The leaf economics spectrum revisited: global trait patterns in wetlands

The leaf economics spectrum (LES) describes consistent correlations among a variety of leaf traits that reflect a gradient from conservative to acquisitive plant strategies. So far, whether the LES holds in wetland plants at a global scale has been unclear. Using data on 365 wetland species from 151 studies, we find that wetland plants in general show a shift within trait space along the same common slope as observed in non-wetland plants, with lower leaf mass per area, higher leaf nitrogen and phosphorus, faster photosynthetic rates, and shorter leaf life span compared to non-wetland plants. We conclude that wetland plants tend to cluster at the acquisitive end of the LES. The presented global quantifications of the LES in wetland plants enhance our understanding of wetland plant strategies in terms of resources acquisition and allocation, and provide a stepping-stone to developing trait-based approaches for wetland ecology.,We defined wetland plants as plants that mainly occur in (or are exposed to) wetland habitats as described by the Ramsar Convention 17. We summarized the 3 major groups including 42 sub-groups wetland habitat types in Ramsar Convention to be 12 categories (as estuary, intertidal wetland, mangrove swamps, rivers and lakes, brackish and saline inland wetlands, permanent non-forested wetlands, temporary non-forested wetlands, permanent forested wetlands, artificial waterbodies, marsh, bog, fen). We collected leaf economics traits for wetland plants on a global scale including those plants exposed to intermittent/permanent wetland conditions (waterlogged or flooded) from both field and experiment measurements. The wetland plant leaf economics trait dataset was compiled based on a systematic search in Web of Science and Google Scholar (last updated on the 5th June 2018). The literature search included permutations of the following keywords: wetland plants, marsh plant, bog plant, isoetid, aquatic plants, macrophytes, submerged plants, floating-leaved plants, emergent plants, mangroves, leaf economics traits, leaf economics spectrum, leaf nitrogen, leaf phosphorus, SLA, LMA, leaf life span, photosynthetic rate, underwater photosynthetic rate, dark respiration rate. Additionally, our network of wetland experts from around the world contributed recommendations for possible literature that we had overlooked. Finally, we added unpublished data of our own and of our network. We did not include data from other trait databases that are dominated by terrestrial records, including TRY, because the few records available for wetland plants in these databases do not have a sufficiently detailed habitat description that would allow the differentiation between waterlogged and submerged required for our analysis. We followed the nomination system in The Plant List (http://www.theplantlist.org) to unify all plant synonyms names from the original references to a unique and consistent accepted name. We supplemented the trait observations in our database with Ellenberg moisture indicator values. The Ellenberg moisture indicator is a classic index which generally reflects the plants’ adaptation/acclimation to habitat wetness. Plant species can be categorized into 12 levels from those occupying very dry habitats (level 1) to strictly aquatic plants (level 12) 40. For the current meta-analysis, we selected plant species with Ellenberg moisture value > 7 to represent wetland plants, as described in detail in Supplementary Methods. For these species, we selected records of the six LES traits (leaf nitrogen, leaf phosphorus, leaf dry mass per unit area, leaf life span, photosynthetic rate, and dark respiration rate). We took trait values for the same six traits for non-wetland plant traits (of 1569 species) from the GLOPNET database for comparison 3. For a consistent analysis of trait-trait trade-offs, we expressed all leaf economics traits on a mass basis. Mass-based and area-based traits can be interconverted via a division by LMA. The mean value for each trait of each species was used (using the median did not alter the interpretation of the results, data not shown). We used species-mean values to attain a sufficient number of trait-trait combinations for a given species. We assume that the trait observations used for calculating the species-mean values were representative for the environmental/growth conditions in which the species occurs. Possible uncertainty in species trait mean values (for example due to intra-specific variation) will then result in noise in trait-trait relationships. In total, 365 wetland species of 184 families from 151 studies were compiled and analyzed, comprising the largest dataset on wetland plant traits to our knowledge. A map of the sampling sites with accurate spatial location information can be found in Supplementary Figure 1. The species are from varied life forms, including grasses, sedges, seagrasses, shrubs/trees, emergent, floating-leaved, isoetid, and submerged plants. Traits of most (308) species had been measured at waterlogged conditions, with submerged measurements being available for 75 species.,The study is a meta-analysis of literature data. We designed a database in which for a given species observations on traits were compiled. For each species record, we thus noted the species, study system, environmental conditions (if available), and for each trait average, sample size, standard deviation and unit. We also documented the reference from which the record had been derived. We only compiled data for species normally occurring in wetlands, or measured at wetland conditions. We collected leaf economics traits for wetland plants on a global scale including those individuals exposed to intermittent/permanent wetland conditions (waterlogged or flooded) from both field and experiment measurements. The wetland plant leaf economics trait dataset was compiled based on a systematic search in Web of Science and Google Scholar (last updated on the 5th June 2018). The literature search included permutations of the following keywords: wetland plants, marsh plant, bog plant, isoetid, aquatic plants, macrophytes, submerged plants, floating-leaved plants, emergent plants, mangroves, leaf economics traits, leaf economics spectrum, leaf nitrogen, leaf phosphorus, SLA, LMA, leaf life span, photosynthetic rate, underwater photosynthetic rate, dark respiration rate. Additionally, our network of wetland experts from around the world contributed recommendations for possible literature that we had not retrieved. Finally, we added unpublished data of our own and of our network. In combination, we aimed to be as complete as possible without predetermined sample size. Any constraint because of the sample size obtained were accounted for in the statistical analysis. The data in the database refer to publications of which the oldest are from the 1960s and the most recent from publications from the year 2018. We did not restrict our search to specific time periods, as we considered the observed trait values to be representative of the plant species involved. Data are meant to represent global patterns, with most data coming from Europe, United states, China and Australia/New Zealand.,

