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21 results for “environmental pressures”
Greenhouse gas partial pressure (CO2, CH4, N2O) and environmental variables (physical, chemical, and biological) measured in urban ponds of Barcelona during summer and winter (2023-2024)
This dataset provides information on the partial pressure of greenhouse gases (CO₂, CH₄, and N₂O) measured in 41 artificial urban ponds—28 naturalized and 13 non-naturalized—using the headspace technique. Additionally, GPS coordinates, as well as physical, chemical, and biological variables for each pond, are included. Data were collected during the summer and winter seasons, during daytime. Furthermore, a subset of 16 ponds (8 naturalized and 8 non-naturalized) was also sampled at night in both seasons. All samples were taken from the water surface.
Data from: Unwrapping broken tails: Biological and environmental correlates of predation pressure in limbless reptiles
<p>Studying species interactions in nature often requires elaborate logistics and intense fieldwork. The difficulties in such task might hinder our ability to answer questions on how biotic interactions change with the environment. Fortunately, a workaround to this problem lies within scientific collections. For some animals, the inspection of preserved specimens can reveal the scars of past antagonistic encounters, such as predation attempts. A common defensive behaviour that leaves scars on animals is autotomy, the loss of a body appendage to escape predation. By knowing the collection site of preserved specimens, it is possible to assess the influence of organismal biology and the surrounding environment in the occurrence of autotomy. We produced data on tail loss for 8,189 preserved specimens of 33 snake and 11 amphisbaenian species to investigate biological and environmental correlates of autotomy in reptiles. We applied generalized linear mixed effect models to evaluate whether body size, sex, life-stage, habitat use, activity pattern, biome, tropicality, temperature, and precipitation affect the probability of tail loss in limbless reptiles. We observed autotomy in 23.6% of examined specimens, with 18.7% of amphisbaenian and 33.4% of snake specimens showing tail loss. Probability of tail loss did not differ between snakes and amphisbaenians, but it was higher among large-sized specimens, particularly in adults and females. Chance of tail loss was higher for diurnal and arboreal species, and among specimens collected in warmer regions, but it was unaffected by biome, precipitation, and tropicality. Autotomy in limbless reptiles was affected by size-dependent factors that interplay with ontogeny and sexual dimorphism, although size-independent effects of life-stage and sex also shaped behavioural responses to predators. The increase in probability of tail loss with verticality and diurnality suggests a risk-balance mechanism between species habitat use and activity pattern. Although autotomy is more likely in warmer regions, it seems unrelated to seasonal differences in snakes and amphisbaenians activity. Our findings reveal several processes related to predator-prey interactions involving limbless reptiles, demonstrating the importance of scientific collections to unveil ecological mechanisms at different spatio-temporal scales.</p>
Monsoon low-pressure system (LPS) tracks in ERA5 over India (1979-2019) with added environmental variables
<p>Derived from the LPS v3.0 dataset (https://doi.org/10.5281/zenodo.7568990). Filtered to monsoon LPSs (majority of track lifetime between June and September), with genesis over the Bay of Bengal and making landfall over India. Temporal resolution also reduced from hourly to six-hourly. This dataset accompanies the paper "Using interpretable gradient-boosted decision-tree ensembles to uncover novel dynamical relationships governing monsoon low-pressure systems" (DOI to follow).</p> <p>Aside from the core variables described in the main LPS dataset (linked above), this version includes a large number of environmental variables, listed below. All are computed from ERA5 unless otherwise stated, "<em>mean</em>" means that the variable is computed as an average within 400 km of the LPS centre, "<em>mcz</em>" means that the variable is computed as an average in the box [75-85°E, 18.5-27°N].