Aboveground Biomass Production Research Articles

How global sensitive is the AquaCrop model to input parameters? A case study of silage maize yield on a regional scale

IntroductionAquaCrop is a water-driven crop growth model that simulates aboveground biomass production in croplands. This study aimed to identify the driving parameters of the AquaCrop model for the model calibration and simplification to fill the research gap in intermediate environmental conditions between sub-tropical sub-humid and temperate sub-humid climates for silage maize.MethodsTo this end, we applied global sensitivity analysis (GSA) by combining the Morris method and the Extended Fourier Amplitude Sensitivity Test (EFAST) on crop yield output. The process involved a field sampling of soil and crop of silage maize carried out in the agricultural fields of Ghale-Nou, southern Tehran, Iran, in the summer of 2019 in order to measure certain model parameters.Results and discussionIn compliance with the Morris method, 30 parameters were identified as the least sensitive, while results from the EFAST test showed 9 parameters as contributing to the highest sensitivities in the model. The results clearly point to the capacity of employing a combination of both methods to attain a more efficient model calibration. Particular root, soil, canopy development, and biomass production parameters were influential and merit attention during calibration. Instead, parameters describing crop responses to water stress were acting rather insensitive in this study condition. The insights gained from this study, i.e., assessing parameter ranges and distinguishing between less sensitive and more sensitive parameters based on environmental and crop conditions, have the potential to be applied to other crop growth models with caution.

Assessing the impact of multi-year droughts on German forests in the context of increased tree mortality

Forests play a crucial role in climate regulation and societal well-being. Despite their significance, the increasing frequency of droughts poses a severe threat to forest ecosystems, impacting carbon sequestration and forest stability. In Germany, the unprecedented 2018–2020 drought resulted in extensive tree mortality and damaged wood volume, with lasting effects observed in subsequent years. As climate models project a continuation of such droughts, understanding the impact of droughts on forests becomes imperative. However, it is unclear how forests will evolve in the future if the drought duration continues to increase.This study employs a forest model to analyze the impact of droughts across various German forest types, focusing on the duration of drought periods and their influence on forest productivity. By utilizing an individual-based forest growth model and national forest inventories, the study addresses critical knowledge gaps regarding the effects of multi-year droughts on biomass and productivity across various forest types, including monocultures and mixed forests. The simulations consider a drought-induced large increase in tree mortality caused by factors such as pest infestations and diseases across Germany.Our simulation results reveal a declining aboveground biomass and gross primary production (GPP) for all simulated drought scenarios, including the three- and six-year drought. GPP is reduced by 46 % in the 3-year drought scenario and by 58 % in the 6-year drought scenario. Notably, prolonged droughts lead to cumulative losses, with a saturation effect in drought scenarios exceeding eight years. Forest stand composition influences these impacts, with greater GPP losses in low-biomass stands. Furthermore, different forest types exhibit varying responses. Monocultures and even-sized forests (mostly planted and managed forests) are more sensitive to drought than mixed and uneven-sized forests.The results provide valuable insights into forest resilience and ecosystem responses to increasingly frequent and prolonged droughts, highlighting the importance of understanding the effects of drought on monocultures and mixed forests to inform future forest management strategies. Modelling the influence of biotic factors on forest dynamics in a process-based manner remains a challenge that requires future research.

Drainage Practice of Rice Paddies as a Sustainable Agronomic Management for Mitigating the Emission of Two Carbon-Based Greenhouse Gases (CO2 and CH4): Field Pilot Study in South Korea

Rice is one of the staple foods in Asian countries, and rice paddies are significant sources of greenhouse gas (GHG) emissions in agricultural sectors. In addition, drainage practice has been recognized as a key factor influencing both rice production and GHG emissions. In this field pot study, the effect of drainage method (e.g., intermittent drainage (ID) and continuous flooding (CF)) on GHG (CO2 and CH4) emissions was determined from three Korean paddies (BG, MG, and JS series), varying soil properties such as soil texture, labile carbon, and mineral types. The emission of GHGs was evidently influenced by the drainage, depending on the paddy’s redox (Eh) shift upon flooding events. The Eh decline upon flooding was slower in JS pot, where pore-water concentration of ferric and sulfate ions is the highest (~up to 3-fold) among three paddies. MG pot was 2- to 3-fold more percolative than the others and the Eh drop during the flooding period was the smallest (staying above −50 mV). In ID treatment, CH4 emission (t CO2-eq ha−1 y−1) was reduced in a wide range by 5.6 for JS pot, 2.08 for BG pot, and 0.29 for MG pot relative to CF, whereas CO2 emissions (t CO2-eq ha−1 y−1) were increased by 1.25 for JS pot, 1.07 for BG pot, and 0.48 for MG pot due to the enhanced oxidation of labile carbon. Grain yield and aboveground biomass production from ID were no less than those from CF (p < 0.05). Consequently, the increase in global warming potential (Σ GWP) by ID varied as the order of JS (37%) > BG (14%) > MG (~0%) pots, and the negligible effect observed for MG pot is due to the equivalent trade-off between CO2 and CH4. The different benefits of drainage practices among paddy pots is due to the redox response of paddy systems. The findings will be helpful to promote the efficacy of drainage practice on mitigating GHG emissions for the sustainable agronomic management of rice paddies in response to climate change.

