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Fig. 6 in Post-collection taphonomy, sampling effects and the role of the collector in palaeontological collections: A case study from an early Late Triassic bone accumulation in southernmost Brazil

Fig. 6. Selected specimens from the three collections showing effects of sullegic (i.e., during sampling activity), trephic (i.e., from transport to preparation and storage) and "taxonomical" factors. A and B show two mandibles of traversodontid cynodonts, of which previously just two out of ten fragments were considered as such, while the rest as indeterminate fragments. In C, several specimens from a single original association, numbered separately, and now together again, still being able to provide taphonomic information. Some of them (e.g., rib fragments) had been associated with similar others and analyzed with systematic interest, losing the taphonomic information. D shows two parts of the same bone (D1, MCP-PV 4017; D2, MCP-PV 4028), a right femur, encountered already separated and isolated, and catalogued as two different specimens, part in D2 being identified as an indeterminate fragment.

Fig. 3 in Post-collection taphonomy, sampling effects and the role of the collector in palaeontological collections: A case study from an early Late Triassic bone accumulation in southernmost Brazil

Fig. 3. Results of the sampling by three institutions (A–C) schematized into the Voorhies Groups (Voorhies 1969, sensu Behrensmeyer 1975; modified), favouring biases in data interpretations and palaeoecological reconstructions. Abbreviations: ifr, indeterminate fragments; ith, isolated teeth; ND, not determinable; VG, Voorhies Groups.

Fig. 2 in Post-collection taphonomy, sampling effects and the role of the collector in palaeontological collections: A case study from an early Late Triassic bone accumulation in southernmost Brazil

Fig. 2. Timeline of the sampling activities carried out at the Schoenstatt site by the three institutions.

Fig. 1 in Post-collection taphonomy, sampling effects and the role of the collector in palaeontological collections: A case study from an early Late Triassic bone accumulation in southernmost Brazil

Fig. 1. Maps showing position of the Santa Maria Supersequence in South America (southern Brazil, Paraná Basin) (A) and the Rio Grande do Sul State (B). C. Location of the outcrops in which the Santacruzodon AZ has been recognized (stars).

opencc-by-4.0Dec 2016View details →

Figure 1 in Quantifying scientific significance of a fossil site: the Gogo Fossil sites (Late Devonian, Western Australia) as a case study

Figure 1. Map showing area covering the Gogo Formation site localities (geology taken from Long and Trinajstic, 2010, figure 1).

FIG. 3 in Response of bryophytes to disturbances in managed forests. A case study from a Polish forest

FIG. 3. — Co-correspondence analysis biplot illustrating the ordination of most frequent bryophyte species colonizing ground in relation to the statistically significant environmental variables (n=75). Abbreviations: Age, forest age; DBH.max, maximal trees diameter at breast height; DW.vol, dead wood volume; L, Ellenberg indicator value (EIV) for light; T, EIV for temperature; F, EIV for moisture; R, EIV for pH; N, EIV for nitrogen; the first four letters of species indicate genus name, next four indicate species names and next four letters subspecies names.

0.0 0.5 1.0 1.5 RDA 1 FIG. 4 in Response of bryophytes to disturbances in managed forests. A case study from a Polish forest

0.0 0.5 1.0 1.5 RDA 1 FIG. 4. — Redundancy analysis biplot illustrating the ordination of most frequent bryophyte species colonizing tree trunks in relation to the statistically significant environmental variables for the plots with the presence of tree host species (n=41). Abbreviations as in Fig. 3.

FIG. 6 in Response of bryophytes to disturbances in managed forests. A case study from a Polish forest

FIG. 6. — Redundancy analysis biplot illustrating the ordination of most frequent bryophyte species colonizing dead wood in relation to the statistically significant environmental variables for the plots with the presence of decaying logs (n=80). Abbreviations as in Fig. 3

FIG. 5 in Response of bryophytes to disturbances in managed forests. A case study from a Polish forest

FIG. 5. — Redundancy analysis biplot illustrating the ordination of most frequent bryophyte species colonizing tree bases in relation to the statistically significant environmental variables for the plots with the presence of tree host species (n=96). Abbreviations as in Fig. 3.