<br> <em>mean_u200</em>: 200 hPa zonal wind (m s<sup>-1</sup>)<br> <em>mean_u850</em>: 850 hPa zonal wind (m s<sup>-1</sup>)<br> <em>mean_skt</em>: surface temperature (K)<br> <em>mean_land_frac</em>: fraction of area within 400 km that is over land<br> <em>mcz_tcwv</em>: mean total column water vapour over monsoon trough (kg m<sup>-2</sup>)<br> <em>vortex_depth</em>: mean_vort_500 x mean_vort_700/mean_vort_850<sup>2</sup><br> <em>over_land</em>: flag for LPS centre (Boolean)<br> <em>dvo850_dt</em>: rate of change of mean_vort_850 (10<sup>-5</sup> s<sup>-1</sup> day<sup>-1</sup>) <br> <em>acc_land_time</em>: accumulated time where over_land = True (hours)<br> <em>total_land_time</em>: final value of acc_land_time} for a given LPS (hours)<br> <em>qshear_850</em>: meridional shear of 850 hPa specific humidity over India (m<sup>3</sup> m<sup>-3</sup> (°)<sup>-1</sup>)<br> <em>ushear_850</em>: meridional shear of 850 hPa zonal wind over India (m s<sup>-1</sup> (°)<sup>-1</sup>)<br> <em>mean_cape</em>: CAPE (J kg<sup>-1</sup>)<br> <em>mcz_cape</em>: mean CAPE over the monsoon trough (J kg<sup>-1</sup>)<br> <em>mean_dthetae_dp_900_750</em>: d(theta_e)/dp between 900 and 750 hPa, a measurement of atmospheric stability (K hPa<sup>-1</sup>)<br> <em>mean_dthetae_dp_750_500</em>: d(theta_e)/dp between 750 and 500 hPa, a measurement of atmospheric stability (K hPa<sup>-1</sup>)<br> <em>mean_land_skt</em>: land surface temperature (K; NaN over ocean)<br> <em>mean_sst</em>: sea surface temperature (K; NaN over land)<br> <em>mean_swvl1</em>: soil moisture in the top layer (m<sup>3</sup> m<sup>-3</sup>; <7 cm; NaN over ocean)<br> <em>mean_swvl2</em>: soil moisture in the second layer (m<sup>3</sup> m<sup>-3</sup>; 7-28 cm; NaN over ocean)<br> <em>mean_swvl1_grad</em>: mean absolute horizontal gradient of mean_swvl1 (m<sup>3</sup> m<sup>-4</sup>)<br> <em>mean_swvl2_grad</em>: mean absolute horizontal gradient of mean_swvl2 (m<sup>3</sup> m<sup>-4</sup>)<br> <em>olr_90</em>: 90th percentile of negative OLR (i.e. ~90th percentile of cloud top height) (W m<sup>-2</sup>)<br> <em>olr_75</em>: 75th percentile of negative OLR (W m<sup>-2</sup>)<br> <em>olr_50</em>: 50th percentile of negative OLR (W m<sup>-2</sup>)<br> <em>qshear_850_background</em>: qshear\_850 averaged over the previous ten days (m<sup>3</sup> m<sup>-3</sup> (°)<sup>-1</sup>)<br> <em>ushear_850_background</em>: ushear\_850 averaged over the previous ten days (m<sup>3</sup> s<sup>-1</sup> (°)<sup>-1</sup>)<br> <em>mean_q_850</em>: 850 hPa specific humidity (m<sup>3</sup> m<sup>-3</sup>)<br> <em>orography_height</em>: elevation of land surface under LPS centre (m)<br> <em>peak_vorticity</em>: largest value of mean_vort_850} attained by a given LPS (10<sup>-5</sup> s<sup>-1</sup>)<br> <em>reached_peak</em>: False if peak\_vorticity has not been reached yet, else True<br> <em>mean_prcp_400</em>: mean precipitation rate within 400 km of the LPS centre over the next six hours (kg m<sup>-2</sup> s<sup>-1</sup>)<br> <em>mean_prcp_800</em>: mean precipitation rate within 800 km of the LPS centre over the next six hours (kg m<sup>-2</sup> s<sup>-1</sup>)<br> <em>max_prcp_400</em>: maximum precipitation rate within 400 km of the LPS centre over the next six hours (kg m<sup>-2</sup> s<sup>-1</sup>)<br> <em>max_prcp_800</em>: maximum precipitation rate within 800 km of the LPS centre over the next six hours (kg m<sup>-2</sup> s<sup>-1</sup>)<br> <em>mean_vimfd_400</em>: vertically integrated moisture flux convergence (kg m<sup>-2</sup> s<sup>-1</sup>)<br> <em>mean_v200</em>: 200 hPa meridional wind speed (m s<sup>-1</sup>)<br> <em>mean_v500</em>: 500 hPa meridional wind speed (m s<sup>-1</sup>)<br> <em>mean_v850</em>: 850 hPa meridional wind speed (m s<sup>-1</sup>)<br> <em>mean_u500</em>: 500 hPa zonal wind speed (m s<sup>-1</sup>)<br> <em>zonal_speed</em>: zonal (x) component of LPS propagation velocity (m s<sup>-1</sup>)<br> <em>merid_speed</em>: meridional (y) component of LPS propagation velocity (m s<sup>-1</sup>)<br> <em>mean_prcp_imerg</em>: as mean_prcp_400 but computed using IMERG data, rather than ERA5 (kg m<sup>-2</sup> hr<sup>-1</sup>)</p> <p> </p> <p>qshear_850, ushear_850 and their backgrounds are averaged over 5° longitude either side of the LPS centre, with the gradient computed between 10°N and 27°N, reflecting the moisture and zonal wind gradients across the monsoon region.</p>
Data from: Unwrapping broken tails: Biological and environmental correlates of predation pressure in limbless reptiles
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Geospatial dataset on human uses, environmental components and MSFD pressure for the Adriatic Sea
<p>Geospatial dataset on human uses, environmental components and MSFD pressure for the Adriatic Sea (reference year 2014-2015). The datasets are derived from ADRIPLAN Portal (http://data.adriplan.eu/) and is suitable for cumulative effects assessment (CEA), maritime use conflict (MUC) analysis and CEA-based marine ecosystem service threat analysis (MES-Threat).</p> <p> </p>
Data from: Biotic pressures and environmental heterogeneity shape beta-diversity of seedling communities in tropical montane forests
