This study examines the influence of the Russo-Ukrainian war on financial markets, conditioned upon a country's dependence on Russian commodities, employing a large panel of 73 countries. Financial markets reacted to the war-induced shock significantly, with a weaker effect on asset prices than volatility. Markets perceived the dependence on Russian commodities as a significant risk factor, sinking stock returns and intensifying instability. The effect of the war on returns was significant for countries with a dependence beyond the [0-20%] level, suggesting a threshold for an adverse effect on asset prices. The armed conflict exacerbated volatility regardless of dependence levels; the effect increased with dependence. Results have implications for diversification strategies in international exchanges.
Growing genetically resistant plants allows pathogen populations to be controlled and reduces the use of pesticides. However, pathogens can quickly overcome such resistance. In this context, how can we achieve sustainable crop protection? This crucial question has remained largely unanswered despite decades of intense debate and research effort. In this study, we used a bibliographic analysis to show that the research field of resistance durability has evolved into three subfields: (i) ‘plant breeding’ (generating new genetic material), (ii) ‘molecular interactions’ (exploring the molecular dialogue governing plant–pathogen interactions) and (iii) ‘epidemiology and evolution’ (explaining and forecasting of pathogen population dynamics resulting from selection pressure(s) exerted by resistant plants). We argue that this triple split of the field impedes integrated research progress and ultimately compromises the sustainable management of genetic resistance. After identifying a gap among the three subfields, we argue that the theoretical framework of population genetics could bridge this gap. Indeed, population genetics formally explains the evolution of all heritable traits, and allows genetic changes to be tracked along with variation in population dynamics. This provides an integrated view of pathogen adaptation, in particular via evolutionary–epidemiological feedbacks. In this Opinion Note, we detail examples illustrating how such a framework can better inform best practices for developing and managing genetically resistant cultivars.
High-throughput DNA sequencing is becoming an increasingly important tool to monitor and better understand biodiversity responses to environmental changes in a standardized and reproducible way. Environmental DNA (eDNA) from organisms can be captured in ecosystem samples and sequenced using metabarcoding, but processing large volumes of eDNA data and annotating sequences to recognized taxa remains computationally expensive. Speed and accuracy are two major bottlenecks in this critical step. Here, we evaluated the ability of convolutional neural networks (CNNs) to process short eDNA sequences and associate them with taxonomic labels. Using a unique eDNA data set collected in highly diverse Tropical South America, we compared the speed and accuracy of CNNs with that of a well-known bioinformatic pipeline (OBITools) in processing a small region (60 bp) of the 12S ribosomal DNA targeting freshwater fishes. We found that the taxonomic labels from the CNNs were comparable to those from OBITools, with high correlation levels for the composition of the regional fish fauna. The CNNs enabled the processing of raw fastq files at a rate of approximately 1 million sequences per minute, which was about 150 times faster than with OBITools. Given the good performance of CNNs in the highly diverse ecosystem considered here, the development of more elaborate CNNs promises fast deployment for future biodiversity inventories using eDNA.
We propose a database to describe the Bay of Biscay mixed demersal European fishery over the period 2010–2020 for the ISIS-Fish simulation tool. It was built upon national and European fishing databases, scientific survey datasets, models estimates, literature, and the formulation of assumptions. It accounts explicitly for spatial and seasonal processes, and for mixed fisheries phenomenons. This database encompasses population dynamics for 3 stocks, hake, sole and Norway lobster, exploitation dynamics for numerous fleets and métiers, and the description of current fishing management, as well as fishers adaptation. A calibration procedure was designed to ensure consistency between all these diverse and heterogeneous parameters compiled and estimated in the ISIS-Fish database and to ensure the model reproduces closely historical catch patterns. This database is a starting point towards operational simulations, of use for understanding the functioning of the fishery, the assessment of management strategies, or delivering short and long-term scenarios. It can be used to reproduce historical catch patterns, with room for improvement on some inter-annual and spatial dynamics.
