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Abstract Lianas, or woody vines, and trees dominate the canopy of tropical forests and comprise the majority of tropical aboveground carbon storage. These growth forms respond differently to contemporary variation in climate and resource availability, but their responses to future climate change are poorly understood because there are very few predictive ecosystem models representing lianas. We compile a database of liana functional traits (846 species) and use it to parameterize a mechanistic model of liana-tree competition. The substantial difference between liana and tree hydraulic conductivity represents a critical source of inter-growth form variation. Here, we show that lianas are many times more sensitive to drying atmospheric conditions than trees as a result of this trait difference. Further, we use our competition model and projections of tropical hydroclimate based on Representative Concentration Pathway 4.5 to show that lianas are more susceptible to reaching a hydraulic threshold for viability by 2100. 

The strength and persistence of the tropical carbon sink hinges on the long‐term responses of woody growth to climatic variations and increasing CO₂. However, the sensitivity of tropical woody growth to these environmental changes is poorly understood, leading to large uncertainties in growth predictions. Here, we used tree ring records from a Southeast Asian tropical forest to constrain ED2.2‐hydro, a terrestrial biosphere model with explicit vegetation demography. Specifically, we assessed individual‐level woody growth responses to historical climate variability and increases in atmospheric CO₂(C_a). When forced with historical C_a, ED2.2‐hydro reproduced the magnitude of increases in intercellular CO₂concentration (a major determinant of photosynthesis) estimated from tree ring carbon isotope records. In contrast, simulated growth trends were considerably larger than those obtained from tree rings, suggesting that woody biomass production efficiency (WBPE = woody biomass production:gross primary productivity) was overestimated by the model. The estimated WBPE decline under increasing C_abased on model‐data discrepancy was comparable to or stronger than (depending on tree species and size) the observed WBPE changes from a multi‐year mature‐forest CO₂fertilization experiment. In addition, we found that ED2.2‐hydro generally overestimated climatic sensitivity of woody growth, especially for late‐successional plant functional types. The model‐data discrepancy in growth sensitivity to climate was likely caused by underestimating WBPE in hot and dry years due to commonly used model assumptions on carbon use efficiency and allocation. To our knowledge, this is the first study to constrain model predictions of individual tree‐level growth sensitivity to C_aand climate against tropical tree‐ring data. Our results suggest that improving model processes related to WBPE is crucial to obtain better predictions of tropical forest responses to droughts and increasing C_a. More accurate parameterization of WBPE will likely reduce the stimulation of woody growth by C_arise predicted by biosphere models.

 

Lateral carbon transport (LCT), the flux of terrestrial C transported to aquatic ecosystems, displaces carbon (C) across the terrestrial‐aquatic continuum and is on the same order of magnitude as terrestrial net ecosystem production. However, few continental scale C models include LCT or the C‐hydrology linkages necessary for modeling LCT. Those that do exist, borrow processes and conceptual understanding from watershed scale models, assuming that large‐scale and small‐scale drivers of LCT are the same. We develop a conceptual framework of LCT, which focuses on lateral dissolved organic carbon (DOC) transport (LCT‐DOC), and operationalize it with a coupled terrestrial‐aquatic C and hydrology model. After comparing our model LCT‐DOC to previous estimates derived from a summation of landscape scale fluxes for the Contiguous U.S., we use model experiments to partition the importance of LCT‐DOC drivers including total annual precipitation, air temperature, and plant traits, which interact across regional and local scales. We find that climate is the strongest driver of LCT‐DOC, where LCT‐DOC is positively related to precipitation but inversely related to temperature at continental scales. However, the net effect of climate on LCT‐DOC is the product of cross‐scale interactions between climate and vegetation. Plant traits also interact strongly with climate and have a measurable influence on LCT‐DOC, with water use efficiency as the most influential plant trait because it couples terrestrial water and C cycling. We demonstrate that our conceptual framework and relatively simple linked C‐hydrology process model of LCT‐DOC can inform hypotheses and predict LCT‐DOC.

 

Identifying factors controlling forest productivity is critical to understanding forest‐climate change feedbacks, modelling vegetation dynamics and carbon finance schemes. However, little research has focused on productivity in regenerating tropical forests which are expanding in their fraction of global area have an order of magnitude larger carbon uptake rates relative to older forest.

We examined above‐ground net primary productivity (ANPP) and its components (wood production and litterfall) over 10 years in forest plots that vary in successional age, soil characteristics and species composition using band dendrometers and litterfall traps in regenerating seasonally dry tropical forests in northwestern Costa Rica.

