K34 eddy flux tower site (2.61°S, 60.21°W), which was part of the Large-Scale Biosphere Atmosphere Experiment in Amazonia (LBA) (Keller et al., 2004), and the Amazon Tall Tower Observatory (ATTO) site (2.15°S, 59.0°W) (Fig. S1) (Andreae et al., 2015), both of which were in the State of Amazonas, Brazil. We also investigated the changes in satellite-based vegetation indices, SIF, and photosynthesis for

Dry-season increase of canopy greenness, SIF, and photosynthesis

First, we examined the seasonality of satellite-based greenness, SIF, and photosynthesis at two moist forest sites, the Amazon Tall Tower (ATTO) and the Manaus K34 eddy tower. We estimated the forest cover within each of the 1-degree gridcells at these sites to be 99% and 96%, respectively, and the forest cover decreased relatively little over the 11-year study period (−0.2% and − 0.3%; Table S1). In terms of seasonal dynamics, Enhanced Vegetation Index (EVI) and Land Surface Water Index

Dry-season increases of greenness, SIF, and GPP

Our findings on the dry-season increase of greenness, SIF, and GPPVPM for the two forest sites in the Amazon agree with the results reported for the LBA eddy flux towers (Restrepo-Coupe et al., 2013), in situ observations of leaf flush, litterfall, and photosynthesis (Doughty et al., 2015; Rice et al., 2004; Saleska et al., 2003), prior satellite observations (Doughty et al., 2019; Huete et al., 2006; Saleska et al., 2007; Xiao et al., 2005), and more recent in situ studies that observed

Conclusions

The small anomalies we found in dry-season greenness, SIF, and photosynthesis of moist tropical forests in the Amazon during ENSO events narrows the number of potential drivers of anomalous changes in the atmospheric CO2 growth rate during ENSO events. It is vital to characterize how drought and pluvial events affect photosynthesis of the moist tropical forests so that we can better understand and more accurately predict the effects of Earth's climate variability and human land management on

Author statement

R. Doughty and X. Xiao conceived the original idea of this work. R. Doughty and X. Xiao wrote the paper. R. Doughty, Y. Qin, X. Wu, and Y. Zhang processed the data and contributed to data analysis. All authors contributed to the drafting and revision of the manuscript.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

This study was supported by research grants through the Geostationary Carbon Cycle Observatory (GeoCarb) Mission from NASA (GeoCarb Contract #80LARC17C0001), the US National Science Foundation EPSCoR Program (IIA-1301789), and the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Program (NNN12AA01C).

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