Growing genetically resistant plants allows pathogen populations to be controlled and reduces the use of chemicals. However, pathogens can quickly overcome such resistance. In this context, how can we achieve sustainable crop protection? This crucial question has remained largely unanswered despite decades of intense debate and research effort. In this study, we used a bibliographic analysis to show that the research field of resistance durability has evolved into three subfields: (i) ‘plant breeding’ (generating new genetic material), (ii) ‘molecular interactions’ (exploring the molecular dialogue governing plant–pathogen interactions) and (iii) ‘epidemiology and evolution’ (explaining and forecasting of pathogen population dynamics resulting from selection pressure(s) exerted by resistant plants). We argue that this triple split of the field impedes integrated research progress and ultimately compromises the sustainable management of genetic resistance. After identifying a gap among the three subfields, we argue that the theoretical framework of population genetics could bridge this gap. Indeed, population genetics formally explains the evolution of all heritable traits, and allows genetic changes to be tracked along with variation in population dynamics. This provides an integrated view of pathogen adaptation, notably via evolutionary–epidemiological feedbacks. In this Opinion Note, we detail examples illustrating how such a framework can better inform best practice for developing and managing genetically resistant cultivars.
Discarding practices have become a source of concern for the perennation of marine resources, prompting efforts of discard reduction around the globe. However, little is known about the fate of discards in marine environments. Discarding may provide food for various marine consumers, potentially affecting food web structure and stability. Yet, quantifying reliance upon discards is difficult because identity and frequency of discards may change according to multiple factors, and most previously used diet assessment techniques do not allow to assume consistency of feeding strategies over time. One currently untested hypothesis is that significant contribution of discards over time should reflect in increased trophic level (TL) of marine fauna, particularly in low TL consumers. Here, we explored this hypothesis by modeling the TL and assimilated diet of consumers living in fishing grounds subject to important discarding activity using stable isotope analysis. We found indications that benthic invertebrates and Chondrichthyes may depict a higher than expected TL, while other fish tend to depict similar to lower TL compared to global averages from the literature. Based on prior knowledge of discard consumption in the same area, stable isotope mixing models congruently revealed that discards may represent substantial portions of the assimilated diet of most benthic invertebrate macrofauna, cephalopods and Chondrichthyes. We highlight limitations and challenges of currently used diet assessment techniques to study discard consumption and stress that understanding their reintegration in marine food webs is crucial in the context of an ecosystem approach to fisheries management and to better understand the functioning of marine ecosystems subject to fishing.
When it comes to the agroecological transition, biodiversity plays a central role in terms of the ecosystem services provided and their role in helping crops adapt to abiotic and biotic stresses. Ecological processes that can support crop adaptation to stresses include biological interactions, such as those between microorganisms and pests (e.g. competition, predation and parasitism), and interactions between microorganisms, plants and pests that modulate plant immunity. The impact of microbiota on crop health and yield has been demonstrated in recent studies describing the relationships between microbiota diversity and various plant phenotypic traits (e.g. disease suppression or resistance and growth promotion). The farming system, plant genotype and plant association are all factors that influence the composition of the plant microbiota, and they must be considered to develop crop management strategies based on improving or maintaining beneficial plant-microbiota interactions. Managing microbiota to improve agricultural production can be achieved by leveraging different plant associations to modulate the soil microbiota and/or by inoculating crops with a microbial strain or consortium with properties that are beneficial to plant growth and health.
