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Leading trait dimensions in flood-tolerant plants

Citation

Pan, Yingji et al. (2022), Leading trait dimensions in flood-tolerant plants, Dryad, Dataset, https://doi.org/10.5061/dryad.51c59zw9v

Abstract

Background and Aims

While trait-based approaches have provided critical insights into general plant functioning, we lack a comprehensive quantitative view on plant strategies in flooded conditions. Plants adapted to flooded conditions have specific traits (e.g. root porosity, low root/shoot ratio and shoot elongation) to cope with the environmental stressors including anoxic sediments, and the subsequent presence of phytotoxic compounds. In flooded habitats, plants also respond to potential nutrient and light limitations, e.g. through the expression of leaf economics traits and size-related traits, respectively. However, we do not know whether and how these trait dimensions are connected.

Methods

Based on a trait dataset compiled on 131 plant species from 141 studies in flooded habitats, we quantitatively analysed how flooding-induced traits are positioned in relation to the other two dominant trait dimensions: leaf economics traits and size-related traits. We evaluated how these key trait components are expressed along wetness gradients, across habitat types and among plant life forms.

Key Results

We found that flooding-induced traits constitute a trait dimension independent from leaf economics traits and size-related traits, indicating that there is no generic trade-off associated with flooding adaptations. Moreover, individual flooding-induced traits themselves are to a large extent decoupled from each other. These results suggest that adaptation to stressful environments, such as flooding, can be stressor specific without generic adverse effects on plant functioning (e.g. causing trade-offs on leaf economics traits).

Conclusions

The trait expression across multiple dimensions promotes plant adaptations and coexistence across multifaceted flooded environments. The decoupled trait dimensions, as related to different environmental drivers, also explain why ecosystem functioning (including, for example, methane emissions) are species and habitat specific. Thus, our results provide a backbone for applying trait-based approaches in wetland ecology by considering flooding-induced traits as an independent trait dimension.

Methods

Data compilation

We compiled functional traits on plants recorded in flooded habitats, following the definition of the international Ramsar Convention (Ramsar Convention Secretariat 2013) and the terminology guidance on the definition of ‘flooding’ (Sasidharan et al. 2017), under both field and laboratory measurements based on a combination of expert knowledge of existing literature and systematic searches in Web of Science and Google Scholar. The literature search included, but was not limited to, the following keywords: wetland, marsh, bog, floodplain, macrophytes, aquatic plants, hydrophyte, submerged, floating-leaved, emergent, isoetid, mangrove, root porosity, root/shoot ratio, shoot elongation, leaf N, leaf P, specific leaf area (SLA), leaf dry matter per unit area (LMA), plant height. We also checked the references of several important reviews of eco-physiological traits for wetlands and flooding events in the recent 15 years (e.g. Voesenek et al., 2006; Bailey-Serres & Voesenek, 2008; Voesenek & Bailey-Serres, 2015). Moreover, we circulated enquiries around our network of wetland/aquatic plant experts for recommendations for literature that we possibly had overlooked. We used The Plant List to eliminate synonyms in species names from our database (http://www.theplantlist.org).

Root porosity was quantified mainly as either the percentage of the hollow area in the root cross-section or the ratio of hollow volume to the whole root volume. These two methods generally show agreement in air-filled root porosity (Van Noordwijk & Brouwer, 1988). Root/shoot ratio was defined as the root dry mass divided by the shoot dry mass. Shoot elongation was calculated as the percentage of the maximum shoot length increase after submergence/flooding. We are aware that there are various other flooding-induced traits (e.g., radial oxygen loss, leaf gas films) that have been emphasized in eco-physiological studies. However, they are either qualitative, or represented in our database by too few consistently measured observations to be included in our statistical analysis.

To evaluate potential drivers of trait-trait relationships, we included habitat wetness, habitat type and growth form in our analysis.

The Ellenberg moisture indicator values provide insights in the extent to which species are known to occur at different extents of wetness of the habitat (Ellenberg 1988). These indicator values are based on expert knowledge of the generic distribution of plant species along a gradient of habitat wetness, categorized into 12 levels from very dry habitats (level 1) to strictly aquatic (level 12). To make the Ellenberg moisture indicator applicable for a global analysis, we related the Ellenberg moisture indicator values to the USDA wetland plant classification to derive Ellenberg values for the flora of the USA (see details in Appendix A).

To obtain more comprehensive insights in the relationships between the traits of the species and the ecological backgrounds relevant to wetland conditions, we also recorded the habitat type for each trait observation according to a modified Ramsar classification as presented in Pan et al. (2020) and we added life form to each plant species based on the descriptions in the original literature.

For this study, we took species mean trait values to allow analysing trait-trait relationships as individual studies did not provide all traits for the same situation (the distribution map of the sampling sites across the globe is shown in Fig. 2). Our analysis covered a total of 131 species of six life form categories (grass, sedge, emergent, submerged, floating-leaved and shrub/tree), with 113 species for root porosity, 60 species for root/shoot ratio, and 32 species for shoot elongation (A list of the data sources and plant species can be found in Appendix B).

Funding

China Scholarship Council, Award: 201606140037