Functional Types Research Articles

Climate change and C4 and C3 grasses in a midlatitude dryland steppe.

Climate change is projected to alter the structure of plant communities due to increasing temperatures and changes to precipitation patterns, particularly in midlatitude dryland ecosystems. Modifications to climatic suitability may lead to major community changes such as altered dominant plant functional types. Previous studies have indicated that climatic suitability is likely to increase for C4 grasses and decrease for C3 grasses in the Western United States. However, if no C4 grass species currently exist to serve as a propagule source, expansion into areas of increased suitability will be limited. We conducted a field and modeling study in the Upper Green River Basin (UGRB) of Western Wyoming to determine if (1) C4 grasses are present to provide a propagule source and (2) C4 grasses are likely to increase in importance relative to C3 grasses due to climatic changes. We searched 44 sites for C4 grasses to establish presence, and modeled suitability at 35 sites using 17 Global Climate Models, two greenhouse gas Representative Concentration Pathways (RCPs; 4.5 and 8.5), and two time periods (mid- and late century; 2030-2060 and 2070-2099, respectively). We found C4 grasses at 10 of the 44 sites, indicating that there is a present propagule source. Our model projected increases in suitability for both C3 and C4 grasses across sites for all RCPs and time periods. In the mid-century RCP 4.5 scenario, the C3 functional type increased in projected biomass in 29 of 35 sites, and the C4 type increased in 31 sites. In this scenario, C3 grasses increased in projected biomass by a median 4 g m-2 (5% change), and C4 grass biomass increased by a median 8 g m-2 (21% change). Our study suggests that climate change will increase climatic suitability for grasses across the UGRB, and that all requirements are in place for C4 grasses to increase in abundance.

Long‐term trends in the genotypic integrity, phenotype and reproductive development of perennial ryegrass (Lolium perenne L.) populations in New Zealand dairy pastures: Implications for pasture persistence

AbstractFailure of perennial ryegrass‐based pastures to persist beyond 3 years post‐sowing is an increasing threat to the sustainability of livestock industries in the north of New Zealand. Little is known of the long‐term responses of plants and populations to the environmental stresses responsible for persistence failure, or the effects of ryegrass genetics on those responses. Plants were collected from 10‐year‐old pastures sown in two environments (Waikato, North Island: warm‐temperate, summer/autumn dry; Canterbury, South Island: cool temperate, irrigated) to four ryegrass functional types and grazed by dairy cattle. Surviving plants in Canterbury pastures were almost all true‐to‐type for the original genotype, whereas there was substantial ingress of volunteer plants in the diploid cultivars in Waikato. Plants confirmed as true‐to‐type were compared to reference plants grown from the original seed lines. Leaf mass was lower in survivor plants than in reference plants for all functional types. This effect was reversed by recruitment of new plants from seed in a grazing deferment treatment applied at the Waikato site 18 months before plant collection, in a manner consistent with epigenetic control. Reproductive development was delayed by 4–6 days in survivors of mid‐ and late flowering diploid cultivars: this effect appeared to be the result of true genetic differentiation. There was less aftermath heading in the Canterbury survivors, but not Waikato survivors, compared with the reference plants. The relevance of these findings for ryegrass survival strategies and targeted selection of traits for improved persistence is discussed.

Functioning and translation of English and Russian architectural terms in academic discourse

