The spatial variations and driving factors of C, N, P stoichiometric characteristics of plant and soil in the terrestrial ecosystem

Carbon(C), nitrogen(N), and phosphorus(P) are crucial elements in the element cycling in the terrestrial ecosystems. In the past decades, the spatial patterns and driving mechanisms of plant and soil ecological stoichiometry have been hot topics in ecological geography. So far, many studies at different spatial and ecological scales have been conducted, but systematic review has not been reported to summarize the research status. In this paper, we tried to fill this gap by reviewing both the spatial variations and driving factors of C, N, P stoichiometric characteristics of plant and soil at regional to large scale. Additionally, we synthesized researches on the relationships between plant and soil C, N and P stoichiometric characteristics. At the global scale, plant C, N, P stoichiometric characteristics exhibited some trends along latitude and temperature gradient. Plant taxonomic classification was the main factor controlling the spatial variations of plant C, N and P stoichiometric characteristics. Climate factor and soil properties showed varying impacts on the spatial variations of plant C, N, P stoichiometric characteristics across different spatial scales. Soil C, N, P stoichiometric characteristics also varied along climate gradient at large scale. Their spatial variations resulted from the combined effects of climate, topography, soil properties, and vegetation characteristics at regional scale. The spatial pattern of soil C, N, P stoichiometric characteristics and the driving effects from environmental factors could be notably different among different ecosystems and vegetation types. Plant C:N:P was obviously higher than that of soil, and there existed a positive correlation between plant and soil C:N:P. Their trends along longitude and latitude were similar, but this correlation varied significantly among different vegetation types. Finally, based on the issues identified in this paper, we highlighted eight potential research themes for the future studies.

Climate factors dominate the elevational variation in grassland plant resource utilization strategies

Specific leaf area (SLA) and leaf dry matter content (LDMC) are key leaf functional traits often used to reflect plant resource utilization strategies and predict plant responses to environmental changes. In general, grassland plants at different elevations exhibit varying survival strategies. However, it remains unclear how grassland plants adapt to changes in elevation and their driving factors. To address this issue, we utilized SLA and LDMC data of grassland plants from 223 study sites at different elevations in China, along with climate and soil data, to investigate variations in resource utilization strategies of grassland plants along different elevational gradients and their dominant influencing factors employing linear mixed-effects models, variance partitioning method, piecewise Structural Equation Modeling, etc. The results show that with increasing elevation, SLA significantly decreases, and LDMC significantly increases (P < 0.001). This indicates different resource utilization strategies of grassland plants across elevation gradients, transitioning from a "faster investment-return" at lower elevations to a "slower investment-return" at higher elevations. Across different elevation gradients, climatic factors are the main factors affecting grassland plant resource utilization strategies, with soil nutrient factors also playing a non-negligible coordinating role. Among these, mean annual precipitation and hottest month mean temperature are key climatic factors influencing SLA of grassland plants, explaining 28.94% and 23.88% of SLA variation, respectively. The key factors affecting LDMC of grassland plants are mainly hottest month mean temperature and soil phosphorus content, with relative importance of 24.24% and 20.27%, respectively. Additionally, the direct effect of elevation on grassland plant resource utilization strategies is greater than its indirect effect (through influencing climatic and soil nutrient factors). These findings emphasize the substantive impact of elevation on grassland plant resource utilization strategies and have important ecological value for grassland management and protection under global change.

Patterns and driving factors of functional traits of desert species with different elevational distributions in the Tibetan Plateau and adjacent areas

Variations in functional traits serve as measures of plants' ability to adapt to environment. Exploring the patterns of functional traits of desert plants along elevational gradients is helpful to understand the responses and adaptation strategies of species to changing environments. However, it is unknown whether the relationship between functional traits and elevation is affected by differences in the species' elevational distributions (elevation preference and species' range). Importantly, most researches have concerned with differences in mean trait values and ignored intraspecific trait variation. Here, we measured functional traits of desert plants along a wide elevational gradient in the Tibetan Plateau and adjacent areas and explored functional trait patterns over elevation in species with different elevational distributions. We decomposed trait variation and further investigated characterizations of intraspecific variation. Ultimately, the main drivers of trait variation were identified using redundancy analysis. We found that species' elevational distributions significantly influenced the relationship of functional traits such as plant height, leaf dry matter content, leaf thickness, leaf nitrogen and carbon content with elevation. Species with a lower elevational preference showed greater trait variation than species with a higher elevational preference, suggesting that species that prefer high elevation are more conservative facing environmental changes. We provide evidence that interspecific trait variation in leaf thickness and leaf carbon content decreased with increasing species' range, indicating that increased variations in resistance traits within species make greater responsiveness to environmental changes, enabling species a wider range. Elevation, temperature and precipitation were the main drivers of trait variation in species with a low elevational preference, while the effect of precipitation on trait variation in species with a high elevational preference was not significant. This study sheds new insights on how plants with different elevational distributions regulate their ecological strategies to cope with changing environments.

