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942 results for “Scenarios”
Data from: Comparing the impact of future cropland expansion on global biodiversity and carbon storage across models and scenarios
<p>Land-use change is a direct driver of biodiversity and carbon storage loss. Projections of future land-use often include notable expansion of cropland areas in response to changes in climate and food demand, although there are large uncertainties in results between models and scenarios. This study examines these uncertainties by comparing three different socio-economic scenarios (SSP1-3) across three models (IMAGE, GLOBIOM and PLUMv2). It assesses the impacts on biodiversity metrics and direct carbon loss from biomass and soil as a direct consequence of cropland expansion. Results show substantial variation between models and scenarios, with little overlap across all nine projections. Although SSP1 projects the least impact, there are still significant impacts projected. IMAGE and GLOBIOM project the greatest impact across carbon storage and biodiversity metrics due to both extent and location of cropland expansion. Furthermore, for all the biodiversity and carbon metrics used, there is a greater proportion of variance explained by model used. This demonstrates the importance of improving the accuracy of land-based models. Incorporating effects of land-use change in biodiversity impact assessments would also help better prioritise future protection of biodiverse and carbon-rich areas.</p>
Data from: Manipulating wetland hydroperiod to improve occupancy rates by an endangered amphibian: modelling management scenarios
Environmental managers have the difficult task of ensuring species persistence despite considerable uncertainty about their response to management. Spatially explicit population models provide one solution for simulating the dynamics of species and evaluating alternative management regimes. We used a Bayesian model to investigate wetland occupancy dynamics of the endangered growling grass frog Litoria raniformis at a wastewater treatment plant in southern Victoria, Australia. We coupled prior information from earlier research on this species with our survey data to quantify the effects of patch-scale variables and connectivity on the probabilities of occupancy, population extinction and colonization. Hydroperiods of 13 sites were experimentally enhanced to bolster occupancy rates by L. raniformis. We used simulations to assess the extent to which the enhanced hydroperiod regime improved the viability of the focal metapopulation. Occupancy rate increased by 15% among the enhanced sites in 2013–2014, whereas the rate of occupancy among unenhanced sites fell by 11% in that year. Forward simulation using the dynamic occupancy model suggested that the minimum occupancy rate across the metapopulation would be 18% higher if the enhanced hydroperiod regime was retained over the next 20 years. Mean posterior effects of patch-scale variables and connectivity on the occupancy dynamics of L. raniformis were consistent with the prior effect in all cases, with only small changes to the size of these effects. There was no clear effect of water chemistry on occupancy dynamics. Synthesis and applications. This work suggests that managing the hydroperiod of constructed wetlands can be an effective tool for the conservation of amphibians and demonstrates the utility of spatially explicit models for assessing metapopulation viability. We encourage managers to experimentally test the efficacy of manipulating patch-scale variables to improve occupancy rates within amphibian metapopulations.
Data from: Predicted 2100 climate scenarios affects growth and skeletal development of tambaqui (Colossoma macropomum) larvae
Climate changes driven by greenhouse gas emissions have been occurring in an accelerated degree, affecting environmental dynamics and living beings. Among all affected biomes, the Amazon is particularly subjected to adverse impacts, such as temperature rises and water acidification. This study aimed to evaluate the impacts of predicted climate change on initial growth and development of an important Amazonian food fish, the tambaqui. We analyzed growth performance, and monitored the initial osteogenic process and the emergence of skeletal anomalies, when larvae were exposed to three climate change scenarios: mild (B1, increase of 1.8 °C, 200 ppm of CO2); moderate (A1B, 2.8 °C, 400 ppm of CO2); and drastic (A2, 3.4 °C, 850 ppm of CO2 ), in addition to a control room that simulated the current climatic conditions of a pristine tropical forest . The exposure to climate change scenarios (B1, A1B and A2) resulted in low survival, especially for the animals exposed to A2, (24.7 ± 1.0 %). Zootechnical performance under the B1 and A1B scenarios was higher when compared to current and A2, except for condition factor, which was higher in current (2.64 ± 0.09) and A1B (2.41 ± 0.14) scenarios. However, skeletal analysis revealed higher incidences of abnormalities in larvae exposed to A1B (34.82 %) and A2 (39.91 %) scenarios when compared to current (15.38 %). Furthermore, the bone-staining process revealed that after 16 days post-hatch (7.8 ± 0.01 mm total length), skeletal structures were still cartilaginous, showing no mineralization in all scenarios. We concluded that tambaqui larvae are well-adapted to high temperatures and may survive mild climate change . However, facing more severe climate conditions, its initial development may be compromised, resulting in high mortality rates and increased incidence of skeletal anomalies, giving evidence that global climate change will hamper tambaqui larvae growth and skeletal ontogeny.
