Variation In Biomass Research Articles

Different climate conditions drive variations in gross primary productivity and woody biomass accumulation in a temperate and a boreal conifer forest in Canada

Understanding the complex relationships between climate, forest carbon (C) uptake and biomass growth has become a research priority, crucial for assessing the climate change impacts on forest C sequestration. Such associations are expected to vary across biomes, due to different climate constraints on tree physiology. However, our understanding of the seasonal dynamics of long-term C sequestration and how climate influences them in different forest biomes is still limited.We investigated a boreal Pinus banksiana forest (Old Jack Pine, OJP) and a temperate Pinus strobus plantation (Turkey Point, TP39) in Canada. We aimed to assess the link between C uptake and above-ground woody biomass growth, and the effects of climate inter-annual variability on them. We used daily records of climate and gross primary productivity (GPP, period 1999–2019 at OJP and 2003–2018 at TP39), and investigated xylem biomass proxies at cell (cell wall area) and tree-ring level (ring wall area) from 1970 to 2019 at OJP, and from 1970 to 2018 at TP39.In both forests, the direct link between C sink and C source was revealed by the common inter-annual variability of GPP and xylem biomass. GPP and xylem biomass were mostly influenced by spring and late summer temperature at OJP. However, at both sites, summer drought negatively influenced GPP, and biomass growth especially in recent decades. Analysis of dry and cold years evidenced short-term negative effects of low temperature on GPP and xylem biomass in OJP, and of drought in TP39.Long-term intra-annual analyses are crucial to assess the variable effects of climate on forest C cycle. Warm spring and autumn can benefit both GPP and biomass growth, but even in the boreal forest, summer drought has negative impacts. Increasing dry spells, especially in the temperate site, could reduce future forest capacity to uptake C and fix it in wood biomass.

Local and General Patterns of Terrestrial Water‐Carbon Coupling

AbstractTerrestrial carbon uptake and water availability have coupled feedbacks; specifically water uptake for plant growth and soil drying via transpiration. While we might expect this coupling over time at arid sites, climatic water availability also widely covaries geographically with biomass variables that control photosynthetic rates. Using eddy covariance data globally, we find convex, positively‐covarying relations between carbon uptake and a turbulent flux metric controlled by land surface moisture (r = 0.73 monthly across sites) at the site level. We estimate a general, empirical relationship based on site‐wise water‐carbon dynamics. Most sites, and the general relationship, show strong power‐law dependence, implicating the role of sub‐seasonal land‐cover dynamics. We also find that long‐term mean carbon/water states follow a similar convex relationship to the site‐specific temporal dynamics. We discuss opportunities and caveats for space‐for‐time frameworks of carbon/water feedback processes globally.

Design, economic analysis, and environmental assessment of an innovative municipal solid waste-based multigeneration system integrating LNG cold utilization and seawater desalination

This paper presents a novel integrated solution for harnessing energy from biomass alongside liquefied natural gas cooling. The process is investigated and evaluated in various scenarios. This integrated system yields electricity, hydrogen, cold water, hot water, and fresh water. Thermodynamic analysis of the process is conducted under different scenarios. Moreover, the overall environmental damage effectiveness factor is calculated using exergo-environmental evaluation, revealing that heat exchanger E-103 exhibits the highest effectiveness factor of environmental damage, with an exergy efficiency of 37.3 %. Simulation results indicate an overall energy efficiency and overall exergy efficiency of 58.24 % and 31.97 %, respectively. Energy efficiencies of the process are found to be 32.15 %, 34.85 %, 36.71 %, and 58.24 % in single generation, combined heat and power, combined cooling, heating, and power, and multi-generation scenarios, respectively. The study evaluates the simultaneous effects of pressure and flow rate variations of liquefied natural gas fluid, input flow rate variations of municipal solid waste biomass, and cyclohexane working fluid pressure variations in the organic Rankine cycle on other variables. Finally, an economic evaluation of the new process outlines its annual cost and the levelized energy cost parameter under base design conditions, which amount to 9,383,042 $ and 0.092 $/kWh, respectively.

