scholarly journals Sensitivity of Functional Traits to Environmental factors in a Karst Plant Community

2022 ◽  
Author(s):  
Yang Wang ◽  
Limin Zhang ◽  
Jin Chen ◽  
Ling Feng ◽  
Fangbing Li ◽  
...  
Keyword(s):  
Environmental Factors ◽  
Nitrogen Content ◽  
Bulk Density ◽  
Leaf Area ◽  
Plant Community ◽  
Functional Traits ◽  
Specific Leaf Area ◽  
Soil Bulk Density ◽  
Leaf Nitrogen ◽  
Leaf Nitrogen Content

In this study, the plant communities at five succession stages (herbage, herbage-shrub, shrub, tree-shrub, and tree) in the Zhenning Karst Plateau area of Guizhou were examined. The changes of plant functional characteristics in different succession stages were analyzed, as was the relationship between functional traits and environmental factors. The main results include the following. (1) During the succes-sion process, plant height, leaf dry matter mass, leaf area, leaf nitrogen content, and leaf phosphorus content gradually increased, whereas leaf thickness and specific leaf area decreased, and leaf C:P ratio and leaf N:P ratios did not change significantly. (2) Soil organic matter, soil total nitrogen, soil total phosphorus, soil C:N, soil C:P, and soil C:K increased at first and then decreased, reaching a peak at the tree-shrub stage. Soil total potassium fluctuated and soil bulk density gradually decreased and reached the lowest value at the tree-shrub stage. (3) Redundancy analysis (RDA) showed that the plant community shifted from a nutri-ent-poor soil environment to a nutrient-rich environment. Soil total phosphorus, soil C:K, soil organic mat-ter, soil C:N, and soil bulk density were the key environmental factors affecting the change of functional traits. (4) Structural equation modeling suggests that that specific leaf area and leaf nitrogen content had more sensitive responses to soil nutrient resources and environmental factors, respectively.

scholarly journals Regional-Scale Relationships of Leaf Area Index to Specific Leaf Area and Leaf Nitrogen Content

1994 ◽  
Vol 4 (2) ◽  
pp. 313-321 ◽  
Author(s):  
Lars L. Pierce ◽  
Steven W. Running ◽  
Joe Walker
Keyword(s):  
Leaf Area Index ◽  
Nitrogen Content ◽  
Leaf Area ◽  
Specific Leaf Area ◽  
Regional Scale ◽  
Leaf Nitrogen ◽  
Leaf Nitrogen Content ◽  
Area Index

scholarly journals Leaf traits and gas exchange in saplings of native tree species in the Central Amazon

2010 ◽  
Vol 67 (6) ◽  
pp. 624-632 ◽  
Author(s):  
Keila Rego Mendes ◽  
Ricardo Antonio Marenco
Keyword(s):  
Gas Exchange ◽  
Nitrogen Content ◽  
Leaf Area ◽  
Tree Species ◽  
Leaf Traits ◽  
Leaf Nitrogen ◽  
Dry Season ◽  
Leaf Thickness ◽  
Rainfall Regime ◽  
Leaf Nitrogen Content

Global climate models predict changes on the length of the dry season in the Amazon which may affect tree physiology. The aims of this work were to determine the effect of the rainfall regime and fraction of sky visible (FSV) at the forest understory on leaf traits and gas exchange of ten rainforest tree species in the Central Amazon, Brazil. We also examined the relationship between specific leaf area (SLA), leaf thickness (LT), and leaf nitrogen content on photosynthetic parameters. Data were collected in January (rainy season) and August (dry season) of 2008. A diurnal pattern was observed for light saturated photosynthesis (Amax) and stomatal conductance (g s), and irrespective of species, Amax was lower in the dry season. However, no effect of the rainfall regime was observed on g s nor on the photosynthetic capacity (Apot, measured at saturating [CO2]). Apot and leaf thickness increased with FSV, the converse was true for the FSV-SLA relationship. Also, a positive relationship was observed between Apot per unit leaf area and leaf nitrogen content, and between Apot per unit mass and SLA. Although the rainfall regime only slightly affects soil moisture, photosynthetic traits seem to be responsive to rainfall-related environmental factors, which eventually lead to an effect on Amax. Finally, we report that little variation in FSV seems to affect leaf physiology (Apot) and leaf anatomy (leaf thickness).