Leaf functional traits vary among growth forms and vegetation zones in the Himalaya

Compression of life zones along elevational gradients in mountains supports diverse vegetation types, and therefore offers ideal setting to study plant functional traits. Functional traits, the features that enable plants to live in varied environmental conditions, help in understanding ecological interactions, evolutionary adaptations, and predicting plant response to global change drivers. To date, little is known how the trait diversity varies across different growth forms and vegetation zones in mountains. Here, we aimed to investigate interspecific leaf trait variability among different growth forms and vegetation zones along a wide elevation gradient (2000-4200 m) in Kashmir Himalaya. We measured leaf functional traits (specific leaf area-SLA, leaf thickness - LT, leaf dry matter content -LDMC) of 76 plant species corresponding to three growth forms (trees, shrubs and herbs) and three vegetation zones (Himalayan dry temperate forests, subalpine forests and alpine grasslands). Our results revealed high trait variability across the regional species pool studied. We found significant variation in leaf functional traits among the different growth forms, with higher values of LT and LDMC recorded for woody species than herbaceous ones. Among different vegetation zones, the SLA was found to be significantly higher at lower to middle elevations, while the other leaf traits (LT and LDMC) showed an opposite trend. Across all the vegetative zones, we also found a negative correlation between SLA and the other leaf traits, and the latter showed a positive trait-trait correlation. Overall, our study contributes to a deeper understanding of trait-trait, trait-growth form and trait-vegetation zone relationships. Our findings suggest that the variation in leaf functional traits among different growth forms seems to be a trade-off mechanism between resource acquisition and leaf construction, and also help in identifying species' adaptive functional traits that are critical for plant survival in the face of ongoing climate change in the Himalaya.

Functional trait diversity and aboveground biomass of herbaceous vegetation in temperate forests of Kashmir Himalaya

Studying functional trait diversity can provide crucial clues about the adaptive survival strategies of regional plant species pool. Despite large-scale trait datasets available worldwide, the plant trait data from many biodiversity hotpot regions, like the Himalaya is still scarce. In this study, we aimed to investigate the plant functional traits and aboveground biomass of understory herbaceous vegetation in temperate forests of Overa-Aru wildlife sanctuary of Kashmir Himalaya. We also investigate how these functional traits correlate and what is the magnitude of trait-biomass relationship across the herbaceous species pool. For this, we conducted field sampling and measured leaf functional traits and aboveground biomass of 38 plant species in the study region during peak growing season (July-August) in the year 2021. The results revealed a significant interspecific trait variability among the species studied. We observed a high variability in leaf size and type spectra of the species, with nanophyll and simple leaf lamina, respectively, the most common types among the species studied. The correlation analysis revealed that plant height was positively correlated with aboveground biomass. The variation partitioning analysis revealed that the plant height explained the maximum fraction of variation in aboveground biomass, while least by specific leaf area. Overall, the findings from the present study provide useful insights in understanding trait-trait relationship and trait-environment interaction at the regional scale and can also help in recognizing adaptive functional traits of plant species that determine plant survival under the changing climate in this Himalayan region.

High-resolution maps of vegetation nitrogen density on the Tibetan Plateau: An intensive field-investigation

Nitrogen (N) is a vital macronutrient in plant growth and development that plays a crucial role in the regulation of numerous physiological processes. The Tibetan Plateau is among the most species-diverse vegetation zones in the world, and is sensitive to climate change; however, research on vegetation N in the region remains limited. This study used field grid-sampling of 2040 plant communities to investigate the spatial variation and driving factors of vegetation N on the Tibetan Plateau. The results yielded an average N content, density and storage in vegetation of 8.48 mg g-1, 27.02 g m-2, and 29.84Tg, respectively. The ratio-based optimal partitioning hypothesis appears to be more suitable than the isometric allocation hypothesis to explain variation in vegetation N on the Tibetan Plateau. Variation in vegetation N density, was influenced by several environmental factors of which the most significant was radiation. Based on these results, a Random Forest model was used to predict a N density distribution map at 1 km resolution, achieving an accuracy (R2) of 0.72 (aboveground N density), 0.61 (belowground N density), and 0.69 (total vegetation N density). Trends for high densities were predicted in the southeast and low densities in the northwest of the region. Our findings and maps could be used to provide key N cycle parameters, contributing to future remote sensing, radar analyses, modeling and ecological management.