Above‐ground biomass retrieval with multi‐source data: Prediction and applicability analysis in Eastern Mongolia

AbstractGrassland aboveground biomass (AGB) is a key variable to measure grassland productivity, and accurate assessment of AGB is important for optimizing grassland resource management and understanding carbon, water, and energy fluxes. Current approaches on large scales such as the Mongolian Steppe Ecosystem often combine field measurements with optical and/or synthetic aperture radar (SAR) data. Meanwhile, especially the representativeness of the field measurements for large‐scale analysis have seldom been accounted for. Therefore, we provide the first remotely sensed AGB product for central and Eastern Mongolia which (1) uses random forest (RF), (2) is fully validated against over 600 field samples, and (3) applies a novel method, dissimilarity index (DI), to derive the area of applicability of the model with respect to the training data. Therefore, different remote sensing data sources such as multi‐scale and multi‐temporal optical images—Worldview 2 (WV2), Sentinel 2 (S2), and Landsat 8 (L8) in combination with SAR data are tested for their suitability to provide an area‐wide estimation on large scale. The results showed that the AGB prediction by combining Sentinel 1 (S1) and S2 using RF had the highest accuracy. Furthermore, the model was applicable to at least 72.61% of the steppe area. Areas where the model was not applicable are mostly distributed along the edges of grassland. This study demonstrates the potential of combining Sentinel‐derived indices and machine learning to provide a reliable AGB prediction for grassland for extremely large ecosystems with strong climatic gradients.

Evaluation of optical and microwave-derived vegetation indices for monitoring aboveground biomass over China

ABSTRACT The microwave-derived vegetation optical depth (VOD) products were used to monitor aboveground biomass (AGB) at regional to global scales, but the ability of VOD to monitor AGB in China is uncertain. This study evaluated the sensitivity of four VOD products (e.g. L-VOD, IB-VOD, LPDR-VOD, and Liu-VOD) and optical vegetation indices (VI) (e.g. NDVI, EVI, LAI, and tree cover from MODIS) to the AGB across China. Our results showed tree cover product has the highest spatial agreement with reference AGBs (indicated by the median correlation value of 0.85), followed by L-VOD (with a median correlation value of 0.80), which performs better than other VIs and VODs. Further comparisons between reference and estimated AGB computed using the fitted logistic regression showed that AGB estimations from tree cover and L-VOD outperformed the estimations from other VIs and VODs over most vegetation types (except forest), indicated by the higher median correlation value of 0.86 and 0.83 and lower RMSD of 23.9 and 27.3 Mg/ha, respectively. The good performance of tree cover could be partly due to that tree cover product is not independent from the reference AGBs. The good performance of L-VOD can be explained by its higher sensitivity to the vegetation characteristics of the entire canopy (including woody component), relative to other VODs and VIs. Among the six reference AGB products, Saatchi-WT and Saatchi-RF products were found to have the best correlations with VIs and VODs. This study demonstrates that microwave VODs, particularly L-VOD, are effective proxies for large-scale monitoring of vegetation AGB in China.

Tree mortality and recruitment in secondary Andean tropical mountain forests along a 3000 m elevation gradient.

