Biomass Distribution Research Articles

Plant diversity loss has limited effects on below‐ground biomass and traits but alters community short‐term root production in a species‐rich grassland

Abstract Many biodiversity–ecosystem functioning (BEF) experiments have shown enhanced productivity with biodiversity, often explained by niche differentiation and complementarity effects. Yet, most of these results are based on artificial plant assemblages, with a major focus on above‐ground productivity. Consequently, our comprehension of the BEF relationship in natural ecosystem and for below‐ground functions remains largely unknown. In this study, we simulated a long‐term non‐random species loss in a naturally diverse temperate meadow. We created a richness gradient spanning from 1 to more than 20 species per plot, removing the rare and sub‐ordinate species from the vegetation. After 3 and 6 years of experimental manipulation, soil cores were collected to investigate the effects of species removal on below‐ground biomass, vertical distribution of roots and root traits. We also used ingrowth cores to quantify the short‐term root production of plant communities. We investigated the consistency of below‐ and above‐ground responses to species removal. Consistent with above‐ground responses, species removal had little effect on root biomass and community root traits, except for a decrease in biomass in the uppermost soil layer (0–5 cm) found only after 6 years. Similarly, the vertical distribution of root biomass and traits was largely unaffected by diversity loss, suggesting little evidence for vertical niche differentiation. Nevertheless, species loss decreased the root production in spring (3 months), albeit this lower short‐term root production was diluted after a year, when monocultures of dominants almost matched the annual root production of controls. Synthesis. Our results from a non‐random species removal experiment revealed minimal impact of a realistic diversity loss on root biomass and traits, but a decrease in short‐term fine root production. These results challenge traditional BEF theory and the niche differentiation hypothesis, suggesting that dominant species primarily determine below‐ground biomass structure and characteristics. High diversity may only temporarily increase short‐term root production.

Evaluating Impact of Agricultural Land Use on CO₂ Sequestration and Oxygen Release: A Case Study in Aranyik Subdistrict, Thailand

This study investigates the impact of various agricultural land use practices on CO₂ sequestration and oxygen release in Aranyik Subdistrict, Mueang District, Phitsanulok Province, Thailand. The region, characterized by lowland plains and a network of canals, supports diverse agricultural activities, with rice paddies dominating the landscape. Our analysis revealed significant variability in biomass distribution and carbon sequestration potential across different land use types. Eucalyptus plantations demonstrated the highest CO₂ sequestration and oxygen release rates, highlighting their role in climate change mitigation. However, the ecological implications of such monocultures, including water consumption and soil health, warrant careful consideration. In contrast, other land use types, such as mixed grasslands, lime orchards, and rice fields, exhibited lower sequestration rates but are crucial for maintaining biodiversity and supporting sustainable land management. This study underscores the importance of integrated land use strategies that balance carbon storage with ecological health, providing valuable insights for regional land use policy and climate change mitigation efforts. Further research should explore temporal land use changes and their broader environmental impacts to enhance the sustainability of agricultural practices in the region.

Stand Age Affects Biomass Allocation and Allometric Models for Biomass Estimation: A Case Study of Two Eucalypts Hybrids

We studied the effects of stand age on the allocation of biomass and allometric relationships among component biomass in five stands ages (1, 3, 5, 7, and 8 years old) of two eucalypts hybrids, including Eucalyptus urophylla × E. grandis and E. urophylla × E. tereticornis, in the Leizhou Peninsula, China. The stem, bark, branch, leaf, and root biomass from 60 destructively harvested trees were quantified. Allometric models were applied to examine the relationship between the tree component biomass and predictor variable (diameter at breast height, D, and height, H). Stand age was introduced into the allometric models to explore the effect of stand age on biomass estimation. The results showed the following: (1) Stand age significantly affected the distribution of biomass in each component. The proportion of stem biomass to total tree biomass increased with stand age, the proportions of bark, branch, and leaf biomass to total tree biomass decreased with stand age, and the proportion of root biomass to total tree biomass first decreased and then increased with stand age. (2) There were close allometric relationships between biomass (i.e., the components biomass, aboveground biomass, and total biomass per tree) and diameter at breast height (D), height (H), the product of diameter at breast height and tree height (DH), and the product of the square of the diameter at breast height and tree height (D2H). The allometric relationship between biomass and measurement parameters (D, H, DH, D2H) could be applied to the biomass assessment of eucalypts plantation. (3) Allometric equations that included stand age as a complementary variable significantly improved the fit and enhanced the accuracy of biomass estimates. The optimal independent variable for the biomass prediction model varied according to each organ. These results indicate that stand age has an important influence on biomass allocation. Allometric equations considering stand age could improve the accuracy of carbon sequestration estimates in plantations.

