Biomass Distribution Research Articles

Genotypic variation in functional contributors to yield for a diverse collection of field‐grown cotton

AbstractYield improvement in cotton could be accelerated through selection for functional yield drivers such as interception of cumulative photosynthetically active radiation (∑IPAR), radiation use efficiency (RUE), and harvest index (HI). However, information on the extent to which these traits vary in cotton in the southeastern United States is limited. It was hypothesized that functional yield drivers would vary significantly within a diverse cotton collection. This study was conducted in Tifton and Athens, GA, and included a total of 4 site‐years. Lint yield, total biomass production, ∑IPAR, RUE, and HI were all affected by genotype. Biomass was more strongly correlated with RUE than ∑IPAR. Even among the highest yielding genotypes, values for functional yield drivers (biomass and harvest index) differed significantly, indicating that high yields could be achieved by differentially manipulating these underlying traits. However, when considered for all genotypes, only HI exhibited a significant positive correlation with yield. Boll production and intra‐boll yield components were also affected by genotype. When considered across upland genotypes, lint per boll, lint per seed, and lint percent were strongly associated with HI and lint yield, whereas boll mass and seed number per boll were not. We conclude that the genotypes evaluated in the current study achieve high lint production per boll and lint yields by manipulating different yield drivers. However, lint yield was primarily maximized through an increase in HI due to increases in boll production and within‐boll distribution of biomass to fiber, not due to increases in total biomass production or boll size.

Estimating the Aboveground Biomass of Robinia pseudoacacia Based on UAV LiDAR Data

Robinia pseudoacacia is widely planted in the Loess Plateau as a major soil and water conservation tree species because of its dense canopy, complex structure, and strong soil and water conservation ability. The precise measurement of small-scale locust forest biomass is crucial to monitoring and evaluating the carbon sequestration functions of soil and water conservation vegetation. This study focuses on an artificial locust forest planted in the early 1990s in Caijiachuan Basin, Jixian County, Shanxi Province. A drone equipped with LiDAR was used to obtain point cloud data and generate a canopy height model. A watershed segmentation algorithm was used to identify tree vertices and extract individual trees. A relationship model between tree height, diameter at breast height, and biomass, combined with sample survey data, was established to explore the spatial distribution of biomass in the artificial locust forest at the level of the entire basin. The results show the following: (1) the structural parameters of locust extracted using UAV point cloud data have a good degree of fit and accuracy, and the recall rate is 72.7%; (2) the average error rate of the extracted maximum tree height value of locust is 7%, that of the minimum tree height value is 14%, and that of the average tree height value is 18%; (3) the average error rate of the extracted maximum diameter at breast height of locust is 15%, that of the minimum diameter at breast height is 37%, and that of the average diameter at breast height is 36%; and (4) the average error rate of the biomass estimation of locust calculated using point cloud data is 16.0%.

On the biology of blackbellied angler, Lophius budegassa Spinola, 1807, in the north-western Mediterranean

In the Mediterranean Sea, the blackbellied angler, Lophius budegassa Spinola, 1807, represents a relevant fraction of the commercial by-catch of bottom trawling and small-scale fisheries that use passive gears (e.g., set nets, bottom longlines, etc.). Despite its importance, there are no comprehensive studies on the population dynamics of this species, and there is still scarce and scattered knowledge of its biology and ecology. Biomass, morphometric, and biological data of the blackbellied angler were collected from 1994 to 2021 by means of the Mediterranean International Bottom Trawl Survey (MEDITS) programme in the Ligurian and northern Tyrrhenian Seas, and in the EU Data Collection Framework during the period of 2006-2021. Furthermore, ageing was performed on specimens collected from 2013 to 2021 during the MEDITS programme. There were high values for the density indices and the spatial distribution of biomass in the central sector of the investigated area (the Tuscan Archipelago), mostly on the continental shelf. The length-weight relationship showed negative allometric growth when considering the sexes together, and no difference between the sexes. The size at first maturity (L50) was estimated at 39.4 cm total length (TL) in females and at 29.2 cm TL in males. The obtained Von Bertalanffy growth parameters were: in females, L∞ = 74.50 cm, k = 0.10 years-1, and t0 = -0.40 years; in males, L∞ = 61.30 cm, k = 0.14 years-1, and t0 = -0.38 years. There were differences in growth between males and females for L∞ (χ2 = 10.04; p < 0.05) and k (χ2 = 6.12; p < 0.05).