Data from: Biogeographical scenarios modulate seagrass resistance to small-scale perturbations
1. Seagrasses constitute a key coastal habitat worldwide, but are are exposed to multiple perturbations. Understanding elements affecting seagrass resistance to disturbances is critical for conservation. Distinct biogeographical scenarios are intrinsically linked with varying ecological and evolution backgrounds shaped across millennia. 2. We addressed whether the resistance (change in shoot abundances) and performance (change in leaf morphology and growth) of the seagrass Cymodocea nodosa to a local stressor, light reduction, varied across three regions (Southeast Iberia, the Balearic Sea and the Canaries) within the temperate northern Atlantic realm. We hypothesized that distinct biogeographical scenarios, in terms of distinct ecological/environmental conditions and genetic diversity of meadows, would affect seagrass resistance and performance, with flow-on effects on associated epifauna. The same experiments, in terms of shading intensities, timing and duration, were replicated at three seagrass meadows within each region. 3. Results demonstrated inter-regional variation in the resistance and performance of C. nodosa. Under moderate and high shading, shoot abundance was abruptly decreased, relative to controls, in the Canaries with concurrent, but less accentuated, changes in leaf morphology and no changes in growth. In the other two regions, however, moderate and high shading had a negligible effect on shoot abundance, leaf morphology and growth. Shading had no overall effect over the total abundance and assemblage structure of epifauna; these faunal attributes, however, varied between regions. Low seagrass resistance at the Canaries is linked with the peripheral distribution of the species there, favoring isolation and decreased genetic diversity. 4. Synthesis. Different biogeographical scenarios shape seagrass resistance to local perturbations. From a conservation perspective, if resistance differs among biogeographical scenarios, universal conservation rules for seagrasses are challenging.
Heat Stress Exposure Maps - Base Scenario 1986 - 2005: Berlin, Germany (Map-1)
<p>Heat Stress Exposure Maps - Base Scenario 1986 - 2005: Berlin, Germany</p> <p>Map-1 (zip.file) ref. to DOI: 10.5281/zenodo.45015</p> <p> </p>
Cascadia FakeQuakes waveform data and scenario plots
<p>Supplementary data for the paper "Kinematic Rupture Scenarios and Synthetic Displacement Data: An Example Application to the Cascadia Subduction Zone<strong>" </strong>by D.Melgar, RJ Leveque, DS Dreger and RM Allen in the Journal of Geophysical Research. Cascadia.zip contains the waveforms, rupture descriptions and scenario plots. File formats are explained in fakequakes_readme.pdf</p>
FIGURE 1 in Conservation assessments in climate change scenarios: spatial perspectives for present and future in two Pristidactylus (Squamata: Leiosauridae) lizards from Argentina
FIGURE 1. General Niche-Environment System Factor Analysis (GNESFA) and Factor Analysis of the Niche, Taking the Environment as the Reference (FANTER) for Pristidactylus species. Left column: grey points show the distribution of the RUs (here the pixels) on the axes found by the analysis and black points correspond to the RUs used by the species. Right column: correlations between the environmental variables and the axes. References: P. achalensis A–B; P. nigroiugulus C–D.
FIGURE 5 in Conservation assessments in climate change scenarios: spatial perspectives for present and future in two Pristidactylus (Squamata: Leiosauridae) lizards from Argentina
FIGURE 5. Area models for suitability habitat from the averaged replications output for: P. achalensis, A) Present model = 5008.55 km², B) Model for 2050 RCP 45 = 4054.00 km², C) Model for 2050 RCP 85 = 2677.83 km²; P. nigroiugulus, 2) Present model = 71957.34 km², E) Model for 2050 RCP 45 = 56162.45 km², F) Model for 2050 RCP 85 = 38501.27 km². References: Country / province names, protected areas perimeters dashed-green lines, protected areas intersected with suitable areas filled in solid green, localities in red dots, and defined accessible area (M) in the upper left box.
FIGURE 4 in Conservation assessments in climate change scenarios: spatial perspectives for present and future in two Pristidactylus (Squamata: Leiosauridae) lizards from Argentina
FIGURE 4. True skill statistic (TSS) performed on the replicates for each species. References: mod, number of model replicate; values close to 1 indicates perfect agreement, values near zero indicates a performance no better than random.
FIGURE 3. RUs histograms for P in Conservation assessments in climate change scenarios: spatial perspectives for present and future in two Pristidactylus (Squamata: Leiosauridae) lizards from Argentina
FIGURE 3. RUs histograms for P. nigroiugulus. The white columns show the distributions of available RUs, whereas grey columns show the distributions of used RUs.
FIGURE 2. RUs histograms for P in Conservation assessments in climate change scenarios: spatial perspectives for present and future in two Pristidactylus (Squamata: Leiosauridae) lizards from Argentina
FIGURE 2. RUs histograms for P. achalensis. The white columns show the distributions of available RUs, whereas grey columns show the distributions of used RUs.
