14 research outputs found

    Seasonal Movements, Aggregations and Diving Behavior of Atlantic Bluefin Tuna (Thunnus thynnus) Revealed with Archival Tags

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    Electronic tags were used to examine the seasonal movements, aggregations and diving behaviors of Atlantic bluefin tuna (Thunnus thynnus) to better understand their migration ecology and oceanic habitat utilization. Implantable archival tags (n = 561) were deployed in bluefin tuna from 1996 to 2005 and 106 tags were recovered. Movement paths of the fish were reconstructed using light level and sea-surface-temperature-based geolocation estimates. To quantify habitat utilization we employed a weighted kernel estimation technique that removed the biases of deployment location and track length. Throughout the North Atlantic, high residence times (167±33 days) were identified in four spatially confined regions on a seasonal scale. Within each region, bluefin tuna experienced distinct temperature regimes and displayed different diving behaviors. The mean diving depths within the high-use areas were significantly shallower and the dive frequency and the variance in internal temperature significantly higher than during transit movements between the high-use areas. Residence time in the more northern latitude high-use areas was significantly correlated with levels of primary productivity. The regions of aggregation are associated with areas of abundant prey and potentially represent critical foraging habitats that have seasonally abundant prey. Throughout the North Atlantic mean diving depth was significantly correlated with the depth of the thermocline, and dive behavior changed in relation to the stratification of the water column. In this study, with numerous multi-year tracks, there appear to be repeatable patterns of clear aggregation areas that potentially are changing with environmental conditions. The high concentrations of bluefin tuna in predictable locations indicate that Atlantic bluefin tuna are vulnerable to concentrated fishing efforts in the regions of foraging aggregations

    Small-Scale Fisheries Bycatch Jeopardizes Endangered Pacific Loggerhead Turtles

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    Background. Although bycatch of industrial-scale fisheries can cause declines in migratory megafauna including seabirds, marine mammals, and sea turtles, the impacts of small-scale fisheries have been largely overlooked. Small-scale fisheries occur in coastal waters worldwide, employing over 99 % of the world’s 51 million fishers. New telemetry data reveal that migratory megafauna frequent coastal habitats well within the range of small-scale fisheries, potentially producing high bycatch. These fisheries occur primarily in developing nations, and their documentation and management are limited or non-existent, precluding evaluation of their impacts on non-target megafauna. Principal Findings/Methodology. 30 North Pacific loggerhead turtles that we satellite-tracked from 1996–2005 ranged oceanwide, but juveniles spent 70 % of their time at a high use area coincident with small-scale fisheries in Baja California Sur, Mexico (BCS). We assessed loggerhead bycatch mortality in this area by partnering with local fishers to 1) observe two small-scale fleets that operated closest to the high use area and 2) through shoreline surveys for discarded carcasses. Minimum annual bycatch mortality in just these two fleets at the high use area exceeded 1000 loggerheads year 21, rivaling that of oceanwide industrial-scale fisheries, and threatening the persistence of this critically endangered population. As a result of fisher participation in this study and a bycatch awareness campaign, a consortium of local fishers and other citizens are working to eliminate their bycatch and to establish a national loggerhea

    Variations in the financial impact of the COVID-19 pandemic across 5 continents: A cross-sectional, individual level analysis.

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    BACKGROUND: COVID-19 has caused profound socio-economic changes worldwide. However, internationally comparative data regarding the financial impact on individuals is sparse. Therefore, we conducted a survey of the financial impact of the pandemic on individuals, using an international cohort that has been well-characterized prior to the pandemic. METHODS: Between August 2020 and September 2021, we surveyed 24,506 community-dwelling participants from the Prospective Urban-Rural Epidemiology (PURE) study across high (HIC), upper middle (UMIC)-and lower middle (LMIC)-income countries. We collected information regarding the impact of the pandemic on their self-reported personal finances and sources of income. FINDINGS: Overall, 32.4% of participants had suffered an adverse financial impact, defined as job loss, inability to meet financial obligations or essential needs, or using savings to meet financial obligations. 8.4% of participants had lost a job (temporarily or permanently); 14.6% of participants were unable to meet financial obligations or essential needs at the time of the survey and 16.3% were using their savings to meet financial obligations. Participants with a post-secondary education were least likely to be adversely impacted (19.6%), compared with 33.4% of those with secondary education and 33.5% of those with pre-secondary education. Similarly, those in the highest wealth tertile were least likely to be financially impacted (26.7%), compared with 32.5% in the middle tertile and 30.4% in the bottom tertile participants. Compared with HICs, financial impact was greater in UMIC [odds ratio of 2.09 (1.88-2.33)] and greatest in LMIC [odds ratio of 16.88 (14.69-19.39)]. HIC participants with the lowest educational attainment suffered less financial impact (15.1% of participants affected) than those with the highest education in UMIC (22.0% of participants affected). Similarly, participants with the lowest education in UMIC experienced less financial impact (28.3%) than those with the highest education in LMIC (45.9%). A similar gradient was seen across country income categories when compared by pre-pandemic wealth status. INTERPRETATION: The financial impact of the pandemic differs more between HIC, UMIC, and LMIC than between socio-economic categories within a country income level. The most disadvantaged socio-economic subgroups in HIC had a lower financial impact from the pandemic than the most advantaged subgroup in UMIC, with a similar disparity seen between UMIC and LMIC. Continued high levels of infection will exacerbate financial inequity between countries and hinder progress towards the sustainable development goals, emphasising the importance of effective measures to control COVID-19 and, especially, ensuring high vaccine coverage in all countries. FUNDING: Funding for this study was provided by the Canadian Institutes of Health Research and the International Development Research Centre

