Network analysis of sea turtle movements and connectivity: A tool for conservation prioritization

Aim: Understanding the spatial ecology of animal movements is a critical element in conserving long-lived, highly mobile marine species. Analyzing networks developed from movements of six sea turtle species reveals marine connectivity and can help prioritize conservation efforts. Location: Global. Methods: We collated telemetry data from 1235 individuals and reviewed the literature to determine our dataset's representativeness. We used the telemetry data to develop spatial networks at different scales to examine areas, connections, and their geographic arrangement. We used graph theory metrics to compare networks across regions and species and to identify the role of important areas and connections. Results: Relevant literature and citations for data used in this study had very little overlap. Network analysis showed that sampling effort influenced network structure, and the arrangement of areas and connections for most networks was complex. However, important areas and connections identified by graph theory metrics can be different than areas of high data density. For the global network, marine regions in the Mediterranean had high closeness, while links with high betweenness among marine regions in the South Atlantic were critical for maintaining connectivity. Comparisons among species-specific networks showed that functional connectivity was related to movement ecology, resulting in networks composed of different areas and links. Main conclusions: Network analysis identified the structure and functional connectivity of the sea turtles in our sample at multiple scales. These network characteristics could help guide the coordination of management strategies for wide-ranging animals throughout their geographic extent. Most networks had complex structures that can contribute to greater robustness but may be more difficult to manage changes when compared to simpler forms. Area-based conservation measures would benefit sea turtle populations when directed toward areas with high closeness dominating network function. Promoting seascape connectivity of links with high betweenness would decrease network vulnerability.Fil: Kot, Connie Y.. University of Duke; Estados UnidosFil: Åkesson, Susanne. Lund University; SueciaFil: Alfaro Shigueto, Joanna. Universidad Cientifica del Sur; Perú. University of Exeter; Reino Unido. Pro Delphinus; PerúFil: Amorocho Llanos, Diego Fernando. Research Center for Environmental Management and Development; ColombiaFil: Antonopoulou, Marina. Emirates Wildlife Society-world Wide Fund For Nature; Emiratos Arabes UnidosFil: Balazs, George H.. Noaa Fisheries Service; Estados UnidosFil: Baverstock, Warren R.. The Aquarium and Dubai Turtle Rehabilitation Project; Emiratos Arabes UnidosFil: Blumenthal, Janice M.. Cayman Islands Government; Islas CaimánFil: Broderick, Annette C.. University of Exeter; Reino UnidoFil: Bruno, Ignacio. Instituto Nacional de Investigaciones y Desarrollo Pesquero; ArgentinaFil: Canbolat, Ali Fuat. Hacettepe Üniversitesi; Turquía. Ecological Research Society; TurquíaFil: Casale, Paolo. Università degli Studi di Pisa; ItaliaFil: Cejudo, Daniel. Universidad de Las Palmas de Gran Canaria; EspañaFil: Coyne, Michael S.. Seaturtle.org; Estados UnidosFil: Curtice, Corrie. University of Duke; Estados UnidosFil: DeLand, Sarah. University of Duke; Estados UnidosFil: DiMatteo, Andrew. CheloniData; Estados UnidosFil: Dodge, Kara. New England Aquarium; Estados UnidosFil: Dunn, Daniel C.. University of Queensland; Australia. The University of Queensland; Australia. University of Duke; Estados UnidosFil: Esteban, Nicole. Swansea