<p>Many theories have been proposed to explain the high diversity of plants in the tropics. However, we lack an understanding of the processes that drive plant diversity and community assembly at different spatial scales. Here, we applied beta-diversity partitioning to test how biotic and abiotic factors are associated with seedling beta-diversity in a tropical montane forest in Southern Ecuador. We recorded seedling communities on 81 subplots at nine plots located at three elevations along a 2000-m elevational gradient. We measured biotic pressures (i.e. herbivory and fungal pathogen attacks) and environmental conditions (i.e. soil moisture and canopy closure) at all subplots and related them to species turnover and richness differences in seedling communities within and between elevations. We found that species turnover increased with differences in biotic dissimilarity within elevations, while differences in species richness within elevations increased with increasing environmental dissimilarity. Between elevations, species turnover increased with increasing environmental dissimilarity. Our findings show that species turnover and changes in species richness are related differently to abiotic and biotic factors, and that the importance of these factors for shaping seedling diversity is scale-dependent. Our study contributes to better understand the processes driving seedling beta-diversity and the assembly of plant communities in highly diverse tropical montane forests.</p>
Data from: Biotic pressures and environmental heterogeneity shape beta-diversity of seedling communities in tropical montane forests
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Environmental DNA can act as a biodiversity barometer of anthropogenic pressures in coastal ecosystems
<p>Loss of biodiversity from lower to upper trophic levels reduces overall productivity and stability of coastal ecosystems in our oceans, but rarely are these changes documented across both time and space. The characterisation of environmental DNA (eDNA) from sediment and seawater using metabarcoding offers a powerful molecular lens to observe marine biota and provides a series of 'snapshots' across a broad spectrum of eukaryotic organisms. Using these next-generation tools and downstream analytical innovations including machine learning sequence assignment algorithms and co-occurrence network analyses, we examined how anthropogenic pressures may have impacted marine biodiversity on subtropical coral reefs in Okinawa, Japan. Based on 18S ribosomal RNA, but not ITS2 sequence data due to inconsistent amplification across samples, as well as proxies for anthropogenic disturbance, we show that eukaryotic richness at the family level significantly increases with medium and high levels of disturbance. This change in richness coincides with compositional changes, a decrease in connectedness among taxa, an increase in fragmentation of taxon co-occurrence networks, and a shift in indicator taxa. Taken together, these findings demonstrate the ability of eDNA to act as a barometer of disturbance and provide an exemplar of how ecological functions, biotic networks, and coral reef resilience may be impacted by anthropogenic activities.</p>
Data from: Regional environmental pressure influences population differentiation in turbot (Scophthalmus maximus)
Unravelling the factors shaping the genetic structure of mobile marine species is challenging due to the high potential for gene flow. However, genetic inference can be greatly enhanced by increasing the genomic, geographic or environmental resolution of population genetic studies. Here we investigated the population structure of turbot (Scophthalmus maximus) by screening 17 random and gene-linked markers in 999 individuals at 290 geographical locations throughout the Northeast Atlantic Ocean. A seascape genetics approach with the inclusion of high resolution oceanographic data was used to quantify the association of genetic variation with spatial, temporal and environmental parameters. Neutral loci identified three subgroups: an Atlantic group, a Baltic Sea group and one on the Irish Shelf. The inclusion of loci putatively under selection suggested an additional break in the North Sea, subdividing southern from northern Atlantic individuals. Environmental and spatial seascape variables correlated marginally with neutral genetic variation, but explained significant proportions (respectively 8.7 % and 10.3 %) of adaptive genetic variation. Environmental variables associated with outlier allele frequencies included salinity, temperature, bottom shear stress, dissolved oxygen concentration and depth of the pycnocline. Furthermore, levels of explained adaptive genetic variation differed markedly among basins (3% vs 12% in the North and Baltic Sea, respectively). We suggest that stable environmental selection pressure contributes to relatively strong local adaptation in the Baltic Sea. Our seascape genetic approach using a large number of sampling locations and associated oceanographic data proved useful for the identification of population units as the basis of management decisions.
