Hans Verbeeck

Variation in stem mortality rates determines patterns of above-ground biomass in Amazonian forests: implications for dynamic global vegetation models

Abstract Understanding the processes that determine above‐ground biomass (AGB) in Amazonian forests is important for predicting the sensitivity of these ecosystems to environmental change and for designing and evaluating dynamic global vegetation models (DGVMs). AGB is determined by inputs from woody productivity [woody net primary productivity (NPP)] and the rate at which carbon is lost through tree mortality. Here, we test whether two direct metrics of tree mortality (the absolute rate of woody biomass loss and the rate of stem mortality) and/or woody NPP, control variation in AGB among 167 plots in intact forest across Amazonia. We then compare these relationships and the observed variation in AGB and woody NPP with the predictions of four DGVMs. The observations show that stem mortality rates, rather than absolute rates of woody biomass loss, are the most important predictor of AGB, which is consistent with the importance of stand size structure for determining spatial variation in AGB. The relationship between stem mortality rates and AGB varies among different regions of Amazonia, indicating that variation in wood density and height/diameter relationships also influences AGB. In contrast to previous findings, we find that woody NPP is not correlated with stem mortality rates and is weakly positively correlated with AGB. Across the four models, basin‐wide average AGB is similar to the mean of the observations. However, the models consistently overestimate woody NPP and poorly represent the spatial patterns of both AGB and woody NPP estimated using plot data. In marked contrast to the observations, DGVMs typically show strong positive relationships between woody NPP and AGB. Resolving these differences will require incorporating forest size structure, mechanistic models of stem mortality and variation in functional composition in DGVMs.

Vegetation Demographics in Earth System Models: a review of progress and priorities

Numerous current efforts seek to improve the representation of ecosystem ecology and vegetation demographic processes within Earth System Models (ESMs). These developments are widely viewed as an important step in developing greater realism in predictions of future ecosystem states and fluxes. Increased realism, however, leads to increased model complexity, with new features raising a suite of ecological questions that require empirical constraints. Here, we review the developments that permit the representation of plant demographics in ESMs, and identify issues raised by these developments that highlight important gaps in ecological understanding. These issues inevitably translate into uncertainty in model projections but also allow models to be applied to new processes and questions concerning the dynamics of real-world ecosystems. We argue that stronger and more innovative connections to data, across the range of scales considered, are required to address these gaps in understanding. The development of first-generation land surface models as a unifying framework for ecophysiological understanding stimulated much research into plant physiological traits and gas exchange. Constraining predictions at ecologically relevant spatial and temporal scales will require a similar investment of effort and intensified inter-disciplinary communication.

Functional community structure of African monodominant Gilbertiodendron dewevrei forest influenced by local environmental filtering

Abstract Monodominant patches of forest dominated by Gilbertiodendron dewevrei are commonly found in central African tropical forests, alongside forests with high species diversity. Although these forests are generally found sparsely distributed along rivers, their occurrence is not thought to be (clearly) driven by edaphic conditions but rather by trait combinations of G. dewevrei that aid in achieving monodominance. Functional community structure between these monodominant and mixed forests has, however, not yet been compared. Additionally, little is known about nondominant species in the monodominant forest community. These two topics are addressed in this study. We investigate the functional community structure of 10 one‐hectare plots of monodominant and mixed forests in a central region of the Congo basin, in DR Congo. Thirteen leaf and wood traits are measured, covering 95% (basal area weighted) of all species present in the plots, including leaf nutrient contents, leaf isotopic compositions, specific leaf area, wood density, and vessel anatomy. The trait‐based assessment of G. dewevrei shows an ensemble of traits related to water use and transport that could be favorable for its location near forest rivers. Moreover, indications have been found for N and P limitations in the monodominant forest, possibly related to ectomycorrhizal associations formed with G. dewevrei. Reduced leaf N and P contents are found at the community level for the monodominant forest and for different nondominant groups, as compared to those in the mixed forest. In summary, this work shows that environmental filtering does prevail in the monodominant G. dewevrei forest, leading to lower functional diversity in this forest type, with the dominant species showing beneficial traits related to its common riverine locations and with reduced soil N and P availability found in this environment, both coregulating the tree community assembly.

