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The impact of state-led traceability on fisheries sustainability
Get PDFThis article addresses two pivotal questions in the realm of fisheries sustainability: (1) the role of state-led traceability systems and (2) their effectiveness in bolstering sustainability efforts. Our investigation centres on the European Union's Catch Certificate (EU's CC), a traceability system to ensure that all seafood imported into the EU is sustainably harvested. We explore these two key questions though the Vietnamese fisheries reform, whereby the country adjusted its fisheries governance to accommodate the EU's CC as a traceability measure. Employing a mixed-methods approach, we uncover a mismatch between the top-down enforcement of traceability measures and the realities of fishing practices, leading to a range of rule-breaking behaviours. Furthermore, the study identifies significant issues of exclusion, as the infrastructural demands of compliance disproportionately affect smaller operators and marginalized communities within the fisheries sector. The Vietnamese case provides nuanced challenges and opportunities presented by state-led traceability in achieving true sustainability in fisheries. It underscores the necessity of integrating environmental and social considerations into traceability systems, questioning whom these efforts ultimately serve and at what cost. We conclude by advocating for state-led initiatives to go beyond mere compliance and contribute to a more sustainable, equitable, and transparent fisheries sector
Metabolic abnormalities and reprogramming in cats with naturally occurring hypertrophic cardiomyopathy
Get PDFBackground and aims The heart is a metabolic organ rich in mitochondria. The failing heart reprograms to utilize different energy substrates, which increase its oxygen consumption. These adaptive changes contribute to increased oxidative stress. Hypertrophic cardiomyopathy (HCM) is a common heart condition, affecting approximately 15% of the general cat population. Feline HCM shares phenotypical and genotypical similarities with human HCM, but the disease mechanisms for both species are incompletely understood. Our goal was to characterize global changes in metabolome between healthy control cats and cats with different stages of HCM. Methods Serum samples from 83 cats, the majority (70/83) of which were domestic shorthair and included 23 healthy control cats, 31 and 12 preclinical cats with American College of Veterinary Internal Medicine (ACVIM) stages B1 and B2, respectively, and 17 cats with history of clinical heart failure or arterial thromboembolism (ACVIM stage C), were collected for untargeted metabolomic analysis. Multiple linear regression adjusted for age, sex and body weight was applied to compare between control and across HCM groups. Results Our study identified 1253 metabolites, of which 983 metabolites had known identities. Statistical analysis identified 167 metabolites that were significantly different among groups (adjusted P < 0.1). About half of the differentially identified metabolites were lipids, including glycerophospholipids, sphingolipids and cholesterol. Serum concentrations of free fatty acids, 3-hydroxy fatty acids and acylcarnitines were increased in HCM groups compared with control group. The levels of creatine phosphate and multiple Krebs cycle intermediates, including succinate, aconitate and alpha-ketoglutarate, also accumulated in the circulation of HCM cats. In addition, serum levels of nicotinamide and tryptophan, precursors for de novo NAD+ biosynthesis, were reduced in HCM groups versus control group. Glutathione metabolism was altered. Serum levels of cystine, the oxidized form of cysteine and cysteine-glutathione disulfide, were elevated in the HCM groups, indicative of heightened oxidative stress. Further, the level of ophthalmate, an endogenous glutathione analog and competitive inhibitor, was increased by more than twofold in HCM groups versus control group. Finally, several uremic toxins, including guanidino compounds and protein bound putrescine, accumulated in the circulation of HCM cats. Conclusions Our study provided evidence of deranged energy metabolism, altered glutathione homeostasis and impaired renal uremic toxin excretion. Altered lipid metabolism suggested perturbed structure and function of cardiac sarcolemma membrane and lipid signalling
Factors influencing smartphone usage of rural farmers: Empirical analysis of five selected provinces in China
Get PDFThe increasing usage of smartphones by practitioners in various fields of expertise is attracting global attention. However, scanty evidence exists on smartphone usage among rural farmers in developing countries. Using data collected from 1286 rural farming households in five provinces in China, this study investigates the factors influencing rural farmers' decisions to use smartphones. The findings from a Probit model reveal that education, health condition, asset ownership, income levels, peers' smartphone usage, internet access, cooperative membership, access to credit, and off-farm work participation are the main factors driving smartphone usage of rural farmers. The age of the farmer rather affects smartphone usage negatively and significantly. Further heterogeneous analysis shows that the influences of factors on smartphone usage vary across the survey provinces
