Changes In Distribution Research Articles

Rock moisture reinforces belowground water storage under different precipitation scenarios and vegetation coverage

Rock moisture is rarely deliberated but crucial for hydrologic regulation in semiarid loess hilly regions. In this study, using in-situ monitoring observation and simulation, soil and rock moisture spatiotemporal variations under planting alfalfa and caragana were analyzed and sketched, and the water storage contributions by weathered bedrock layers (WBLs) under different rainwater scenarios were then simulated and estimated. The results showed that WBLs had apparent spatiotemporal changes in water distribution and storage with rainfall events. Under water scarcity scenarios, WBLs increased the variabilities of water storage, with an average increase of 89.9 % in alfalfa and 14.2 % in caragana, providing wider water supply boundaries for vegetation. However, higher volumetric water content was presented under relatively abundant water scenarios. The average soil water content was 0.08 cm3 cm−3 in alfalfa and 0.09 cm3 cm−3 in caragana, while the average rock water content was 0.12 cm3 cm−3 in alfalfa and 0.13 cm3 cm−3 in caragana. Profile water consumption goes to surface soil evaporation and plant transpiration over an entire growing season, while extrawater would be stored in WBLs to maintain vegetation growth during the water-scarce seasons. Moreover, water storage had a positive linear relationship with the thickness of WBLs. Rock water storage increased by 6.9 % in alfalfa and 3.7 % in caragana after adding 20 cm WBLs, while it increased by 23.6 % in alfalfa and 9.9 % in caragana after adding 50 cm WBLs. Furthermore, various exogenous rainwater simulations showed that differences in water storage were significantly increased with WBLs thickness. This study would provide new insights into the deep-rooted plant distribution planning in semiarid loess hilly regions, and could also be helpful for the rational water resources utilization and management in shallow soil areas.

Tracking annual dynamics of carbon storage of salt marsh plants in the Yellow River Delta national nature reserve of china based on sentinel-2 imagery during 2017–2022

Coastal salt marshes play a key role in coastal carbon sequestration. Understanding the spatial distribution and annual changes of carbon storage of salt marsh plants at a local scale is helpful for accurate protection and restoration. However, the annual carbon storage of salt marsh plants has not yet been obtained in the Yellow River Delta National Nature Reserve (YRDNNR), China. Here, we developed a fast and reliable method to produce an annual map of carbon storage of herbaceous salt marsh plants from 2017 to 2022 based on multi-year in situ data and 10-meter resolution Sentinel-2 images in YRDNNR. That is, a deep belief network based on conjugate gradient (CGDBN) pixel-level classification, a generative adversarial network with a constrained factor (GAN-CF) measured sample expansion and multiple linear regression (MLR) quantitative inversion algorithm is used. The results showed that: (1) The carbon storage of herbaceous salt marsh plants in the YRDNNR increased in 2017–2018 and 2019–2021, with an average carbon storage dynamic of 4.53–8.39 Mg/ha. (2) In 2021, the area of salt marsh vegetation increased significantly by 20 % compared to 2017. Although its area decreased sharply due to the removal of invasive species (S. alterniflora) in 2022, the carbon storage per unit area of salt marsh plants remained at 7.77 Mg/ha. (3) The carbon storage of salt marsh vegetation showed a gradient change along the community succession from land to sea. Estimating annual carbon storage of salt marsh plants could provide basic data for recognizing the ‘blue carbon’ contribution of coastal plants and managing the coastal salt marsh ecosystem in Yellow River Delta.

Characteristics of lipid metabolism after treatment of colon cancer mice with American ginseng vesicles.

