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Figure 3 in Seasonal Abundance of Economically Important Fruit Flies (Diptera: Tephritidae: Dacinae) in Bangladesh, in Relation to Abiotic Factors and Host Plants
Figure 3. Distribution and mean monthly trap captures of Bactrocera rubigina (A) and B. correcta (B), in relation with abiotic factors.
Figure 2 in Seasonal Abundance of Economically Important Fruit Flies (Diptera: Tephritidae: Dacinae) in Bangladesh, in Relation to Abiotic Factors and Host Plants
Figure 2. Distribution and mean monthly trap captures of Bactrocera dorsalis (A) and B. zonata (B), in relation with abiotic factors and host fruit availability.
Figure 1. A in Seasonal Abundance of Economically Important Fruit Flies (Diptera: Tephritidae: Dacinae) in Bangladesh, in Relation to Abiotic Factors and Host Plants
Figure 1. A: Fruit fly trapping sites maintained at the Atomic Energy Research Establishment compound in Bangladesh in 2016–2017 (sites 1 to 10) and 2017–2018 (sites 1, 8, 9). B: Mean monthly rainfall and minimum and maximum temperature recorded in Dhaka, Bangladesh, during the study period.
Figure 3 in Metagenomic study of the communities of bacterial endophytes in the desert plant Senna Italica and their role in abiotic stress resistance in the plant
Figure 3. Alfa rarefaction curve observed based on observed species (OTUs) value. The curve has shown flatter to the right, which indicates the comparatively high species richness of the senna italica samples. Roots samples: Roots.1, Roots.2, and Roots.3. Leaves samples: Leaves.1, Leaves.2, and Leaves.3 are associated with Senna italica.
Figure 1 in Metagenomic study of the communities of bacterial endophytes in the desert plant Senna Italica and their role in abiotic stress resistance in the plant
Figure 1. (A) Results of clustering: Assembling a group of organisms (The organisms in the same group are similar). (B) The number of OTUs generated for each sample. The Root.1 sample had the most OTUs of 24, while the Leave.1 sample had the fewest of 13. Roots samples: Roots.1, Roots.2, and Roots.3. Leaves samples: Leaves.1, Leaves.2, and Leaves.3 are associated with Senna italica.
Figure 6. A in Metagenomic study of the communities of bacterial endophytes in the desert plant Senna Italica and their role in abiotic stress resistance in the plant
Figure 6. A. The phylum level in Bacteria (bar chart), the bacterial composition of the different samples was similar, while the distribution of each phylum varied in all samples. Based on the V3-V4 region of the 16S rRNA region. Bacterial communities at the phylum classification among the samples (pie chart), as a percentage of the total bacteria isolated from roots and leaves endophyte region. Based on the full-length 16S rRNA sequences. (B) The number of Actinobacteria among the samples. (C) The number of Proteobacteria among the samples. (D) The number of unclassified phyla among the samples. (E) The number of Firmicutes phyla among the samples. (F) The number of Cyanobacteria/Chloroplast among the samples. Roots samples: Roots.1, Roots.2, and Roots.3. Leaves samples: Leaves.1, Leaves.2, and Leaves.3 are associated with Senna italica.
Figure 5 in Metagenomic study of the communities of bacterial endophytes in the desert plant Senna Italica and their role in abiotic stress resistance in the plant
Figure 5. Phylogenetic tree based on 16S rRNA gene sequences representing the diversity of endophytic bacterial communities associated with the leaves and roots from the desert medicinal plant Senna italica "at the Phylum level". The tree was constructed using the "one-click" mode in Phylogeny.fr.(Dereeper et al., 2008).
Figure 4 in Diurnal vertical distribution of zooplankton in a newly formed reservoir (Tahtalı Reservoir, Kocaeli): the role of abiotic factors and chlorophyll a
Figure 4. The vertical distribution of A) K. cochlearis, B) P. vulgaris, C) P. sulcata, D) total Rotifera, E) B. longirostris, F) total Cladocera, G) copepod nauplii, and H) total Copepoda, denoted by the time of sampling.
Fig. 3 in Gastrointestinal parasite infestation in the alpine mountain hare (Lepus timidus varronis): Are abiotic environmental factors such as elevation, temperature and precipitation affecting prevalence of parasite species?
Fig. 3. Parasite infestation in faeces and ambient temperature. Correlation between parasite infestation in Alpine mountain hare faeces (n = 52) and average, minimal, and maximal temperature found in Vorarlberg (Austria) during the years 2014 and 2015. Count visualises the number of faecal samples. See text for details on statistics.
Fig. 2 in Gastrointestinal parasite infestation in the alpine mountain hare (Lepus timidus varronis): Are abiotic environmental factors such as elevation, temperature and precipitation affecting prevalence of parasite species?
Fig. 2. Number of parasite types per faeces and severity of parasitic infestation. Correlation between number of parasite types per Alpine mountain hare faeces and severity of parasitic infestation (n = 28) found in Vorarlberg (Austria) during the years 2014 and 2015. Count visualises the number of faecal samples. The severity of infestation is indicated by scattered ((+)), low (+), intermediate (++), and high (+++) infestation. See text for details on statistics.
Fig. 2 in Biotic factors are more important than abiotic factors in regulating the abundance of Plutella xylostella L., in Southern Brazil
Fig. 2. Abundance of Plutella xylostella on broccoli (A) and cauliflower crops (B) in the county of Colombo, Paraná State, Southern Brazil.