The study provides the analysis of architectural terminology in English and Russian in academic discourse. The object of the study is the terminological system of architecture. The subject of the study is the specifics of the use, functioning and translation of English and Russian architectural terminology in academic discourse. The classification and systematization of architectural terms, their hierarchical structure and functional types in academic texts are considered. In addition, the interdisciplinary nature of the architectural sublanguage is emphasized, which intersects with terms from the fields such as engineering, architecture, construction, art and design. The paper also identifies existing difficulties and problems that arise when translating English and Russian-language architectural terms, including differences in the linguistic structure of languages, semantic ambiguity, the need for a high degree of specialization of the translator for the correct interpretation of the term, the use of idiomatic and figurative language to describe some architectural terms, etc. The study uses a comprehensive methodology, in particular, methods of comparative and component analysis, as well as methods of corpus linguistics used to study semantic fields, hierarchical relationships and functional types of terms. The research results emphasize the importance of standardization of architectural terminology, understanding of cultural and historical background, as well as technical knowledge to ensure effective communication in the global architectural community. Analyzing the corpus of texts, including dictionaries, architectural reviews and academic articles, the author explains how specific terms function in academic discourse. This study makes a special contribution to the development of linguistic research in the field of architecture, offering an in-depth analysis of semantic fields and their role in structuring architectural vocabulary. The novelty of the research lies in an integrated approach to the study of the functioning and translation of architectural terms, which allows to identify the difficulties associated with the interdisciplinary character of the terminology. The results of the study will be useful not only for teachers and translators, but also for international experts in the field of architecture.

Streamlined multi-scenario revocation method leveraging blockchain and auxiliary trees

Access revocation is a fundamental aspect of modern information systems, ensuring that data remains secure and authorized personnel have appropriate access rights. However, existing access revocation methods address only one type of scenario, offering either partial or complete revocation functionalities but not both, leading to limitations in flexibility and effectiveness. This paper introduces a novel approach called streamlined multi-scenario revocation method (SMSRM) that combines block chain technology and auxiliary trees to streamline the process of multi-scenario access revocation. The SMSRM method defines two separate revoke request formats for partial and complete revocation. Auxiliary trees are used to keep track of non-revoked users, which is very important during the revocation process. In addition, the proposed method utilizes a block chain to record each and every revocation-related operation to provide forward secrecy. Through a comparative analysis, we evaluate the performance of our approach against existing methods. The results highlight that our method performs better in terms of response time and various performance metrics.

Advances in the selection of functional monomers for molecularly imprinted polymers: A review.

Molecularly imprinted polymers, a type of special polymer materials, are widely used in biosensing and other fields due to their ability to specifically recognize target molecules, often called "artificial receptors.". Nowadays, researchers are constantly exploring new design and synthesis methods for molecularly imprinted materials to improve the selectivity and sensitivity of molecularly imprinted materials. Among them, the selection of functional monomers has attracted great attention. This review comprehensively analyzes and discusses the selection methods of functional monomers. The most commonly used functional monomers among different types of templates are screened based on the structural properties of the template molecules, including the selection of functional monomers among ion-imprinted polymers, protein-imprinted polymers, and bacterial imprinted polymers. The rich binding sites and functional group types of multifunctional monomers are also highlighted to advance the development of molecular imprinting technology. The article further explores the current challenges and prospects in the selection of functional monomers and emphasizes multiplex experiments and computer simulations as important directions for future research. This review provides comprehensive information and constructive guidelines for researchers in selecting functional monomers in areas such as analytical chemistry and biosensors.

Large Divergence of Projected High Latitude Vegetation Composition and Productivity Due To Functional Trait Uncertainty

AbstractVegetation distribution and composition are expected to change in northern high latitudes under rapid warming, which regulates ecosystem functions but remains challenging to predict. Vegetation change arises from the interplay of chronic climate trends such as warming and transient demographic processes of recruitment, growth, competition, and mortality. Most predictive models overlooked the role of demographic dynamics controlled by plant traits. Here, we simulate vegetation dynamics at the Kougarok Hillslope site in Alaska under historical and future climates using the E3SM Land Model coupled to the Functionally Assembled Terrestrial Simulator (ELM‐FATES). To evaluate the roles of plant traits, we parameterize the model with 5,265 trait configurations representing diverse physiological and demographic strategies. Results show current modeled biomass, composition, and productivity are most sensitive to traits controlling photosynthetic capacity, carbon allocation, allometry, and phenology. Among all trait configurations, ∼5% reproduce in situ biomass and plant functional type (PFT) composition measured in 2016, that are indistinguishable from these two observed ecosystem states. Notably, these same trait configurations produce diverging biomass, composition, and productivity under future climate, where the uncertainty attributable to traits is twice the change attributable to climate change. The variation of projected productivity arises from emerging PFT composition under novel climate regimes, primarily explained by traits controlling cold‐induced mortality, recruitment, and allometry. Our findings highlight the importance and uncertainty of demographic dynamics and its interaction with climate change in shaping Arctic vegetation change. Improved model predictions will likely benefit from explicit consideration of vegetation demography and better constraints of critical traits.

