Leaf and stem economics spectra drive diversity of functional plant traits in a dynamic global vegetation model

Functional diversity is critical for ecosystem dynamics, stability and productivity. However, dynamic global vegetation models (DGVMs) which are increasingly used to simulate ecosystem functions under global change, condense functional diversity to plant functional types (PFTs) with constant parameters. Here, we develop an individual‐ and trait‐based version of the DGVM LPJmL (Lund‐Potsdam‐Jena managed Land) called LPJmL‐ flexible individual traits (LPJmL‐FIT) with flexible individual traits) which we apply to generate plant trait maps for the Amazon basin. LPJmL‐FIT incorporates empirical ranges of five traits of tropical trees extracted from the TRY global plant trait database, namely specific leaf area (SLA), leaf longevity (LL), leaf nitrogen content (N_area), the maximum carboxylation rate of Rubisco per leaf area (), and wood density (WD). To scale the individual growth performance of trees, the leaf traits are linked by trade‐offs based on the leaf economics spectrum, whereas wood density is linked to tree mortality. No preselection of growth strategies is taking place, because individuals with unique trait combinations are uniformly distributed at tree establishment. We validate the modeled trait distributions by empirical trait data and the modeled biomass by a remote sensing product along a climatic gradient. Including trait variability and trade‐offs successfully predicts natural trait distributions and achieves a more realistic representation of functional diversity at the local to regional scale. As sites of high climatic variability, the fringes of the Amazon promote trait divergence and the coexistence of multiple tree growth strategies, while lower plant trait diversity is found in the species‐rich center of the region with relatively low climatic variability. LPJmL‐FIT enables to test hypotheses on the effects of functional biodiversity on ecosystem functioning and to apply the DGVM to current challenges in ecosystem management from local to global scales, that is, deforestation and climate change effects.     

Diversity of Tropical Tree Seedling Responses to Drought

Drought is an important seedling mortality agent in dry and moist tropical forests, and more severe and frequent droughts are predicted in the future. The effect of drought on leaf gas exchange and seedling survival was tested in a dry-down experiment with four tree species from dry and moist forests in Bolivia. Seedlings were droughted and wilting stage and gas exchange were monitored. Drought led to a gradual reduction of photosynthesis and stomatal conductance over time, whereas respiration and photosynthetic water-use efficiency initially increased with drought and then declined. Seedlings gradually went through the different wilting stages, until they eventually died, but the trajectory differed for the four species. The strong relationship between wilting stage and photosynthesis means that simple field observations can provide valuable information on plant physiological performance. Three different drought strategies were identified. Dry forest species Ceiba samauma shed its leaves and survived. The moist forest species Cariniana ianeirensis postponed drought stress by having low rates of transpiration and high water-use efficiency. Dry forest Astronium urundeuva and moist forest Triplaris americana followed an opportunistic strategy; they are early successional species that can quickly grow to maturity but periodic drought can be lethal. Strikingly, dry and moist forest species did not differ clearly in their drought tolerance strategies.     

Coupling of Methanothermobacter thermautotrophicus Methane Formation and Growth in Fed-Batch and Continuous Cultures under Different H2 Gassing Regimens

In nature, H₂- and CO₂-utilizing methanogenic archaea have to couple the processes of methanogenesis and autotrophic growth under highly variable conditions with respect to the supply and concentration of their energy source, hydrogen. To study the hydrogen-dependent coupling between methanogenesis and growth, Methanothermobacter thermautotrophicus was cultured in a fed-batch fermentor and in a chemostat under different 80% H₂-20% CO₂ gassing regimens while we continuously monitored the dissolved hydrogen partial pressures (p_H2). In the fed-batch system, in which the conditions continuously changed the uptake rates by the growing biomass, the organism displayed a complex and yet defined growth behavior, comprising the consecutive lag, exponential, and linear growth phases. It was found that the in situ hydrogen concentration affected the coupling between methanogenesis and growth in at least two respects. (i) The microorganism could adopt two distinct theoretical maximal growth yields (Y_{CH4 max}), notably approximately 3 and 7 g (dry weight) of methane formed mol⁻¹, for growth under low (p_H2 < 12 kPa)- and high-hydrogen conditions, respectively. The distinct values can be understood from a theoretical analysis of the process of methanogenesis presented in the supplemental material associated with this study. (ii) The in situ hydrogen concentration affected the “specific maintenance” requirements or, more likely, the degree of proton leakage and proton slippage processes. At low p_H2 values, the “specific maintenance” diminished and the specific growth yields approached Y_{CH4 max}, indicating that growth and methanogenesis became fully coupled.     