University; Reino UnidoFil: Formia, Angela. Wildlife Conservation Society; Estados UnidosFil: Fuentes, Mariana M. P. B.. Florida State University; Estados UnidosFil: Fujioka, Ei. University of Duke; Estados UnidosFil: Garnier, Julie. The Zoological Society of London; Reino UnidoFil: Godfrey, Matthew H.. North Carolina Wildlife Resources Commission; Estados UnidosFil: Godley, Brendan J.. University of Exeter; Reino UnidoFil: González Carman, Victoria. Instituto National de Investigación y Desarrollo Pesquero; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Harrison, Autumn Lynn. Smithsonian Institution; Estados UnidosFil: Hart, Catherine E.. Grupo Tortuguero de las Californias A.C; México. Investigacion, Capacitacion y Soluciones Ambientales y Sociales A.C; MéxicoFil: Hawkes, Lucy A.. University of Exeter; Reino UnidoFil: Hays, Graeme C.. Deakin University; AustraliaFil: Hill, Nicholas. The Zoological Society of London; Reino UnidoFil: Hochscheid, Sandra. Stazione Zoologica Anton Dohrn; ItaliaFil: Kaska, Yakup. Dekamer—Sea Turtle Rescue Center; Turquía. Pamukkale Üniversitesi; TurquíaFil: Levy, Yaniv. University Of Haifa; Israel. Israel Nature And Parks Authority; IsraelFil: Ley Quiñónez, César P.. Instituto Politécnico Nacional; MéxicoFil: Lockhart, Gwen G.. Virginia Aquarium Marine Science Foundation; Estados Unidos. Naval Facilities Engineering Command; Estados UnidosFil: López-Mendilaharsu, Milagros. Projeto TAMAR; BrasilFil: Luschi, Paolo. Università degli Studi di Pisa; ItaliaFil: Mangel, Jeffrey C.. University of Exeter; Reino Unido. Pro Delphinus; PerúFil: Margaritoulis, Dimitris. Archelon; GreciaFil: Maxwell, Sara M.. University of Washington; Estados UnidosFil: McClellan, Catherine M.. University of Duke; Estados UnidosFil: Metcalfe, Kristian. University of Exeter; Reino UnidoFil: Mingozzi, Antonio. Università Della Calabria; ItaliaFil: Moncada, Felix G.. Centro de Investigaciones Pesqueras; CubaFil: Nichols, Wallace J.. California Academy Of Sciences; Estados Unidos. Center For The Blue Economy And International Environmental Policy Program; Estados UnidosFil: Parker, Denise M.. Noaa Fisheries Service; Estados UnidosFil: Patel, Samir H.. Coonamessett Farm Foundation; Estados Unidos. Drexel University; Estados UnidosFil: Pilcher, Nicolas J.. Marine Research Foundation; MalasiaFil: Poulin, Sarah. University of Duke; Estados UnidosFil: Read, Andrew J.. Duke University Marine Laboratory; Estados UnidosFil: Rees, ALan F.. University of Exeter; Reino Unido. Archelon; GreciaFil: Robinson, David P.. The Aquarium and Dubai Turtle Rehabilitation Project; Emiratos Arabes UnidosFil: Robinson, Nathan J.. Fundación Oceanogràfic; EspañaFil: Sandoval-Lugo, Alejandra G.. Instituto Politécnico Nacional; MéxicoFil: Schofield, Gail. Queen Mary University of London; Reino UnidoFil: Seminoff, Jeffrey A.. Noaa National Marine Fisheries Service Southwest Regional Office; Estados UnidosFil: Seney, Erin E.. University Of Central Florida; Estados UnidosFil: Snape, Robin T. E.. University of Exeter; Reino UnidoFil: Sözbilen, Dogan. Dekamer—sea Turtle Rescue Center; Turquía. Pamukkale University; TurquíaFil: Tomás, Jesús. Institut Cavanilles de Biodiversitat I Biologia Evolutiva; EspañaFil: Varo Cruz, Nuria. Universidad de Las Palmas de Gran Canaria; España. Ads Biodiversidad; España. Instituto Canario de Ciencias Marinas; EspañaFil: Wallace, Bryan P.. University of Duke; Estados Unidos. Ecolibrium, Inc.; Estados UnidosFil: Wildermann, Natalie E.. Texas A&M University; Estados UnidosFil: Witt, Matthew J.. University of Exeter; Reino UnidoFil: Zavala Norzagaray, Alan A.. Instituto politecnico nacional; MéxicoFil: Halpin, Patrick N.. University of Duke; Estados Unido

