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

Ocular accommodation and cognitive demand: An additional indicator besides pupil size and cardiovascular measures?

<p>Abstract</p> <p>Background</p> <p>The aim of the present study was to assess accommodation as a possible indicator of changes in the autonomic balance caused by altered cognitive demand. Accounting for accommodative responses from a human factors perspective may be motivated by the interest of designing virtual image displays or by establishing an autonomic indicator that allows for remote measurement at the human eye. Heart period, pulse transit time, and the pupillary response were considered as reference for possible closed-loop accommodative effects. Cognitive demand was varied by presenting monocularly numbers at a viewing distance of 5 D (20 cm) which had to be read, added or multiplied; further, letters were presented in a "n-back" task.</p> <p>Results</p> <p>Cardiovascular parameters and pupil size indicated a change in autonomic balance, while error rates and reaction time confirmed the increased cognitive demand during task processing. An observed decrease in accommodation could not be attributed to the cognitive demand itself for two reasons: (1) the cognitive demand induced a shift in gaze direction which, for methodological reasons, accounted for a substantial part of the observed accommodative changes. (2) Remaining effects disappeared when the correctness of task processing was taken into account.</p> <p>Conclusion</p> <p>Although the expectation of accommodation as possible autonomic indicator of cognitive demand was not confirmed, the present results are informative for the field of applied psychophysiology noting that it seems not to be worthwhile to include closed-loop accommodation in future studies. From a human factors perspective, expected changes of accommodation due to cognitive demand are of minor importance for design specifications – of, for example, complex visual displays.</p

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