Summary
Amazonian droughts are predicted to become increasingly frequent and intense, and the vulnerability of Amazonian trees has become increasingly documented. However, little is known about the ...physiological mechanisms and the diversity of drought tolerance of tropical trees due to the lack of quantitative measurements.
Leaf water potential at wilting or turgor loss point (πtlp) is a determinant of the tolerance of leaves to drought stress and contributes to plant‐level physiological drought tolerance. Recently, it has been demonstrated that leaf osmotic water potential at full hydration (πo) is tightly correlated with πtlp. Estimating πtlp from osmometer measurements of πo is much faster than the standard pressure–volume curve approach of πtlp determination. We used this technique to estimate πtlp for 165 trees of 71 species, at three sites within forests in French Guiana. Our data set represents a significant increase in available data for this trait for tropical tree species.
Tropical trees showed a wider range of drought tolerance than previously found in the literature, πtlp ranging from −1·4 to −3·2 MPa. This range likely corresponds in part to adaptation and acclimation to occasionally extreme droughts during the dry season.
Leaf‐level drought tolerance varied across species, in agreement with the available published observations of species variation in drought‐induced mortality. On average, species with a more negative πtlp (i.e. with greater leaf‐level drought tolerance) occurred less frequently across the region than drought‐sensitive species.
Across individuals, πtlp correlated positively but weakly with leaf toughness (R2 = 0·22, P = 0·04) and leaf thickness (R2 = 0·03, P = 0·03). No correlation was detected with other functional traits (leaf mass per area, leaf area, nitrogen or carbon concentrations, carbon isotope ratio, sapwood density or bark thickness).
The variability in πtlp among species indicates a potential for highly diverse species responses to drought within given forest communities. Given the weak correlations between πtlp and traditionally measured plant functional traits, vegetation models seeking to predict forest response to drought should integrate improved quantification of comparative drought tolerance among tree species.
Lay Summary
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.
Forest dynamic models predict the current and future states of ecosystems and are a nexus between physiological processes and empirical data, forest plot inventories and remote-sensing information. ...The problem of biodiversity representation in these models has long been an impediment to a detailed understanding of ecosystem processes. This challenge is amplified in species-rich and high-carbon tropical forests. Here we describe an individual-based and spatially explicit forest growth simulator, TROLL, that integrates recent advances in plant physiology. Processes (carbon assimilation, allocation, reproduction, and mortality) are linked to species-specific functional traits, and the model was parameterized for an Amazonian tropical rainforest. We simulated a forest regeneration experiment from bare soil, and we validated it against observations at our sites. Simulated forest regeneration compared well with observations for stem densities, gross primary productivity, aboveground biomass, and floristic composition. After 500 years of regrowth, the simulated forest displayed structural characteristics similar to observations (e.g., leaf area index and trunk diameter distribution). We then assessed the model's sensitivity to a number of key model parameters: light extinction coefficient and carbon quantum yield, and to a lesser extent mortality rate, and carbon allocation, all influenced ecosystem features. To illustrate the potential of the approach, we tested whether variation in species richness and composition influenced ecosystem properties. Overall, species richness had a positive effect on ecosystem processes, but this effect was controlled by the identity of species rather by richness per se. Also, functional trait community means had a stronger effect than functional diversity on ecosystem processes. TROLL should be applicable to many tropical forests sites, and data requirement is tailored to ongoing trait collection efforts. Such a model should foster the dialogue between ecology and the vegetation modeling community, help improve the predictive power of models, and eventually better inform policy choices.
Abstract
A central challenge in ecology is understanding the emergence of patterns as the result of interactions among individuals. Dynamic forest models can provide a fine‐scale description of the ...ecological, physiological and environmental processes that explain the demography of coexisting tree species. This in turn helps predict changes under future scenarios. However, model accessibility is a major obstacle to a wide use and communication across scientific disciplines and for educational purposes.
Here, we present the R package
rcontroll
, which provides access to the
TROLL
forest simulator in the R environment.
TROLL
is individual‐based and spatially explicit and leverages knowledge of ecology, biogeochemistry and tree ecophysiology through a trait‐based parameterisation.
TROLL
has been used to simulate carbon fluxes and tree diversity in tropical and subtropical forests and to explore forest resilience to disturbance and environmental changes more generally.
rcontroll
provides a user‐friendly environment to set up and analyse TROLL simulations with varying community compositions, ecological parameters and climate conditions.
