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Expanding the plant economics spectrum with root nitrogen reallocation

Cite this dataset

Wang, Ruzhen et al. (2024). Expanding the plant economics spectrum with root nitrogen reallocation [Dataset]. Dryad.


Harnessing root nitrogen reallocation (RNR) for optimization of plant productivity commences with positioning RNR in root economics space about which we still know little. We conducted a global synthesis linking RNR to root traits, combined with a two-year 15N-labelling field experiment to position RNR in plant economics spectrum under acidification. RNR correlated negatively with specific root length (SRL) and mycorrhizal colonization globally, suggesting that RNR is a conservative trait. Sedges, grasses and forbs coordinated root traits (e.g., SRL) from acquisitive to conservative and from low to high RNR reliance (and vice versa for their direct-root N uptake) in the 15N-tracing experiment. Specifically, sedges and forbs exhibited the lowest and highest RNR that increased and decreased with acidification, respectively. Grasses cooperated well with mycorrhizas, showing moderate RNR and root traits. Our results demonstrated the significance of RNR in plant growth, and the necessity of considering RNR as a conservative trait.


Column Entry Value Unit Explanation
A Geographic coordinate Geographic coordinate of fifteen researches of RNR in global
B RNR Numerical % Nitrogen reallocation from storage organs to new-growing tissues for plant regrowth in global sites
C SRL Numerical g·m-1 Specific root length of plant in global sites
D RD Numerical mm Root diameter of plant in global sites
E Mycorrhizal colonization Numerical % Ectomycorrhizal fungi (ECM)/arbuscular mycorrhizal fungi (AMF) colonization in global sites
G pH Numerical Soil pH in global sites
H Treatment 1-5 Sulfur addition rates of 0, 5, 10, 20, and 50 g S m-2 yr-1 respectively
I Block 1-5 Physical block in the sulfur addition experimental platform; this was also the replicate number in the treament combination
J soil pH Numerical soil pH
K N reallocation (RNR) of sedges/grasses/forbs Numerical mg·m-2 Reallocation of N from roots to new-growing tissues for plant regrowth
L N uptake of sedges/grasses/forbs Numerical mg·m-2 N uptake of sedges/grasses/forbs from soils
M RD of sedges/grasses/forbs Numerical mm Root diameter of sedges/grasses/forbs
N RTD of sedges/grasses/forbs Numerical g·cm-3 Root tissue density of sedges/grasses/forbs
O SRL of sedges/grasses/forbs Numerical g·m-1 Specific root length of sedges/grasses/forbs
P SRA of sedges/grasses/forbs Numerical cm-2·g-1 Specific root surface area of sedges/grasses/forbs
Q RLD of sedges/grasses/forbs Numerical cm·cm-3 Root length density of sedges/grasses/forbs
R AMF colonization of sedges/grasses/forbs Numerical % Arbuscule mycorrhizal fungi colonization of sedges/grasses/forbs
S Sedges/grasses/forbs biomass regrowth Numerical g·m-2 Regrowth of of sedges/grasses/forbs shoot biomass after the biomass clipping


A global study for reallocation of N from roots

To position RNR in the root economics space, we compiled a global dataset on N reallocation by searching the keywords of ‘nitrogen reallocation’ OR ‘nitrogen remobilization’ OR ‘nitrogen redistribution’ OR ‘root nitrogen’ using “Web of Science”, “Scopus” and “Google Scholar”. Based on the criteria of RNR quantification, only 15 papers met the merit for inclusion. These selected studies applied either 15N isotope or N budget approaches to quantify RNR (14 versus one study). For the 15N isotope approach, soil available N pool was labelled with 15N tracers directly after defoliation, and thereafter the 15N enrichment of the soil available N pool was used to quantify N uptake from the soil and N remobilization was then estimated as the difference between the N pool in regrown shoots and soil N uptake (Yang et al., 2023). Regarding the N-budget approach, it was also implemented with the facilitation of 15N tracers, where the percentage of N uptake from soil (i.e., 100%-RNR%) in the second-year growth was equal to the annual depletion rate of 15N in plant biomass since labelling at the first year (Weinbaum & Kessel, 1998).

15N isotope labelling

In late July of 2021, a 1 × 1 m subplot was randomly implemented within each treatment plot for tracer 15N application at peak plant community biomass. Aboveground plant biomass was clipped to 10 mm above the soil surface for each subplot to ensure plant regrowth. Afterwards, the 15N tracer (99.16 atom%, as 15NH415NO3) was dissolved in 500-mL deionized water and uniformly sprayed onto each subplot with a small sprayer. Based on 15N isotopic signatures, similar to the methodology used in the studies from the above data synthesis, we estimated the contribution of direct N uptake from soil and the contribution of RNR (N stored in roots prior to clipping and reallocated to aboveground organs during their growth). An additional 500 mL of deionized water was sprayed to wash any 15N attached to plant stubbles down to the soil surface. The tracer application rate was 50 mg 15N m-2, which ensured the detection of 15N signatures without interfering with the natural N cycling processes (Templer et al., 2012). The same tracer application procedure was repeated in late July of 2022, by choosing another subplot of 1 m × 1 m at least 1-m away from the previously labelled subplot within each plot.


Plant and soil sampling

Plant samples clipped before the tracer application were separated into species and dried at 65 °C for 48 h to constant weight. Three weeks after tracer application and plant regrowth, aboveground plant biomass was clipped again to determine the biomass regrowth of each species in the same way (see details in Zhang et al., 2022). We combined and homogenized the species belonging to the same functional group and then ground them into powder for chemical analyses. The 15N signature was measured on aboveground tissues for each functional group separately.

Unlabelled soils were also collected for background 15N measurement in the subplots prior to the tracer application. Briefly, topsoil samples (0-10 cm) were collected by randomly selecting three cores and then mixed thoroughly in each subplot. Twenty-one days after labelling, topsoil was sampled again in the same way. Both unlabelled and labelled soil samples were sieved through a 2-mm mesh size to remove the stones and plant residues. Plant and soil samples were collected and processed in the same way for 2021 and 2022.

Given that sorting roots to species or functional group level would be extremely challenging, we chose to quantify root traits only for the most dominant plant species from each functional group. Leymus chinensis (Trin.) Tzvel (L.c), Carex duriuscula C.A.Mey (C.d) and Pulsatilla turczaninovii Kryl. et Serg (P.t) were the dominant species for grasses, sedges and forbs, respectively, accouting for the largest percentages of overall biomass at the community level (68%, 11%, and 6%, respectively; Supplementary Fig. 2a) and in their corresponding functional groups (97%, 100%, and 31%, respectively; Supplementary Fig. 2b-d). Specifically, plant roots were collected by a spade to a depth of 10 cm from a soil block (20 cm long × 15 cm width) around the selected individual plant species and soils adhered to the roots were carefully removed. Root samples were rinsed with distilled water and then frozen at -20 °C for later analysis of morphological traits and AMF colonization.


National Natural Science Foundation of China, Award: 32222056

National Natural Science Foundation of China, Award: 32271677

National Natural Science Foundation of China, Award: 32071563