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Fig. 2 in Growth Rate Modulation Enables Coexistence in a Competitive Exclusion Scenario Between Microbial Eukaryotes
Fig. 2. Growth curves of Arcella intermedia and Pyxidicula operculata in the monospecific culture experiments (three replicates each). Dots represent the raw sampled data; colored intervals represent the 95% credibility intervals of cell counts from the Bayesian model fitting.
Fig. S2 in Growth Rate Modulation Enables Coexistence in a Competitive Exclusion Scenario Between Microbial Eukaryotes
Fig. S2. Posterior distributions of the logistic model parameters. The values of K are in cells cm–2, r = d–1. P is the detection probability. P has a fixed range between 0.9 and 1. Color lines represents each one of the single-species experiments, color legend is in the right corner of the figure. A.intermedia experiments are Arc 1, 2 and 3. P.operculata experiments are Pyx 1, 2 and 3.
Fig. S1 in Growth Rate Modulation Enables Coexistence in a Competitive Exclusion Scenario Between Microbial Eukaryotes
Fig. S1. Overview of data collection design. Microcosms are assembled and sampled by a sub- sampling strategy where the organisms are counted by eye. Model adjustment considers both the system dynamics and the sampling level.
Fig. S4. Growth curves for A.intermedia when started the experiment with a in Growth Rate Modulation Enables Coexistence in a Competitive Exclusion Scenario Between Microbial Eukaryotes
Fig. S4. Growth curves for A.intermedia when started the experiment with a single cell. Color points represents each one of the single-cell experiments, color legend is in the left corner of the figure. Black line correspond to the average growth between experiments.
Fig. S3 in Growth Rate Modulation Enables Coexistence in a Competitive Exclusion Scenario Between Microbial Eukaryotes
Fig. S3. Posterior distributions of the competition model parameters for the species Arcella intermedia (A) and Pyxidicula operculata (P). Each colored line represent one of the replicates of the competition experiment (color legend shown in the last figure). The values of k are in a logarithmic scale of cells cm-2, r are in days–1. aAP is the competition coefficient of the influence of A species on P (Eq. 3), whereas aPA is the competition coefficient of the influence of P on A (Eq. 4).
Fig. 4 in Growth Rate Modulation Enables Coexistence in a Competitive Exclusion Scenario Between Microbial Eukaryotes
Fig. 4. Posterior estimates of the parameters of models fitted to cell counts in each culture. Each panel shows the medians (dots) and 95% credibility intervals (lines) of posterior distributions of one parameter of the models fitted to data from a replicate (seven for the competition cultures in lower part and three for mono-specific cultures in the upper part). In red, estimates for Arcella intermedia and in blue estimates for Pyxidicula operculata. The values of K are in cm–2, r are in days–1. The competition coefficients are α (red) and β (blue) of Eqs. 3–4.
Fig. 1 in Growth Rate Modulation Enables Coexistence in a Competitive Exclusion Scenario Between Microbial Eukaryotes
Fig. 1. Species used in this study. A – Arcella intermedia LEP isolate 6, magnification 630×. B – Pyxidicula operculata LEP isolate 1, magnification 1000×.
Fig. 7 in Fig. 7 in Coexistence of Juvenile with Adult at Culebra Beach, Panama: A Temporal-spatial Partitioning Compromise.
Fig. 7. Non-metric Multidimensional Scaling plot of the activity budget of the juvenile and adult Ocypode gaudichaudii from Culebra Beach superimposed with Bray-Curtis cluster analysis using 60% and 80% similarity. 2D stress = 0.15.
Fig. 3 in Fig. 7 in Coexistence of Juvenile with Adult at Culebra Beach, Panama: A Temporal-spatial Partitioning Compromise.
Fig. 3. Boxplots of the median carapace width and interquartile range of Ocypode gaudichaudii during the day and night at Culebra Beach. Dark bands represent medians, boxes represent interquartile range and whiskers represent 1.5 times the interquartile range.
Fig. 6 in Fig. 7 in Coexistence of Juvenile with Adult at Culebra Beach, Panama: A Temporal-spatial Partitioning Compromise.
Fig. 6. Mean proportion of time (± S.E.) that Ocypode gaudichaudii from Culebra Beach were engaged in seven behaviors after burrow emergence. ScF, scavenging; DepF, deposit-feeding; Probe, probing for food; BurM, burrow maintenance; Walk, walking; In bur, staying within the burrow; Rest, resting at the burrow entrance.
Fig. 2 in Fig. 7 in Coexistence of Juvenile with Adult at Culebra Beach, Panama: A Temporal-spatial Partitioning Compromise.
