Northwest Spain Research Articles

Deep-Sea asteroids (Echinodermata; Asteroidea) from the Galician Bank (North Atlantic Ocean).

The Galician Bank (GB) is a seamount located 180 km away from the Galician coast (Northwest Spain), in the Northeast Atlantic Ocean. The summit occurs at a depth between 650 and 1500 m with the maximum depth reaching 4000 m (the abyssal bottom). The water masses, twists, eddies, and geomorphology favour the retention of nutrients and larvae, thus, being an area rich in nutrients. It is a hotspot of biodiversity and an important place for benthic communities. This study aims to inventory and review the asteroid fauna collected during the LIFE+INDEMARES project in GB, compare the new findings with previous studies Official Spanish Checklist (IEEM: "Inventario Español de Especies Marinas", Manjón-Cabeza et al. 2017, 2020) and update our knowledge of the diversity and distribution of known species. In this study a total of 272 asteroid specimens belonging to 19 species were found at 45 stations in depths between 765-1764 m, as part of the LIFE+INDEMARES-Galician Bank (2010-2011) surveys. The most frequently encountered species were Plinthaster dentatus (Perrier, 1884), Peltaster placenta (Müller & Troschel, 1842) and Henricia caudani (Koehler, 1895). Circeaster americanus (A.H. Clark, 1916) and Hymenaster giboryi (Perrier, 1894) are new observations from this area. For several species, including Henricia caudani, Pedicellaster typicus M. Sars, 1861, Podosphaeraster thalassae Cherbonnier, 1970 and Hymenaster giboryi known bathymetric range has been extended.

Basic micro-pollutants in sludge from municipal wastewater treatment plants in the Northwest Spain: Occurrence and risk assessment of sludge disposal

Sludge is one of the most problematic residues generated during wastewater treatment. Herein, we validate a single-step, sensitive procedure for the determination of a selection of 46 basic micro-pollutants, either used as pharmaceuticals or pesticides, in sludge from municipal sewage treatment plants (STPs), using liquid chromatography tandem mass spectrometry as determination technique. The proposed method permitted to achieve accurate recoveries (values from 70% to 120%, for samples spiked at different concentration levels) using solvent-based calibration standards. This feature, combined with limits of quantification lower than 5 ng g−1 (dry weight), allowed the rapid and sensitive quantification of target compounds in freeze-dried sludge samples. Out of 46 investigated pollutants, 33 species showed detection frequencies above 85% in a group of 48 sludge samples, obtained from 45 STPs located in the Northwest of Spain. The assessment of eco-toxicological risks associated to sludge disposal as fertilizer in agriculture and/or forestry, considering average concentrations found in sludge samples, highlighted eight pollutants (sertraline, venlafaxine, N-desethyl amiodarone, amiodarone, norsertraline, trazodone, amitriptyline and ketoconazole) representing an environmental hazard based on ratios between predicted soil levels and non-effect concentrations estimated using the equilibrium partition method.

Explanatory model of the psychosocial variables related to the social acceptance of a uranium mine project in northwest Spain.

The demographic growth and the development of the welfare system have been accompanied by an important social dilemma between preserving nature or promoting energy development by assuming the benefits and risks of both proposals. This research attempts to address this social dilemma by analyzing the psychosocial factors that influence the acceptance or rejection of a new uranium mining development and exploitation project. The main objective was to test an explanatory theoretical model of uranium mining project acceptance, based on the interrelation of sociodemographic variables (e.g., age, gender, economic and educational situation, and level of knowledge about uranium energy) and cognitive variables (e.g., environmental beliefs, risk, and benefit perceptions), along with the activation of an emotional balance in response to the proposal of constructing a uranium mine. Three hundred seventy-one individuals responded to the questionnaire about the variables included in the model. The results showed that older participants showed lower levels of agreement with the mining proposal people, while women and those with greater knowledge of nuclear energy perceived greater risks and had a more negative emotional balance. The proposed explanatory model based on sociodemographic, cognitive, and affective variables showed good fit indices for explaining the assessment of the uranium mine. Thus, age, level of knowledge, risks and benefits, and emotional balance had a direct effect on the acceptance of the mine. Likewise, emotional balance showed a partial mediation effect between the relationships existing between the perception of benefits and risks and the acceptance of the mining proposal. The results are discussed based on the consideration of analyzing sociodemographic, cognitive, and affective variables to understand potential conflicts in communities affected by energy projects.