Dalbergia nigra (Vell.) grown using hydrogel planting methods in the establishment of a silvopastoral system in a degraded soil

This work tested the use of a superabsorbent polymer (hydrogel) in a silvopastoral system with Brazilian-rosewood (Dalbergia nigra (Vell.) Allemão ex Benth.) in a degraded pasture area. The experimental site is part of the Bananal do Norte experimental farm, Cachoeiro de Itapemirim, Espírito Santo, Brazil. Over 480 seedlings were planted and submitted to the treatments: Dry hydrogel (DRY); Hydrated hydrogel around the root ball (HAR); Hydrated hydrogel mixed with soil (HMS); and water only (WAT). The design was in randomized blocks, with three repetitions. The tested variables were plant survival, height and root collar diameter until 672 days after planting, soil moisture at 93 days after planting and total biomass and leaf chemical analysis at 184 days after planting. Survival was positively influenced by the application of the hydrogel, but there was little or no effect regarding the application method. The hydrogel and its application techniques did not alter growth in height and root collar diameter. The polymer did not influence the development in biomass and nutritional content of the leaves, but did influence the biomass distribution. The use of the superabsorbent polymer was therefore not effective in accelerating plant growth and anticipating the stages in the implantation of the silvopastoral system. Keywords: agroforestry, brazilian-rosewood, degraded pasture.

An open web-based GIS service for biomass data in Finland

Reliable, up-to-date biomass data are needed for climate change mitigation and resource efficiency. Therefore, a calculation and reporting tool with thematic maps and data was developed. A free web-tool, Biomass Atlas, collects the spatial distribution of biomasses in Finland. Over 300 data layers present land use, cultivation, residual biomasses from forest, crop production, animal husbandry, municipalities, and industry at 1 km2 spatial resolution. The service enables calculations of biomass amount in a defined geographical area of interest and examining the opportunities and restrictions to utilise biomasses. The service was evaluated with six test-users in laboratory tests and 20 voluntary pilot test-users. Biomass Atlas shows the regional potential of biomaterials, fertilizer products, and renewable energy, as well as potential targets for utilized, recyclable biomass. Other possible uses include monitoring plant cover on fields and assessing land use diversity. Application enables users with no experience in GIS or biomass assessments to analyse biomass resources, produce maps and data summaries for decision making.

Management Strategy of Slow-Release Nitrogen Fertilizers for Direct-Sown Cotton after Wheat Harvest

