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Background and aims Rumex alpinus is a native plant in the mountains of Europe whose distribution has partly been affected by its utilization as a vegetable and medicinal herb. The distribution of micro and risk elements in its organs is not well-known. The study examined the safety of consuming R. alpinus from the Krkonoše Mountains, the Czech Republic, and the Alps (Austria and Italy). Methods We determined the total and plant-available content of Fe, Zn, Cu, Mn, Al, As, Cr, Ni, Pb, and Cd in the soil and the total content in organs of R. alpinus. Results The uptake and distribution of elements by plants were characterized by bioaccumulation (BF) and translocation (TF) factors. The level of elements accumulation by R. alpinus is considerably different, depending on local geological substrates and environmental conditions. Rumex alpinus has considerable tolerance to Zn, Cu, As, Cr, Ni, with an easy accumulation strategy. High Al and Cd content in belowground biomass (rhizome) indicate a defensive mechanism for them. Although the aboveground biomass (emerging, senescent, mature leaves, petiole) has some degree of accumulation of risk elements, the results showed that R. alpinus is an excluder. Conclusion Rumex alpinus does not accumulate risk elements in organs (leaf and petiole) that are consumed based on the permissible limit according to World Health Organization ( 2001 ) and can therefore be used without concern. Caution must, therefore, be taken when consuming these plant parts in heavily contaminated soils.

In terrestrial ecosystems, atmospheric nitrogen (N) deposition has greatly increased N availability relative to other elements, particularly phosphorus (P). Alterations in the availability of N relative to P can affect plant growth rate and functional traits, as well as resource allocation to above‐ versus belowground biomass (MA and MB). Biomass allocation among individual plants is broadly size‐dependent, and this can often be described as an allometric relationship between MA and MB, as represented by the equation MA=αMBβ, or log MA = logα + βlog MB. Here, we investigated whether the scaling exponent or regression slope may be affected by the N:P supply ratio. We hypothesized that the regression slope between MA and MB should be steeper under a high N:P supply ratio due to P limitation, and shallower under a low N:P supply ratio due to N limitation. To test these hypotheses, we experimentally altered the levels of N, P, and the N:P supply ratio (from 1.7:1 to 135:1) provided to five alpine species representing two functional groups (grasses and composite forbs) under greenhouse conditions; we then measured the effects of these treatments on plant morphology and tissue content (SLA, leaf area, and leaf and root N/P concentrations) and on the scaling relationship between MA and MB. Unbalanced N:P supply ratios generally negatively affected plant biomass, leaf area, and tissue nutrient concentration in both grasses and composite forbs. High N:P ratios increased tissue N:P ratios in both functional groups, but more in the two composite forbs than in the grasses. The positive regression slopes between log MA and log MB exhibited by plants raised under a N:P supply ratio of 135:1 were significantly steeper than those observed under the N:P ratio of 1.7:1 and 15:1. Synthesis: Plant biomass allocation is highly plastic in response to variation in the N:P supply ratio. Studies of resource allocation of individual plants should focus on the effects of nutrient ratios as well as the availability of individual elements. The two forb species were more sensitive than grasses to unbalanced N:P supplies. To evaluate the adaptive significance of this plasticity, the effects of unbalanced N:P supply ratio on individual lifetime fitness must be measured. Alterations in the availability of N relative to P can affect plant growth rate and functional traits, as well as resource allocation to above‐ versus belowground biomass. We found plant biomass allocation is highly plastic in response to variation in the N:P supply ratio. Studies of resource allocation of individual plants should focus on the effects of nutrient ratios as well as the availability of individual elements.