This study addresses the understudied dynamics of mortality and recruitment in Tropical Mountain forests, critical determinants of forest structural processes and biomass turnover. We examine how these demographic processes change with elevation and varying degrees of forest recovery by utilizing two forest censuses (2015 and 2019) from 16 plots (0.36 ha) across a 600-3500 m asl elevation gradient in the Ecuadorian Andes. Employing multivariate PCA analyses, we characterize successional forest dynamics and explore relationships between demographic rates, elevation, and indicators of forest recovery using standard linear regression and generalized additive models (GAMs). Contrary to our hypothesis, mortality exhibits a unimodal response, peaking at mid-elevations, with no significant relationship to above-ground biomass productivity (AGBp). In our successional forests, dominance by fast-growing species alters expected patterns, leading to increased mortality rates and AGBp, particularly at low-mid elevations. Forest recovery emerges as a significant driver of mortality and the sole predictor of recruitment, especially across different recovery statuses. Although forest recovery doesn't impact mortality rates, it elucidates the identity of declining species in forests with varying recovery degrees. Our findings underscore that while forest recovery does not alter mortality rates, it provides critical insights into understanding which species are affected under varying recovery conditions. Recruitment, primarily driven by successional dynamics, exhibits higher rates in sites with less recovery. Furthermore, we demonstrate the utility of forest structure indicators, such as above-ground biomass, in inferring successional dynamics when the time since the last disturbance is unknown. The study emphasizes the importance of considering disturbances in comprehending the intricate interplay between the environment and forest dynamics in secondary forests.

Changes in Relationship between Forest Biomass Productivity and Biodiversity of Different Type Subtropical Forests in Southern China

Forest productivity is influenced by various factors, including biodiversity, environmental factors, functional traits, and forest types. However, the relative importance of these factors in determining the productivity of subtropical forests in southern China remains controversial. In this study, we analyzed a dataset of 24 forest plots from four subtropical forest types in the Nanling Mountains with the main goal of identifying and quantifying the relative contribution of the main driving factors of forest productivity in these forests. Generalized linear regression and structural equation modeling were used to examine the relationship between forest biomass productivity (aboveground, belowground and total), biodiversity (taxonomic diversity, phylogenetic diversity and functional diversity), and environmental variables (i.e., physiography and climate). The results indicated that both environmental factors and biodiversity played pivotal roles in explaining the biomass productivity of the Nanling subtropical forests. Environmental factors had the greatest influence on total productivity, while the impacts of different types of biodiversity on various productivity components (aboveground and belowground) varied notably. Taxonomic diversity showed the strongest positive effect on the aboveground and belowground biomass productivity. However, phylogenetic and functional diversity had negative effects on productivity. Furthermore, these relationships also exhibited variations when considering different altitude gradients, with low altitudes generally leading to negative biodiversity–productivity correlations. We contextualized our results regarding the three state-of-the-art theories about biodiversity–productivity relationships (selection probability, niche complementarity, and biomass ratio) and concluded that both selection probability and niche complementarity are the driving mechanisms of productivity in the subtropical forests of the Nanling Mountains. This study offers valuable insights into the functioning and biodiversity mechanisms of subtropical forest ecosystems in southern China.

Contrasting drivers of aboveground woody biomass and aboveground woody productivity in lowland forests of Colombia

The relative importance of abiotic and biotic factors in shaping forest biomass stocks and fluxes remains a controversial issue. Here, using data gathered from 39 1 ha plots located in flooded and terra firme mature tropical lowland forests of the Amazon and Orinoquia regions of Colombia, we evaluated the importance of climate, soil fertility, and flooding, as well as tree taxonomic/phylogenetic diversity and forest structural properties, in determining the aboveground biomass stocks (AGB; Mg ha−1) and aboveground woody productivity (AWP; Mg ha−1 year−1). Using information‐theoretic multimodel inference and variance partitioning we found that forest structural features such as the number of trees with diameter at breast height ≥ 70 cm, and wood density, are the main drivers of variation in AGB. However, taxonomic diversity also contributes to AGB because it is associated with more large trees in these forests. In contrast, the key drivers of AWP in these forests were soil P and Mg concentrations, with no significant effects of diversity indices. These findings emphasize the need to include major soil cations other than N and P (e.g. Mg) in experimental studies to improve our understanding about the extent to which soil fertility can modulate increases in forest AWP due to climate change. Terra firme forests had higher AGB stocks than flooded forests, but both had similar AWP; and we found similar results for the drivers of AGB and AWP between flooded and terra firme forests. Our results provide limited evidence for strong effects of plant diversity on AGB or AWP. Therefore, we call for caution on generalizations of nature‐based initiatives aiming to preserve diversity based on maximizing carbon stocks and productivity, due to the complex nature of the processes controlling carbon accumulation and carbon fluxes in tropical forests.

