Multi-dimensionality in plant root traits: progress and challenges

Abstract

Plant roots, the major agent for water and nutrient acquisition, are fundamental for plant growth, evolution and ecosystem services that human beings depend on (Bardgett et al. 2014; Weigelt et al. 2023). Nutrient acquisition can be depicted by a wealth of traits of absorptive roots, the few terminal root branch orders with primarily developed tissues (Guo et al. 2008; McCormack et al. 2015). All our discussion in this perspective paper refers to the absorptive roots. For example, a frequently used database, Global Root Traits (GRooT), includes 38 core root functional traits with over 110 000 normalized trait measurements (Guerrero-Ramírez et al. 2021); the Fine-Root Ecology Database (FRED) currently includes more than 330 root functional traits and over 150 000 trait observations (Iversen and McCormack 2021). Both the above trait databases include great variations in root traits, especially those in root morphology. Absorptive root diameter (RD), one of the key morphological traits related to root function, has a great interspecific variation over 100-fold (Zhang et al. 2024a). Identifying a few key dimensions for root trait variation is one of the overarching aims of plant root ecologists (Cusack et al. 2021; Dallstream et al. 2023). These key root trait dimensions are fundamental to our understanding of plant adaptation to heterogeneous environments, species coexistence and responses to climatic change. For example, different combinations of root traits in different dimensions represent the divergence of nutrient acquisition strategies by roots (Kramer-Walter et al. 2016; Weigelt et al. 2023; Zhang et al. 2024b). Different root strategies are usually formed under different edaphic and/or climatic conditions, i.e. different niches, which facilitates the coexistence of species with different root strategies. Currently, two independent trait dimensions have been found in root trait space: one is represented by a negative relationship between RD and specific root length (SRL, root length per unit root dry mass). Plants with thick absorptive roots (usually lower SRL) usually have high mycorrhizal colonization, and hence high dependence on mycorrhizal fungi for nutrient acquisition; in contrast, species with thin absorptive roots are less dependent on mycorrhizal fungi. Therefore, the SRL–RD dimension represents a transition of nutrient acquisition from roots to symbiotic mycorrhizal fungi, and this dimension is termed the mycorrhizal collaboration dimension. The other root trait dimension is represented by a negative relationship between root tissue density (RTD, root dry mass per unit root volume) and root nitrogen content (RN). Higher RTD (lower RN) is usually characterized by more structural compounds in roots, i.e. more conservation of nutrients in roots and lower root activity in nutrient acquisition (Schneider et al. 2021; Zhang et al. 2024b). Therefore, the RTD–RN dimension depicts a tradeoff between nutrient acquisition and conservation in roots, which is known as the conservation dimension, i.e. the traditional root economics spectrum (Reich 2014). The bi-dimensionality in root traits, consisting of the collaboration and the conservation dimension, represents a milestone achievement in root ecological studies. This bi-dimensionality has been a prevailing paradigm by which we look into the great diversity in root form and function. However, it should be noted that such bi-dimensionality mainly refers mainly to the roots rather than their associations with mycorrhizal fungi. This is because the root trait bi-dimensionality is universal across plant species regardless of the type of mycorrhizal associations (e.g. arbuscular mycorrhiza and ectomycorrhiza) and the degree of mycorrhizal colonization (Bergmann et al. 2020; Ding et al. 2020, 2023; Yan et al. 2022). Given the global recognition of the root trait bi-dimensionality, it is urgent to unveil how this bi-dimensionality comes into being. Physiologically, nutrient acquisition by roots could roughly be separated into two processes (Fig. 1). First, the roots proliferate in the soil to contact soil nutrients by root epidermis and/or root hairs, and this process is called nutrient ‘foraging’. After reaching the root surface, soil nutrients are transported to the stele through the cortex, and this process is called nutrient ‘uptake’. Generally, longer absorptive roots have larger root surface area, and hence higher capacity of nutrient foraging. Therefore, SRL can represent the quantity of the roots in nutrient foraging. As aforementioned, higher RTD (lower RN) indicates lower root activity in nutrient uptake (Chen et al. 2022; Reich et al. 2008; Zhang et al. 2024a). Then, the bi-dimensionality in root traits can be regarded as statistically and ecologically independent of the quantity of root nutrient foraging from the activity in root nutrient uptake. Traditionally, SRL