Fig. 3 in Effect of vegetation and abiotic factors on the abundance and population structure of Crocodylus acutus (Cuvier, 1806) in coastal lagoons of Colima, Mexico
Fig. 3. Dendrogram considering the crocodiles observed, water salinity, temperature, depth, and the four vegetation types present. Acronym definitions and characteristics of the sites are given in Table 1.
Fig. 1 in Effect of vegetation and abiotic factors on the abundance and population structure of Crocodylus acutus (Cuvier, 1806) in coastal lagoons of Colima, Mexico
Fig. 1. Selected sites in the study area. Acronym definitions and characteristics of the sites are given in Table 1.
Fig. 2 in Effect of vegetation and abiotic factors on the abundance and population structure of Crocodylus acutus (Cuvier, 1806) in coastal lagoons of Colima, Mexico
Fig. 2. Non-metric Multidimensional Scaling (NMDS) analysis showing the formation of two groups, by taking into account the crocodiles observed, water salinity, temperature, depth, and the four vegetation types present. Acronym definitions and characteristics of the sites are given in Table 1.
Fig. 2 in Influence of biotic and abiotic factors on flea species population dynamics on Lasiopodomys brandtii
Fig. 2. Community structure of Lasiopodomys brandtii fleas by seasons. Three flea species were collected throughout the study meanwhile, Rhadinopsylla rothschildi was only detected in autumn. The top of each column indicates the number of samples for each season.
Fig. 6 in Fish larvae from the upper Paraná River: Do abiotic factors affect larval density?
Fig. 6. Conceptual model showing the relationships among abiotic factors, species larvae and areas (arrow directions on axis show increasing values of abiotic factors).
Fig. 3 in Fish larvae from the upper Paraná River: Do abiotic factors affect larval density?
Fig. 3. Mean scores (rectangles) and standard error (bars) (Axis 1=a and Axis 2=b of the Detrended Correspondence Analysis; DCA), derived from the larva density matrix for the different areas (AMA= Amambaí River, IVA= Ivaí River, PAR= Paraná River and RES= Itaipu Reservoir).
Abiotic controls on warm-water carbonates through geological times
<p>Evaluation of global carbonate distribution and accumulation over the past 265 Myr accounting for changes in paleogeography, plate tectonics, and paleo-climatic conditions.</p>
Effects of temporal abiotic drivers on the dynamics of an allometric trophic network model
<p>Current ecological research and ecosystem management call for improved understanding of the abiotic drivers of community dynamics, including temperature effects on species interactions and biomass accumulation. Allometric trophic network (ATN) models, which simulate material (carbon) transfer in trophic networks from producers to consumers based on mass-specific metabolic rates, provide an attractive framework to study consumer-resource interactions from organisms to ecosystems. However, the developed ATN models rarely consider temporal changes in some key abiotic drivers that affect e.g. consumer metabolism and producer growth. Here, we evaluate how temporal changes in carrying capacity and light-dependent growth rate of producers and in temperature-dependent mass-specific metabolic rate of consumers affect ATN model dynamics, namely seasonal biomass accumulation, productivity and standing stock biomass of different trophic guilds, including age-structured fish communities. Our simulations of the pelagic Lake Constance (LC) food web indicated marked effects of temporally changing abiotic parameters on seasonal biomass accumulation of different guild groups, particularly among the lowest trophic levels (primary producers and invertebrates). While the adjustment of average irradiance had a minor effect, increasing metabolic rate associated with 1–2˚C temperature increase led to a marked decline of larval (0-year age) fish biomass, but to a substantial biomass increase of 2- and 3-year-old fish that were not predated by ≥4-year-old top predator fish, European perch. However, when averaged across the 100 simulation years, the inclusion of seasonality in abiotic drivers caused only minor changes in standing stock biomasses and productivity of different trophic guilds. Our results demonstrate the potential of introducing seasonality in and adjusting the average values of abiotic ATN model parameters to simulate temporal fluctuations in food-web dynamics, which is an important step in ATN model development aiming to e.g. assess potential future community-level responses to ongoing environmental changes.</p>
The interplay between abiotic and biotic factors on dispersal decisions: evidence and implications for metacommunities
<p>Suitable conditions for species to survive and reproduce constitute their ecological niche, which is built by abiotic conditions and interactions with conspecifics and heterospecifics. Organisms should ideally assess and use information about all these environmental dimensions to adjust their dispersal decisions depending on their own internal conditions. Dispersal plasticity is often considered through its dependence to abiotic conditions or conspecifics density, and to a lesser extent with the effects of interactions with heterospecifics, potentially leading to misinterpretation of dispersal drivers. Here, we first review the evidence for effects of, and the potential interplays between abiotic factors, biotic interactions with conspecifics and heterospecifics, and phenotype on dispersal decisions. We then present an experimental test of these potential interplays, testing the effects of density and interactions with conspecifics and heterospecifics on temperature-dependent dispersal in microcosms of <i>Tetrahymena </i>ciliates. We found significant differences in dispersal rates depending on temperature, density, and presence of another strain or species. However, the presence and density of conspecifics and heterospecifics had no effects on the thermal-dependency of dispersal. We discuss the causes and consequences of the (lack of) interplay between the different environmental dimensions and the phenotype for metacommunity assembly and dynamics.</p>
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.