Plant Functional Traits Research Articles

Plant trait networks reveal adaptation strategies in the drylands of China

BackgroundPlants accomplish multiple functions by the interrelationships between functional traits. Clarifying the complex relationships between plant traits would enable us to better understand how plants employ different strategies to adapt to the environment. Although increasing attention is being paid to plant traits, few studies focused on the adaptation to aridity through the relationship among multiple traits. We established plant trait networks (PTNs) to explore the interdependence of sixteen plant traits across drylands.ResultsOur results revealed significant differences in PTNs among different plant life-forms and different levels of aridity. Trait relationships for woody plants were weaker, but were more modularized than for herbs. Woody plants were more connected in economic traits, whereas herbs were more connected in structural traits to reduce damage caused by drought. Furthermore, the correlations between traits were tighter with higher edge density in semi-arid than in arid regions, suggesting that resource sharing and trait coordination are more advantageous under low drought conditions. Importantly, our results demonstrated that stem phosphorus concentration (SPC) was a hub trait correlated with other traits across drylands.ConclusionsThe results demonstrate that plants exhibited adaptations to the arid environment by adjusting trait modules through alternative strategies. PTNs provide a new insight into understanding the adaptation strategies of plants to drought stress based on the interdependence among plant functional traits.

Can lamina fresh mass be used to represent lamina dry mass? Evidence from Photinia serratifolia

Lamina dry mass (LDM) per unit area is an important plant functional trait. However, it is time-consuming to dry leaves in practice. Previous studies have demonstrated that lamina fresh mass (LFM) is approximately proportional to LDM for some broad-leaved plants. However, those studies largely overlooked the influence of leaf age on the proportional relationship, and leaves were sampled without distinguishing age. In the present study, we used eight leaf-age groups of Photinia serratifolia to test whether LDM is proportional to LFM. And we also compared the two linear equations (y = a + bx, and y = a + x, where x = ln LFM, y = ln LDM, a and b are constants to be estimated) to test whether the introduction of parameter b is worthwhile based on the percent error of the goodness-of-fit between the two equations. There were four of eight leaf-age groups whose 95% confidence intervals (CIs) for b included unity, and for the other four leaf-age groups the difference between the lower limit of the 95% CI and unity was smaller than 0.03, supporting the validity of the LDM vs. LFM proportional relationship. Additionally, the percent errors between the two equations for the eight leaf-age groups were all smaller than 5%, which further supports the hypothesis of a proportional relationship at the individual leaf-age group level. However, the LDM/LFM ratio exhibited a non-linear (quadratic) function of time, which indicates that the intercept, a, depends upon leaf age.

Plant trait‐environment relationships in tundra are consistent across spatial scales

Patterns and processes shaping ecosystems vary across spatiotemporal scales. As plant functional traits reflect ecosystem properties, investigating their relationships with environment provides an important tool to understand and predict ecosystem structure and functioning. This is particularly important in the tundra where a changing climate may trigger severe alterations in plant communities as both summer and winter conditions are changing. Here, we investigate the relationships between key environmental drivers including summer temperature, snow persistence, topographic position and soil pH, and species height, specific leaf area (SLA) and seed mass as plant traits. The study is carried out at three spatial extents in the arctic–alpine region of Fennoscandia, modelling the trait‐environment relationships at each scale to investigate whether the relationships are scale dependent. Our results show that summer temperature and snow persistence are the most important variables explaining community trait composition. Temperature is important especially to vegetation height, which increased towards higher temperatures, whereas seed mass and SLA are related to snow persistence. Seed mass decreased towards longer snow persistence, while SLA responded in scale‐dependent ways. Topographic position and soil pH affect community trait composition moderately. Overall, our study demonstrates that trait‐environment relationships in the tundra are largely consistent across spatial scales. Our findings highlight the ecological relevance of snow for all three functional traits regardless of scale, showing that snow information could be particularly important to better understand large‐scale trends in plant community composition and ecosystem functioning as seasonal snow cover is shrinking globally.

