Jean-Paul Laclau’s research while affiliated with French Agricultural Research Centre for International Development and other places

The extent of the potassium (K) limitation of forest productivity is probably more widespread than previously thought, and K-limitation could influence the response of forests to future global changes. To understand the effects of K-limitation on forest primary production, we have developed the first ecophysiological model simulating the K cycle and its interactions with the carbon (C) and water cycles. We focused on the limitation of the gross primary productivity (GPP) by K availability in tropical eucalypt plantations in Brazil. We used results from large-scale fertilisation experiments as well as C flux measurements in two tropical eucalypt plantations to parameterize the model. The model was parameterized for fertilised conditions and then used to test for the effects of contrasting additions of K fertiliser. Simulations showed that K-deficiency limits GPP by more than 50 % during a 6-year rotation, a value in agreement with the literature. The negative effects of K-deficiency on canopy transpiration and water use efficiency were also reported and discussed. Through a sensitivity analysis, we used the model to identify the most critical processes to consider when studying K-limitation of GPP. The external inputs of K to the stands, such as the atmospheric deposition and weathering fluxes, and the regulation of the internal fluxes of K within the ecosystem were critical for the response of the system to K deficiency. Litter decomposition processes were of lower importance. The new forest K-cycle model developed in the present study includes multiple K processes interacting with the carbon and water cycles, and strong feedbacks on GPP through forest growth were outlined.

Potassium availability constrains forest productivity. Brazilian eucalypt plantations are a good example of the K-limitation of wood production. Here, we built upon a previously described model (CASTANEA-MAESPA-K) and used it to understand whether the simulated decline in C-source under K deficiency was sufficient to explain the K-limitation of wood productivity in Brazilian eucalypt plantations. We developed allocation schemes for both C and K and included into CASTANEA-MAESPA-K. No direct limitations of the C-sink activity, nor direct modifications of the C-allocation by K availability were included in the model. Simulation results show that the model was successful in replicating the observed patterns of wood productivity, growth, NPP limitation by K deficiency. Simulations also show that the response of NPP is not linear with increasing K fertilisation. Simulated stem carbon use and water use efficiencies decreased with decreasing levels of K availability. Simulating a direct stoichiometric limitation of wood productivity, growth, NPP was not necessary to reproduce the observed decline of productivity under K limitation, suggesting that K stoichiometric plasticity could be different than that of N and P. Confirming previous results from the literature, the model simulated an intense recirculation of K in the trees, suggesting that retranslocation processes were essential for tree functioning. Optimal K fertilisation levels calculated by the model were similar to nutritional recommendations currently applied in Brazilian eucalypt plantations, paving the way for validating the model at a larger scale and this approach to develop decision-making tools to improve fertilisation practices.

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait– nvironmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.