Development of a Seafloor Community Classification for the New Zealand Region Using a Gradient Forest Approach

To support ongoing marine spatial planning in New Zealand, a numerical environmental classification using Gradient Forest models was developed using a broad suite of biotic and high-resolution environmental predictor variables. Gradient Forest modeling uses species distribution data to control the selection, weighting and transformation of environmental predictors to maximise their correlation with species compositional turnover. A total of 630,997 records (39,766 unique locations) of 1,716 taxa living on or near the seafloor were used to inform the transformation of 20 gridded environmental variables to represent spatial patterns of compositional turnover in four biotic groups and the overall seafloor community. Compositional turnover of the overall community was classified using a hierarchical procedure to define groups at different levels of classification detail. The 75-group level classification was assessed as representing the highest number of groups that captured the majority of the variation across the New Zealand marine environment. We refer to this classification as the New Zealand “Seafloor Community Classification” (SCC). Associated uncertainty estimates of compositional turnover for each of the biotic groups and overall community were also produced, and an added measure of uncertainty – coverage of the environmental space – was developed to further highlight geographic areas where predictions may be less certain owing to low sampling effort. Environmental differences among the deep-water New Zealand SCC groups were relatively muted, but greater environmental differences were evident among groups at intermediate depths in line with well-defined oceanographic patterns observed in New Zealand’s oceans. Environmental differences became even more pronounced at shallow depths, where variation in more localised environmental conditions such as productivity, seafloor topography, seabed disturbance and tidal currents were important differentiating factors. Environmental similarities in New Zealand SCC groups were mirrored by their biological compositions. The New Zealand SCC is a significant advance on previous numerical classifications and includes a substantially wider range of biological and environmental data than has been attempted previously. The classification is critically appraised and considerations for use in spatial management are discussed.

The Impact of Hurricane Disturbances on a Tropical Forest: Implementing a Palm Plant Functional Type and Hurricane Disturbance Module in ED2-HuDi V1.0

Hurricanes commonly disturb and damage tropical forests. It is predicted that changes in climate will result in changes in hurricane frequency and intensity. Modeling is needed to investigate the potential response of forests to future disturbances. Unfortunately, existing models of forests dynamics are not presently able to account for hurricane disturbances. We implement the Hurricane Disturbance in the Ecosystem Demography model (ED2) (ED2-HuDi). The hurricane disturbance includes hurricane-induced immediate mortality and subsequent recovery modules. The parameterizations are based on observations at the Bisley Experimental Watersheds (BEW) in the Luquillo Experimental Forest in Puerto Rico. We add one new plant functional type (PFT) to the model—Palm, as palms cannot be categorized into one of the current existing PFTs and are known to be an abundant component of tropical forests worldwide. The model is calibrated with observations at BEW using the generalized likelihood uncertainty estimates (GLUE) approach. The optimal simulation obtained from GLUE has a mean relative error of −21 %, −12 %, and −15 % for stem density, basal area, and aboveground biomass, respectively. The optimal simulation also agrees well with the observation in terms of PFT composition (+1%, −8 %, −2 %, and +9 % differences in the percentages of Early, Mid, Late, and Palm PFTs, respectively) and size structure of the forest (+0.8 % differences in the percentage of large stems). Lastly, using the optimal parameter set, we study the impact of forest initial condition on the recovery of the forest from a single hurricane disturbance. The results indicate that, compared to a no-hurricane scenario, a single hurricane disturbance has little impact on forest structure (+1 % change in the percentage of large stems) and composition (< 1 % change in the percentage of each of the four PFTs) but leads to 5 % higher aboveground biomass after 80 years of succession. The assumption of a less severe hurricane disturbance leads to a 4 % increase in aboveground biomass.

Seismic Attenuation Anisotropy in the Southernmost Part of the Taupo Volcanic Zone, North Island, New Zealand