Should more individuals be sampled when measuring functional traits of tree species in habitat-heterogeneous karst forests?

When measuring plant functional traits across geomorphologies, 5–10 healthy individuals of a plant species are commonly sampled. However, whether more individuals should be sampled in habitat-heterogeneous karst vegetation remains unknown. In this study, two dominant tree species (Clausena dunniana and Platycarya strobilacea) in karst evergreen and broadleaved mixed forests in Southwestern China were selected. On the basis of a large quantity of individuals of the two species grown in different peak clumps and slope positions, variations of 10 morphological traits in the two species were statistically analyzed. The suggested sampling number of individuals, which could mostly represent the common trait characteristics, was further explored. All traits showed significant differences between the two species (p < 0.05). The traits of P. strobilacea displayed larger intraspecific variations than those of C. dunniana, except for twig dry matter content. The bark thickness (BT), leaf area (LA), and specific leaf area (SLA) of C. dunniana and the BT, SLA, LA, leaf tissue density, and bark tissue density of P. strobilacea presented large intraspecific variations. Most traits exhibited significant differences between peak clumps and/or among slope positions (p < 0.05). Random sampling analysis indicated that the suggested sampling numbers of individuals for the 10 traits are 6–23 in C. dunniana and 9–29 in P. strobilacea. The common accepted sample size in normal geomorphologies is not sufficiently large in most cases. Larger sample sizes are recommended for traits, such as SLA, BT, and LA, with larger intraspecific variations. Therefore, under sufficient labor, material, and time, more individuals should be sampled when measuring plant functional traits in habitat-heterogeneous karst vegetation.

Within leaf nitrogen allocation regulates the photosynthetic behavior of xerophytes in response to increased soil rock fragment content

There is limited information on how plant functional traits vary with soil rock fragment content (RFC), especially for xerophytes growing in stony soils. We examined leaf functional traits of three xerophytes (Sophora davidii; Cotinus szechuanensi; and Artemisia vestita) grown under an RFC gradient in a heavy loamy soil. Our results show that photosynthetic capacity increased linearly with RFC in S. davidii, whereas unimodal patterns were observed for the other two species. The RFC that maximized photosynthetic capacity (Asat) and photosynthetic N use efficiency (PNUE) were achieved by allocating more N to photosynthetic apparatus at the expense of cell walls. For C. szechuanensis, the increased fraction of photosynthetic N allocated to carboxylation (PC) bioenergetics (PB), and thylakoid light-harvesting components (PL) together contributed to the higher Asat and PNUE values. As for S. davidii, both PC and PB mainly contributed to higher Asat and PNUE, whereas for A. vestita only PB was the main contributor. Our results suggest that increased non-capillary porosity of high RFC soil conditions through promoting the root growth of S. davidii and C. szechuanensis ensures sufficient water and N supply for photosynthetic capacity. In shallow-rooted species A. vestita, low RFC soil maintained higher nitrate N in the topsoil, enhancing leaf photosynthetic capacity. We conclude that rock fragments promoted leaf photosynthetic capacity in the studied loamy soil system, but the promoting effect was species-specific. The results highlight the relevance of consideration of soil rock fraction in evaluation of photosynthetic behavior of xerophytes in heterogeneous rocky soils.

Improvement of transpiration estimation based on a two-leaf conductance-photosynthesis model with seasonal parameters for temperate deciduous forests.