Drought alters aboveground biomass production efficiency: Insights from two European beech forests

The fraction of photosynthetically assimilated carbon that trees allocate to long-lasting woody biomass pools (biomass production efficiency – BPE), is a key metric of the forest carbon balance. Its apparent simplicity belies the complex interplay between underlying processes of photosynthesis, respiration, litter and fruit production, and tree growth that respond differently to climate variability. Whereas the magnitude of BPE has been routinely quantified in ecological studies, its temporal dynamics and responses to extreme events such as drought remain less well understood. Here, we combine long-term records of aboveground carbon increment (ACI) obtained from tree rings with stand-level gross primary productivity (GPP) from eddy covariance (EC) records to empirically quantify aboveground BPE (= ACI/GPP) and its interannual variability in two European beech forests (Hainich, DE-Hai, Germany; Sorø, DK-Sor, Denmark). We found significant negative correlations between BPE and a daily-resolved drought index at both sites, indicating that woody growth is de-prioritized under water limitation. During identified extreme years, early-season drought reduced same-year BPE by 29 % (Hainich, 2011), 31 % (Sorø, 2006), and 14 % (Sorø, 2013). By contrast, the 2003 late-summer drought resulted in a 17 % reduction of post-drought year BPE at Hainich. Across the entire EC period, the daily-to-seasonal drought response of BPE resembled that of ACI, rather than that of GPP. This indicates that BPE follows sink dynamics more closely than source dynamics, which appear to be decoupled given the distinctive climate response patterns of GPP and ACI. Based on our observations, we caution against estimating the magnitude and variability of the carbon sink in European beech (and likely other temperate forests) based on carbon fluxes alone. We also encourage comparable studies at other long-term EC measurement sites from different ecosystems to further constrain the BPE response to rare climatic events.

ANÁLISIS DEL CRECIMIENTO DE CULTIVARES DE CAÑA DE AZÚCAR A TRAVÉS DE LA EVALUACIÓN DEL RENDIMIENTO Y MATERIA SECA

<p><strong>Background:</strong> The production of aboveground biomass of sugarcane is mainly due to the interactions between edaphic, climatic, and genetic factors. Objective: To evaluate the growth of three sugarcane cultivars through the evaluation of yield and dry matter accumulation, during the template and soca cultivation cycles, in the supply area of the Santa Rosalía de la Chontalpa Sugar Mill. <strong>Methodology:</strong> In the supply area of the Santa Rosalia de la Chontalpa Sugar Mill (ISRCH), Tabasco, an experiment was established under rainfed conditions, during two cycles (plantilla and soca), with three cultivars (MEX69-290, MEX79-431 and CP72-2086), established in a eutric Fluvisol soil. In each plot, five observation sites of 30 x 30 m were set up, in which the production of stems and biomass was determined.<strong> Results:</strong> In the plant cycle, the cane yield at 450 days after sowing (DAS) followed the following order CP72-2086> MEX79-431> MEX69-290 with 144.73, 130.09 and 94.18 t ha<sup>-1</sup>, respectively. On the contrary, in ratoon 360 days after harvest (DAH), MEX69-290 presented higher stem yield. In ratoon cycle, the stems yield decreased 14.5, 30.9 and 32.5% for MEX69-290, MEX79-431 and CP72-2086, respectively, compared to the plant cycle. The maximum absolute growth rate reached by the evaluated cultivars was 187, 192 and 262 kg ha<sup>-1</sup> day<sup>-1</sup> at 210 DAS in the plant cycle and 193, 177 and 151 kg ha<sup>-1</sup> day<sup>-1</sup> at 180 DAH in ratoon cycle for MEX69-290, CP72-2086 and MEX79-431, respectively. <strong>Implications:</strong> This allows knowing the growth rate of sugarcane cultivation in the humid tropics. <strong>Conclusions:</strong> The yield and harvest index of sugarcane varies with respect to the age of the crop (Cycle) and the cultivar.</p>

Decadal forest mensuration cycle significantly underestimates net primary production in dense young beech stands

The early development of naturally regenerated forest stands is highly dynamic and includes rapid shifts in productivity and mortality. To characterise the growth dynamics in the initial decades, we assessed aboveground biomass stocks (Sab),aboveground biomass productivity (DPab), and aboveground biomass mortality (DMab) in five naturally regenerated European beech stands located in the Inner Western Carpathians. We developed allometric models for aboveground biomass compartments based on a sample of 262 trees. We also established five circular sampling plots within each stand and, for 15 years, carried out annual measurements of stem diameter at the base and height for all trees within the sampling plots. We then utilised the allometric models to calculate annual biomass accumulation in aboveground biomass compartments on an area basis. Our findings show that, despite the declining contribution of foliage to the total aboveground stock, about a quarter of annual net primary production in young beech stands enters the dead biomass pool due to leaf fall and tree mortality. The growth dynamics and biomass allocation patterns of young beech forests necessitate the development of specific allometric models to describe their growth and carbon capture processes.