scholarly journals Variation Patterns of Functional Trait Moments Along Geographical Gradients and Their Environmental Determinants in the Subtropical Evergreen Broadleaved Forests

2021 ◽  
Vol 12 ◽  
Author(s):  
Caishuang Huang ◽  
Yue Xu ◽  
Runguo Zang
Keyword(s):  
Climate Variability ◽  
Leaf Area ◽  
Functional Traits ◽  
Specific Leaf Area ◽  
Functional Trait ◽  
Leaf Nitrogen ◽  
Subtropical Region ◽  
Mean Variance ◽  
Nitrogen Phosphorus ◽  
Skewness And Kurtosis

Understanding how environmental change alters the composition of plant assemblages is a major challenge in the face of global climate change. Researches accounting for site-specific trait values within forest communities help bridge plant economics theory and functional biogeography to better evaluate and predict relationships between environment and ecosystem functioning. Here, by measuring six functional traits (specific leaf area, leaf dry matter content, leaf nitrogen, and phosphorus concentration, leaf nitrogen/phosphorus, wood density) for 292 woody plant species (48,680 individuals) from 250 established permanent forest dynamics plots in five locations across the subtropical evergreen broadleaved forests (SEBLF) in China, we quantified functional compositions of communities by calculating four trait moments, i.e., community-weighted mean, variance, skewness, and kurtosis. The geographical (latitudinal, longitudinal, and elevational) patterns of functional trait moments and their environmental drivers were examined. Results showed that functional trait moments shifted significantly along the geographical gradients, and trait moments varied in different ways across different gradients. Plants generally showed coordinated trait shifts toward more conservative growth strategies (lower specific leaf area, leaf N and P concentration while higher leaf nitrogen/phosphorus and wood density) along increasing latitude and longitude. However, trends opposite to the latitudinal and longitudinal patterns appeared in trait mean values along elevation. The three sets of environmental variables (climate, soil and topography) explained 35.0–69.0%, 21.0–56.0%, 14.0–31.0%, and 16.0–30.0% of the variations in mean, variance, skewness, and kurtosis across the six functional traits, respectively. Patterns of shifts in functional trait moments along geographical gradients in the subtropical region were mainly determined by the joint effects of climatic and edaphic conditions. Climate regimes, especially climate variability, were the strongest driving force, followed by soil nutrients, while topography played the least role. Moreover, the relationship of variance, skewness and kurtosis with climate and their geographical patterns suggested that rare phenotypes at edges of trait space were selected in harsher environments. Our study suggested that environmental filtering (especially climate variability) was the dominant process of functional assembly for forest communities in the subtropical region along geographical gradients.

scholarly journals Resource colimitation governs plant community responses to altered precipitation

2015 ◽  
Vol 112 (42) ◽  
pp. 13009-13014 ◽  
Author(s):  
Anu Eskelinen ◽  
Susan P. Harrison
Keyword(s):  
Leaf Area ◽  
Plant Community ◽  
Functional Traits ◽  
Specific Leaf Area ◽  
Water Availability ◽  
Species Turnover ◽  
Soil Nutrient ◽  
Resource Limitation ◽  
Tall Stature ◽  
Multiple Resource

Ecological theory and evidence suggest that plant community biomass and composition may often be jointly controlled by climatic water availability and soil nutrient supply. To the extent that such colimitation operates, alterations in water availability caused by climatic change may have relatively little effect on plant communities on nutrient-poor soils. We tested this prediction with a 5-y rainfall and nutrient manipulation in a semiarid annual grassland system with highly heterogeneous soil nutrient supplies. On nutrient-poor soils, rainfall addition alone had little impact, but rainfall and nutrient addition synergized to cause large increases in biomass, declines in diversity, and near-complete species turnover. Plant species with resource-conservative functional traits (low specific leaf area, short stature) were replaced by species with resource-acquisitive functional traits (high specific leaf area, tall stature). On nutrient-rich soils, in contrast, rainfall addition alone caused substantial increases in biomass, whereas fertilization had little effect. Our results highlight that multiple resource limitation is a critical aspect when predicting the relative vulnerability of natural communities to climatically induced compositional change and diversity loss.

