Thresholds for persistent leaf photochemical damage predict plant drought resilience in a tropical rainforest.

Water stress can cause declines in plant function that persist after rehydration. Recent work has defined 'resilience' traits characterizing leaf resistance to persistent damage from drought, but whether these traits predict resilience in whole-plant function is unknown. It is also unknown whether the coordination between resilience and 'resistance' - the ability to maintain function during drought - observed globally occurs within ecosystems. For eight rainforest species, we dehydrated and subsequently rehydrated leaves, and measured water stress thresholds for declines in rehydration capacity and maximum quantum yield of photosystem II (Fv /Fm ). We tested correlations with embolism resistance and dry season water potentials (ΨMD ), and calculated safety margins for damage (ΨMD - thresholds) and tested correlations with drought resilience in sap flow and growth. Ψ thresholds for persistent declines in Fv /Fm , indicating resilience, were positively correlated with ΨMD and thresholds for leaf vein embolism. Safety margins for persistent declines in Fv /Fm , but not rehydration capacity, were positively correlated with drought resilience in sap flow. Correlations between resistance and resilience suggest that species' differences in performance during drought are perpetuated after drought, potentially accelerating shifts in forest composition. Resilience to photochemical damage emerged as a promising functional trait to characterize whole-plant drought resilience.

The function-dominance correlation drives the direction and strength of biodiversity-ecosystem functioning relationships.

Community composition is a primary determinant of how biodiversity change influences ecosystem functioning and, therefore, the relationship between biodiversity and ecosystem functioning (BEF). We examine the consequences of community composition across six structurally realistic plant community models. We find that a positive correlation between species' functioning in monoculture versus their dominance in mixture with regard to a specific function (the "function-dominance correlation") generates a positive relationship between realised diversity and ecosystem functioning across species richness treatments. However, because realised diversity declines when few species dominate, a positive function-dominance correlation generates a negative relationship between realised diversity and ecosystem functioning within species richness treatments. Removing seed inflow strengthens the link between the function-dominance correlation and BEF relationships across species richness treatments but weakens it within them. These results suggest that changes in species' identities in a local species pool may more strongly affect ecosystem functioning than changes in species richness.

Slow rate of secondary forest carbon accumulation in the Guianas compared with the rest of the Neotropics.

Secondary forests are a prominent component of tropical landscapes, and they constitute a major atmospheric carbon sink. Rates of carbon accumulation are usually inferred from chronosequence studies, but direct estimates of carbon accumulation based on long-term monitoring of stands are rarely reported. Recent compilations on secondary forest carbon accumulation in the Neotropics are heavily biased geographically as they do not include estimates from the Guiana Shield. We analysed the temporal trajectory of aboveground carbon accumulation and floristic composition at one 25-ha secondary forest site in French Guiana. The site was clear-cut in 1976, abandoned thereafter, and one large plot (6.25 ha) has been monitored continuously since. We used Bayesian modeling to assimilate inventory data and simulate the long-term carbon accumulation trajectory. Canopy change was monitored using two aerial lidar surveys conducted in 2009 and 2017. We compared the dynamics of this site with that of a surrounding old-growth forest. Finally, we compared our results with that from secondary forests in Costa Rica, which is one of the rare long-term monitoring programs reaching a duration comparable to our study. Twenty years after abandonment, aboveground carbon stock was 64.2 (95% credibility interval 46.4, 89.0) Mg C/ha, and this stock increased to 101.3 (78.7, 128.5) Mg C/ha 20 yr later. The time to accumulate one-half of the mean aboveground carbon stored in the nearby old-growth forest (185.6 [155.9, 200.2] Mg C/ha) was estimated at 35.0 [20.9, 55.9] yr. During the first 40 yr, the contribution of the long-lived pioneer species Xylopia nitida, Goupia glabra, and Laetia procera to the aboveground carbon stock increased continuously. Secondary forest mean-canopy height measured by lidar increased by 1.14 m in 8 yr, a canopy-height increase consistent with an aboveground carbon accumulation of 7.1 Mg C/ha (or 0.89 Mg C·ha-1 ·yr-1 ) during this period. Long-term AGC accumulation rate in Costa Rica was almost twice as fast as at our site in French Guiana. This may reflect higher fertility of Central American forest communities or a better adaptation of the forest tree community to intense and frequent disturbances. This finding may have important consequences for scaling-up carbon uptake estimates to continental scales.