<p>We investigate the mechanisms of seismic anisotropy and attenuation (1/Q) beneath the southernmost part of the Taupo Volcanic Zone (TVZ) by computing variations in S-wave attenuation factors with the direction of wave polarization. We rotate pairs of horizontal components in steps of 22.5◦ from 0◦ to 67.5◦ and into the radial and transverse directions to search for the optimal separation of the attenuation curves and thereby determine an anisotropy symmetry system. The frequency dependence of Q for the rotated S-waves is estimated by means of the non-parametric generalized inversion technique (GIT) of Castro et al. (1990) using shallow earthquakes (< 40 km depth) recorded by GeoNet within 100 km of Mt. Ruapehu. To analyze the effects on computed attenuation properties of source locations, we divide our dataset into two groups: a “TVZ” group containing earthquakes within the TVZ in a distance range of 5–55 km and a “non-TVZ” group containing earthquakes outside the TVZ in a distance range of 5–50 km. To measure Q, we compute the spectral amplitude decay with distance in terms of empirical functions at 20 separate frequencies in the frequency bands 2–10 Hz and 2– 12 Hz for the TVZ and non-TVZ datasets respectively. We construct homogeneous and two-layer Q models for the TVZ dataset based on characteristic features of the attenuation function, while for outside TVZ we only analyse a homogeneous Q model. The homogeneous Q models obtained for the two datasets indicate that S-waves are more attenuated within the TVZ than outside. The homogeneous Q model for the TVZ dataset reveals that the S-wave is anisotropic at high frequencies ( f > 6 Hz) along N–S/E– W directions with the relation QSE ( f ) = (6.15±1.22) f (1.73±0.12) and QSN ( f ) = (4.14± 1.26) f (2.06±0.14), while the non-TVZ dataset shows a weak frequency dependence of attenuation anisotropy at low frequencies in NE–SW/SE–NW directions giving the power law function QSNE ( f ) = (50.93±1.18) f (0.20±0.10) and QSSE ( f ) = (22.60±1.10) f (0.53±0.06). Here, the uncertainty estimates are 95% confidence intervals. To investigate the variation of attenuation anisotropy with depth within the TVZ, we first calculate Q along propagation paths (< 25 km, which corresponds to a maximum turning point depth of 9 km ) and then using paths of 25–55 km length. Small attenuation anisotropy with low attenuation in the N–S direction for the upper crust of TVZ may be related to heterogenous structure as reported by previous studies. Attenuation anisotropy in the northwest direction yielding lower attenuation inferred for the deeper crust suggests the presence of connected melt aligned with the extension direction of TVZ .</p>

Seismic Attenuation Anisotropy in the Southernmost Part of the Taupo Volcanic Zone, North Island, New Zealand

<p>We investigate the mechanisms of seismic anisotropy and attenuation (1/Q) beneath the southernmost part of the Taupo Volcanic Zone (TVZ) by computing variations in S-wave attenuation factors with the direction of wave polarization. We rotate pairs of horizontal components in steps of 22.5◦ from 0◦ to 67.5◦ and into the radial and transverse directions to search for the optimal separation of the attenuation curves and thereby determine an anisotropy symmetry system. The frequency dependence of Q for the rotated S-waves is estimated by means of the non-parametric generalized inversion technique (GIT) of Castro et al. (1990) using shallow earthquakes (< 40 km depth) recorded by GeoNet within 100 km of Mt. Ruapehu. To analyze the effects on computed attenuation properties of source locations, we divide our dataset into two groups: a “TVZ” group containing earthquakes within the TVZ in a distance range of 5–55 km and a “non-TVZ” group containing earthquakes outside the TVZ in a distance range of 5–50 km. To measure Q, we compute the spectral amplitude decay with distance in terms of empirical functions at 20 separate frequencies in the frequency bands 2–10 Hz and 2– 12 Hz for the TVZ and non-TVZ datasets respectively. We construct homogeneous and two-layer Q models for the TVZ dataset based on characteristic features of the attenuation function, while for outside TVZ we only analyse a homogeneous Q model. The homogeneous Q models obtained for the two datasets indicate that S-waves are more attenuated within the TVZ than outside. The homogeneous Q model for the TVZ dataset reveals that the S-wave is anisotropic at high frequencies ( f > 6 Hz) along N–S/E– W directions with the relation QSE ( f ) = (6.15±1.22) f (1.73±0.12) and QSN ( f ) = (4.14± 1.26) f (2.06±0.14), while the non-TVZ dataset shows a weak frequency dependence of attenuation anisotropy at low frequencies in NE–SW/SE–NW directions giving the power law function QSNE ( f ) = (50.93±1.18) f (0.20±0.10) and QSSE ( f ) = (22.60±1.10) f (0.53±0.06). Here, the uncertainty estimates are 95% confidence intervals. To investigate the variation of attenuation anisotropy with depth within the TVZ, we first calculate Q along propagation paths (< 25 km, which corresponds to a maximum turning point depth of 9 km ) and then using paths of 25–55 km length. Small attenuation anisotropy with low attenuation in the N–S direction for the upper crust of TVZ may be related to heterogenous structure as reported by previous studies. Attenuation anisotropy in the northwest direction yielding lower attenuation inferred for the deeper crust suggests the presence of connected melt aligned with the extension direction of TVZ .</p>

