Relative Aboveground Biomass Research Articles

A radar backscatter simulation of a forest canopy using 3D physical structures derived from LiDAR scanning

ABSTRACT This study aims to explore the forest aboveground biomass relationship to C-band backscatter. A one-hectare area in Wytham Woods, located west of Oxford, was selected for this research. The area has a total of 525 trees of seven different tree species. The Michigan Microwave Canopy Scattering Model (MIMICS), a two-layer radiative transfer model, was applied to simulate canopy backscatter responses in this deciduous UK forest. Model parameters related to forest structure were derived from previously published terrestrial laser (LiDAR) data. Simulated backscatter was performed for co-polarized and cross-polarized modes at a C-band frequency range and incidence angles (20° to 45° at 5° increments). The research includes five objectives: i) backscatter sensitivity analysis from the variation of different model parameters; ii) backscatter seasonal effect under spring–summer (leaf-on) and autumn–winter (leaf-off) periods; iii) backscatter comparison between species as well as between simulated and satellite observations in a spatial pattern; iv) relationship between simulated backscatter and aboveground biomass; and v) relationship between MIMICS forest structure parameters and simulated backscatter. Sensitivity analysis results showed significant differences in backscatter from changes in leaf distribution, leaf thickness and water content (leaf, trunk and soil) for both polarization modes in leaf-on scenarios. Leaf-off scenarios presented significant differences from changes in branch distribution but only for the co-polarized mode. Seasonal variations presented significant backscatter differences between spring–summer and autumn–winter scenarios; additionally, backscatter differences among species for each seasonality in the co-polarized mode were observed. The computation of the grid resolution (20 m × 20 m) showed a range of backscatter values depending on the grid and incidence angle. Higher backscatter values were observed for the satellite data than for the simulated data. Finally, the aboveground biomass and the MIMICS input parameters presented high random variability and little systematic co-variation with the total backscatter on both simulated seasons, suggesting that more robust allometric equations for biomass estimation are required.

No effect of invasive tree species on aboveground biomass increments of oaks and pines in temperate forests

Prunus serotina and Robinia pseudoacacia are the most widespread invasive trees in Central Europe. In addition, according to climate models, decreased growth of many economically and ecologically important native trees will likely be observed in the future. We aimed to assess the impact of these two neophytes, which differ in the biomass range and nitrogen-fixing abilities observed in Central European conditions, on the relative aboveground biomass increments of native oaks Quercus robur and Q. petraea and Scots pine Pinus sylvestris. We aimed to increase our understanding of the relationship between facilitation and competition between woody alien species and overstory native trees. We established 72 circular plots (0.05 ​ha) in two different forest habitat types and stands varying in age in western Poland. We chose plots with different abundances of the studied neophytes to determine how effects scaled along the quantitative invasion gradient. Furthermore, we collected growth cores of the studied native species, and we calculated aboveground biomass increments at the tree and stand levels. Then, we used generalized linear mixed-effects models to assess the impact of invasive species abundances on relative aboveground biomass increments of native tree species. We did not find a biologically or statistically significant impact of invasive R. pseudoacacia or P. serotina on the relative aboveground biomass increments of native oaks and pines along the quantitative gradient of invader biomass or on the proportion of total stand biomass accounted for by invaders. The neophytes did not act as native tree growth stimulators but also did not compete with them for resources, which would escalate the negative impact of climate change on pines and oaks. The neophytes should not significantly modify the carbon sequestration capacity of the native species. Our work combines elements of the per capita effect of invasion with research on mixed forest management.

Both the selection and complementarity effects underpin the effect of structural diversity on aboveground biomass in tropical forests

AbstractAimDespite mounting empirical evidence regarding the positive effects of forest structural diversity (STRDIV) on forest functioning, the underlying biotic mechanisms and controlling abiotic factors remain poorly understood. This study provides the first assessment of the interactive effects of STRDIV and diversity in species and functional traits on aboveground biomass (AGB) in natural forests in West and East Africa.LocationWest and East Africa.Time period2014–2020.Major taxa studiedWoody plants.MethodsUsing data from 276 plots and 7993 trees of 207 species distributed across various types of natural forests and major climatic zones of Africa, linear mixed‐effects and structural equation models, we have evaluated how alternative causal relationships between STRDIV and taxonomic and functional diversity attributes influence AGB, while accounting for the effects of environmental covariates. We also assessed the consistency of these relationships across floristically and environmentally homogenous forest types.ResultsWe found that the positive effects of STRDIV on AGB were underpinned by both the community‐weighted mean (CWM) of trait values (selection effects) and species richness (niche complementarity), but the relative importance of these effects varied depending on forest types. Across the forest types, STRDIV primarily mediated the effects of CWM of traits and species richness on AGB. We also found that STRDIV–AGB relationships were constrained by resource (water and nutrient) availability.Main conclusionsOur findings provide novel insights into the role of functional traits as key determinants of the effects of STRDIV on AGB in tropical forests. We suggest that forest management and climate change mitigation strategies aimed at conserving biodiversity, and fostering biomass storage through increased STRDIV should focus on maintaining high levels of functionally dominant species while also increasing tree species diversity.

