BAAD: A biomass and allometry database for woody plants.

Understanding how plants are constructed—i.e., how key size dimensions and the amount of mass invested in different tissues varies among individuals—is essential for modeling plant growth, carbon stocks, and energy fluxes in the terrestrial biosphere. Allocation patterns can differ through ontogeny, but also among coexisting species and among species adapted to different environments. While a variety of models dealing with biomass allocation exist, we lack a synthetic understanding of the underlying processes. This is partly due to the lack of suitable data sets for validating and parameterizing models. To that end, we present the Biomass And Allometry Database (BAAD) for woody plants. The BAAD contains 259 634 measurements collected in 176 different studies, from 21 084 individuals across 678 species. Most of these data come from existing publications. However, raw data were rarely made public at the time of publication. Thus, the BAAD contains data from different studies, transformed into standard units and variable names. The transformations were achieved using a common workflow for all raw data files. Other features that distinguish the BAAD are: (i) measurements were for individual plants rather than stand averages; (ii) individuals spanning a range of sizes were measured; (iii) plants from 0.01– 100 m in height were included; and (iv) biomass was estimated directly, i.e., not indirectly via allometric equations (except in very large trees where biomass was estimated from detailed sub-sampling). We included both wild and artificially grown plants. The data set contains the following size metrics: total leaf area; area of stem cross-section including sapwood, heartwood, and bark; height of plant and crown base, crown area, and surface area; and the dry mass of leaf, stem, branches, sapwood, heartwood, bark, coarse roots, and fine root tissues. We also report other properties of individuals (age, leaf size, leaf mass per area, wood density, nitrogen content of leaves and wood), as well as information about the growing environment (location, light, experimental treatment, vegetation type) where available. It is our hope that making these data available will improve our ability to understand plant growth, ecosystem dynamics, and carbon cycling in the world’s vegetation.EEA Santa CruzFil: Falster, Daniel S. Macquarie University. Biological Sciences; Australia.Fil: Duursma, Remko A. University of Western Sydney. Hawkesbury Insitute for the Environment; Australia.Fil: Ishihara, Masae I. Hiroshima University. Graduate School for International Development and Cooperation; Japón.Fil: Barneche, Diego R. Macquarie University. Biological Sciences; Australia.Fil: FitzJohn, Richard G. Macquarie University. Biological Sciences; Australia.Fil: Vårhammar, Angelica. University of Western Sydney. Hawkesbury Insitute for the Environment; Australia.Fil: Aiba, Masahiro. Tohoku University. Graduate School of Life Sciences; Japón.Fil: Ando, Makoto. Kyoto University. Field Science Education and Research Center; JapónFil: Anten, Niels. Centre for Crop Systems Analysis; Países BajosFil: Aspinwall, Michael J. University of Western Sydney. Hawkesbury Insitute for the Environment; Australia.Fil: Gargaglione Verónica Beatriz. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Santa Cruz; Argentina.Fil: Gargaglione Verónica Beatriz. Universidad Nacional de la Patagonia Austral; Argentina.Fil: Peri, Pablo Luis. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Santa Cruz; Argentina.Fil: Peri, Pablo Luis. Universidad Nacional de la Patagonia Austral; Argentina.Fil: Peri, Pablo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: York, Robert A. University of California Berkeley. Center for Forestry; Estados Unido

Large sensitivity in land carbon storage due to geographical and temporal variation in the thermal response of photosynthetic capacity

1. Plant temperature responses vary geographically, reflecting thermally contrasting habitats and long‐term species adaptations to their climate of origin. Plants also can acclimate to fast temporal changes in temperature regime to mitigate stress. Although plant photosynthetic responses are known to acclimate to temperature, many global models used to predict future vegetation and climate–carbon interactions do not include this process. 2. We quantify the global and regional impacts of biogeographical variability and thermal acclimation of temperature response of photosynthetic capacity on the terrestrial carbon (C) cycle between 1860 and 2100 within a coupled climate–carbon cycle model, that emulates 22 global climate models. 3. Results indicate that inclusion of biogeographical variation in photosynthetic temperature response is most important for present‐day and future C uptake, with increasing importance of thermal acclimation under future warming. Accounting for both effects narrows the range of predictions of the simulated global land C storage in 2100 across climate projections (29% and 43% globally and in the tropics, respectively). 4. Contrary to earlier studies, our results suggest that thermal acclimation of photosynthetic capacity makes tropical and temperate C less vulnerable to warming, but reduces the warming‐induced C uptake in the boreal region under elevated CO2

