Environmental drivers of large-scale movements of baleen whales in the mid-North Atlantic Ocean

© The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Perez-Jorge, S., Tobena, M., Prieto, R., Vandeperre, F., Calmettes, B., Lehodey, P., & Silva, M. A. Environmental drivers of large-scale movements of baleen whales in the mid-North Atlantic Ocean. Diversity and Distributions, 00, (2020): 1-16, doi:10.1111/ddi.13038.Aim Understanding the environmental drivers of movement and habitat use of highly migratory marine species is crucial to implement appropriate management and conservation measures. However, this requires quantitative information on their spatial and temporal presence, which is limited in the high seas. Here, we aimed to gain insights of the essential habitats of three baleen whale species around the mid‐North Atlantic (NA) region, linking their large‐scale movements with information on oceanographic and biological processes. Location Mid‐NA Ocean. Methods We present the first study combining data from 31 satellite tracks of baleen whales (15, 10 and 6 from fin, blue and sei whales, respectively) from March to July (2008–2016) with data on remotely sensed oceanography and mid‐ and lower trophic level biomass derived from the spatial ecosystem and population dynamics model (SEAPODYM). A Bayesian switching state‐space model was applied to obtain regular tracks and correct for location errors, and pseudo‐absences were created through simulated positions using a correlated random walk model. Based on the tracks and pseudo‐absences, we applied generalized additive mixed models (GAMMs) to determine the probability of occurrence and predict monthly distributions. Results This study provides the most detailed research on the spatio‐temporal distribution of baleen whales in the mid‐NA, showing how dynamic biophysical processes determine their habitat preference. Movement patterns were mainly influenced by the interaction of temperature and the lower trophic level biomass; however, this relationship differed substantially among species. Best‐fit models suggest that movements of whales migrating towards more productive areas in northern latitudes were constrained by depth and eddy kinetic energy. Main conclusions These novel insights highlight the importance of integrating telemetry data with spatially explicit prey models to understand which factors shape the movement patterns of highly migratory species across large geographical scales. In addition, our outcomes could contribute to inform management of anthropogenic threats to baleen whales in sparsely surveyed region.We are very grateful to Cláudia Oliveira, Irma Cascão, Maria João Cruz, Miriam Romagosa and many volunteers, skilled skippers, crew and spotters that participated in the tagging fieldwork. This work was supported by Fundação para a Ciência e Tecnologia (FCT), Azores 2020 Operational Programme and Fundo Regional da Ciência e Tecnologia (FRCT) through research projects FCT‐Exploratory project (IF/00943/2013/CP1199/CT0001), TRACE (PTDC/MAR/74071/2006) and MAPCET (M2.1.2/F/012/2011) co‐funded by FEDER, COMPETE, QREN, POPH, ESF, ERDF, Portuguese Ministry for Science and Education, and Proconvergencia Açores/EU Program. We also acknowledge funds provided by FCT to MARE, through the strategic project UID/MAR/04292/2013. SPJ was supported by a postdoctoral grant (REF.GREENUP/001‐2016), MT by a DRCT doctoral grant (M3.1.a/F/028/2015), MAS by an FCT‐Investigator contract (IF/00943/2013), FV by an FCT Investigator contract (CEECIND/03469/2017) and RP by an FCT postdoctoral grant (SFRH/BPD/108007/2015). LMTL modelling work has been supported by the CMEMS Service Evolution GREENUP project, funded by Mercator Ocean. We are grateful to Elliott Hazen for offering guidance and advice, and to two anonymous referees whose comments greatly improved this work

Multi-state open robust design applied to opportunistic data reveals dynamics of wide-ranging taxa: The sperm whale case.