Soil macrofauna diversity and biomass associated with the “fertility islands” beneath oak trees in a semi-arid woodland

Fertility islands are patches of soil beneath the trees and shrub's canopy and contain higher nutrient availability and water content than the surrounding areas in arid and semi-arid lands. Fertility islands are home to various soil organisms that play a crucial role in nutrient cycling. This study aimed to determine the influence of fertility islands beneath the coppiced oak trees on soil macrofauna diversity and biomass in semi-arid oak woodland. For this purpose, two main microhabitats, including beneath the patches of oak sprout-clumps (BPSC) and the interspaces (SBSC), were considered. Each microhabitat was divided into four classes with respect to the number of sprouts per sprout-clumps (N = 1–3, N = 3–10, N = 10–20, and N > 20) and distance gradient from the canopy (D = 0 m, D = 1–3 m, D = 3–5 m, and D > 5 m). Soil physical and chemical properties, soil macrofauna taxonomic group diversity, and biomass were measured for each microhabitat class. Most of the soil's physical and chemical properties, such as soil litter, soil organic carbon (SOC), available phosphorus (P), moisture content, and electrical conductivity (EC), were higher in BPSC than in SBSC. These properties were influenced by the structure (number of sprouts) of oak sprout-clumps and the distance gradient from the canopy. Soil macrofauna individuals (density), biomass, and diversity were higher in BPSC than in SBSC. A significant difference in soil macrofauna groups composition was found only at the canopy edge and was not affected by increasing distance from the canopy. The soil macrofauna diversity was positively correlated with soil moisture, SOC, and P. It was concluded that the sprout-clumps' structure influences the quality of fertility islands beneath the oak sprout-clumps and consequently dictates the variation of soil macrofauna composition and biomass.

Spatial distribution patterns and drivers of above- and below- biomass in Chinese terrestrial ecosystems

Unraveling the dynamics of the global carbon cycle and assessing the sustainability of terrestrial ecosystems are critically dependent on a comprehensive understanding of vegetation biomass. This exploration delves into the pivotal role of biomass within vegetation communities, emphasizing its impact on ecosystem health, productivity, and community structure development. These insights are invaluable for advancing ecological science and conservation efforts. The synthesis of aboveground (AGB) and belowground (BGB) biomass data from 4485 and 3442 locations across China, respectively, collates a wide range of published sources. Integrating this extensive dataset with environmental parameters and applying advanced machine learning techniques facilitated an in-depth analysis of AGB and BGB spatial patterns within China. Techniques such as variance decomposition analysis and piecewise structural equation modeling were employed to dissect the factors contributing to the spatial variability of vegetation biomass. Significant spatial heterogeneity in biomass distribution was uncovered, with vegetation biomass in the northwest markedly lower than in the southern and northeastern regions. It was observed that AGB consistently surpassed BGB. Climatic conditions, soil characteristics, and soil nutrients were found to significantly explain 53 % and 48 % of the total variance in AGB and BGB, respectively. Specifically, solar radiation and soil total nitrogen were identified as critical factors influencing variations in AGB and BGB. The findings offer profound contributions to the understanding of the global carbon balance and the evaluation of terrestrial ecosystems sustainability. Moreover, they provide essential insights into the ecosystems' response mechanisms to global changes, serving as a fundamental reference for future studies on terrestrial ecosystem carbon cycling and carbon sequestration potentials.

Effects of different sowing dates on biomass allocation of various organs and allometric growth of Fagopyrum esculentum.

The sowing date plays a crucial role in influencing the growth and reproduction of plants, with its specific impact on biomass allocation and allometric growth remaining unclear. Understanding these effects is essential for optimizing agricultural practices and enhancing crop productivity. To investigate the effects of sowing dates on biomass allocation and allometric growth, a field experiment was conducted with sequential sowings of Fagopyrum esculentum from April 12th to August 11th in 2018. Biomass measurements were taken across various plant organs, and corresponding allocation calculations were made. A detailed analysis of the allometric growth relationship involving organ biomass variations was performed. The study revealed that the accumulation and allocation of organ biomass in buckwheat were significantly impacted by the sowing dates. Delayed planting led to reduced vegetative growth and increased biomass allocation towards reproduction. Allometric parameters such as exponent, constant, and individual size of buckwheat were notably affected by delayed planting. Interestingly, the allometric exponents governing the relationships between reproductive vs. vegetative biomass and belowground vs. aboveground biomass exhibited varying trends across different sowing dates. Notably, late sowings resulted in significantly higher reproductive biomass compared to early and middle sowings. These findings highlight the nuanced relationship between plant size and reproductive biomass under different sowing dates, emphasizing the critical role of planting timing in shaping mature plant sizes and reproductive outcomes. The study underscores the importance of considering sowing dates in agricultural practices to optimize plant growth and productivity.