Estimation of Aboveground Biomass for Different Forest Types Using Data from Sentinel-1, Sentinel-2, ALOS PALSAR-2, and GEDI

Forest aboveground biomass (AGB) is integral to the global carbon cycle and climate change study. Local and regional AGB mapping is crucial for understanding global carbon stock dynamics. NASA’s global ecosystem dynamics investigation (GEDI) and combination of multi-source optical and synthetic aperture radar (SAR) datasets have great potential for local and regional AGB estimation and mapping. In this study, GEDI L4A AGB data and ground sample plots worked as true AGB values to explore their difference for estimating forest AGB using Sentinel-1 (S1), Sentinel-2 (S2), and ALOS PALSAR-2 (PALSAR) data, individually and in their different combinations. The effects of forest types and different true AGB values for validation were investigated in this study, as well. The combination of S1 and S2 performed best in forest AGB estimation with R2 ranging from 0.79 to 0.84 and RMSE ranging from 7.97 to 29.42 Mg/ha, with the ground sample plots used as ground truth data. While for GEDI L4A AGB product working as reference, R2 values range from 0.36 to 0.47 and RMSE values range from 31.41 to 37.50 Mg/ha. The difference between using GEDI L4A and ground sample plot as reference shows obvious dependence on forest types. In summary, optical dataset and its combination with SAR performed better in forest AGB estimation when the average AGB is less than 150 Mg/ha. The AGB predictions from GEDI L4A AGB product used as reference underperformed across the different forest types and study sites. However, GEDI can work as ground truth data source for forest AGB estimation in a certain level of estimation accuracy.

Does drip irrigation contribute to the economic sustainability of soybean production?

A two-year (2020, 2022) field experiment on soybean was conducted in northeaster Italy to evaluate the effect of irrigation (drip irrigation vs. rainfed), soil amendment (compost vs. digestate) and a cover crop (triticale vs. no cover crop) on grain yield and quality. Highly different rainfall amounts (627 mm and 258 mm in 2020 and 2022, respectively) and similar ET0 (578 mm and 581 mm in 2020 and 2022, respectively) were recorded during the growing seasons. Irrigation was managed using the web platform Irriframe suppling 51 mm in 2020 and 157 mm in 2022. Irrigation was the only experimental factor with significant effects on soybean grain yield and quality, except soil amendment on aboveground biomass production. In 2020, drip irrigation had no significant effect on grain yield (4.6 Mg ha-1 on average), while it increased it by 157% in 2022 compared to the rainfed control (1.0 Mg ha-1). The grain protein content was reduced by irrigation (43.2 ± 1.3% and 42.6 ± 0.9% under rainfed and irrigation managements, respectively). No treatment effect was observed on the grain oil content. A positive effect of irrigation was observed on water use efficiency, with values ranging from 0.40 ± 0.19 kg m-3 to 0.71 ± 0.12 kg m-3. The balance of the economic sustainability of drip irrigation was negative in both years: this irrigation method was not sustainable for soybean within the economic framework of the study area at the time. However, the results also confirmed that irrigation is a key agronomic technique to reduce production variability and dryland vulnerability of soybean.

Genetic Variability for the Yield and Yield-Related Traits in Some Maize (Zea mays L.) Inbred Lines in the Central Highland of Ethiopia