is considered as the efficiency of nutrient benefit per unit investment in root biomass (Pregitzer 2002). While the quantity-activity framework for root nutrient acquisition, as mentioned above, offers an insightful perspective for our understanding of the bi-dimensionality in root traits (Han et al. 2024; He et al. 2020, 2023). For example, following the quantity-activity framework, a recent study has proposed that the worldwide bi-dimensionality in root traits arises from patterns or processes occurring at different levels (Zhang et al. 2024a). This study is conducted using a well-known formula that includes both the quantity (i.e. SRL) and activity (i.e. RTD) of the roots under a common assumption of the cylindrical shape of the roots: Conceptual diagram for root foraging, uptake and mining soil nutrients. Roots forage soil nutrients by contacting them with the root surface. Nutrients are then taken up through the ToS (tissues outside the stele, including epidermis, exodermis and cortex) to the stele in absorptive roots. A typical root cross-sectional area is presented in the middle section of this figure. Exudates are secreted from roots (the shadow in orange around the root surface) to mine organically bound soil nutrients (solid circle in magenta) into inorganic ones (nitrogen, pink solid circles; phosphorus, blue solid circles). It should be noted that for cases where there are no or very few root exudates (e.g. the legumes), and little nutrient is acquired through such a mining way. Based on the above formula, Zhang et al. (2024a) have demonstrated that the cylindrical geometry of the roots is the dominant driver in shaping the bi-dimensionality in root traits. That is, such bi-dimensionality only appears when the absorptive roots are built in cylindrical shapes with varying RDs. This is a novel idea contrasting with the conventional opinion that mycorrhizal association contributes to the root trait bi-dimensionality (Kong et al. 2017; Weemstra et al. 2016). Additionally, the root trait bi-dimensionality can be due to the tissue-level allometric assembly in root anatomical structures, i.e. as the diameter of the absorptive roots increases, the thickness of the root cortex increases more steeply than the stele radius (Kong et al. 2019), as well as the cellular independence between cell quantity and activity in absorptive roots (Zhang et al. 2024a). Recently, we have discovered for the first time that such root trait bi-dimensionality is underpinned by molecular-level carbon traits, a novel term depicting the content, composition and diversity of the carbon compounds in the roots (Wang et al. 2024). This is the first study that advances our understanding of the root trait bi-dimensionality in the molecular era. Together, these proceedings offer a promising roadmap for future studies on the bi- or even the multi-dimensionality in root trait space using methods at integrated scales from individual roots to molecular carbon compounds. Despite the fruitful achievements under the root quantity-activity framework regarding root trait multi-dimensionality, there are still quite a few challenges that should be taken into account urgently in future studies. First, we should clarify how the biomass of absorptive roots is assigned to the root trait space. Theoretically, total root length, a proxy for root foraging, can be obtained by the product of SRL and root biomass. Sparse evidence suggests that root biomass outcompetes SRL in determining root foraging capacity (Freschet et al. 2015). However, it remains unclear about how root biomass is related to SRL. For example, is the root biomass coupled with or decoupled from the root foraging dimension represented by SRL? If decoupled, it implies that root biomass is the third root trait dimension, and the root trait space is three-dimensional at least: the foraging dimension (or the collaboration dimension), the uptake dimension (or the conservation dimension) and the biomass dimension. Therefore, determining the position of root biomass in the root trait space is a fundamental question in the studies on root trait multi-dimensionality (Fig. 2). Three components of nutrient foraging by absorptive roots. Absorptive roots are represented by root branches in gray. Root foraging capacity is determined by root biomass, SRL and root hairs. For species with no root hairs, the trait values for the root hair are set as ‘0’. SRL, root length per unit root biomass. Testing the above expectations can be feasible in non-woody plants, e.g. annuals, perennials or small shrubs, as their absorptive roots can be easily determined by digging out the whole root system (Zhou et al. 2022). However, it is a great challenge to collect all the absorptive roots, especially in natural forest ecosystems where the root branches of these trees and large shrubs often extend well beyond the plant canopy (Freschet and Roumet 2017; Freschet et al. 2021). For these trees and shrubs, absorptive