Coupling of Methanothermobacter thermautotrophicus methane formation and growth in fed-batch and continuous cultures under different H2 gassing regimens

In nature, H2- and CO2-utilizing methanogenic archaea have to couple the processes of methanogenesis and autotrophic growth under highly variable conditions with respect to the supply and concentration of their energy source, hydrogen. To study the hydrogen-dependent coupling between methanogenesis and growth, Methanothermobacter thermautotrophicus was cultured in a fed-batch fermentor and in a chemostat under different 80% H(2)-20% CO2 gassing regimens while we continuously monitored the dissolved hydrogen partial pressures (pH2). In the fed-batch system, in which the conditions continuously changed the uptake rates by the growing biomass, the organism displayed a complex and yet defined growth behavior, comprising the consecutive lag, exponential, and linear growth phases. It was found that the in situ hydrogen concentration affected the coupling between methanogenesis and growth in at least two respects. (i) The microorganism could adopt two distinct theoretical maximal growth yields (YCH4 max), notably approximately 3 and 7 g (dry weight) of methane formed mol-1, for growth under low (pH2 < 12 kPa)- and high-hydrogen conditions, respectively. The distinct values can be understood from a theoretical analysis of the process of methanogenesis presented in the supplemental material associated with this study. (ii) The in situ hydrogen concentration affected the "specific maintenance" requirements or, more likely, the degree of proton leakage and proton slippage processes. At low pH2 values, the "specific maintenance" diminished and the specific growth yields approached YCH4 max, indicating that growth and methanogenesis became fully coupled.     

Growth-Factor-Driven Rescue to Receptor Tyrosine Kinase (RTK) Inhibitors through Akt and Erk Phosphorylation in Pediatric Low Grade Astrocytoma and Ependymoma

Up to now, several clinical studies have been started investigating the relevance of receptor tyrosine kinase (RTK) inhibitors upon progression free survival in various pediatric brain tumors. However, single targeted kinase inhibition failed, possibly due to tumor resistance mechanisms. The present study will extend our previous observations that vascular endothelial growth factor receptor (VEGFR)-2, platelet derived growth factor receptor (PDGFR)β, Src, the epidermal growth factor receptor (ErbB) family, and hepatocyte growth factor receptor (HGFR/cMet) are potentially drugable targets in pediatric low grade astrocytoma and ependymoma with investigations concerning growth-factor-driven rescue. This was investigated in pediatric low grade astrocytoma and ependymoma cell lines treated with receptor tyrosine kinase (RTK) inhibitors e.g. sorafenib, dasatinib, canertinib and crizotinib. Flow cytometry analyses showed high percentage of cells expressing VEGFR-1, fibroblast growth factor receptor (FGFR)-1, ErbB1/EGFR, HGFR and recepteur d’origine nantais (RON) (respectively 52-77%, 34-51%, 63-90%, 83-98%, 65-95%). Their respective inhibitors induced decrease of cell viability, measured with WST-1 cell viability assays. At least this was partially due to increased apoptotic levels measured by Annexin V/Propidium Iodide apoptosis assays. EGF, HGF and FGF, which are normally expressed in brain (tumor) tissue, showed to be effective rescue inducing growth factors resulting in increased cell survival especially during treatment with dasatinib (complete rescue) or sorafenib (partial rescue). Growth-factor-driven rescue was less prominent when canertinib or crizotinib were used. Rescue was underscored by significantly activating downstream Akt and/or Erk phosphorylation and increased tumor cell migration. Combination treatment showed to be able to overcome the growth-factor-driven rescue. In conclusion, our study highlights the extensive importance of environmentally present growth factors in developing tumor escape towards RTK inhibitors in pediatric low grade astrocytoma and ependymoma. It is of great interest to anticipate upon these results for the design of new therapeutic trials with RTK inhibitors in these pediatric brain tumors.     