Inconsistent elevational patterns of soil microbial biomass, diversity, and community structure on four elevational transects from subtropical forests

The use of elevational gradients as proxies for time in predicting soil microbial responses to imminent climate changes is common, yet reliance on single-transect studies has raised concerns about the method's validity due to the lack of replication. Addressing this gap, our study evaluates the effects of elevation on soil microbial communities within subtropical forests, using four closely situated transects with consistent climatic and vegetative characteristics. Through phospholipid fatty acid analysis and Illumina MiSeq sequencing, we investigate variations in microbial biomass and the composition of communities at different elevations. Our results show that the ways microbial communities, both bacteria and fungi, respond to changes in elevation, particularly in aspects of biomass and diversity, vary significantly across different transects. Environmental factors, like soil pH, soil organic carbon concentration, and climatic factors, distinctly affect the attributes of these microbial communities through diverse mechanisms. These results underscore the need for multi-transect studies to accurately measure soil microbial responses to elevation and climate changes, challenging the predictive reliability of studies based on a single transect.

The topology of spatial networks affects stability in experimental metacommunities.

Understanding the drivers of community stability has been a central goal in ecology. Traditionally, emphasis has been placed on studying the effects of biotic interactions on community variability, and less is understood about how the spatial configuration of habitats promotes or hinders metacommunity stability. To test the effects of contrasting spatial configurations on metacommunity stability, I designed metacommunities with patches connected as random or scale-free networks. In these microcosms, two prey and one protist predator dispersed, and I evaluated community persistence, tracked biomass variations, and measured synchrony between local communities and the whole metacommunity. After 30 generations, scale-free metacommunities had lower global biomass variability and higher persistence, suggesting higher stability. Synchrony between patches was lower in scale-free metacommunities. Patches in scale-free metacommunities showed a positive relationship between variability and patch connectivity, indicating higher stability in isolated communities. No clear relationship between variability and patch connectivity was observed in random networks. These results suggest the increased heterogeneity in connectivity of scale-free networks favours the prevalence of isolated patches of the metacommunity, which likely act as refugia against competition-the dominant interaction in this system-resulting in higher global stability. These results highlight the importance of accounting for network topology in the study of spatial dynamics.

Pattern of plant biomass and carbon stock along different elevational forests in eastern Nepal

The primary aim of this investigation was to determine the biomass and carbon stock distribution pattern among different forest stands of diverse elevations in the Morang district of East Nepal. It is noteworthy to estimate carbon stock and biomass of relatively least underexplored forests in east Nepal. The data for estimating the biomass and carbon stocks of the five different forest sites, viz. Bhaunne, Raja-Rani, Murchungi, Adheri, and Sagma located between 100-1300m above the mean sea level, were acquired through the measurement of inventory plots selected randomly. Altogether, 50 sample plots were established within five forest stands located on different elevational zone; within each forest site, 10 sample plots of 20m × 20m size, were laid out for the measurement of trees. In the case of shrubs and herbs, nested plots of 5m × 5m and 1m ×1m, respectively were established. Calculation of the biomass of trees and shrubs was facilitated through the application of an allometric equation, while the biomass of herbs was determined by the harvest method. The carbon concentration in the plant materials was estimated using ash content method. The comprehensive analysis of the stand biomass in the Bhaunne, Raja-Rani, Murchungi, Adheri, and Sagma forest sites were: 815.86 Mg ha-1, 414.19 Mg ha-1, 606.81 Mg ha-1, 519.20 Mg ha-1, and 299.96 Mg ha-1, respectively, with minimum at the Sagma site (high-altitude forest) and maximum at the Bhaunne site (low-altitude forest). As per the variation in stand biomass, the carbon stocks in the forest sites also showed the same trend, but the values ranged from 140.19 Mg C ha-1 to 333.63 Mg C ha-1, with the minimum in the Sagma site and the maximum in the Bhaunne site. The application of the Friedman Test revealed statistically significant variation in the tree biomass between the Murchungi and Sagma sites and also in the shrub biomass between the Adheri and Sagma sites. Similarly, noteworthy variations were observed in the herb biomass of the Bhaunne, Raja-Rani, Murchungi, and Adheri sites as compared to that of the Sagma site. The present study contributes to the understanding of forest ecosystems in context to carbon management.