root biomass per soil volume (or the root mass density) can be determined by some indirect methods. For example, we can measure the root mass density regrown into root ingrowth bags for a pruned thick lateral root branch (Eissenstat et al. 2015). Alternatively, root biomass density can be calculated indirectly by molecular methods (Valverde-Barrantes et al. 2013). In brief, we can first establish the relationship between the absorptive root biomass of a tree species and the content of DNA unique to the tree species. Absorptive root biomass of the tree in forest stands can then be determined by measuring the unique DNA content and then transforming such DNA content into root biomass according to the above relationship. Another challenge lies in that root hair traits should be taken into account in assessing root forging capacity (Fig. 2). It is well known that root hairs can substantially enlarge root surface area (Duddek et al. 2023; Holdaway et al. 2011). Previous studies have observed that species with thinner absorptive roots have a higher probability to grow root hairs (Baylis 1975; unpublished data by D.K.). Notwithstanding, for absorptive roots bearing root hairs, we know little about whether root hair traits align with the root foraging dimension. For example, do thicker absorptive roots have any of the following combinations of root hair traits: (i) more and shorter, (ii) more and longer, (iii) less and shorter or (iv) less and longer root hairs (Fig. 2)? Considering that both root hair length and density (number of root hair per unit root surface area or root length) contribute to total root hair length, root hair traits should fall into root foraging dimension. However, if root hair length is negatively correlated with density, resulting in a constant total root hair length across plant species, this could lead to a decoupling of root hair with root foraging dimension. Therefore, it is necessary to account for root hair traits and test how they are integrated into the multi-dimensional root trait space. Together, we propose that SRL, root biomass and root hairs, should be examined concomitantly in assessing the capacity of root foraging (Fig. 2). Whether the three components of root foraging are broken down into one or more dimensions needs to be clarified in future studies. The third challenge is that only a few physiological traits are included in the current root trait bi-dimensionality. The conservation dimension, or the uptake dimension as aforementioned, is related to the activity of roots in nutrient uptake, and decoupled from the root forging dimension. Besides RN and RTD, there are many other physiological traits related to root activity in nutrient uptake, such as root respiration and acid phosphatase activity (Apase) in roots (Guilbeault-Mayers and Laliberte 2024; Han et al. 2022; Reich et al. 2008). However, some studies using root physiological traits showed coupling of these root uptake-related traits with root foraging dimension. For example, a recent study has reported a positive relationship between root respiration and SRL (Liang et al. 2023), and a negative correlation between root Apase and RD was observed in some other studies (Han et al. 2022; Pang et al. 2018; Ushio et al. 2015; Wen et al. 2019). In addition to direct nutrient foraging, plant roots can also mine nutrients especially the organically bound ones by secreting organic acids, extracellular enzymes (root exudates) or indirectly by the exudate-stimulated soil microbes (Fig. 1). Accordingly, root exudation is referred to here as root mining dimension (Fig. 1; also see Ding et al. 2023). We observed couples of mixed relationships between root mining and root uptake dimension. For example, root exudation was observed to be positively correlated with root respiration (Sun et al. 2021), whereas there was also no relationship between root exudate and root Apase in a study (Pang et al. 2018). The contrasting relationships between root physiological traits (root respiration and Apase) and between physiological traits and root exudation suggest that we are far from a clear understanding of the relationship between root uptake and mining dimension (Wang et al. 2022). This is due to that very few species have been examined for these root traits. Prominently, these root uptake and mining traits are sensitive to changes in edaphic and climatic factors as well as plant age. It is uncertain whether it is a universal pattern or only a case study for the coupling or decoupling of the above root physiological traits with root uptake dimension. Future studies should test how root physiological traits and root exudates fit into the multi-dimensional root trait space by examining more plant species and covering more environmental change scenarios, such as drought, nitrogen deposition and global warming. The fourth challenge is that there is still a knowledge gap in our understanding of the community-level pattern of