Evaluation of the Fulfilment of the Therapeutic Objectives in Type 2 Diabetes People Attended in Primary Care Centres in Northwest Spain

Evaluation of the Fulfilment of the Therapeutic Objectives in Type 2 Diabetes People Attended in Primary Care Centres in Northwest Spain

Sustainability, investment strategy, and governance: evaluation of wind energy sector in North-West Spain

Climate change is one of the greatest challenges humanity faces globally. For this reason, governmental efforts to reduce emissions of polluting gases have multiplied in the last decade. Against this panorama, petroleum companies have adopted a strategic policy focused on energy diversification, intending to contribute to sustainable development. In the case of Spain, wind energy has been one of the renewable energies that have attracted the most investment from petroleum companies. In particular, this trend is especially acute in Galicia (a region located in the northwest of Spain), since its biophysical conditions and, above all, its institutional framework for the promotion of photovoltaic energy has aroused the interest of petroleum companies. The objective of this article is to perform a feasibility analysis of an average wind project in Galicia. through the calculation of the initial investment, the necessary financing, and the preparation of balance sheets and profit and loss accounts. For this purpose, the methodology used is based on the preparation of a feasibility plan, through which the necessary investment is analyzed and the flows of receipts and payments generated by the company are considered. In this way, this analysis is intended to be useful for companies that are considering the appropriateness/inappropriateness to carry out this type of investment. The results show a high internal rate of return, which indicates the high profitability of the project.

Ferranicluibacter rubi gen. nov., sp. nov., a new member of family Rhizobiaceae isolated from stems of elmleaf blackberry (Rubus ulmifolius Schott) in Northwest Spain.

Strain CRRU44T was isolated from the stems of Rubus ulmifolius plants growing in Salamanca (Spain). The phylogenetic analysis of the 16S rRNA gene sequence places this strain within the family Rhizobiaceae showing that it is equidistant to the type species of several genera from this family with similarity values ranging from 91.0 to 96.3 %. Strain CRRU44T formed a divergent lineage which clustered with Endobacterium cereale RZME27T, Neorhizobium galegae HAMBI540T and Pseudorhizobium pelagicum R1-200B4T. The phylogenomic analysis showed that strain CRRU44T was equal to or more distant from the remaining genera of the family Rhizobiaceae than other genera among them. The calculated average nucleotide identity based on blast and average amino acid identity values with respect to the type species of all genera from the family Rhizobiaceae were lower than 78.5 and 76.5 %, respectively, which are the currently cut-off values proposed to differentiate genera within this family. All these results together with those from phenotypic and chemotaxonomic analyses support that strain CRRU44T represents a novel species of a novel genus within the family Rhizobiaceae, for which the name Ferranicluibacter rubi gen. nov., sp. nov. is proposed (type strain CRRU44T=CECT 30117T=LMG 31822T).

Predicting Daily Aerobiological Risk Level of Potato Late Blight Using C5.0 and Random Forest Algorithms under Field Conditions.

Late blight, caused by Phytophthora infestans, is a major disease of the potato crop with a strong negative impact on tuber yield and tuber quality. The control of late blight in conventional potato production systems is often through weekly application of prophylactic fungicides, moving away from a sustainable production system. In support of integrated pest management practices, machine learning algorithms were proposed as tools to forecast aerobiological risk level (ARL) of Phytophthora infestans (>10 sporangia/m3) as inoculum to new infections. For this, meteorological and aerobiological data were monitored during five potato crop seasons in Galicia (northwest Spain). Mild temperatures (T) and high relative humidity (RH) were predominant during the foliar development (FD), coinciding with higher presence of sporangia in this phenological stage. The infection pressure (IP), wind, escape or leaf wetness (LW) of the same day also were significantly correlated with sporangia according to Spearman's correlation test. ML algorithms such as random forest (RF) and C5.0 decision tree (C5.0) were successfully used to predict daily sporangia levels, with an accuracy of the models of 87% and 85%, respectively. Currently, existing late blight forecasting systems assume a constant presence of critical inoculum. Therefore, ML algorithms offer the possibility of predicting critical levels of Phytophthora infestans concentration. The inclusion of this type of information in forecasting systems would increase the exactitude in the estimation of the sporangia of this potato pathogen.