The direct-sown cotton after wheat harvest (DSCWH) cropping system has attracted wide attention due to reduced labor inputs compared to transplanting. However, the management strategy of slow-release nitrogen is unclear in such a system. This study aims to investigate the impact of different timings and dosages of slow-release nitrogen fertilizer on the yield, biomass accumulation and distribution, and nitrogen absorption and nitrogen utilization in the DSCWH cropping system. This study was investigated at the experimental farm of Yangzhou University, China in 2020 and 2021, with the short-season cotton variety “Zhongmian 50” used as experimental material. Three dosages of the slow-release nitrogen fertilizer (45 kg·ha−1, 90 kg·ha−1, and 135 kg·ha−1) were applied at two stages of growth (two-leaf and four-leaf). The results showed that applying a 90 kg·ha−1 dosage at the two-leaf stage achieved the highest yield, which was increased by 12.6% compared to the no-fertilization control. Applying 90 kg·ha−1 of the slow-release nitrogen at the two-leaf stage promoted biomass accumulation, especially in reproductive organs, and this increase in biomass of reproductive organs was attributed to optimum nitrogen accumulation in reproductive organs (80~140 kg·ha−1). In addition, when 90 kg·ha−1 was applied at the two-leaf stage, there was a significant enhancement in nitrogen recovery efficiency (NRE), nitrogen agronomic use efficiency (NAE), and nitrogen physiological efficiency (NPE), with increases of 7.2% to 13.0%, 5.7% to 5.8%, and 5.6% to 6.5%, respectively. These results revealed that applying slow-release nitrogen fertilizer with the optimal dosage at the seedling stage could significantly enhance nitrogen use efficiency, nitrogen accumulation and partitioning, and biomass accumulation and distribution, which ultimately resulted in a higher lint yield in DSCWH. Therefore, to optimize yield and NUE, 90 kg·ha−1 slow-release nitrogen applied at the two-leaf stage would be recommended in the direct-sown cotton after wheat harvest cropping system.

Contrasting biomass allocations explain adaptations to cold and drought in the world's highest-growing angiosperms.

Understanding biomass allocation among plant organs is crucial for comprehending plant growth optimization, survival and responses to the drivers of global change. Yet, the mechanisms governing mass allocation in vascular plants from extreme elevations exposed to cold and drought stresses remain poorly understood. We analysed organ mass weights and fractions in 258 Himalayan herbaceous species across diverse habitats (wetland, steppe, alpine), growth forms (annual, perennial taprooted, rhizomatous and cushiony) and climatic gradients (3500-6150 m elevation) to explore whether biomass distribution adhered to fixed allometric or optimal partitioning rules, and how variations in size, phylogeny and ecological preferences influence their strategies for resource allocation. Following optimal partitioning theory, Himalayan plants distribute more biomass to key organs vital for acquiring and preserving limited resources necessary for their growth and survival. Allocation strategies are mainly influenced by plant growth forms and habitat conditions, notably temperature, water availability and evaporative demands. Alpine plants invest primarily in below-ground stem bases for storage and regeneration, reducing above-ground stems while increasing leaf mass fraction to maximize carbon assimilation in their short growing season. Conversely, arid steppe plants prioritize deep roots over leaves to secure water and minimize transpiration. Wetland plants allocate resources to above-ground stems and below-ground rhizomes, enabling them to resist competition and grazing in fertile environments. Himalayan plants from extreme elevations optimize their allocation strategies to acquire scarce resources under specific conditions, efficiently investing carbon from supportive to acquisitive and protective functions with increasing cold and drought. Intraspecific variation and shared ancestry have not significantly altered biomass allocation strategies of Himalayan plants. Despite diverse evolutionary histories, plants from similar habitats have developed comparable phenotypic structures to adapt to their specific environments. This study offers new insights into plant adaptations in diverse Himalayan environments and underscores the importance of efficient resource allocation for survival and growth in challenging conditions.

Effect of pore size distribution of biomass activated carbon adsorbents on the adsorption capacity

AbstractBACKGROUNDIn order to investigate the correlation between the pore size distribution of biomass activated carbon adsorbents (BACAs) and VOCs (volatile organic compounds) adsorption/desorption performance. Four BACAs with same specific surface area but different pore size distribution were prepared under different experimental conditions and processes.RESULTSThe impact of the pore size distribution of BACAs on the adsorption/desorption performance of benzene, toluene and xylene was investigated. The results indicated that the adsorption ability of the prepared BACAs for benzene, toluene and xylene was mostly affected by the pore sizes distributed in the 2.60 ~ 3.25, 2.68 ~ 3.35and 4.20 ~ 4.90 nm ranges, respectively, when the studied BACAs had similar specific surface area (SBET ≈ 1080 m2 g−1). However, the desorption amount of adsorbed benzene molecules mainly relied on the pore structures of BACAs having pore sizes in the 3.95 ~ 4.60 nm range.CONCLUSIONThe pore structures of BACAs distributed in different pore size ranges have various effects on the phenyl VOCs adsorption capacity. Benzene adsorption on the BACAs was mainly affected by the microporous structures. The pore structure with larger pore size was more favorable for the desorption of the adsorbed toluene and xylene molecules compared to the adsorbed benzene molecules. Benzene, toluene and xylene had low residual rates in the studied activated carbon adsorbents attesting to their superior regenerative properties. This work could provide an important reference for the design, preparation, and selection of activated carbon adsorbents for the adsorption capacity of benzene, toluene and xylene. © 2024 Society of Chemical Industry (SCI).

