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

Contributions to the Wood Anatomy of the Rubioideae (Rubiaceae)

The secondary xylem of Craterispermeae, Coussareeae, Morindeae s.str., Prismatomerideae, Pauridiantheae, Urophylleae, and Triainolepideae (Rubiaceae, Rubioideae) is described and illustrated in detail. Genera that were previously placed in the Morindeae or Psychotrieae such as Damnacanthus, Lasianthus, Saldinia, and Trichosfachys are also included. Wood anatomical characters are compared with recent phylogenetic insights into the study group on the basis of molecular data. The observations demonstrate that the delimitation and separation of several taxa from the former Coussareeae/Morindeae/Prismatomerideae/Psychotrieae aggregate is supported by wood anatomical data. The Coussareeae can be distinguished from the other Rubioideae by their scanty parenchyma, septate libriform fibres, and the combination of uniseriate and very high multiseriate rays with sheath cells. Axial parenchyma bands and fibre-tracheids characterise Gynochtodes and some species of Morinda (Morindeae sstr.), but the latter genus is variable with respect to several features (e.g. vessel groupings and axial parenchyma distribution). Wood data support separation of Rennelia and Prismatomeris from Morindeae s.str.; vessels in both genera are exclusively solitary and axial parenchyma is always diffuse to diffuse-in-aggregates. Damnacanthus differs from the Morindeae alliance by the occurrence of septate fibres, absence of axial parenchyma, and the occasional presence of fibre wall thickenings. There are interesting similarities between members of the Lasianfhus clade and the Pauridiantheae/Urophyleae group such as the sporadic occurrence of spiral thickenings in axial parenchyma cells

IAWA List of Microscopic Bark Features

NaturalisPlant science

Flowering-time genes modulate meristem determinacy and growth form in Arabidopsis thaliana

Plants have evolved annual and perennial life forms as alternative strategies to adapt reproduction and survival to environmental constraints. In isolated situations, such as islands, woody perennials have evolved repeatedly from annual ancestors(1). Although the molecular basis of the rapid evolution of insular woodiness is unknown, the molecular difference between perennials and annuals might be rather small, and a change between these life strategies might not require major genetic innovations(2,3). Developmental regulators can strongly affect evolutionary variation(4) and genes involved in meristem transitions are good candidates for a switch in growth habit. We found that the MADS box proteins SUPPRESSOR OF OVEREXPRESSION OF CONSTANS 1 ( SOC1) and FRUITFULL (FUL) not only control flowering time, but also affect determinacy of all meristems. In addition, downregulation of both proteins established phenotypes common to the lifestyle of perennial plants, suggesting their involvement in the prevention of secondary growth and longevity in annual life forms

Overview of current practices in data analysis for wood identification. A guide for the different timber tracking methods

Today we have five types of timber tracking tools available. Each has its ownstrengths and limitations (see the Timber Tracking Tool Infogram), but togetherthey offer a broad range of methods that can assist us in identifying the botanical aswell as the geographic origin (provenance) of most kinds of timber samples, eventhose smaller than 1 cm³.With this guide we want to provide an overview of the current best-practicemethods used to analyse data derived from different wood identification methods,while presenting their respective strengths and limitations. We give advice on dataanalysis, from the development of reference data, through to the verification ofidentity and provenance of unknown samples against the reference database. We endwith an expert view on combining methods for wood identification and discusshow timber identification possibilities could expand in the future.The guide is meant for all researchers doing identification work to support regularlaw enforcement measures, initiatives for transparent supply chains, andcontinued scientific research. Undertaking forensic casework is qualitativelydifferent from undertaking scientific research (UNODC 2016)1. To support court cases,the chain of custody of evidence material must be tracked and reference materialmust be valid. How to fulfil all requirements for forensic timber identification will notbe discussed here. Instead, we refer to the best practice guide of the UNODC (2016)and the standards and guidelines of the Society for Wildlife Forensic Sciences.We hope that this guide will be a first step towards the harmonisation of dataanalysis procedures within the global network of wood identification experts; andwill facilitate collaborations, further innovations, and ensure reliable timber trackingmethods

