Climatic and biotic factors influencing regional declines and recovery of tropical forest biomass from the 2015/16 El Niño

Dominant role of the non-forest woody vegetation in the post 2015/16 El Niño tropical carbon recovery

The extreme dry and hot 2015/16 El Niño episode caused large losses in tropical live aboveground carbon (AGC) stocks. Followed by climatic conditions conducive to high vegetation productivity since 2016, tropical AGC are expected to recover from large losses during the El Niño episode; however, the recovery rate and its spatial distribution remain unknown. Here, we used low-frequency microwave satellite data to track AGC changes, and showed that tropical AGC stocks returned to pre-El Niño levels by the end of 2020, resulting in an AGC sink of0.18 0.14 0.26 $$ {0.18}_{0.14}^{0.26} $$ Pg C year-1 during 2014-2020. This sink was dominated by strong AGC increases (0.61 0.49 0.84 $$ {0.61}_{0.49}^{0.84} $$ Pg C year-1) in non-forest woody vegetation during 2016-2020, compensating the forest AGC losses attributed to the El Niño event, forest loss, and degradation. Our findings highlight that non-forest woody vegetation is an increasingly important contributor to interannual to decadal variability in the global carbon cycle.

Tree species explain only half of explained spatial variability in plant water sensitivity

Spatiotemporal patterns of plant water uptake, loss, and storage exert a first-order control on photosynthesis and evapotranspiration. Many studies of plant responses to water stress have focused on differences between species because of their different stomatal closure, xylem conductance, and root traits. However, several other ecohydrological factors are also relevant, including soil hydraulics, topographically driven redistribution of water, plant adaptation to local climatic variations, and changes in vegetation density. Here, we seek to understand the relative importance of the dominant species for regional-scale variations in woody plant responses to water stress. We map plant water sensitivity (PWS) based on the response of remotely sensed live fuel moisture content to variations in hydrometeorology using an auto-regressive model. Live fuel moisture content dynamics are informative of PWS because they directly reflect vegetation water content and therefore patterns of plant water uptake and evapotranspiration. The PWS is studied using 21,455 wooded locations containing U.S. Forest Service Forest Inventory and Analysis plots across the western United States, where species cover is known and where a single species is locally dominant. Using a species-specific mean PWS value explains 23% of observed PWS variability. By contrast, a random forest driven by mean vegetation density, mean climate, soil properties, and topographic descriptors explains 43% of observed PWS variability. Thus, the dominant species explains only 53% (23% compared to 43%) of explainable variations in PWS. Mean climate and mean NDVI also exert significant influence on PWS. Our results suggest that studies of differences between species should explicitly consider the environments (climate, soil, topography) in which observations for each species are made, and whether those environments are representative of the entire species range.

Increased crossing of thermal stress thresholds of vegetation under global warming

Temperature extremes exert a significant influence on terrestrial ecosystems, but the precise levels at which these extremes trigger adverse shifts in vegetation productivity have remained elusive. In this study, we have derived two critical thresholds, using standard deviations (SDs) of growing-season temperature and satellite-based vegetation productivity as key indicators. Our findings reveal that, on average, vegetation productivity experiences rapid suppression when confronted with temperature anomalies exceeding 1.45 SD above the mean temperature during 2001-2018. Furthermore, at temperatures exceeding 2.98 SD above the mean, we observe the maximum level of suppression, particularly in response to the most extreme high-temperature events. When Earth System Models are driven by a future medium emission scenario, they project that mean temperatures will routinely surpass both of these critical thresholds by approximately the years 2050 and 2070, respectively. However, it is important to note that the timing of these threshold crossings exhibits spatial variation and will appear much earlier in tropical regions. Our finding highlights that restricting global warming to just 1.5°C can increase safe areas for vegetation growth by 13% compared to allowing warming to reach 2°C above preindustrial levels. This mitigation strategy helps avoid exposure to detrimental extreme temperatures that breach these thresholds. Our study underscores the pivotal role of climate mitigation policies in fostering the sustainable development of terrestrial ecosystems in a warming world.