Repurposing selective serotonin reuptake inhibitors for severity of COVID-19: A population-based study

The World Health Organization has proposed that a search be made for alternatives to vaccines for the prevention and treatment of COVID-19, with one such alternative being selective serotonin reuptake inhibitors (SSRIs). This study thus sought to assess: the impact of previous treatment with SSRI antidepressants on the severity of COVID-19 (risk of hospitalisation, admission to an intensive care unit [ICU], and mortality), its influence on susceptibility to SARS-CoV-2 and progression to severe COVID-19. We conducted a population-based multiple case-control study in a region in the north-west of Spain. Data were sourced from electronic health records. Adjusted odds ratios (aORs) and 95%CIs were calculated using multilevel logistic regression. We collected data from a total of 86,602 subjects: 3060 cases PCR+, 26,757 non-hospitalised cases PCR+ and 56,785 controls (without PCR+). Citalopram displayed a statistically significant decrease in the risk of hospitalisation (aOR=0.70; 95% CI 0.49–0.99, p = 0.049) and progression to severe COVID-19 (aOR=0.64; 95% CI 0.43–0.96, p = 0.032). Paroxetine was associated with a statistically significant decrease in risk of mortality (aOR=0.34; 95% CI 0.12 – 0.94, p = 0.039). No class effect was observed for SSRIs overall, nor was any other effect found for the remaining SSRIs. The results of this large-scale, real-world data study indicate that, citalopram, could be a candidate drug for being repurposed as preventive treatment aimed at reducing COVID-19 patients’ risk of progressing to severe stages of the disease.

Correction of phenology-induced effects in forest canopy height models based on airborne laser scanning data. Insights from the deciduous mountain forests in Picos de Europa National Park in Spain

The comparison of ALS time-series is an important element of modern landscape conservation planning, especially to monitor forest ecosystems. Modellers must evaluate phenology when comparing ALS-based maps of ground elevation or canopy height between years. We showcase the scenario using a National Park in the North-West of Spain where bi-temporal ALS has been used to map deciduous mountain forests. We compare the 2010 and 2021 surveys using the same algorithms to interpret ALS data and to generate actionable products for managers, mainly digital terrain models and canopy height models. We implemented a hybrid approach to correct the discrepancies between the surveys, showing the problems arising from differences in phenology or the selection of the scaling. We quantified around 5% of the area suffered from >1 m difference in DTM and higher impact on CHM values. With the hybrid method, modellers can highly reduce the uncertainty when comparing two ALS surveys and derivable products. We provided a solid graphical and analytical diagnosis of these emerging problems in the context of multi-temporal ALS surveys testing the hybrid approach at two resolutions: 1 and 2 m, fine-grained scales. The assessment of phenology-induced effects is important under the context of nationwide ALS survey programmes currently in operation and on high-demand. Finally, we discuss and frame the hybrid-approach as a well-suited vector of canopy gap detection methods to support conservation planning and enforce species-specific habitat improvements.

Multivariate Statistical Approach for the Discrimination of Honey Samples from Galicia (NW Spain) Using Physicochemical and Pollen Parameters.