Spatial Model of Carbon Stocks in Special Purpose Forest Area (KHDTK) Mungku Baru, Central Kalimantan Province, Indonesia

This study aims to estimate vegetation biomass and spatial distribution of carbon stocks in Special Purpose Forest Area (KHDTK) Mungku Baru, Palangka Raya City, Central Kalimantan Province, Indonesia. KHDTK Mungku Baru is a former logging area from the 1970s, which has undergone secondary succession and is dominated by pole and sapling levels. The approach used in this study involves remote sensing technology and field inventory data, which allows carbon stock calculations to be carried out quickly and accurately over a very large area. A linear regression algorithm was used to obtain a spatial model of carbon stocks using NDVI obtained from Landsat as a predictor. The developed model shows positive correlation results with an R2 value of 0.70; an Adjusted R2 value of 0.69 with a p-level < 0.05, and RMSE of 42 tons/ha. This carbon stock mapping results serve as a basis for formulating various management plans for KHDTK Mungku Baru regarding ecological, social, and economic aspects. Keywords: carbon stocks, normalized difference vegetation index, spatial model, special purpose forest area, vegetation biomass

Study on Salt-Ion Content and Biomass Distribution Characteristic of Different Organs of Poacynum pictum in Different Water–Salt Habitats

Study on Salt-Ion Content and Biomass Distribution Characteristic of Different Organs of Poacynum pictum in Different Water–Salt Habitats

The current state of the benthic communities in the area of the Cape Svyatoy settlement of the Iceland scallop in the Barents Sea

The aim. Assessment of the current state of the zoobenthos in the southern part of the Cape Svyatoy settlement of the Iceland scallop in five years after the finish of its commercial exploitation.Material and methods used. Analyzed material was sampled from the R/V «Professor Boyko» during a resource survey of the Icelandic scallop in the Barents Sea in September 2023. A complete quantitative taxonomic analysis of the Sigsbee trawl bycatches of bottom invertebrates was carried out at 85 stations within twelve-mile zone of the Cape Svyatoy settlement of the Icelandic scallop. Four indices were used for assessment of the macrobenthos ecological quality: Clark’s W-statistic, the predominant life strategy index DE, AMBI and M-AMBI indices.The results. The main characteristics of macrozoobenthos in the area of the Cape Svyatoy settlement of the Iceland scallop are described (taxonomic composition, distribution of species richness, diversity, total abundance and biomass, list of the most abundant species, characteristics and distribution of the main bottom communities). The level of average benthic biomass within the study area is estimated as lower than expected given the long preceding warm period. Based on comparison of 2016 and 2023 benthic data, the positive dynamics of the trophic structure of benthos are noted. According to results of bio-testing the ecological state of benthos, in the main part of the study area, is assessed as good and undisturbed, with the exception of area to southeast of Cape Svyatoy, where the lower values of ecological status, abundance and species diversity of benthos are caused by natural environmental conditions.Practical significance: The results of the study provides insight into the bottom communities’ recovery after intensive fishing pressure.

The trophic distribution of biomass in ecosystems with co-occurring wildlife and livestock

Trophic interactions regulate populations, but anthropogenic processes influence primary productivity and consumption by both herbivore and carnivore species. Trophic ecology studies often focus on natural systems such as protected areas, even though livestock globally comprise the majority of terrestrial vertebrate biomass. Here we explore spatial and temporal patterns in the distribution of biomass between plants, and large herbivores and carnivores (> 10 kg) in Norwegian rangelands, including both wildlife and livestock. We find high spatial variation in the relationship between plant and herbivore biomass, with both positive and negative divergence in observed biomass from expectations based on primary productivity. Meanwhile, despite recent partial recoveries in carnivore densities across Norway, carnivore biomass is still lower than expected based on herbivore biomass, even if livestock are excluded from the estimation. Our study highlights how temporal trends in both herbivores and carnivores reflect policy development. The role of livestock husbandry and wildlife management is thus key in determining realised biomass distributions in anthropogenically influenced ecosystems.