Data from: Environmental perturbation, grazing pressure and soil wetness jointly drive mountain tundra toward divergent alternative states
1. Plant communities are structured by complex interactions between multiple factors, which veil our understanding of the effects of environmental changes on communities and ecosystems. Besides the relative role of biotic and abiotic factors as community-structuring processes, addressing how they jointly affect the ecological resilience and resistance of plant communities is crucial to understand better the long-term response of communities facing global changes. 2. Here, we used the results from a long-term (23 years) perturbation experiment set up in Fennoscandian mountain tundra to test these mechanisms. The experiment consisted of a transplantation of twenty blocks of Vaccinium myrtillus heath vegetation including upper soil layer from a lower elevation tundra heath habitat to a snowbed habitat 150 m higher in elevation where V. myrtillus lies at its upper limit. In the snowbed with contrasting levels of soil wetness, half of the transplanted blocks were protected from mammalian herbivores. 3. Our results revealed that in addition to the important role of environmental conditions as a structuring force, the joint effects of multiple drivers resulted in divergent patterns in both plant functional composition and species diversity among transplanted communities. Under environmental perturbation (i.e. transplantation to snowbed), the heath vegetation was altered by grazing pressure that reduced the cover of shrubs (especially V. myrtillus). In grazed dry snowbed, a species rich community with high functional type evenness and diversity developed. Reversely, in dry exclosures, V. myrtillus gained high dominance associated with only few graminoids and forbs. In wet snowbed conditions, shrubs tended to decline both in grazed plots and exclosures whereas bryophytes attained high abundance. Grazing promoted species richness while soil waterlogging tended to promote among-plot heterogeneity (β-diversity) which was highest in wet exclosures. 4. Synthesis Our long-term experiment reveals that environmental perturbation, grazing and soil wetness exhibit joint effects that induce divergent trajectories of tundra plant communities. We suggest that a strong environmental perturbation triggers mountain tundra heath community to move away from its equilibrium state. The outcome of this shift depends on the interplay between grazing pressure and soil wetness that drive tundra plant communities toward divergent alternative states.
Data from: Environmental perturbation, grazing pressure and soil wetness jointly drive mountain tundra toward divergent alternative states
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Data from: Regional environmental pressure influences population differentiation in turbot (Scophthalmus maximus)
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Data from: When Bergmann's rule fails: evidences of environmental selection pressures shaping phenotypic diversification in a widespread seabird
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Data from: Geometric morphometrics suggests different environmental pressures on small and large <em>Polygnathus</em> conodonts during the recovery after the Hangenberg crisis (latest Devonian-earliest Carboniferous)
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Environmental DNA can act as a biodiversity barometer of anthropogenic pressures in coastal ecosystems
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Environmental resistance strongly deters, but does not eliminate, propagule pressure
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Data from: Evolution of cross-resistance to medical triazoles in Aspergillus fumigatus through selection pressure of environmental fungicides
Resistance to medical triazoles in Aspergillus fumigatus is an emerging problem for patients at risk of aspergillus diseases. There are currently two presumed routes for medical triazole-resistance selection: (i) through selection pressure of medical triazoles when treating patients and (ii) through selection pressure from non-medical sterol-biosynthesis-inhibiting (SI) triazole fungicides which are used in the environment. Previous studies have suggested that SI fungicides can induce cross-resistance to medical triazoles. Therefore, to assess the potential of selection of resistance to medical triazoles in the environment, we assessed cross-resistance to three medical triazoles in lineages of A. fumigatus from previous work where we applied an experimental evolution approach with one of five different SI fungicides to select for resistance. In our evolved lines we found widespread cross-resistance indicating that resistance to medical triazoles rapidly arises through selection pressure of SI fungicides. All evolved lineages showed similar evolutionary dynamics to SI fungicides and medical triazoles, which suggests that the mutations inducing resistance to both SI fungicides and medical triazoles are likely to be the same. Whole-genome sequencing revealed that a variety of mutations were putatively involved in the resistance mechanism, some of which are in known target genes.
Data from: Evolution of cross-resistance to medical triazoles in Aspergillus fumigatus through selection pressure of environmental fungicides
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Evaluating Patient Comfort and Environmental Conditions in the Carecube Negative Pressure Isolation Chamber.1
ClinicalTrials.gov study NCT05468723. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Osteosarcoma tumors maintain intratumoral heterogeneity, even while adapting to environmental pressures that drive clonal selection
GEO Series GSE179681. Homo sapiens; Mus musculus. 22 samples. Type: Expression profiling by high throughput sequencing.
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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)
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DANDI Archive for NWB datasets
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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.