© The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Boys, R. M., Oliveira, C., Perez-Jorgeo, S., Prieto, R., Steiner, L., & Silva, M. A. Multi-state open robust design applied to opportunistic data reveals dynamics of wide-ranging taxa: The sperm whale case. Ecosphere, 10(3), (2019):e02610, doi:10.1002/ecs2.2610.Capture–mark–recapture methods have been extensively used to estimate abundance, demography, and life history parameters of populations of several taxa. However, the high mobility of many species means that dedicated surveys are logistically complicated and expensive. Use of opportunistic data may be an alternative, if modeling takes into account the inevitable heterogeneity in capture probability from imperfect detection and incomplete sampling, which can produce significant bias in parameter estimates. Here, we compare covariate‐based open Jolly‐Seber models (POPAN) and multi‐state open robust design (MSORD) models to estimate demographic parameters of the sperm whale population summering in the Azores, from photo‐identification data collected opportunistically by whale‐watching operators and researchers. The structure of the MSORD also allows for extra information to be obtained, estimating temporary emigration and improving precision of estimated parameters. Estimates of survival from both POPAN and MSORD were high, constant, and very similar. The POPAN model, which partially accounted for heterogeneity in capture probabilities, estimated an unbiased super‐population of ~1470 whales, with annual abundance showing a positive trend from 351 individuals (95% CI: 234–526) in 2010 to 718 (95% CI: 477–1082) in 2015. In contrast, estimates of abundance from MSORD models that explicitly incorporated imperfect detection due to temporary emigration were less biased, more precise, and showed no trend over years, from 275 individuals (95% CI: 188–404) in 2014 to 367 (95% CI: 248–542) in 2012. The MSORD estimated short residence time and an even‐flow temporary emigration, meaning that the probability of whales emigrating from and immigrating to the area was equal. Our results illustrate how failure to account for transience and temporary emigration can lead to biased estimates and trends in abundance, compromising our ability to detect true population changes. MSORD models should improve inferences of population dynamics, especially when capture probability is low and highly variable, due to wide‐ranging behavior of individuals or to non‐standardized sampling. Therefore, these models should provide less biased estimates and more accurate assessments of uncertainty that can inform management and conservation measures.We acknowledge IFAW for providing photo‐identification data from the early period of the study (1987–1993), Biosphere Expeditions and clients of Whale Watch Azores for making data collection possible. We thank Sara Magalhães, Tiago Sá, João Medeiros, Yves Cuenot, Pablo Chevallard Navarro, and numerous volunteers that over the years helped with data collection and organization of the photo‐identification catalogue. We are deeply grateful to Gary White, Bill Kendall, Jim Hines, James Nichols, Paul Conn, and Olivier Gimenez for offering guidance and advice on CMR modeling. We thank Jonathan Gordon for his comments on an earlier version of the manuscript. We are thankful to the three anonymous reviewers for providing very helpful comments. This work was supported by Fundação para a Ciência e Tecnologia (FCT), Azores 2020 Operational Programme, and Fundo Regional da Ciência e Tecnologia (FRCT) through research projects FCT‐Exploratory project (IF/00943/2013/CP1199/CT0001), WATCH IT (Acores‐01‐0145‐FEDER‐000057), and MISTIC SEAS II (GA11.0661/2017/750679/SUB/ENV.C2) co‐funded by FEDER, COMPETE, QREN, POPH, ESF, Portuguese Ministry for Science and Education, and EU‐DG/ENV. The Azores 2020 Operational Programme is funded by the community structural funds ERDF and ESF. We also acknowledge funds provided by FCT to MARE, through the strategic project UID/MAR/04292/2013. Rebecca M Boys is supported by an Estagiar L scholarship, Cláudia Oliveira by a research assistant contract from WATCH IT and Mónica A Silva by an FCT‐Investigator contract (IF/00943/2013), and Rui Prieto by an FCT postdoctoral grant (SFRH/BPD/108007/2015). Mónica A Silva conceptualized the project, acquired funding, administered, and supervised the project. Lisa Steiner, Cláudia Oliveira, Rebecca M Boys, and Mónica A Silva involved in data curation. Rebecca M Boys, Mónica A Silva, Sergi Pérez‐Jorge, and Cláudia Oliveira involved in formal analysis, investigation, and methodology. Rebecca M Boys preparation and visualization of the data. Rebecca M Boys, Mónica A Silva, Sergi Pérez‐Jorge, Rui Prieto wrote the original draft of the manuscript. Rebecca M Boys, Mónica A Silva, Rui Prieto, Sergi Pérez‐Jorge, Cláudia Oliveira, and Lisa Steiner wrote, reviewed, and edited the manuscript