Conductance-photosynthesis (Gs-A) models, accompanying with light use efficiency (LUE) models for calculating carbon assimilation, are widely used for estimating canopy stomatal conductance (Gs) and transpiration (Tc) under the two-leaf (TL) scheme. However, the key parameters of photosynthetic rate sensitivity (gsu and gsh) and maximum LUE (ϵmsu and ϵmsh) are typically set to temporally constant values for sunlit and shaded leaves, respectively. This may result in Tc estimation errors, as it contradicts field observations. In this study, the measured flux data from three temperate deciduous broadleaved forests (DBF) FLUXNET sites were adopted, and the key parameters of LUE and Ball-Berry models for sunlit and shaded leaves were calibrated within the entire growing season and each season, respectively. Then, the estimations of gross primary production (GPP) and Tc were compared between the two schemes of parameterization: (1) entire growing season-based fixed parameters (EGS) and (2) season-specific dynamic parameters (SEA). Our results show a cyclical variability of ϵmsu across the sites, with the highest value during the summer and the lowest during the spring. A similar pattern was found for gsu and gsh, which showed a decrease in summer and a slight increase in both spring and autumn. Furthermore, the SEA model (i.e., the dynamic parameterization) better simulated GPP, with a reduction in root mean square error (RMSE) of about 8.0 ± 1.1% and an improvement in correlation coefficient (r) of 3.7 ± 1.5%, relative to the EGS model. Meanwhile, the SEA scheme reduced Tc simulation errors in terms of RMSE by 3.7 ± 4.4%. These findings provide a greater understanding of the seasonality of plant functional traits, and help to improve simulations of seasonal carbon and water fluxes in temperate forests.

Rapid changes in functional trait expression and decomposition following high severity fire and experimental warming

Uncharacteristically severe wildfires are occurring at higher frequency, across larger spatial extents, and in new seasons in many parts of the globe. At the same time, climate change is elevating temperatures and altering precipitation patterns. High severity fires have the potential to produce shifts in ecosystem type and function in communities that are adapted to low severity fire via changes in community composition, functional trait values, and nutrient cycling processes. However, interactive effects between climate warming and fire severity on community composition, trait values, and ecosystem functioning are rarely studied and poorly understood. We assessed the impact of experimental warming via open top warming chambers across a burn severity gradient on the understory plant community of a Ponderosa pine (Pinus ponderosa) forest in northern Arizona, USA. Specifically, we examined community composition, three plant functional traits (specific leaf area (SLA), leaf dry matter content (LDMC), and plant height) and one ecosystem function (decomposition rate) in the first post-fire growing season. High burn severity produced significant shifts in community composition. The combination of experimental warming and high burn severity significantly decreased community weighted mean LDMC and plant height, and increased decomposition rate. Our study demonstrates significant and rapid responses of community composition, trait expression, and ecosystem function in response to burn severity, experimental warming, and their interaction. This suggests that ecosystems experiencing atypically severe fire under future climate and wildfire conditions may recover in fundamentally different ways than in the past, favoring a different suite of species and traits, with altered ecosystem function.

Interplay between Plant Functional Traits and Soil Carbon Sequestration under Ambient and Elevated CO2 Levels

Unique plant functional traits (morpho-physio-anatomical) may respond to novel environmental conditions to counterbalance elevated carbon dioxide (eCO2) concentrations. Utilizing CO2, plants produce photoassimilates (carbohydrates). A mechanistic understanding of partitioning and translocation of carbon/photoassimilates into different plant parts and soils under ambient and eCO2 is required. In this study, we examine and present the intrinsic relationship between plant functional traits and eCO2 and seek answers to (i) how do plant functional traits (morpho-physio-anatomical features) affect C storage and partitioning under ambient and eCO2 in different plant parts? (ii) How do plant functional traits influence C transfer to the soil and rhizosphere services? Our study suggests that morpho-physio-anatomical features are interlinked, and under eCO2, plant functional traits influence the quantity of C accumulation inside the plant biomass, its potential translocation to different plant parts, and to the soil. The availability of additional photoassimilates aids in increasing the above- and belowground growth of plants. Moreover, plants may retain a predisposition to build thick leaves due to reduced specific leaf area, thicker palisade tissue, and higher palisade/sponge tissue thickness. eCO2 and soil-available N can alter root anatomy, the release of metabolites, and root respiration, impacting potential carbon transfer to the soil.