The impact of alternative trait-scaling hypotheses for the maximum photosynthetic carboxylation rate (Vcmax) on global gross primary production

The maximum photosynthetic carboxylation rate (Vcmax) is an influential plant trait that has multiple scaling hypotheses, which is a source of uncertainty in predictive understanding of global gross primary production (GPP). Four trait-scaling hypotheses (plant functional type, nutrient limitation, environmental filtering, and plant plasticity) with nine specific implementations were used to predict global Vcmax distributions and their impact on global GPP in the Sheffield Dynamic Global Vegetation Model (SDGVM). Global GPP varied from 108.1 to 128.2 PgC yr−1, 65% of the range of a recent model intercomparison of global GPP. The variation in GPP propagated through to a 27% coefficient of variation in net biome productivity (NBP). All hypotheses produced global GPP that was highly correlated (r = 0.85–0.91) with three proxies of global GPP. Plant functional type-based nutrient limitation, underpinned by a core SDGVM hypothesis that plant nitrogen (N) status is inversely related to increasing costs of N acquisition with increasing soil carbon, adequately reproduced global GPP distributions. Further improvement could be achieved with accurate representation of water sensitivity and agriculture in SDGVM. Mismatch between environmental filtering (the most data-driven hypothesis) and GPP suggested that greater effort is needed understand Vcmax variation in the field, particularly in northern latitudes

TRY plant trait database – enhanced coverage and open access

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–environmental 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

TRY plant trait database – enhanced coverage and open access

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–environmental 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

Coming back to our senses: Exploring the potential of guided forest bathing as an intervention for human-nature connection

Fostering human-nature connection (HNC) relates to the inner worlds of humans as a realm of influence for sustainability and is considered a deep leverage point for system transformation. Both direct nature experiences and states of mindfulness are significant for influencing the development of HNC. Therefore, in this thesis, I explore the potential of guided forest bathing – an originally Japanese practice of mindfully immersing one’s senses in the atmosphere of a forest – as an intervention for HNC. I do so by applying a mixed-methods approach and a relational, multidimensional assessment of the qualities and effects of a guided forest bathing session, as conducted in the methodology of the Scandinavian Nature and Forest Therapy Institute. While not able to establish causality, the study results suggest that participation in just one guided forest bathing session may positively influence the development of HNC, primarily in participants new to the experience. The results also suggest that several qualities of guided forest bating are important for influencing HNC, including mindfulness, engagement of senses, and self-restoration. These qualities and others related to the specific structure and social setting of the experience can provoke thoughts that meaningfully shift how individuals perceive and interact with nature. This leads the thesis to conclude that guided forest bathing represents a novel nature experience with promising potential as an intervention for HNC

Coming back to our senses: Exploring the potential of guided forest bathing as an intervention for human-nature connection

Fostering human-nature connection (HNC) relates to the inner worlds of humans as a realm of influence for sustainability and is considered a deep leverage point for system transformation. Both direct nature experiences and states of mindfulness are significant for influencing the development of HNC. Therefore, in this thesis, I explore the potential of guided forest bathing – an originally Japanese practice of mindfully immersing one’s senses in the atmosphere of a forest – as an intervention for HNC. I do so by applying a mixed-methods approach and a relational, multidimensional assessment of the qualities and effects of a guided forest bathing session, as conducted in the methodology of the Scandinavian Nature and Forest Therapy Institute. While not able to establish causality, the study results suggest that participation in just one guided forest bathing session may positively influence the development of HNC, primarily in participants new to the experience. The results also suggest that several qualities of guided forest bating are important for influencing HNC, including mindfulness, engagement of senses, and self-restoration. These qualities and others related to the specific structure and social setting of the experience can provoke thoughts that meaningfully shift how individuals perceive and interact with nature. This leads the thesis to conclude that guided forest bathing represents a novel nature experience with promising potential as an intervention for HNC