One of ecology's grand challenges is developing general rules to explain and predict highly complex systems. Understanding and predicting ecological processes from species' traits has been considered a ‘Holy Grail’ in ecology. Plant functional traits are increasingly being used to develop mechanistic models that can predict how ecological communities will respond to abiotic and biotic perturbations and how species will affect ecosystem function and services in a rapidly changing world; however, significant challenges remain. In this review, we highlight recent work and outstanding questions in three areas: - (i) selecting relevant traits; - (ii) describing intraspecific trait variation and incorporating this variation into models, and; - (iii) scaling trait data to community- and ecosystem-level processes. 

Over the past decade, there have been significant advances in the characterization of plant strategies based on traits and trait relationships, and the integration of traits into multivariate indices and models of community and ecosystem function. However, the utility of trait-based approaches in ecology will benefit from efforts that demonstrate how these traits and indices influence organismal, community, and ecosystem processes across vegetation types, which may be achieved through meta-analysis and enhancement of trait databases. Additionally, intraspecific trait variation and species interactions need to be incorporated into predictive models using tools such as Bayesian hierarchical modelling. Finally, existing models linking traits to community and ecosystem processes need to be empirically tested for their applicability to be realized.

Revisiting the Holy Grail: Using plant functional traits to understand ecological processes

Adaptation of bamboo to heterogeneous habitat: phenotypic plasticity

Rapeseed cake is an important agricultural waste. After enzymatic fermentation, rapeseed cake not only has specific microbial diversity but also contains a lot of fatty acids, organic acids, amino acids and their derivatives, which has potential value as a high-quality organic fertilizer. However, the effects of fermented rapeseed cake on tea rhizosphere microorganisms and soil metabolites have not been reported. In this study, we aimed to elucidate the effect of enzymatic rapeseed cake fertilizer on the soil of tea tree, and to reveal the correlation between rhizosphere soil microorganisms and nutrients/metabolites.The results showed that: (1) The application of enzymatic rapeseed cake increased the contents of soil organic matter (OM), total nitrogen (TN), total phosphorus (TP), available nitrogen (AN), and available phosphorus (AP); increased the activities of soil urease (S-UE), soil catalase (S-CAT), soil acid phosphatase (S-ACP) and soil sucrase (S-SC); (2) The application of enzymatic rapeseed cake increased the relative abundance of beneficial rhizosphere microorganisms such as Chaetomium, Inocybe, Pseudoxanthomonas, Pseudomonas, Sphingomonas, and Stenotrophomonas; (3) The application of enzymatic rapeseed cake increased the contents of sugar, organic acid, and fatty acid in soil, and the key metabolic pathways were concentrated in sugar and fatty acid metabolisms; (4) The application of enzymatic rapeseed cake promoted the metabolism of sugar, organic acid, and fatty acid in soil by key rhizosphere microorganisms; enzymes and microorganisms jointly regulated the metabolic pathways of sugar and fatty acids in soil.Enzymatic rapeseed cake fertilizer improved the nutrient status and microbial structure of tea rhizosphere soil, which was beneficial for enhancing soil productivity in tea plantations. These findings provide new insights into the use of enzymatic rapeseed cake as an efficient organic fertilizer and expand its potential for application in tea plantations. 

Enzymatic fermentation of rapeseed cake significantly improved the soil environment of tea rhizosphere

Abstract Land degradation is one of the most pressing environmental problems of the 21st century particularly due to its impact on global food security and environmental quality through the loss of biodiversity and ecosystem services. Land degradation happens at an accelerated rate and affects regions inhabited by more than one‐third population of the world. This phenomenon resulted in a dramatic reduction in the productivity of cropland and rangeland of world thus threatening the environmental quality and food security. It manifests in various forms such as desertification, soil erosion, sodicity, salinity, heavy metal contamination, pesticide contamination, declining soil fertility, and fate of polycyclic aromatic hydrocarbons. The world now has a real chance for the next generation to grow sustainably and eliminate acute food scarcity. Microbes, as vital elements of soil, play an important role in maintaining soil biological properties and fertility. Due to their multifarious biological functions and metabolic uniqueness, microorganisms can fix or solubilize nutrients, add organic matters to the soil to improve its quality. Many of the microorganisms can produce biological compounds or enzymes, which can degrade or scavenge toxic substances from the soils. In this review, we have discussed in detail how diverse microorganisms can help to restore different types of degraded lands. The limitations in application of microorganisms in restoration of soil health and possible scopes to improve the applicability have also been discussed here. 