Soil Microbial Biomass and Bacterial Diversity Enhanced through Fallow Cover Cropping in Rice–Fish Coculture

Traditional rice production is often reliant on the unsustainable practice of utilizing intensive inputs in monoculture cropping systems. Alternatives fallow cover cropping and rice–fish coculture (RFC) offer promising solutions. However, the potential of fallow cover cropping in RFC remains underexplored, and its impact on soil microbes is poorly understood. In this study, assessments of soil–plant–microbe interactions were conducted across three cover cropping systems: Chinese milk vetch (Astragalus sinicus L.) single cropping (CM), Rapeseed (Brassica napus L.) single cropping (RP), and a combination of Chinese milk vetch and rapeseed intercropping (CM_RP). These systems were evaluated with and without nitrogen (N) addition, encompassing both the RFC and rice monoculture (RMC) systems. The findings indicate a notable increase in soil microbial biomass nitrogen (MBN) with CM. Soil microbial biomass carbon (MBC), influenced more by N-fertilizer than crop species, decreased with N addition. In the RFC system, the soil bacterial co-occurrence network exhibited more connections, yet negative links increased. CM_RP displayed similarities to CM without N but shifted closer to RP with N addition. N addition in intercropping significantly increased the root–shoot ratio (R/S) of A. sinicus, associated with decreased aboveground biomass and total root length. Compared to RMC, RFC with N addition reduced the relative abundance of Anaerolineaceae in CM while increasing Bacillus and Pontibacter across cover cropping systems. Overall, with N addition, both RFC and RMC showed decreased soil bacterial diversity indices. Changes in soil bacterial diversity correlated significantly with soil MBC, MBN, and plant R/S. Continuous fallow cover cropping altered soil microbial biomass and affected cover crop biomass distribution, impacting bacterial composition in paddy soil. These results shed light on how bacterial communities respond to N addition and fallow cover cropping in RFC and RMC systems, offering insights for sustainable nutrient management in paddy systems.

Bi-objective optimization modeling for biomass supply chain planning

Biomass energy plays an essential role in renewable energy for many reasons, such as reducing the dependence on fossil fuels and lowering greenhouse gas emissions, providing heat, electricity, and biofuels for various applications, and utilizing waste materials for helpful energy products. Besides, it can create employment opportunities and promote rural development, especially in developing countries where biomass resources are abundant and accessible. In the context of renewable energy research and application, this paper aims to develop a multi-objective mixed integer linear programming for designing multiple echelon biomass supply chain networks. The model is formulated to consider the economic costs and environmental impact of biomass distribution from the suppliers to the biomass plants. In this research, the Epsilon constraint method is adopted to generate Pareto fonts, which provides the trade-offs between two objectives. Moreover, sensitivity analysis is implemented to provide decision-makers with information about a network with changed parameters such as demand. Our model allows the decision maker to determine the capacity of warehouses and biomass power plants, inventory levels, type of trucks, etc. The proposed model is verified and evaluated using a practical dataset from Can Tho province, Central Mekong River Delta in Vietnam, generating several benefits for energy security and sustainability. Such a network includes 3 types of power plants, 3 scales of warehouses, 13 potential locations, and 41 suppliers. From the generated solutions, with the proportion of biomass electricity satisfaction varying from 5% to 30%, Hung Phu, O Mon, and Cai Rang industrial parks are the most suitable for power plants.