Predictive model of sperm whale prey capture attempts from time-depth data

Funding: Research was supported by the Portuguese Science & Technology Foundation (FCT), the Azorean Science & Technology Fund (FRCT), and the EU through research projects WATCH IT-Acores-01-0145-FEDER-000057, FCT-IF/00943/2013/CP1199/CT0001, META-FA_06_2017_017, and SUMMER-H2020 GA 817806, co-funded by FEDER, COMPETE, QREN, POPH, ESF, PO AZORES 2020, Portuguese Ministry for Science and Education, and individual contracts/grants to CO (WATCH IT-Acores-01-0145-FEDER-000057, 3/SRMCT/DRAM/2019 under RAGES-SUB/ENV.C.2-GA 110661, and INTERTAGUA-MAC2/1.1a/385), SPJ (SUMMER-H2020 GA 817806), IC (FCT-IP Project UIDP/05634/2020). PJW is funded by RANNÍS Icelandic Research Fund grant 207081. RP and MAS are co-financed by AZORES2020, through the EU Fund 01-0145-FEDER-000140 “MarAZ Researchers: Consolidate a body of researchers in Marine Sciences in the Azores”. Okeanos is funded by FCT (UIDB/05634/2020) and by the Regional Government of the Azores through the initiative to support the Research Centers of the University of the Azores (M1.1.A/REEQ.CIENTÍFICO UI&D/2021/010).Background High-resolution sound and movement recording tags offer unprecedented insights into the fine-scale foraging behaviour of cetaceans, especially echolocating odontocetes, enabling the estimation of a series of foraging metrics. However, these tags are expensive, making them inaccessible to most researchers. Time-Depth Recorders (TDRs), which have been widely used to study diving and foraging behaviour of marine mammals, offer a more affordable alternative. Unfortunately, data collected by TDRs are bi-dimensional (time and depth only), so quantifying foraging effort from those data is challenging. Methods A predictive model of the foraging effort of sperm whales (Physeter macrocephalus) was developed to identify prey capture attempts (PCAs) from time-depth data. Data from high-resolution acoustic and movement recording tags deployed on 12 sperm whales were downsampled to 1 Hz to match the typical TDR sampling resolution and used to predict the number of buzzes (i.e., rapid series of echolocation clicks indicative of PCAs). Generalized linear mixed models were built for dive segments of different durations (30, 60, 180 and 300 s) using multiple dive metrics as potential predictors of PCAs. Results Average depth, variance of depth and variance of vertical velocity were the best predictors of the number of buzzes. Sensitivity analysis showed that models with segments of 180 s had the best overall predictive performance, with a good area under the curve value (0.78 ± 0.05), high sensitivity (0.93 ± 0.06) and high specificity (0.64 ± 0.14). Models using 180 s segments had a small difference between observed and predicted number of buzzes per dive, with a median of 4 buzzes, representing a difference in predicted buzzes of 30%. Conclusions These results demonstrate that it is possible to obtain a fine-scale, accurate index of sperm whale PCAs from time-depth data alone. This work helps leveraging the potential of time-depth data for studying the foraging ecology of sperm whales and the possibility of applying this approach to a wide range of echolocating cetaceans. The development of accurate foraging indices from low-cost, easily accessible TDR data would contribute to democratize this type of research, promote long-term studies of various species in several locations, and enable analyses of historical datasets to investigate changes in cetacean foraging activity.Publisher PDFPeer reviewe

High-resolution optical imaging of the core of the globular cluster M15 with FastCam

We present high-resolution I-band imaging of the core of the globular cluster M15 obtained at the 2.5 m Nordic Optical Telescope with FastCam, a low readout noise L3CCD based instrument. Short exposure times (30 ms) were used to record 200000 images (512 x 512 pixels each) over a period of 2 hours 43 min. The lucky imaging technique was then applied to generate a final image of the cluster centre with FWHM ~ 0".1 and 13" x 13" FoV. We obtained a catalogue of objects in this region with a limiting magnitude of I=19.5. I-band photometry and astrometry are reported for 1181 stars. This is the deepest I-band observation of the M15 core at this spatial resolution. Simulations show that crowding is limiting the completeness of the catalogue. At shorter wavelengths, a similar number of objects has been reported using HST/WFPC observations of the same field. The cross-match with the available HST catalogues allowed us to produce colour-magnitude diagrams where we identify new Blue Straggler star candidates and previously known stars of this class.Comment: 11 pages, 15 figures. Accepted for publication in Monthly Notices of the Royal Astronomical Societ

