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Quantifying and scaling global plant trait diversity

TRY is a network of vegetation scientists headed by
Future Earth, the Max Planck Institute for Biogeochemistry, and iDiv
providing free and open access to plant trait data.

Database version 5 online (2019-03-26)
11,850,781 trait records
279,875 plant taxa


10 Billion Data Served (2020-08-11)
As of today, TRY has released more than 10,000,000,000 data from the database, 1.3 billion traits and 8.7 billion auxiliary data. (link)

New Publication (2020-07-02)
Byun, Blois and Brisson: Restoring functionally diverse communities enhances invasion resistance in a freshwater wetland. Journal of Ecology. (link)

New Publication (2020-07-02)
Bergmann et al.: The fungal collaboration gradient dominates the root economics space in plants. Science Advances. (link)

Request 10.000 (2020-05-20)
TRY has just received the 10.000th request for data from the Plant Trait Database (link)

Global maps of leaf traits (2020-04-09)
Moreno-Martínez et al. have published global high-resolution (1km, 3km) maps of the leaf traits: specific leaf area (SLA), leaf dry matter content (LDMC), leaf nitrogen and phosphorus content per area. The data 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. (link)

News Archive

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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 imprint of mycorrhizal fungi on whole-plant nutrient economics

__Most plants on Earth form a symbiosis with root-associated (i.e., mycorrhizal) fungi, trading plant photosynthate for fungal-acquired soil nutrients. Ecologists have long thought that different types of mycorrhizal fungi—arbuscular vs. ectomycorrhizal—represent adaptations to high vs. low soil nutrient availability. Here we show that these different mycorrhizal associations are linked to differences in a suite of plant traits related to nutrient economic strategies. Ectomycorrhizal plant species are more nutrient use-conservative than arbuscular mycorrhizal plant species, an effect that is robust to controlling for plant growth form and evolutionary history. These findings bolster emerging theories in ecosystem ecology that leverage the ecology of mycorrhizal fungi to better predict ecosystem carbon-nutrient cycle interactions (Averill et al. 2019 PNAS).

Inferring plant functional diversity from space: the potential of Sentinel-2

__Plant functional diversity (FD) is an important component of biodiversity that characterizes the variability of functional traits within a community, landscape, or even large spatial scales. It can influence ecosystem processes and stability. Hence, it is important to understand how and why FD varies within and between ecosystems, along resource availability gradients and climate gradients, and across vegetation successional stages. Usually, FD is assessed through labor-intensive field measurements, while assessing FD from space may provide a way to monitor global FD changes in a consistent, time and resource-efficient way. The potential of operational satellites for inferring FD, however, remains to be demonstrated. Here we studied the relationships between FD and spectral reflectance measurements taken by ESAs Sentinel-2 satellite over 117 field plots located in 6 European countries, with 46 plots having in-situ sampled leaf traits and the other 71 using traits from the TRY database. Based on spaceborne observations we could predict 55% of the variation in the observed FDis. The novelty of this study is the effective integration of space-borne and in-situ measurements at a continental scale, and hence represents a key step towards achieving rapid global biodiversity monitoring schemes. (Ma et al. 2019 Remote Sensing of Environment)

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)

Disclaimer Page calls: 523014 Gerhard Boenisch, Jens Kattge, created 2012-01-11, modified 2019-12-12