Detecting Vegetation Stress in Mixed Forest Ecosystems Through the Joint Use of Tree‐Water Monitoring and Land Surface Modeling

AbstractRecent European heatwaves have significantly impacted forest ecosystems, leading to increased plant water stress. Advances in land surface models aim to improve the representation of vegetation drought responses by incorporating plant hydraulics into the plant functional type (PFT) classification system. However, reliance on PFTs may inadequately capture the diverse plant hydraulic traits (PHTs), potentially biasing transpiration and vegetation water stress representations. The detection of vegetation drought stress is further complicated by the mixing of different tree species and forest patches. This study uses the Community Land Model version 5.0 to simulate an experimental mixed‐forest catchment with configurations representing standalone, patched mixed, and fully‐mixed forests. Biome‐generic, PFT‐specific, or species‐specific PHTs are employed. Results emphasize the crucial role of accurately representing mixed forests in reproducing observed vegetation water stress and transpiration fluxes for both broadleaf and needleleaf tree species. The dominant vegetation fraction is a key determinant, influencing aggregated vegetation response patterns. Segregation level in PHT parameterizations shapes differences between observed and simulated transpiration fluxes. Simulated root water potential emerges as a potential metric for detecting vegetation stress periods. However, the model's plant hydraulic system has limitations in reproducing the long‐term effects of extreme weather events on needleleaf tree species. These findings highlight the complexity of modeling mixed forests and underscore the need for improved representation of plant diversity in land surface models to enhance the understanding of vegetation water stress under changing climate conditions.

The impact of hypoglycaemia on daily functioning among adults with diabetes: a prospective observational study using the Hypo-METRICS app

Aims/hypothesisThe aim of this work was to examine the impact of hypoglycaemia on daily functioning among adults with type 1 diabetes or insulin-treated type 2 diabetes, using the novel Hypo-METRICS app.MethodsFor 70 consecutive days, 594 adults (type 1 diabetes, n=274; type 2 diabetes, n=320) completed brief morning and evening Hypo-METRICS ‘check-ins’ about their experienced hypoglycaemia and daily functioning. Participants wore a blinded glucose sensor (i.e. data unavailable to the participants) for the study duration. Days and nights with or without person-reported hypoglycaemia (PRH) and/or sensor-detected hypoglycaemia (SDH) were compared using multilevel regression models.ResultsParticipants submitted a mean ± SD of 86.3±12.5% morning and 90.8±10.7% evening check-ins. For both types of diabetes, SDH alone had no significant associations with the changes in daily functioning scores. However, daytime and night-time PRH (with or without SDH) were significantly associated with worsening of energy levels, mood, cognitive functioning, negative affect and fear of hypoglycaemia later that day or while asleep. In addition, night-time PRH (with or without SDH) was significantly associated with worsening of sleep quality (type 1 and type 2 diabetes) and memory (type 2 diabetes). Further, daytime PRH (with or without SDH), was associated with worsening of fear of hyperglycaemia while asleep (type 1 diabetes), memory (type 1 and type 2 diabetes) and social functioning (type 2 diabetes).Conclusions/interpretationThis prospective, real-world study reveals impact on several domains of daily functioning following PRH but not following SDH alone. These data suggest that the observed negative impact is mainly driven by subjective awareness of hypoglycaemia (i.e. PRH), through either symptoms or sensor alerts/readings and/or the need to take action to prevent or treat episodes.Graphical

Evaluation of the coupling of EMACv2.55 to the land surface and vegetation model JSBACHv4

