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FIGURE 4 in Short-term response of fish assemblages to instream habitat restoration in heavily impacted streams
FIGURE 4 | Changes in environmental parameters (mean ± sd) depth, flow and structural diversity in pre and post-restoration conditions. C= Control treatment, W= Wood treatment, WL= Wood/leaf treatment, *= p-values <0,05.
FIGURE 4 in Fish biomarker responses to perturbation by drought in streams
FIGURE 4 | Two-dimensional Non-Metric Multidimensional Scaling (NMDS) ordination showing biomarker responses of fish from intermittent and perennial streams in the dry (D) and rainy (R) seasons. The stress value of 0.12 indicates a good representation of the original data (Clarke, Warwick, 2001).
FIGURE 1 in Fish biomarker responses to perturbation by drought in streams
FIGURE 1 | Location of the Intermittent (yellow circle) and Perennial (blue circle) stream in the Montividiu drainage in the Brazilian Cerrado (yellow in the smaller map).
FIGURE 1 in Short-term response of fish assemblages to instream habitat restoration in heavily impacted streams
FIGURE 1 | Map of the study area, highlighting the state of São Paulo and the location of the streams within the watersheds: Tietê River (streams P1, P2, P6 and P7), São José dos Dourados River (P3 and P4), and Turvo River (P5 and P8).
Fig. 6 in Integrated biomarker response index using a Neotropical fish to assess the water quality in agricultural areas
Fig. 6. DNA damage scores (mean ± SEM, n = 8) in erythrocytes of A. altiparanae exposed in situ for seven days in five sites along Água das Araras stream (S1, S2, S3, S4, and S5) and in a reference site (Ref). Different letters indicate significant differences between sites (P <0.05).
Fig. 2 in Integrated biomarker response index using a Neotropical fish to assess the water quality in agricultural areas
Fig. 2. Activity (mean ± SEM, n = 8) of glutathione S-transferase in liver (A) and gills (B) of A. altiparanae exposed in situ for seven days in five sites along Água das Araras stream (S1, S2, S3, S4, and S5) and in a reference site (Ref). Different letters indicate significant differences between sites (P <0.05).
Fig. 3 in Integrated biomarker response index using a Neotropical fish to assess the water quality in agricultural areas
Fig. 3. Activity (mean ± SEM, n = 8) of catalase in liver (A) and gills (B) of A. altiparanae exposed in situ for seven days in five sites along Água das Araras stream (S1, S2, S3, S4, and S5) and in a reference site (Ref). Different letters indicate significant differences between sites (P <0.05).
Fig. 4 in Integrated biomarker response index using a Neotropical fish to assess the water quality in agricultural areas
Fig. 4. Content (mean ± SEM, n = 8) of glutathione in liver (A) and gills (B) of A. altiparanae exposed in situ for seven days in five sites along Água das Araras stream (S1, S2, S3, S4, and S5) and in a reference site (Ref). Different letters indicate significant differences between sites (P<0.05).
Fig. 3 in Effect of beta 1,3 glucan in stress responses of the pencilfish (Nannostomus trifasciatus) during transport within the rio Negro basin
Fig. 3. Whole-body cortisol levels (mean ± SD) during transportation of pencilfish (Nannostomus trifasciatus) previously fed with different levels of beta 1,3 glucan. No significant differences between all sampling times using the Kruskal-Wallis ANOVA on ranks were observed (P>0.05).0: initial time of transport; 24: 24 hours of transport; 24 AT: 24 hours after transport (recovery time).
Fig. 2 in Effect of beta 1,3 glucan in stress responses of the pencilfish (Nannostomus trifasciatus) during transport within the rio Negro basin
Fig. 2. Net Na+ (A) and K+ (B) fluxes during transportation of pencilfish (Nannostomus trifasciatus) previously fed with different levels of beta 1,3glucan. Positive values indicate net influxes and negative values net effluxes. N = 4 boxes per treatment in each sample time. Different lower case letters indicate significant difference among times of transport within the same group and * indicate significant difference from control group within the same time of transport by Scheirer-Ray-Hare extension of the Kruskal-Wallis test followed by the Nemenyi test (P<0.05).
Figure 4 in Diatom responses to river water quality in the Kruger National Park, South Africa
Figure 4. The relationship between SPI and two physicochemical water quality parameters. Open symbols represent rivers with large catchments outside the KNP. Closed represent rivers with relatively small parts of their catchments outside the KNP. In both cases, the dark- er the symbol, the larger the catchment.