Justicia americana exhibits stem density–aboveground biomass relationships and variability in elemental composition and isotopic signature across tissue types and land use gradients

Riverine macrophytes are increasingly understood to influence both the physical and chemical dynamics of rivers by creating biogeochemical hotspots and stabilizing benthic sediments. They contribute carbon and nutrients to both aquatic and adjacent terrestrial ecosystems through senescence and herbivory. Here, we report the relationships between Justicia americana biomass, stem length, and stem density, and % carbon (%C), % nitrogen (%N), C:N, δ15N, and δ13C relationships between tissues types (roots, stems, and leaves). Additionally, we report the effects of land use on the plant's tissue. We found that (1) J. americana stem density and dry biomass were positively correlated ( P < 0.001); (2) δ13C and %N were significantly different in leaf and root tissue; (3) δ13C and δ15N were both positively correlated across tissue types; (4) Leaf C:N was less than ½ of root and stem tissue; (5) %C in leaf tissue was positively correlated ( P < 0.05) with forest cover and negatively correlated with urbanization and watershed area; and (6) provide evidence that J. americana utilizes a C3 photosynthetic pathway. Overall, this study provides novel insight into the ecology of J. americana by elucidating the nutritional quality of different plant tissues and stoichiometric changes in the plant in response to land use.

Precipitation and Temperature Influence the Relationship between Stand Structural Characteristics and Aboveground Biomass of Forests—A Meta-Analysis

Forest aboveground biomass (AGB) is not simply affected by a single factor or a few factors, but also by the interaction between them in complex ways across multiple spatial scales. Understanding the joint effect of stand structural characteristics and climate factors on AGB on large scales is critical for accurate forest carbon storage prediction and sustainable management. Despite numerous attempts to clarify the relationships between stand structural characteristics (tree density/TD, diameter at breast height/DBH, basal area/BA), climate factors (mean annual temperature/MAT, mean annual precipitation/MAP), and AGB, they remain contentious on a large scale. Therefore, we explored the relationships between stand structural characteristics, climate factors, and AGB at a biome level by meta-analyzing datasets contained in 40 articles from 25 countries, and then answered the questions of how stand structural characteristics influence AGB at the biome level and whether the relationships are regulated by climate on a large scale. Through using regression analysis and the establishment of a structural equation model, the results showed that the influence of basal area on AGB at the biome level was more substantial than that of tree density and DBH, and the significant relationship between basal area and AGB was relatively stable regardless of biome variation, but the effects of tree density and DBH was non-negligible within the biome. Climatic factors (e.g., temperature and precipitation), should be considered. Our meta-analysis illustrated the complicated interactions between climate factors, stand structural characteristics, and the AGB of forests, highlighting the importance of climate effects on regulating stand structural characteristics and AGB relationships. We suggest that basal area be preferred and considered in forest sustainable management practice to optimize stand structure for increasing carbon storage potential, with close attention to local climate conditions. Overall, our meta-analysis will crucially aid forest management and conservation in the context of global environmental changes, and provide novel insights and a scientific reference to lead to future carbon storage research on large scales.