Predicting community traits along an alpine grassland transect using field imaging spectroscopy

Assessing plant community traits is important for understanding how terrestrial ecosystems respond and adapt to global climate change. Field hyperspectral remote sensing is effective for quantitatively estimating vegetation properties in most terrestrial ecosystems, although it remains to be tested in areas with dwarf and sparse vegetation, such as the Tibetan Plateau. We measured canopy reflectance in the Tibetan Plateau using a handheld imaging spectrometer and conducted plant community investigations along an alpine grassland transect. We estimated community structural and functional traits, as well as community function based on a field survey and laboratory analysis using 14 spectral vegetation indices (VIs) derived from hyperspectral images. We quantified the contributions of environmental drivers, VIs, and community traits to community function by structural equation modelling (SEM). Univariate linear regression analysis showed that plant community traits are best predicted by the normalized difference vegetation index, enhanced vegetation index, and simple ratio. Structural equation modelling showed that VIs and community traits positively affected community function, whereas environmental drivers and specific leaf area had the opposite effect. Additionally, VIs integrated with environmental drivers were indirectly linked to community function by characterizing the variations in community structural and functional traits. This study demonstrates that community-level spectral reflectance will help scale plant trait information measured at the leaf level to larger-scale ecological processes. Field imaging spectroscopy represents a promising tool to predict the responses of alpine grassland communities to climate change.

Ecological Strategy Spectra for Communities of Different Successional Stages in the Tropical Lowland Rainforest of Hainan Island

Plant ecological strategies are shaped by long-term adaptation to the environment and are beneficial to plant survival and reproduction. Research is ongoing to better understand how plants best allocate resources for growth, survival and reproduction, as well as how ecological strategies may shift in plant communities over the course of succession. In this study, 12 forest dynamics plots in three different successional stages were selected for study in the tropical lowland rainforest ecosystem of Hainan Island. For each plot, using Grime’s competitor, a stress-tolerator, the ruderal (CSR) scheme and using the CSR ratio tool “StrateFy”, an ecological strategy spectrum was constructed using functional trait data obtained by collecting leaf samples from all woody species. The ecological strategy spectra were compared across successional stages to reveal successional dynamics. The results showed: (1) The ecological strategy spectra varied among forest communities belonging to three different successional stages. (2) The community-weighted mean CSR (CWM-CSR) strategies shifted with succession: CWM-S values decreased, while the CWM-C and CWM-R values increased. Overall, shifts in plant functional traits occurred slowly and steadily with succession showing complex and diverse trade-offs and leading to variation among the ecological strategy spectra of different successional stages.

Addressing Gender Inequities in Forest Science and Research

Forest research and professional workforces continue to be dominated by men, particularly at senior and management levels. In this review, we identify some of the historical and ongoing barriers to improved gender inclusion and suggest some solutions. We showcase a selection of women in forestry from different disciplines and parts of the globe to highlight a range of research being conducted by women in forests. Boosting gender equity in forest disciplines requires a variety of approaches across local, regional and global scales. It is also important to include intersectional analyses when identifying barriers for women in forestry, but enhanced equity, diversity and inclusion will improve outcomes for forest ecosystems and social values of forests, with potential additional economic benefits.

Nitrogen storage in China's terrestrial ecosystems

Nitrogen (N) is an essential element for plant growth and ecosystem productivity. Accurate estimation of N storage in terrestrial ecosystems is crucial because it is one of the most important N pools in the earth system; however, the spatial patterns of N storage and the main influencing factors remain unclear due to the limited data available, particularly on the N content in plant organs. Here we systematically estimated the N storage in China for the first time using 44,337 field-measured data. The total N storage was 10.43 Pg N, with 0.29 Pg N in vegetation and 10.14 Pg N in soil (0-100 cm); of these, approximately 62.07% (0.18 Pg N) of the vegetation N was stored in active plant organs (leaf and root). Furthermore, N storage in the forest, grassland, wetland, and cropland ecosystems (excluding vegetation) was 3.74, 3.15, 0.24, and 1.93 Pg N, respectively. The spatial patterns of N density were different in vegetation and soil. Redundancy analysis showed that the main factor influencing the spatial patterns in vegetation was climate, whereas the main factors influencing the spatial patterns in soil were climate and soil nutrient. Our study clarified the N pools of each subsystem (particularly for plant organs) and revealed the main influencing factors. In addition, we compiled N density datasets for different plant organs and soil depths across various climatic regions in China, which could provide parameters for regional N cycle models or serve as a reference for regional N management.