2D probabilistic prediction of sparsely measured earth properties constrained by geophysical imaging fully accounting for tomographic reconstruction ambiguity

Many hydrological, environmental, or engineering exploration tasks require predicting spatially continuous scenarios of sparsely measured borehole logging data. We present a methodology to probabilistically predict such scenarios constrained by ill-posed geophysical tomography. Our approach allows for transducing tomographic reconstruction ambiguity into the probabilistic prediction of spatially continuous target parameter scenarios. It is even applicable to data sets where petrophysical relations in the survey area are non-unique, i.e., different facies related petrophysical relations may be present. We employ static two-layer artificial neural networks (ANNs) for prediction and additionally evaluate, whether the training performance of the ANNs can be used to rank geophysical tomograms, which are mathematically equal reconstructions of physical parameter distributions in the ground. We illustrate our methodology using a realistic synthetic database for maximal control about the prediction performance and ranking potential of the approach. For doing so, we try to link geophysical radar and seismic tomography as input parameters to porosity of the ground as target parameter of ANN. However, the approach is flexible and can cope with any combination of geophysical tomograms and hydrologic, environmental or engineering target parameters. Ranking of equivalent geophysical tomograms based on additional borehole logging data is found to be generally possible, but risks remain that the ranking based on the ANN training performance does not fully coincide with the closeness of geophysical tomograms to ground truth. Since geophysical field data sets do usually not offer control options similar to those used in our synthetic database, we do not recommend the utilization of recurrent ANNs to learn weights for the individual geophysical tomograms used in the prediction procedure.     

The Juchatengo complex: an upper-level ophiolite assemblage of late Paleozoic age in Oaxaca,southern Mexico

International Journal of Earth Sciences - The Juchatengo complex (JC) suite is located between the Proterozoic Oaxacan complex to the north and the Xolapa complex to the south, and was amalgamated...     

Modeling the Population Effects of Hypoxia on Atlantic Croaker (<Emphasis Type="Italic">Micropogonias undulatus</Emphasis>) in the Northwestern Gulf of Mexico: Part 1—Model Description and Idealized Hypoxia

We developed a spatially explicit, individual-based model to analyze how hypoxia effects on reproduction, growth, and mortality of Atlantic croaker in the northwestern Gulf of Mexico lead to population-level responses. The model follows the hourly growth, mortality, reproduction, and movement of individuals on a 300 × 800 spatial grid of 1-km² cells for 140 years. Chlorophyll-a concentration, water temperature, and dissolved oxygen (DO) were specified daily for each grid cell and repeated for each year of the simulation. A bioenergetics model was used to represent growth, mortality was assumed stage- and age-dependent, and the movement behavior of juveniles and adults was modeled based on temperature and avoidance of low DO. Hypoxia effects were imposed using exposure effect submodels that converted time-varying exposures to low DO to reduced hourly growth, increased hourly mortality, and reduced annual fecundity. Results showed that 100 years of either mild or intermediate hypoxia produced small reductions in population abundance, while repeated severe hypoxia caused a 19% reduction in long-term population abundance. Relatively few individuals were exposed to low DO each hour, but many individuals experienced some exposure. The response was dominated by a 5% average reduction in annual fecundity of individuals. Under conditions of random sequences of mild, intermediate, and severe hypoxia years occurring in proportion to their historical frequency, the model predicted a 10% decrease in the long-term population abundance of croaker. A companion paper substitutes hourly DO values from a three-dimensional water quality model for the idealized hypoxia and results in a more realistic population reduction of about 25%.     

Evaluating Tidal Wetland Restoration Performance Using National Estuarine Research Reserve System Reference Sites and the Restoration Performance Index (RPI)

Evaluations of tidal wetland restoration efforts suffer from a lack of appropriate reference sites and standardized methods among projects. To help address these issues, the National Estuarine Research Reserve System (NERRS) and the NOAA Restoration Center engaged in a partnership to monitor ecological responses and evaluate 17 tidal wetland restoration projects associated with five reserves. The goals of this study were to (1) determine the level of restoration achieved at each project using the restoration performance index (RPI), which compares change in parameters over time between reference and restoration sites, (2) compare hydrologic and excavation restoration projects using the RPI, (3) identify key indicator parameters for assessing restoration effectiveness, and (4) evaluate the value of the NERRS as reference sites for local restoration projects. We found that the RPI, modified for this study, was an effective tool for evaluating relative differences in restoration performance; most projects achieved an intermediate level of restoration from 2008 to 2010, and two sites became very similar to their paired reference sites, indicating that the restoration efforts were highly effective. There were no differences in RPI scores between hydrologic and excavation restoration project types. Two abiotic parameters (marsh platform elevation and groundwater level) were significantly correlated with vegetation community structure and thus can potentially influence restoration performance. Our results highlight the value of the NERRS as reference sites for assessing tidal wetland restoration projects and provide improved guidance for scientists and restoration practitioners by highlighting the RPI as a trajectory analysis tool and identifying key monitoring parameters.     