Relationship between plant species diversity and aboveground biomass in alpine grasslands on the Qinghai–Tibet Plateau: Spatial patterns and the factors driving them

Alpine grasslands are important ecosystems on the Qinghai–Tibet Plateau and are extremely sensitive to climate change. However, the spatial responses of plant species diversity and biomass in alpine grasslands to environmental factors under the background of global climate change have not been thoroughly characterized. In this study, a random forest model was constructed using grassland ground monitoring data with satellite remote sensing data and environmental variables to characterize the plant species diversity and aboveground biomass of grasslands in the Three-River Headwaters Region within the Qinghai–Tibet Plateau and analyze spatial variation in the relationship between the plant species diversity and aboveground biomass and their driving factors. The results show that (1) the selection of characteristic variables can effectively improve the accuracy of random forest models. The stepwise regression variable selection method was the most effective approach, with an R2 of 0.60 for the plant species diversity prediction model and 0.55 for the aboveground biomass prediction model, (2) The spatial distribution patterns of the plant species diversity and aboveground biomass in the study area were similar, they were both high in the southeast and low in the northwest and gradually decreased from east to west. The relationship between the plant species diversity and aboveground biomass varied spatially, they were mostly positively correlated (67.63%), but they were negatively correlated in areas with low and high values of plant species diversity and aboveground biomass, and (3) Analysis with geodetector revealed that longitude, average annual precipitation, and elevation were the main factors driving variation in the plant species diversity and aboveground biomass relationship. We characterized plant species diversity and aboveground biomass, as well as their spatial relationships, over a large spatial scale. Our data will aid biodiversity monitoring and grassland conservation management, as well as future studies aimed at clarifying the relationship between biodiversity and ecosystem functions.

Structural and taxonomic diversity predict above‐ground biomass better than functional measures of maximum height in mixed‐species forests

AbstractAims:Mixed‐species forests are known to be highly productive systems because of their high species diversity, including taxonomic diversity (species richness) and structural diversity. Recent empirical evidence also points to plant maximum height, as a functional trait that potentially drives forest above‐ground biomass (AGB). However, the interrelations between these biotic variables are complex, and it is not always predictable if structural diversity attributes or functional metrics of plant maximum height would act as the most important determinant of stand biomass. Here we evaluated the relative importance of structural diversity attributes and functional metrics of plant maximum height (Hmax) in predicting and mediating AGB response to variation in species richness in mixed‐species forests, while also accounting for fine‐scale environmental variation.Location:Northern Benin.Methods:We used forest inventory data from mixed‐species stands of native and exotic species. We quantified structural diversity as coefficient of variation of tree diameter at breast height (CVdbh) and of height (CVHt). For plant Hmax, we computed three metrics: functional range (FRHmax), functional divergence (FDHmax) and community‐weighted mean (CWMHmax). We used topographical variables such as elevation and slope to account for possible environmental effects. Simple and multiple mixed‐effects models, and structural equation models were performed to assess the direct and indirect links of AGB with species richness through structural diversity attributes and functional metrics of plant Hmax.Results:Species richness and CVdbh were positively related to AGB, while functional metrics of plant Hmax were not. Structural equation models revealed that species richness influenced AGB indirectly via CVdbh, which alone strongly promoted AGB. Elevation only had a positive direct effect on AGB. While increasing species richness enhanced CVdbh and functional measures of plant Hmax, there was no support for the latter mediating the effects of species richness on AGB.Conclusion:Structural diversity has a significant advantage in predicting and mediating the positive effect of species richness on AGB more so than functional measures of plant Hmax. We argue that structural diversity acts as a mechanism for the species richness–AGB relationship, and that maintaining high structural diversity would enhance biomass in mixed‐species forests.

Morphological and physiological traits of triticale as affected by drought stress

Triticale (×Triticosecale Wittm.) is a major forage crop of arid and semiarid areas in China with yields much constrained by drought stress. Genetic improvement could benefit from a better understanding of drought effects on plant morphology and physiology. In this study, the morphophysiological traits of four triticale genotypes (line C31, varieties ‘Gannong No.1’, ‘Gannong No.2’, and ‘Shida No.1’) were determined on days 7, 14, 21, 35, 49, and 63 for treatments of the normal irrigation and drought stress, respectively. Rainfall of the drought stress treatments was controlled during the study using an anti-rain shed. Our findings suggest that drought stress had significant effects on all morphophysiological traits except for the relative number of leaves (RL) and catalase activities (RCAT). Among four genotypes, the averaged relative plant height (RH) of ‘Gannong No.2’ (0.90) was the highest, the averaged relative number of tillers (RT) of ‘Gannong No.1’ (0.77) was the highest, the averaged relative aboveground biomass yields (RAB) (0.53), relative leaf water content (RRWC) (0.96), and peroxidase activity (RPOD) (0.92) of C31 were the highest, respectively, and the averaged RCAT (1.06) of ‘Shida No.1’ was the highest. The interaction between genotype and drought stress days was significant for all morphophysiological traits except for the RT and RL. A comprehensive evaluation revealed that C31 was the most drought-tolerant genotype under persistent drought stress. These findings may be useful for the breeding and identification of drought-tolerant germplasms in the arid and semi-arid regions.