Comprehensive assessment of salt-alkali tolerance of different soybean varieties at the maturation stage

Soil salinization is a significant global challenge impacting food security and arable land safety. Biological amelioration for the development and utilization of salt-alkali land has gained attention in recent years but the breeding and selection of salt-alkali-tolerant crop varieties remain a challenge. Cultivated soybeans are moderately salt-tolerant crops; however, a precise threshold for salt-alkali conditions has not been determined and varies by genotype. Therefore, this study evaluated the salt-alkali tolerance of 15 different soybean varieties using correlation, principal component, membership function, and cluster analyses. The average soybean indices decreased with increasing salt-alkali stress concentrations. Under severe salt-alkali stress, the coefficients of variation for grain yield and biomass were significantly higher than those under mild salt-alkali stress. Plant height and node number were significantly positively correlated, whereas bottom pod height was significantly negatively correlated with branch number, effective pod number, and grain number per plant. Node and grain numbers per plant were significantly positively correlated. Branch number, effective pod number, grain number per plant, and hundred-grain weight were significantly and positively correlated. Effective pod number was significantly positively correlated with grain number per plant, biomass, and yield. Grain number per plant exhibited a significant negative correlation with hundred-grain weight. Biomass and yield were significantly positively correlated. The salt-alkali tolerance of 15 soybean varieties ranged from strong weak as follows: Cangdou 1438, 0734, 1426, 1418, 1453, 1327, 1846, 1412, 1817, 1301, 1821, 1819, 1815, 1814, and 1850. Salt-alkali-sensitive and salt-alkali-tolerant varieties were successfully identified.

Trait variation and performance across varying levels of drought stress in cultivated sunflower (Helianthus annuus L.).

Drought is a major agricultural challenge that is expected to worsen with climate change. A better understanding of drought responses has the potential to inform efforts to breed more tolerant plants. We assessed leaf trait variation and covariation in cultivated sunflower (Helianthus annuus L.) in response to water limitation. Plants were grown under four levels of water availability and assessed for environmentally induced plasticity in leaf stomatal and vein traits as well as biomass (performance indicator), mass fractions, leaf area, leaf mass per area, and chlorophyll content. Overall, biomass declined in response to stress; these changes were accompanied by responses in leaf-level traits including decreased leaf area and stomatal size, and increased stomatal and vein density. The magnitude of trait responses increased with stress severity and relative plasticity of smaller-scale leaf anatomical traits was less than that of larger-scale traits related to construction and growth. Across treatments, where phenotypic plasticity was observed, stomatal density was negatively correlated with stomatal size and positively correlated with minor vein density, but the correlations did not hold up within treatments. Four leaf traits previously shown to reflect major axes of variation in a large sunflower diversity panel under well-watered conditions (i.e. stomatal density, stomatal pore length, vein density, and leaf mass per area) predicted a surprisingly large amount of the variation in biomass across treatments, but trait associations with biomass differed within treatments. Additionally, the importance of these traits in predicting variation in biomass is mediated, at least in part, through leaf size. Our results demonstrate the importance of leaf anatomical traits in mediating drought responses in sunflower, and highlight the role that phenotypic plasticity and multi-trait phenotypes can play in predicting productivity under complex abiotic stresses like drought.

Real-world waste dispersion modelling for benthic integrated multi-trophic aquaculture.