Long-term nitrogen addition modifies fine root growth and vertical distribution by affecting soil nutrient availability in a Mongolian pine plantation

Fine roots are the primary organ of tree species in water and nutrient acquisition, and are the major contributor of forest soil organic carbon (C). However, it remains largely unknown how fine root growth dynamics and vertical distribution respond to long-term nitrogen (N) enrichment, which prevents us from accurately evaluating forest C sequestration potential under N deposition. Here, we investigated the effects of nine-year N addition (0 and 10 g N m−2 year−1) on fine root nutrients, biomass, production, turnover rate and vertical distribution in three soil layers (0–10, 10–20 and 20–40 cm) of a Mongolian pine (Pinus sylvestris var. mongolica) plantation in the Keerqin Sandy Lands, Northeast China. We found that soil inorganic N was increased and Olsen-P was decreased by N addition. N addition increased fine root N, C:P and N:P ratios, but reduced fine root P and C:N ratio across all soil layers. N addition reduced fine root biomass in 0–10 cm soil layer but increased it in 20–40 cm soil layer. N addition accelerated fine root turnover rate in 0–10 cm soil layer, and increased fine root necromass across all soil layers. Moreover, N addition significantly enhanced biomass of ectomycorrhizal extraradical hyphae in the 0–10 cm soil layer. Redundancy analysis showed that variations of fine root traits were well explained by soil NO3−-N in 0–10 and 10–20 cm soil layers, and by soil NH4+-N and Olsen-P in 20–40 cm soil layer. Collectively, our results highlight the shift from N limitation to P limitation of Mongolian pine plantations under long-term N addition, and suggest that changes in fine root growth and vertical distribution induced by N addition could accelerate belowground C allocation in Mongolian pine plantations.

The Role of Wood Density Variation and Biomass Allocation in Accurate Forest Carbon Stock Estimation of European Beech (Fagus sylvatica L.) Mountain Forests

The European beech (Fagus sylvatica L.) is one of the most common tree species in Romania, with importance both economically and environmentally. Accurate methods of biomass assessment at the tree compartment level (i.e., stump, stem, branches, and leaves) are necessary for carbon stock estimation. Wood density (WD) is an important factor in determining biomass and, ultimately, the tree’s carbon content. The average tree density was found to be 578.6 kg/m3. For this study, WD was evaluated by the weighting method related to tree volume. Also, to investigate a practical approach to determining the weighted wood density (WWDst), models were run using density at the base of the tree (WDBase), density at breast height level using discs (WDDBH), the wood core density (WDic), and the diameter at breast height (DBH) as predictors. The biomass assessment was conducted using different model evaluations for WWDst as well as allometric equations using the destructive method. From the results, it was noted that using the WWDst, the total biomass was underestimated by −0.7% compared to the biomass measured in the field. For allometric equations that included DBH and tree height as independent variables, the explained variability was around 99.3% for total aboveground biomass (AGBtotal), while it was 97.9% for allometric function using just the DBH. Overall, the distribution of biomass across different compartments was as follows: 73.5% in stems, 23.8% in branches, 1.9% in stumps, and 1.3% in leaves. The study findings offer valuable insights into WD, biomass distribution among different components, and biomass allometric quantification in natural beech forest environments in mountainous areas.