Soil health restoration in degraded lands: A microbiological perspective

Moso bamboo invasion potentially alters litter, soil properties and soil microbial communities in forest ecosystems. However, the overall direction and magnitude of this alteration at a large spatial scale remain unclear. Here, we conducted a meta-analysis of 72 experimental studies on the impact of moso bamboo invasion on litter, soil physicochemical properties, and soil microbial communities. Overall, the moso bamboo invasion increased litter decomposition, soil pH, and NH4+-N, while concurrently leading to a decrease in soil bulk density, soil electrical conductivity, soil TN: TP ratio, soil NO3--N, and available potassium. Moreover, we observed that the invasion significantly enhanced soil microbial biomass nitrogen, fungal ACE diversity index, fungal biomass, and bacterial Shannon diversity index, while decreasing the ratio of Gram-positive to Gram-negative bacteria and the biomass of Gram-positive bacteria. Furthermore, we identified the primary factors influencing specific soil properties and microbial community responses to moso bamboo invasion. Specifically, the response of NH4+-N, NO3--N, soil bulk density, fungal diversity and pH were found to be primarily influenced by climatic factors (mean annual temperature, mean annual precipitation), topographic factors (aspect), and invasion stage, respectively. In addition, we further revealed a close relationship between soil physicochemical properties and microbial communities during moso bamboo invasion. Specifically, the response of soil microbial biomass nitrogen was positively correlated with the responses of soil organic nitrogen and total nitrogen content, Gram-positive bacteria biomass was positively correlated with soil total nitrogen but negatively correlated with soil pH. Meanwhile, soil bacterial diversity showed a significant positive correlation with soil pH but exhibited a negative correlation with soil SOC. Our study suggests that macro-climatic conditions, local microenvironment, and invasion stage co-regulate the important effects of moso bamboo invasion on litter, soil physicochemical properties, and microbial communities. 

Unveiling the impacts moso bamboo invasion on litter and soil properties: A meta-analysis.

Functional characteristics reflect plant strategies and adaptability to the changing environment. Determining the dynamics of these characteristics after harvesting would improve the understanding of forest response strategies. Strip clearcutting (SC) of moso bamboo forests, which significantly reduces the cutting cost, has been proposed to replace manual selective harvesting. A comparison of restoration features shows that 8 m is the optimal cutting width. However, the precise response of functional features to the resulting harvest-created gap remains unclear. In this study, three SC plots were selected which was performed in February 2019, with three unharvested plots as a control (C). The study focused on 10 functional traits, including leaf area (LA), specific leaf area (SLA), leaf dry matter content (LDMC), leaf nitrogen content (LNC), leaf phosphorus content (LPC), nitrogen/phosphorus ratio (N:P), wood density (WD), fine root biomass (FRB), specific fine root length (SRL), and root length density (RLD). A one-way ANOVA was used to compare differences in functional traits and soil nutrients between treatments. Strip clearcutting significantly reduced the soil organic carbon (SOC) and total nitrogen (TN) contents (p 0.05). This study highlighted that root trait, soil content of total phosphorus (TP) and total potassium (TK) returned to the level of uncut plots after a year’s recovery. The LPC, LNC, and N:P were negatively correlated with LA, and LDMC and WD were negatively correlated with SLA, while the effect of SC on fine root traits was limited (p > 0.05). Fine root traits (FRB, RLD, and SRL) were positively associated with SOC, TN, and TP, but negatively correlated with TK. The changes in soil nutrient content caused by the removal of biomass were normal. Increased light and the rapid growth of new trees will increase nutrient regressions; therefore, these results further confirm the feasibility of SC.

https://www.mdpi.com/1999-4907/12/6/793/pdf

Functional Trait Responses to Strip Clearcutting in a Moso Bamboo Forest

Height to crown base (HCB) is an important variable used as a predictor of forest growth and yield. This study developed a nonlinear, mixed-effects HCB model through inclusion of plot-level random effects using data from 29 sample plots distributed across a state-owned Yixing forest farm in Jiangsu province, eastern China. Among several predictor variables evaluated in the analyses, bamboo height, canopy density, and total basal area of bamboo with a diameter larger than that of the subject bamboo individual contributed significantly to the HCB variations. The inclusion of random effects improved the prediction accuracy of the model significantly, indicating that the HCB variations within and across the sample plots were substantial. The model was localized using four sampling strategies, and the study identified that using two medium-sized bamboos by diameter at breast height per sample plot resulted in the smallest prediction error. This strategy, which would balance both measurement cost and potential error, may be applied to estimate the random effects and localization of the nonlinear mixed-effects HCB model for moso bamboo in eastern China.