Sweetened yogurts can contain between 10 and 13% added sugar. However, studies have shown that sugar reduction or replacement can influence yogurt quality. The main objective of this research was to investigate the effects of yogurt with added natural sweeteners on temporal sensory profile, liking, satiety and postconsumption measures. Yogurt samples were prepared with iso‐sweet concentrations of sucrose (9 g/100 g of plain yogurt) using xylitol (10 g/100 g), stevia (0.15 g/100 g), and monk fruit (0.15 g/100 g). Fifty panelists evaluated the temporal sensory profile of these yogurts using multiple‐intake temporal dominance of sensations (TDS), and overall liking for each intake. In addition, satiety (hunger, thirst, and fullness) and other postconsumption attributes (healthiness, satisfaction, and purchase intent) were determined. The temporal profile of yogurt sweetened with xylitol was similar to yogurt sweetened with sucrose without any onset of negative sensory characteristics at any point in intake. Yogurt sweetened with stevia had a high dominance duration for astringency. Moreover, yogurt sweetened with monk fruit showed increased dominance of attributes bitter and astringent from the first to third intake. In terms of liking, yogurt containing xylitol was scored the highest followed by stevia and monkfruit. Sweet was a positive temporal driver of liking in yogurt sweetened with monk fruit. However, mouthcoating, sweet, and sour decreased liking in yogurt sweetened with sucrose, xylitol, and stevia respectively. In terms of perceived healthiness, satisfaction and purchase intent, yogurt sweetened with sucrose scored the highest followed by xylitol. Consumption of yogurt sweetened with xylitol, stevia, or monk fruit significantly decreased hunger compared to yogurt sweetened with sucrose. The current findings will play an important role for the dairy industry in understanding how sugar replacement with natural sweeteners in yogurt can influence its sensory perception and postconsumption behavior.
The growth of the urban population promotes a strong pressure to occupy open spaces in urban center, including around watercourses. Canalization and drainage techniques favored urban expansion and occupation of these spaces. In long term, this has not been efficient, since it is not a sustainable decision, mainly in view of the challenges provided by climate change. The purpose of this work was to analyze the modification of the landscape and multifunctionality of the urban watercourses in relation to socioeconomic and environmental scope of the evolution of an urban area using Lavras city, Brazil, as model. For that, city's hydrographic grid was drawn from the digital elevation model (DEM) corrected by manual vectorization after field visits and analysis of high-resolution images. To understand natural and sociocultural evolution processes, a compilation of geo-historical information about the origin and formation of the city was made using Patchwork Quilt methodology. To understand the actions and perceptions of different actors from urban watercourses in Lavras, questionnaires were applied to the population, and interviews were directed to the public and private managers. It was observed that the watercourses and their surroundings lost a large part of their natural, social, and economic functions, after the 1980s, only having a drainage function. The areas in expansion prioritize the natural function preservation but lack the incentive to implement the other functions such as social and economic. With the economic valuation of land, the implementation of green and blue infrastructure has not yet been prioritized. Even with the legislation that provides multifunctional uses for rivers and their banks, the urban watercourses from Lavras remained largely monofunctional. This did not contribute to increasing the city's green areas and the reintegration of watercourses into the urban landscape. The population values the water present in the urban landscape and yearns for multifunctional solutions such as green areas and urban gardens. Public and private actors recognize the lack of clarity in the legislation, and in the definition of concepts and techniques to be adopted. Multifunctional solutions can be in favor of reconciling different interests, promoting the reintegration of rivers into the urban landscape.
We present XEM, an eXplainable-by-design Ensemble method for Multivariate time series classification. XEM relies on a new hybrid ensemble method that combines an explicit boosting-bagging approach to handle the bias-variance trade-off faced by machine learning models and an implicit divide-and-conquer approach to individualize classifier errors on different parts of the training data. Our evaluation shows that XEM outperforms the state-of-the-art MTS classifiers on the public UEA datasets. Furthermore, XEM provides faithful explainability-by-design and manifests robust performance when faced with challenges arising from continuous data collection (different MTS length, missing data and noise).