Raw honey is a food with a close relation to the territory in which it is produced because of factors such as soil conditions, weather patterns, and plant communities living in the area together. Furthermore, beekeeping management affects the properties of honey. Protected Geographical Indication Miel de Galicia protects the honey produced in Galicia (Northwest Spain). Various types of honeys (362 samples) from this geographical area were analyzed using chemometric techniques. Principal component analysis was favorable to analyzing the physicochemical and pollen variables with the greatest weight in the differentiation of honey. The linear discriminant analysis correctly classified 89.8% of the samples according to the botanical origin using main pollen spectra and physicochemical attributes (moisture, pH, electrical conductivity, diastase content, phenols, flavonoids, and color). Regarding unifloral honey, blackberry, eucalyptus, and heather honeys were correctly grouped, while five chestnut honeys and fourteen samples of honeydew honeys were misclassified. The chestnut and honeydew honeys have similar physicochemical properties and frequently similar pollen spectra profiles complicating the differentiation. Experimental evidence suggests the potential of multivariate statistics in the characterization of honey of the same geographical origin. Therefore, the classification results were good, with electrical conductivity, total phenol content, total flavonoid content and dominant pollens Eucalyptus, Erica, Rubus and Castanea sativa as the variables of higher importance in the differentiation of botanical origin of honeys.

Automatic forest change detection through a bi-annual time series of satellite imagery: Toward production of an integrated land cover map

Land cover mapping is fundamental for national and international agencies to monitor forest resources. However, monitoring forest disturbances by direct comparison of these maps poses several difficulties and challenges. As a result, different methodologies have been explored to detect forest disturbances. However, most of them cannot be fully integrated with land cover map production since they require additional input data, while others are not suitable for monitoring small land parcels. This study presents a methodology that fulfils the need to integrate land cover mapping with land cover change detection. Specifically, this methodology was designed to complement the Sentinel-2-based land cover mapping used in Galicia, northwest Spain, a region characterized by small land parceling. First, two previously obtained land cover maps from 2019 and 2020 were compared to identify all the pixels with potential land cover changes using QGIS. The behavior of spectral indexes in a time series were then analyzed to identify which of the previously identified pixels correspond to forest disturbances. This step was implemented in the software R. Using the Normalized Difference Vegetation Index (NDVI) to detect different land cover changes it was obtained an overall accuracy of 82%, considering the existence of varying phenologies, diverse topographic conditions, and areas with a high level of stand fragmentation. This study could help agencies that have already developed their own land cover maps to easily advance the integration of their maps with land cover change detection, since this technique can be applied with any land cover mapping methodology based on multitemporal analysis of satellite images, without the need for additional input data.

Effects of optical and radar satellite observations within Google Earth Engine on soil organic carbon prediction models in Spain

The modeling and mapping of soil organic carbon (SOC) has advanced through the rapid growth of Earth observation data (e.g., Sentinel) collection and the advent of appropriate tools such as the Google Earth Engine (GEE). However, the effects of differing optical and radar sensors on SOC prediction models remain uncertain. This research aims to investigate the effects of different optical and radar sensors (Sentinel-1/2/3 and ALOS-2) on SOC prediction models based on long-term satellite observations on the GEE platform. We also evaluate the relative impact of four synthetic aperture radar (SAR) acquisition configurations (polarization mode, band frequency, orbital direction and time window) on SOC mapping with multiband SAR data from Spain. Twelve experiments involving different satellite data configurations, combined with 4027 soil samples, were used for building SOC random forest regression models. The results show that the synthesis mode and choice of satellite images, as well as the SAR acquisition configurations, influenced the model accuracy to varying degrees. Models based on SAR data involving cross-polarization, multiple time periods and “ASCENDING” orbits outperformed those involving copolarization, a single time period and “DESCENDING” orbits. Moreover, combining information from different orbital directions and polarization modes improved the soil prediction models. Among the SOC models based on long-term satellite observations, the Sentinel-3-based models (R2 = 0.40) performed the best, while the ALOS-2-based model performed the worst. In addition, the predictive performance of MSI/Sentinel-2 (R2 = 0.35) was comparable with that of SAR/Sentinel-1 (R2 = 0.35); however, the combination (R2 = 0.39) of the two improved the model performance. All the predicted maps involving Sentinel satellites had similar spatial patterns that were higher in northwest Spain and lower in the south. Overall, this study provides insights into the effects of different optical and radar sensors and radar system parameters on soil prediction models and improves our understanding of the potential of Sentinels in developing soil carbon mapping.