Figure 3 in Diatom responses to river water quality in the Kruger National Park, South Africa
Figure 3. Two-dimension MDS plot of diatom community composition in 1983 and 2015 at different sites along the Olifants (OM and OC), Letaba (LC and LK) and Sabie rivers (SL and SB). Note that all sites' diatom composition shifted significantly from 1983 to 2015 irrespective of whether the index values changed or not (see Table 4). Sample site abbreviations also in Table 4.
Figure 2 in Diatom responses to river water quality in the Kruger National Park, South Africa
Figure 2. Long-term changes in two selected river chemical parameters in the Olifants, Letaba and Sabie rivers between 1983 and 2015. The closed symbols represent data extracted from the Department of Water Affairs and Sanitation. Open symbols represent the values recorded at sites within the three focal rivers during the present study in 2015.
Figure 3 in Response and tolerance mechanism of food crops under high temperature stress: a review
Figure 3. Process of development of heat-resistant cultivars. Identify heat-resistant genes from natural genetic resources through genome wide association mapping and then study the study how these genes are operated. Select those genes which are associated with various signaling pathways and then transform them into current germplasm.
Figure 1 in Response and tolerance mechanism of food crops under high temperature stress: a review
Figure 1. Schematic representation of most sensitive phase of various crops during high temperature stress.
Figure 1. A in Diatom responses to river water quality in the Kruger National Park, South Africa
Figure 1. A map of the Kruger National Park, showing the location of the study area and diatom sampling sites.
Figure 2 in Response of Rhizobacterial strains and organic amendments on chickpea growth
Figure 2. Soil organic matter as affected by Rhizobacterial strains. T: control. T: Enterobactor asburiae. T: Enterobacter mori. T: 1 2 3 4 rhizobiu ceceri. T5: Pesodomonas aeruginosa. T6: Pesodomonas putida.
Figure 1 in Response of Rhizobacterial strains and organic amendments on chickpea growth
Figure 1. Soil Nitrogen as affected by Rhizobacterial strains. T 1: control. T 2: Enterobactor asburiae. T 3: Enterobacter mori. T 4: rhizobiu ceceri. T 5: Pesodomonas aeruginosa. T: Pesodomonas putida.
Data from: Integrating genomic data and simulations to evaluate alternative species distribution models and improve predictions of glacial refugia and future responses to climate change
<p>Climate change poses a threat to biodiversity, and it is unclear whether species can adapt to or tolerate new conditions, or migrate to areas with suitable habitats. Reconstructions of range shifts that occurred in response to environmental changes since the last glacial maximum from species distribution models (SDMs) can provide useful data to inform conservation efforts. However, different SDM algorithms and climate reconstructions often produce contrasting patterns, and validation methods typically focus on accuracy in recreating current distributions, limiting their relevance for assessing predictions to the past or future. We modeled historically suitable habitat for the threatened North American tree green ash (<em>Fraxinus pennsylvanica</em>) using 24 SDMs built using two climate models, three calibration regions, and four modeling algorithms. We evaluated the SDMs using contemporary data with spatial block cross-validation and compared the relative support for alternative models using a novel integrative method based on coupled demographic-genetic simulations. We simulated genomic datasets using habitat suitability of each of the 24 SDMs in a spatially-explicit model. Approximate Bayesian Computation (ABC) was then used to evaluate the support for alternative SDMs through comparisons to an empirical population genomic dataset. Models had very similar performance when assessed with contemporary occurrences using spatial cross-validation, but ABC model selection analyses consistently supported SDMs based on the CCSM climate model, an intermediate calibration extent, and the generalized linear modeling algorithm. Finally, we projected the future range of green ash under four climate change scenarios. Future projections using the SDMs selected via ABC suggest only minor shifts in suitable habitat for this species, while some of those that were rejected predicted dramatic changes. Our results highlight the different inferences that may result from the application of alternative distribution modeling algorithms and provide a novel approach for selecting among a set of competing SDMs with independent data.</p>
Fig. 5 in Expression profile of two HSP70 chaperone proteins in response to extreme thermal acclimation in Xestia c-nigrum (Lepidoptera: Noctuidae)
Fig. 5. Xc-HSC70 mRNA expression profiles induced by cold (−7 to 5 °C) and heat (37 to 47 °C) in 2nd, 3rd, 4th, 5th, and 6th instars and pupae of Xestia cnigrum. The relative quantities indicate the levels of the HSC70 gene transcript normalized against transcript levels of β-actin as an internal standard and compared with the transcript levels of the untreated control at 25 °C. An asterisk indicates a significant difference between the control and heat shock conditions (significant, * P <0.05). The data are denoted as the mean ± SEM (error bar).
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.