We show how to test parameter sensitivity in TROLL using the
rcontroll
R package
.
We also demonstrate the flexibility and ease of use of
rcontroll
by replicating a previously published study based on the
TROLL
simulator. Both examples are included with reproducible code documents.
Complex forest simulators are important scientific tools for science and education, and wide access to these tools is an important condition for their adoption.
TROLL
is designed to address a wide range of ecological and environmental questions, and the new R package
rcontroll
is designed to be an entry point for
TROLL
model users.
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.
Human activities modify the disturbance regimes of tropical forests. Since tropical forests host high biological diversity, understanding the role of biodiversity in ecosystem recovery pathways and ...the underlying ecological mechanisms is crucial to predict the fate of tropical ecosystems. Studies relying on regularly censused forest plots, rarely include disturbed forests, are not long enough to assess long‐term forest dynamics and often lack repeatability.
We used an individual‐based model of tropical forest growth to assess the effect of species and functional diversity on long‐term ecosystem recovery from disturbance. We manipulated the number of species and functional assemblages across a large number of simulations and simulated different levels of disturbance. To investigate the ecological mechanisms that underlie the effect of biodiversity on forest functioning along recovery pathways, we partitioned the net effect of biodiversity on ecosystem properties into complementarity and selection effects over time.
We found that functional diversity improved tropical forest resilience after a disturbance. The complementarity effect dominated soon after the disturbance but was progressively surpassed by a selection effect as more competitive species dominated the forest community. This pattern increased with the intensity of the disturbance.
Synthesis. We found that the mechanisms through which biodiversity influences forest functioning depend on the ecosystem state, shifting from a dominant complementarity effect in recently disturbed systems to a selection effect in systems disturbed a long time ago. Our results thus suggest that the time since the last disturbance is a key to understanding biodiversity–ecosystem functioning relationships in tropical forests and can help reconcile previous contrasting results obtained with snapshots of ecosystem state in empirical studies.
We found that the mechanisms through which biodiversity influences forest functioning depend on the ecosystem state, shifting from a dominant complementarity effect in recently disturbed systems to a selection effect in systems disturbed a long time ago. Our results thus suggest that the time since the last disturbance is a key to understanding biodiversity–ecosystem functioning relationships in tropical forests and can help reconcile previous contrasting results obtained with snapshots of ecosystem state in empirical studies.
Plants are enormously diverse in their traits and ecological adaptation, even within given ecosystems, such as tropical rainforests. Accounting for this diversity in vegetation models poses serious ...challenges. Global plant functional trait databases have highlighted general trait correlations across species that have considerably advanced this research program. However, it remains unclear whether trait correlations found globally hold within communities, and whether they extend to drought tolerance traits.
For 134 individual plants spanning a range of sizes and life forms (tree, liana, understorey species) within an Amazonian forest, we measured leaf drought tolerance (leaf water potential at turgor loss point, πtlp), together with 17 leaf traits related to various functions, including leaf economics traits and nutrient composition (leaf mass per area, LMA; and concentrations of C, N, P, K, Ca and Mg per leaf mass and area), leaf area, water‐use efficiency (carbon isotope ratio), and time‐integrated stomatal conductance and carbon assimilation rate per leaf mass and area. We tested trait coordination and the ability to estimate πtlp from the other traits through model selection. Performance and transferability of the best predictive model were assessed through cross‐validation.
Here πtlp was positively correlated with leaf area, and with N, P and K concentrations per leaf mass, but not with LMA or any other studied trait. Five axes were needed to account for >80% of trait variation, but only three of them explained more variance than expected at random. The best model explained only 30% of the variation in πtlp, and out‐sample predictive performance was variable across life forms or canopy strata, suggesting a limited transferability of the model.
Synthesis. We found a weak correlation among leaf drought tolerance and other leaf traits within a forest community. We conclude that higher trait dimensionality than assumed under the leaf economics spectrum may operate among leaves within plant communities, with important implications for species coexistence and responses to changing environmental conditions, and also for the representation of community diversity in vegetation models.
We found a weak correlation among leaf drought tolerance and other leaf traits within a forest community. We conclude that higher trait dimensionality than assumed under the leaf economics spectrum may operate among leaves within plant communities, with important implications for species coexistence and responses to changing environmental conditions, and also for the representation of community diversity in vegetation 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.