Partitioning Ground Motion Uncertainty When Conditioned on Station Data

ABSTRACT Rapid estimation of earthquake ground shaking and proper accounting of associated uncertainties in such estimates when conditioned on strong-motion station data or macroseismic intensity observations are crucial for downstream applications such as ground failure and loss estimation. The U.S. Geological Survey ShakeMap system is called upon to fulfill this objective in light of increased near-real-time access to strong-motion records from around the world. Although the station data provide a direct constraint on shaking estimates at specific locations, these data also heavily influence the uncertainty quantification at other locations. This investigation demonstrates methods to partition the within- (phi) and between-event (tau) uncertainty estimates under the observational constraints, especially when between-event uncertainties are heteroscedastic. The procedure allows the end users of ShakeMap to create separate between- and within-event realizations of ground-motion fields for downstream loss modeling applications in a manner that preserves the structure of the underlying random spatial processes.

From Validation Statistics to Uncertainty Estimates: Application to VIIRS Ocean Color Radiometric Products at European Coastal Locations

Uncertainty estimates are needed to assess ocean color products and qualify the agreement between missions. Comparison between field observations and satellite data, a process defined as validation, has been the traditional way to assess satellite products. However validation statistics can provide only an approximation for satellite data uncertainties as field measurements have their own uncertainties and as the validation process is imperfect, comparing data potentially differing in temporal, spatial or spectral characteristics. This study describes a method to interpret in terms of uncertainties the validation statistics obtained for ocean color remote sensing reflectance RRS knowing the uncertainties associated with field data. This approach is applied to observations collected at sites part of the Ocean Color component of the Aerosol Robotic Network (AERONET-OC) located in coastal regions of the European seas, and to RRS data from the VIIRS sensors on-board the SNPP and JPSS1 platforms. Similar estimates of uncertainties σVRS (term accounting for non-systematic contributions to the uncertainty budget) are obtained for both missions, decreasing with wavelength from the interval 0.8–1.4 10−3 sr−1 in the blue to a maximum of 0.24 10−3 sr−1 in the red, values that are at least twice (but up to 8 times) the uncertainties reported for the field data. These uncertainty estimates are then used to qualify the agreement between the VIIRS products, defining the extent to which they agree within their stated uncertainty. Despite significant biases between the two missions, their RRS products appear fairly compatible.

Can the sedentary behavior of basketball and volleyball players impact bone mass and bone geometry?

The aim of the study was to evaluate the relationship between sedentary behavior, bone mass, and bone geometry among young male basketball and volleyball players. This cross-sectional study included 55 adolescent basketball ( n = 21) and volleyball ( n = 34) players (14–17 years). Body composition (body mass index, fat mass, and lean mass) was measured by dual-energy X-ray absorptiometry, comprising bone mineral density, bone mineral content at the lumbar spine, and femoral neck. Bone geometry considered the femur strength index, section modulus, cross-sectional moment of inertia, and cross-sectional area. Dietary intake was obtained through a semiquantitative questionnaire, and the sedentary behavior, by the Adolescent Sedentary Activity Questionnaire. Linear regression models, fitted by Bayesian methods, explored the variation of the variables by sport. Body composition and bone mass values were high for both sports, but there was no variation for body composition. Adjusting for age, there was no association of sedentary behavior on bone parameters. For femoral strength index, age had a moderate to large association with all bone indicators. Lastly, there was influence of sport (level-2 unit) on the estimates of the association between sedentary behavior and age with bone indicators, as uncertainty estimates for group-level effects were high. There is no association between sedentary behavior and bone parameters, showing that accumulated training loads (15+ h/wk) among young basketball and volleyball players are critical; producing a positive stimulus on bone parameters development.

Adversarial Attack for Uncertainty Estimation: Identifying Critical Regions in Neural Networks

We propose a novel method to capture data points near decision boundary in neural network that are often referred to a specific type of uncertainty. In our approach, we sought to perform uncertainty estimation based on the idea of adversarial attack method. In this paper, uncertainty estimates are derived from the input perturbations, unlike previous studies that provide perturbations on the model's parameters as in Bayesian approach. We are able to produce uncertainty with couple of perturbations on the inputs. Interestingly, we apply the proposed method to datasets derived from blockchain. We compare the performance of model uncertainty with the most recent uncertainty methods. We show that the proposed method has revealed a significant outperformance over other methods and provided less risk to capture model uncertainty in machine learning.