Enterobacter-inoculation altered the C, N contents and regulated biomass allocation in Reaumuria soongorica to promote plant growth and improve salt stress tolerance.

Soil salinization poses a significant ecological and environmental challenge both in China and across the globe. Plant growth-promoting rhizobacteria (PGPR) enhance plants' resilience against biotic and abiotic stresses, thereby playing a vital role in soil improvement and vegetation restoration efforts. PGPR assist plants in thriving under salt stress by modifying plant physiology, enhancing nutrient absorption, and synthesizing plant hormones. However, the mechanisms through which PGPR regulate the contents of carbon (C) and nitrogen (N), and biomass allocation of desert plant in response to salt stress is still unclear. This study explores the impact of PGPR on biomass allocation, C, and N contents of R. soongorica seedlings through a pot experiment. Strains P6, N20, and N21, identified as Enterobacter, were isolated from the rhizosphere of R. soongorica, and they exhibited various beneficial traits such as indole-3-acetic acid (IAA) production, phosphate solubilization, nitrogen fixation, and tolerance to up to 8% NaCl stress. We found that under NaCl stress, R. soongorica seedlings exhibit significant reductions in plant height, basal diameter, and root surface area (P<0.05). However, inoculation with strains P6, N20, and N21 reverses these trends. Compared to NaCl treatment alone, co-treatment with these strains significantly increases the biomass of roots, stems, and leaves, particularly root biomass, which increases by 99.88%, 85.55%, and 141.76%, respectively (P<0.05). Moreover, N contents decrease significantly in the roots, stems and leaves, C contents increase significantly in the roots and leaves compared to NaCl treatment (P<0.05). Specifically, N contents in roots decrease by 14.50%, 12.47%, and 8.60%, while C contents in leaves increase by 4.96%, 4.45%, and 4.94%, respectively (P<0.05). Additionally, stem and leaf biomasses exhibit a significant positive correlation with C contents and a significant negative correlation with N contents in these tissues. In conclusion, inoculation of Enterobacter strains enhanced the biomass of R. soongorica seedlings, regulated the biomass distribution, and modifies C and N contents to promote plant growth and improve salt stress tolerance. This study provides a novel adaptive strategy for the integrated use of PGPR and halophytes in saline-alkali soil improvement and vegetation restoration efforts.

Harnessing the Power of Marine Biomass‐Derived Carbon for Electrochemical Energy Storage

ABSTRACTMarine biomass presents a promising and sustainable pathway for advancing electrochemical energy storage (EES) technologies. This review provides a comprehensive, state‐of‐the‐art examination of marine biomass‐derived carbon as a high‐performance electrode material for EES devices. The global abundance and distribution of marine biomass are discussed, followed by a detailed investigation into the chemical composition of various aquatic organisms. Key conventional synthesis methods for converting marine biomass into carbon are critically analyzed, emphasizing strategies to enhance electrochemical performance. Diverse applications of marine biomass‐derived carbon in EES are explored, offering an in‐depth evaluation of its electrochemical activity and mechanical properties in relation to structural variations. A dedicated section addresses the “Technology to Market” transition, presenting a strategic overview of the commercial potential of this material. Lastly, the review identifies current challenges and future opportunities, emphasizing the need for continued research into both structural innovations and scalable solutions to advance sustainable energy storage systems, addressing critical environmental and economic issues.

Quantifying rice dry biomass to determine the influence of straw burning on BC and NO2 emissions in the Hanoi metropolitan region.