In real-world situations, marine fish farms accommodate multiple fish species and cohorts within the farm, leading to diverse farm layouts influenced by cage dimensions, configurations, and intricate arrangements. These cage management practices are essential to meet production demands, however, farm-level complexities can impact model predictions of waste deposition and benthic impact near fish cages. This is of particular importance when the cages are used for integrated multi-trophic aquaculture (IMTA) with benthic feeders, where this waste not only affects environmental conditions but also provides a potential food source. The Cage Aquaculture Particulate Output and Transport (CAPOT) model incorporated multiple species, cohorts, and cage arrangements to estimate waste distribution from a commercial fish farm in the Mediterranean between October 2018 and July 2019. This spreadsheet model estimated dispersion for individual fish cages using a grid resolution of 5 m x 5 m. The study categorized discrete production periods for each fish cage every month, aligning with intermittent changes in biomass and food inputs due to different cage management practices throughout production. This approach facilitated the use of detailed input data and enhanced model representativeness by considering variations in cage biomass, food types, settling velocities, and configurations. Model outputs, represented in contour plots, indicated higher deposition directly below fish cages that varied monthly throughout fish production cycles. Deposition footprints reflected changes in cage biomass, food inputs, and farm-level practices reflecting this real-world scenario where aquaculture does not follow a production continuum. Moreover, cohort dynamics and cage movements associated with the cage management practices of the fish farm influenced the quantity and fate of wastes distributed around fish cages, revealing variability in deposition footprints. Clearly, these findings have important implications for the design of benthic IMTA systems, with species such as sea cucumber and polychaetes. Variability in waste deposition creates challenges in identifying where the benthic organisms should be placed to allow optimal uptake of waste to meet their food requirements and increase survivability. Evidently, models have an important role to play and this study emphasizes the need for representative input data to describe actual food inputs, cage biomass changes, and management practices for more representative farm-scale modelling and essentially to improve particulate waste management. To effectively mitigate benthic impacts through IMTA, models must quantify and resolve particulate waste distribution and impact around fish farms to maintain a balanced system with net removal of wastes. Resolving farm-level complexities provides vital information about the variability of food availability and quality for extractive organisms that helps improve recycling of organic wastes in integrated systems, demanding a more representative modelling approach.

Seasonal freeze‒thaw processes impact microbial communities of soil aggregates associated with soil pores on the Qinghai–Tibet Plateau

BackgroundSeasonal freeze‒thaw (FT) processes alter soil formation and cause changes in soil microbial communities, which regulate the decomposition of organic matter in alpine ecosystems. Soil aggregates are basic structural units and play a critical role in microbial habitation. However, the impact of seasonal FT processes on the distribution of microbial communities associated with soil pores in different aggregate fractions under climate change has been overlooked. In this study, we sampled soil aggregates from two typical alpine ecosystems (alpine meadow and alpine shrubland) during the seasonal FT processes (UFP: unstable freezing period, SFP: stable frozen period, UTP: unstable thawing period and STP: stable thawed period). The phospholipid fatty acid (PLFA) method was used to determine the biomass of living microbes in different aggregate fractions.ResultsThe microbial biomass of 0.25–2 mm and 0.053–0.25 mm aggregates did not change significantly during the seasonal FT process while the microbial biomass of > 2 mm aggregates presented a significant difference between the STP and UTP. Bacterial communities dominated the microbes in aggregates, accounting for over 80% of the total PLFAs. The microbial communities of soil aggregates in the surface layer were more sensitive to the seasonal FT process than those in other soil layers. In the thawing period, Gram positive bacteria (GP) was more dominant. In the freezing period, the ratio of Gram-positive to Gram-negative bacterial PLFAs (GP/GN) was low because the enrichment of plant litter facilitated the formation of organic matter. In the freezing process, pores of 30–80 μm (mesopores) favored the habitation of fungal and actinobacterial communities while total PLFAs and bacterial PLFAs were negatively correlated with mesopores in the thawing process.ConclusionsThe freezing process caused a greater variability in microbial biomass of different aggregate fractions. The thawing process increased the differences in microbial biomass among soil horizons. Mesopores of aggregates supported the habitation of actinobacterial and fungal communities while they were not conducive to bacterial growth. These findings provide a further comprehension of biodiversity and accurate estimation of global carbon cycle.

An Integrating Framework for Biomass and Carbon Stock Spatialization and Dynamics Assessment Using Unmanned Aerial Vehicle LiDAR (LiDAR UAV) Data, Landsat Imagery, and Forest Survey Data in the Mediterranean Cork Oak Forest of Maamora