Lipid molecules are present in tumours and play an important role in the anti-inflammatory response as well as in antiviral protection. Changes in the type and location of lipids in the intestine following exposure to environmental stressors play an important role in several disorders, including ulcerative colitis (UC), inflammatory bowel disease (IBD), and colorectal cancer. The aim of this work is to provide a new theoretical basis for tumour initiation and development by accurately measuring the spatial distribution of lipids and metabolites in intestinal tissue. Spatial metabolomics allows the detection of samples with minimal sample volume by label-free imaging of complex samples in their original state. The distribution of lipid molecules in tumours has not been reported, although the distribution of lipid molecules in intestinal tissue has been reported in the literature. The range of lipid profiles in colon cancer mouse tumour tissue was compiled using a spatial metabolomics: lipid extraction method. The changes in lipid distribution in two regions after oral administration of American Ginseng (Panax quinquefolius L.) vesicles were also compared. Tumour tissue samples were extracted with 80% methanol-20% formic acid in water. The resulting spatial metabolic profile allowed the identification of seven lipid classes in mouse tumours. The distribution of fibre tissue cells was 23.2% higher than tumour tissue cells, with the exception of the fatty acid (FA) species.

Simulating drifting fish aggregating device trajectories to identify potential interactions with endangered sea turtles.

Purse-seine fishers using drifting fish aggregating devices (dFADs), mainly built with bamboo, plastic buoys, and plastic netting, to aggregate and catch tropical tuna, deploy 46,000-65,000 dFADs per year in the Pacific Ocean. Some of the major concerns associated with this widespread fishing device are potential entanglement of sea turtles and other marine fauna in dFAD netting; marine debris and pollution; and potential ecological damage via stranding on coral reefs, beaches, and other essential habitats for marine fauna. To assess and quantify the potential connectivity (number of dFADs deployed in an area and arriving in another area) between dFAD deployment areas and important oceanic or coastal habitat of critically endangered leatherback (Dermochelys coriacea) and hawksbill (Eretmochelys imbricata) sea turtles in the Pacific Ocean, we conducted passive-drift Lagrangian experiments with simulated dFAD drift profiles and compared them with known important sea turtle areas. Up to 60% of dFADs from equatorial areas were arriving in essential sea turtle habitats. Connectivity was less when only areas where dFADs are currently deployed were used. Our simulations identified potential regions of dFAD interactions with migration and feeding habitats of the east Pacific leatherback turtle in the tropical southeastern Pacific Ocean; coastal habitats of leatherback and hawksbill in the western Pacific (e.g., archipelagic zones of Indonesia, Papua New Guinea, and Solomon Islands); and foraging habitat of leatherback in a large equatorial area south of Hawaii. Additional research is needed to estimate entanglements of sea turtles with dFADs at sea and to quantify the likely changes in connectivity and distribution of dFADs under new management measures, such as use of alternative nonentangling dFAD designs that biodegrade, or changes in deployment strategies, such as shifting locations.

The impact of future UK offshore wind farm distribution and climate change on generation performance and variability

The UK plans to significantly increase offshore wind generation capacity as part of the effort to achieve net zero targets. Current installation is densely located in a few areas, particularly off the east coast of England, and although current siting proposals include new offshore regions, significant volumes of wind generation capacity are yet to be located to meet 2050 installation targets. This paper uses a recent dataset of multi-decadal offshore wind power capacity factor timeseries to assess how UK offshore wind generation is likely to be affected by both the spatial distribution of future wind farms, and by the impacts of near-future (2020–2050) climate change. We determine that a wider geographic spread of offshore capacity results in a much-improved and less-variable UK-aggregated power generation profile, with substantial reductions in periods of low generation and extreme wind power ramping events, without negatively impacting mean or peak generation outputs. The impact of near-term climate change appears to be minor, slightly reducing overall generation and possibly resulting in an underestimation of future installation requirements, but this climate signal is outweighed by the effects of spatial distribution, and even more so by inherent hourly to inter-annual wind speed variability. This study implies that the intermittency of wind generation can be partly mitigated through increasing the spatial diversity of the existing wind farm distribution. Alongside a more in depth investigation of future climate change, and a holistic assessment of relevant geospatial factors such as Levelised Cost of Energy, infrastructure, and environmental constraints, this study could be used for optimisation of future offshore wind siting.