Abstract. We present the coupling of the Jena Scheme for Biosphere–Atmosphere Coupling in Hamburg version 4 (JSBACHv4) to the ECHAM/MESSy Atmospheric Chemistry (EMAC) model. With JSBACH, the soil water bucket model in EMAC is replaced by a diffusive hydrological transport model for soil water that includes water storage and infiltration in five soil layers, preventing soil from drying too rapidly and reducing biases in soil temperature and moisture. A three-layer soil scheme is implemented, and phase changes in water in the soil are considered. The leaf area index (LAI) climatology in EMAC has been substituted with a phenology module calculating the LAI. Multiple land cover types are included to provide a state-dependent surface albedo, which accounts for the absorption of solar radiation by vegetation. Plant net primary productivity, leaf area index and surface roughness are calculated according to the plant functional types. This paper provides a detailed evaluation of the new coupled model based on observations and reanalysis data, including ERA5/ERA5-Land datasets, Global Precipitation Climatology Project (GPCP) data and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data. Land surface temperature (LST), terrestrial water storage (TWS), surface albedo (α), net top-of-atmosphere radiation flux (RadTOA), precipitation (precip), leaf area index (LAI), fraction of absorbed photosynthetic active radiation (FAPAR) and gross primary productivity (GPP) are evaluated in particular. The strongest correlation (r) between reanalysis data and the newly coupled model is found for LST (r=0.985, with an average global bias of −1.546 K), α (r=0.947, with an average global bias of −0.015) and RadTOA (r=0.907, with an average global bias of 3.56 W m−2). Precipitation exhibits a correlation with the GPCP dataset of 0.523 and an average global bias of 0.042 mm d−1. The LAI optimisation yields a correlation of 0.637 with observations and a global mean deviation of −0.212. FAPAR and GPP exemplify two of the many additional variables made available through JSBACH in EMAC. FAPAR and observations show a correlation of 0.663, with an average global difference of −0.223, while the correlation for GPP and observations is 0.564 and the average global difference is −0.001 kg carbon km−1. Benefiting from the numerous added features within the simulated land system, the representation of soil moisture is improved, which is critical for vegetation modelling. This improvement can be attributed to a general increase in soil moisture and water storage in deeper soil layers and a closer alignment of simulated TWS with observations, mitigating the previously widespread problem of soil drought. We show that the numerous newly added components strongly improve the land surface, e.g. soil moisture, TWS and LAI, while surface parameters, such as LST, surface albedo or RadTOA, which were mostly prescribed according to climatologies, remain similar. The coupling of JSBACH brings EMAC a step closer towards a holistic comprehensive Earth system model and extends its versatility.

Overstory and fuel traits drive moisture dynamics of mesophytic and pyrophytic leaf litter and 10-h woody debris fuels in a mixed longleaf pine-hardwood woodland

BackgroundFollowing decades of fire exclusion, many open pine and oak forests across the central and eastern US are shifting to closed-canopy forests that are increasingly dominated by shade-tolerant, fire-sensitive species (i.e., mesophytes). As mesophytes encroach into historically pyrophytic landscapes, changes in crown traits and understory microclimate may interact with fine fuel traits to influence fuel moisture retention, and ultimately, fire behavior. To better understand potential interactions among overstory trees and underlying fine fuels that occur during mesophyte encroachment, we measured in situ drying rates of leaf litter and 10-h woody debris of three functional groups (pyrophytic pine, pyrophytic oak, and mesophytic oak) in gaps and beneath overstory trees of each functional group within a longleaf pine-mixed oak woodland along with crown (area, volume, cover), leaf litter (curling, thickness, specific leaf area, volume), and woody debris (density) traits of each functional group and understory microclimate (vapor pressure deficit (VPD)).ResultsWe found that leaf litter from pyrophytic and mesophytic oaks had higher initial moisture content than pyrophytic pines, but pyrophytic pine and pyrophytic oak leaf litter dried 1.5 times faster than that of mesophytic oaks, likely due to their greater leaf curl, thickness, and volume. Initial moisture content of mesophytic oak woody fuels was lower than that of pyrophytic pine and pyrophytic oak, potentially because of higher wood density, but there were no differences in fuel drying rates. Regardless of fuel functional type, leaf litter and woody fuels dried 1.5 times faster in gaps and underneath pyrophytic pine compared to mesophytic oaks, likely due to the more open conditions in these areas. Notably overstory functional group and time of the day interacted to influence VPD, with VPD increasing throughout the day for all groups, but more so for gaps and beneath pyrophytic pines than either oak functional group.ConclusionsThus, fuel and crown traits differentially impacted understory microclimate and leaf litter and 10-h woody debris drying rates, leading to slower drying of fuels of encroaching mesophytes compared to pyrophytic pines and oaks, which could lead to reduced forest flammability, and consequently, the continued encroachment of mesophytic species into fire-dependent pine and oak forests.