A new alternative for matrix balancing under conflicting information

Balancing input–output tables using iterative proportional fitting techniques can be prevented due to conflicting information. What is to be done in such cases? Literature suggests a wide variety of alternative methods. Within iterative proportional fitting techniques, modifying the constraint set to circumvent conflicting information problems has been suggested as a promising avenue. Following this approach, we identify some opportunities for improvement not yet been addressed. As a result of this research, we present an iterative proportional fitting variant. Our algorithm uses information contained in the matrix to be balanced for dynamically modifying our constraint set. We ensure economically meaningful solutions, avoiding unsought sign flips. We also respect all macroeconomic aggregates. To illustrate our findings, we provide an empirical example based on the supply-use tables for the region of Galicia (Northwest Spain). Results suggest that our methodological proposal can yield estimates almost as accurate as other alternatives while avoiding undesired outcomes.

New Evidence for Women’s Labor Participation and Occupational Structure in Northwest Spain, 1877–1930

Abstract The traditional historical analysis of the occupational structure in Spain is flawed, based on incomplete and inaccurate census data; the consequence is an underestimation of women’s work. Census data can be corrected with interdisciplinary methodologies that make use of literature and art, as well as ethnographic, legal, and sociological studies. Applied to Galicia (an agrarian and fishing region in northwest Spain), these methods reveal a more accurate, and significantly higher, estimation of women’s participation in the primary industries (agriculture, retail trade, fishing, and seafood processing) between 1877 and 1930.

Abstract P4-07-39: NEOADYUVANT TREATMENT IN THE COVID ERA

Abstract Since Coronavirus Disease 2019 (COVID-19) was declared pandemic in March 2020, there have been 545.226.550 cases up to 4 July 2022 (1). Several studies concluded that patients (pts) with cancer are at increased risk of COVID-19 infection, morbidity and mortality. Those undergoing neoadyuvant treatment are at particularly risk of disease progression if chemotherapy or surgery are delayed. Also, is known that a higher NLR (neutrophil to limphocyte ratio) is related to worse outcomes (3). Our hospital is located at the Northwest of Spain and in the last months we noticed a never seen number of infections in cancer population. The aim of this study is to evaluate the severity of COVID-19 and its impact on chemotherapy and surgery delay in pts undergoing neoadjuvant chemotherapy breast cancer. METHODS: We conducted a ambispective, unicenter, observational study of breast cancer pts, treated with neoadjuvant chemotherapy, between March 2020 and May 2022 at University Hospital A Coruña (Spain). We analyzed type of infection, need of hospitalization, chemotherapy and surgical delay, and its association with tumor type; BRCA germline mutation; clinical stage; treatment; vaccination status; and neutrophils, lymphocytes, and NLR before COVID-19 disease. RESULTS: During the study period, from 1 March 2020 to 31 May 2022, 183 pts underwent neoadjuvant chemotherapy. A total of 23 (12.5%) pts experienced COVID-19 infection, of which 21 were diagnosed between January and May 2022. The median age was 47,91 years [range 33 – 69 years]. Luminal B HER 2 negative comprised the most common molecular subtype (40.9%), followed by Triple Negative (36.4%), Luminal B HER 2 positive (13.6%), and HER 2 enriched (9.1%). Germline mutations in BRCA account for 13.6% pts. At diagnosis, 4.5%, 72.7%, and 22.7% had stages I, II, and III respectively. Chemotherapy treatments included: paclitaxel followed by Adryamicine-Cyclophosphamide (AC) (45.4%); carboplatin – paclitaxel – trastuzumab - pertuzumab (18,2%); carboplatin – paclitaxel followed by AC (18,2%); KEYNOTE-756: pembrolizumab/placebo - paclitaxel followed by AC (13.7%); and paclitaxel – trastuzumab – pertuzumab followed by myocet – cyclophosphamide – trastuzumab - pertuzumab (4.5%). The association of G-CSF ocurred in 9 pts (40.9%). 22 pts were fully vaccinated, 8 pts (36.4%) with two doses and 13 pts (59.1%) with three doses. 77.3% pts experienced mild respiratory symptoms with 9.1% hospitalizations. The median duration of delays was 15 days for chemotherapy and 29,58 days for surgery. NLR percentil 25 was associated with COVID-19 type of infection. For those pts with a lower rate, infection was asymptomatic and for those with a higher rate symptoms were moderate (Χ2= 5,119, p = 0,024). CONCLUSIONS: COVID-19 disease become a high prevalent infection in pts undergoing neoadjuvant breast cancer chemotherapy. Most pts are fully vaccinated and experienced an indolent infection. NLR is an easily measurable and cost-effective parameter that could be useful as a prognostic marker of severity in COVID-19. We will continue to follow-up these pts to see the impact of chemotherapy or surgery delay in pathological complete response and disease-free survival until the congress in December 2022. BIBLIOGRAPHY: 1. WHO Coronavirus (COVID-19) Dashboard [Internet]. world health organization. 2022 [3rd July 2022]. Disponible en: https://covid19.who.int. 2. YekedÜz E, Utkan G, ÜrÜn Y. A systematic review and meta-analysis: the effect of active cancer treatment on severity of COVID-19 [Internet]. European Journal of Cancer. 2020. [24th June 2022]. Disponible en: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7538140/pdf/main.pdf 3. Jimeno S, Ventura PS, Castellano JM, García-Adasme SI, Miranda M, Touza P, et al. Prognostic implications of neutrophil-lymphocyte ratio in COVID-19 [Internet]. Eur J Clin Invest. 2021. [22th June 2022]. Disponible en: https://onlinelibrary.wiley.com/doi/10.1111/eci.13404. Table 1: Clinical characteristics of patients Table 2: Blood cell count in percentils Citation Format: Beatriz Alonso de Castro, Igor Gomez-Randulfe Rodriguez, Sofia Silva Diaz, Cristina Reboredo, Silvia Antolin Novoa, Eva Perez Lopez, Patricia Cordeiro, Rocio Lesta, Iria Parajo Vazquez, Lourdes Calvo. NEOADYUVANT TREATMENT IN THE COVID ERA [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P4-07-39.