Effectiveness of the Reconstructed MODIS Typical-Angle Reflectances on Forest Biomass Estimation

Multi-angle optical reflectance measurements such as those from the NASA moderate resolution imaging spectroradiometer (MODIS) are sensitive to forest 3D structures, potentially serving as a useful proxy to estimate forest structural variables such as aboveground biomass (AGB)—a potential theoretically recognized but rarely explored. In this paper, we examined the effectiveness of the reconstructed MODIS typical-angle reflectances—reflectances observed from the hotspot, darkspot, and nadir directions—for estimating forest AGB from both theoretical and practical perspectives. To gain theoretical insights, we first tested the sensitivities of typical-angle reflectances to forest AGB through simulations using the 4-scale bidirectional reflectance distribution function (BRDF) model. We then built statistical models to fit the relationship between MODIS multi-angle observations and field-measured deciduous-broadleaf/mixed-temperate forest AGB at five sites in the eastern USA, assisted by a semivariogram analysis to determine the effect of pixel heterogeneity on the MODIS–AGB relationship. We also determined the effects of terrain and season on the predictive relationships. Our results indicated that multi-angle reflectances with fewer visible shadows yielded better AGB estimates (hotspot: R2 = 0.63, RMSE = 54.28 Mg/ha; nadir: R2 = 0.55, RMSE = 59.95 Mg/ha; darkspot: R2 = 0.46, RMSE = 65.66 Mg/ha) after filtering out the effects of complex terrain and pixel heterogeneity; the MODIS typical-angle reflectances in the NIR band were the most sensitive to forest AGB. We also found strong sensitivities of estimated accuracies to MODIS image acquisition dates or season. Overall, our results suggest that the current practice of leveraging only single-angle MODIS data can be a suboptimal strategy for AGB estimation. We advocate the use of MODIS multi-angle reflectances for optical remote sensing of forest AGB or potentially other ecological applications requiring forest structure information.

The short-term impacts of soil disturbance on soil microbial community in a degraded Leymus chinensis steppe, North China

The synergy between vegetation and soil is a fundamental driver of ecosystem restoration, yet the short-term impacts of soil disturbance on soil microbes and the relations between vegetation and soil during vegetation recovery remain unclear. We compared the responses of plants, soil physicochemical properties, and microbial communities after seven years of application of soil disturbance techniques (harrowing, HA; shallow ploughing, SP; and natural recovery, NR, the control) in a degraded Leymus chinensis steppe. Our results showed that bacterial community was more stable and did not change significantly under soil disturbance, but the fungal community was more sensitive to soil disturbance and was closely related to soil water content, bulk density, and relative aboveground biomass of dominant plant species. The results of this study suggest that soil disturbance techniques directly (mainly via changes in soil physical properties) and indirectly (mainly via changes in plant community composition) affected soil fungal community composition. Data show that SP largely facilitated the recovery of L. chinensis but decreased plant richness and diversity, resulted in a slower rate of soil microbial and soil quality restoration relative to the other treatments. It is also clear that HA and NR exerted positive effects on the recovery of the plant and soil microbial communities across degraded Leymus chinensis steppe over short timescales. Our results provide scientific guidance for more effective management of degraded grassland, and suggest that above- and belowground communities should be considered to be precise indicators of grassland ecosystem restoration. The long-term effects of soil disturbance techniques on soil microbial communities require further study.

Shifting community composition determines the biodiversity–productivity relationship under increasing precipitation and N deposition