scholarly journals Functional Traits Are Good Predictors of Tree Species Abundance Across 101 Subtropical Forest Species in China

2021 ◽  
Vol 12 ◽  
Author(s):  
Ronghua Li ◽  
Shidan Zhu ◽  
Juyu Lian ◽  
Hui Zhang ◽  
Hui Liu ◽  
...  
Keyword(s):  
Nitrogen Content ◽  
Functional Traits ◽  
Phosphorus Content ◽  
Species Abundance ◽  
Leaf Nitrogen ◽  
Subtropical Forest ◽  
Evergreen Forest ◽  
Forest Plot ◽  
Stem Density ◽  
Leaf Nitrogen Content

What causes variation in species abundance for a given site remains a central question in community ecology. Foundational to trait-based ecology is the expectation that functional traits determine species abundance. However, the relative success of using functional traits to predict relative abundance is questionable. One reason is that the diversity in plant function is greater than that characterized by the few most commonly and easily measurable traits. Here, we measured 10 functional traits and the stem density of 101 woody plant species in a 200,000 m2 permanent, mature, subtropical forest plot (high precipitation and high nitrogen, but generally light- and phosphorus-limited) in southern China to determine how well relative species abundance could be predicted by functional traits. We found that: (1) leaf phosphorus content, specific leaf area, maximum CO2 assimilation rate, maximum stomata conductance, and stem hydraulic conductivity were significantly and negatively associated with species abundance, (2) the ratio of leaf nitrogen content to leaf phosphorus content (N:P) and wood density were significantly positively correlated with species abundance; (3) neither leaf nitrogen content nor leaf turgor loss point were related to species abundance; (4) a combination of N:P and maximum stomata conductance accounted for 44% of the variation in species’ abundances. Taken together, our findings suggested that the combination of these functional traits are powerful predictors of species abundance. Species with a resource-conservative strategy that invest more in their tissues are dominant in the mature, subtropical, evergreen forest.

Leaf Photosynthesis and Drought Adaptation in Field-Grown Oilseed Rape (Brassica napus L.)

1996 ◽  
Vol 23 (5) ◽  
pp. 631 ◽  
Author(s):  
CR Jensen ◽  
VO Mogensen ◽  
G Mortensen ◽  
MN Andersen ◽  
JK Schjoerring ◽  
...  
Keyword(s):  
Brassica Napus ◽  
Nitrogen Content ◽  
Leaf Area ◽  
Leaf Nitrogen ◽  
C3 Plants ◽  
Soil Drying ◽  
Leaf Nitrogen Content ◽  
Drought Adaptation ◽  
Brassica Napus L ◽  
Use Efficiency

Photosynthesis and drought adaptation in leaves of field grown rape (Brassica napus L. cv. Global) were investigated in 1992 under temperate climatic conditions in plants grown in lysimeters in a sand and in a loam soil. Light-saturated net photosynthesis (Amax), leaf conductance to water vapour (ge), leaf water potential (Ψe), leaf osmotic potential at full turgor (Ψπ100), specific leaf area (SLA), spectral reflection index (RI) used as a measure of leaf area, and leaf nitrogen content, were determined in irrigated plants and in plants exposed to soil drying. In the early growth stages before flowering, Amax was 35-45 μmol m-2 s-1 and ge was 1-1.5 mol m-2 s-1. Maximum rates of CO2 assimilation greater than 30 μmol m-2 s-1 were obseved for up to 19 days. Stomata partly closed in ageing leaves maintaining a constant CI/Ca ratio. Both photosynthetic nitrogen use efficiency (NUE; Amax per unit of nitrogen) and photosynthetic water use efficiency (WUE; Amax/ge) were high compared with efficiencies of stems and husks and of other C3 plants. In bracts Amax and ge were 10-15 μmol m-2 s-1 and 0.2-0.7 mol mol m-2 s-1, respectively. Both Amax and ge varied linearly with leaf nitrogen content. When soil water was depleted, both Ψπ100 and RI decreased relative to controls on both soil types before any significant decrease in Ψπ occurred. On loam with slow soil drying SLA, ge and Amax decreased before any significant decrease in Ψe occurred. We suggest that these responses might have been triggered by a non-hydraulic signal transmitted from the roots. When water was more depleted, rape maintained positive turgor down to Ψe of -1.6 MPa. Rape had a high TW/DW ratio (9-11) and a 6 limited ability to adjust osmotically, ΔΨe100 being at most 0.3-0.4 MPa.