The urban setting notwithstanding, rice cultivation prevails on the outskirts of Hanoi, with the burning of rice straw in the fields posing a significant challenge. Therefore, it is crucial to conduct spatial mapping of rice distribution, assess dry biomass, and determine emissions from rice straw burning within Hanoi city. The efficacy of the deep convolutional neural networks (DCNN) model has been evident in accurately mapping the spatial distribution of rice in Hanoi, where rice cultivation extensively thrives in suburban areas. In the tropical climate of Vietnam, data derived from synthetic aperture radar (SAR) could serve as a valuable resource for mapping rice fields. Additionally, the amalgamated model, Ant Colony Optimization-eXtreme Gradient Boosting (ACO-XGBoost), could serve as a potent instrument in gauging the aboveground biomass (AGB) of rice within this urban center. The current research reveals the spatial distribution of rice biomass in Hanoi city. Among the six levels of the rice biomass distribution map, the majority of regions in Hanoi city were dominated by the fifth tier, ranging between 3.0 and 4.0 kg/m2. This emerges as a pivotal source of emissions impacting the atmospheric quality of the city. It should be emphasized that the incidence of rice straw burning remains substantial, exceeding 80% in the monitored districts of Hanoi city, notably higher in proximity to the city center. These findings serve a significant function for management and policy making to generate data and calculate air pollution levels in Hanoi.

Dynamic stochastic model of allometric equations and cumulative distribution for biomass-carbon in Pinus hartwegii Lindl., facing climate change

Objective: to construct a dynamic stochastic model with validated biospheric-interaction, estimating allometric equations for the total volumetric increase and cumulative distribution of biomass for Pinus hartwegii Lindl in the states of Mexico and Puebla, considering climate change. Design/ Methodology/ Approach: the methodology included the use of SiBiFor numerical databases, NASA Power data, Ordinary Least Squares mathematical models, the Random-Forest software, Ridge model with regression, R algorithms and Newton volumetric estimation equations. Results: estimated allometric equations were obtained for the total volume of trees in 2023, highlighting the importance of linear regression models and the validity of the variables used. Newton's mathematical equations and theoretical models for excurrent tree-form types were found to have the best accuracy in estimating the total volume of the barked tree. Limitations of the study/ Implications: this study has limitations in terms of generalization to other forest types and the availability of data in Mexico. However, it highlights the importance of understanding forest responses to environmental changes and the need for validated dynamic stochastic models to estimate allometric equations and assess carbon sequestration. Findings/ Conclusions: this study highlights the importance of understanding and assessing the carbon storage capacity of forests, especially in the context of climate change. In addition, it underlines the usefulness of linear regression models and variable validation to estimate carbon sequestration in Pinus hartwegii forests.

Effects of drought and salt stress on the root phenotype of wheat seedlings and underlying gene expression analysis.

In our previous study, three TaPSK genes highly expressed in the roots of wheat were screened. To explore the effects of adverse stresses on the wheat root phenotype and the expression of TaPSK3, TaPSK9 and TaPSK10, we measured the phenotypic parameters of the JM22 root system at the seedling stage after treatment with different concentrations of NaCl and PEG6000. Additionally, the relative expression levels of TaPSK3, TaPSK9, and TaPSK10 were analyzed via RT-qPCR within 72 h of treatment with 150 mM NaCl and 30% PEG6000. The results revealed that drought and salt stress significantly inhibited phenotypic parameters such as total root length, root surface area, root biomass distribution estimation and root tip number in wheat. Notably, salt stress causes wheat roots to germinate more root hairs. The expression of TaPSK3 did not change significantly during salt stress but was upregulated approximately five-fold at 12 h of drought stress. The gene expression levels of TaPSK9 and TaPSK10 were upregulated to varying degrees but gradually returned to normal at 72 h. These results show that when wheat encounters stresses, the expression of TaPSK genes is upregulated to promote root growth and ensure the normal growth and development of plants. This study provides data and theoretical support for further study of TaPSK gene function and cultivation of high-quality wheat plants with strong stress resistance.

