The &amp;#8216;rtry&amp;#8217; R package for preprocessing plant trait data

Lam, Olee Hoi Ying; Tautenhahn, Susanne; Walther, Gabriel; Boenisch, Gerhard; Baddam, Pramod; Kattge, Jens

doi:10.5194/egusphere-egu22-13251

Cited by 3 publications

(4 citation statements)

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“…Traits values were obtained with the ‘BIEN’ R package (Maitner et al., 2018) or extracted from the TRY database (Kattge et al., 2020). In this step, we used the ‘rtry’ package (Lam et al., 2022) for trait preprocessing, which included data exploration, selection, and export. The trait values from the TRY database exhibited a low error risk (i.e., z ‐score), ranging from −1.80 to 1.83 for leaf area and −1.20 to 1.12 for maximum height (Díaz et al., 2022).…”

Section: Methodsmentioning

confidence: 99%

Multiple aspects of tree beta diversity in coastal ecosystems in Brazil

da Silva Oliveira,

Landim,

Gouveia

2024

Journal of Biogeography

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AimPatterns of beta diversity reflect the formation dynamics of ecological communities. Here, we integrated geographic, phylogenetic, and phenotypic information of coastal woody vegetation to investigate (1) whether the observed dissimilarity between assemblages differs from that expected by chance, examining the roles of spatial and deterministic processes; (2) the relative contribution of beta‐diversity components (turnover and nestedness) for taxonomic, phylogenetic, and functional beta diversity; and (3) what environmental factors drive the differences in composition between assemblages for all these dimensions.LocationBrazil.TaxonAngiosperm trees.MethodsWe built dissimilarity matrices and partitioned the taxonomic, phylogenetic, and functional beta diversity from an incidence matrix, a phylogeny including the region's plants, and a matrix expressing functional distances. Using linear regressions, we tested the effects of different environmental predictors representative of the effects of water availability, thermal energy, habitat heterogeneity, edaphic constraints, climatic stability, and human influence on beta‐diversity patterns.ResultsTaxonomic, phylogenetic, and functional dissimilarities exhibited a typical pattern of greater dissimilarity with distance (i.e., as expected by chance). However, these patterns showed different contributions of beta‐diversity components, predominating turnover in taxonomic and phylogenetic dissimilarity, and nestedness in functional dissimilarity. Water availability had a slight effect on patterns of taxonomic and phylogenetic dissimilarities.Main conclusionsThe Brazilian coastal woody vegetation appears to have emerged through a dynamic of colonisation of evolutionarily distinct but functionally similar lineages that originated from adjacent phytogeographic domains, proportional to their diversity. This is consistent with a combination of both neutral and non‐neutral processes. Our findings underscore the complementary roles of different dimensions of beta diversity in explaining the dynamics of these vegetation communities.

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Section: Methodsmentioning

confidence: 99%

Multiple aspects of tree beta diversity in coastal ecosystems in Brazil

da Silva Oliveira,

Landim,

Gouveia

2024

Journal of Biogeography

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“…We cleaned the downloaded portion of the TRY database following suggested cleaning methodology provided by TRY for data quality assurance (Figure 1; Kattge et al, 2020;Lam et al, 2022). Hereafter, this cleaning protocol will be referred to as the "standard" cleaning.…”

Section: Standard Data Cleaning Protocolmentioning

confidence: 99%

“…For each data point, we determined whether data met the following criteria: (1) applicable , or whether the data point is original, representative, logical, and comparable, and (2) traceable , or whether the data point is published, cited, and consistent (see FAIR and ALCOA principles for similar standards; Rattan, 2018; Wilkinson et al., 2016). We used these criteria to create a rigorous data cleaning protocol and compared this to the standard cleaning protocol taken by most researchers and that is suggested by TRY (Lam et al., 2022). With this, we asked: (1) how does the quality of data available from TRY differ between rigorous and standard cleaning protocols?…”

Section: Introduction—global Ecological Databases In the Era Of Big Datamentioning

confidence: 99%

Improper data practices erode the quality of global ecological databases and impede the progress of ecological research

Augustine,

Bailey‐Marren,

Charton

et al. 2024

Global Change Biology

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The scientific community has entered an era of big data. However, with big data comes big responsibilities, and best practices for how data are contributed to databases have not kept pace with the collection, aggregation, and analysis of big data. Here, we rigorously assess the quantity of data for specific leaf area (SLA) available within the largest and most frequently used global plant trait database, the TRY Plant Trait Database, exploring how much of the data were applicable (i.e., original, representative, logical, and comparable) and traceable (i.e., published, cited, and consistent). Over three‐quarters of the SLA data in TRY either lacked applicability or traceability, leaving only 22.9% of the original data usable compared with the 64.9% typically deemed usable by standard data cleaning protocols. The remaining usable data differed markedly from the original for many species, which led to altered interpretation of ecological analyses. Though the data we consider here make up only 4.5% of SLA data within TRY, similar issues of applicability and traceability likely apply to SLA data for other species as well as other commonly measured, uploaded, and downloaded plant traits. We end with suggested steps forward for global ecological databases, including suggestions for both uploaders to and curators of databases with the hope that, through addressing the issues raised here, we can increase data quality and integrity within the ecological community.

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“…We processed the data using R statistical software (version 4.0.4), keeping the data at species-level . To manipulate the extracted functional traits, we used the package {rtry} (Lam et al, 2022) d eveloped to support the preprocessing of TRY Database ( version 1.0.0), and {tidyverse} package ( Wickham et al, 2019) with its dependencies (version 1.3.2).…”

Section: Data Collectionmentioning

confidence: 99%

Leaf habit and nutrient availability drive leaf nutrient resorption globally

Sophia,

Caldararu,

Stocker

et al. 2024

Preprint

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Abstract. Nutrient resorption from senescing leaves can significantly affect ecosystem nutrient cycling, making it an essential process to better understand long-term plant productivity under environmental change that affects the balance between nutrient availability and demand. Although it is known that nutrient resorption rates vary strongly between different species and across environmental gradients, the underlying driving factors are insufficiently quantified. Here, we present an analysis of globally distributed observations of leaf nutrient resorption to investigate the factors driving resorption efficiencies for nitrogen (NRE) and phosphorus (PRE). Our results show that leaf structure and habit, together with indicators of nutrient availability, are the two most important factors driving spatial variation in NRE. Overall, we found higher NRE in deciduous plants (65.2 % ± 12.4 % , n=400) than in evergreen plants (57.9 % ± 11.4 %, n=551) , likely associated with a higher share of metabolic N in leaves of deciduous plants. Tropical regions show the lowest resorption for N (NRE: 52.4 % ± 12.1 % ) and tundra ecosystems in polar regions show the highest (NRE: 69.6 % ± 12.8 %), while the minimum PRE is in temperate regions (57.8 % ± 13.6 %) increasing to boreal regions (67.3 % ± 13.6 %). Soil clay content, N and P atmospheric deposition – a globally available proxy for soil fertility – and MAP played an important role in this pattern, where we found higher NRE and PRE in high latitudes. The statistical relationships developed in this analysis indicate an important role of leaf habit and type for nutrient cycling and guide improved representations of plant-internal nutrient re-cycling and nutrient conservation strategies in vegetation models.

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The ‘rtry’ R package for preprocessing plant trait data

Cited by 3 publications

References 0 publications

Multiple aspects of tree beta diversity in coastal ecosystems in Brazil

Multiple aspects of tree beta diversity in coastal ecosystems in Brazil

Improper data practices erode the quality of global ecological databases and impede the progress of ecological research

Leaf habit and nutrient availability drive leaf nutrient resorption globally

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