AbstractQuestionsThe relationships between biodiversity and ecosystem functioning (BEF) vary largely across natural ecosystems, with a unimodal, monotonous linear or no relationship. However, it remains unclear how BEF relationships vary under global change. Given future predicted changes in precipitation and nitrogen (N) deposition, it is crucial to determine how precipitation change and N deposition affect grassland biodiversity and productivity, and regulate their relationships.LocationA Dry Mixed‐Grass Prairie of western Canada.MethodsWe established a manipulative field experiment of increased precipitation (water addition with approximately 15% and 30% more monthly precipitation) and N addition (10 g/m2) using a randomized complete block design, including six treatments, each replicated five times (30 plots). We conducted vegetation sampling with a 1 m × 1 m quadrat in each plot from 2016 to 2017, to examine the individual and interactive effects of water and N addition on plant diversity, functional group composition, above‐ and below‐ground productivity, and the diversity–productivity relationships.ResultsWe found a positive linear diversity–above‐ground biomass (AGB) relationship under increased precipitation, which was attributed to the water‐induced increase in the abundance of forbs in the plant community, further promoting the positive effect of plant diversity on AGB. However, N addition caused a negative linear diversity–AGB relationship by increasing AGB and reducing plant diversity. The effects of N on diversity and productivity can be further strengthened under increased precipitation, which was due to the increase of C3rhizomatous grasses with high above‐ and below‐ground biomass and the decrease of forbs with high richness.ConclusionsOur results suggest that changes in functional group composition determine the plant species’ diversity, productivity, and their relationships under increasing precipitation and N deposition, which has significant implications for understanding and modelling ecosystem productivity in the context of global change.

Assessment of linear relationships between TanDEM-X coherence and canopy height as well as aboveground biomass in tropical forests

ABSTRACT Information about the forest structure attributes like canopy height and aboveground biomass (AGB) are crucial for forest monitoring systems and in the assessment of the global carbon cycle. The globally available TerraSAR-X add-on for Digital Elevation Measurement (TanDEM-X) data are a potential data source for estimating canopy height and AGB. Several empirical and semi-empirical investigations have indicated a linear relationship between X-band coherence and canopy height as well as AGB. The generality of this relationship is to date underexplored. In this study, the volume coherence of bistatic TanDEM-X acquisitions was retrieved and linearly related to canopy height and AGB in different tropical study areas to assess the generality of their relationship. Airborne light detection and ranging (LiDAR) data were also used to complement the estimation of canopy height and AGB with the X-band volume coherence. The results indicated that the linear function provides a statistically significant fit to the observed relationship between coherence and canopy height as well as AGB. The estimation of canopy height with this linear relationship resulted in a coefficient of determination R 2 of 0.72 and a root mean square error (RMSE) of 6.4 m (15.7%), where the AGB estimation had a decreased accuracy with an R 2 of 0.59 and RMSE of 88.2 t ha−1 (21%). The estimation where the LiDAR (light detection and ranging)-based AGB relationship and coherence was combined revealed generally similar accuracies compared to the coherence alone. This confirms that the TanDEM-X coherence can support the consistent estimation of canopy height and AGB, where it provides as a minimum a source for a stratification to assess the spatial distribution of qualitative AGB classes.

Biodiversity, environmental context and structural attributes as drivers of aboveground biomass in shrublands at the middle and lower reaches of the Yellow River basin

Biodiversity–biomass relationships have been debated for decades and remain subject to controversy. Understanding the relationship between biodiversity and biomass will be crucial for soil and water conservation of the whole basin of the Yellow River. The positive effects of biodiversity on aboveground biomass are altered via two fundamental mechanisms—niche complementarity and selection effects—and are modulated by environmental context and community structure in natural communities. Most studies of biodiversity–biomass relationships have focused on grasslands and forests, rather than on shrublands. We combine multiple biotic variables (biodiversity, functional identity and community structural attributes) and environmental context with aboveground biomass across shrubland habitat types (temperate hilly, temperate montane and subtropical montane) at neighbourhood and community spatial scales, to evaluate the effects of these factors on shrubland aboveground biomass, in the Yellow River basin. We found aboveground biomass was influenced primarily by the community-weighted mean plant maximum height, followed by species richness and community-weighted mean specific leaf area. Furthermore, individual plant size inequality, mean annual precipitation and water availability either directly or indirectly influenced aboveground biomass. The biodiversity–aboveground biomass relationship was stronger at the broader spatial scale. Thus, our findings indicate that both niche complementarity and selection effects shape the effects of biodiversity on shrubland aboveground biomass, although selection effects are more important. Moreover, they indicate that water is the most important environmental factor for determining aboveground biomass, and suggest that community structure and spatial scale could influence shrubland aboveground biomass and its response to biodiversity.

Leaf Multi-Element Network Reveals the Change of Species Dominance Under Nitrogen Deposition.