Distribution of zooplankton biomass in the Shatt Al-Arab River and Shatt Al-Basra Canal, Southern Iraq

Zooplankton is the important component of aquatic ecosystems. These organisms are important biological indicator of water quality of aquatic ecosystem due to their response to the environmental changes. In this study, we investigated distribution of zooplankton biomass in the Shatt Al-Basra Canal and Shatt Al-Arab River. Zooplankton samples were collected from two stations in the Shatt Al-Basra Canal, before (S1) and after (S2) the dam, and two stations in the Shatt Al-Arab River, Al-Siba (S3) and Al-Faw (S4). The biomass of zooplankton in the Shatt Al-Basra Canal varied between 23.102 - 520.875 mg/m3 in terms of wet weight and 3.787 - 102.132 mg/m3 in terms of dry weight at two stations (before the dam and after the dam) during the period of January and May, respectively. The displacement volume and standing crops also showed variations of the biomass of zooplankton. In the Shatt Al-Basra Canal, the range was from 0.06 ml/m3 and 3.9 mgC/m3 during January at S1 to 1.083 ml/m3 and 70.395 mgC/m3 during May at S2. While in the Shatt Al-Arab River, the biomass of zooplankton in terms of wet weight ranged from 10.671 - 655.78 mg/m3 during December at S3 (Al-Siba) and may at S4 (Al-Faw) respectively. In terms of dry weight, the biomass ranged from 1.423 to 168.149 mg/m3 in S3 during the December and in S4 during May respectively. In terms of displacement volume and standing crops, they ranged from 0.03 ml/m3 to 1.95 mgC/m3 during December at S3 to 1.819 ml/m3 and 118.235 mgC/m3 during February at S4.

Managing the Dissolved Oxygen Balance of Open Atlantic Salmon Sea Cages: A Narrative Review

ABSTRACTAs Atlantic salmon depend on dissolved oxygen (DO) to survive and grow, managing DO is essential for welfare and growth. However, the dynamics of DO in the open sea cages are complex, caused by a range of factors that interact and create compounding effects. To understand DO dynamics, two pillars of knowledge are essential: the supply of DO to the cages and the consumption of DO in the cages. The components of these two pillars vary greatly across both time and space, with factors including ambient sea temperature and current, density stratification, fish size, health and metabolism, biomass density and distribution, topography, production routines and farm configuration. In the production environment, these factors often interact, making related analyses on effects, causality and effective management highly challenging. Exacerbating matters, existing knowledge is fragmented across multiple disciplines, making it challenging for end‐users to access. Using sensors is often necessary to understand and manage the complexity of DO, and the interest to implement digital technologies to aquaculture operations and utilize big data analyses is growing, but to succeed in the application, an in‐depth understanding of the relevant dynamics is necessary. Consequently, this review is produced to compile existing knowledge on the many factors that influence the consumption or supply of DO in the sea cages, and their relationship to each other. In this narrative review, we explore the known interactions and compounding effects between these factors, and synthesize it in a causal diagram for holistic analyses of the DO balance.

Accuracy Assessment of Advanced Laser Scanner Technologies for Forest Survey Based on Three-Dimensional Point Cloud Data

Forests play a crucial role in carbon sequestration and climate change mitigation, offering ecosystem services, biodiversity conservation, and water resource management. As global efforts to reduce greenhouse gas emissions intensify, the demand for accurate spatial information to monitor forest conditions and assess carbon absorption capacity has grown. LiDAR (Light Detection and Ranging) has emerged as a transformative tool, providing high-resolution 3D spatial data for detailed analysis of forest attributes, including tree height, canopy structure, and biomass distribution. Unlike traditional manpower-intensive forest surveys, which are time-consuming and often limited in accuracy, LiDAR offers a more efficient and reliable solution. This study evaluates the accuracy and applicability of advanced LiDAR technologies—drone-mounted, terrestrial, and mobile scanners—for generating 3D forest spatial data. The results show that the terrestrial LiDAR achieved the highest precision for diameter at breast height (DBH) and tree height measurements, with RMSE values of 0.66 cm and 0.91 m, respectively. Drone-mounted LiDAR demonstrated excellent efficiency for large-scale surveys, while mobile LiDAR offered portability and speed but required further improvement in accuracy (e.g., RMSE: DBH 0.76 cm, tree height 1.83 m). By comparing these technologies, this study identifies their strengths, limitations, and optimal application scenarios, contributing to more accurate forest management practices and carbon absorption assessments.