After rice and wheat, maize (Zea mays L.) is the third most significant and valuable crop in terms of industrial production in the world. The experiment was conducted to determine the nature and magnitude of genetic variability for various traits of maize inbred lines at the Ambo Plant Protection Research Center experimental field during 2013/2014, the major cropping season. The experiment’s design was described in 5 × 5 triple lattice designs. The results of the analysis of variance revealed that genotypic mean squares were significant for all traits, indicating that the inbred lines under study had a higher level of genetic diversity. In terms of genotypic and phenotypic variation, the largest coefficient was found in grain yield per hectare (28.49 and 35.43) followed by the number of tassel branches (23.14 and 24.92), respectively. Both days to 50% silking (91.57) and days to 50% tasseling (86.56) showed a high magnitude of broad-sense heritability. The results of the phenotypic and genotypic correlation analyses showed that grain yield per plant significantly correlated positively with five traits at both the phenotypic and genotypic levels. The number of kernels per row, aboveground biomass production per plant, harvest index, and grain yield per hectare might all be employed as selection criteria to increase the maize grain yield, according to path coefficient analysis at the phenotypic and genotypic levels. The grain yield and other significant yield components were found to be superior with inbred lines AMH169-55 and AMH169-86. Therefore, it is advised that these lines be used to further enhance the maize crop.

Three years of cover crops management increased soil organic matter and labile carbon pools in a subtropical vegetable agroecosystem

AbstractCover crops have been widely adopted to improve soil functions in agroecosystems, including providing carbon (C) inputs that can contribute to soil C sequestration. However, soil C changes may be slow after introducing cover crops in unfavorable environments for soil organic matter (SOM) accumulation, like the Southeast United States subtropical region characterized by a warm humid climate, and coarse‐textured soils. We examined labile C pools as potential early indicators of SOM changes after cover crop introduction in a sandy subtropical vegetable production system. We compared the effects of four cover crop monocultures namely two grasses [sorghum sudangrass, Sorghum bicolor × S bicolor var. Sudanese and pearl millet, Pennisetum glaucum (L.) R. Br.], two legumes (sunn hemp, Crotalaria juncea L., and cowpea, Vigna unguiculata Walp.), and one four‐species mixture on soil organic carbon pools for 3 years. Soil samples were collected at a 15‐cm depth before cover crop planting and post cover crop incorporation to assess changes in SOM, permanganate‐oxidizable carbon (POX‐C), mineralizable carbon (Cmin), and water extractable organic carbon (WEOC). The incorporation of cover crops increased concentrations of SOM, POX‐C, and Cmin in year 3 relative to their baseline values in year 1. Concentration of SOM increased by 0.24 ± 0.05% (mean ± standard error) after 3 years of cover crop management. However, concentrations of WEOC significantly decreased in years 2 and 3 relative to the baseline. Monocultures and the mixture had similar effects on measured C pools, likely due to comparable aboveground biomass production. Our findings highlight the potential of POX‐C and Cmin as early indicators of SOM accumulation driven by cover crops use, as well as the capacity of cover crops to build SOM in similar subtropical systems and coarser textured soils.

Drought reduces productivity and anti-herbivore defences, but not mycorrhizal associations, of perennial prairie forbs.

During drought, plants allocate resources to aboveground biomass production and belowground carbohydrate reserves, often at the expense of production of defence traits. Additionally, drought has been shown to alter floral resources, with potential implications for plant-pollinator interactions. Although soil symbionts, such as arbuscular mycorrhizal (AM) fungi, can alleviate drought stress in plants, certain levels of drought may negatively impact this relationship, with potential cascading effects. Because of their importance to plant and animal community diversity, we examined effects of drought on biomass production, physical defence properties, nectar production, and associated AM fungal abundance of five common prairie forb species in a greenhouse study. Reduced soil moisture decreased vegetative biomass production. Production of trichomes and latex decreased under drought, relative to well-watered conditions. Ruellia humilis flowers produced less nectar under drought, relative to well-watered conditions. Intra-radical AM fungal colonization was not significantly affected by drought, although extra-radical AM fungal biomass associated with S. azurea decreased following drought. Overall, grassland forb productivity, defence, and nectar production were negatively impacted by moderate drought, with possible negative implications for biotic interactions. Reduced flower and nectar production may lead to fewer pollinator visitors, which may contribute to seed limitation in forb species. Reduced physical defences increase the likelihood of herbivory, further decreasing the ability to store energy for essential functions, such as reproduction. Together, these results suggest drought can potentially impact biotic interactions between plants and herbivores, pollinators, and soil symbionts, and highlights the need for direct assessments of these relationships under climate change scenarios.