Elements are important functional traits reflecting plant response to climate change. Multiple elements work jointly in plant physiology. Although a large number of studies have focused on the variation and allocation of multiple elements in plants, it remains unclear how these elements co-vary to adapt to environmental change. We proposed a novel concept of the multi-element network including the mutual effects between element concentrations to more effectively explore the alterations in response to long-term nitrogen (N) deposition. Leaf multi-element networks were constructed with 18 elements (i.e., six macronutrients, six micronutrients, and six trace elements) in this study. Multi-element networks were species-specific, being effectively discriminated irrespective of N deposition level. Different sensitive elements and interactions to N addition were found in different species, mainly concentrating on N, Ca, Mg, Mn, Li, Sr, Ba, and their related stoichiometry. Interestingly, high plasticity of multi-element network increased or maintained relative aboveground biomass (species dominance) in community under simulated N deposition, which developed the multi-element network hypothesis. In summary, multi-element networks provide a novel approach for exploring the adaptation strategies of plants and to better predict the change of species dominance under altering nutrient availability or environmental stress associated with future global climate change.

Climate regulates the functional traits – aboveground biomass relationships at a community-level in forests: A global meta-analysis

The relationships between plant functional traits and aboveground biomass (AGB) stock have been explored across forest biomes. Yet, meta-analyses synthesizing our understanding regarding the influences of climate and soil on the functional traits – AGB relationships at a community-level in global forests are still unavailable. Here, we evaluated the latitudinal gradient in the functional traits –AGB relationships in forests, including functional trait diversity (FTD) – AGB (FTD-AGB), community-weighted mean (CWM) of conservative traits (CWMCT-AGB), CWM of acquisitive traits (CWMAT-AGB), and CWM of plant maximum height or diameter (FunDom-AGB), and then answer the question whether climate and soil conditions modulate the functional traits – AGB relationships in global forests. To do so, we selected those studies which reported the relationships of FTD and CWM with AGB stock (i.e. in Mg ha−1) rather with AGB productivity or growth (i.e. Mg ha−1 yr−1) at a community-level (i.e. forest plot). By using piecewise structural equation meta-modeling, we found that: (1) functional traits – AGB relationships at a community-level were driven by mean annual temperature (MAT), aridity and soil fertility. (2) Higher MAT and low aridity promoted FTD-AGB relationships but the opposite trend was true for CWMCT-AGB, whereas higher MAT promoted CWMAT-AGB and FunDom-AGB at high aridity levels. (3) The FunDom-AGB relationship increased with increasing the number of forest plots but other relationships declined. (4) The negligible or negative FTD-AGB relationships but the positive AGB-FunDom relationships were conspicuous across global forests, indicating the mass ratio effect in terms of functional dominance. Our meta-analysis suggests that functional dominance and conservative species' strategy in relation to favorable abiotic conditions should be promoted to increase AGB stock under global environmental changes.

Assessment of Leaf Area Index Models Using Harmonized Landsat and Sentinel-2 Surface Reflectance Data over a Semi-Arid Irrigated Landscape

Leaf area index (LAI) is an essential indicator of crop development and growth. For many agricultural applications, satellite-based LAI estimates at the farm-level often require near-daily imagery at medium to high spatial resolution. The combination of data from different ongoing satellite missions, Sentinel 2 (ESA) and Landsat 8 (NASA), provides this opportunity. In this study, we evaluated the leaf area index generated from three methods, namely, existing vegetation index (VI) relationships applied to Harmonized Landsat-8 and Sentinel-2 (HLS) surface reflectance produced by NASA, the SNAP biophysical model, and the THEIA L2A surface reflectance products from Sentinel-2. The intercomparison was conducted over the agricultural scheme in Bekaa (Lebanon) using a large set of in-field LAIs and other biophysical measurements collected in a wide variety of canopy structures during the 2018 and 2019 growing seasons. The major studied crops include herbs (e.g., cannabis: Cannabis sativa, mint: Mentha, and others), potato (Solanum tuberosum), and vegetables (e.g., bean: Phaseolus vulgaris, cabbage: Brassica oleracea, carrot: Daucus carota subsp. sativus, and others). Additionally, crop-specific height and above-ground biomass relationships with LAIs were investigated. Results show that of the empirical VI relationships tested, the EVI2-based HLS models statistically performed the best, specifically, the LAI models originally developed for wheat (RMSE:1.27), maize (RMSE:1.34), and row crops (RMSE:1.38). LAI derived through European Space Agency’s (ESA) Sentinel Application Platform (SNAP) biophysical processor underestimated LAI and provided less accurate estimates (RMSE of 1.72). Additionally, the S2 SeLI LAI algorithm (from SNAP biophysical processor) produced an acceptable accuracy level compared to HLS-EVI2 models (RMSE of 1.38) but with significant underestimation at high LAI values. Our findings show that the LAI-VI relationship, in general, is crop-specific with both linear and non-linear regression forms. Among the examined indices, EVI2 outperformed other vegetation indices when all crops were combined, and therefore it can be identified as an index that is best suited for a unified algorithm for crops in semi-arid irrigated regions with heterogeneous landscapes. Furthermore, our analysis shows that the observed height-LAI relationship is crop-specific and essentially linear with an R2 value of 0.82 for potato, 0.79 for wheat, and 0.50 for both cannabis and tobacco. The ability of the linear regression to estimate the fresh and dry above-ground biomass of potato from both observed height and LAI was reasonable, yielding R2: ~0.60.