Spatio-temporal changes in the phytoplankton in Lake Baikal during late Summer. II. Biomass

The results of phytoplankton biomass study in different regions of the Lake Baikal according to data of 15 expeditions from 1994 to 2013 are presented in the paper. Spatial distribution and interannual dynamics of biomass of phytoplankton in all three throughs of the lake are analyzed. The general biomass of phytoplankton during late Summer is not high. The multiyear average phytoplankton biomass equals 169 ± 5 mg/m3 for open waters of the lake. It is distributed relatively uniformly around the Southern Baikal. Higher multiyear average values are along Eastern shore in the Middle and Northern Baikal. The late summer phytoplankton biomass in Southern and Middle throughs does not differ. Average multiyear biomass of phytoplankton of Northern through is accurately lower than one for two other throws. There is no increase of biomass for any region of the lake demonstrated. The relations of general biomass of phytoplankton with water temperatures are very slight.

STARdbi: A pipeline and database for insect monitoring based on automated image analysis

Insects are highly abundant and diverse, and play major roles in ecosystem functions. Monitoring of insect populations is key to their sustainable management. However, the labor and expertise needed to identify insects, and the challenges of archiving the wealth of data collected in monitoring programs, often limit these efforts. We describe a pipeline to reduce the barriers associated with curating and mining big data of insect biodiversity. The pipeline, STARdbi, includes capturing flying insects with sticky traps, scanning the traps, storing the trap-images in a public database with a web-based interface, and applying machine learning models to extract information from the images. To illustrate the insights that can be gained from STARdbi, we describe two case studies. One of them involves monitoring of circadian activity patterns of grain pests and of their natural enemies, and the other compares insect abundance, biomass and size distributions between agricultural and semi-natural habitats. We invite the community of insect ecologists to contribute to the STARdbi database, and to use its image analysis tools to address diverse ecological and evolutionary questions.

Yield reduction caused by elevated temperatures and high nitrogen fertilization is mitigated by SP6A overexpression in potato (Solanum tuberosum L.).

Potatoes (Solanum tuberosum L.) are a fundamental staple for millions of people worldwide. They provide essential amino acids, vitamins, and starch - a vital component of the human diet, providing energy and serving as a source of fiber. Unfortunately, global warming is posing a severe threat to this crop, leading to significant yield losses, and thereby endangering global food security. Industrial agriculture traditionally relies on excessive nitrogen (N) fertilization to boost yields. However, it remains uncertain whether this is effective in combating heat-related yield losses of potato. Therefore, our study aimed to investigate the combinatory effects of heat stress and N fertilization on potato tuber formation. We demonstrate that N levels and heat significantly impact tuber development. The combination of high N and heat delays tuberization, while N deficiency initiates early tuberization, likely through starvation-induced signals, independent of SELF-PRUNING 6A (SP6A), a critical regulator of tuberization. We also found that high N levels in combination with heat reduce tuber yield rather than improve it. However, our study revealed that SP6A overexpression can promote tuberization under these inhibiting conditions. By utilizing the excess of N for accumulating tuber biomass, SP6A overexpressing plants exhibit a shift in biomass distribution towards the tubers. This results in an increased yield compared to wild-type plants. Our results highlight the role of SP6A overexpression as a viable strategy for ensuring stable potato yields in the face of global warming. As such, our findings provide insights into the complex factors impacting potato crop productivity.

Trait‐based mechanistic approach highlights global patterns and losses of herbivore biomass functional diversity