Palynology of Triassic–Jurassic boundary sections in northern Switzerland

A first palynostratigraphic scheme of Upper Triassic deposits in northern Switzerland was established based on spore-pollen associations and dinoflagellate cyst records from the upper part of the Upper Triassic Klettgau Formation and the lower part of the Lower Jurassic Staffelegg Formation. Drill cores from the Adlerberg region (Basel Tabular Jura) and from Weiach (northern part of Canton Zurich) as well as from an outcrop at the Chilchzimmersattel (Basel Folded Jura) were studied and five informal palynological associations are distinguished. These palynological associations correlate with palynological association of the Central European Epicontinental Basin and the Tethyan realm and provide a stratigraphic framework for the uppermost Triassic sediments in northern Switzerland. Throughout the uppermost Triassic to Jurassic palynological succession a remarkable prominence of Classopollis spp. is observed. Besides Classopollis spp. the three Rhaetian palynological associations A to C from the Upper Triassic Belchen Member include typical Rhaetian spore-pollen and dinoflagellate taxa (e.g., Rhaetipollis germanicus, Geopollis zwolinskae, Rhaetogonyaulax rhaetica, and Dapcodinium priscum). Association B differs from association A in a higher relative abundance of the sporomorph taxa Perinopollenites spp. and the consistent occurrence of Granuloperculatipollis rudis and Ricciisporites tuberculatus. Spore diversity is highest in the late Rhaetian palynological association C and includes Polypodiisporites polymicroforatus. A Rhaetian age for the Belchen Member is confirmed by palynological associations A–C, but there is no record of the latest Rhaetian and the earliest Jurassic. In contrast to the Rhaetian palynological associations the Early Jurassic associations W and D include Pinuspollenites spp., Trachysporites fuscus (in association W), and Ischyosporites variegatus. In the view of the end-Triassic mass extinction and contemporaneous environmental changes the described palynofloral succession represents the pre-extinction phase (associations A and B) including a distinct transgression, the extinction phase (association C) associated with a regression, and the post-extinction phase (association W).     

Rice crop phenology mapping at high spatial and temporal resolution using downscaled MODIS time-series

Satellite data holds considerable potential as a source of information on rice crop growth which can be used to inform agronomy. However, given the typical field sizes in many rice-growing countries such as China, data from coarse spatial resolution satellite systems such as the Moderate Resolution Imaging Spectroradiometer (MODIS) are inadequate for resolving crop growth variability at the field scale. Nevertheless, systems such as MODIS do provide images with sufficient frequency to be able to capture the detail of rice crop growth trajectories throughout a growing season. In order to generate high spatial and temporal resolution data suitable for mapping rice crop phenology, this study fused MODIS data with lower frequency, higher spatial resolution Landsat data. An overall workflow was developed which began with image preprocessing, calculation of multi-temporal normalized difference vegetation index (NDVI) images, and spatiotemporal fusion of data from the two sensors. The Spatial and Temporal Adaptive Reflectance Fusion Model was used to effectively downscale the MODIS data to deliver a time-series of 30 m spatial resolution NDVI data at 8-day intervals throughout the rice-growing season. Zonal statistical analysis was used to extract NDVI time-series for individual fields and signal filtering was applied to the time-series to generate rice phenology curves. The downscaled MODIS NDVI products were able to characterize the development of paddy rice at fine spatial and temporal resolutions, across wide spatial extents over multiple growing seasons. These data permitted the extraction of key crop seasonality parameters that quantified inter-annual growth variability for a whole agricultural region and enabled mapping of the variability in crop performance between and within fields. Hence, this approach can provide rice crop growth data that is suitable for informing agronomic policy and practice across a wide range of scales.