Author correction : a global database for metacommunity ecology, integrating species, traits, environment and space

Correction to: Scientific Data https://doi.org/10.1038/s41597-019-0344-7, published online 08 January 202

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

This article has 730 authors, of which I have only listed the lead author and myself as a representative of University of HelsinkiPlant 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.Peer reviewe

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

KONCEPCJA I REALIZACJA SYSTEMU PLECAKOWEGO DLA WIELOKANAŁOWEJ ELEKTROFIZJOLOGII U SWOBODNIE ZACHOWUJĄCYCH SIĘ GRYZONI

Technologies for multichannel electrophysiology are experiencing astounding growth. Numbers of channels reach thousands of recording sites, systems are often combined with electrostimulations and optic stimulations. However, the task of design the cheap, flexible system for freely behaving animals without tethered cable are not solved completely. We propose the system for multichannel electrophysiology for both rats and mice. The system allows to record unit activity and local field potential (LFP) up to 32 channels with different types of electrodes. The system was constructed using Intan technologies RHD 2132 chip. Data acquisition and recordings take place on the DAQ-card, which is placed as a back-pack on the animal. The signal is amplified with amplifier cascade and digitalized with 16-bit ADC. Instrumental filters allow to filter the signal in 0.1–20000 Hz bandwidth. The system is powered from the mini-battery with capacity 340 mA/hr. The system was validated with generated signals, in anaesthetized rat and showed a high quality of recordings.Technologie elektrofizjologii wielokanałowej odnotowują zdumiewający wzrost. Liczba kanałów dociera do tysięcy miejsc rejestracji, systemy często łączone są z elektrostymulacjami i stymulacjami optycznymi. Jednak zadanie zaprojektowania taniego, elastycznego systemu pozwalającego na swobodne zachowania zwierząt bez przywiązanego kabla nie zostało całkowicie rozwiązane. Zaproponowano system wielokanałowej elektrofizjologii zarówno dla szczurów, jak i myszy. System pozwala rejestrować aktywność jednostki i potencjał pola lokalnego (LFP) do 32 kanałów z różnymi rodzajami elektrod. System został zbudowany przy użyciu technologii Intan RHD 2132. Akwizycja danych i nagrania odbywają się na karcie DAQ, która została umieszczona w plecaku zwierzęcia. Sygnał jest wzmacniany kaskadą wzmacniaczy i digitalizowany za pomocą 16-bitowego przetwornika ADC. Filtry pozwalają filtrować sygnał w paśmie 0,1–20000 Hz. Zasilany jest z mini-baterii o wydajności 340 mA/godz. System został zwalidowany generowanymi sygnałami u znieczulonego szczura i wykazał wysoką jakość nagrań