Spatialization of biomass and carbon stocks is essential for a good understanding of the forest stand and its characteristics, especially in degraded Mediterranean cork oak forests. Furthermore, the analysis of biomass and carbon stock changes and dynamics is essential for understanding the carbon cycle, in particular carbon emissions and stocks, in order to make projections, especially in the context of climate change. In this research, we use a multidimensional framework integrating forest survey data, LiDAR UAV data, and extracted vegetation indices from Landsat imagery (NDVI, ARVI, CIG, etc.) to model and spatialize cork oak biomass and carbon stocks on a large scale. For this purpose, we explore the use of univariate and multivariate regression modeling and examine several types of regression, namely, multiple linear regression, stepwise linear regression, random forest regression, simple linear regression, logarithmic regression, and quadratic and cubic regression. The results show that for multivariate regression, stepwise regression gives good results, with R2 equal to 80% and 65% and RMSE equal to 2.59 and 1.52 Mg/ha for biomass and carbon stock, respectively. Random forest regression, chosen as the ML algorithm, gives acceptable results, explaining 80% and 60% of the variation in biomass and carbon stock, respectively, and an RMSE of 2.74 and 1.72 Mg/ha for biomass and carbon stock, respectively. For the univariate regression, the simple linear regression is chosen because it gives satisfactory results, close to those of the quadratic and cubic regressions, but with a simpler equation. The vegetation index chosen is ARVI, which shows good performance indices, close to those of the NDVI and CIG. The assessment of biomass and carbon stock changes in the study area over 35 years (1985–2020) showed a slight increase of less than 10 Mg/ha and a decrease in biomass and carbon stock over a large area.

Variation in Root Biomass and Distribution Based on the Topography, Soil Properties, and Tree Influence Index: The Case of Mt. Duryun in Republic of Korea.

Root biomass and distribution are influenced by abiotic factors, such as topography and soil physicochemical properties, determining belowground productivity. Hence, we investigated the variation in root biomass and vertical root distribution based on the topography, soil physicochemical properties, and tree influence index, and their relationships, across soil depths (0-10 cm, 10-20 cm, and 20-30 cm) and topographical gradients in a warm-temperate forest in Mt. Duryun, Republic of Korea. Two contrasting research sites were established: a lower slope oriented at ≤3° and an upper slope with a slope of 30°. Each site comprised eleven 400 m2 sampling plots from which root samples from various diameter classes (<2 mm, 2-5 mm, 5-10 mm, and >10 mm) were collected. While the bulk density increased with soil depth in the lower slope, the organic matter, available phosphorus, Ca2+, and Mg2+ showed a reversed pattern. Linear mixed-effects models generally revealed significant negative correlations between root biomass and soil pH, total nitrogen, and cation exchange capacity, particularly in small roots (βstd = -1.03 to -1.51) and coarse roots (βstd = -6.30). Root biomass exhibited a 10-15% increase in the upper slope compared to the lower slope, particularly in fine (median = 52.0 g m2-65.64 g m2) and medium roots (median = 56.04 g m2-69.52 g m2) at a 0-20 cm soil depth. While no significant correlation between root biomass and the tree influence index was found on the lower slope, a different pattern was found on the upper slope. Our results indicate that the variation in root biomass and distribution can also be explained by the differences in the soil environment and topographical positions.

Long-term declines in chlorophyll a and variable phenology revealed by a 60-year estuarine plankton time series

Long-term ecological time series provide a unique perspective on the emergent properties of ecosystems. In aquatic systems, phytoplankton form the base of the food web and their biomass, measured as the concentration of the photosynthetic pigment chlorophyll a (chl a), is an indicator of ecosystem quality. We analyzed temporal trends in chl a from the Long-Term Plankton Time Series in Narragansett Bay, Rhode Island, USA, a temperate estuary experiencing long-term warming and changing anthropogenic nutrient inputs. Dynamic linear models were used to impute and model environmental variables (1959 to 2019) and chl a concentrations (1968 to 2019). A long-term chl a decrease was observed with an average decline in the cumulative annual chl a concentration of 49% and a marked decline of 57% in winter-spring bloom magnitude. The long-term decline in chl a concentration was directly and indirectly associated with multiple environmental factors that are impacted by climate change (e.g., warming temperatures, water column stratification, reduced nutrient concentrations) indicating the importance of accounting for regional climate change effects in ecosystem-based management. Analysis of seasonal phenology revealed that the winter-spring bloom occurred earlier, at a rate of 4.9 ± 2.8 d decade-1. Finally, the high degree of temporal variation in phytoplankton biomass observed in Narragansett Bay appears common among estuaries, coasts, and open oceans. The commonality among these marine ecosystems highlights the need to maintain a robust set of phytoplankton time series in the coming decades to improve signal-to-noise ratios and identify trends in these highly variable environments.