Abstract Mammalian herbivores play a pivotal role in Earth System processes by affecting biogeochemical cycles and ecosystem functioning, potentially leading to significant repercussions on atmosphere–biosphere feedbacks. Global dynamic models of mammalian populations can improve our understanding of their ecological role at large scales and the consequences of their extinctions. However, such models are still lacking and mammals are poorly integrated in Earth System Science. We developed a mechanistic global model of terrestrial herbivore populations simulated with 37 functional groups defined through the analysis of eco‐physiological traits across all extant herbivores (2599 species). We coupled this model with a global vegetation model to predict herbivores' maximum potential biomass in pre‐industrial and at present‐day and to study the environmental drivers explaining the distribution of herbivore biomass. Present‐day biomass was estimated by accounting for anthropogenic activity causing habitat and range losses. We show that natural ecosystems could have sustained a potential wild herbivore wet biomass of 330 Mt (95% CI: 245–417), comprised of 193 Mt (95% CI: 177–208) by large species (body mass >1–10 kg, depending on functional group) and 138 Mt (95% CI: 68–209) by small species. We estimate that the remaining present‐day large herbivores biomass is 82 Mt (95% CI: 32–133), reduced by 57% due to anthropogenic activity; consequently, small herbivores currently dominate global herbivore biomass with 98 Mt (95% CI: 91–106, −29%). Losses vary greatly across climatic zones and functional groups, suggesting that size is not the only discriminant feature of biomass decline. Actual evapotranspiration is the most important driver of total, large and small herbivore biomass and explains 64%, 59% and 49% of its variation, respectively. Distribution of modelled and observed large herbivores' biomass suggested a high dependency on energy and water with more biomass in hot and wet areas. These results challenge the notion that large herbivore biomass peaks primarily in ecosystems with intermediate precipitation levels such as savannas. Outside Africa and the Tropics, pre‐industrial biomass hotspots occur in areas today dominated by humans; this could undermine the recovery of larger species biomass in certain areas. Our herbivore biomass estimates provide a quantitative benchmark for setting conservation and rewilding goals at large spatial scales. The herbivore model and functional classification create new opportunities to integrate mammals into Earth System Science and models. Read the free Plain Language Summary for this article on the Journal blog.

Incorporating small‐scale disturbances in models of forest structure and aboveground biomass of tropical mountains

AbstractSeveral efforts have been made to model forest structure and estimate global aboveground biomass (AGB) magnitude and distribution. However, AGB models still show large uncertainties, especially over tropical mountains that are difficult to survey and understudied. Although forest disturbance and land use greatly influence forest structure and AGB accumulation, they are rarely considered in forest structure and AGB models. Including the effect of forest disturbance and land use could improve model performance. In this study, we used Landsat time series analysis and forest inventory data to assess and model the effect of small‐scale disturbance and land use on tropical montane forest structure and AGB. We explored two approaches: abrupt forest change detection, using the algorithm Breaks For Additive Seasonal Trend (BFAST), and gradual vegetation change by calculating the variation of remote sensing vegetation indices over time. We found that tropical montane landscapes are very dynamic and heterogenous. Out of the 284 forest plots analyzed, 27% had abrupt disturbances at least once between 1993 and 2014, and some of them showed abrupt disturbances several times. Forest plots with abrupt disturbances exhibit statistically significant lower basal area, tree height, and AGB than plots without abrupt disturbances. Using linear mixed‐effects models, we found that the number of breakpoints, annual Normalized Difference Vegetation Index SD, and Normalized Difference Water Index minimum values over time were the most informative variables for predicting forest structure, particularly basal area (adjusted R2 = 0.61). These variables are easy to calculate and could add significant power to forest structure and AGB models. In conclusion, incorporating small‐scale disturbance to model forest structure and AGB at regional scales is feasible through the identification of recent abrupt and gradual forest change using remote sensing time series. Including recent forest disturbance variables as predictors in forest structure models can greatly improve biomass predictability and mapping in dynamic landscapes.

Modeling Physical and Physiological Processes Reveals the Role of Turbulence in the Prerequisites for Microcystis Blooms