Critical nitrogen dilution curves and nitrogen nutrition diagnosis of spring maize under different precipitation patterns in Weibei dryland

<p indent=0mm>The excessive nitrogen (N) applications, large rainfall variations and poor water-nitrogen couplings are main problems to efficient nitrogen fertilizer uses in spring maize production of Weibei dryland. Critical nitrogen dilution curves under different rainfall scenarios in Weibei dryland were constructed in this study to analyze the feasibilities of diagnosing and evaluating nitrogen nutritional conditions in terms of nitrogen nutrition index (NNI), which would provide a theoretical basis for reasonable nitrogen fertilizations application of dryland maize in response to different rainfalls. The experiment design using Zhengdan 958 (ZD958) and Shaandan 8806 (SD8806) as tested materials was five treatments level, N applied at 0(N0), 75(N1), 150(N2), 270(N3), and 360(N4) kg hm^–2 in 2016 and 2017, and at 0(N0), 90(N0), 180(N2), 270(N3), and 360(N4) kg hm^–2 in 2018 and 2019, respectively. It was rainy at the ear stage and dry at the grain stage in 2016 and 2018, whereas dry at the ear stage and rainy at the grain stage in 2017 and 2019. Critical nitrogen dilution curve models for spring maize with two precipitation patterns were constructed and verified using the data collected in the four-year position nitrogen fertilization experiment. The results showed that: (1) increased nitrogen fertilizer application significantly increased aboveground biomass and plant N concentrations, and there were significantly different among different treatments. Both critical nitrogen concentrations (<italic>N</italic>_c) and aboveground biomass conformed the exponential relations with the two precipitation patterns, but there were differences between the parameters of the models for these relations (a. Rainy at the ear stage: <italic>N</italic>_c = 35.98DM^–0.35; b. Dry at the ear stage: <italic>N</italic>_c = 35.04DM^–0.23). The relatively stable model had a linear correlation between the fitted and actual plant N concentrations, which shown that the RMSE and <italic>n</italic>–RMSE were 1.03 and 5.75% at the ear stage over the rainy years and 1.53 and 6.78% at the ear stage in the dry years, respectively. (2) at the different growth stages, NNI were increased with the increased application, and there were differences in the optimal nitrogen application under different precipitation conditions. The optimum N rate in the form of basal fertilizers was <sc>150–180 kg</sc> hm^–2, and in the form of top dressing fertilizers was <sc>45–75 kg</sc> hm^–2 at the ear stage in the rainy years. The nitrogen nutrition index (NNI) was significantly correlated with relative nitrogen uptake (RN_upt), as were relative aboveground biomass (RDW) and relative yield (RY). When the NNI was 1.02 at the ear stage in the rainy years, the maximum RY was 0.95; and when the NNI was 1.08 at the ear stage in the dry years, the maximum RY was 0.92. The critical nitrogen dilution curve model and nitrogen nutrition index model constructed in this study were able to accurately predict nitrogen nutrition conditions from jointing stage to maturity stage under the two precipitation patterns of spring maize. They would provide an important guidance for nitrogen diagnosis and fertilization application in maize growing stage.