Spatio‐temporal data integration for species distribution modelling in R‐INLA

Abstract Species distribution modelling is a highly used tool for understanding and predicting biodiversity change, and recent work has emphasised the importance of understanding how species distributions change over both time and space. Spatio‐temporal models require large amounts of data spread over time and space, and as such are clear candidates to benefit from model‐based integration of different data sources. However, spatio‐temporal models are highly computationally intensive and integrating different data sources can make this approach even more unfeasible to ecologists. Here we demonstrate how the R‐INLA methodology can be used for model‐based data integration for spatio‐temporally explicit modelling of species distribution change. We demonstrate that this method can be applied to both point and areal data with two contrasting case studies, one using the SPDE approach for modelling spatio‐temporal change in the Gatekeeper butterfly (Pyronia tithonus) across Great Britain and the second using a spatio‐temporal areal model to describe change in caddisfly (Trichoptera) populations across the River Thames catchment. We show that in the caddisfly case study integrating together different data sources led to greater understanding of the change in abundance across the River Thames both seasonally and over 5 years of data. However, in the butterfly case study moving to a spatio‐temporal context exacerbated differences between the data sources and resulted in no greater ecological insight into change in the Gatekeeper population. Our work provides a computationally feasible framework for spatio‐temporally explicit integration of data within SDMs and demonstrates both the potential benefits and the challenges in applying this methodology to real ecological data.

Re-Inventories at Two Study Sites in the Oberpfalz (Bavaria, Germany): Increase in RWA Nests, Herb Biodiversity and Dead Wood in Sustainably Managed Forests

A large-scale re-inventory of red wood ant (RWA; Formica rufa-group) nests and a comparative analysis of their presence/absence data was carried out for the first time in 2023 at two study sites in the Oberpfalz, NE Bavaria, Germany, to investigate the suspected decline of nests, their relationship with forestry aspects, and possible changes in spatial distribution due to tectonic activity (GeoBio-Interactions). We inventoried, in two sustainably managed forests, outstanding nest occurrences (5393 nests including 5276 active nests) and an increase of ≈8% over 4–7 years. Our results do not support claims that the number of nests in the Oberpfalz is in sharp decline. RWA preferred mature and medium–mature pine-dominated forests. Standing and downed dead wood did not negatively affect nests. The number of nests with woodpecker cavities and the diversity of the herb layer increased. Nests clusters in NW–SE direction suggest a strong interaction between nest distribution and active tectonics. Our (re-)inventory approach combined with the extensive photo database is a valuable tool for (a) monitoring the entire forest habitat including natural restocking, herb biodiversity, woodpecker cavities, and dead wood in, at, and around nests, and (b) identifying GeoBio-Interactions. Such an approach will lead to more realistic counts of RWA nests and provide scientific evidence of the current situation of nests occurrence. We suggest seven to eight years as an appropriate time interval for re-inventories.

Multi-source remote sensing big data mining reveals cross-regional correlation between aquaculture and Enteromorpha disaster outbreaks

ABSTRACT Marine aquaculture is one of the most important marine resource utilization types, widely distributed in seashore areas. Because mass marine aquaculture development will lead to the eutrophication disaster of macroalgae blooms (green tide), it is imperative to discover the latent relationship. Inspired by the big data analysis theory, the spatiotemporal correlation change in 2017 and 2019 of the marine aquaculture and macroalgae blooms in Jiangsu Shoal in the West of the Yellow Sea and its adjacent seas were monitored and extracted respectively based on multi-source remote sensing images. Through optical and Synthetic Aperture Radar (SAR) images, the imaging characteristics of marine aquaculture in different growth cycles and sea conditions are analyzed. The relationship between the green tide and marine aquaculture harvest was explored from the early green algae distribution and spatiotemporal distribution changes. The earliest harvest area of marine aquaculture is the exact location of the outbreak of green tide. Along with the rapid reduction of aquaculture area, the distribution range of green tide gradually increased. The two showed opposite trends through many multi-source remote sensing data statistical analyses. Therefore, they have a strong correlation, which can be utilized to offer a significant value for the balance of marine environmental protection and resource development.