Growth of hydrogenotrophic methanogen Methanoculleus bourgensis MAB1 in the presence of dunite
Get PDFThis study investigated the long-term potential of low-temperature serpentinization of dunite to support the growth of the hydrogenotrophic methanogen Methanoculleus bourgensis strain MAB1. Incubation experiments were conducted for over 800 days, using dunite powder as the sole energy source, with and without the addition of nickel, an essential cofactor for methanogenesis. The results indicated that hydrogen released from dunite was sufficient to sustain methanogen growth, but the process was slow, with methane production beginning only after approximately 300 days. The release of toxic metals from dunite, particularly zinc, appeared to inhibit methanogen growth over time, leading to the cessation of methane production after 528 days and likely the lysing of the methanogenic cells. The study suggests that hydrogen availability, rather than nickel, is the limiting factor for methanogen growth in these conditions
Multispectral drone images for the early detection of bark beetle infestations: assessment over large forest areas in the Italian South-Eastern Alps
Get PDFIntroduction European forests face increasing threats from climate change-induced stressors, which create favorable conditions for bark beetle outbreaks. The most critical spruce forest pest in Europe is the European Spruce Bark Beetle (Ips typographus L.). Effective forest management of this beetles' outbreaks necessitates timely detection of recently attacked spruce trees, which is challenging given the difficulty in identifying symptoms on infested tree crowns, especially over large areas. This study assessed the detectability of infested trees over large spruce dominated areas (20-60 ha) using high-resolution drone multispectral imagery.Methods A multispectral sensor mounted on an Unmanned Aerial Vehicle (UAV) was used to capture images of the investigated spruce stands weekly during June 2023. These were used to compute the reflectance of all single trees, derive vegetation indices, and then compare these between bark beetle infested trees and healthy ones.Results The results showed that it was possible to separate the spectral features of recently infested trees from the healthy trees during the final developmental stage of the first beetles' generation, despite the limitations due to difficulties in image processing over large areas. The best performing vegetation indices included NDRE (Normalized Difference Red Edge index) and GNDVI (Green Normalized Difference Vegetation Index), which allowed the earlier separation between infested and healthy trees.Discussion The study shows that the use of UAV high-resolution imagery can present some limitations when performing early detection over larger areas. The integration of sensors focused on narrower spectral windows around the Red-Edge and Green bands and other remote sensing methods (e.g., satellite imagery) could help overcome these limitations and improve early-detection over large forest areas. The proposed early-detection approach will increase the understanding of which factors to consider when performing early detection with remote sensing techniques. In particular, it will add insights when upscaling to larger spatial scales, providing useful guidance for the management of areas suffering pest outbreaks
Downstream Temperature Effects of Boreal Forest Clearcutting Vary With Riparian Buffer Width
Get PDFClearcutting increases temperatures of forest streams, and, in temperate zones, the effects can extend far downstream of the clearcut itself. Here, we studied whether similar patterns are found in colder, boreal zones, and if riparian buffers can prevent stream water from heating up. We recorded temperature at 45 locations across nine streams with varying buffer widths. In these streams, we compared upstream (control) reaches with reaches at clearcuts and up to 150 m immediately downstream of the clearcut. In summer, we found daily maximum water temperature increases at clearcuts up to 4.1 degrees C, with the warmest week ranging from 12.0 degrees C to 18.6 degrees C. We further found that warming was sustained 150 m downstream of clearcuts in three out of six streams with buffers <10 m. Surprisingly, temperature patterns in autumn resembled those in summer, yet, with lower absolute temperatures (maximum warming was 1.9 degrees C in autumn). Clearcuts in boreal forests can indeed warm streams, and, because these temperature effects are propagated downstream, we risk catchment-scale effects and cumulative warming when streams pass through several clearcuts. In this study, riparian buffers wider than 15 m protected against water temperature increases; hence, we call for a general increase of riparian buffer width along small streams in boreal forests
Multi-Block Chemometric Approaches to the Unsupervised Spectral Characterization of Geological Samples