Influence of climate, soil and vegetation diversity on the leaf area index as measured by canopy hemispherical photography in tropical rainforests across a wide elevational gradient

Tropical rainforests (TRFs) play an important role in regulating the global climate and conserving biodiversity. Leaf area index (LAI) determines the capacity of TRFs for radiation interception and carbon sequestration via photosynthesis while also influencing the water loss from TRF canopies via transpiration. Elevational gradients in tropical environments provide an approach to investigate the influence of environmental variations on key vegetation properties such as the LAI. In this work we determined the concurrent, interactive influences of the elevational gradients of the environment (i.e. selected climatic and soil properties) and vegetation (tree diversity and structure) in determining the variation of LAI of one-hectare permanent sampling plots (PSPs) within TRFs across a wide elevational gradient (from 117 m to 2132 m above sea level). Eight rounds of canopy hemispherical photography were carried out at three-month intervals over a 24-month period from 2019 to 2022. Canopy LAI was estimated using HemiView image processing software. Long-term mean climatic data from 1990 to 2021 were extracted for the PSPs from monthly global weather database of CRU-TS-4.06-bias corrected with WorldClim-2.1. Key soil properties were measured at 0–15 cm and 15–30 cm depths via soil sampling. Tree diversity was determined by a complete census of all trees with equal or greater than 10 cm in diameter at breast height. Total tree biomass was estimated using allometric equations. Linear mixed model analysis of LAI showed significant (p < 0.05) variance for the random effects of elevation and elevation × time interaction. In a majority of measurement rounds, variance of LAI due to elevation was significant while at a majority of elevations, the fixed effect of measurement round on LAI was significant. Leaf area index showed significant linear reductions with elevation in all rounds, at rates ranging from 0.175 to 0.357 per 1000 m. Linear and multiple regression analyses identified increasing maximum cumulative soil water deficit, CSWDMax (an index of water deficit computed as the difference between evapotranspiration and precipitation), as the major climatic factor responsible for the reduction of LAI with elevation. Decreasing solar irradiance (SR) and increasing day-night temperature difference (DTR) with elevation also contributed to the observed LAI trend. Multiple regression analysis showed soil exchangeable potassium (KEx) and available phosphorus (PAv) influencing LAI positively while electrical conductivity (EC) and total nitrogen (NTot) influencing LAI negatively. Variation of Shannon-Wiener tree diversity index (H) and total tree biomass per hectare (TBM) contributed positively to the observed elevational variation of LAI. Factor analysis extracted two underlying factor constructs which accounted for 86 % of the combined variation in climate, soil and vegetation across the elevational gradient. Plot-wise scores of Factor 1, which had CSWDMax, SR, DTR, soil EC, NTot and H loading strongly and accounting for 70 % of the variation, showed a significant linear relationship with LAI. A cluster analysis incorporating the elevational variation of LAI, climate, soil and vegetation clearly classified the TRFs into four ranges of elevation at a linkage distance of 0.75. We conclude that LAI of TRFs in our study decreases with increasing elevation and identify increasing water deficits with elevation as the major climatic factor controlling this reduction.

Biophysical characterization of summer Arctic sea-ice habitats using a remotely operated vehicle-mounted underwater hyperspectral imager

The impact of a rapidly shifting sea-ice cover on climate, ecosystem processes and biophysical habitat properties is not yet fully understood, particularly in the central Arctic Ocean, due to a lack of spatially representative observations. From June to July 2020 during the year-long Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC, leg 4) in the Transpolar Drift, we deployed an underwater hyperspectral imager (UHI) mounted on a remotely operated vehicle (ROV) to characterize the biophysical properties of different sea-ice habitats. We conducted UHI surveys along two transects: i) under level first-year sea ice (FYI), which had a mean sea-ice draft of 1.4 m and was composed of primarily level FYI but also had a relatively shallow ridge (keel depth ∼2.6 m); and ii) under the flank of a ridge, named Jaridge, with a mean ice draft of 1.7 m, which was composed of a mix of level ice and thicker ridge blocks with over 3 m draft. We present a new unsupervised bio-optical quantification algorithm for hyperspectral surveys, the relative ice algal biomass index (RBI), using spectral mixture analysis (SMA). We compare this method to the supervised machine learning habitat classification algorithm, Support Vector Machine (SVM). The RBI showed good agreement to literature-based normalized difference indices (NDI) and PCA analyses, which confirm the RBI as a reliable unsupervised index for ice algal biomass. Our biophysical characterization of the two surveyed regions showed an association of sea-ice algal biomass with sea-ice ridge features. Our surveys also indicate that ice algal spatial distribution may be influenced by ice melt rates, and the formation of under ice meltwater layers and false bottoms. With high spatial coverage (>100 m) at microscale resolution (∼cm) we documented large spatial variability of summer Arctic sea-ice algal biomass and different patterns between adjacent ice habitats. We further demonstrate the need for improved understanding of sea-ice algal spatial variability as a complementary tool for sea-ice biogeochemical sampling using destructive ice core sampling.