Multi-kingdom characterization of living organisms by 13C CPMAS NMR spectroscopy reveals unique traits in bacteria, fungi, algae, and higher plants

Determining the chemical quality of soil organic matter and decomposing organisms is critical for predicting carbon fluxes in ecosystems. However, the classical C/N and lignin/N ratios have been criticized for their capability in predicting ecosystem function including litter decay rate, nitrogen mineralization and soil aggregation. Therefore, with our work we aim to complement information on the chemical properties of primary producers and decomposers based on 13C NMR. Overall, 108 unique 13C NMR spectra were collected from higher plant tissues including leaf litter, fine roots, woody debris, as well as a range of microbes i.e. bacteria, fungi, and marine algae. Results showed clear discrimination between organisms belonging to different kingdoms, but with limited variability within bacteria, fungi, and microalgae. In detail, bacteria were found to be distinct not only from plant tissues but also from fungi, characterized by a high proportion of alkyl and carbonyl C types and a rather low relative abundance of O Alkyl C and di-O Alkyl C types. Among the fungi, we found clear separation between yeasts, which are more similar to bacteria, and filamentous species, which are rich in O Alkyl and di-O Alkyl C types. Microalgae are characterized by a high content of aliphatic, carboxylic and methoxyl C fractions. In the spectra of terrestrial plants, the O Alkyl C region, associated with sugars and cellulose, is more abundant compared to algae and bacteria. In addition, the aromatic carbon signal, which is mainly associated with lignin, is much higher for higher plants than in microorganisms. As for plant tissues, woody tissues are clearly different from leaves and fine roots, with grasses, sedges, and ferns being well distinguished from forbs, coniferous and deciduous trees. In summary, our study contains the largest freely available 13C NMR spectral library of bacteria, fungi, algae, and higher plant tissues. However, the data from higher plants are sufficient to cover different functional types, which is not yet possible for bacteria and fungi.

Harnessing true capacitive activity of nitrogen-doped MXene through hydrogel assembly and theoretical understanding of the role of dopant sites

Heteroatom nitrogen (N) doping in MXene can significantly push its energy storage metric. However, translating the intrinsic improvement of individual sheets into macroscopic electrodes is challenging due to the blockage of dopant sites by restacking. Here, we report the development of restack-controlled N-doped MXene hydrogel through speedy interfacial assembly methods to keep the dopant sites electrochemically accessible. Application of a small voltage between two zinc plates in an aqueous dispersion of N-doped MXene leads to the rapid development of doped hydrogel over the positive zinc plate via electrophoretic drag and linking by interfacial released zinc ions. As-developed hydrogels having continuous porosity and quasi-oriented sheet arrangement preserve ion transporting channels, thus allowing the surface dopant sites to participate in the supercapacitive energy storage actively. N-doped hydrogel displays a high capacitance of 488 F g−1 at 5 mV s−1 much higher as compared to compact film. The N-doped MXene hydrogels display excellent rate performance with retention over 88 % at 1000 mV s−1 and cyclic stability of 87 % over 10000 cycles. The detailed density functional theory (DFT) calculation reveals a major pseudocapacitive contribution from the surface adsorption and functional group substitution type N dopant sites as compared to another dopant site, namely, lattice substitution.

