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Deep-water access is arguably the most effective, but under-studied, mechanism that plants employ to survive during drought. Vulnerability to embolism and hydraulic safety margins can predict mortality risk at given levels of dehydration, but deep-water access may delay plant dehydration. Here, we tested the role of deep-water access in enabling survival within a diverse tropical forest community in Panama using a novel data-model approach. We inversely estimated the effective rooting depth (ERD, as the average depth of water extraction), for 29 canopy species by linking diameter growth dynamics (1990-2015) to vapor pressure deficit, water potentials in the whole-soil column, and leaf hydraulic vulnerability curves. We validated ERD estimates against existing isotopic data of potential water-access depths. Across species, deeper ERD was associated with higher maximum stem hydraulic conductivity, greater vulnerability to xylem embolism, narrower safety margins, and lower mortality rates during extreme droughts over 35years (1981-2015) among evergreen species. Species exposure to water stress declined with deeper ERD indicating that trees compensate for water stress-related mortality risk through deep-water access. The role of deep-water access in mitigating mortality of hydraulically-vulnerable trees has important implications for our predictive understanding of forest dynamics under current and future climates.

Leaf mass per area (LMA) is a key plant trait, reflecting tradeoffs between leaf photosynthetic function, longevity, and structural investment. Capturing spatial and temporal variability in LMA has been a long-standing goal of ecological research and is an essential component for advancing Earth system models. Despite the substantial variation in LMA within and across Earth's biomes, an efficient, globally generalizable approach to predict LMA is still lacking. We explored the capacity to predict LMA from leaf spectra across much of the global LMA trait space, with values ranging from 17 to 393 g m-2 . Our dataset contained leaves from a wide range of biomes from the high Arctic to the tropics, included broad- and needleleaf species, and upper- and lower-canopy (i.e. sun and shade) growth environments. Here we demonstrate the capacity to rapidly estimate LMA using only spectral measurements across a wide range of species, leaf age and canopy position from diverse biomes. Our model captures LMA variability with high accuracy and low error (R2 = 0.89; root mean square error (RMSE) = 15.45 g m-2 ). Our finding highlights the fact that the leaf economics spectrum is mirrored by the leaf optical spectrum, paving the way for this technology to predict the diversity of LMA in ecosystems across global biomes.

Understanding the pronounced seasonal and spatial variation in leaf carboxylation capacity (Vc,max ) is critical for determining terrestrial carbon cycling in tropical forests. However, an efficient and scalable approach for predicting Vc,max is still lacking. Here the ability of leaf spectroscopy for rapid estimation of Vc,max was tested. Vc,max was estimated using traditional gas exchange methods, and measured reflectance spectra and leaf age in leaves sampled from tropical forests in Panama and Brazil. These data were used to build a model to predict Vc,max from leaf spectra. The results demonstrated that leaf spectroscopy accurately predicts Vc,max of mature leaves in Panamanian tropical forests (R2 = 0.90). However, this single-age model required recalibration when applied to broader leaf demographic classes (i.e. immature leaves). Combined use of spectroscopy models for Vc,max and leaf age enabled construction of the Vc,max -age relationship solely from leaf spectra, which agreed with field observations. This suggests that the spectroscopy technique can capture the seasonal variability in Vc,max , assuming sufficient sampling across diverse species, leaf ages and canopy environments. This finding will aid development of remote sensing approaches that can be used to characterize Vc,max in moist tropical forests and enable an efficient means to parameterize and evaluate terrestrial biosphere models.

During droughts, leaves are predicted to act as 'hydraulic fuses' by shedding when plants reach critically low water potential (Ψplant ), thereby slowing water loss, stabilizing Ψplant and protecting against cavitation-induced loss of stem hydraulic conductivity (Ks ). We tested these predictions among trees in seasonally dry tropical forests, where leaf shedding is common, yet variable, among species. We tracked leaf phenology, Ψplant and Ks in saplings of six tree species distributed across two forests. Species differed in their timing and extent of leaf shedding, yet converged in shedding leaves as they approached the Ψplant value associated with a 50% loss of Ks and at which their model-estimated maximum sustainable transpiration rate approached zero. However, after shedding all leaves, the Ψplant value of one species, Genipa americana, continued to decline, indicating that water loss continued after leaf shedding. Ks was highly variable among saplings within species and seasons, suggesting a minimal influence of seasonal drought on Ks . Hydraulic limits appear to drive diverse patterns of leaf shedding among tropical trees, supporting the hydraulic fuse hypothesis. However, leaf shedding is not universally effective at stabilizing Ψplant , suggesting that the main function of drought deciduousness may vary among species.

We surveyed Lepidoptera found on 11 species of Inga (Fabaceae:Mimosoideae) co-existing on Barro Colorado Island, Panama, to evaluate factors influencing diet choice. Of the 47 species of caterpillars (747 individuals) recorded, each fed on a distinct set of Inga .I n the field, 96% of the individuals were found on young leaves. Growth rates of caterpillars that were fed leaves in the laboratory were 60% higher on young leaves compared to mature leaves. When caterpillars were fed leaves of nonhost Inga, they grew more slowly. These data provide support for a link between preference and performance. However, among hosts on which larvae normally occurred, faster growth rates were not associated with greater host electivity (the proportion of larvae found on each host species in the field, corrected for host abundance). Growth rates on normal hosts were positively correlated with leaf expansion rates of the host, and fast expansion was associated with leaves with higher nutritional content. Detailed studies on a gelechiid leaf roller, the species with the largest diet breadth, allowed us to assess the importance of factors other than growth that could influence diet electivity. This species showed a 1.7-fold difference in growth rate among Inga hosts and faster growth on species with fast-expanding leaves. However, there was no correlation between caterpillar growth rate and abundance on different host species. Instead, abundance of the gelechiid on each Inga species was significantly correlated with the temporal predictability of food (synchrony of leaf flushing) and was negatively correlated with competition (amount of leaf area removed by species other than the gelechiid). Although rates of parasitism were high (23- 43%), there were no differences among hosts. Parasitism was also not related to measures of escape, such as growth rates of caterpillars, leaf expansion rates, and synchrony of leaf production. Together, food availability, parasitism, and competition explained 84% of the variation in host preference by the gelechiid. We suggest that these ecological interactions may be particularly important in determining diet choice initially and that preferences may be reinforced by subsequent divergence in host chemistry and/or the herbivore's ability to tolerate the secondary metabolites.