DNA Barcoding of the Genus Magnisudis (Aulopiformes: Paralepididae) with a Coastal Record and Biological Features of Magnisudis atlantica

One specimen of the duckbill barracudina Magnisudis atlantica of 402 mm TL was caught in a shallow coastal area in Galician waters, northwest of Spain. Morphometric and meristic parameters along with DNA barcoding, based on cytochrome c oxidase subunit I, were used to confirm the specimen identity. Neighbor-joining analysis of nominal sequences of the genus Magnisudis obtained from the Barcode of Life Data System indicates the presence of six representative groupings of potential species, in contrast to the three that are currently recognized as valid. The stomach contents showed remains of digested crustaceans, tentatively identified as Euphausiids. Histological examination of the gonads revealed the specimen to be an immature female with oocytes at the primary growth stage, indicative of a lack of hermaphroditism. The results add new biological and taxonomic data that contribute to improved understanding of these poorly characterized, mainly deep-water species, demonstrating, once again, the effectiveness of DNA barcoding for identifying deep-sea fishes and characterizing their genetic differences.

Genetic monitoring on the world’s first MSC eco-labeled common octopus (O. vulgaris) fishery in western Asturias, Spain

Octopus vulgaris (Cuvier, 1797) is a cephalopod species with great economic value. In western Asturias (northwest of Spain), O. vulgaris artisanal fisheries are relatively well monitored and conditionally eco-labeled by the Marine Stewardship Council (MSC). Despite this, the Asturian octopus stocks have not been genetically assessed so far. In order to improve the current fishery plan and contrast the octopus eco-label validity in Asturias, 539 individuals from five regions of the O. vulgaris geographic distribution, including temporal samplings in Asturias, were collected and genotyped at thirteen microsatellite loci. All the samples under analysis were in agreement with Hardy–Weinberg expectations. Spatial levels of genetic differentiation were estimated using F-statistics, multidimensional scaling, and Bayesian analyses. Results suggested that the O. vulgaris consists of at least four genetically different stocks coming from two ancestral lineages. In addition, temporal analyses showed stability in terms of genetic variation and high NE (> 50) for several generations in different localities within Asturias, pointing out to indeed sustainable fishery exploitation levels. Even though, the current Asturias fishery plan shows no significant genetic damages to the stocks, the regional-specific management plans need systematic genetic monitoring schemes as part of an efficient and preventive regional fishery regulation strategy.

