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

The spatial variability of turbulence above a forest

The spatial variability of turbulence above a forest has been examined. Two measurement towers were erected 800 m apart within a heterogeneous mixed forest located in the north east of the Netherlands. The measurements of u*/u were analysed and subsequently used to test a surface layer model. The model simulated the magnitude of the measurements reasonably well, but measured trends were not always reproduced by the model. The variable (du/dz)/u did not adapt as quickly to the new surface as u*/u. This is in agreement with Schmid (1994), and can be explained by a local decrease in mixing length. It is recommended to adapt the mixing length near a surface transition to improve the accuracy of surface layer models of heterogeneous landscapes

Fetch Requirements near a Forest Edge

Measurements on forest-atmosphere exchange should be executed some distance from the forest boundaries to be representative for this forest. In this study the minimum fetch at measuring height is estimated by analysing measurements just above a mixed forest stand near the edge. The objective was to gain insight in the development of the Equilibrium Layer (EL) after a transition in vegetation height; only wind and shear stress were considered. The variations in u*/u and wind speed gradients above the canopy, as a function of wind direction and fetch were analysed. In this canopy roughness layer, stability corrections are small due to the large roughness of the forest. An adapted version of the model was used to simulate fluxes as well as gradients above the forest. It appeared that the disturbances from equilibrium arise not only from the forest edges, but also from the local changes in tree height between patches within the forest itself. A fetch:height ratio of 36 for the EL seemed appropriate for specific fetch directions at the site under study. This is in agreement with previous studies.

Increased heat fluxes near a forest edge

Observations of sensible and latent heat flux above forest downwind of a forest edge show these fluxes to be larger than the available energy over the forest. The enhancement averages to 56 W m-2, or 16% of the net radiation, at fetches less than 400 m, equivalent to fetch to height ratios less than 15. The enhancement of turbulent energy fluxes is explained by advection and increases with the difference in temperature and humidity of the air over the upwind area as compared to the forest. The relatively high temperature and humidity of the upwind air are not caused by high surface heat fluxes, but are explained by the relatively low aerodynamic roughness of the upwind surface. Although the heat fluxes over forest are enhanced, the momentum fluxes are almost adjusted to the underlying forest. The different behaviour of heat and momentum fluxes is explained by absorption of momentum by pressure gradients near the forest edge. It is concluded that fetch requirements to obtain accurate surface fluxes from atmospheric observations need to be more stringent for scalar fluxes as compared to momentum fluxes.

TRY plant trait database, enhanced coverage and open access

Plant traits-the morphological, ahawnatomical, 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