Empirical evidence for resilience of tropical forest photosynthesis in a warmer world

Tropical forests may be vulnerable to climate change1-3 if photosynthetic carbon uptake currently operates near a high temperature limit4-6. Predicting tropical forest function requires understanding the relative contributions of two mechanisms of high-temperature photosynthetic declines: stomatal limitation (H1), an indirect response due to temperature-associated changes in atmospheric vapour pressure deficit (VPD)7, and biochemical restrictions (H2), a direct temperature response8,9. Their relative control predicts different outcomes-H1 is expected to diminish with stomatal responses to future co-occurring elevated atmospheric [CO2], whereas H2 portends declining photosynthesis with increasing temperatures. Distinguishing the two mechanisms at high temperatures is therefore critical, but difficult because VPD is highly correlated with temperature in natural settings. We used a forest mesocosm to quantify the sensitivity of tropical gross ecosystem productivity (GEP) to future temperature regimes while constraining VPD by controlling humidity. We then analytically decoupled temperature and VPD effects under current climate with flux-tower-derived GEP trends in situ from four tropical forest sites. Both approaches showed consistent, negative sensitivity of GEP to VPD but little direct response to temperature. Importantly, in the mesocosm at low VPD, GEP persisted up to 38 °C, a temperature exceeding projections for tropical forests in 2100 (ref. 10). If elevated [CO2] mitigates VPD-induced stomatal limitation through enhanced water-use efficiency as hypothesized9,11, tropical forest photosynthesis may have a margin of resilience to future warming.6 month embargo; published 12 October 2020This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Carbon exchange in an Amazon forest: from hours to years

In Amazon forests, the relative contributions of climate, phenology, and disturbance to net ecosystem exchange of carbon (NEE) are not well understood. To partition influences across various timescales, we use a statistical model to represent eddy-covariance-derived NEE in an evergreen eastern Amazon forest as a constant response to changing meteorology and phenology throughout a decade. Our best fit model represented hourly NEE variations as changes due to sunlight, while seasonal variations arose from phenology influencing photosynthesis and from rainfall influencing ecosystem respiration, where phenology was asynchronous with dry-season onset. We compared annual model residuals with biometric forest surveys to estimate impacts of drought disturbance. We found that our simple model represented hourly and monthly variations in NEE well (R-2 = 0.81 and 0.59, respectively). Modeled phenology explained 1% of hourly and 26% of monthly variations in observed NEE, whereas the remaining modeled variability was due to changes in meteorology. We did not find evidence to support the common assumption that the forest phenology was seasonally light-or water-triggered. Our model simulated annual NEE well, with the exception of 2002, the first year of our data record, which contained 1.2 MgCha(-1) of residual net emissions, because photosynthesis was anomalously low. Because a severe drought occurred in 1998, we hypothesized that this drought caused a persistent, multi-year depression of photosynthesis. Our results suggest drought can have lasting impacts on photosynthesis, possibly via partial damage to still-living trees.National Science Foundation PIRE fellowship [OISE 0730305]; US Department of Energy grant [DE-SC0008311]Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Albert_et_al_2018_TNF_leaf_chlorophyll_data

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Albert_et_al_2018_TNF_Gs_porometer

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Ecosystem heterogeneity and diversity mitigate Amazon forest resilience to frequent extreme droughts

The impact of increases in drought frequency on the Amazon forest's composition, structure and functioning remain uncertain. We used a process- and individual-based ecosystem model (ED2) to quantify the forest's vulnerability to increased drought recurrence.We generated meteorologically realistic, drier-than-observed rainfall scenarios for two Amazon forest sites, Paracou (wetter) and Tapajos (drier), to evaluate the impacts of more frequent droughts on forest biomass, structure and composition.The wet site was insensitive to the tested scenarios, whereas at the dry site biomass declined when average rainfall reduction exceeded 15%, due to high mortality of large-sized evergreen trees. Biomass losses persisted when year-long drought recurrence was shorter than 2-7yr, depending upon soil texture and leaf phenology.From the site-level scenario results, we developed regionally applicable metrics to quantify the Amazon forest's climatological proximity to rainfall regimes likely to cause biomass loss >20% in 50yr according to ED2 predictions. Nearly 25% (1.8 million km(2)) of the Amazon forests could experience frequent droughts and biomass loss if mean annual rainfall or interannual variability changed by 2 sigma. At least 10% of the high-emission climate projections (CMIP5/RCP8.5 models) predict critically dry regimes over 25% of the Amazon forest area by 2100

Ecosystem heterogeneity and diversity mitigate Amazon forest resilience to frequent extreme droughts.