Differential roles of seed and sprout regeneration in forest diversity and productivity after disturbance

Natural regeneration after disturbances is a key phase of forest development, which determines the trajectory of successional changes in tree species composition and diversity. Regenerating trees can originate from either seeds or sprouts produced by disturbed trees with sprouting ability. Although both regeneration strategies often develop and co-occur after a disturbance, they tend to affect forest development differently due to significant functional differences. However, the origin of tree regeneration is rarely distinguished in post-disturbance forest surveys and ecological studies, and the differential roles of seed and sprout regeneration in forest productivity and diversity remain poorly understood. To address these research gaps, we explored the role of sprout and seed regeneration in the formation of woody species diversity and above-ground biomass (AGB) productivity in early-stage forest development. Data were collected in two experimental forest stands in the Czech Republic, where trees were cut with varying intensities with the density of residual (uncut) trees ranging from 0 to 275 trees per hectare. All trees were mapped and their sizes were measured before cutting and then, either as a stump with sprouts or a residual tree, remeasured 11 years later. In addition, all tree saplings were mapped and measured 11 years after logging, and their origin (sprout or seed) was identified. To assess abundances and productivity, we estimated AGB of all 2,685 sprouting stumps of 19 woody species and 504 generative (i.e., seed origin) individuals of 16 woody species, using allometric equations. Mixed-effects models were used to analyze the effects of each regeneration strategy on woody species diversity and the total AGB under varying densities of residual trees. Nonmetric multidimensional scaling was used to evaluate the effect of regeneration strategies on species composition. AGB and diversity of sprouts were significantly higher than those of seed regeneration. Sprouts formed on average 97.1% of the total regeneration AGB in Hády and 98.6% in Soběšice. The average species richness of sprouts was 4.7 in Hády and 2.2 in Soběšice, while the species richness of seed regeneration averaged 2.1 and 1.1 in Hády and Soběšice, respectively. Increasing density of residual trees reduced AGB and diversity of both sprouts and seed regeneration, but seed regeneration was affected to a greater extent. Residual trees had an especially strong inhibitory effect on the establishment of seed regeneration. Consequently, seed-originated saplings were nearly absent in plots with high residual tree density, and abundant sprouts accounted for most of the AGB and diversity. However, unlike sprouts whose species composition resembled that of the original stand, seed regeneration brought in new species, enriching the stand's overall species pool and beta diversity. Our results demonstrated differential roles of sprout and seed regeneration in the early stage of forest succession. Sprout regeneration was the main source of woody AGB productivity as well as species diversity, and its importance increased with the increasing density of standing mature trees. The results indicate the crucial yet previously underestimated role of sprout regeneration in post-disturbance forest dynamics. They suggest that the presence of residual mature trees, whether retained after partial cutting or undisturbed, can substantially suppress seed regeneration while the role of sprout regeneration in early succession becomes more distinctly evident.

Inter- and intra-year forest change detection and monitoring of aboveground biomass dynamics using Sentinel-2 and Landsat

National aboveground forest biomass products enable monitoring of biomass dynamics in a consistent and repeatable manner to inform carbon accounting and sustainable forest management activities. The availability of images of the Earth's surface from a combination of Landsat and Sentinel-2A and -2B provides an opportunity and capability to track intra-year biomass dynamics availing upon a twice weekly acquisition opportunity. We developed an algorithm that leverages these spatially and spectrally compatible data sources, called Tracking Intra- and Inter-year Change (TIIC), to monitor forest change across Canada's forested ecozones (>650Mha) in near-real time. Combining the stand-replacing change information from TIIC with spatially explicit maps of aboveground biomass (AGB), we demonstrate how intra-annual and inter-annual AGB dynamics, including losses due to stand-replacing disturbances and gains from vegetation growth, can be quantified temporally and spatially. Using independent validation data, our results for the focus year 2019 indicate that TIIC, by analysing images from May 30 to September 1, can accurately detect stand-replacing disturbances across Canada's forested ecozones with an overall accuracy of 99% and correctly attribute the type of change (i.e., wildfire or mechanical removal, the latter of which includes timber harvesting) with an overall accuracy of 99%. From an initial producer's accuracy of 23% for the changed class, accuracy increases incrementally as additional images are added throughout the growing season. attaining a producer's accuracy of 98% by the end of the analysis period. Intra-year change information complements information on long-term trends derived from annual time series monitoring over several decades. Our analysis of AGB dynamics indicated that in every ecozone, widespread small positive AGB increments yielded overall AGB gains that were greater than the sum of the large, punctual AGB losses resulting from stand-replacing disturbances. Overall in 2019, forest AGB increased across Canada's forested ecozones by 2.54%. Temporally, 80% of AGB losses stemming from mechanical removal occurred over the winter and are as such concentrated at the beginning of the growing season. In contrast, AGB losses linked to fires happen more stochastically throughout the growing season and occupy a greater area. By way of disturbance type, 36% of 2019 AGB loss was attributed to mechanical removal, and 64% was attributed to wildfire. Following the approach demonstrated herein, AGB changes can be tracked at a temporal frequency informative of forest management practices and ecological processes on the landscape, thereby refining our understanding of AGB dynamics.