Model performance of tree height-diameter relationships in the central Congo Basin

Key messageTree heights in the central Congo Basin are overestimated using best-available height-diameter models. These errors are propagated into the estimation of aboveground biomass and canopy height, causing significant bias when used for calibration of remote sensing products in this region.ContextTree height-diameter models are important components of estimating aboveground biomass (AGB) and calibrating remote sensing products in tropical forests.AimsFor a data-poor area of the central Congo Basin, we quantified height-diameter model performance of local, regional and pan-tropical models for their use in estimating AGB and canopy height.MethodsAt three old-growth forest sites, we assessed the bias introduced in height estimation by regional and pan-tropical height-diameter models. We developed an optimal local model with site-level randomizations accounted for by using a mixed-effects modeling approach. We quantified the error propagation of modeled heights for estimating AGB and canopy height.ResultsRegional and pan-tropical height-diameter models produced a significant overestimation in tree height, propagating into significant overestimations of AGB and Lorey’s height. The pan-tropical model accounting for climatic drivers performed better than the regional models. We present a local height-diameter model which produced nonsignificant errors for AGB and canopy height estimations at our study area.ConclusionThe application of general models at our study area introduced bias in tree height estimations and the derived stand-level variables. Improved delimitation of regions in tropical Africa with similar forest structure is needed to produce models fit for calibrating remote sensing products.

Liana and tree below-ground water competition—evidence for water resource partitioning during the dry season

Abstract To date, reasons for the increase in liana abundance and biomass in the Neotropics are still unclear. One proposed hypothesis suggests that lianas, in comparison with trees, are more adaptable to drought conditions. Moreover, previous studies have assumed that lianas have a deeper root system, which provides access to deeper soil layers, thereby making them less susceptible to drought stress. The dual stable water isotope approach (δ18O and δ2H) enables below-ground vegetation competition for water to be studied. Based on the occurrence of a natural gradient in soil water isotopic signatures, with enriched signatures in shallow soil relative to deep soil, the origin of vegetation water sources can be derived. Our study was performed on canopy trees and lianas reaching canopy level in tropical forests of French Guiana. Our results show liana xylem water isotopic signatures to be enriched in heavy isotopes in comparison with those from trees, indicating differences in water source depths and a more superficial root activity for lianas during the dry season. This enables them to efficiently capture dry season precipitation. Our study does not support the liana deep root water extraction hypothesis. Additionally, we provide new insights into water competition between tropical canopy lianas and trees. Results suggest that this competition is mitigated during the dry season due to water resource partitioning.

Modelling understorey dynamics in temperate forests under global change : challenges and perspectives

The understorey harbours a substantial part of vascular plant diversity in temperate forests and plays an important functional role, affecting ecosystem processes such as nutrient cycling and overstorey regeneration. Global change, however, is putting these understorey communities on trajectories of change, potentially altering and reducing their functioning in the future. Developing mitigation strategies to safeguard the diversity and functioning of temperate forests in the future is challenging and requires improved predictive capacity. Process-based models that predict understorey community composition over time, based on first principles of ecology, have the potential to guide mitigation endeavours but such approaches are rare. Here, we review fourteen understorey modelling approaches that have been proposed during the last three decades. We evaluate their inclusion of mechanisms that are required to predict the impact of global change on understorey communities. We conclude that none of the currently existing models fully accounts for all processes that we deem important based on empirical and experimental evidence. Based on this review, we contend new models are needed to project the complex impacts of global change on forest understoreys. Plant functional traits should be central to such future model developments, as they drive community assembly processes and provide valuable information on the functioning of the understorey. Given the important role of the overstorey, a coupling of understorey models to overstorey models will be essential to predict the impact of global change on understorey composition and structure, and how it will affect the functioning of temperate forests in the future.