Forest biomass allocation is a direct manifestation of biological adaptation to environmental changes. Studying the distribution patterns of forest biomass along elevational gradients is ecologically significant for understanding the specific impacts of global change on plant resource allocation strategies. While aboveground biomass has been extensively studied, research on belowground biomass remains relatively limited. Furthermore, the patterns and driving factors of the belowground biomass proportion (BGBP) along elevational gradients are still unclear. In this study, we investigated the specific influences of climatic factors, soil nutrients, and key leaf traits on the elevational pattern of BGBP using data from 926 forests at 94 sites across China. In this study, BGBP data were calculated from the root biomass to the depth of 50 cm. Our findings indicate considerable variability in forest BGBP at a macro scale, showing a significant increasing trend along elevational gradients (p < 0.01). BGBP significantly decreases with increasing temperature and precipitation and increases with annual mean evapotranspiration (MAE) (p < 0.01). It decreases significantly with increasing soil phosphorus content and increases with soil pH (p < 0.01). Key leaf traits (leaf nitrogen (LN) and leaf phosphorus (LP)) are positively correlated with BGBP. Climatic factors (R2 = 0.46) have the strongest explanatory power for the variation in BGBP along elevations, while soil factors (R2 = 0.10) and key leaf traits (R2 = 0.08) also play significant roles. Elevation impacts BGBP directly and also indirectly through influencing such as climate conditions, soil nutrient availability, and key leaf traits, with direct effects being more pronounced than indirect effects. This study reveals the patterns and controlling factors of forests’ BGBP along elevational gradients, providing vital ecological insights into the impact of global change on plant resource allocation strategies and offering scientific guidance for ecosystem management and conservation.

Global warming has caused changes in the area and thickness of permafrost on the Qinghai-Tibet Plateau and prompted the transition from permafrost to seasonally frozen soil, which has affected the soil moisture, soil temperature, and distribution of plant roots. This, in turn, affects grassland vegetation productivity and aboveground/belowground biomass. In this study, we took Qinghai Province in the northeastern Qinghai-Tibet Plateau as the research area to model the spatial pattern of grassland biomass and then evaluated the potential influence of frozen soil type information on aboveground and belowground biomass. Our research shows that there are significantly more biomass observations in seasonally frozen soil regions than in permafrost regions. However, when we ignore the type of frozen soil, the model does not show more accurate simulation in seasonally frozen soil regions, mainly because the stronger correlation between permafrost biomass and environmental factors, such as precipitation, compensates for the lack of observational data. In addition, we found that the biomass estimation error can be reduced significantly by building different models for each type of frozen soil, which implies that the type of frozen soil has an important impact on grassland biomass. Therefore, in considering the effects of future climate warming, more attention should be given to the impact of changes in frozen soil type on regional vegetation productivity. In addition, our investigation contributes a benchmark dataset of above- and belowground vegetation carbon storage in different frozen soil types, which provides the research community with useful information for optimizing process-based carbon cycle models.

Biomass is a direct reflection of community productivity, and the allocation of aboveground and belowground biomass is a survival strategy formed by the long-term adaptation of plants to environmental changes. However, under global changes, the patterns of aboveground–belowground biomass allocations and their controlling factors in different types of grasslands are still unclear. Based on the biomass data of 182 grasslands, including 17 alpine meadows (AMs) and 21 desert steppes (DSs), this study investigates the spatial distribution of the belowground biomass allocation proportion (BGBP) in different types of grasslands and their main controlling factors. The research results show that the BGBP of AMs is significantly higher than that of DSs (p < 0.05). The BGBP of AMs significantly decreases with increasing mean annual temperature (MAT) and mean annual precipitation (MAP) (p < 0.05), while it significantly increases with increasing soil nitrogen content (N), soil phosphorus content (P), and soil pH (p < 0.05). The BGBP of DSs significantly decreases with increasing MAP (p < 0.05), while it significantly increases with increasing soil phosphorus content (P) and soil pH (p < 0.05). The random forest model indicates that soil pH is the most important factor affecting the BGBP of both AMs and DSs. Climate-related factors were identified as key drivers shaping the spatial distribution patterns of BGBP by exerting an influence on soil nutrient availability. Climate and soil factors exert influences not only on grassland biomass allocation directly, but also indirectly by impacting the availability of soil nutrients.