The impacts of modelling prescribed vs. dynamic land cover in a high-CO2 future scenario – greening of the Arctic and Amazonian dieback

Abstract. Terrestrial biosphere models are a key tool in investigating the role played by land surface in the global climate system. However, few models simulate the geographic distribution of biomes dynamically, opting instead to prescribe them using remote sensing products. While prescribing land cover still allows for the simulation of the impacts of climate change on vegetation growth and the impacts of land use change, it prevents the simulation of climate-change-driven biome shifts, with implications for the projection of future terrestrial carbon sink. Here, we isolate the impacts of prescribed vs. dynamic land cover implementations in a terrestrial biosphere model. We first introduce a new framework for evaluating dynamic land cover (i.e., the spatial distribution of plant functional types across the land surface), which can be applied across terrestrial biosphere models alongside standard benchmarking of energy, water, and carbon cycle variables in model intercomparison projects. After validating simulated land cover, we then show that the simulated terrestrial carbon sink differs significantly between simulations with dynamic vs. prescribed land cover for a high-CO2 future scenario. This is because of important range shifts that are only simulated when dynamic land cover is implemented: tree expansion into the Arctic and Amazonian transition from forest to grassland. In particular, the projected change in net land–atmosphere CO2 flux at the end of the 21st century is twice as large in simulations with dynamic land cover than in simulations with prescribed land cover. Our results illustrate the importance of climate-change-driven biome shifts for projecting future terrestrial carbon sink.

Evaluation of the Reliability of the CCM-300 Chlorophyll Content Meter in Measuring Chlorophyll Content for Various Plant Functional Types.

Chlorophyll fluorescence is a well-established method to estimate chlorophyll content in leaves. A popular fluorescence-based meter, the Opti-Sciences CCM-300 Chlorophyll Content Meter (CCM-300), utilizes the fluorescence ratio F735/F700 and equations derived from experiments using broadleaf species to provide a direct, rapid estimate of chlorophyll content used for many applications. We sought to quantify the performance of the CCM-300 relative to more intensive methods, both across plant functional types and years of use. We linked CCM-300 measurements of broadleaf, conifer, and graminoid samples in 2018 and 2019 to high-performance liquid chromatography (HPLC) and/or spectrophotometric (Spec) analysis of the same leaves. We observed a significant difference between the CCM-300 and HPLC/Spec, but not between HPLC and Spec. In comparison to HPLC, the CCM-300 performed better for broadleaves (r = 0.55, RMSE = 154.76) than conifers (r = 0.52, RMSE = 171.16) and graminoids (r = 0.32, RMSE = 127.12). We observed a slight deterioration in meter performance between years, potentially due to meter calibration. Our results show that the CCM-300 is reliable to demonstrate coarse variations in chlorophyll but may be limited for cross-plant functional type studies and comparisons across years.

Ecosystem CO2 flux responses to extreme droughts depend on interaction of seasonal timing and plant community composition

Abstract Droughts can affect ecosystem CO2 fluxes directly or indirectly by changing plant community composition. However, it is unknown whether shifts in plant community composition buffer or amplify the response of ecosystem CO2 fluxes to droughts with different seasonal timing, as plant phenology and physiology of the different plant functional types respond differently to droughts. To identify the interaction of drought timing and plant community composition in regulating ecosystem CO2 fluxes, we conducted a three‐year manipulative experiment in which extreme droughts occurring in the early, mid and late growing seasons were separately imposed on experimental plot communities comprising graminoids, shrubs and their combination in a semi‐arid grassland of Inner Mongolia, China. Overall, mid‐season drought caused the largest negative effects regardless of plant community composition. In addition to decreasing aboveground biomass, mid‐season drought suppressed fluxes by reducing leaf photosynthetic rate, while early‐season and late‐season drought reduced fluxes mainly by shortening growing season length. All three community compositions had consistent responses to early‐season and mid‐season droughts. However, ecosystem CO2 fluxes in the combination community were less negatively affected by late‐season drought than in either shrub or graminoid communities because the growing season length was shortened less. Synthesis. Our results highlight that it is important to account for interactions of seasonal timing and plant community composition when predicting magnitude and pathways of drought effects on ecosystem carbon cycling.

