Plant type dominates fine‐root C:N:P stoichiometry across China: A meta‐analysis

Abstract

Aim Fine roots play an important role in biogeochemical cycling in terrestrial ecosystems. However, our understanding of large scale biogeographical patterns and drivers of fine‐root C:N:P stoichiometry is extremely limited. Location China. Methods We compiled data for fine‐root carbon (C), nitrogen (N) and phosphorus (P) concentrations at 165 sites across China to explore large‐scale biogeographical patterns and drivers of fine‐root C:N:P stoichiometry. Results The geometric means of fine‐root C, N, and P concentrations were 448.81, 10.73, and 0.9 mg/g, respectively, whereas C:N, C:P, and N:P ratios were 41.84, 508.32, and 11.73, respectively. The fine‐root elemental concentrations and their ratios varied widely among plant groups and biomes, and showed clear latitudinal and longitudinal trends, as a consequence of differences in climate, soil, and plant type. However, plant type was the largest contributor to the total variance in fine‐root C, N, and P and their ratios compared to climate factors or soil features. Main conclusions The data reveal the existence of broad biogeographical patterns of fine‐root C:N:P stoichiometry in China. These results advance our knowledge about the biogeochemical cycling of fine roots.

Root trait variation of seed plants from China and the primary drivers

“…This result was also in agreement with previous studies that highlighted that the variability and seasonality of temperature and precipitation are the main determinants of root length density (Padilla et al, 2015), RD/length and root branching ratio (McCormack et al, 2020). It is worth noticing that after considering climate variability and seasonality variables, the explanatory power of the environmental component increased by approximately 20% for root chemical traits (compared to the results of Wang et al, 2020) and 25% for SRL and RTD (compared to the results of Wang et al, 2018). This may be related to the fact that these climate variables reflect seasonal fluctuations and variability in temperature and precipitation (Vazquez et al, 2017), which may alter soil nutrient mobility and availability (Morillas et al, 2013;Yang et al, 2020), and thus affect root resource acquisition strategies.…”

“…Kramer‐Walter et al (2016) revealed significant correlations between SRL and soil fertility at a regional scale, but this was not found at a local scale. Wang et al (2020) demonstrated that fine‐root N and P concentrations in all biomes in China were higher than those reported by Zhang et al (2018), who only focused on forest ecosystems in China. Together, these studies suggested that the generalisation of patterns and drivers of root trait variation among different spatial scales is still highly debatable.…”

“…# indicates that Comas and Eissenstat (2009) and NM groups in the present study, even in current global dataset, we were not able to thoroughly examine the variation in the studied root traits. Third, we used STN, STP and STK concentrations as proxies for the soil nutrient supply; however, these variables did not appear to be sufficient indicators of soil nutrient availability (Ordoñez et al, 2009;Wang et al, 2020). Extensive data on soil nutrient availability are required to provide more direct evidence for the effects of soil nutrient availability on root traits, especially on chemical traits.…”

“…For example, RNC showed a positive correlation with mean annual precipitation (MAP) and no correlation with MAT at the global scale (Yuan et al, 2011), but it had a negative correlation with MAP and MAT at a regional scale (i.e. in China) (Wang et al, 2020). It was reported that RTD is not significantly correlated with any climate or soil factors in eastern China (Wang et al, 2018), but it was found to be closely associated with MAT and soil fertility parameters in alpine coniferous forests (Ding et al, 2020).…”

“…Previous studies have demonstrated the patterns in some root trait distributions and their drivers in China (e.g. Chen et al, 2013;Gu et al, 2014;Wang et al, 2018Wang et al, , 2020Zhao et al, 2016); however, these studies focused on specific biomes (mainly forests) or only a few drivers, and climate variability and seasonality variables were not included in these studies. Therefore, there is a great knowledge gap regarding the factors regulating root trait variation in China at the national level, which may differ from global and local findings or from the findings of other regional studies.…”