Fig. 2. Location of Culebra Beach with the inset showing a 30 × 30 m plot marked out as the sampling area across six five-metre zones (zone 1 to zone 6). The area was divided into 36 (5 × 5 m) quadrats.
Fig. 5 in Fig. 7 in Coexistence of Juvenile with Adult at Culebra Beach, Panama: A Temporal-spatial Partitioning Compromise.
Fig. 5. Burrow densities of the juvenile and adult Ocypode gaudichaudii in zones 1 to 3 of Culebra Beach during the night with respect to the high and low tide levels from 9 June to 29 November, 2012.
Fig. 4 in Fig. 7 in Coexistence of Juvenile with Adult at Culebra Beach, Panama: A Temporal-spatial Partitioning Compromise.
Fig. 4. Burrow densities of the juvenile and adult Ocypode gaudichaudii at zones 1 to 5 of Culebra Beach during the day with respect to the high and low tide levels from 9 June to 29 November, 2012.
Fig. 6 in Tolerance to Anhydrobiotic Conditions Among Two Coexisting Tardigrade Species Differing in Life Strategies.
Fig. 6. Relation of the measured activity indices to time spent in the tun stage in Milnesium inceptum: (A) time to first movement of any first individual (FM); (B) time to first movement of all individuals (FAA); (C) time to full activity of any first individual (FA); (D) time to full activity of all individuals (FAA). Curves were ± SE fitted with Local Polynomial Regression Fitting (LOESS).
Fig. 5 in Tolerance to Anhydrobiotic Conditions Among Two Coexisting Tardigrade Species Differing in Life Strategies.
Fig. 5. Relationship between the measured activity indices and time spent during the tun stage for Ramazzottius subanomalus: (A) time to first movement of any first individuals (FM); (B) time to first movement of all individuals (FAA); (C) time to full activity of any first individual (FA); (D) time to full activity of all individuals (FAA). Curves ± SE were fitted with Local Polynomial Regression Fitting (LOESS).
Fig. 3. A in Tolerance to Anhydrobiotic Conditions Among Two Coexisting Tardigrade Species Differing in Life Strategies.
Fig. 3. A time from the start of rehydration to the first movement (FM) of any first individual and all individuals (FMA) in the experimental groups representing increasing duration of the tun stage for Milnesium inceptum (A, C) and Ramazzottius subanomalus (B, D). The number of replicate samples for each group n = 10.
Fig. 4. A in Tolerance to Anhydrobiotic Conditions Among Two Coexisting Tardigrade Species Differing in Life Strategies.
Fig. 4. A time from the start of rehydration to the full activity (FA) of any first individual and all individuals (FAA) in the experimental groups representing increasing duration of the tun stage for Milnesium inceptum (A, C) and Ramazzottius subanomalus (B, D). The number of replicate samples for each group n = 10.
Fig. 2 in Tolerance to Anhydrobiotic Conditions Among Two Coexisting Tardigrade Species Differing in Life Strategies.
Fig. 2. Differences in the number of non-moving (NM) and not fully active (NFA) individuals between experimental groups representing increasing duration of the tun stage for Milnesium inceptum (A, C) and Ramazzottius subanomalus (B, D). The number of replicate samples for each group n = 10.
Text-fig. 3. CA climate charts for the Monte Tondo and Tossignano floras, showing climatic ranges of the Nearest Living Relatives of the fossil taxa with respect to MAT. Right-hand positoned large bold figures and shaded areas in each case indicate the Coexistence Interval, with the number of overlapping taxa being at a maximum. in Palaeoenvironmental Analysis Of The Messinian Macrofossil Floras Of Tossignano And Monte Tondo (Vena Del Gesso Basin, Romagna Apennines, Northern Italy)
Text-fig. 3. CA climate charts for the Monte Tondo and Tossignano floras, showing climatic ranges of the Nearest Living Relatives of the fossil taxa with respect to MAT. Right-hand positoned large bold figures and shaded areas in each case indicate the Coexistence Interval, with the number of overlapping taxa being at a maximum.
Figure 4 in Coexistence of Syrian Woodpecker Dendrocopos syriacus and Great Spotted Woodpecker Dendrocopos major in nonforest tree stands of the agricultural landscape in SE Poland
Figure 4. Frequency of the Syrian Woodpecker's (open dots and dashed line) and Great Spotted Woodpecker's (filled dots and continuous line) park occupancy depending on the area of the tree stand within the park.
ScienceDex guides
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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.