Spatial Distribution of Carbon Stored in Forests of the Democratic Republic of Congo

National forest inventories in tropical regions are sparse and have large uncertainty in capturing the physiographical variations of forest carbon across landscapes. Here, we produce for the first time the spatial patterns of carbon stored in forests of Democratic Republic of Congo (DRC) by using airborne LiDAR inventory of more than 432,000u2009ha of forests based on a designed probability sampling methodology. The LiDAR mean top canopy height measurements were trained to develop an unbiased carbon estimator by using 92 1-ha ground plots distributed across key forest types in DRC. LiDAR samples provided estimates of mean and uncertainty of aboveground carbon density at provincial scales and were combined with optical and radar satellite imagery in a machine learning algorithm to map forest height and carbon density over the entire country. By using the forest definition of DRC, we found a total of 23.3u2009±u20091.6 GtC carbon with a mean carbon density of 140u2009±u20099 MgC ha−1 in the aboveground and belowground live trees. The probability based LiDAR samples capture variations of structure and carbon across edaphic and climate conditions, and provide an alternative approach to national ground inventory for efficient and precise assessment of forest carbon resources for emission reduction (ER) programs.

Assessing the role of megafauna in tropical forest ecosystems and biogeochemical cycles - the potential of vegetation models

Megafauna (terrestrial vertebrate herbivores > 5 kg) can have disproportionate direct and indirect effects on forest structure, function, and biogeochemical cycles. We reviewed the literature investigating these effects on tropical forest dynamics and biogeochemical cycles in relation to ecology, paleoecology, and vegetation modelling. We highlight the limitations of field-based studies in evaluating the long-term consequences of loss of megafauna. These limitations are due to inherent space-time restrictions of field-studies and a research focus on seed dispersal services provided by large animals. We further present evidence of a research gap concerning the role of megafauna in carbon cycling in tropical ecosystems. Specifically, changes in aboveground biomass might not be noticeable in short-term studies because of slow vegetation dynamics requiring decades to respond to disturbance (i.e. defaunation). Nutrient cycling has received even less attention in relation to the role of megafauna in tropical forests. We present an approach to investigate the effects of megafauna from new perspectives and with various tools (notably, vegetation models), which can simulate long-term dynamics in different environmental and megafauna density scenarios. Vegetation models could facilitate interaction between plant–animal ecology and biogeochemistry research. We present practical examples on how to integrate plant–animal interactions in vegetation models to further our understanding of the role of large herbivores in tropical forests.

Functional Composition of Tree Communities Changed Topsoil Properties in an Old Experimental Tropical Plantation

Forest biogeochemistry is strongly determined by the interaction between the tree community and the topsoil. Functional strategies of tree species are coupled to specific chemical leaf traits, and thus also to litter composition, which affects mineral soil characteristics. The limited understanding on this interaction is mainly based on shorter-term common garden experiments in temperate forest, and needs to be extended to other forest types and climates if we want to understand the universality of this linkage. In particular, for highly diverse tropical forests, our understanding of this interaction remains limited. Using an old experimental plantation within the central Congo basin, we examined the relationship between leaf and litter chemical composition and topsoil properties. Canopy, litter and topsoil characteristics were measured and we determined how the community-level leaf and litter chemical composition altered the topsoil carbon, major plant nutrients and exchangeable cation concentration, acidity and pH over the last eight decades. We found that functional composition strongly affected topsoil pH. In turn, topsoil pH strongly determined the soil total carbon and available phosphorus, total nitrogen and exchangeable potassium. Our results indicate that, as observed in temperate common garden experiments, trees alter chemical topsoil properties primarily through soil acidification, differently induced by functional composition of the tree community. The strong link between this community-level composition and topsoil characteristics, on a highly representative soil type for the tropics, improves our understanding of tropical forests biogeochemistry.

Reconciling biodiversity and carbon stock conservation in an Afrotropical forest landscape

Positive relationships between carbon storage and taxonomic diversity are not predominant at the local scale. Protecting aboveground carbon stocks in tropical forests is essential for mitigating global climate change and is assumed to simultaneously conserve biodiversity. Although the relationship between tree diversity and carbon stocks is generally positive, the relationship remains unclear for consumers or decomposers. We assessed this relationship for multiple trophic levels across the tree of life (10 organismal groups, 3 kingdoms) in lowland rainforests of the Congo Basin. Comparisons across regrowth and old-growth forests evinced the expected positive relationship for trees, but not for other organismal groups. Moreover, differences in species composition between forests increased with difference in carbon stock. These variable associations across the tree of life contradict the implicit assumption that maximum co-benefits to biodiversity are associated with conservation of forests with the highest carbon storage. Initiatives targeting climate change mitigation and biodiversity conservation should include both old-growth and regenerating forests to optimally benefit biodiversity and carbon storage.