Phenology- and light-based parameterization of stomatal conductance model for urban woody species in northern China

Surface ozone (O3) poses a significant threat to urban vegetation health, and assessing the O3 risk across woody species is of vital importance for maintaining the health of urban infrastructure. In the present study, Jarvis-type stomatal conductance model was parameterized for ten urban species in northern China. Incorporating the effects of time of day and diurnal O3 concentration significantly enhanced the model performance. For different plant functional types (greening trees, greening shrubs, and orchard-grown trees), three parameterizations were established to estimate stomatal O3 uptake (POD1, phytotoxic O3 dose over an hourly threshold of 1 nmol m−2 s−1). The differences in POD1 between greening trees and shrubs were primarily due to the difference in their stomatal sensitivity to light. Orchard-grown trees displayed the lowest O3 removal capacity (lowest value of POD1) because of their shorter growing season despite of high stomatal conductance. These results indicated that plant phenology and light responsiveness determined stomatal O3 uptake, and the three parameterizations developed here could be applicable to various urban species in northern regions. Among climatic factors for O3 risk assessment, O3 concentration was the most important factor determining annual variation of POD1, which was primarily driven by air temperature. However, when O3 pollution decreased, O3 concentration exhibited less dependence on temperature and more dependence on light. These findings provide crucial insights for urban policy-makers and environmental scientists aiming to mitigate O3 pollution effects and enhance urban vegetation health.

How do intervals between fires influence canopy seed production and viability?

Abstract Canopy storage of seed (serotiny) is an important persistence strategy in fire‐prone environments. Serotinous populations can be threatened when fire intervals are shorter than the time needed to accumulate seed, or when longer than plant lifespans. Understanding how fire regimes influence canopy seedbanks requires study of the timing of plant maturity, seed output and germination traits. Research that spans plant functional types, such as resprouters or obligate seeders, helps to understand the mechanisms through which fire has influence. Using field data collected at 57 sites in a Mediterranean shrubland of southeastern Australia, we modelled how time since fire and mean fire interval influenced infructescence (hereby cone) production. Additionally, seed output, viability and germination speed were assessed in the laboratory. Reproductively mature resprouters were first observed 2 to 4 years post‐fire in the field, and reproductively mature obligate seeders 6 years post‐fire, depending on the species. Reproductively mature plants were not observed at short mean fire intervals: until 3 and 9 years for resprouters and nine and 18 years for obligate seeders, again, varying by species. When resprouter species reached maturity, we observed a decline in cone production as time since fire increased. This decline was not observed for obligate seeder species. Fire influenced the number of viable seeds produced within cones for one resprouter species, Allocasuarina paludosa, but we did not detect a relationship for other species. Germination speed was faster for species that produce few seeds per cone, and slower for species that produce many seeds, indicating a trade‐off between fire‐related seed traits. For example, Hakea rostrata, which holds two seeds per cone, germinated mostly within the first few weeks, while Callitris rhomboidea, which holds many seeds per cone, germinated asynchronously over 9 months. Short intervals between fires reduce canopy seed production for the serotinous species studied. Obligate seeders were more sensitive to frequent fire than resprouters. In the context of expected increases in wildfire frequency and droughts in Mediterranean ecosystems, our findings suggest that serotinous species' reproduction and recruitment will be differentially impacted depending on a suite of functional traits. Read the free Plain Language Summary for this article on the Journal blog.

From nutrients to fish: Impacts of mesoscale processes in a global CESM-FEISTY eddying ocean model framework