Another model minority? Immigrant scholars from the former Soviet Union in Israeli academia

ABSTRACTThree decades have passed since the start of the largest immigration wave in Israeli history, comprised of around one million Russian-speaking Jews from the FSU. This study examines the professional and personal experiences of individuals from the “1.5 generation” – those who immigrated in childhood – now employed as senior faculty in Israeli academia. Recent studies have examined the integration of immigrants from this “1.5 generation” into Israeli society, and their sense of identity and belonging. However, no study has focused on the integration of this generation within academia. The study uses a narrative approach, emphasising participants’ stories from their own perspectives, focusing on subjective processes of integration and professional identity formation. We employ the notion of cultural, social, and resilience capitals to shed light on integration hurdles faced by immigrants – from a community largely perceived as a model minority within Israeli society – when accessing elite social spaces. Our findings highlight differences in the cultural, social, and resilience capitals required and valued in their new environment. Our participants shared how they creatively forged new forms of capitals, sometimes by assimilating completely, sometimes by rebelling and emphasising their separate identity, as well as developing super resilience capital based on international connections

Study of Water Freezing in Low-Fat Milky Ice Cream with Oat β-Glucan and Its Influence on Quality Indicators

The work is devoted to the study of the functional and technological properties of oat β-glucan in low-fat milky ice cream (2% fat) in comparison with the stabilization system Cremodan® SI 320. β-glucan (0.5%) has a greater effect on the cryoscopic temperature of ice cream mixes than Cremodan® SI 320 in the same amount (decrease by 0.166 °C vs. 0.078 °C), which inhibits the freezing process of free water in ice cream during technological processing in the temperature range from −5 to −10 °C. Microscopy of ice cream samples after freezing and hardening shows the ability of β-glucan to form a greater number of energy bonds due to specific interaction with milk proteins. Analysis of the microstructure of ice cream samples during 28 d of storage confirms the ability of oat β-glucan to suppress the growth of ice crystals more effectively than Cremodan® SI 320. Oat β-glucan gives ice cream a rich creamy taste, increases overrun and resistance to melting, which brings this type of frozen dessert closer to a full-fat analogue (10% fat)

How are perceptions associated with water consumption in Canadian Inuit? A cross-sectional survey in Rigolet, Labrador

Concerns regarding the safety and aesthetic qualities of one's municipal drinking water supply are important factors influencing drinking water perceptions and consumption patterns (i.e. sources used and daily volume of consumption). In northern Canada, Inuit communities face challenges with drinking water quality, and many Inuit have reported concerns regarding the safety of their drinking water. The objectives of this research were to describe perceptions of municipal tap water, examine use of water sources and changes following the installation of a potable water dispensing unit (PWDU) in 2014, and identify factors associated with water consumption in the Inuit community of Rigolet. This study used data from three cross-sectional census surveys conducted between 2012 and 2014. Principal component analysis (PCA) was used to aggregate data from multiple variables related to perceptions of water, and logistic regressions were used to identify variables associated with water consumption patterns. Three quarters of residents reported using the PWDU after its installation, with concomitant declines reported in consumption of bottled, tap, and brook water. Negative perceptions of tap water were associated with lower odds of consuming tap water (OR PCAcomponent1 = 0.73, 95% CI 0.56–0.94; OR PCAcomponent2 = 0.67, 95% CI 0.49–0.93); women had higher odds of drinking purchased water compared to men (OR = 1.90, 95% CI 1.11–3.26). The median amount of water consumed per day was 1 L. Using brook water (OR = 2.60, 95% CI 1.22–5.56) and living in a household where no one had full-time employment (OR = 2.94, 95% CI 1.35–6.39) were associated with consuming > 2 L of water per day. Results of this study may inform drinking water interventions, risk assessments, and public health messaging in Rigolet and other Indigenous communities

Search for the lepton-flavor violating decay Bs0→ϕμ±τ∓B^0_s\to\phi\mu^\pm\tau^\mp

International audienceA search for the lepton-flavor violating decays $B^0_s\to\phi\mu^\pm\tau^\mp$ is presented, using a sample of proton-proton collisions at center-of-mass energies of 7, 8, and 13 TeV, collected with the LHCb detector and corresponding to a total integrated luminosity of $9\,\text{fb}^{-1}$. The $\tau$ leptons are selected using decays with three charged pions. No significant excess is observed, and an upper limit on the branching fraction is determined to be ${\cal B}( B^0_s\to\phi\mu^\pm\tau^\mp) < 1.0\times 10^{-5}$ at 90% confidence level

Comprehensive analysis of local and nonlocal amplitudes in the B0→K∗0μ+μ−B^0\rightarrow K^{*0}\mu^+\mu^- decay