Assessing Carbon Sequestration and Biomass Distribution across Diverse Land Use Types in Ban Krang Subdistrict, Phitsanulok Province

This study investigates carbon dioxide (CO₂) sequestration and biomass distribution across various plant components and land use types in Ban Krang Subdistrict, Mueang District, Phitsanulok Province, with the goal of enhancing carbon management strategies. Field surveys were conducted using 14 plots of 40x40 meters to quantify biomass and estimate CO₂ sequestration across different vegetation types. The findings reveal an average CO₂ sequestration of 122.81 Ton ha⁻¹, with aboveground biomass, particularly stems, contributing the most to carbon storage. Notably, abandoned perennial crops and mixed perennial crops demonstrated the highest sequestration rates, at 657.94 Ton ha⁻¹ and 613.00 Ton ha⁻¹, respectively. In contrast, agricultural lands such as rice paddies and cassava plantations exhibited the lowest sequestration rates, though rice paddies contributed the highest total CO₂ sequestration, amounting to 61,119.71 Tons, due to their extensive area. The study highlights the critical role of diverse and dense vegetation, particularly perennial crops, in maximizing carbon sequestration. It also underscores the potential for improving carbon storage in agricultural lands through better land management practices. The results suggest that targeted strategies should prioritize high-sequestration land use types while also enhancing carbon storage in low-sequestration areas. By optimizing land use and management practices, the region can significantly increase its carbon storage capacity, contributing to climate change mitigation and promoting long-term ecological sustainability. These insights are crucial for formulating effective carbon management strategies in Ban Krang Subdistrict, as well as in other comparable regions.

Modelling global mesozooplankton biomass using machine learning

Mesozooplankton are a crucial link between primary producers and higher trophic levels and play a vital role in marine food webs, biological carbon pumps, and sustaining fishery resources. However, the global distribution of mesozooplankton biomass and the relevant controlling mechanisms remain elusive. We compared four machine learning algorithms (Boosted Regression Trees, Random Forest, Artificial Neural Network, and Support Vector Machine) to model the spatiotemporal distributions of global mesozooplankton biomass. These algorithms were trained on a compiled dataset of published mesozooplankton biomass observations with corresponding environmental predictors from contemporaneous satellite observations (temperature, chlorophyll, salinity, and mixed layer depth). We found that Random Forest achieved the best predictive accuracy with R2 and RMSE (Root Mean Standard Error) of 0.57 and 0.39, respectively. Also, the global distribution of mesozooplankton biomass predicted by the Random Forest model was more consistent with the observational data than other models. We used the Random Forest model to create a global map of mesozooplankton biomass which serves as a reference for validating process-based ecosystem models. The model outputs confirm that environmental factors, especially surface Chl a, a proxy for prey availability, significantly correlate with the spatiotemporal distribution of mesozooplankton biomass. The scaling relationship between the mesozooplankton biomass and Chl a can be used as an emergent constraint for model validation and development. Moreover, our model predicts that the global mesozooplankton biomass will decrease by 3% by the end of this century under the “business-as-usual” scenarios, potentially reducing fishery production and carbon sequestration. Our study contributes to predicting global mesozooplankton biomass and provides deep insights into the underlying environmental impacts on the distribution of mesozooplankton biomass.

Fuel models for forest soil cover plant

Abstract This study presents the development and application of forest fuel models to predict fire behaviour in different forest habitats, focusing on biomass distribution, moisture variability and the calorific value of soil cover components. On analysing forest fire data from 2007 to 2013, we identified high-risk habitats, especially in younger stands and in stands dominated by Scots pine. The variability of moisture in the different soil cover components, including litter and deadwood, was statistically analysed; it revealed significant dependencies on litter moisture and rain-free intervals. These dependencies allowed the creation of equations to accurately predict fuel load and moisture content based on stand age, habitat type and environmental conditions. Using the calorific value measurements with an average calorific value of 18,920 kJ/kg for dry soil cover materials, fuel models were developed to estimate the potential intensity of fires. The models categorise the biomass into decayed, dead and live components and take into account key variables such as bulk density and moisture content that influence fire spread. Data-driven categorisation enables fire risk assessments at the compartment level, which increases accuracy compared to more comprehensive district-level assessments. Applications of fuel models include mapping the spatial distribution of biomass by fuel type, creating fire hazard maps and optimising firefighting infrastructure. These models support planning and operations by enabling forest managers to visualise high-risk areas and predict fire behaviour based on real-time meteorological data. The models are a critical step towards a more effective firefighting system that provides fine-grained, actionable insights into fire risk at the local level.

