Combining multisensor images and social network data to assess the area flooded by a hurricane event.

In this study, multisensor remote sensing datasets were used to characterize the land use and land covers (LULC) flooded by Hurricane Willa which made landfall on October 24, 2018. The landscape characterization was done using an unsupervised K-means algorithm of a cloud-free Sentinel-2 MultiSpectral Instrument (MSI) image, acquired during the dry season before Hurricane Willa. A flood map was derived using the histogram thresholding technique over a Synthetic Aperture Radar (SAR) Sentinel-1 C-band and combined with a flood map derived from a Sentinel-2 MSI image. Both, the Sentinel-1 and Sentinel-2 images were obtained after Willa landfall. While the LULC map reached an accuracy of 92%, validated using data collected during field surveys, the flood map achieved 90% overall accuracy, validated using locations extracted from social network data, that were manually georeferenced. The agriculture class was the dominant land use (about 2,624 km2), followed by deciduous forest (1,591 km2) and sub-perennial forest (1,317 km2). About 1,608 km2 represents the permanent wetlands (mangrove, salt marsh, lagoon and estuaries, and littoral classes), but only 489 km2 of this area belongs to aquatic surfaces (lagoons and estuaries). The flooded area was 1,225 km2, with the agricultural class as the most impacted (735 km2). Our analysis detected the saltmarsh class occupied 541 km2in the LULC map, and around 328 km2 were flooded during Hurricane Willa. Since the water flow receded relatively quickly, obtaining representative imagery to assess the flood event was a challenge. Still, the high overall accuracies obtained in this study allow us to assume that the outputs are reliable and can be used in the implementation of effective strategies for the protection, restoration, and management of wetlands. In addition, they will improve the capacity of local governments and residents of Marismas Nacionales to make informed decisions for the protection of vulnerable areas to the different threats derived from climate change.

Role of oceanography in shaping the genetic structure in the North Pacific hake Merluccius productus.

Determining the relative influence of biotic and abiotic factors on genetic connectivity among populations remains a major challenge in evolutionary biology and in the management and conservation of species. North Pacific hake (Merluccius productus) inhabits upwelling regions in the California Current ecosystem from the Gulf of California to the Gulf of Alaska. In this study, we examined mitochondrial DNA (mtDNA) and microsatellite variation to estimate levels of genetic differentiation of M. productus in relation to the role of oceanographic features as potential barriers to gene flow. Samples were obtained from nine sites spanning a large part of the geographic range of the species, from Puget Sound, Washington to Costa Rica. The microsatellite results revealed three genetically discrete populations: one spanning the eastern Pacific coast, and two apparently resident populations circumscribed to the Puget Sound and the northern Gulf of California (FST = 0.032, p = 0.036). Cytochrome b sequence data indicated that isolation between the Puget Sound and northern Gulf of California populations from the coastal Pacific were recent phenomena (18.5 kyr for Puget Sound and 40 kyr for the northern Gulf of California). Oceanographic data obtained from the Gulf of California support the hypothesis that permanent fronts within the region, and strong gradients at the entrance to the Gulf of California act as barriers to gene flow. A seascape genetics approach found significant genetic-environment associations, where the daytime sea surface temperature and chlorophyll concentrations were the best predictive variables for the observed genetic differentiation. Considering the potential causes of genetic isolation among the three populations, e.g. spawning areas in different latitudes associated with upwelling processes, oceanographic barriers, asymmetric migration and specialized diet, oceanographic barriers appear to be a likely mechanism restricting gene flow.

Assessment of runoff response to landscape changes in the San Pedro subbasin (Nayarit, Mexico) using remote sensing data and GIS.

Results on runoff estimates as a response to land-use and land-cover changes are presented. We used remote sensing and GIS techniques with rainfall time-series data, spatial ancillary information, and the curve-number method (NRCS-CN) to assess the runoff response in the San Pedro subbasin. Thematic maps with eight land-cover classes derived from satellite imagery classification (1973, 1990, and 2000) and hydrologic soil-group maps were used as the input for the runoff calculation. About 20% to 25% of the subbasin landscape has changed since 1973, mainly as consequence of the growth of agriculture. Forest is the main cover, although further analyses indicate that forest is degrading from good to poor conditions when evaluated as a function of the spectral response. Soils with low infiltration rates, classified as the hydrological soil-group "C", were dominant in the area (52%). The overlaying of all the hydrological soil groups with the land-use map produced a total of 43 hydro-group and land-use categories for which runoff was calculated using the curve-number method. Estimates of total runoff volumes (26 x 10(6) m3) were similar for the three dates analyzed in spite of landscape changes, but there were temporal variations among the hydro-group and land-use categories as a consequence. Changes are causing the rise of covers with high runoff potential and the increase of runoff depth is expected, but it can be reversed by different management of subbasin hydro-groups and land-use units.