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Earth system models (ESMs) have a limited capacity to represent plant functional diversity and shifts in trait distributions. Approaches to improving the representation of this complexity in ESMs include (i) optimality‐based approaches that predict trait–environment responses and (ii) explicitly modelling coexistence and community assembly. These approaches are expected to converge only when optimality‐based approaches identify competitively dominant strategies, which often differ from strategies that maximize ecosystem functioning or fitness components in monoculture.We used two models, LM3‐PPA (a vegetation demographic model designed as an ESM component) and BiomeE (a computationally efficient analog for LM3‐PPA), to explore how water limitation affects carbon allocation strategies of canopy trees. We compared competitive allocation strategies and those that maximize biomass or productivity in monoculture. We did not explicitly model coexistence or community assembly. Rather, we used model experiments to identify competitive and maximizing strategies in a two‐dimensional trait space under different precipitation and mortality scenarios.At 10 eastern US locations, we simulated historical, wet and dry climate scenarios, novel drought and three different mortality scenarios (low, medium or high sensitivity to water deficit). For each site and scenario, we identified the competitive strategy and three maximizing strategies (maximum biomass, productivity or drought‐tolerance).Root: leaf ratios tended to increase and leaf area tended to decrease with increasing water stress (increasing water limitation and its effects on mortality). However, relative to maximizing strategies, competitive strategies shifted towards greater allocation to roots and leaves with increasing water stress.Competitive overinvestments (greater allocation to roots and leaves by competitive strategies compared with maximizing strategies) were robust across different modelling contexts, including vegetation parameter sets (Acer vs. Populus), models (LM3‐PPA vs. BiomeE) and uncalibrated vsersus calibrated BiomeE versions.Synthesis: The theoretical prediction that competitive and maximizing allocation strategies differ under water limitation is confirmed for a demographic model designed as an ESM component. Optimality‐based trait predictions can simplify representing trait diversity in ESMs but do not always correspond to competitive outcomes. Explicitly modelling coexistence and community assembly in ESMs is challenging but is likely the most general approach to representing trait diversity. [ABSTRACT FROM AUTHOR]

Despite their low contribution to forest carbon stocks, lianas (woody vines) play an important role in the carbon dynamics of tropical forests. As structural parasites, they hinder tree survival, growth and fecundity; hence, they negatively impact net ecosystem productivity and long-term carbon sequestration.Competition (for water and light) drives various forest processes and depends on the local abundance of resources over time. However, evaluating the relative role of resource availability on the interactions between lianas and trees from empirical observations is particularly challenging. Previous approaches have used labour-intensive and ecosystem-scale manipulation experiments, which are infeasible in most situations.We propose to circumvent this challenge by evaluating the uncertainty of water and light capture processes of a process-based vegetation model (ED2) including the liana growth form. We further developed the liana plant functional type in ED2 to mechanistically simulate water uptake and transport from roots to leaves, and start the model from prescribed initial conditions. We then used the PEcAn bioinformatics platform to constrain liana parameters and run uncertainty analyses.Baseline runs successfully reproduced ecosystem gas exchange fluxes (gross primary productivity and latent heat) and forest structural features (leaf area index, aboveground biomass) in two sites (Barro Colorado Island, Panama and Paracou, French Guiana) characterized by different rainfall regimes and levels of liana abundance.Model uncertainty analyses revealed that water limitation was the factor driving the competition between trees and lianas at the drier site (BCI), and during the relatively short dry season of the wetter site (Paracou). In young patches, light competition dominated in Paracou but alternated with water competition between the wet and the dry season on BCI according to the model simulations.The modelling workflow also identified key liana traits (photosynthetic quantum efficiency, stomatal regulation parameters, allometric relationships) and processes (water use, respiration, climbing) driving the model uncertainty. They should be considered as priorities for future data acquisition and model development to improve predictions of the carbon dynamics of liana-infested forests. Synthesis. Competition for water plays a larger role in the interaction between lianas and trees than previously hypothesized, as demonstrated by simulations from a process-based vegetation model.

1. To assess the impacts of climate change on vegetation from stand to global scales, models of forest dynamics that include tree demography are needed. Such models are now available for 50 years, but the currently existing diversity of model formulations and its evolution over time are poorly documented. This hampers systematic assessments of structural uncertainties in model-based studies. 2. We conducted a meta-analysis of 28 models, focusing on models that were used in the past five years for climate change studies. We defined 52 model attributes in five groups (basic assumptions, growth, regeneration, mortality and soil moisture) and characterized each model according to these attributes. Analyses of model complexity and diversity included hierarchical cluster analysis and redundancy analysis. 3. Model complexity evolved considerably over the past 50 years. Increases in complexity were largest for growth processes, while complexity of modelled establishment processes increased only moderately. Model diversity was lowest at the global scale, and highest at the landscape scale. We identified five distinct clusters of models, ranging from very simple models to models where specific attribute groups are rendered in a complex manner and models that feature high complexity across all attributes. 4. Most models in use today are not balanced in the level of complexity with which they represent different processes. This is the result of different model purposes, but also reflects legacies in model code, modelers' preferences, and the ‘prevailing spirit of the epoch’. The lack of firm theories, laws and ‘first principles’ in ecology provides high degrees of freedom in model development, but also results in high responsibilities for model developers and the need for rigorous model evaluation. 5. Synthesis. The currently available model diversity is beneficial: convergence in simulations of structurally different models indicates robust projections, while convergence of similar models may convey a false sense of certainty. The existing model diversity—with the exception of global models—can be exploited for improved projections based on multiple models. We strongly recommend balanced further developments of forest models that should particularly focus on establishment and mortality processes, in order to provide robust information for decisions in ecosystem management and policymaking. [ABSTRACT FROM AUTHOR]

1. Recently, it has been suggested that forest mortality has been generally increasing because of increasing drought and heat stress. But it is unclear if the observations at the investigated forest sites and regions are representative of forests globally and it has not been tested whether forest models are capable of reproducing these observations. We analysed historical climate data and used a dynamic global vegetation model (LPJ-GUESS) to assess (i) Which forests globally might have been affected by drought, (ii) If the field observations are representative for all forests and (iii) If the model can reproduce the reported mortality events. 2. Using two climate data sets and three drought indices, we identified no general global drying trend across all forests, but a large spatial variability. We neither detected a general increase in extreme drought events. A weak drying trend and an increase in extreme drought events were only apparent for forests in already dry climates and the locations or regions for which drought-induced mortality trends have been reported are predominantly in these dry climates. 3. LPJ-GUESS reproduced 66% of the reported mortality events and in 49% of the reported drought-induced mortality events drought was apparent in any of the climatologically derived drought indices. However, only in 30% of the cases simulated increased mortality coincided with drought events. 4. Synthesis. Our results indeed suggest that dry forests have been experiencing increasing drought-induced mortality. However, this does not apply to forests in general and the spatial variability has been large. The poor correspondence between the simulated and reported mortality events indicates that models like LPJ-GUESS driven by standard climatologies, and soil input data do not represent drought-induced mortality well. But the poor detection of the reported drought events in our climate indices also suggests that drought stress might not be the main driver of all the reported drought-mortality events. [ABSTRACT FROM AUTHOR]