scholarly journals Estimating the Leaf Nitrogen Content with a New Feature Extracted from the Ultra-High Spectral and Spatial Resolution Images in Wheat

2021 ◽  
Vol 13 (4) ◽  
pp. 739
Author(s):  
Jiale Jiang ◽  
Jie Zhu ◽  
Xue Wang ◽  
Tao Cheng ◽  
Yongchao Tian ◽  
...  
Keyword(s):  
Nitrogen Content ◽  
Precision Agriculture ◽  
Field Experiments ◽  
Mean Squared Error ◽  
Growing Season ◽  
Leaf Nitrogen ◽  
Textural Analysis ◽  
Hyperspectral Images ◽  
Leaf Nitrogen Content ◽  
New Feature

Real-time and accurate monitoring of nitrogen content in crops is crucial for precision agriculture. Proximal sensing is the most common technique for monitoring crop traits, but it is often influenced by soil background and shadow effects. However, few studies have investigated the classification of different components of crop canopy, and the performance of spectral and textural indices from different components on estimating leaf nitrogen content (LNC) of wheat remains unexplored. This study aims to investigate a new feature extracted from near-ground hyperspectral imaging data to estimate precisely the LNC of wheat. In field experiments conducted over two years, we collected hyperspectral images at different rates of nitrogen and planting densities for several varieties of wheat throughout the growing season. We used traditional methods of classification (one unsupervised and one supervised method), spectral analysis (SA), textural analysis (TA), and integrated spectral and textural analysis (S-TA) to classify the images obtained as those of soil, panicles, sunlit leaves (SL), and shadowed leaves (SHL). The results show that the S-TA can provide a reasonable compromise between accuracy and efficiency (overall accuracy = 97.8%, Kappa coefficient = 0.971, and run time = 14 min), so the comparative results from S-TA were used to generate four target objects: the whole image (WI), all leaves (AL), SL, and SHL. Then, those objects were used to determine the relationships between the LNC and three types of indices: spectral indices (SIs), textural indices (TIs), and spectral and textural indices (STIs). All AL-derived indices achieved more stable relationships with the LNC than the WI-, SL-, and SHL-derived indices, and the AL-derived STI was the best index for estimating the LNC in terms of both calibration (Rc2 = 0.78, relative root mean-squared error (RRMSEc) = 13.5%) and validation (Rv2 = 0.83, RRMSEv = 10.9%). It suggests that extracting the spectral and textural features of all leaves from near-ground hyperspectral images can precisely estimate the LNC of wheat throughout the growing season. The workflow is promising for the LNC estimation of other crops and could be helpful for precision agriculture.

scholarly journals Functional Trait Responses to Strip Clearcutting in a Moso Bamboo Forest

Forests ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 793
Author(s):  
Yaxiong Zheng ◽  
Fengying Guan ◽  
Shaohui Fan ◽  
Yang Zhou ◽  
Xiong Jing
Keyword(s):  
Leaf Area ◽  
Functional Traits ◽  
Root Length ◽  
Fine Root ◽  
Root Traits ◽  
Moso Bamboo ◽  
Leaf Nitrogen Content ◽  
Dry Matter Content ◽  
Functional Characteristics ◽  
Functional Features

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). In terms of functional characteristics, SC significantly decreased LA and increased LNC, LPC, and N:P (p < 0.05). However, SC had no significant effect on fine root traits (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.

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