The global biodiversity crisis from anthropogenic activities significantly weakens the functioning of marine ecosystems and jeopardizes their ecosystem services. Increasing monitoring of marine ecosystems is crucial to understand the breadth of the changes in biodiversity, ecosystem functioning and propose more effective conservation strategies. Such strategies should not only focus on maximizing the number of species (i.e., taxonomic diversity) but also the diversity of phylogenetic histories and ecological functions within communities. To support future conservation decisions, multicomponent biodiversity monitoring can be combined with high‐throughput species assemblage detection methods such as environmental DNA (eDNA) metabarcoding. Here, we used eDNA to assess fish biodiversity along the coast of southern Brittany (France, Iroise Sea). We filtered surface marine water from 17 sampling stations and applied an eDNA metabarcoding approach targeting Actinopterygii and Elasmobranchii taxa. We documented three complementary biodiversity components—taxonomic, phylogenetic, and functional diversity—and three diversity facets—richness, divergence and regularity. We identified a north/south contrast with higher diversity for the three facets of the biodiversity components in the northern part of the study area. The northern communities showed higher species richness, stronger phylogenetic overdispersion and lower functional clustering compared to the ones in the southern part, due to the higher diversity of habitats (reefs, rocky shores) and restricted access for fishing. Moreover, we also detected a higher level of taxonomic, phylogenetic, and functional uniqueness in many offshore stations compared to more coastal ones, with the presence of species typically living at greater depths (> 300 m), which suggests an influence of hydrodynamic structures and currents on eDNA dispersion and hence sample composition. eDNA metabarcoding can, therefore, be used as an efficient sampling method to reveal fine‐scale community compositions and in combination with functional and phylogenetic information to document multicomponent biodiversity gradients in coastal marine systems. By filtering surface marine water and using eDNA we assessed fish biodiversity along the coast of southern Brittany (Iroise Sea). For Actinopterygii and Elasmobranchii taxa, we documented three complementary biodiversity components ‐ taxonomic, phylogenetic and functional diversity ‐ and three diversity facets ‐ richness, divergence and regularity. We identified a north/south gradient with a higher diversity for the three facets of the biodiversity components in the northern part of the study area.
Understanding the ecological rules structuring the organization of species interactions is a prerequisite to predicting how ecosystems respond to environmental changes. While the ecological determinants of single networks have been documented, it remains unclear whether network ecological rules are conserved along spatial and environmental gradients. To address this gap, we reconstructed 48 plant–herbivore interaction networks along six elevation gradients in the Central European Alps in Switzerland, using DNA metabarcoding on orthoptera feces. We developed hypotheses on the ecological mechanisms expected to structure interaction networks, based on plant phylogeny, plant abundance, leaf toughness, leaf nitrogen content and plant metabolomics. We show that plant phylogenetic relationships and species abundance have the greatest explanatory power regarding the structure of the ecological networks. Moreover, we found that leaf nitrogen content is a key determinant of interactions in warmer environments, while phenolic compounds and terpenoids are more important in colder environments, suggesting that determinants of species interactions can shift along environmental gradients. With this work, we propose an approach to study the mechanisms that structure the way species interact with each other between bioregions and ecosystems.
Little is known about the impact of social and environmental enrichment on improving livestock resilience, i.e. the ability to quickly recover from perturbations. We evaluated the effect of an alternative housing system (AHS) on resilience of pigs, as compared to conventional housing (CONV). The AHS consisted of multi-litter housing during lactation, delayed weaning, extra space allowance and environmental enrichment at all times. We assessed recovery to a 2 h-transport challenge, an LPS injection, 2 h-heat stress and a biopsy wound in 96 pigs. Additionally, indicators of long-term “wear and tear” on the body were determined. AHS pigs had better physiological recoveries with quicker returns to baseline in the transport and LPS challenges, showed lower cortisol accumulation in hairs and lower variance in weight gain over the experimental period compared to conventionally-housed (CONV) pigs. They also had higher levels of natural antibodies binding KLH than CONV pigs. Their response to heat stress revealed a different strategy compared to CONV pigs. Taken together, AHS pigs appear to be more resilient and experience less chronic stress. Enhancing welfare by provision of social and environmental enrichment that better meets the behavioural needs of pigs seems to be a promising approach to improve their resilience.