Can Satellite Remote Sensing Assist in the Characterization of Yeasts Related to Biogeographical Origin?

Biogeography is a key concept associated with microbial terroir, which is responsible for the differentiation and uniqueness of wines. One of the factors influencing this microbial terroir is the vegetation, which in turn is influenced by climate, soil, and cultural practices. Remote sensing instruments can provide useful information about vegetation. This study analyses the relationship between NDVI, calculated using Sentinel-2 and Landsat-8 satellite images of different veraison dates, and microbial data obtained in 2015 from 14 commercial (organic and conventional) vineyards belonging to four Designations of Origin (DOs) from Galicia (northwest Spain). Microbial populations in grapes and musts were identified using PCR techniques and confirmed by sequencing. Statistical analyses were made using PCA, CCA, TB-PLS, and correlation analyses. This study confirms that the NDVI is positively correlated with the diversity of yeasts, both in grapes' surface and must samples. Moreover, the results of this study show: (i) Sentinel-2 images, as well as Landsat-8 images, can establish differences in NDVI related to yeast terroir in grapes and musts, as it is the most relevant DO factor, (ii) Sentinel-2 NDVI and yeast biogeography are moderately to strongly correlated, (iii) Sentinel-2 achieved a better delimitation of the DOs than Landsat-8 and can establish more accurate differences in NDVI-yeast terroir correlations, and (iv) a higher NDVI was associated with the yeast biogeographical patterns of the DOs with higher species richness (S) consisting of weakly fermenting yeasts (Hanseniaspora uvarum, Pichia spp., Starmerella bacillaris, and Zygosaccharomyces spp). However, NDVI values did not correlate well with biogeographic patterns of yeasts previously studied at frequency level (proportion or percentage of each species) in each particular DO. This study suggests that satellite imagery has the potential to be a valuable tool for wine quality management and a decision-making instrument for DO regulators and winegrowers.

Genetic Diversity of Five Galician (Northwestern Spain) Local Primitive Bovine Breeds Using Pedigree Records

Characterization, inventory and monitoring trends of animal genetic resources of local breeds are crucial factors for the development of conservation strategies. Using genealogical information, the genetic diversity of five Spanish local bovine breeds located in the northwest of Spain in the region of Galicia, and called in the past Morenas Gallegas (Cachena, Caldelá, Frieiresa, Limiá and Vianesa), has been analysed. The results achieved a good quality of pedigree records in terms of integrity and deepness. In spite of the low census of the five breeds, (no more or even less than one thousand animals), the strategies developed for genetic diversity conservation since the end of the last century revealed positive results. An increase of generation intervals, the use of reproductive technologies and a higher animal exchange between herds are some strategies suggested to preserve the genetic diversity of the five Galician bovine breeds analysed

First Confirmed Record of the Smalltooth Sand Tiger, Odontapis Ferox, in Galicia (NW Spain)

The smalltooth sand tiger shark Odontaspis ferox (Risso, 1810) appears to have an extensive and fragmented distribution in tropical and warm-temperate worldwide oceans. One female of O. ferox was caught and released by a small-scale fishery vessel in Ría de Arousa (Northwest of Spain), subsequently stranded still alive on the coast (42°33’18.4"N 8°49’18.3"O) after a few hours. The individual (336 cm total length, weight ~ 300 kg) was identified based on a collection of features including the characteristic dentition, body morphology and by molecular assignment. This is the first confirmed record of O. ferox in Galician waters. This finding complements the knowledge of the geographic distribution and occurrence of this rare and sparse species in the Northeastern Atlantic.