Evolution of endemismon a young tropical mountain

Tropical mountains are hot spots of biodiversity and endemism(1-3), but the evolutionary origins of their unique biotas are poorly understood(4). In varying degrees, local and regional extinction, long-distance colonization, and local recruitment may all contribute to the exceptional character of these communities(5). Also, it is debated whether mountain endemics mostly originate from local lowland taxa, or from lineages that reach the mountain by long-range dispersal from cool localities elsewhere(6). Here we investigate the evolutionary routes to endemism by sampling an entire tropical mountain biota on the 4,095-metre-high Mount Kinabalu in Sabah, East Malaysia. We discover that most of its unique biodiversity is younger than the mountain itself (6 million years), and comprises a mix of immigrant pre-adapted lineages and descendants from local lowland ancestors, although substantial shifts from lower to higher vegetation zones in this latter group were rare. These insights could improve forecasts of the likelihood of extinction and 'evolutionary rescue'(7) in montane biodiversity hot spots under climate change scenarios

Global trait:environment relationships of plant communities

Abstract Plant functional traits directly affect ecosystem functions. At the species level, trait combinations depend on trade-offs representing different ecological strategies, but at the community level trait combinations are expected to be decoupled from these trade-offs because different strategies can facilitate co-existence within communities. A key question is to what extent community-level trait composition is globally filtered and how well it is related to global versus local environmental drivers. Here, we perform a global, plot-level analysis of trait–environment relationships, using a database with more than 1.1 million vegetation plots and 26,632 plant species with trait information. Although we found a strong filtering of 17 functional traits, similar climate and soil conditions support communities differing greatly in mean trait values. The two main community trait axes that capture half of the global trait variation (plant stature and resource acquisitiveness) reflect the trade-offs at the species level but are weakly associated with climate and soil conditions at the global scale. Similarly, within-plot trait variation does not vary systematically with macro-environment. Our results indicate that, at fine spatial grain, macro-environmental drivers are much less important for functional trait composition than has been assumed from floristic analyses restricted to co-occurrence in large grid cells. Instead, trait combinations seem to be predominantly filtered by local-scale factors such as disturbance, fine-scale soil conditions, niche partitioning and biotic interactions

sPlotOpen:an environmentally balanced, open-access, global dataset of vegetation plots

Abstract Motivation: Assessing biodiversity status and trends in plant communities is critical for understanding, quantifying and predicting the effects of global change on ecosystems. Vegetation plots record the occurrence or abundance of all plant species co-occurring within delimited local areas. This allows species absences to be inferred, information seldom provided by existing global plant datasets. Although many vegetation plots have been recorded, most are not available to the global research community. A recent initiative, called ‘sPlot’, compiled the first global vegetation plot database, and continues to grow and curate it. The sPlot database, however, is extremely unbalanced spatially and environmentally, and is not open-access. Here, we address both these issues by (a) resampling the vegetation plots using several environmental variables as sampling strata and (b) securing permission from data holders of 105 local-to-regional datasets to openly release data. We thus present sPlotOpen, the largest open-access dataset of vegetation plots ever released. sPlotOpen can be used to explore global diversity at the plant community level, as ground truth data in remote sensing applications, or as a baseline for biodiversity monitoring. Main types of variable contained: Vegetation plots (n = 95,104) recording cover or abundance of naturally co-occurring vascular plant species within delimited areas. sPlotOpen contains three partially overlapping resampled datasets (c. 50,000 plots each), to be used as replicates in global analyses. Besides geographical location, date, plot size, biome, elevation, slope, aspect, vegetation type, naturalness, coverage of various vegetation layers, and source dataset, plot-level data also include community-weighted means and variances of 18 plant functional traits from the TRY Plant Trait Database. Spatial location and grain: Global, 0.01–40,000 m². Time period and grain: 1888–2015, recording dates. Major taxa and level of measurement: 42,677 vascular plant taxa, plot-level records. Software format: Three main matrices (.csv), relationally linked