Monocyte populations as markers of response to adalimumab plus MTX in rheumatoid arthritis

INTRODUCTION: The treatment of rheumatoid arthritis (RA) patients with anti-tumor necrosis factor alpha (TNFα) biological drugs has dramatically improved the prognosis of these patients. However, a third of the treated patients do not respond to this therapy. Thus, the search for biomarkers of clinical response to these agents is currently highly active. Our aim is to analyze the number and distribution of circulating monocytes, and of their CD14(+high)CD16(-), CD14(+high)CD16(+ )and CD14(+low)CD16(+ )subsets in methotrexate (MTX) non-responder patients with RA, and to determine their value in predicting the clinical response to adalimumab plus MTX treatment. METHODS: This prospective work investigated the number of circulating monocytes, and of their CD14(+high)CD16(-), CD14(+high)CD16(+ )and CD14(+low)CD16(+ )subsets, in 35 MTX non-responder patients with RA before and after three and six months of anti-TNFα treatment using multiparametric flow cytometry. The number of circulating monocytes in an age- and sex-matched healthy population was monitored as a control. RESULTS: Non-responder patients with RA show an increased number of monocytes and of their CD14(+high)CD16(-), CD14(+high)CD16(+ )and CD14(+low)CD16(+ )subsets after three months of adalimumab plus MTX treatment that remained significantly increased at six months. In contrast, significant normalization of the numbers of circulating monocytes was found in responders at three months of adalimumab plus MTX treatment that lasts up to six months. CX3CR1 expression is increased in monocytes in non-responders. At three months of anti-TNFα treatment the number of circulating monocytes and their subsets was associated with at least 80% sensitivity, 84% specificity and an 86% positive predictive value (PPV) in terms of discriminating between eventual early responders and non-responders. CONCLUSIONS: The absolute number of circulating monocytes and of their CD14(+high)CD16(-), CD14(+high)CD16(+ )and CD14(+low)CD16(+ )subsets at three months of adalimumab plus MTX treatment, have a predictive value (with high specificity and sensitivity) in terms of the clinical response after six months of anti-TNFα treatment in patients with RA

AOLI-- Adaptive Optics Lucky Imager: Diffraction Limited Imaging in the Visible on Large Ground-Based Telescopes

The highest resolution images ever taken in the visible were obtained by combining Lucky Imaging and low order adaptive optics. This paper describes a new instrument to be deployed on the WHT 4.2m and GTC 10.4 m telescopes on La Palma, with particular emphasis on the optical design and the expected system performance. A new design of low order wavefront sensor using photon counting CCD detectors and multi-plane curvature wavefront sensor will allow dramatically fainter reference stars to be used, allowing virtually full sky coverage with a natural guide star. This paper also describes a significant improvements in the efficiency of Lucky Imaging, important advances in wavefront reconstruction with curvature sensors and the results of simulations and sensitivity limits. With a 2 x 2 array of 1024 x 1024 photon counting EMCCDs, AOLI is likely to be the first of the new class of high sensitivity, near diffraction limited imaging systems giving higher resolution in the visible from the ground than hitherto been possible from space.Comment: SPIE vol 8446, 201

The AOLI low-order non-linear curvature wavefront sensor: a method for high sensitivity wavefront reconstruction

The Adaptive Optics Lucky Imager (AOLI) is a new instrument under development to demonstrate near diffraction limited imaging in the visible on large ground-based telescopes. We present the adaptive optics system being designed for the instrument comprising a large stroke deformable mirror, fixed component non-linear curvature wavefront sensor and photon-counting EMCCD detectors. We describe the optical design of the wavefront sensor where two photoncounting CCDs provide a total of four reference images. Simulations of the optical characteristics of the system are discussed, with their relevance to low and high order AO systems. The development and optimisation of high-speed wavefront reconstruction algorithms are presented. Finally we discuss the results of simulations to demonstrate the sensitivity of the system.Comment: 10 pages. To be published in Proc SPIE 8447: Adaptive Optics Systems II