    Enabling the use of earth observation data for integrated water resource management in Africa with the Water Observation and Information System

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    The Water Observation and Information System (WOIS) is an open source software tool for monitoring, assessing and inventorying water resources in a cost-effective manner using Earth Observation (EO) data. The WOIS has been developed by, among others, the authors of this paper under the TIGER-NET project, which is a major component of the TIGER initiative of the European Space Agency (ESA) and whose main goal is to support the African Earth Observation Capacity for Water Resource Monitoring. TIGER-NET aims to support the satellite-based assessment and monitoring of water resources from watershed to cross-border basin levels through the provision of a free and powerful software package, with associated capacity building, to African authorities. More than 28 EO data processing solutions for water resource management tasks have been developed, in correspondence with the requirements of the participating key African water authorities, and demonstrated with dedicated case studies utilizing the software in operational scenarios. They cover a wide range of themes and information products, including basin-wide characterization of land and water resources, lake water quality monitoring, hydrological modeling and flood forecasting and mapping. For each monitoring task, step-by-step workflows were developed, which can either be adjusted by the user or largely automatized to feed into existing data streams and reporting schemes. The WOIS enables African water authorities to fully exploit the increasing EO capacity offered by current and upcoming generations of satellites, including the Sentinel missions.ESA’s TIGE

    FORSAT: a 3D forest monitoring system for cover mapping and volumetric 3D change detection

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    A 3D forest monitoring system, called FORSAT (a satellite very high resolution image processing platform for forest assessment), was developed for the extraction of 3D geometric forest information from very high resolution (VHR) satellite imagery and the automatic 3D change detection. FORSAT is composed of two complementary tasks: (1) the geometric and radiometric processing of satellite optical imagery and digital surface model (DSM) reconstruction by using a precise and robust image matching approach specially designed for VHR satellite imagery, (2) 3D surface comparison for change detection. It allows the users to import DSMs, align them using an advanced 3D surface matching approach and calculate the 3D differences and volume changes (together with precision values) between epochs. FORSAT is a single source and flexible forest information solution, allowing expert and non-expert remote sensing users to monitor forests in three and four (time) dimensions. The geometric resolution and thematic content of VHR optical imagery are sufficient for many forest information needs such as deforestation, clear-cut and fire severity mapping. The capacity and benefits of FORSAT, as a forest information system contributing to the sustainable forest management, have been tested and validated in case studies located in Austria, Switzerland and Spain

    FORSAT: a 3D forest monitoring system for cover mapping and volumetric 3D change detection *

    No full text
    A 3D forest monitoring system, called FORSAT (a satellite very high resolution image processing platform for forest assessment), was developed for the extraction of 3D geometric forest information from very high resolution (VHR) satellite imagery and the automatic 3D change detection. FORSAT is composed of two complementary tasks: (1) the geometric and radiometric processing of satellite optical imagery and digital surface model (DSM) reconstruction by using a precise and robust image matching approach specially designed for VHR satellite imagery, (2) 3D surface comparison for change detection. It allows the users to import DSMs, align them using an advanced 3D surface matching approach and calculate the 3D differences and volume changes (together with precision values) between epochs. FORSAT is a single source and flexible forest information solution, allowing expert and non-expert remote sensing users to monitor forests in three and four (time) dimensions. The geometric resolution and thematic content of VHR optical imagery are sufficient for many forest information needs such as deforestation, clear-cut and fire severity mapping. The capacity and benefits of FORSAT, as a forest information system contributing to the sustainable forest management, have been tested and validated in case studies located in Austria, Switzerland and Spain.Publisher's Versio