AbstractHarmful algal blooms of Microcystis have become a global problem. Turbulence, a determining factor affecting blooms, not only disperses surface scum but also controls the growth of Microcystis. Numerous studies have analyzed the effects of turbulence on the growth and colony size of Microcystis in laboratories, but the turbulence thresholds for Microcystis growth and colony disaggregation in the field are difficult to determine due to the complex environment. In addition, the quantitative contribution of turbulence‐driven blooms and the intrinsic mechanisms of the spatial distribution responding to turbulence are unclear. In this study, a fully integrated filed scale computational model focusing on turbulence‐driven blooms was developed, which incorporates physical processes (turbulence‐induced vertical mixing, VMT) and physiological processes such as buoyancy‐controlling transport (BCT), turbulence‐induced colony size variation (CSV), and growth rate variation (GRV). We performed model sensitivity analysis and evaluated the effects of turbulence intensity and duration on the biomass and vertical distribution of Microcystis. The results show that the optimal turbulence dissipation rate for Microcystis growth in the field is 1.0 × 10−5 m2/s3 and the critical turbulence dissipation rate for aggregation distribution is 3.81 × 10−6 m2/s3 in shallow lakes. A quantitative comparison of the effects of physical/physiological processes on blooms shows that physiological processes (CSV, GRV, and BCT) are critical for biomass enrichment, and the accumulation of Microcystis at the water surface is dominated by physical processes (VMT). This study reveals the mechanisms of turbulence‐driven Microcystis blooms and provides new insights for algal bloom prediction and control.

A comparison of adenosine triphosphate with other metrics of microbial biomass in a gradient from the North Atlantic to the Chesapeake Bay

A new, simplified protocol for determining particulate adenosine triphosphate (ATP) levels allows for the assessment of microbial biomass distribution in aquatic systems at a high temporal and spatial resolution. A comparison of ATP data with related variables, such as particulate carbon, nitrogen, chlorophyll, and turbidity in pelagic samples, yielded significant and strong correlations in a gradient from the tributaries of the Chesapeake Bay (sigma-t = 8) to the open North Atlantic (sigma-t = 29). Correlations varied between ATP and biomass depending on the microscopic method employed. Despite the much greater effort involved, biomass determined by microscopy correlated poorly with other indicator variables including carbon, nitrogen, and chlorophyll. The ATP values presented here fit well within the range of ATP biomass estimates in the literature for similar environments. A compilation of prior research data from a wide range of marine habitats demonstrated that ATP values can be ranked according to broad trophic gradients, from the deep sea to eutrophic inland waters. Using a mass-based conversion factor of 250, the contribution of biomass to overall particulate organic carbon (POC) ranged from 15% to 30% along the gradient, from the open ocean to locations in the Chesapeake Bay respectively. Our data corroborate the notion that ATP, due to its consistency and simplicity, is a promising high-throughput indicator of cytoplasm volume with distinct benefits over cell counts and measures of chlorophyll or POC.

Latitudinal variation and driving factors of above-ground carbon proportion of large trees in old-growth forests across China

Large trees play a vital role in forest carbon stocks, dominating the distribution of community biomass. However, climate change and deforestation are reducing large trees globally, resulting in regional differences in their contribution to carbon stocks. Here, we examined the latitudinal change pattern and drivers of large trees' contributions to stand carbon stocks. Above-ground carbon storage was calculated for 530 plots in old-growth forests across China. Linear regression was used to calculate latitudinal variation in the proportion of above-ground carbon in large trees (i.e., AGC proportion). Variance partitioning and multiple linear regression were used to calculate the relative importance of species diversity, stand structure, functional traits, and environmental factors to AGC proportion. The study found that AGC proportion decreased with increasing latitude, averaging at 64.44 %. Stand structure, particularly the coefficient of variation of DBH, was identified as the key drivers of the AGC proportion. The number of common species (Hill's 1D) had no direct effect on the AGC proportion, while wood density, maximum tree height, and leaf nitrogen-to‑phosphorus ratio showed negative effects. The mass-ratio effects on AGC proportion were stronger than diversity effects. Climate variables primarily affected the AGC proportion through stand variables. These results indicate that simultaneously managing high diversity and AGC proportion may pose challenges. Moreover, considering the substantial contribution of large trees to carbon stocks, their storage capacity and sensitivity to environmental changes exert significant control over forest carbon cycles. Therefore, preserving and enhancing the carbon sink function of old-growth forests in the face of climate change and disturbance may depend primarily on protecting existing large trees and soon-to-be large-diameter trees.