FIGURE 4 in A new species of Deltamys Thomas, 1917 (Rodentia: Cricetidae) endemic to the southern Brazilian Araucaria Forest and notes on the expanded phylogeographic scenario of D. kempi
FIGURE 4. Karyotype (conventional Giemsa staining) of Deltamys araucaria sp. n. showing 2n=34 and FNa=34. The small metacentric pair corresponds to pair 16.
FIGURE 8 in A new species of Deltamys Thomas, 1917 (Rodentia: Cricetidae) endemic to the southern Brazilian Araucaria Forest and notes on the expanded phylogeographic scenario of D. kempi
FIGURE 8. Dorsal (left), ventral (middle) and lateral (right) views of skull and labial view of mandible (bottom right) of Deltamys araucaria sp. n. (holotype, FURB 20296; above) and Deltamys kempi (AMNH 206139). Bar = 5 mm.
FIGURE 7 in A new species of Deltamys Thomas, 1917 (Rodentia: Cricetidae) endemic to the southern Brazilian Araucaria Forest and notes on the expanded phylogeographic scenario of D. kempi
FIGURE 7. Convex hull for specimen scores of Deltamys kempi (crosses) and Deltamys araucaria sp. n. (circles) on the principal components 1 and 2 (above) and 1 and 3 (below) extracted from the variance-covariance matrix of 21 cranial measurements.
FIGURE 3 in A new species of Deltamys Thomas, 1917 (Rodentia: Cricetidae) endemic to the southern Brazilian Araucaria Forest and notes on the expanded phylogeographic scenario of D. kempi
FIGURE 3. Haplotype network for Deltamys kempi obtained under the median-joining method. Population labels are given according to Table 1 (bold indicates haplotypes [H1-H10] found by Montes et al. [2008] in the same localities sampled in this study). The size of each circle is proportional to the haplotype frequency. Median vectors are represented by small black circles. All lines represent one mutational step. Clades represent major haplogroups (A and B) of D. kempi identified in the phylogenetic analysis.
FIGURE 2 in A new species of Deltamys Thomas, 1917 (Rodentia: Cricetidae) endemic to the southern Brazilian Araucaria Forest and notes on the expanded phylogeographic scenario of D. kempi
FIGURE 2. Maximum likelihood tree of Deltamys constructed based on cytochrome b complete sequences. Boostrap branch support is indicated by gradient of colors, accordingly to the legend. Numbers above branches represent the percentage of genetic divergence (p-distance) between clades. Bold indicate specimens of the new taxa described in this study.
FIGURE 1 in A new species of Deltamys Thomas, 1917 (Rodentia: Cricetidae) endemic to the southern Brazilian Araucaria Forest and notes on the expanded phylogeographic scenario of D. kempi
FIGURE 1. Distributional range of Deltamys in South America, showing the allopatry of lowland and highland populations. Collecting localities of Deltamys kempi are marked in yellow circles, Deltamys araucaria sp. n.. is indicated by the red triangle, and Deltamys sp. (2n=40) is indicated by the light-blue square. Numbers correspond to localities presented in Table 1.
FIGURE 6 in A new species of Deltamys Thomas, 1917 (Rodentia: Cricetidae) endemic to the southern Brazilian Araucaria Forest and notes on the expanded phylogeographic scenario of D. kempi
FIGURE 6. Morphological distinctive traits in Deltamys. Above, first upper molar of Deltamys araucaria sp. n. (FURB 20330; left) and D. kempi (TR 2136; right), showing the presence of protostyle (A) and enteroloph (B) in D. araucaria (bar = 0.5 mm; 30x). Middle, position of M1 anterior border in relation to posterior border of zygomatic plate in D. auraucaria sp. n. (left) and D. kempi (right) (bar=1 mm). Bottom, proportion of interparietal in D. araucaria (left) and D. kempi (right) (bar=2mm).
FIGURE 10. Scores for Deltamys kempi specimens from haplogroup A in A new species of Deltamys Thomas, 1917 (Rodentia: Cricetidae) endemic to the southern Brazilian Araucaria Forest and notes on the expanded phylogeographic scenario of D. kempi
FIGURE 10. Scores for Deltamys kempi specimens from haplogroup A (crosses) and B (circles) on the principal components 1 and 2 (above) and 1 and 3 (below) extracted from the variance-covariance matrix of 21 cranial measurements.
FIGURE 9 in A new species of Deltamys Thomas, 1917 (Rodentia: Cricetidae) endemic to the southern Brazilian Araucaria Forest and notes on the expanded phylogeographic scenario of D. kempi
FIGURE 9. Left maxillary molars (left) and right mandibular molars (right) of Deltamys araucaria sp. n. holotype (FURB 20296) (bar=1mm).
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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
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.