Increasing speed and magnitude of global change threaten the world’s biodiversity and particularly coral reef fishes. A better understanding of large-scale patterns and processes on coral reefs is essential to prevent fish biodiversity decline but it requires new monitoring approaches. Here, we use environmental DNA metabarcoding to reconstruct well-known patterns of fish biodiversity on coral reefs and uncover hidden patterns on these highly diverse and threatened ecosystems. We analysed 226 environmental DNA (eDNA) seawater samples from 100 stations in five tropical regions (Caribbean, Central and Southwest Pacific, Coral Triangle and Western Indian Ocean) and compared those to 2047 underwater visual censuses from the Reef Life Survey in 1224 stations. Environmental DNA reveals a higher (16%) fish biodiversity, with 2650 taxa, and 25% more families than underwater visual surveys. By identifying more pelagic, reef-associated sequence assignment, possibly combined with incomplete detection in the environment, for some species. Combining eDNA metabarcoding and extensive visual census offers novel insights on the spatial organization of the richest marine ecosystems. and crypto-benthic species, eDNA offers a fresh view on assembly rules across spatial scales. Nevertheless, the reef life survey identified more species than eDNA in 47 shared families, which can be due to incomplete
Particle size-starch digestibility relationships were investigated in cryo- and hammer-milled (11 sizes) non-fractionated (compositionally homogeneous) potato flours. Hydration, pasting, structural, gelatinisation, colour, and time-course in vitro starch digestion properties were studied, revealing particle size differences as the sole factor. The flours’ starch digestograms were adequately (p ≤ 0.05) modelled with recent objective logarithm of slope procedure, and multiterm exponential and non-exponential equations. Heterogeneity tests significantly (p ≤ 0.05) revealed true mono-, bi-, and tri-phasic digestograms in the flours. Digestion parameters showed an inverse relationship with the particle size, the square (Ap²) of which linearly (p ≤ 0.05) related with the reciprocal of the rates of starch digestion (1/K) of the multiphasic starch digestograms. The inverse slope of 1/K-Ap² plots (0.04–2.58 × 10⁻⁷ cm² s⁻¹) revealed a diffusion-controlled digestion process. The study presents an innovative modelling of starch digestograms and the first particle size-starch digestibility relationships in multiphasic digestograms.
Estimating the efficiency of N utilization for milk production (MNE) of individual cows at a large scale is difficult, particularly because of the cost of measuring feed intake. Nitrogen isotopic discrimination (Δ¹⁵N) between the animal (milk, plasma, or tissues) and its diet has been proposed as a biomarker of the efficiency of N utilization in a range of production systems and ruminant species. The aim of this study was to assess the ability of Δ¹⁵N to predict the between-animal variability in MNE in dairy cows using an extensive database. For this, 20 independent experiments conducted as either changeover (n = 14) or continuous (n = 6) trials were available and comprised an initial data set of 1,300 observations. Between-animal variability was defined as the variation observed among cows sharing the same contemporary group (CG; individuals from the same experimental site, sampling period, and dietary treatment). Milk N efficiency was calculated as the ratio between mean milk N (grams of N in milk per day) and mean N intake (grams of N intake per day) obtained from each sampling period, which lasted 9.0 ± 9.9 d (mean ± SD). Samples of milk (n = 604) or plasma (n = 696) and feeds (74 dietary treatments) were analyzed for natural ¹⁵N abundance (δ¹⁵N), and then the N isotopic discrimination between the animal and the dietary treatment was calculated (Δ¹⁵n = δ¹⁵Nanimal − δ¹⁵Ndiet). Data were analyzed through mixed-effect regression models considering the experiment, sampling period, and dietary treatment as random effects. In addition, repeatability estimates were calculated for each experiment to test the hypothesis of improved predictions when MNE and Δ¹⁵N measurements errors were lower. The considerable protein mobilization in early lactation artificially increased both MNE and Δ¹⁵N, leading to a positive rather than negative relationship, and this limited the implementation of this biomarker in early lactating cows. When the experimental errors of Δ¹⁵N and MNE decreased in a particular experiment (i.e., higher repeatability values), we observed a greater ability of Δ¹⁵N to predict MNE at the individual level. The predominant negative and significant correlation between Δ¹⁵N and MNE in mid- and late lactation demonstrated that on average Δ¹⁵N reflects MNE variations both across dietary treatments and between animals. The root mean squared prediction error as a percentage of average observed value was 6.8%, indicating that the model only allowed differentiation between 2 cows in terms of MNE within a CG if they differed by at least 0.112 g/g of MNE (95% confidence level), and this could represent a limitation in predicting MNE at the individual level. However, the one-way ANOVA performed to test the ability of Δ¹⁵N to differentiate within-CG the top 25% from the lowest 25% individuals in terms of MNE was significant, indicating that it is possible to distinguish extreme animals in terms of MNE from their N isotopic signature, which could be useful to group animals for precision feeding.