multi-dimensionality in root traits. The current framework of bi-dimensionality in root traits mainly arises from studies at the species scale. It remains unclear whether the multi-dimensionality of root traits at the community level is similar to that at the species level. Uncovering root trait multi-dimensionality at the community level by accounting for root biomass, root hairs, root physiological traits as well as root exudation (Figs 1 and 2) is important because these root traits are the potential drivers of plant community structure and ecosystem functioning (Bardgett et al. 2014; Weemstra et al. 2023b). This shall be a fruitful research field in future studies. Apart from the aforementioned bi-dimensionality in root traits consisting of root foraging and uptake dimensions, recent studies suggest some other dimensions in root trait space (Weemstra et al. 2023a; Yaffar et al. 2022), e.g. root depth (Weigelt et al. 2021; Yang et al. 2021) and chemical defense (Comas and Eissenstat 2009). In arid conditions or desert ecosystems, the depth to which roots can penetrate the soil is very important for water acquisition by plants. Meanwhile, the investment in chemical defense is necessary for the functioning of roots in soils usually with abundant pathogens. Nevertheless, the position of root depth and chemical defense in the multi-dimensional root trait space remains uncertain. This is because root depth has been determined in a very limited number of plant species due to the great difficulty in measuring root depth, especially for trees in natural forests. We are unsure whether the root depth dimension found in a limited species pool still holds true for other plant species. This knowledge gap can be fulfilled by measuring root depth using advanced techniques such as ground penetrating radar. For the chemical defense of roots, a recent study reports that it is coupled with the root foraging dimension (Xia et al. 2021) rather than being assigned to the third dimension as suggested by an early study (Comas and Eissenstat 2009). The discrepancy between the two studies could be due to the use of different chemical defense compounds and the small number of plant species examined in the studies. Last but not least, the challenge we are facing is to explore a long-lasting root–leaf relationship in ecological studies from the perspective of multi-dimensional plant trait space (Ma et al. 2022; Yu et al. 2023). Recent studies have revealed that root uptake (or conservation) dimension is coupled with leaf economics spectrum (LES), an analogy to the aforementioned root conservation dimension (Bergmann et al. 2020; Reich 2014; Wright et al. 2004), and that both root uptake dimension and LES are independent of root foraging (or collaboration) dimension (Carmona et al. 2021; Weigelt et al. 2021, 2023). Nevertheless, these studies did not take into account root biomass and root mining dimension, nor leaf hydraulics (indicating leaf water supply and water demand via leaf veins and stomata, respectively) and leaf size, both of which are independent of LES (Cao et al. 2023; Díaz et al. 2016; Ke et al. 2022; Li et al. 2015; Sack et al. 2012) (Fig. 3). Moreover, similar to absorptive roots, the function of leaves not only depends on the area- or mass-based leaf traits (e.g. leaf economics, hydraulics, size) but also on the quantity of leaves in a plant individual, i.e. leaf biomass (Fig. 3). However, leaf biomass, the quantity-related key leaf trait, has not yet been integrated into leaf trait space, especially in tree species. To fully understand the leaf–root relationship, it is necessary to identify and include the multi-dimensions in both leaves and roots (Fig. 3). Relationships between roots and leaves from the perspective of multi-dimensional plant trait space. The multi-dimensionality in root traits includes traits in root foraging (biomass, SRL and root hairs), uptake (nutrients, respiration, acid phosphatase, etc.), mining (root exudates), root depth and root defense. For species that do not secrete acid phosphatases or have no exudates, these trait values are set as ‘0’. The multi-dimensionality in leaf traits consists of the following aspects of the leaves: leaf biomass (per individual plant), economics (SRL, nutrients, etc.), hydraulics (veins and stomata) and size (leaf area for a single leaf). This work was financially supported by the National Natural Science Foundation of China (32171746, 42077450, 31870522 and 31670550), and the leading talents of basic research in Henan Province, Research Funds for overseas returnee in Henan Province, China. We thank three anonymous referees and the editor, Prof. Zeqing Ma, for their valuable comments and suggestions for this study. Thanks are also given to Shiyang Zhou for her nice polishing of the language of this manuscript. Conflict of interest statement. The authors declare that they have no conflict of interest.

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