Aboveground biomass (AGB) and belowground biomass (BGB) allocation and productivity–richness relationship are controversial. Here, we assessed AGB and BGB allocation and the productivity–richness relationship at community level across four grassland types based on the biomass data collected from 80 sites across the Qinghai Plateau during 2011–2012. The reduced major axis regression and general linear models were used and showed that (a) the median values of AGB were significantly higher in alpine meadow than in other three grassland types; the ratio of root to shoot (R/S) was significantly higher in desert grassland (36.06) than intemperate grassland (16.60), alpine meadow (13.35), and meadow steppe (19.46). The temperate grassland had deeper root distribution than the other three grasslands, with about 91.45% roots distributed in the top 30 cm soil layer. (b) The slopes between log AGB and log BGB in the temperate grassland and meadow steppe were 1.09 and 1, respectively, whereas that in the desert grassland was 1.12, which was significantly different from the isometric allocation relationship. A competitive relationship between AGB and BGB was observed in the alpine meadow with a slope of −1.83, indicating a trade‐off between AGB and BGB in the alpine meadow. (c) A positive productivity–richness relationship existed across the four grassland types, suggesting that the positive productivity–richness relationship might not be affected by the environmental factors at the plant location. Our results provide a new insight for biomass allocation and biodiversity–ecosystem functioning research. The median values of aboveground biomass (AGB) were significantly higher in alpine meadow than in other three grassland types. The temperate grassland had deeper root distribution than the other three grasslands, with about 91.45% roots distributed in the top 30 cm soil layer. A positive productivity–richness relationship existed across the four grassland types.

BackgroundThe occurrence of climate change at an unprecedented scale has resulted in alterations of ecosystems around the world. Numerous studies have reported on the potential to slow down climate change through the sequestration of carbon in soil and trees. Freshwater wetlands hold significant potential for climate change mitigation owing to their large capacity to sequester atmospheric carbon dioxide (CO2). Wetlands among all terrestrial ecosystems have the highest carbon density and are found to store up to three to five times more carbon than terrestrial forests. The current study was undertaken to quantify carbon stocks of two carbon pools: aboveground biomass (AGB) and belowground biomass (BGB). Chosen study sites; Kolonnawa wetland and Thalawathugoda wetland park are distributed within the Colombo wetland complex. Colombo was recognized as one of the 18 global Ramsar wetland cities in 2018. A combination of field measurements and allometric tree biomass regression models was used in the study. Stratification of the project area was performed using the normalized difference vegetation index (NDVI).ResultsThe AGB carbon stock, across strata, is estimated to be in the range of 13.79 ± 3.65–66.49 ± 6.70 tC/ha and 8.13 ± 2.42–52.63 ± 10.00 tC/ha at Kolonnawa wetland and Thalawathugoda wetland park, respectively. The BGB carbon stock is estimated to be in the range of 2.47 ± 0.61–10.12 ± 0.89 tC/ha and 1.56 ± 0.41–8.17 ± 1.39 tC/ha at Kolonnawa wetland and Thalawathugoda wetland park, respectively. The total AGB carbon stock of Kolonnawa wetland was estimated at 19,803 ± 1566 tCO2eq and that of Thalawathugoda wetland park was estimated at 4180 ± 729 tCO2eq.ConclusionsIn conclusion, the study reveals that tropical freshwater wetlands contain considerable potential as carbon reservoirs. The study suggests the use of tropical freshwater wetlands in carbon sequestration enhancement plans in the tropics. The study also shows that Annona glabra, an invasive alien species (IAS), has the potential to enhance the net sink of AGB carbon in these non-mangrove wetlands. However, further studies are essential to confirm if enhanced carbon sequestration by Annona glabra is among the unexplored and unreported benefits of the species.