An Integrative Review of Drivers and Responses of Grassland Phenology under Global Change

This review synthesizes studies of grassland phenology and associations with plant resource-investment tradeoffs, functional traits, environmental and genetic regulators, genome size (GS), and management practices of nitrogen (N) fertilization, grazing, and mowing. Afterwards, the following five knowledge gaps were identified: (i) there is a lack of clarity of constraints of resource acquisition and allocation strategies, which constitute the plant economics spectrum, on herbaceous species vegetative and reproductive phenology; (ii) evidence is lacking for the tuning of phenology by functional traits via coordination of niche dimensionality and nutrient complementarity in species with contrasting community dominance; (iii) the role of keystone regulatory genes, such as AIL1, FDL1, ABI3, FT, and FRIGIDA, on phenology under contrasting environmental conditions (temperature, water, photoperiod) require confirmation; (iv) there is an urgent need to quantify trait-based and resource-partitioning links between GS and phenology to improve understanding of species coexistence; and (v) effects of N fertilization, grazing and mowing on phenological stages of coexisting species and growing season length, through impacts on inter-specific functional traits, light competition, pollination-syndromes, and carbon-investment economics are unclear. Thus, this review has identified areas of research that need to improve model predictions of the direction and magnitude of plant community responses and evolutionary mechanisms under global environmental change.

Minding the gap: Range size and economic use drive functional trait data gaps in the Atlantic forest

Biodiversity shortfalls are knowledge gaps that result from uneven sampling through time and space, and human interest of species. Gaps in functional trait data may hamper a more mechanistic understanding of the relationships between biodiversity and ecosystem services, with potential negative implications for conservation and restoration practices. Here we aim to investigate the potential drivers of trait data gaps and where geographically they are in the Atlantic Forest biodiversity hotspot. We quantified trait gaps, in the literature and open access data bases, for eight key plant functional traits of 2335 trees species and evaluated if species range size and economic use of wood drive trait gaps among species. We also evaluated if urban areas, protected areas, mean economic use of wood, and mean range size drive trait gaps geographically. We found larger trait gaps for species with small range sizes and with no economic use. Geographically, we found that gaps are lower in locations harboring more species with economic use of wood, especially in Atlantic Forest eastern locations. Our results allowed us to highlight which species and areas should be prioritized when sampling for functional traits. Efforts towards filling trait gaps of species with small ranges and no economic use of wood and of eastern Atlantic Forest locations are essential to further advance conservation and restoration of the Atlantic Forest informed by theoretical advances in trait-based ecology.

Plant diversity increases above- and below-ground biomass by regulating multidimensional functional trait characteristics.

Nitrogen enrichment affects biodiversity, plant functional traits and ecosystem functions. However, the direct and indirect effects of nitrogen addition and biodiversity on the links between plant traits and ecosystem functions have been largely overlooked, even though multidimensional characteristics of plant functional traits are probably critical predictors of ecosystem functions. To investigate the mechanism underlying the links between plant trait identity, diversity, network topology and above- and below-ground biomass along a plant species richness gradient under different nitrogen addition levels, a common garden experiment was conducted in which those driving factors were manipulated. The study found that nitrogen addition increased above-ground biomass but not below-ground biomass, while species richness was positively associated with above- and below-ground biomass. Nitrogen addition had minor effects on plant trait identity and diversity, and on the connectivity and complexity of the trait networks. However, species richness increased above-ground biomass mainly by increasing leaf trait diversity and network modularity, and enhanced below-ground biomass through an increase in root nitrogen concentration and network modularity. The results demonstrate the mechanistic links between community biomass and plant trait identity, diversity and network topology, and show that the trait network architecture could be an indicator of the effects of global changes on ecosystem functions as importantly as trait identity and diversity.

The Shift in Key Functional Traits Caused by Precipitation under Nitrogen and Phosphorus Deposition Drives Biomass Change in Leymus chinensis.