Distribution of twelve moist forest canopy tree species in Liberia and Côte d'Ivoire: response curves to a climatic gradient

Abstract. The occurrence and abundance of 12 canopy tree species from the moist tropical forests of West Africa have been studied in relation to a climatic gradient. We focused on environmental factors related to water availability: annual amount of rainfall, the length of the dry season, and cumulative water deficit. Species occurrence and abundance data are used for 39 forest sites in Liberia and southwest Côte d'Ivoire. Species responses are modelled using a set of five increasingly complex models, ranging from a no-trend model to a skewed bell-shaped response curve. The study species show different distribution patterns. Most of them suggest a close relationship to climatic conditions. Fitting of species occurrence data to each of the three climatic factors results in most cases in simple models. In only one out of 36 cases a bell-shaped response curve is needed to describe the data. Four of the 12 species show no response to the climatic factors when only occurrence is evaluated. When abundance data are used, in 33 of the 36 cases significant response models are found. In general these are much more complex than in the cases of species occurrence data: in 10 of the 36 cases a bell-shaped response model is found to describe the data best. This is in contrast with the widespread belief that species response curves are bell-shaped: within the forest zone in the area studied this is not generally the case. The importance of the three climatic factors for the distribution of the species is evaluated: for four species mean annual rainfall is the most important variable, for four species the length of the dry period, and for one species cumulative water deficit. Consequently, the assumption that mean annual rainfall is the most important factor determining tree species distribution in West African forests is not correct. Species response models to climatic factors show where species have their geographical optima. Implications for forest management are briefly discussed.     

Making Large-Scale Networks from fMRI Data

Pairwise correlations are currently a popular way to estimate a large-scale network (> 1000 nodes) from functional magnetic resonance imaging data. However, this approach generally results in a poor representation of the true underlying network. The reason is that pairwise correlations cannot distinguish between direct and indirect connectivity. As a result, pairwise correlation networks can lead to fallacious conclusions; for example, one may conclude that a network is a small-world when it is not. In a simulation study and an application to resting-state fMRI data, we compare the performance of pairwise correlations in large-scale networks (2000 nodes) against three other methods that are designed to filter out indirect connections. Recovery methods are evaluated in four simulated network topologies (small world or not, scale-free or not) in scenarios where the number of observations is very small compared to the number of nodes. Simulations clearly show that pairwise correlation networks are fragmented into separate unconnected components with excessive connectedness within components. This often leads to erroneous estimates of network metrics, like small-world structures or low betweenness centrality, and produces too many low-degree nodes. We conclude that using partial correlations, informed by a sparseness penalty, results in more accurate networks and corresponding metrics than pairwise correlation networks. However, even with these methods, the presence of hubs in the generating network can be problematic if the number of observations is too small. Additionally, we show for resting-state fMRI that partial correlations are more robust than correlations to different parcellation sets and to different lengths of time-series.     

Book reviews

Book reviewed in this article: A. V. DOLMATOVA et N. A. DEMINA: Les Phlébotomes (Phlebotominae) et les maladies qu'ils transmettent. Traduction française: A. Kobylansky ANONYMUS: La lutte biologique en forét. T. N. ANANTHAKRISHNAN: Indian Thysanoptera R. Fritsche , E. Karl , W. Lehman & G. Proesler : Tierische Vektoren pftanzenpathogener Viren.