Purification of stilbenes from grape stems in a continuous process based on photo-molecularly imprinted adsorbents and hydroalcoholic solvents

This study presents a sustainable method to purify stilbenes from residual grape stem biomass. This approach was experimentally validated through the use of a pilot size fixed-bed adsorption prototype for the automation of the purification process. Molecularly imprinted polymers, synthesized through photopolymerization at room temperature and incorporating the 4-vinylpyridine monomer, serve as adsorbents. The purification procedure leads to a significant enrichment, with a more than 22-fold increase in (E)-ε-viniferin and a 9-fold increase in (E)-resveratrol. High recoveries of 80.3% and 62.1% for (E)-ε-viniferin and (E)-resveratrol, respectively, were achieved. Notably, the use of eco-friendly water and ethanol mixtures distinguishes this method from others focused on stilbenes purification. This study further explores the variability of the stilbenes in the residual grape stems by analysing different varieties, emphasizing the complexity of the starting material of the purification process. The range of purities achieved for the fractions enriched with stilbenes (e.g., 12.8% for (E)-ε-viniferin and 3.4% for (E)-resveratrol) are suitable for direct use in controlling of Plasmopara viticola, the agent causing grapevine downy mildew. Furthermore, through compositional combination of these fractions, it is possible to conceive new stilbene-containing phytochemicals with improved anti-fungal activity. Therefore, the developed adsorbents and purification process, enabling the steady enrichment of stilbenes regardless of the unavoidable variability in the initial vine biomass, is a contribution towards the quest for more environmentally friendly and sustainable phytochemicals.

Lichen biocrusts contribute to soil microbial biomass carbon in the northern temperate zone: A meta‐analysis

AbstractBiological soil crusts (biocrusts) have crucial ecological functions in dryland ecosystems, yet understanding the variations in soil microbial biomass within biocrusts across diverse ecosystems, climates and soil conditions remains limited. This knowledge gap constrains our understanding of how microbial communities within biocrusts regulate terrestrial carbon and nitrogen cycling. Hence, we conducted a meta‐analysis using 255 paired observations from 42 study sites across the northern temperate ecosystem. The analysis revealed that biocrusts harbour significantly higher soil microbial biomass carbon and nitrogen (SMBC and SMBN, respectively) levels than bare (non‐biocrust) soil across all habitat types. Notably, deeper soil layers (5–10 and &gt;10 cm) accumulated less SMBC and SMBN than biocrust and biocrust–5‐cm soil, revealing that biocrusts influence shallow soil environments. Ecosystem type, soil texture, depth and season emerged as key factors influencing the distribution of SMBC within biocrusts. Of particular interest, lichen biocrusts accumulated the most SMBC compared with other biocrust types. Furthermore, the difference in SMBC between biocrust and non‐biocrust soils was more pronounced in oligotrophic habitats (e.g., desert, grassland, sand and sandy loam soils) than in eutrophic habitats (e.g., forest and loam soils). Random forest analysis confirmed that soil variables affected SMBC accumulation in biocrusts more than climatic factors. Soil organic carbon (SOC), as the primary source of SMBC, could be the most important determinant. Moreover, the disparity between non‐biocrust SMBC and biocrust SMBC increased with increasing mean annual temperature (MAT) or decreasing altitude. These insights underscore the substantial contribution of lichen biocrusts to SMBC and emphasize the need to incorporate this knowledge into regional models for predicting the effects of climate change on soil carbon budgets within biocrust microbiomes in temperate ecosystems of the Northern Hemisphere.