The Variation Driven by Differences between Species and between Sites in Allometric Biomass Models

Background and Objectives: It is commonly assumed that allometric biomass models are species-specific and site-specific. However, the magnitude of species and site dependency in these models is not well-known. This study aims to investigate the variation in allometric models (i.e., aboveground biomass predicted by diameter at breast height and tree height) that has originated from the differences between tree species and between sites, thereby contributing to a better understanding of species and site-specificity issue in these models. Materials and Methods: The study is based on two large biomass datasets of 4921 and 5199 trees, from Eurasia and Canada. Using a nested ANOVA model on relative aboveground biomass residuals (with species and site as random effects), the proportion of variance explained by species or site was assessed by means of Variance Partition Coefficient (VPC). Results: The proportion of variance explained by species (VPCspecies = 42.56%, SE = 6.10% for Dataset 1 and VPCspecies = 47.54%, SE = 6.07% for Dataset 2) was larger than that explained by site (VPCsite = 20.08%, SE = 3.35% for Dataset 1 and VPCsite = 8.27%, SE = 1.38% for Dataset 2). The proportion of variance explained by site decreased by 24%–44% and the proportion of variance explained by species changed only slightly, when height is included in the allometric biomass models (i.e., models based on diameter at breast height alone, compared to models based on diameter at breast height and tree height). Conclusions: Allometric biomass models were more species-specific than they were site-specific. Therefore, the species (i.e., differences between species) seems to be a more important driver of variability in allometric models compared to site (i.e., differences between sites). Including height in allometric biomass models helped reduce the dependency of these models, on sites only.

Root trait-mediated belowground competition and community composition of a temperate steppe under nitrogen enrichment

Shifts of plant community composition with enhanced atmospheric nitrogen (N) deposition in grasslands have occurred globally. Despite extensive studies on the effects of enhanced N deposition on plant species composition of grassland community, few studies have focused on belowground ecological processes and duration of N addition. In situ long-term (14-year: 2004–2017) and short-term (4-year: 2014–2017) N-addition experiments in the same sites were conducted in a temperate steppe of northern China. We investigated the effects of N-addition on plant community composition and root traits by comparing results of short-term and long-term N addition. Nitrogen-evoked changes in plant community composition were primarily dependent on N-addition duration and functional groups. Short-term N addition favored growth of grasses, and depressed growth of forbs, while long-term N addition favored growth of sedges, and concurrently depressed growth of grasses and forbs, ultimately leading to a time-dependent shift of plant community composition from co-dominance by grasses and forbs to dominance by grasses, then to dominance by sedges. Similar to the observed aboveground biomass, short-term N addition led to an increase in the relative belowground biomass (the proportion of belowground biomass of individual plant to community belowground biomass) of the grass Stipa krylovii and a decrease in the relative belowground biomass of the forb Artemisia frigida, respectively. In contrast, long-term N addition enhanced the relative belowground biomass of the sedge Carex korshinskyi, and reduced the relative belowground biomass of the grass S. krylovii and the forb A. frigida. Moreover, traits of absorptive fine roots (first-two orders) in the three species (grass: S. krylovii; forb: A. frigida; sedge: C. korshinskyi) that are representatives of three functional groups differed in their responses to short-term and long-term N addition, thus rendering them differentially competitive for acquisition of belowground resource. The changes in root traits of the three species in responses to N addition of varying duration were associated with their relative aboveground biomass. Root traits play important roles in mediating the competition for belowground resource and changes in plant community composition of temperate grasslands under N enrichment. Our findings provide novel insights into N-deposition-induced changes in steppe community composition by linking root traits of functional groups and duration of N addition.

Relative performance of co-occurring alien plant invaders depends on traits related to competitive ability more than niche differences

Although conservation managers usually have to deal with multiple invaders that co-occur in native ecosystems, research to date has concentrated on the study of single highly invasive species. Consequently, this study aims to better understand the interactions among co-occurring alien plants. Specifically, I aim to determine how relative performance in mixture (compared to monoculture) depends on phylogenetic relatedness and similarity in functional traits. I investigated interactions among 18 alien annual plant species in Germany from six families in a multi-species common garden experiment, where plant individuals were grown in all pairwise species combinations. I measured growth, reproductive output and functional traits of the species, and determined phylogenetic and multivariate trait distances (representing niche differences) and individual trait hierarchies (representing average fitness differences that determine competitive superiority) between pairs. Across the 153 interspecific species combinations, individuals equally often experienced higher intraspecific or interspecific competition, with competitive responses varying greatly depending on species. Hierarchical differences in individual traits affected growth and seed production: being taller, having larger seed mass and higher specific leaf area benefitted relative performance of alien species when co-occurring with other aliens. Multivariate trait distance also had a positive effect on relative aboveground biomass production in mixture. Overall, hierarchical trait differences related to competitive ability appear to be more important than niche differences in determining performance for co-occurring alien plants. A better understanding on interaction type and strength among multiple plant invaders is crucial to determine appropriate management actions and contributes to ecological theory of community assembly.