The trade-offs between key functional traits in plants have a decisive impact on biomass production. However, how precipitation and nutrient deposition affect the trade-offs in traits and, ultimately, productivity is still unclear. In the present study, a mesocosm experiment was conducted to explore the relationships between biomass production and the aboveground and belowground key functional traits and their trade-offs under changes in precipitation and nutrient depositions in Leymus chinensis, a monodominant perennial rhizome grass widespread in the eastern Eurasian steppe. Our results showed that moisture is the key factor regulating the effect of nitrogen (N) and phosphorus (P) deposition on increased biomass production. Under conditions of average precipitation, water use efficiency (WUE) was the key trait determining the biomass of L. chinensis. There were obvious trade-offs between WUE and leaf area, specific leaf area, leaf thickness, and leaf dry matter. Conversely, under increasing precipitation, the effect of restricted soil water on leaf traits was relieved; the key limiting trait changed from WUE to plant height. These findings indicate that the shift of fundamental traits of photosynthetic carbon gain induced by precipitation under N and P deposition is the key ecological driving mechanism for the biomass production of typical dominant species in semi-arid grassland.

The influence of climate warming on flowering phenology in relation to historical annual and seasonal temperatures and plant functional traits.

Climate warming has the potential to influence plant flowering phenology which in turn can have broader ecological consequences. Herbarium collections offer a source of historical plant data that makes possible the ability to document and better understand how warming climate can influence long-term shifts in flowering phenology. We examined the influence of annual, winter, and spring temperatures on the flowering phenology of herbarium specimens for 36 species collected from 1884-2015. We then compared the response to warming between native and non-native, woody and herbaceous, dry and fleshy fruit, and spring vs summer blooming species. Across all species, plants flowered 2.26 days earlier per 1°C increase in annual average temperatures and 2.93 days earlier per 1°C increase in spring onset average temperatures. Winter temperatures did not significantly influence flowering phenology. The relationship of temperature and flowering phenology was not significantly different between native and non-native species. Woody species flowered earlier than herbaceous species only in response to increasing annual temperatures. There was no difference in the phenological response between species with dry fruits and those fleshy fruits for any of the temperature periods. Spring blooming species exhibited a significantly greater phenological response to warming yearly average temperatures than summer blooming species. Although herbarium specimens can reveal climate change impacts on phenology, it is also evident that the phenological responses to warming vary greatly among species due to differences in functional traits such as those considered here, as well as other factors.

From spectra to plant functional traits: Transferable multi-trait models from heterogeneous and sparse data

Large-scale information on several vegetation properties (‘plant traits’) is critical to assess ecosystem functioning, functional diversity and their role in the Earth system. Hyperspectral remote sensing of plant canopies offers a key tool to map multiple plant traits. However, we are still lacking generalized methods to translate hyperspectral reflectance into a suite of relevant plant traits across biomes, land cover and sensor types. The absence of globally representative data sets and the gap between the available reflectance data with corresponding in-situ measurements have hampered such approaches. In recent years, the scientific community acquired multiple data sets encompassing canopy hyperspectral reflectance and plant traits from different plant types and sensors. To combine these heterogeneous data sets, we propose three multi-trait modeling approaches based on Convolutional Neural Networks (CNNs) to simultaneously infer a broad set of 20 structural and chemical traits (e.g. leaf mass per area, leaf area index, pigments, nitrogen). The performance of these multi-trait CNN models predicting these traits was compared against single-trait CNN as well as single-trait partial least squares regression (PLSR). We found that the multi-trait CNNs performances significantly increased from single-trait CNNs (nRMSE = 0.027–19.61%) and the state-of-the-art PLSR models (nRMSE = 1.94–40.07%) across a broad range of vegetation types (crops, forest, tundra, grassland, shrubland) and sensor types. Thus, providing a single model for multiple traits not only proved to be computationally more efficient, but also more accurate, since it enabled the model to incorporate traits' co-variation. Despite the data heterogeneity of the merged data set, our models performances' were comparable or exceeded those of previous studies. Overall, this study highlights the potential of weakly supervised approaches to overcome the scarcity of in-situ measurements and take a step forward in creating efficient predictive models of multiple biochemical and biophysical vegetation properties.

Plant Traits Guide Species Selection in Vegetation Restoration for Soil and Water Conservation.