Improving plant allometry by fusing forest models and remote sensing.

Allometry determines how tree shape and function scale with each other, related through size. Allometric relationships help scale processes from the individual to the global scale and constitute a core component of vegetation models. Allometric relationships have been expected to emerge from optimisation theory, yet this does not suitably predict empirical data. Here we argue that the fusion of high-resolution data, such as those derived from airborne laser scanning, with individual-based forest modelling offers insight into how plant size contributes to large-scale biogeochemical processes. We review the challenges in allometric scaling, how they can be tackled by advances in data-model fusion, and how individual-based models can serve as data integrators for dynamic global vegetation models.

Stronger seasonal adjustment in leaf turgor loss point in lianas than trees in an Amazonian forest.

Pan-tropically, liana density increases with decreasing rainfall and increasing seasonality. This pattern has led to the hypothesis that lianas display a growth advantage over trees under dry conditions. However, the physiological mechanisms underpinning this hypothesis remain elusive. A key trait influencing leaf and plant drought tolerance is the leaf water potential at turgor loss point (πtlp). πtlp adjusts under drier conditions and this contributes to improved leaf drought tolerance. For co-occurring Amazonian tree (n = 247) and liana (n = 57) individuals measured during the dry and the wet seasons, lianas showed a stronger osmotic adjustment than trees. Liana leaves were less drought-tolerant than trees in the wet season, but reached similar drought tolerances during the dry season. Stronger osmotic adjustment in lianas would contribute to turgor maintenance, a critical prerequisite for carbon uptake and growth, and to the success of lianas relative to trees in growth under drier conditions.

Rethinking the nature of intraspecific variability and its consequences on species coexistence.

Intraspecific variability (IV) has been proposed to explain species coexistence in diverse communities. Assuming, sometimes implicitly, that conspecific individuals can perform differently in the same environment and that IV increases niche overlap, previous studies have found contrasting results regarding the effect of IV on species coexistence. We aim at showing that the large IV observed in data does not mean that conspecific individuals are necessarily different in their response to the environment and that the role of high-dimensional environmental variation in determining IV has largely remained unexplored in forest plant communities. We first used a simulation experiment where an individual attribute is derived from a high-dimensional model, representing "perfect knowledge" of individual response to the environment, to illustrate how large observed IV can result from "imperfect knowledge" of the environment. Second, using growth data from clonal Eucalyptus plantations in Brazil, we estimated a major contribution of the environment in determining individual growth. Third, using tree growth data from long-term tropical forest inventories in French Guiana, Panama and India, we showed that tree growth in tropical forests is structured spatially and that despite a large observed IV at the population level, conspecific individuals perform more similarly locally than compared with heterospecific individuals. As the number of environmental dimensions that are well quantified at fine scale is generally lower than the actual number of dimensions influencing individual attributes, a great part of observed IV might be represented as random variation across individuals when in fact it is environmentally driven. This mis-representation has important consequences for inference about community dynamics. We emphasize that observed IV does not necessarily impact species coexistence per se but can reveal species response to high-dimensional environment, which is consistent with niche theory and the observation of the many differences between species in nature.

Tackling unresolved questions in forest ecology: The past and future role of simulation models.

Understanding the processes that shape forest functioning, structure, and diversity remains challenging, although data on forest systems are being collected at a rapid pace and across scales. Forest models have a long history in bridging data with ecological knowledge and can simulate forest dynamics over spatio-temporal scales unreachable by most empirical investigations.We describe the development that different forest modelling communities have followed to underpin the leverage that simulation models offer for advancing our understanding of forest ecosystems.Using three widely applied but contrasting approaches - species distribution models, individual-based forest models, and dynamic global vegetation models - as examples, we show how scientific and technical advances have led models to transgress their initial objectives and limitations. We provide an overview of recent model applications on current important ecological topics and pinpoint ten key questions that could, and should, be tackled with forest models in the next decade.Synthesis. This overview shows that forest models, due to their complementarity and mutual enrichment, represent an invaluable toolkit to address a wide range of fundamental and applied ecological questions, hence fostering a deeper understanding of forest dynamics in the context of global change.