The ocean sustains ecosystems that are essential for human livelihood and habitability of the planet. The ocean holds an enormous amount of carbon, and serves as a critical source of nutrition for human societies worldwide. Climate variability and change impact marine biogeochemistry and ecosystems. Thus, having state-of-the-art simulations of the ocean, which include marine biogeochemistry and ecosystems, is critical for understanding the role of climate variability and change on the ocean biosphere. Here we present a novel global eddy-resolving (0.1° horizontal resolution) simulation of the ocean and sea ice, including ocean biogeochemistry, performed with the Community Earth System Model (CESM). The simulation is forced by the atmospheric dataset based on the Japanese Reanalysis (JRA-55) product over the 1958–2021 period. We present a novel configuration of the CESM marine ecosystem model in this simulation which includes two zooplankton classes: microzooplankton and mesozooplankton. This novel planktonic food web structure facilitates “offline” coupling with the Fisheries Size and Functional Type (FEISTY) model. FEISTY is a size- and trait-based model of fish functional types contributing to fisheries. We present an evaluation of the ocean biogeochemistry, marine ecosystem (including fish types), and sea ice in this high resolution simulation compared to available observations and a corresponding low resolution (nominal 1°) simulation. Our analysis offers insights into environmental controls on trophodynamics within the ocean. We find that this high resolution simulation provides a realistic reconstruction of nutrients, oxygen, sea ice, plankton and fish distributions over the global ocean. On global and large regional scales the high resolution simulation is comparable to the standard 1° simulation, but on smaller scales, explicitly resolving the mesoscale dynamics is shown to be important for accurately capturing trophodynamic structuring, especially in coastal ecosystems. We show that fine-scale ocean features leave imprints on ocean ecosystems, from plankton to fish, from the tropics to polar regions. This simulation also offers insights on ocean acidification over the past 64 years, as well as how large-scale climate variations may impact upper trophic levels. The data generated by the simulations are publicly available and will be a fruitful community resource for a large variety of oceanographic science questions.

Modeling hydration of graphene oxide (GO) – Does size matter?

The biomedical applications of graphene-based materials become one of hot scientific and technological topics in the last few years. Flake graphene oxide (GO) is considered as one of the promising materials for biomedical use due to a number of specific properties, in particular in design of advanced drug delivery systems (DDS). The key factor in the formation of non-covalently bonded complexes for drug transport is the strength of non-covalent interactions of the carrier with both the drug and the environment. In the current work, we have focused on molecular modeling of solvation of zigzag-edged graphene oxide, functionalized with hydroxyl and carboxyl substituents. The hydration was determined from the magnitude of weak intermolecular interactions of GO with one or two water molecules. Our goal was to establish the dependence of the degree and type of functionalization, as well as the size of graphene flakes and the position of hydrophilic substituents on the number and strength of H-bonds. All calculations were performed using density functional theory (DFT) at the B3LYPD3BJ/6-311++G** level. The effect of water solvent was established using an explicit (discrete) model of solvent.

A novel framework to generate plant functional groups for ecological modelling

An effective way to reduce complexity in ecological modelling is by grouping species that share similar characteristics into functional groups or types. Often, the creation of plant functional groups (PFGs) is carried out for each case study in an ad-hoc way using a small set of traits. This limits the transferability of these PFGs to other geographical areas or study systems. We propose a novel generic framework to generate PFGs that considers the most important ecological dimensions, is applicable to case studies globally, and that emerges from patterns of functional redundancy across species. Based on most relevant and measured plant characteristics, we designed a multi-step process that includes: i) data harmonisation and missing values imputation; ii) species clustering based on multiple characteristics encompassing the main ecological dimensions featured in plant community ecological models (i.e., dispersal, competition, and demography) and iii) the combination of ecological dimension-specific groups into comprehensive PFGs. We demonstrate this framework by applying it to a global dataset of plant characteristics including a functional traits dataset and a plant-soil co-occurrence dataset for 19,102 species. Lastly, to test the ability of generated PFGs to summarise species’ functional variation within plant communities, we correlate taxonomical and functional diversity indices calculated at the species and at the PFGs level across a global dataset of plant communities (sPlotOpen). Our framework generated 465 global, robust data-driven PFGs with non-overlapping combinations of traits for each ecological dimension divided by growth form. The validation returned positive correlation values between PFGs and species-level diversity metrics, supporting the ability of the obtained PFGs to capture functional and taxonomic diversity patterns across a variety of plant communities worldwide. The framework allows for the easy integration of newly available species characteristics data. The obtained global PFGs, covering all main known ecological processes and environmental conditions at small resolution, can increase the predictive power and accuracy of process-based models and help furthering varying-scale ecological studies.