FIG. 2 in Response of bryophytes to disturbances in managed forests. A case study from a Polish forest

FIG. 2. — Frequency of occurrence of bryophytes generally and in the four types of substrates considered.

opencc-zeroJun 2024View details →

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Code from: Enhancing data-limited assessments with random effects: A case study on Korea chub mackerel (Scomber japonicus)

<div> <div> <div> <p>In a state-space framework, temporal variations in fishery-dependent processes can be modeled as random effects. This modeling flexibility makes state-space models (SSMs) powerful tools for data-limited assessments. Though SSMs enable the model-based inference of the unobserved processes, their flexibility can lead to overfitting and non-identifiability issues. To address these challenges, we developed a suite of state-space length-based age-structured models and applied them to the Korean chub mackerel (<em>Scomber japonicus</em>) stock. Our research demonstrated that incorporating temporal variations in fishery-dependent processes can rectify model mis-specification but may compromise robustness, which can be diagnosed through a series of model checking processes. To tackle non-identifiability, we used a non- degenerate estimator, implementing a gamma distribution as a penalty for the standard deviation parameters of observation errors. This penalty function enabled the simultaneous estimation of both process and observation error variances with minimal bias, a notably challenging task in SSMs. These results highlight the importance of model checking and the effectiveness of the penalized approach in estimating SSMs. Additionally, we discussed novel assessment outcomes for the mackerel stock.</p> </div> </div> </div>

opencc-by-4.0Jun 2024View details →

Dataset from: "Assessment of depression, anxiety, and psychological symptoms in parents of pediatric palliative care patients: A single-center case-control study"

<p>The dataset comprises raw data from a case-control study that compared levels of depression, anxiety, and general psychological symptoms between parents of pediatric palliative care (PPC) patients and parents of healthy controls.</p> <p>Beck Depression Inventory (BDI), Beck Anxiety Inventory (BAI), and Symptom Checklist-90 Revised (SCL-90-R) were employed to provide a comprehensive and nuanced understanding of the mental health challenges faced by parents.</p> <p>The designation "case" in the first column (A) represents the parents of PPC patients, while the designation "control" represents the control group.  The columns labeled B to S present demographic characteristics data, while columns T to AR present inventory scores. Columns BB to GC, in turn, present the responses to the inventory items.</p> <p> </p> <p> </p>

opencc-by-4.0Feb 2024View details →

Fig. 4 in Refining the Occurrence of Viral Encephalopathy and Retinopathy, Photobacteriosis, and Vibriosis in Connection with Seawater Physicochemical Parameters: A Five-Year Case Study Abstract

Fig. 4: Estimated time series of the probability of absence/presence (0 to 1) based on the model (depicted by a line), alongside on-site records of absence/presence (represented by dots) for three diseases at Fish Farm A.

opencc-by-4.0Feb 2024View details →

Fig. 2 in Refining the Occurrence of Viral Encephalopathy and Retinopathy, Photobacteriosis, and Vibriosis in Connection with Seawater Physicochemical Parameters: A Five-Year Case Study Abstract

Fig. 2: A - Annual variation (HREG) of physico-chemical parameters based on mean value parameters (T=temperature °C), TS- D=standard deviation of T, S=salinity (psu), SSD=standard deviation of salinity, O=oxygen (mg/ml), OSD=standard deviation of oxygen, pH, pHSD=standard deviation of pH). B - Presence/absence of diseases (t0= 1/1, step 1 day) (VAO1=Vibriosis, PHDP=- Photobacteriosis, VER=viral encephalopathy & retinopathy).

opencc-by-4.0Feb 2024View details →

Fig. 3 in Refining the Occurrence of Viral Encephalopathy and Retinopathy, Photobacteriosis, and Vibriosis in Connection with Seawater Physicochemical Parameters: A Five-Year Case Study Abstract

Fig. 3: Presence/absence of fish diseases in the years 2011-2015. (A: VER - Viral Encephalopathy & Retinopathy, B: PHDP - Photobacteriosis, C: VAO1 - Vibriosis). For the presence of disease, the value was [1], and for absence, it was [0].

