Assembly of functional diversity in an oceanic island flora
|Oceanic island floras are well known for their morphological peculiarities and exhibit striking examples of trait evolution1. These morphological shifts are commonly attributed to insularity and are thought to be shaped by the biogeographical processes and evolutionary histories of oceanic islands. Here the authors describe the functional trait space of the native flora of an oceanic island (Tenerife, Canary Islands, Spain) using extensive field and laboratory measurements, and relate it to global trade-offs in ecological strategies. They find that the island trait space exhibits a remarkable functional richness but that most plants are concentrated around a functional hotspot dominated by shrubs with a conservative life-history strategy. Their results also suggest that colonization via long-distance dispersal and the interplay between inter-island dispersal and archipelago-level speciation processes drive functional divergence and trait space expansion. By combining biogeography, ecology and evolution, the approach opens new avenues for trait-based insights into how dispersal, speciation and persistence shape the assembly of entire native island floras. (Barajas Barbosa et al. 2023, Nature)
Consolidated ‘Plant Growth Form’ data for >200,000 species from the GIFT database now publicly available via TRY
|Highly consolidated data for ‘Plant Growth Form’ (tree, shrub, herb) for more than 200,000 species contributed to TRY by the Global Inventory of Floras and Traits (GIFT) database are now publicly available via TRY. GIFT is a global archive of regional plant checklists and floras, and plant functional traits. It contains information about the floristic status of 367,854 species across 3,485 geographic regions. In addition, functional trait information is available for 281,836 species and 109 traits.
Citizen science plant observations encode global trait patterns
|With the increasing popularity of species identification apps, citizen scientists contribute to growing vegetation data collections. Wolf et al. show that global trait patterns can be mapped by complementing vascular plant observations from the global citizen science project iNaturalist with measurements from the plant trait database TRY. The maps are evaluated against traits in the global vegetation plot dataset sPlotOpen and show correlations up to 0.69. As citizen science data collections continue to grow, they expect them to play a significant role in further improving maps of plant functional traits. (Wolf et al. 2022, Nature Ecology & Evolution)
Intercomparison of global foliar trait maps
|The intercomparison of global foliar trait maps reveals fundamental differences in upscaling approaches.
Dechant et al. compare global upscaled foliar trait maps at 0.5° spatial resolution (six maps for SLA, five for N, and three for P). Their findings indicate the importance of within-grid-cell trait variation and of the approach to account for this variation in the upscaling. (Dechant et al. 2023, EarthArXiv)
rtry - an R package to process TRY database output files
|rtry is designed to support the application of plant trait data providing easily applicable functions for the basic steps of data preprocessing, e.g. data import, data exploration, selection of columns and rows, excluding trait data according to different attributes, geocoding, long- to wide-table transformation, and data export. rtry makes use of specific features of data released from the TRY database but can be used for other datasets as well. The use of rtry does not need in-depth knowledge of R. (Lam et al. 2022, CRAN R Archive)
Climatic and soil factors explain the two-dimensional spectrum of global plant trait variation
|Plant functional traits can predict community assembly and ecosystem functioning and are thus widely used in global models of vegetation dynamics and land–climate feedbacks. Still, we lack a global understanding of how land and climate affect plant traits. A previous global analysis of six traits observed two main axes of variation: (1) size variation at the organ and plant level and (2) leaf economics balancing leaf persistence against plant growth potential. The orthogonality of these two axes suggests they are differently influenced by environmental drivers. The authors find that these axes persist in a global dataset of 17 traits across more than 20,000 species. The authors find a dominant joint effect of climate and soil on trait variation. Additional independent climate effects are also observed across most traits, whereas independent soil effects are almost exclusively observed for economics traits. Variation in size traits correlates well with a latitudinal gradient related to water or energy limitation. In contrast, variation in economics traits is better explained by interactions of climate with soil fertility. These findings have the potential to improve our understanding of biodiversity patterns and our predictions of climate change impacts on biogeochemical cycles. (Joswig et al. 2021, Nature Ecology and Evolution)
A reporting format for leaf-level gas exchange data and metadata
|Leaf-level gas exchange data support the mechanistic understanding of plant fluxes of carbon and water. The high value of these data is exemplified by the many publications that reuse and synthesise gas exchange data. However, the lack of metadata and data reporting conventions makes full and efficient use of these data difficult. The authors propose a reporting format for leaf-level gas exchange data and metadata to guide data contributors on storing data in repositories to maximize their discoverability, facilitate their efficient reuse, and add value to individual datasets (Ely et al. 2021 Ecological Informatics).