Characterization of Respirable Coal Mine Dust Recovered from Fibrous Polyvinyl Chloride Filters by Scanning Electron Microscopy

AbstractThe characterization of respirable dust on the basis of constituent fractions and particle sizes is increasingly of concern for evaluating exposure hazards. For high-resolution particle analysis, scanning electron microscopy with energy dispersive X-ray (SEM-EDX) can be an effective tool. However, it requires particles to be deposited on a smooth, uniform substrate such as a polycarbonate (PC) filter for optimal results. While direct sampling onto PC is possible, this is not the standard approach in many situations. For example, in coal mines, respirable dust samples have typically been collected onto polyvinyl chloride (PVC) filters because they are intended for gravimetric and/or infrared spectroscopy analysis. Such fibrous substrates are not ideal for SEM-EDX (or other microscopy), but an effective method to recover and redeposit the dust particles could render such samples suitable for the additional analysis. Here, we present a simple method and compare SEM-EDX results for paired samples analyzed directly on PC and following recovery from PVC and redeposition on PC. Both laboratory-generated dust samples (n = 10 pairs) and field samples of respirable coal mine dust (n = 44 pairs) are included in this study. Although some changes in particle size distributions were observed between samples analyzed directly and those that were recovered and redeposited prior to analysis, the results indicate the dust recovery method generally yields a representative sample in terms of mineral constituents. That said, results also highlighted the effects of high particle loading density on individual particle analysis. Considering all sample pairs, those with similar loading density between the directly analyzed and recovered sample tended to exhibit similar mineralogy distributions. This was generally the case for the lab-generated sample pairs, and the Freeman-Halton exact test of independence indicated that the samples in just three (of 10) pairs were in disagreement in terms of their mineralogy distributions. On the other hand, for the field samples, the directly analyzed sample often had higher loading density than the recovered sample; and the Freeman-Halton test showed that 25 (of 44) pairs were in disagreement. However, the effect of possible particle agglomeration on the directly analyzed samples cannot be ruled out—and exploration of this factor was beyond the scope of the current study.

Thermal Field Simulation and Optimization of PbF2 Single Crystal Growth by the Bridgman Method

PbF2 single crystals are usually grown in the temperature gradient region by the Bridgman–Stockbarger method. Temperature distribution during the growth process is particularly important for the preparation of high-quality crystals. In this study, the temperature field during the growth of the PbF2 single crystals was simulated based on the finite element method. The temperature distribution and temperature gradient changes in the crucible were investigated at different growth stages, including the seeding, shouldering, and iso-diameters stages. The calculated results show that as the crucible position continues downward during the growth process, the axial temperature gradient increases and then decreases from the bottom to the top of the crucible, with almost flat isotherms near the solid–liquid interface where the axial temperature gradient is larger. At the shoulder below the crucible, the solid–liquid interface was improved by adjusting the tilt angle. Furthermore, based on a novel design of the heat-insulating baffle, the concave solid–liquid interface in the iso-diameter stage can be effectively adjusted to realize a lower radial temperature gradient. This study provides theoretical guidance for the optimization of the growth of high-quality PbF2 crystals by the Bridgman method.

Impact of Dynamic Wheel Loading on Flexible Pavement Responses for Non-Free Rolling Conditions

Since 2000, pavement design methodologies have transitioned from empirical to mechanistic-empirical procedures. However, the complexities of loading patterns, contact stress distribution, material characterization, vehicle maneuvering, and dynamic load amplification are still not fully considered, despite their significant effect on pavement performance. In this study, state-of-the-art numerical models were used to investigate the changes in critical pavement responses derived from the combined effect of roughness-induced dynamic loading and vehicle maneuvering. A decoupled vehicle–tire–pavement interaction approach composed of a random process to generate artificial road roughness profiles, a mechanical full truck model, and three-dimensional finite element tire and flexible pavement models allow the prediction of the impact of road roughness on vehicle dynamics. In addition, the study quantifies the effect of dynamic loading on contact stresses, and consequently, on pavement critical responses. Because of the expected increase in axle weight from truck electrification, overweight scenarios were also considered. Changes in load history and distribution of strain fields were assessed for two typical pavement structures (thin and thick). The combined effect of roughness-induced dynamic loading and vehicle maneuvering greatly altered the critical pavement responses associated with bottom-up fatigue cracking, near-surface cracking, and rutting. Under the most adverse conditions, the critical tensile strains at the bottom of the asphalt concrete increased up to 125%, the shear strain increased up to 100%, and the compressive strain escalated to 120% when compared with the reference cases. Higher temperatures exacerbated the impact of dynamic wheel loading and vehicle maneuvering.