Effect of Different Macronutrient Supply Levels on the Drought Tolerance of Rainfed Grass Based on Biomass Production, Water Use Efficiency and Macroelement Content

Water shortage, one of the main limiting factors for plant growth and development, can be alleviated by an adequate nutrient supply. The effect of different nitrogen (N), phosphorus (P) and potassium (K) supply levels and their combinations was examined in different rainfall supply periods (wet, normal, dry) on a grass sward in a field experiment. Dry and fresh aboveground biomass production were primarily increased by the N–rainfall supply interaction, from 0.739 to 6.51 and from 1.84 to 21.8 t ha−1, respectively, but the P–rainfall supply and N–P interactions and K treatment all had significant effects. Dry matter content was primarily influenced by the N–rainfall supply interaction, increasing in response to N in dry periods and declining in wet periods. Water use efficiency (WUE) was increased by the N–rainfall supply interaction from 28.3 to 127 kg ha−1 mm−1, but the N–P interaction had a similarly strong effect, and K treatment increased it in the dry period. The N, P and K contents of the aboveground biomass were increased by treatment with the corresponding element, but were also influenced by rainfall supply. The increase in biomass, mainly due to N treatment, caused the dilution of the P and K contents in grass in treatments poorly supplied with P and K. Biomass production and WUE were significantly improved up to a dose of 200 kg ha−1 year−1 of N, up to a supply level of 153 mg kg−1 of P2O5, and 279 mg kg−1 of K2O measured in the soil. Treating grass with the N, P and K macroelements may effectively increase biomass production and water use efficiency, but above a certain level their application is unnecessary.

Accuracy evaluation and effect factor analysis of GEDI aboveground biomass product for temperate forests in the conterminous United States

ABSTRACT The Global Ecosystem Dynamics Investigation (GEDI) is expected to revolutionize the quantification of aboveground carbon at continental scales, through its unprecedented dense vertical observations of vegetation structure. As its primary task, GEDI recently introduced GEDI L4A, the 25 m near-global footprint aboveground biomass density (AGBD) product. As a global mission with significant policy and management applications, it is urgent to conduct a comprehensive evaluation of GEDI L4A and to analyze the factors affecting the product’s performance. In this study, the accuracy of GEDI L4A is assessed using co-registered airborne Lidar surveys collected during 2018 ~ 2019 and corresponding AGBD plots at 19 sites of the National Ecological Observatory Network (NEON). The analysis included 11 forest types and spanned 17 eco-climatic domains across the conterminous United States to ensure the representativeness and comprehensiveness of the evaluation result. The interplay of nine factors affecting GEDI L4A is quantified, including the simulated waveform strategy deviation (SWSD) used in GEDI L4A, canopy characteristics (tree height, crown size, and canopy cover), canopy heterogeneity (crown size standard deviation, tree height standard deviation, and tree density), and other factors (forest type and topographic slope). Results show that compared with NEON observations, GEDI L4A generally underestimates the AGBD (Bias: −31.65 Mg/ha), with a moderate relative error exhibited in 14 of 19 sites (%RMSE ranging from 19% to 50%). For half of the forest types, the threshold of the lowest accuracy requirement of AGBD products set by GCOS was met or was close to being met. Broadleaf forests with high AGBD values had the lowest %RMSE (less than 35%), while coniferous forests with low AGBD values had the highest %RMSE (over 50%). Among the different factors considered, the SWSD contributed the most to GEDI L4A’s accuracy, with a relative importance of 56.63%, and manifested the indirect impacts of canopy heterogeneity and canopy characteristics. The relative importance of canopy heterogeneity (32.40%) was the second highest after SWSD; it was also much higher than that of canopy characteristics (3.99%). These results indicate the limitation of using only relative heights as predictors in GEDI L4A due to limited representation of horizontal structure and vertical tree complexity within a footprint. The findings in this study are a step forward in GEDI L4A’s appropriate application and provide perspectives to aid its improvement.