/pdf/nonlinear-mixed-effects-height-to-crown-base-model-for-moso-24b94rx2.pdf

Nonlinear Mixed-Effects Height to Crown Base Model for Moso Bamboo (Phyllostachys heterocycla (Carr.) Mitford cv. Pubescens) in Eastern China

Understanding fine root characteristics in relation to soil properties of bamboo–broadleaf mixed forests may help optimize belowground production management and ecological functions in mixed-forest ecosystems. In this study, we compared four different bamboo–broadleaf mixed forests: Castanopsis chinensis (Sprengel) Hance with moso bamboo (CCB), Alniphyllum fortunei (Hemsl.) Makino with moso bamboo (AFB), Choerospondias axillaris (Roxb.) Burtt and Hill with moso bamboo (CAB), and Castanopsis fargesii Franch with moso bamboo (CFB), and analyzed their effects on the traits of fine roots of moso bamboo, soil nutrient contents, and enzyme activities. In January 2022, fine root and soil samples from four different mixed bamboo–broadleaf forests were collected from a subtropical region of Fujian Province, China. Results showed that CAB significantly increased fine root biomass (FRB) and root length density (RLD); however, specific root length (SRL) was only in the 0–20 cm soil layer. Specific surface area (SSA) was significantly reduced in the CCB in the 0–20 cm and 20–40 cm soil layers. The total phosphorous (TP) and total potassium (TK) contents of AFB and CAB were significantly increased (p < 0.05), and the alkali-hydrolyzable nitrogen (AN) content was significantly increased by CCB in the 0–20 cm soil layer (p < 0.05). Additionally, CFB increased the activities of acid phosphatase (ACP) and catalase (CAT) but decreased the activity of sucrase (SC). Principal component analysis showed that fine root traits (FRB, RLD, SRL, and SSA) were not only positively associated with soil organic carbon (SOC), total nitrogen (TN) and available potassium (AK) but also associated with urease (UE) and CAT. Therefore, belowground interactions between different species have a significant impact on the characteristics of fine roots and soil in bamboo–broadleaf mixed forests.

/pdf/effects-of-tree-species-on-moso-bamboo-phyllostachys-edulis-3bod3xcu.pdf

Effects of Tree Species on Moso Bamboo (Phyllostachys edulis (Carriere) J. Houzeau) Fine Root Morphology, Biomass, and Soil Properties in Bamboo–Broadleaf Mixed Forests

Degraded bamboo shoots (DBS) constitute an important variable in the carbon fixation of bamboo forests. DBS are useful for informed decision making in bamboo forests. Despite their importance, studies on DBS are limited. In this study, we aimed to develop models to describe DBS variations. By using DBS data from 64 plots of Yixing forest farm in Jiangsu Province, China, a mixed-effects model was constructed, including block-level random effects. We evaluated the potential impact of several variables on DBS. The number of bamboo shoots (NBS), mean height to crown base (MHCB), hydrolytic nitrogen (HN), and available potassium (AK) significantly contributed to the model. By introducing the block-level random effect in the logistic model, the fitting statistics were significantly improved. The model showed that there were increased DBS in bamboo stands with decreased MHCB and AK, whereas DBS decreased with decreasing NBS and HN. The application of K fertilizer reduced the number of DBS during the emergence stage. By adjusting these factors, the number of DBS in bamboo forests can be reduced, which provides a theoretical basis for increasing the biomass of bamboo forests. It can also provide an important basis for studying the carbon sink characteristics of bamboo forests and help to formulate more effective bamboo forest management plans.

/pdf/modeling-degraded-bamboo-shoots-in-southeast-china-2lyqbd7w.pdf

Modeling Degraded Bamboo Shoots in Southeast China

Height to crown base (HCB) is an important predictor variable for forest growth and yield models and is of great significance for bamboo stem utilization. However, existing HCB models built so far on the hierarchically structured data are for arbor forests, and not applied to bamboo forests. Based on the fitting of data acquired from 38 temporary sample plots of Phyllostachys edulis forests in Yixing, Jiangsu Province, we selected the best HCB model (logistic model) from among six basic models and extended it by integrating predictor variables, which involved evaluating the impact of 13 variables on HCB. Block- and sample plot-level random effects were introduced to the extended model to account for nested data structures through mixed-effects modeling. The results showed that bamboo height, diameter at breast height, total basal area of all bamboo individuals with a diameter larger than that of the subject bamboo, and canopy density contributed significantly more to variation in HCB than other variables did. Introducing two-level random effects resulted in a significant improvement in the accuracy of the model. Different sampling strategies were evaluated for response calibration (model localization), and the optimal strategy was identified. The prediction accuracy of the HCB model was substantially improved, with an increase in the number of bamboo samples in the calibration. Based on our findings, we recommend the use of four randomly selected bamboo individuals per sample to provide a compromise between measurement cost, model use efficiency, and prediction accuracy.

/pdf/two-level-mixed-effects-height-to-crown-base-model-for-moso-25a4m4gk.pdf

Two-level mixed-effects height to crown base model for moso bamboo (Phyllostachys edulis) in Eastern China

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