Deployment of power-to-protein technology in Ethiopia to provide drought-related emergency relief and mitigate food insecurity

Food insecurity in Ethiopia is an immediate humanitarian crisis that is expected to worsen due to population growth and climate change. This study applied GIS-based approaches to evaluate the feasibility of deploying an emergent type of single-cell protein (SCP) technology to supplement the nutritional needs of Ethiopian citizens who are most vulnerable to drought. The technology—power-to-protein (PtP)—uses H2 and O2 from water electrolysis and CO2 from woody biomass combustion in a two-stage bioprocess to produce nutrient-rich protein powder for human consumption. Population density, land use, and other geographical data were used to identify optimal site locations for these PtP systems based on two deployment strategies: large centralized plants vs. small decentralized units. The model also accounted for biomass availability, collection, and distribution logistics. The analysis revealed three sites that are both (highly) vulnerable/food-insecure and accessible within walking distance. The identified sites are proximate to the urban areas of Mekele in northern Ethiopia, Addis Ababa in central Ethiopia, and Hawasa south of Addis Ababa. If centralized PtP were deployed, the protein requirements of these populations could be sustained for several months, assuming a modest biomass collection radius of 35 km. Decentralized PtP deployment was similarly effective, requiring a distribution density of 5.4–11.0 PtP units per km2 under conservative estimates and 0.76–1.1 units per km2 under optimistic estimates. Lastly, a theoretical comparison showed that PtP is more efficient than conventional agricultural food production regarding biomass-to-protein conversion yields. Overall, our study suggests that PtP technology would be a feasible approach to supplement the nutritional needs of Ethiopian people in times of drought-related emergencies. However, given logistical limitations and considering social preference factors, it would be more practical to implement PtP in conjunction with standard emergency food aid measures.

Investigation of Nitrogen Fixation Efficiency in Diverse Alfalfa Varieties Utilizing Sinorhizobium meliloti LL2

To investigate the precise and efficient symbiosis between Sinorhizobium meliloti LL2 and different alfalfa varieties, we conducted experiments using eight alfalfa varieties along with the S. meliloti LL2. Our objective was to identify highly effective symbiotic combinations by analyzing differences in nodulation, nitrogen fixation, and biomass accumulation. The results revealed that Gannong NO.9 had higher values for single effective root nodule weight (1.30 mg) and the number of infected cells in root nodules (2795) compared to other varieties (p &lt; 0.05). Additionally, Gannong NO.9 exhibited the highest nitrogenase activity (0.91 μmol·g−1·h−1), nitrogen fixation percentage (67.16%), and amount of nitrogen fixation (18.80 mg/pot). Moreover, there was a significant 26.50% increase in aboveground tissue nitrogen accumulation compared to the control check (CK) (p &lt; 0.05). Furthermore, underground tissue showed excellent values for nitrogen accumulation (35.68 mg/plant) and crude protein content (17.75%) when compared with other treatments. The growth of plants was demonstrated by the combined impact of nodulation and nitrogen fixation. The distribution of biomass after nitrogen fixation was compared to the control group (p &lt; 0.05) to investigate accumulation. The eight combinations of symbiotic nitrogen fixation (SNF) were classified into six distinct types based on their significantly different biomass growth rates compared to CK. ① Aboveground accumulation type: Gannong NO.9 (there was a 24.31% increase in aboveground dry weight); ② aboveground and underground accumulation type: Qingshui (the aboveground dry weight increased by 135.94%, while the underground dry weight grew by 35.26%); ③ aboveground accumulation, underground depletion type: Gannong NO.5 ( ); ④ zero-growth type (there was no significant difference in dry weights, both above and below ground, compared to CK): WL168HQ, WL319HQ and Longzhong; ⑤ aboveground and underground depletion type: WL298HQ (the aboveground dry weight decreased by 29.29%, while the underground dry weight decreased by 20.23%); ⑥ underground depletion type: Gannong NO.3 (the underground dry weight showed a decrease of 34.49%); no type with aboveground consumption and underground accumulation was found. The study clarified the optimal combination of LL2 and Gannong NO.9, finding that biomass accumulation after symbiotic nitrogen fixation is variety-dependent.