International audienceA comprehensive study of the local and nonlocal amplitudes contributing to the decay $B^0\rightarrow K^{*0}(\to K^+\pi^-) \mu^+\mu^-$ is performed by analysing the phase-space distribution of the decay products. The analysis is based on \proton\proton collision data corresponding to an integrated luminosity of 8.4fb$^{-1}$ collected by the LHCb experiment. This measurement employs for the first time a model of both one-particle and two-particle nonlocal amplitudes, and utilises the complete dimuon mass spectrum without any veto regions around the narrow charmonium resonances. In this way it is possible to explicitly isolate the local and nonlocal contributions and capture the interference between them. The results show that interference with nonlocal contributions, although larger than predicted, only has a minor impact on the Wilson Coefficients determined from the fit to the data. For the local contributions, the Wilson Coefficient $C_9$, responsible for vector dimuon currents, exhibits a $2.1\sigma$ deviation from the Standard Model expectation. The Wilson Coefficients $C_{10}$, $C_{9}'$ and $C_{10}'$ are all in better agreement than $C_{9}$ with the Standard Model and the global significance is at the level of $1.5\sigma$. The model used also accounts for nonlocal contributions from $B^{0}\to K^{*0}\left[\tau^+\tau^-\to \mu^+\mu^-\right]$ rescattering, resulting in the first direct measurement of the $b s\tau\tau$ vector effective-coupling $C_{9\tau}$

Search for the rare Λc+→pμ+μ−\Lambda_c^+ \to p \mu^+ \mu^- decay

International audienceA search for the nonresonant $\Lambda_c^+ \to p \mu^+ \mu^-$ decay is performed using proton-proton collision data recorded at a centre-of-mass energy of 13 TeV by the LHCb experiment, corresponding to an integrated luminosity of 5.4 fb$^{-1}$. No evidence for the decay is found in the dimuon invariant-mass regions where the expected contributions of resonances is subdominant. The upper limit on the branching fraction of the $\Lambda_c^+ \to p \mu^+ \mu^-$ decay is determined to be $2.9~(3.2) \times 10^{-8}$ at 90% (95%) confidence level. The branching fractions in the dimuon invariant-mass regions dominated by the $\eta$, $\rho$ and $\omega$ resonances are also determined

Transverse polarisation measurement of Λ\Lambda hyperons in ppNe collisions at sNN\sqrt{s_{NN}}=68.4 GeV with the LHCb detector

A measurement of the transverse polarization of the $\Lambda$ and $\bar{\Lambda}$hyperons in $p$Ne fixed-target collisions at $\sqrt{s_{NN}}$=68.4 GeV is presented using data collected by the LHCb detector. The polarization is studied using the decay $\Lambda \rightarrow p \pi^-$ together with its charge conjugated process, the integrated values measured are $$P_{\Lambda} = 0.029 \pm 0.019 \, (\rm{stat}) \pm 0.012 \, (\rm{syst}) \, ,$$ $$P_{\bar{\Lambda}} = 0.003 \pm 0.023 \, (\rm{stat}) \pm 0.014 \,(\rm{syst}) \,$$ Furthermore, the results are shown as a function of the Feynman $x$ variable, transverse momentum, pseudorapidity and rapidity of the hyperons, and are compared with previous measurements.A measurement of the transverse polarization of the $\Lambda$ and $\bar{\Lambda}$ hyperons in $p$Ne fixed-target collisions at $\sqrt{s_{NN}}$ = 68.4 GeV is presented using data collected by the LHCb detector. The polarization is studied using the decay $\Lambda \rightarrow p \pi^-$ together with its charge conjugated process, the integrated values measured are $$P_{\Lambda} = 0.029 \pm 0.019 \, (\rm{stat}) \pm 0.012 \, (\rm{syst}) \, ,$$ $$P_{\bar{\Lambda}} = 0.003 \pm 0.023 \, (\rm{stat}) \pm 0.014 \,(\rm{syst}) \,.$$ Furthermore, the results are shown as a function of the Feynman~$x$~variable, transverse momentum, pseudorapidity and rapidity of the hyperons, and are compared with previous measurements