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. Geosphere-Biosphere Program (IGBP) and DIVERSITAS, the TRY database (TRY-not an acronym, rather a statement of sentiment; https ://www.try-db.org; Kattge et al., 2011) was proposed with the explicit assignment to improve the availability and accessibility of plant trait data for ecology and earth system sciences. The Max Planck Institute for Biogeochemistry (MPI-BGC) offered to host the database and the different groups joined forces for this community-driven program. Two factors were key to the success of TRY: the support and trust of leaders in the field of functional plant ecology submitting large databases and the long-term funding by the Max Planck Society, the MPI-BGC and the German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, which has enabled the continuous development of the TRY database.

[1] This study analyzes evapotranspiration data for three wet and two seasonally dry rain forest sites in Amazonia. The main environmental (net radiation, vapor pressure deficit, and aerodynamic conductance) and vegetation (surface conductance) controls of evapotranspiration are also assessed. Our research supports earlier studies that demonstrate that evapotranspiration in the dry season is higher than that in the wet season and that surface net radiation is the main controller of evapotranspiration in wet equatorial sites. However, our analyses also indicate that there are different factors controlling the seasonality of evapotranspiration in wet equatorial rain forest sites and southern seasonally dry rain forests. While the seasonality of evapotranspiration in wet equatorial forests is driven solely by environmental factors, in seasonally dry forests, it is also biotically controlled with the surface conductance varying between seasons by a factor of approximately 2. The identification of these different drivers of evapotranspiration is a major step forward in our understanding of the water dynamics of tropical forests and has significant implications for the future development of vegetation-atmosphere models and land use and conservation planning in the region.

Aim Spatial and temporal biases in species-occurrence data can compromise broad-scale biogeographical research and conservation planning. Although spatial biases have been frequently scrutinized, temporal biases and the overall quality of species-occurrence data have received far less attention. This study aims to answer three questions: (1) How reliable are species-occurrence data for flowering plants in Africa? (2) Where and when did botanical sampling occur in the past 300 years? (3) How complete are plant inventories for Africa?Methods By filtering a publicly available dataset containing 3.5 million records of flowering plants, we obtained 934,676 herbarium specimens with complete information regarding species name, date and location of collection. Based on these specimens, we estimated inventory completeness for sampling units (SUs) of 25 km 3 25 km. We then tested whether the spatial distribution of well-sampled SUs was correlated with temporal parameters of botanical sampling. Finally, we determined whether inventory completeness in individual countries was related to old or recently collected specimens.Results Thirty-one per cent of SUs contained at least one specimen, whereas only 2.4% of SUs contained a sufficient number of specimens to reliably estimate inventory completeness. We found that the location of poorly sampled areas remained almost unchanged for half a century. Moreover, there was pronounced temporal bias towards old specimens in South Africa, the country that holds half of the available data for the continent. There, high inventory completeness stems from specimens collected several decades ago.Main conclusions Despite the increasing availability of species occurrence data for Africa, broad-scale biogeographical research is still compromised by the uncertain quality and spatial and temporal biases of such data. To avoid erroneous inferences, the quality and biases in species-occurrence data should be critically evaluated and quantified prior to use. To this end, we propose a quantification method based on inventory completeness using easily accessible species-occurrence data.

Understanding public perceptions of biodiversity is essential to ensure continued support for conservation efforts. Despite this, insights remain scarce at broader spatial scales, mostly due to a lack of adequate methods for their assessment. The emergence of new technologies with global reach and high levels of participation provide exciting new opportunities to study the public visibility of biodiversity and the factors that drive it. Here, we use a measure of internet saliency to assess the national and international visibility of species within four taxa of Brazilian birds (toucans, hummingbirds, parrots and woodpeckers), and evaluate how much of this visibility can be explained by factors associated with familiarity, aesthetic appeal and conservation interest. Our results strongly indicate that familiarity (human population within the range of a species) is the most important factor driving internet saliency within Brazil, while aesthetic appeal (body size) best explains variation in international saliency. Endemism and conservation status of a species had small, but often negative, effects on either metric of internet saliency. While further studies are needed to evaluate the relationship between internet content and the cultural visibility of different species, our results strongly indicate that internet saliency can be considered as a broad proxy of cultural interest.

Digital Data Sources and Methods approaches to explore connections between topics, time-series analysis for temporal data, and spatial modeling to highlight spatial patterns. Outstanding challenges associated with culturomics research include issues of interdisciplinarity, ethics, data biases, and validation. The practical guidance we offer will help conservation researchers and practitioners identify and obtain the necessary data and carry out appropriate analyses for their specific questions, thus facilitating the wider adoption of culturomics approaches for conservation applications.

Accurate estimates of photosynthetically active radiation (PAR) are critical for the development of realistic models of plant productivity. However, in many areas such as the vast Amazon region of South America, there have been few empirical studies of PAR. Here, we analyzed the relationship between PAR and broadband solar irradiance (R s ) and formulated models to estimate PAR in two experimental sites (pasture and forest) in the Brazilian Amazon. Three different models of increasing complexity were developed based on information from R s (model 1), R s and clearness index (k t ; model 2), and R s , k t , and water vapor pressure (model 3). Estimates of PAR were generated for each season and for the entire year. All models had very high determination coefficients and indices of agreement for both pasture and forest sites. This strongly supports the use of R s and k t to produce robust estimates of PAR. The results obtained by annual models were close than that found by seasonal models, demonstrating that a single annual model is able to estimate PAR, albeit with lower accuracy.

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