Modelling how a pandemic is spreading over time is a challenging issue. The new coronavirus disease called COVID-19 does not escape this rule as it has embraced over two hundred countries. As for previous pandemics, several studies have attempted to model the occurrence of cases caused by COVID-19. However, no study has succeeded in accurately modelling the impact of the infectious agent. Here we show that COVID-19 daily case distribution in humans obeys a Gamma law, which two new parameters can describe without any adjustment. Though the Gamma law has been exploited for nearly two centuries to describe the statistical distribution of spatial or temporal quantities, the goodness-of-fit rationale using two or three parameters has remained enigmatic. The new Gamma law approach we demonstrate here emerges from actual data and sheds light on the underlying mechanisms of the observed phenomenon. This finding has promising applicability in the epidemiological domain and in all disciplines involving branching systems, for which our Gamma law approach may bring a solution to hitherto unsolved problems.
Propionibacterium freudenreichii is crucial in Swiss-type cheese manufacture. Classic propionic acid fermentation yields the nutty flavor and the typical eyes. Co-metabolism of aspartate pronounces the flavor of the cheese; however, it also increases the size of the eyes, which can induce splitting and reduce the cheese quality. Aspartase (EC 220.127.116.11) catalyzes the deamination of aspartate, yielding fumarate and ammonia. The aspartase activity varies considerably among P. freudenreichii strains. Here, the correlation between aspartase activity and the locus of aspartase-encoding genes (aspA ) and dcuA encoding the C4-dicarboxylate transporter was investigated in 46 strains to facilitate strain selection for cheese culture. Low aspartase activity was correlated with a particular genomic rearrangement: low in vitro aspartase activity always occurred in strains with gene clusters aspA - dcuA where the dcuA was frameshifted, producing a stop codon or was disrupted by an ISL3-like element. The low aspartase activity could be due to the protein sequence of the aspartase or a dysfunctional DcuA. The highest values of aspartase activity were detected in strains with aspA1 - aspA2-dcuA with a DcuA sequence sharing 99.07 – 100% identity with the DcuA sequence of strain DSM 20271 T and an additional C4-dicarboxylate transporter belonging to the DcuAB family.
Intranasal oxytocin (IN OXT) administration has been proposed as a pharmacological treatment for a range of biomedical conditions including neurodevelopmental disorders. However, studies evaluating the potential long-lasting effects of chronic IN OXT during development are still scarce. Here we conducted a follow-up study of a cohort of adult titi monkeys that received intranasal oxytocin 0.8 IU/kg (n = 15) or saline (n = 14) daily for six months during their juvenile period (12 to 18 months of age), with the goal of evaluating the potential long-lasting behavioral and neural effects one year post-treatment. Subjects were paired with an opposite-sex mate at 30 months of age (one year post-treatment). We examined pair affiliative behavior in the home cage during the first four months and tested for behavioral components of pair bonding at one week and four months post-pairing. We assessed long-term changes in brain glucose uptake using ¹⁸FDG positron emission tomography (PET) scans. Our results showed that OXT-treated animals were more affiliative across a number of measures, including tail twining, compared to SAL treated subjects (tail twining is considered the “highest” type of affiliation in titi monkeys). Neuroimaging showed no treatment differences in glucose uptake between SAL and OXT-treated animals; however, females showed higher glucose uptake in whole brain at 23 months, and in both the whole brain and the social salience network at 33 months of age compared to males. Our results suggest that chronic IN OXT administration during development can have long-term effects on adult social behavior.
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