The impact of increases in drought frequency on the Amazon forest's composition, structure and functioning remain uncertain. We used a process- and individual-based ecosystem model (ED2) to quantify the forest's vulnerability to increased drought recurrence. We generated meteorologically realistic, drier-than-observed rainfall scenarios for two Amazon forest sites, Paracou (wetter) and Tapajós (drier), to evaluate the impacts of more frequent droughts on forest biomass, structure and composition. The wet site was insensitive to the tested scenarios, whereas at the dry site biomass declined when average rainfall reduction exceeded 15%, due to high mortality of large-sized evergreen trees. Biomass losses persisted when year-long drought recurrence was shorter than 2-7 yr, depending upon soil texture and leaf phenology. From the site-level scenario results, we developed regionally applicable metrics to quantify the Amazon forest's climatological proximity to rainfall regimes likely to cause biomass loss > 20% in 50 yr according to ED2 predictions. Nearly 25% (1.8 million km2 ) of the Amazon forests could experience frequent droughts and biomass loss if mean annual rainfall or interannual variability changed by 2σ. At least 10% of the high-emission climate projections (CMIP5/RCP8.5 models) predict critically dry regimes over 25% of the Amazon forest area by 2100

Albert_et_al_2018_TNF_gas_exchange_parameters

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Albert_et_al_2018_TNF_leaf_demo_data

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Data from: Age-dependent leaf function and consequences for crown-scale carbon uptake during the dry season in an Amazon evergreen forest

* Satellite and tower-based metrics of forest-scale photosynthesis generally increase with dry season progression across central Amazônia, but the underlying mechanisms lack consensus. * We conducted demographic surveys of leaf age composition, and measured age-dependence of leaf physiology in broadleaf canopy trees of abundant species at a central eastern Amazon site. Using a novel leaf-to-branch scaling approach, we used this data to independently test the much-debated hypothesis—arising from satellite and tower-based observations—that leaf phenology could explain the forest-scale pattern of dry season photosynthesis. * Stomatal conductance and biochemical parameters of photosynthesis were higher for recently mature leaves than for old leaves. Most branches had multiple leaf age categories simultaneously present, and the number of recently mature leaves increased as the dry season progressed because old leaves were exchanged for new leaves. * These findings provide the first direct field evidence that branch-scale photosynthetic capacity increases during the dry season, with a magnitude consistent with increases in ecosystem-scale photosynthetic capacity derived from flux towers. Interaction between leaf age-dependent physiology and shifting leaf age-demographic composition are sufficient to explain the dry season photosynthetic capacity pattern at this site, and should be considered in vegetation models of tropical evergreen forests

Seasonal and drought‐related changes in leaf area profiles depend on height and light environment in an Amazon forest

Seasonal dynamics in the vertical distribution of leaf area index (LAI) may impact the seasonality of forest productivity in Amazonian forests. However, until recently, fine-scale observations critical to revealing ecological mechanisms underlying these changes have been lacking. To investigate fine-scale variation in leaf area with seasonality and drought we conducted monthly ground-based LiDAR surveys over 4 yr at an Amazon forest site. We analysed temporal changes in vertically structured LAI along axes of both canopy height and light environments. Upper canopy LAI increased during the dry season, whereas lower canopy LAI decreased. The low canopy decrease was driven by highly illuminated leaves of smaller trees in gaps. By contrast, understory LAI increased concurrently with the upper canopy. Hence, tree phenological strategies were stratified by height and light environments. Trends were amplified during a 2015-2016 severe El Niño drought. Leaf area low in the canopy exhibited behaviour consistent with water limitation. Leaf loss from short trees in high light during drought may be associated with strategies to tolerate limited access to deep soil water and stressful leaf environments. Vertically and environmentally structured phenological processes suggest a critical role of canopy structural heterogeneity in seasonal changes in Amazon ecosystem function