Tracking states and transitions in semiarid rangelands: A spatiotemporal archetypal analysis of productivity dynamics using wavelets

Climate change poses challenges in classifying ecosystem dynamics, as they are influenced by shifting dynamics resulting from changes in climate forces and meteorological variables, including temperature and water availability. To address this, our study presents a novel approach using Continuous Wavelet Transform (CWT) and power spectrum analysis to classify vegetation dynamics, considering the time-dependent variability of ecosystem frequencies. We applied our method to centred and standardized MODIS NDVI time series for the period 2000–2021, using an experimental field station in northern Patagonia as a case study. By performing a continuous wavelet transform on the data for each pixel, we obtained instantaneous power spectra, capturing variability across different dates and pixels. These spectrums were then consolidated into a comprehensive database, and subsequently classified using archetypal analysis. We identified a convex combination of archetypal spectrums that best represented the entire power spectrum database. Mapping the resulting archetypes and their weights in both space and time allowed us to explore pixels' variations in archetype weights in relation to factors such as time, topography, and climate. In addition, to examine the potential relationship between the NDVI time series and climate drivers, we computed the Average Cross-Wavelet Power Spectrum (ACWPS) to different climatic indices. Three archetypes were sufficient to explain the majority of power spectrum variability in the study area. These archetypes exhibited distinctive characteristics: 1) medium-frequency variability (2–4 years), 2) low-frequency variability (>4 years), and 3) an annual (i.e. seasonal) cycle with low-frequency variability. Spatially, the first two archetypes were predominantly observed in highland steppes, while the third archetype prevailed in lowland areas associated with meadows. At the beginning of the studied period, Archetypes 1 and 3 dominated, but after the Puyehue-Cordón Caulle Volcanic Complex eruption in 2011 their prominence diminished, and Archetype 2 became more prevalent in the whole study area. Finally, all three NDVI series representative of archetypes showed a relative peak at approximately four years, which could be linked to the Indian Ocean Dipole variability. These results highlight an abrupt shift in the system's behaviour, primarily related to changes in variability distribution rather than mean values. This disturbance-induced transition aligns with the theory of state and transitions in ecological system dynamics. We propose that the states in this model are not fixed but represent alternative dynamic behaviours, akin to different types of limit cycles. Consequently, employing a wavelet analysis-based classification method provides a robust means of studying and understanding such variability and transitions, thereby offering clarity and comprehension of ecosystem states. Notably, this methodology proves particularly effective for large databases of detailed time series.

Noise source localization using deep learning

Summary Ambient noise source localization is of great significance for estimating seismic noise source distribution, understanding source mechanisms and imaging subsurface structures. The commonly used methods for source localization, such as the matched field processing and the full-waveform inversion, are time-consuming and not applicable for time-lapse monitoring of the noise source distribution. We propose an efficient alternative of using deep learning for noise source localization. In the neural network, the input data are noise cross-correlation functions and the output are matrices containing the information of noise source distribution. It is assumed that the subsurface structure is a horizontally layered earth model and the model parameters are known. A wavefield superposition method is employed to efficiently simulate ambient noise data with quantities of local noise sources labelled as training datasets. We use a weighted binary cross-entropy loss function to address the prediction inaccuracy caused by a sparse label matrix during training. The proposed deep learning framework is validated by synthetic tests and two field data examples. The successful applications to locate an anthropogenic noise source and a carbon dioxide (CO2) degassing area demonstrate the accuracy and efficiency of the proposed deep learning method for noise source localization, which has great potential for monitoring the changes of the noise source distribution in a survey area.