Get PDFAs an example for the potential use of multi-block chemometric methods to provide improved unsupervised characterization of compositionally complex materials through the integration of multi-modal spectrometric data sets, we analysed spectral data derived from five field instruments (one XRF, two NIR, and two FT-Raman), collected on 76 bedrock samples of diverse composition. These data were analysed by single- and multi- block latent variable models, based on principal component analysis (PCA) and partial least squares (PLS). For the single-block approach, PCA and PLS models were generated; whilst hierarchical partial least squares (HPLS) regression was applied for the multi-block modelling. We also tested whether dimensionality reduction resulted in a more computationally efficient muti-block HPLS model with enhanced model interpretability and geological characterization power using the variable influence on projection (VIP) feature selection method.The results showed differences in the characterization power of the five spectrometer data sets for the bedrock samples based on their mineral composition and geological properties; moreover, some spectroscopic techniques under-performed for distinguishing samples by composition. The multi-block HPLS and its VIP-strengthened model yielded a more complete unsupervised geological aggrupation of the samples in a single parsimonious model. We conclude that multi-block HPLS models are effective at combining multi-modal spectrometric data to provide a more comprehensive characterization of compositionally complex samples, and VIP can reduce HPLS model complexity, while increasing its data interpretability. These approaches have been applied here to a geological data set, but are amenable to a broad range of applications across chemical and biomedical disciplines
Resultat från övervakningen av kustfisk
Get PDFI den här rapporten redovisas resultaten från provfisket i Vaxholm. Provfisket är en del av den regionala miljöövervakningen för kustfisk och har utförts årligen i augusti sedan 2016. Provfisket utförs med nordiska kustöversiktsnät och fångstens artsammansättning, samt fiskens storlek och antal, studeras. I samband med provfisket noteras även omgivningsvariabler. Åldersbestämning av abborre och gös utförs efter genomfört provfiske.Provfiskeområdet ligger i Vaxholms kommun i Stockholms län, och kustvattentypen är Stockholms inre skärgård och Hallsfjärden. Med sin mångfald av miljöer och bottentyper erbjuder området lek- och uppväxtområden för många i Östersjön vanligt förekommande kustfiskarter som abborre, karpfiskar och sik. Området är påverkat av den tunga fartygstrafiken till och från Stockholm, är relativt näringsrikt, och både fritidsbåtstrafiken och utnyttjande av strandnära områden är omfattande.Resultaten visar att salthalten är låg och att siktdjupet i området är lågt. Trots en betydande mänsklig påverkan är fisksamhället både tal- och artrikt. Totalfångsten har ökat över tid och både varm- och kallvattenarter har ökat. Noterbart är att det fångas mycket karpfisk och speciellt då mört, samt en hög andel stor abborre. Abborren i Vaxholm växer dock relativt långsamt. Fångsten av gös är mycket liten och endast enstaka individer har påträffats årligen. Svartmunnad smörbult, en invasiv främmande art, har fångats under de senaste tre åren, vilket tyder på att arten troligen är etablerad i Stockholms inre skärgård
Advancements in Forest Monitoring: Applications and Perspectives of Airborne Laser Scanning and Complementarity with Satellite Optical Data
Get PDFThis study reviews research from 2010 to 2023 on the integration of airborne laser scanning (ALS) metrics with satellite and ground-based data for forest monitoring, highlighting the potential of the combined use of ALS and optical remote sensing data in improving the accuracy and the frequency. Following an in-depth screening process, 42 peer-reviewed scientific manuscripts were selected and comprehensively analyzed, identifying how the integration among different sources of information facilitate frequent, large-scale updates, crucial for monitoring forest ecosystems dynamics and changes, aiding in supporting sustainable management and climate smart forestry. The results showed how ALS metrics-especially those related to height and intensity-improved estimates precision of forest volume, biomass, biodiversity, and structural attributes, even in dense vegetation, with an R2 up to 0.97. Furthermore, ALS data were particularly effective for monitoring urban forest variables (R2 0.83-0.92), and for species classification (overall accuracy up to 95%), especially when integrated with multispectral and hyperspectral imagery. However, our review also identified existing challenges in predicting biodiversity variables, highlighting the need for continued methodological improvements. Importantly, while some studies revealed great potential, novel applications aiming at improving ALS-derived information in spatial and temporal coverage through the integration of optical satellite data were still very few, revealing a critical research gap. Finally, the ALS studies' distribution was extremely biased. Further research is needed to fully explore its potential for global forest monitoring, particularly in regions like the tropics, where its impact could be significant for ecosystem management and conservation