We show that the components of ANPP are differentially driven by age and annual rainfall and that local soil variation is important. Total ANPP was explained by a combination of age, annual rainfall and soil variation. Wood production comprised 35% of ANPP on average across sites and years, and was explained by annual rainfall but not forest age. Conversely, litterfall increased with forest age and soil fertility yet was not affected by annual rainfall. In this region, edaphic variability is highly correlated with plant community composition. Thus, variation in ecosystem processes explained by soil may also be partially explained by species composition.

These results suggest that future changes in annual rainfall can alter the secondary forest carbon sink, but this effect will be buffered by the litterfall flux which varies little among years. In determining the long‐term strength of the secondary forest carbon sink, both rainfall and forest age will be critical variables to track. We also conclude that detailed understanding of local site variation in soils and plant community may be required to accurately predict the impact of changing rainfall on forest carbon uptake.

Synthesis. We show that in seasonally dry tropical forest, annual rainfall has a positive relationship with the growth of above‐ground woody tissues of trees and that droughts lead to significant reductions in above‐ground productivity. These results provide evidence for climate change—carbon cycle feedbacks in the seasonal tropics and highlight the value of longitudinal data on forest regeneration.

 

In the central Amazon, surrounding Manaus City, Brazil, the landscape dominated by forest and water bodies supports development of river breezes. Seasonal inundations modify this local scenery affecting, consequently, the local circulations. However, this effect has not properly been investigated yet. Thus, we carried out numerical experiments for a river breeze case to investigate the seasonal flooding effect on the river breeze and detail the processes involved in the river breeze development. In the numerical experiments, we ran the Catchment‐Based Macro‐scale Floodplain (CaMa‐Flood) model to simulate flooding depth and extent and used the CaMa‐Flood outputs to force the Ocean‐Land‐Atmosphere Model. The seasonal flooding alters the surface energy partitioning causing a temperature decrease over the river region and intensification of the river breezes in the daytime. The intensified river breezes propagate more rapidly through the upland region, take longer to dissipate and promote stronger upward vertical motion altering the heat and mass transport. These novel findings are fundamentally important to the understanding of the local climate variability of the central Amazon. We can infer that river breezes and its consequence to local climate are less (more) pronounced in drought (wet) years.

 

Sensitivity of forest mortality to drought in carbon‐dense tropical forests remains fraught with uncertainty, while extreme droughts are predicted to be more frequent and intense. Here, the potential of temporal autocorrelation of high‐frequency variability in Landsat Enhanced Vegetation Index (EVI), an indicator of ecosystem resilience, to predict spatial and temporal variations of forest biomass mortality is evaluated against in situ census observations for 64 site‐year combinations in Costa Rican tropical dry forests during the 2015 ENSO drought. Temporal autocorrelation, within the optimal moving window of 24 months, demonstrated robust predictive power for in situ mortality (leave‐one‐out cross‐validationR² = 0.54), which allows for estimates of annual biomass mortality patterns at 30 m resolution. Subsequent spatial analysis showed substantial fine‐scale heterogeneity of forest mortality patterns, largely driven by drought intensity and ecosystem properties related to plant water use such as forest deciduousness and topography. Highly deciduous forest patches demonstrated much lower mortality sensitivity to drought stress than less deciduous forest patches after elevation was controlled. Our results highlight the potential of high‐resolution remote sensing to “fingerprint” forest mortality and the significant role of ecosystem heterogeneity in forest biomass resistance to drought.

 

There are two theories about how allocation of metabolic products occurs. The allometric biomass partitioning theory (APT) suggests that all plants follow common allometric scaling rules. The optimal partitioning theory (OPT) predicts that plants allocate more biomass to the organ capturing the most limiting resource.

Whole‐plant harvests of mature and juvenile tropical deciduous trees, evergreen trees, and lianas and model simulations were used to address the following knowledge gaps: (1) Do mature lianas comply with theAPTscaling laws or do they invest less biomass in stems compared to trees? (2) Do juveniles follow the same allocation patterns as mature individuals? (3) Is either leaf phenology or life form a predictor of rooting depth?

It was found that: (1) mature lianas followed the same allometric scaling laws as trees; (2) juveniles and mature individuals do not follow the same allocation patterns; and (3) mature lianas had shallowest coarse roots and evergreen trees had the deepest.

It was demonstrated that: (1) mature lianas invested proportionally similar biomass to stems as trees and not less, as expected; (2) lianas were not deeper‐rooted than trees as had been previously proposed; and (3) evergreen trees had the deepest roots, which is necessary to maintain canopy during simulated dry seasons.