Fig. 5 in Using spatial indicators to investigate fish spawning strategies from ichthyoplankton surveys: A case study on co-occurring pelagic species from the North-East Aegean Sea Abstract

Fig. 5: Distribution and abundance maps of eggs during May (A, B) and July 2010 (C-E), in the NE Aegean Sea. The major patches are indicated by different colours, while the size of the circles is scaled by the maximum abundance per species and period (Table 2). The number of each patch indicates the ranking according to the abundance of individuals in each patch. The small black cross symbols show the centres of gravity (CG) of each major patch (i.e. those patches having more than 10% of the overall abundance; Table 3). The large cross indicates the CG of the population. The length of the cross axes indicate the isotropy of the egg distribution. The 200m isobaths are also shown (dark contour line).

Fig. 4 in Using spatial indicators to investigate fish spawning strategies from ichthyoplankton surveys: A case study on co-occurring pelagic species from the North-East Aegean Sea Abstract

Fig. 4: Box-and-whisker plots for temperature (oC; at 10 m depth), salinity (at 10 m depth), log-transformed integrated fluorescence (μg l-1) and log-transformed mesozooplankton biomass (mg m-2) between three groups of sampling stations: L – Lemnos plateau, O – offshore pelagic area north of Lemnos island, and T- Thracian Sea shelf. Boxes indicate median and interquartile ranges, whiskers delineate full ranges. F-values are provided for comparisons of the parameters between the three groups (L, O, T) and within each season. For comparisons that did not meet the assumptions of the analysis of variance, the Kruskal-Wallis statistic H is provided. Asterisks indicate significant differences: *p <0.05, **p <0.01, ***p <0.001. Post-hoc multiple comparisons were performed with a Student-Newman-Keul's test, where statistically significant differences among groups are indicated by letters a, b, c on the left side of each box. Groups with the same letter do not differ significantly.

Fig. 3 in Using spatial indicators to investigate fish spawning strategies from ichthyoplankton surveys: A case study on co-occurring pelagic species from the North-East Aegean Sea Abstract

Fig. 3: Contour maps of the vertical distribution of temperature (oC; left column), salinity (middle column) and fluorescence (μg Chlα l-1; right column) during May 2010 along transect A (A-C) and transect B (D-F), and during July 2010 along transects A (H-J) and B (K-M). Y-axis: depth of the water column; X-axis: distance (nmi) from the northern sampling station (0 nmi) to the southern station. The position (distance, nmi) of the sampling stations along the transects are shown in white, dashed lines on top of the temperature contour maps.

Fig. 2 in Using spatial indicators to investigate fish spawning strategies from ichthyoplankton surveys: A case study on co-occurring pelagic species from the North-East Aegean Sea Abstract

Fig. 2: Temperature (oC, 10 m depth; A, E), salinity (10 m; B, F), integrated fluorescence (μg Chl-a l-1, 0-100 m; C, G) and mesozooplankton biomass (mg m-2; D, H) during May (A-D) and July 2010 (E-H) in the study area.

Fig. 1 in Using spatial indicators to investigate fish spawning strategies from ichthyoplankton surveys: A case study on co-occurring pelagic species from the North-East Aegean Sea Abstract

Fig. 1: Ichthyoplankton (shown as open red circles) and CTD sampling stations (shown as filled red circles) during May and July 2010. The isobaths of 100 and 200 m are shown (light and dark blue lines, respectively). Black arrows indicate the main circulation pattern in the area: LIS - Lemnos-Imvros stream, SG - Samothraki gyre (Somarakis et al., 2002). The sampling stations of transects A and B (grey lines) show the vertical structure of the water column in Figure 3.