Forest models can help understanding the processes that shape forest functioning, structure and diversity, since they can can simulate forest dynamics over spatio‐temporal scales unreachable by most empirical investigations. Here we describe the development of three widely applied but contrasting forest mo−delling approaches — species distribution models, individual‐based models and dynamic global vegetation models. We provide an overview of recent model applications and pinpoint ten key questions that could, and should, be tackled with forest models in the next decade.
•A land surface model accounts for tree demography over the Amazon forest.•Accounting for tree demography allow to simulate observable stand structure variables.•Trees preferentially use water in the ...deepest soil layer during the dry season.•Flexible root water uptake is crucial to simulate fluxes seasonality.
Amazonian forest plays a crucial role in regulating the carbon and water cycles in the global climate system. However, the representation of biogeochemical fluxes and forest structure in dynamic global vegetation models (DGVMs) remains challenging. This situation has considerable implications to simulate the state and dynamics of Amazonian forest. This study aims at simulating the dynamic of the evapotranspiration (ET), productivity (GPP), biomass (AGB) and forest structure of wet tropical forests in the Amazon basin using the updated ORCHIDEE land surface model. The latter is improved for two processes: stand structure and demography, and plant water uptake by roots. Stand structure is simulated by adapting the CAN version of ORCHIDEE, originally developed for temperate forests. Here, we account for the permanent recruitment of young individual trees, the distribution of stand level growth into 20 different cohorts of variable diameter classes, and mortality due to asymmetric competition for light. Plant water uptake is simulated by including soil-to-root hydraulic resistance (RS). To evaluate the effect of the soil resistance alone, we performed factorial simulations with demography only (CAN) and both demography and resistance (CAN-RS). AGB, ET and GPP outputs of CAN-RS are also compared with the standard version of ORCHIDEE (TRUNK) for which eco-hydrological parameters were tuned globally to fit GPP and evapotranspiration at flux tower sites. All the model versions are benchmarked against in situ and regional datasets. We show that CAN-RS correctly reproduce stand level structural variables (as CAN) like diameter classes and tree densities when validated using in-situ data. Besides offering the key advantage to simulate forest's structure, it also correctly simulates ET and GPP and improves fluxes spatial patterns when compared to TRUNK. With the new formulation of soil water uptake, which is driven by soil water availability rather than root-biomass, the simulated trees preferentially use water in the deepest soil layers during the dry seasons. This improves the seasonality of ET and GPP compared to CAN, especially on clay soils for which the soil moisture potential drops rapidly in the dry season. Nevertheless, since demography parameters in CAN-RS are constant for all evergreen tropical forests, spatial variability of AGB and basal area across the Amazon remains too uniform compared to observations, and are very comparable to the TRUNK. Additional processes such as climate driven mortality and phosphorus limitation on growth leading to the prevalence of species with different functional traits across the Amazon need to be included in the future development of this model.
•An individual-based model is shown to be transferable across two tropical forests.•A limited subset of the parameters needs to be recalibrated across forest sites.•Model shows consistent response to ...climate forcing conditions at both sites.•Productivity increases but stem density and biomass decrease at higher temperatures.
Individual-based forest models (IBMs) are useful to investigate the effect of environment on forest structure and dynamics, but they are often restricted to site-specific applications. To build confidence for spatially distributed simulations, model transferability, i.e. the ability of the same model to provide reliable predictions at contrasting sites, has to be thoroughly tested. We tested the transferability of a spatially explicit forest IBM, TROLL, with a trait-based species parameterization and global gridded climate forcing, by applying it to two sites with sharply contrasting climate and floristic compositions across the tropics, one in South America and one in Southeast Asia. We identified which parameters are most influential for model calibration and assessed the model sensitivity to climatic conditions for a given calibration. TROLL produced realistic predictions of forest structure and dynamics at both sites and this necessitates the recalibration of only three parameters, namely photosynthesis efficiency, crown allometry and mortality rate. All three relate to key processes that constrain model transferability and warrant further model development and data acquisition, with mortality being a particular priority of improvement for the current generation of vegetation models. Varying the climatic conditions at both sites demonstrate similar, and expected, model responses: GPP increased with temperature and irradiance, while stem density and aboveground biomass declined as temperature increased. The climate dependence of productivity and biomass was mediated by plant respiration, carbon allocation and mortality, which has implications both on model development and on forecasting of future carbon dynamics. Our detailed examination of forest IBM transferability unveils key processes that need to improve in genericity before reliable large-scale implementations can be envisioned.
Display omitted
PDF