Current models for oak species could not accurately estimate biomass in northeastern China, since they are usually restricted to Mongolian oak (Quercus mongolica Fisch. ex Ledeb.) on local sites, and specifically, no biomass models are available for Liaodong oak (Quercuswutaishanica Mayr). The goal of this study was, therefore, to develop generic biomass models for both oak species on a large scale and evaluate the biomass allocation patterns within tree components. A total of 159 sample trees consisting of 120 Mongolian oak and 39 Liaodong oak were harvested and measured for wood (inside bark), bark, branch and foliage biomass. To account for the belowground biomass, 53 root systems were excavated following the aboveground harvest. The share of biomass allocated to different components was assessed by calculating the ratios. An aboveground additive system of biomass models and belowground equations were fitted based on predictors considering diameter (D), tree height (H), crown width (CW) and crown length (CL). Model parameters were estimated by jointly fitting the total and the components’ equations using the weighted nonlinear seemingly unrelated regression method. A leave-one-out cross-validation procedure was used to evaluate the predictive ability. The results revealed that stem biomass accounts for about two-thirds of the aboveground biomass. The ratio of wood biomass holds constant and that of branches increases with increasing D, H, CW and CL, while a reverse trend was found for bark and foliage. The root-to-shoot ratio nonlinearly decreased with D, ranging from 1.06 to 0.11. Tree diameter proved to be a good predictor, especially for root biomass. Tree height is more prominent than crown size for improving stem biomass models, yet it puts negative effects on crown biomass models with non-significant coefficients. Crown width could help improve the fitting results of the branch and foliage biomass models. We conclude that the selected generic biomass models for Mongolian oak and Liaodong oak will vigorously promote the accuracy of biomass estimation.

Soil fungi are a major factor maintaining plant diversity and productivity, but the underlying mechanisms are still poorly understood. Based on a biodiversity–ecosystem functioning experiment in southeast China, we evaluated the impacts of root-associated soil fungi on plant total, above- and belowground biomass production in monocultures and in different 2- and 4-tree species mixtures using two pools of four subtropical tree species each. All plots were inoculated with forest soil but half of the plots were additionally treated with fungicide to suppress fungi. Tree species richness promoted individual biomass only in control but not in fungicide-treated soils, leading to positive relative yield totals (RYTs, sum of the relative growth of each tree species in mixture to monoculture) of mixed species plots in control soils. Additive partitioning analysis showed that the net biodiversity effects were due to positive complementarity effects (CE) rather than selection effects. The relative yield of individual tree species was positively correlated with arbuscular mycorrhizal (AM) colonization for AM trees but not significantly correlated with ectomycorrhizal (EM) colonization for EM trees. The molecular analysis of the root-associated fungi showed that larger RYT and CE values were correlated with greater dissimilarity in pathogenic fungal communities between tree species, suggesting distinct pathogen compositions will result in overyielding and high complementarity in mixture.

IntroductionTrees on agricultural landscape play a vital role in ecosystem services including food security that supports human livelihood. They can further offer synergy between adaptation and mitigation in addressing climate change impact. Understanding aboveground tree biomass and soil organic carbon stocks along the altitudinal gradient provide opportunities for better management of the carbon pools. However, little is known on how altitudinal gradient influences on carbon stock of woody biomass and soil of scattered trees on farmland, particularly in a dry area.MethodsThe study area were stratified in to five class (500–1000, 1000–1500, 1500–2000, 2000–2500, and 2500–3000 m a.s.l). Quadrats (100 m × 50 m) were randomly selected from each of stratified altitudinal gradients. At every sampling point, one composite soil sample was taken at 60 cm soil depth for soil organic carbon analysis. For the purpose of woody biomass estimation, allometric equations developed for a similar area were used. Finally, aboveground biomass carbon (AGC), belowground biomass carbon (BGC), soil organic carbon (SOC), and total carbon stock (TC) status were estimated and variables were compared using one-way analysis of variance (ANOVA).ResultsThe result indicated that AGC, BGC, SOC, and TC varied significantly (p < 0.05) along with an altitudinal gradient. The upper altitude (2500–3000 m a.s.l) AGC, BGC, SOC, and TC stock was estimated as 17.97 Mg C ha−1, 6.53 Mg C ha−1, 23.09 Mg C ha−1, 47.59 Mg C ha−1 respectively, and significantly higher than the other altitudinal gradient.ConclusionsWe conclude that scattered trees on farmland hold a high potential of carbon storage which may greatly contribute to the climate resilience green economy strategy and their conservation should be promoted.