Great efforts have been made to improve the soil and water conservation capacity by restoring plant communities in different climatic and land-use types. However, how to select suitable species from local species pools that not only adapt to different site environments, but also achieve certain soil and water conservation capacities is a great challenge in vegetation restoration for practitioners and scientists. So far, little attention has been paid to plant functional response and effect traits related to environment resource and ecosystem functions. In this study, together with soil properties and ecohydrological functions, we measured the seven plant functional traits for the most common species in different restoration communities in a subtropical mountain ecosystem. Multivariate optimization analyses were performed to identify the functional effect types and functional response types based on specific plant traits. We found that the community-weighted means of traits differed significantly among the four community types, and the plant functional traits were strongly linked with soil physicochemical properties and ecohydrological functions. Based on three optimal effect traits (specific leaf area, leaf size, and specific root length) and two response traits (specific leaf area and leaf nitrogen concentration), seven functional effect types in relation to the soil and water conservation capacity (interception of canopy and stemflow, maximum water-holding capacity of litter, maximum water-holding capacity of soil, soil surface runoff, and soil erosion) and two plant functional response types to soil physicochemical properties were identified. The redundancy analysis showed that the sum of all canonical eigenvalues only accounted for 21.6% of the variation in functional response types, which suggests that community effects on soil and water conservation cannot explain the overall structure of community responses related to soil resources. The eight overlapping species between the plant functional response types and functional effect types were ultimately selected as the key species for vegetation restoration. Based on the above results, we offer an ecological basis for choosing the appropriate species based on functional traits, which may be very helpful for practitioners involved in ecological restoration and management.

Response of soil properties to C, N, and P stoichiometry of plants in Qilian Mountains, China

Subsequent findings reveal the combination characteristics and spatial patterns of plant functional traits, and their response and adaptation to environmental changes in the Qinghai-Tibet Plateau. We analyzed the variation in characteristics and the influence of environmental factors on leaf functional traits from 78 quadrats in July 2021, using: one-way ANOVA, Tukey’s Honest Significant Difference (HSD) post hoc test, Pearson correlation coefficient (r) analysis, and redundancy analysis (RDA) in the Qilian Mountains. Only the leaf carbon content (LCC) of arbors was a weak variation indicator in leaf function traits of different plant types, whereas other leaf function traits including: the LCC of herbaceous plants (herbs) and shrub plants (shrubs), and the leaf nitrogen content (LNC) and carbon to nitrogen (C/N) ratio of arbors were medium variation indicators. The LNC, leaf phosphorus content (LPC), C/N ratio(C/N), C/P ratio(C/P), and N/P ratio (N/P)of herbs and shrubs, and the LPC, C/P, and N/P of arboreal plants (arbors) were strong variation indicators. Altitude was also one of the main factors affecting functional traits of plants in cold regions. Electrical conductivity (EC) and soil phosphorus content (SPC) were the main factors affecting changes in the leaf functional traits of herbs. Soil bulk density (SBD) and Soil salinity (SAL) were the main factors affecting changes in the leaf functional traits of shrubs. Soil nitrogen content (SNC) and soil temperature (ST) were the main factors affecting changes in the leaf functional traits of arbors.

Why do plants respond differently to hydropeaking disturbance? A functional approach

Hydropeaking, which refers to large and rapid flow fluctuations caused by the turning on or off of hydro-turbines to generate electricity, is a topic of growing interest due to its impact on fluvial ecosystems. To date, most hydropeaking studies have focused on the impact of this hydropower operation mode on invertebrate and fish communities, but little attention has been paid to its impact on riverine communities and how functional traits may make plants resistant to hydropeaking. We determined how a set of 32 plant functional traits are expressed in 14 riverine species, and how such expression affects their capacity to cope with common sources of hydropeaking disturbance (i.e., inundation, water stress, and rapid water fluctuations linked to up-ramping and down-ramping hydropeaking operations). We categorized species as “resistant”, “partially-resistant” or “vulnerable” based on the capacity of each trait to confer resistance to hydropeaking disturbances. Two indexes (i.e., “hydropeaking plant species resistance index” (HPPR) and “hydropeaking plant community resistance” index (HPCR)) were developed to rank our species based on their tolerance to hydropeaking and to determine which were the commonest “hydropeaking-resistant” traits within the plant community. Our results evidenced that coincidences in trait expression are common between species with similar growth forms. Grasses were the most resistant to inundation and water fluctuations, whereas trees and shrubs were so to water stress. In general, forbs were rather vulnerable to all the hydropeaking disturbances. The differences observed between the resistance expected and the obtained for several plant species illustrate the importance of our approach to fine-tune the diagnostics on plant species vulnerability to hydropeaking.. We believe this initiative will help river managers to detect suitable species to restore rivers affected by hydropower production.