Body fat and circulating leptin levels in the captive short-beaked echidna (Tachyglossus aculeatus).

It is possible that the reproductive strategy of the short-beaked echidna is related to seasonal changes in fat deposition and energy availability, regulated by seasonal changes in endocrine function. We predicted that circulating leptin levels would be directly proportional to adiposity during most of the year, but that a change in this relationship would occur during the pre-breeding season to allow increased fat deposition. To test this hypothesis, we made use of a captive colony of echidnas to describe and quantify changes in fat distribution and the adipostatic hormone leptin. First we assessed seasonal changes in circulating leptin levels, body mass and adiposity for three male and three female adult echidnas maintained on a standard diet. Second, we explored the relationship between circulating leptin levels and increased caloric intake for an additional five adult female echidnas that were provided with supplemented nutrition. Third we visualised fat distribution in male and female adult echidnas using magnetic resonance imaging (MRI) before and after the breeding season, to determine where fat is deposited in this species. For echidnas maintained on the standard diet, there were no seasonal changes in body mass, body fat or plasma leptin levels. However, female echidnas provided with supplemented nutrition had significantly elevated plasma leptin levels during the breeding season, compared to the pre-and post- breeding periods. MRI showed substantial subcutaneous fat depots extending dorso-laterally from the base of the skull to the base of the tail, in both sexes. Pre-breeding season, both sexes had considerable fat deposition in the pelvic/rump region, whilst the female echidna accumulated most fat in the abdominal region. This study shows that male and female echidnas accumulate body fat in the pelvic/rump and the abdominal regions, respectively and that circulating leptin may promote fattening in female echidnas during the breeding season by means of leptin resistance. However, further research is required to evaluate the precise relationship between seasonal changes in leptin and adiposity.

Outstanding Lithium Storage Performance of a Copper‐Coordinated Metal‐Covalent Organic Framework as Anode Material for Lithium‐Ion Batteries

Metal‐covalent organic frameworks (MCOF) as a bridge between covalent organic framework (COF) and metal organic framework (MOF) possess the characteristics of open metal sites, structure stability, crystallinity, tunability as well as porosity, but still in its infancy. In this work, a covalent organic framework DT‐COF with a keto‐enamine structure synthesized from the condensation of 3,3′‐dihydroxybiphenyl diamine (DHBD) and triformylphloroglucinol (TFP) was coordinated with Cu2+ by a simple post‐modification method to a obtain a copper‐coordinated metal‐covalent organic framework of Cu‐DT COF. The isomerization from a keto‐enamine structure of DT‐COF to a enol‐imine structure of Cu‐DT COF is induced due to the coordination interaction of Cu2+. The structure change of Cu‐DT COF induces the change of the electron distribution in the Cu‐DT COF, which greatly promotes the activation and deep Li‐storage behavior of the COF skeleton. As anode material for lithium‐ion batteries (LIBs), Cu‐DT COF exhibits greatly improved electrochemical performance, retaining the specific capacities of 760 mAh g−1 after 200 cycles and 505 mAh g−1 after 500 cycles at a current density of 0.5 A g−1. The preliminary lithium storage mechanism studies indicate that Cu2+ is also involved in the lithium storage process. A possible mechanism for Cu‐DT COF was proposed on the basis of FT‐IR, XPS, EPR characterization and electrochemical analysis. This work enlightens a novel strategy to improve the energy storage performance of COF and promotes the application of COF and MCOF in LIBs.