Anthropogenic disturbance exacerbates resilience loss in the Amazon rainforests

Uncovering the mechanisms that lead to Amazon forest resilience variations is crucial to predict the impact of future climatic and anthropogenic disturbances. Here, we apply a previously used empirical resilience metrics, lag-1 month temporal autocorrelation (TAC), to vegetation optical depth data in C-band (a good proxy of the whole canopy water content) in order to explore how forest resilience variations are impacted by human disturbances and environmental drivers in the Brazilian Amazon. We found that human disturbances significantly increase the risk of critical transitions, and that the median TAC value is ~2.4 times higher in human-disturbed forests than that in intact forests, suggesting a much lower resilience in disturbed forests. Additionally, human-disturbed forests are less resilient to land surface heat stress and atmospheric water stress than intact forests. Among human-disturbed forests, forests with a more closed and thicker canopy structure, which is linked to a higher forest cover and a lower disturbance fraction, are comparably more resilient. These results further emphasize the urgent need to limit deforestation and degradation through policy intervention to maintain the resilience of the Amazon rainforests.

Asymmetric response of Amazon forest water and energy fluxes to wet and dry hydrological extremes reveals onset of a local drought-induced tipping point

Understanding the effects of intensification of Amazon basin hydrological cycling-manifest as increasingly frequent floods and droughts-on water and energy cycles of tropical forests is essential to meeting the challenge of predicting ecosystem responses to climate change, including forest "tipping points". Here, we investigated the impacts of hydrological extremes on forest function using 12+ years of observations (between 2001-2020) of water and energy fluxes from eddy covariance, along with associated ecological dynamics from biometry, at the Tapajós National Forest. Measurements encompass the strong 2015-2016 El Niño drought and La Niña 2008-2009 wet events. We found that the forest responded strongly to El Niño-Southern Oscillation (ENSO): Drought reduced water availability for evapotranspiration (ET) leading to large increases in sensible heat fluxes (H). Partitioning ET by an approach that assumes transpiration (T) is proportional to photosynthesis, we found that water stress-induced reductions in canopy conductance (Gs ) drove T declines partly compensated by higher evaporation (E). By contrast, the abnormally wet La Niña period gave higher T and lower E, with little change in seasonal ET. Both El Niño-Southern Oscillation (ENSO) events resulted in changes in forest structure, manifested as lower wet-season leaf area index. However, only during El Niño 2015-2016, we observed a breakdown in the strong meteorological control of transpiration fluxes (via energy availability and atmospheric demand) because of slowing vegetation functions (via shutdown of Gs and significant leaf shedding). Drought-reduced T and Gs , higher H and E, amplified by feedbacks with higher temperatures and vapor pressure deficits, signaled that forest function had crossed a threshold, from which it recovered slowly, with delay, post-drought. Identifying such tipping point onsets (beyond which future irreversible processes may occur) at local scale is crucial for predicting basin-scale threshold-crossing changes in forest energy and water cycling, leading to slow-down in forest function, potentially resulting in Amazon forests shifting into alternate degraded states.

The detection and attribution of extreme reductions in vegetation growth across the global land surface

Negative extreme anomalies in vegetation growth (NEGs) usually indicate severely impaired ecosystem services. These NEGs can result from diverse natural and anthropogenic causes, especially climate extremes (CEs). However, the relationship between NEGs and many types of CEs remains largely unknown at regional and global scales. Here, with satellite-derived vegetation index data and supporting tree-ring chronologies, we identify periods of NEGs from 1981 to 2015 across the global land surface. We find 70% of these NEGs are attributable to five types of CEs and their combinations, with compound CEs generally more detrimental than individual ones. More importantly, we find that dominant CEs for NEGs vary by biome and region. Specifically, cold and/or wet extremes dominate NEGs in temperate mountains and high latitudes, whereas soil drought and related compound extremes are primarily responsible for NEGs in wet tropical, arid and semi-arid regions. Key characteristics (e.g., the frequency, intensity and duration of CEs, and the vulnerability of vegetation) that determine the dominance of CEs are also region- and biome-dependent. For example, in the wet tropics, dominant individual CEs have both higher intensity and longer duration than non-dominant ones. However, in the dry tropics and some temperate regions, a longer CE duration is more important than higher intensity. Our work provides the first global accounting of the attribution of NEGs to diverse climatic extremes. Our analysis has important implications for developing climate-specific disaster prevention and mitigation plans among different regions of the globe in a changing climate.

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.