Climatic conditions affect shoot flammability by influencing flammability-related functional traits in non-fire-prone habitats.

Plant flammability is an important driver of wildfires, and flammability itself is determined by several plant functional traits. While many plant traits are influenced by climatic conditions, the interaction between climatic conditions and plant flammability has rarely been investigated. Here, we explored the relationships among climatic conditions, shoot-level flammability components, and flammability-related functional traits for 186 plant species from fire-prone and non-fire-prone habitats. For species originating from non-fire-prone habitats, those from warmer areas tended to have lower shoot moisture content and larger leaves, and had higher shoot flammability with higher ignitibility, combustibility, and sustainability. Plants in wetter areas tended to have lower shoot flammability with lower combustibility and sustainability due to higher shoot moisture contents. In fire-prone habitats, shoot flammability was not significantly related to any climatic factor. Our study suggests that for species originating in non-fire-prone habitats, climatic conditions have influenced plant flammability by shifting flammability-related functional traits, including leaf size and shoot moisture content. Climate does not predict shoot flammability in species from fire-prone habitats; here, fire regimes may have an important role in shaping plant flammability. Understanding these nuances in the determinants of plant flammability is important in an increasingly fire-prone world.

Soil characteristics and plant functional traits under long-term conservation in arid desert ecosystems

Soil characteristics and plant functional traits under long-term conservation in arid desert ecosystems

Plant Traits Variably Respond to Plant–Soil Interactions during Secondary Succession on the Loess Plateau

Knowledge of plant photosynthesis, biomass, and stress resistance could contribute to exploring the growth and restoration of vegetation. However, the response of these plant traits to plant–soil interactions at different successional stages remains poorly understood, which limits the understanding of secondary succession. A greenhouse experiment was designed to test the effects of rhizosphere soils collected from early- (EarlySoil), mid- (MidSoil), and late-successional (LateSoil) plant communities on plant traits of early-, mid-, and late-successional species (EarlySp, MidSp, and LateSp, respectively). We found that plant traits reacted in a specific direction to plant–soil interactions at different successional stages. Specifically, compared with treatments of plants growing in their own soil, the net photosynthetic rate and single-photon avalanche diode significantly increased in LateSp–EarlySoil (treatment of plants growing in soil) (20%–31%) and LateSp–MidSoil (10%–18%); the maximum quantum efficiency of photosystem II increased in MidSp–EarlySoil (1%) and LateSp–MidSoil (4%); belowground soluble sugar concentrations decreased in LateSp–EarlySoil (33%) and LateSp–MidSoil (45%); leaf, stem, and root biomass increased in MidSp–EarlySoil (76%–123%), LateSp–EarlySoil (180%–342%), and LateSp–MidSoil (83%–137%), and in turn they decreased in EarlySp–MidSoil (40%–73%) and EarlySp–LateSoil (53%–67%). The results indicated that soil conditioned by pre-successional species (early- or mid-successional species) would be conducive to plant functional traits of subsequent successional species (mid- or late-successional species). Constrained redundancy analysis and path analysis suggested that water-soluble ammonium N, total N, and available N concentrations were key soil factors affecting early-, mid-, and late-successional species, respectively. Our findings confirm the directionality of succession and provide new information for plant population dynamics during secondary succession.