How to beat the bull: Lycopene as a tool to improve in vitro fertilization efficiency in bulls with high polyspermy

High levels of reactive oxygen species (ROS) derived from in vitro conditions compromise oocyte quality and subsequent polyspermy prevention by the zona and membrane block. Antioxidant supplementation, like lycopene, during in vitro maturation (IVM) mitigates ROS effects, yet, its efficacy in blocking polyspermy remains uncertain. This study aims to evaluate the effect of lycopene supplementation during IVM on oocyte maturation, fertilization, and developmental parameters. To this end, bovine oocytes were supplemented with 0.2 µM lycopene and fertilized with semen from three bulls. The three bulls showed different fertilization potential in vitro, with bull 1 showing the highest penetration and polyspermy rates and the lowest in vitro fertilization (IVF) efficiency. Interestingly, in bull 1, the treatment with lycopene improved IVF efficiency (p = 0.043) and reduced the polyspermy rate (p = 0.028). However, none of these effects were observed in bulls 2 and 3. Bulls with higher penetration rates exhibited better blastocyst rates although those rates did not seem to be associated with polyspermy or IVF efficiency. Oocyte mitochondrial distribution and activity and cortical granule migration and distribution were not influenced by lycopene. In conclusion, we demonstrated that lycopene addition during oocyte maturation had a positive impact on IVF efficiency by reducing polyspermy rates in a bull-dependent manner. The reduction in polyspermy rates was not caused by changes in cortical granule migration or oocyte mitochondrial distribution. Lycopene must therefore induce other changes in the oocyte that lower the in vitro penetration rates of specific bulls prone to polyspermy.

Quantitative MRI imaging of parenchyma and venation networks in Brassica napus leaves: effects of development and dehydration

BackgroundCharacterisation of the structure and water status of leaf tissues is essential to the understanding of leaf hydraulic functioning under optimal and stressed conditions. Magnetic Resonance Imaging is unique in its capacity to access this information in a spatially resolved, non-invasive and non-destructive way. The purpose of this study was to develop an original approach based on transverse relaxation mapping by Magnetic Resonance Imaging for the detection of changes in water status and distribution at cell and tissue levels in Brassica napus leaves during blade development and dehydration.ResultsBy combining transverse relaxation maps with a classification scheme, we were able to distinguish specific zones of areoles and veins. The tissue heterogeneity observed in young leaves still occurred in mature and senescent leaves, but with different distributions of T2 values in accordance with the basipetal progression of leaf blade development, revealing changes in tissue structure. When subjected to severe water stress, all blade zones showed similar behaviours.ConclusionThis study demonstrates the great potential of Magnetic Resonance Imaging in assessing information on the structure and water status of leaves. The feasibility of in planta leaf measurements was demonstrated, opening up many opportunities for the investigation of leaf structure and hydraulic functioning during development and/or in response to abiotic stresses.

Incorporating physiological knowledge into correlative species distribution models minimizes bias introduced by the choice of calibration area

AbstractCorrelative species distribution models (SDMs) are important tools to estimate species’ geographic distribution across space and time, but their reliability heavily relies on the availability and quality of occurrence data. Estimations can be biased when occurrences do not fully represent the environmental requirement of a species. We tested to what extent species’ physiological knowledge might influence SDM estimations. Focusing on the Japanese sea cucumber Apostichopus japonicus within the coastal ocean of East Asia, we compiled a comprehensive dataset of occurrence records. We then explored the importance of incorporating physiological knowledge into SDMs by calibrating two types of correlative SDMs: a naïve model that solely depends on environmental correlates, and a physiologically informed model that further incorporates physiological information as priors. We further tested the models’ sensitivity to calibration area choices by fitting them with different buffered areas around known presences. Compared with naïve models, the physiologically informed models successfully captured the negative influence of high temperature on A. japonicus and were less sensitive to the choice of calibration area. The naïve models resulted in more optimistic prediction of the changes of potential distributions under climate change (i.e., larger range expansion and less contraction) than the physiologically informed models. Our findings highlight benefits from incorporating physiological information into correlative SDMs, namely mitigating the uncertainties associated with the choice of calibration area. Given these promising features, we encourage future SDM studies to consider species physiological information where available.

Mechanistic account of distinct change in organic anion transporting polypeptide 1B (OATP1B) substrate pharmacokinetics during OATP1B-mediated drug-drug interactions using physiologically-based pharmacokinetic modeling.