Global maps of leaf traits using remote sensing, climatological data, the TRY database, and machine learning
|Moreno-Martínez et al. have published global high-resolution maps of leaf traits. In particular, they present global maps of specific leaf area (SLA), leaf dry matter content (LDMC), leaf nitrogen and phosphorus content per area. The methodology combines MODIS and Landsat data, climatological data, the TRY database and machine learning algorithms. It is an updated version of Moreno-Martínez et al. 2018 (A methodology to derive global maps of leaf traits using remote sensing and climate data. Remote Sensing of Environment. https://doi.org/10.1016/j.rse.2018.09.006), which prevents extrapolation and uses an updated categorical trait table. The data are available at two spatial resolutions: 3km and 1km. They can be downloaded from the TRY File Archive: https://www.try-db.org/TryWeb/Data.php#59 and https://www.try-db.org/TryWeb/Data.php#60.
TRY - A plant trait database of databases
|Plant traits, such as height or specific leaf area, are expressions of plant performance and are important indicators of ecosystem function. Here, the TRY plant database is highlighted as the most comprehensive archive of global plant data, with open access to the public (Fraser 2019 Global Change Biology)
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. (Kattge et al. 2019 GCB)
Global trait–environment relationships of plant communities
|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, the authors 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 the authors find a strong filtering of 17 functional traits, similar climate conditions support communities differing greatly in mean trait values. The 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 of large grid cells. Instead, trait combinations seem to be predominantly filtered by local-scale factors such as disturbance, soil conditions, niche partitioning and biotic interactions. (Bruelheide et al. 2018 Nature Ecology and Evolution)
A methodology to derive global maps of leaf traits using remote sensing and climate data
|This paper introduces a modular processing chain to derive global high-resolution maps of leaf traits. The paper presents global maps at 500 m resolution of specific leaf area, leaf dry matter content, leaf nitrogen and phosphorus content per dry mass, and leaf nitrogen/phosphorus ratio. The processing chain exploits machine learning techniques along with optical remote sensing data (MODIS/Landsat) and climate data for gap filling and up-scaling of in-situ measured leaf traits. (Moreno-Martinez et al. 2018 Remote Sensing of Environment)
Plant functional trait change across a warming tundra biome
|Until now, the Arctic tundra has been the domain of low-growing grasses and dwarf shrubs. Defying the harsh conditions, these plants huddle close to the ground and often grow only a few centimeters high. But new, taller plant species have been slowly taking over this chilly neighborhood, report an international group of nearly 130 biologists led by scientists from the German Senckenberg Biodiversity and Climate Research Centre and the German Centre for Integrative Biodiversity Research (iDiv) today in Nature. This has led to an overall increase in the height of tundra plant communities over the past three decades. (Bjorkman et al. 2018 Nature)
Late Quaternary climate legacies in contemporary plant functional composition
|Climate may determine functional composition if there is variation in the rates of immigration and exclusion linked to functional traits. The authors show strong Pleistocene legacies on the contemporary functional composition in the New World plant assemblages consistent with slow community assembly processes. (Blonder et al. 2018 Global Change Biology)
Symbiont switching and alternative resource acquisition strategies drive mutualism breakdown
|Cooperative interactions among species—mutualisms—are major sources of evolutionary innovation. However, despite their importance, two species that formerly cooperated sometimes cease their partnership. Why do mutualisms break down? We asked this question in the partnership between arbuscular mycorrhizal (AM) fungi and their plant hosts, one of the most ancient mutualisms. We analyze two potential trajectories toward evolutionary breakdown of their cooperation, symbiont switching and mutualism abandonment. We find evidence that plants stop interacting with AM fungi when they switch to other microbial mutualists or when they evolve alternative strategies to extract nutrients from the environment. Our results show vital cooperative interactions can be lost, but only if successful alternatives evolve. (Werner et al. 2018 PNAS)
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|Gerhard Boenisch, Jens Kattge, created 2012-01-11, modified 2019-12-12