叶片经济谱（leaf economics spectrum, LES）描述了多种叶片性状间的一致相关性，反映了植物从保守型到获取型策略的梯度变化。迄今为止，叶片经济谱是否在全球尺度的湿地植物中成立尚不明确。通过分析来自151项研究的365种湿地植物数据，我们发现：湿地植物总体上在性状空间内沿与非湿地植物相同的共同斜率偏移，与非湿地植物相比，其单位叶面积质量（leaf mass per area, LMA）更低、叶片氮磷含量更高、光合速率更快且叶寿命更短。我们得出结论：湿地植物倾向于聚集在叶片经济谱的获取型一端。

我们将湿地植物定义为主要生长于（或暴露于）拉姆萨尔公约（Ramsar Convention）所述湿地生境的植物[17]。我们将拉姆萨尔公约中包含42个亚类的3大类湿地生境归纳为12个类别：河口、潮间带湿地、红树林沼泽、河流与湖泊、咸淡水及盐沼内陆湿地、永久性非森林湿地、临时性非森林湿地、永久性森林湿地、人工水体、沼泽、泥炭沼泽、草甸沼泽。我们在全球尺度收集湿地植物的叶片经济性状数据，包括间歇性/永久性湿地条件（积水或水淹）下的植株，数据来源于野外和实验测量。湿地植物叶片经济性状数据集基于Web of Science和Google Scholar的系统检索构建（最后更新于2018年6月5日）。文献检索关键词包括：湿地植物、沼泽植物、泥炭沼泽植物、水韭型植物（isoetid）、水生植物、大型水生植物、沉水植物、浮叶植物、挺水植物、红树林、叶片经济性状、叶片经济谱、叶片氮、叶片磷、比叶面积（specific leaf area, SLA）、单位叶面积质量（LMA）、叶寿命、光合速率、水下光合速率、暗呼吸速率。此外，我们的全球湿地专家网络为可能遗漏的文献提供了推荐。最后，我们补充了自身及专家网络的未发表数据。我们未纳入以陆地记录为主的其他性状数据库（如TRY），因这些数据库中湿地植物的少量记录缺乏足够详细的生境描述，无法区分本研究所需的积水与沉水条件。我们遵循《植物名录》（The Plant List，http://www.theplantlist.org）的命名体系，将原始文献中的植物同义词统一为唯一且一致的接受名。我们用埃伦伯格湿度指数（Ellenberg moisture indicator）补充了数据库中的性状观测数据。该指数为经典指标，反映植物对生境湿度的适应/驯化能力，植物物种可分为12个等级（极干旱生境1级至严格水生植物12级）[40]。本荟萃分析中，我们选择埃伦伯格湿度指数>7的物种代表湿地植物，详情见补充方法。对于这些物种，我们选取6个叶片经济谱性状记录：叶片氮含量、叶片磷含量、单位叶面积干质量、叶寿命、光合速率及暗呼吸速率。我们从GLOPNET数据库获取1569种非湿地植物的相同6个性状值用于对比[3]。为一致分析性状间权衡关系，所有叶片经济性状均以质量为基础表示（质量基与面积基性状可通过除以LMA转换）。我们采用每个物种各性状的均值（中位数不改变结果解释，数据未展示），以获得特定物种足够的性状组合数量。我们假设用于计算物种均值的观测值能代表该物种所处的环境/生长条件，种内变异等导致的物种性状均值不确定性会引入性状关系噪声。最终，我们编译并分析了来自151项研究的184科365种湿地植物，构成目前已知最大的湿地植物性状数据集。采样点空间分布地图见补充图1。物种涵盖多种生活型：禾本科、莎草科、海草、灌木/乔木、挺水植物、浮叶植物、水韭型植物（isoetid）及沉水植物。308种物种的性状在积水条件下测量，75种有沉水条件下的测量数据。

本研究为文献数据的荟萃分析。我们设计数据库编译特定物种的性状观测数据，每条记录包含物种名称、研究系统、环境条件（若有）、各性状均值、样本量、标准差、单位及参考文献。我们仅编译正常生长于湿地或在湿地条件下测量的物种数据。我们在全球尺度收集湿地植物叶片经济性状数据（包括间歇性/永久性湿地条件下的植株，来源为野外和实验测量），数据集基于Web of Science和Google Scholar系统检索构建（最后更新于2018年6月5日），检索关键词同前所述。此外，全球湿地专家网络推荐了可能遗漏的文献，我们补充了自身及网络的未发表数据。我们力求数据完整且无预设样本量，因样本量限制产生的约束均在统计分析中考虑。数据库数据来自1960年代至2018年的出版物，未限制检索时间范围（观测性状值被认为具有物种代表性）。数据旨在反映全球模式，大部分来自欧洲、美国、中国及澳大利亚/新西兰。