The role of transporters in drug clearance is widely acknowledged, directly and indirectly by facilitating tissue/enzyme exposure. Through the latter, transporters also affect volume of distribution. Drug-drug interactions (DDIs) involving organic anion transporting polypeptides (OATPs) 1B1/1B3 and SLCO1B1 pharmacogenetics lead to altered pharmacokinetics of OATP1B substrates; however, several factors may confound direct interpretation of pharmacokinetic parameters from these clinical studies using noncompartmental analysis (NCA). A review of clinical data herein indicates a single dose of OATP1B inhibitor rifampin almost never leads to increased substrate half-life but often a decrease, and that most clinical OATP1B substrates are CYP3A4 substrates and/or undergo enterohepatic cycling (EHC). Using hypothetically simple OATP1B substrate physiologically-based pharmacokinetic (PBPK) models, simulated effect of rifampin differed from specific OATP1B inhibition, due to short rifampin half-life causing dissipation of OATP1B inhibition over time combined with CYP3A4 induction. Calculated using simulated tissue data, volume of distribution indeed decreased with OATP1B inhibition and was expectedly limited to the contribution of liver volume. However, an apparent and counterintuitive effect of rifampin on volume greater than that on clearance resulted for CYP3A4 substrates, using NCA. Effect of OATP1B inhibition and rifampin on OATP1B substrate models incorporating EHC +/- renal clearance was distinct compared to simpler models. Using PBPK models incorporating reversible lactone metabolism for clinical OATP1B substrates atorvastatin and pitavastatin, DDIs reporting decreased half-life with rifampin were reproduced. These simulations provide explanation for the distinct change in OATP1B substrate pharmacokinetics observed in clinical studies, including changes in volume of distribution and additional mechanisms. Significance Statement Transporters are involved in both drug clearance and volume of distribution and distinct changes in OATP1B substrate pharmacokinetics are observed with OATP1B inhibitor rifampin. Using hypothetical and validated PBPK models and simulations we address the limitations of single-dose rifampin and complicated clinical OATP1B substrate disposition in evaluating the pharmacokinetic parameters of OATP1B substrates during rifampin DDIs. These models account for the change in volume of distribution and identify additional mechanisms underlying apparent pharmacokinetic changes in OATP1B DDIs.

Extralimital terrestrials: A reassessment of range limits in Alaska's land mammals.

Understanding and mitigating the effects of anthropogenic climate change on species distributions requires the ability to track range shifts over time. This is particularly true for species occupying high-latitude regions, which are experiencing more extreme climate change than the rest of the world. In North America, the geographic ranges of many mammals reach their northernmost extent in Alaska, positioning this region at the leading edge of climate-induced distribution change. Over a decade has elapsed since the publication of the last spatial assessments of terrestrial mammals in the state. We compared public occurrence records against commonly referenced range maps to evaluate potential extralimital records and develop repeatable baseline range maps. We compared occurrence records from the Global Biodiversity Information Facility for 61 terrestrial mammal species native to mainland Alaska against a variety of range estimates (International Union for Conservation of Nature, Alaska Gap Analysis Project, and the published literature). We mapped extralimital records and calculated proportions of occurrences encompassed by range extents, measured mean direction and distance to prior range margins, evaluated predictive accuracy of published species models, and highlighted observations on federal lands in Alaska. Range comparisons identified 6,848 extralimital records for 39 of 61 (63.9%) terrestrial mainland Alaskan species. On average, 95.5% of Alaska Gap Analysis Project occurrence records and ranges were deemed accurate (i.e., > 90.0% correct) for 31 of 37 species, but overestimated extents for 13 species. The International Union for Conservation of Nature range maps encompassed 68.1% of occurrence records and were > 90% accurate for 17 of 39 species. Extralimital records represent either improved sampling and digitization or actual geographic range expansions. Here we provide new data-driven range maps, update standards for the archiving of museum-quality locational records and offer recommendations for mapping range changes for monitoring and conservation.