    3-dimensional pre-and post-fire comparison of forest areas

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    \u3cp\u3eForest agencies give special attention to forest fires where post-disaster loss can rarely be gauged in a quick and economic way unless an appropriate technology is adopted. Determination of the planimetric and volumetric changes between pre- and post-fire is in high demand. The FORSAT system (a satellite processing platform for high resolution forest assessment) was developed to meet the relevant demands. It has the capability of extracting of 3D geometric information from the very-high resolution (VHR) imagery from satellite optical sensors and automatic 3D change detection. FORSAT includes two main units. The first one is dedicated to the geometric and radiometric processing of satellite optical imagery and 2D/3D information extraction. This includes: image radiometric pre-processing, image and ground point measurement, improvement of geometric sensor orientation, quasi-epipolar image generation for stereo measurements, digital surface model (DSM) extraction by using a precise and robust image matching approach specially designed for VHR satellite imagery, generation of orthoimages, and 3D measurements in single images using mono-plotting and in stereo images. FORSAT supports most of the VHR optically imagery commonly used for civil applications: IKONOS, OrbView - 3, SPOT - 5 HRS, SPOT - 5 HRG, QuickBird, GeoEye-1, WorldView-1/2, Pléiades 1A/1B, SPOT 6/7. The second unit of FORSAT is dedicated to 3D surface comparison for change detection. It allows users to import DSMs, to co-register them using an advanced 3D surface matching approach and to calculate the planimetric and volumetric changes between epochs. The capacity and benefits of FORSAT have been tested in two real cases, where are burned areas located in Cyprus and Austria. The geometric characteristics of burned forest areas have been identified both in 2D plane and 3D volume dimensions, using pre- and post-fire optical data from different sensors. FORSAT is a single source and flexible forest information solution, allowing expert and non-expert remote sensing users to monitor forests in three and four dimensions from VHR optical imagery for many forest information needs.\u3c/p\u3

    A precision estimation method for volumetric changes

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    Earth surface changes are often computed by comparing the sequences of digital elevation models (DEMs) so called the DEM of difference (DoD) method. We present an operational DEM generation, co-registration and DoD comparison software in which the surface changes are quantified in metric units of volume. A practical method, which is based on the law of error propagation, is developed to estimate the theoretical precisions of volumetric changes. The proposed pipeline can estimate the change of object volumes (in terms of loss and gain) together with their precision numbers. Change of the forest volume in a fire effected region in a test site is analyzed for the validation. The method can be used for various change detection applications related to forestry as well as other topics such as earthworks, geomorphology, mining, and urbanization.Publisher's Versio

    3-dimensional pre-and post-fire comparison of forest areas

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    Forest agencies give special attention to forest fires where post-disaster loss can rarely be gauged in a quick and economic way unless an appropriate technology is adopted. Determination of the planimetric and volumetric changes between pre- and post-fire is in high demand. The FORSAT system (a satellite processing platform for high resolution forest assessment) was developed to meet the relevant demands. It has the capability of extracting of 3D geometric information from the very-high resolution (VHR) imagery from satellite optical sensors and automatic 3D change detection. FORSAT includes two main units. The first one is dedicated to the geometric and radiometric processing of satellite optical imagery and 2D/3D information extraction. This includes: image radiometric pre-processing, image and ground point measurement, improvement of geometric sensor orientation, quasi-epipolar image generation for stereo measurements, digital surface model (DSM) extraction by using a precise and robust image matching approach specially designed for VHR satellite imagery, generation of orthoimages, and 3D measurements in single images using mono-plotting and in stereo images. FORSAT supports most of the VHR optically imagery commonly used for civil applications: IKONOS, OrbView - 3, SPOT - 5 HRS, SPOT - 5 HRG, QuickBird, GeoEye-1, WorldView-1/2, Pléiades 1A/1B, SPOT 6/7. The second unit of FORSAT is dedicated to 3D surface comparison for change detection. It allows users to import DSMs, to co-register them using an advanced 3D surface matching approach and to calculate the planimetric and volumetric changes between epochs. The capacity and benefits of FORSAT have been tested in two real cases, where are burned areas located in Cyprus and Austria. The geometric characteristics of burned forest areas have been identified both in 2D plane and 3D volume dimensions, using pre- and post-fire optical data from different sensors. FORSAT is a single source and flexible forest information solution, allowing expert and non-expert remote sensing users to monitor forests in three and four dimensions from VHR optical imagery for many forest information needs

    FORSAT: a 3D forest monitoring system for cover mapping and volumetric 3D change detection

    No full text
    A 3D forest monitoring system, called FORSAT (a satellite very high resolution image processing platform for forest assessment), was developed for the extraction of 3D geometric forest information from very high resolution (VHR) satellite imagery and the automatic 3D change detection. FORSAT is composed of two complementary tasks: (1) the geometric and radiometric processing of satellite optical imagery and digital surface model (DSM) reconstruction by using a precise and robust image matching approach specially designed for VHR satellite imagery, (2) 3D surface comparison for change detection. It allows the users to import DSMs, align them using an advanced 3D surface matching approach and calculate the 3D differences and volume changes (together with precision values) between epochs. FORSAT is a single source and flexible forest information solution, allowing expert and non-expert remote sensing users to monitor forests in three and four (time) dimensions. The geometric resolution and thematic content of VHR optical imagery are sufficient for many forest information needs such as deforestation, clear-cut and fire severity mapping. The capacity and benefits of FORSAT, as a forest information system contributing to the sustainable forest management, have been tested and validated in case studies located in Austria, Switzerland and Spain.This research received funding from the EUROSTARS [grant number E!7358] funding scheme, co-funded by the European Commission and the participating countries. We thank the anonymous reviewers for their valuable comments. Their contribution improved the quality of the manuscriptPublisher's Versio
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