Satellite-derived multivariate world-wide lake physical variable timeseries for climate studies.

A consistent dataset of lake surface water temperature, ice cover, water-leaving reflectance, water level and extent is presented. The collection constitutes the Lakes Essential Climate Variable (ECV) for inland waters. The data span combined satellite observations from 1992 to 2020 inclusive and quantifies over 2000 relatively large lakes, which represent a small fraction of the number of lakes worldwide but a significant fraction of global freshwater surface. Visible and near-infrared optical imagery, thermal imagery and microwave radar data from satellites have been exploited. All observations are provided in a common grid at 1/120° latitude-longitude resolution, jointly in daily files. The data/algorithms have been validated against in situ measurements where possible. Consistency analysis between the variables has guided the development of the joint dataset. It is the most complete collection of consistent satellite observations of the Lakes ECV currently available. Lakes are of significant interest to scientific disciplines such as hydrology, limnology, climatology, biogeochemistry and geodesy. They are a vital resource for freshwater supply, and key sentinels for global environmental change.

Water Resources in Africa under Global Change: Monitoring Surface Waters from Space.

Abstract: The African continent hosts some of the largest freshwater systems worldwide, characterized by a large distribution and variability of surface waters that play a key role in the water, energy and carbon cycles and are of major importance to the global climate and water resources. Freshwater availability in Africa has now become of major concern under the combined effect of climate change, environmental alterations and anthropogenic pressure. However, the hydrology of the African river basins remains one of the least studied worldwide and a better monitoring and understanding of the hydrological processes across the continent become fundamental. Earth Observation, that offers a cost-effective means for monitoring the terrestrial water cycle, plays a major role in supporting surface hydrology investigations. Remote sensing advances are therefore a game changer to develop comprehensive observing systems to monitor Africa's land water and manage its water resources. Here, we review the achievements of more than three decades of advances using remote sensing to study surface waters in Africa, highlighting the current benefits and difficulties. We show how the availability of a large number of sensors and observations, coupled with models, offers new possibilities to monitor a continent with scarce gauged stations. In the context of upcoming satellite missions dedicated to surface hydrology, such as the Surface Water and Ocean Topography (SWOT), we discuss future opportunities and how the use of remote sensing could benefit scientific and societal applications, such as water resource management, flood risk prevention and environment monitoring under current global change. Article Highlights: The hydrology of African surface water is of global importance, yet it remains poorly monitored and understoodComprehensive review of remote sensing and modeling advances to monitor Africa's surface water and water resourcesFuture opportunities with upcoming satellite missions and to translate scientific advances into societal applications.

Towards a better characterisation of deep-diving whales' distributions by using prey distribution model outputs?

In habitat modelling, environmental variables are assumed to be proxies of lower trophic levels distribution and by extension, of marine top predator distributions. More proximal variables, such as potential prey fields, could refine relationships between top predator distributions and their environment. In situ data on prey distributions are not available over large spatial scales but, a numerical model, the Spatial Ecosystem And POpulation DYnamics Model (SEAPODYM), provides simulations of the biomass and production of zooplankton and six functional groups of micronekton at the global scale. Here, we explored whether generalised additive models fitted to simulated prey distribution data better predicted deep-diver densities (here beaked whales Ziphiidae and sperm whales Physeter macrocephalus) than models fitted to environmental variables. We assessed whether the combination of environmental and prey distribution data would further improve model fit by comparing their explanatory power. For both taxa, results were suggestive of a preference for habitats associated with topographic features and thermal fronts but also for habitats with an extended euphotic zone and with large prey of the lower mesopelagic layer. For beaked whales, no SEAPODYM variable was selected in the best model that combined the two types of variables, possibly because SEAPODYM does not accurately simulate the organisms on which beaked whales feed on. For sperm whales, the increase model performance was only marginal. SEAPODYM outputs were at best weakly correlated with sightings of deep-diving cetaceans, suggesting SEAPODYM may not accurately predict the prey fields of these taxa. This study was a first investigation and mostly highlighted the importance of the physiographic variables to understand mechanisms that influence the distribution of deep-diving cetaceans. A more systematic use of SEAPODYM could allow to better define the limits of its use and a development of the model that would simulate larger prey beyond 1,000 m would probably better characterise the prey of deep-diving cetaceans.

Seasonal distributions and migrations of Northwest Atlantic swordfish: inferences from integration of pop-up satellite archival tagging studies.

Data sets from three laboratories conducting studies of movements and migrations of Atlantic swordfish (Xiphias gladius) using pop-up satellite archival tags were pooled, and processed using a common methodology. From 78 available deployments, 38 were selected for detailed examination based on deployment duration. The points of deployment ranged from southern Newfoundland to the Straits of Florida. The aggregate data comprise the most comprehensive information describing migrations of swordfish in the Atlantic. Challenges in using data from different tag manufacturers are discussed. The relative utility of geolocations obtained with light is compared with results derived from temperature information for this deep-diving species. The results show that fish tagged off North America remain in the western Atlantic throughout their deployments. This is inconsistent with the model of stock structure used in assessments conducted by the International Commission for the Conservation of Atlantic Tunas, which assumes that fish mix freely throughout the North Atlantic.