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Figure 3 in Locomotory activity and orientation of Mesobuthus gibbosus (Scorpiones: Buthidae) in central Aegean Archipelago
Figure 3. The average fraction of the moon visible (± SD) during the time of capture comparatively for scorpions found hidden and those found in the open field.
Figure 1 in Locomotory activity and orientation of Mesobuthus gibbosus (Scorpiones: Buthidae) in central Aegean Archipelago
Figure 1. Distribution of Mesobuthus gibbosus individuals recaptured in the days elapsed after previous capture.
Engaging online students by activating ecological knowledge
<p>The current COVID-19 pandemic has forced the global higher education community to rapidly adapt to partially- or fully-online course offerings. For field- or lab-based courses in ecological curricula, this presents unique challenges. Fortunately, a diverse set of active learning techniques exist, and these techniques translate well to online settings. However, limited guidance and resources exist for developing, implementing, and evaluating active learning assignments that fulfil specific objectives of ecology-focused courses. To address these informational gaps, we (1) identify broad learning objectives across a variety of ecology-focused courses, (2) provide examples, based on our collective online teaching experience, of active learning activities that are relevant to the identified ecological learning objectives, and (3) provide guidelines for successful implementation of active learning assignments in online courses. Using The Wildlife Society's list of online higher education ecology-focused courses as a guide, we obtained syllabi from 45 ecology-focused courses, comprising a total of 321 course-specific learning objectives. We classified all course-specific learning objectives into at least one of five categories: (1) Identification, (2) Application of Concepts/Hypotheses/Theories, (3) Management of Natural Resources, (4) Development of Professional Skills, or (5) Evaluation of Concepts/Practices. We then provided two examples of active learning activities for each of the five categories, along with guidance on their implementation in online settings. We suggest that, when based on sound pedagogy, active learning techniques can enhance the online student's experience by <i>activating</i> ecological knowledge.</p>
Figure 5 in Foraging mode of Australolacerta rupicola (FitzSimons, 1933) (Sauria: Lacertidae): evidence of seasonal variation in an extremely active predator?
Figure 5. Australolacerta rupicola feeding on a spider (a) and a grasshopper (b). Credit: S. Kirchhof.
Figure 1 in Clues supporting photoperiod as the main determinant of seasonal variation in amphibian activity
Figure 1. Path diagram of structural equation model, evaluating 265 the hypotheses that anuran species respond to the month as a latent variable that is a construct of photoperiod, temperature and rainfall. The whole model is congruent with observed data as indicated by its non-significant probability. Paths values are standardized effects ± 1 standard error. Asterisks (*) denote significant coefficients (P <0.05) and "ns" denote non-significant coefficients (P> 0.05). Arrow width represents the strength of the causal link. Month, latent variable; S, number of species calling per month; P, photoperiod; T, mean monthly temperature; R, monthly rainfall; u1 to u4, associated error variable.
Figure 3 in Clues supporting photoperiod as the main determinant of seasonal variation in amphibian activity
Figure 3. Correlation between residuals of the regression between photoperiod and amphibian activity and the fit of the sinusoidal model.
Figure 2 in Clues supporting photoperiod as the main determinant of seasonal variation in amphibian activity
Figure 2. Linear regression of the number of species calling per month (S) between September 1998 and April 2000 with photoperiod (P).
Figure 2. Mean monthly temperatures per year for the period April 1998 in Effect of temperature on the flight activity of culicids in Buenos Aires City, Argentina
Figure 2. Mean monthly temperatures per year for the period April 1998 to March 2001, and minimum, maximum and mean temperatures for the period 1861–2003. Buenos Aires City.
Figure 1 in Effect of temperature on the flight activity of culicids in Buenos Aires City, Argentina
Figure 1. Collection sites of mosquitoes using CDC light traps. Buenos Aires City, April 1998 to March 2001.
Figure 4 in Effect of temperature on the flight activity of culicids in Buenos Aires City, Argentina
Figure 4. Median, quartiles and thermal amplitude of capture events according to the mean temperature of the day at which they were recorded. Species are ranked from higher to lower thermal amplitudes (indicated in brackets).
Figure 3 in Effect of temperature on the flight activity of culicids in Buenos Aires City, Argentina
Figure 3. Proportion of captures by season and species. Buenos Aires City, April 1998 to March 2001.
Figure 10. Mean male and female abundance with 95 in Diurnal flight activity of Ichneumonidae (Insecta: Hymenoptera) in Cabañeros National Park (Spain)
Figure 10. Mean male and female abundance with 95% confidence intervals for each period. Significant differences between periods (as measured by Tukey tests) in italics.
Figure 8 in Diurnal flight activity of Ichneumonidae (Insecta: Hymenoptera) in Cabañeros National Park (Spain)
Figure 8. Scatter plot for numbers of individuals against humidity. The estimated normal curve is represented.
Figure 7 in Diurnal flight activity of Ichneumonidae (Insecta: Hymenoptera) in Cabañeros National Park (Spain)
Figure 7. Scatter plot for numbers of individuals against temperature. The estimated normal curve is represented.
Figure 6 in Diurnal flight activity of Ichneumonidae (Insecta: Hymenoptera) in Cabañeros National Park (Spain)
Figure 6. All samples distributed in a two-dimensional plot according to the factors obtained with the principal components analysis. Each sample is represented by the sampling hour and the sampling day (first, second or third). Similar samples are grouped by ellipses.
Figure 4 in Diurnal flight activity of Ichneumonidae (Insecta: Hymenoptera) in Cabañeros National Park (Spain)
Figure 4. Relationship between species richness and number of individuals trapped per sampling hour.
Figure 3 in Diurnal flight activity of Ichneumonidae (Insecta: Hymenoptera) in Cabañeros National Park (Spain)
Figure 3. Number of individuals and number of species trapped per sampling hour. Discontinuous lines separate the three sampling days.
Figure 2 in Diurnal flight activity of Ichneumonidae (Insecta: Hymenoptera) in Cabañeros National Park (Spain)
Figure 2. Hourly totals of trapped Ichneumonidae related to air temperature, relative humidity and illuminance over three sampling days.
Figure 5 in Diurnal flight activity of Ichneumonidae (Insecta: Hymenoptera) in Cabañeros National Park (Spain)
Figure 5. Diurnal flight activity for both sexes in the three sampling days, against air temperature.
Figure 11 in Diurnal flight activity of Ichneumonidae (Insecta: Hymenoptera) in Cabañeros National Park (Spain)
Figure 11. Mean values for richness (left) and Margalef index (right) with 95% confidence interval for each period. Significant differences between periods (as indicated by Tukey tests) in italics.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.