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638 results for “biomes”
Linked collectors and determiners for: The spider genus Patrera Simon (Araneae: Dionycha, Anyphaeninae) in the Atlantic Forest biome, with the description of one new species from Brazil.
Natural history specimen data linked to collectors and determiners held within, "The spider genus Patrera Simon (Araneae: Dionycha, Anyphaeninae) in the Atlantic Forest biome, with the description of one new species from Brazil". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/f9dde51c-a2b9-4f3e-abe5-a7a3d7b0002d">https://bionomia.net/dataset/f9dde51c-a2b9-4f3e-abe5-a7a3d7b0002d</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/f9dde51c-a2b9-4f3e-abe5-a7a3d7b0002d">https://gbif.org/dataset/f9dde51c-a2b9-4f3e-abe5-a7a3d7b0002d</a>. Formatted as a Frictionless Data package.
Text-fig. 4. Known geographic distribution of Microtscoptini on a modern-day biome map (Arc-GIS feature TNC terrestrial ecoregions). 1 – Ertemte 1 and 2; 2 – Olan Chorea; 3 – Harr Obo 2; 4 – Shala; 5 – Baogeda Ula; 6 – Bilutu; 7 – Kholu (Southern Tuva); 8 – Sarayskoe (Olkhon Island); 9 – Hyargas-nuur; 10 – Petropavlovsk; 11 – Pavlodar; 12 – Akshauli; 13 – Selety 1A; 14 – Kedej 1A; 15 – Makovka; 16 – Cherevychne 3; 17 – Protopopovka 3; 18 – Verkhnya Krynytsa 2; 19 – Vasylivka 1; 20 – Lobkove; 21 – Rome; 22 – Bartlett Mountain; 23 – Bartlett Mountain (General); 24 – Juniper Creek; 25 – Little Valley; 26 – Stroud Claim; 27 – Kelley Road; 28 – Moonstone Formation; 29 – Lemoyne Quarry; 30 – Feltz Ranch; 31 – Cambridge; 32 – Rick Irwin Site; 33 – Rabbit Hole. 1–20, 30–32 – Steppe biomes, 21–29, 33 – xeric shrubland biomes. in Comments On The Age And Dispersal Of Microtoscoptini (Rodentia: Cricetidae)
Text-fig. 4. Known geographic distribution of Microtscoptini on a modern-day biome map (Arc-GIS feature TNC terrestrial ecoregions). 1 – Ertemte 1 and 2; 2 – Olan Chorea; 3 – Harr Obo 2; 4 – Shala; 5 – Baogeda Ula; 6 – Bilutu; 7 – Kholu (Southern Tuva); 8 – Sarayskoe (Olkhon Island); 9 – Hyargas-nuur; 10 – Petropavlovsk; 11 – Pavlodar; 12 – Akshauli; 13 – Selety 1A; 14 – Kedej 1A; 15 – Makovka; 16 – Cherevychne 3; 17 – Protopopovka 3; 18 – Verkhnya Krynytsa 2; 19 – Vasylivka 1; 20 – Lobkove; 21 – Rome; 22 – Bartlett Mountain; 23 – Bartlett Mountain (General); 24 – Juniper Creek; 25 – Little Valley; 26 – Stroud Claim; 27 – Kelley Road; 28 – Moonstone Formation; 29 – Lemoyne Quarry; 30 – Feltz Ranch; 31 – Cambridge; 32 – Rick Irwin Site; 33 – Rabbit Hole. 1–20, 30–32 – Steppe biomes, 21–29, 33 – xeric shrubland biomes.
Fig. 6 in Trophic structure of a fish community in Bananal stream subbasin in Brasília National Park, Cerrado biome (Brazilian Savanna), DF
Fig. 6. Proportion of autochthonous feeding items (black) and allochthonous (gray) with respect to the rainy (C) and dry (S) seasons for the fish species that presented this significant variation. Species abbreviations: Aspidoras fuscoguttatus (aspfus), Astyanax sp. (astsp), Characidium xanthopterum (chaxan), Hasemania sp. (hassp), Hyphessobrycon balbus (hypbal), Heptapterus sp. (hepsp), Knodus moenkhausii (knomoe), Kolpotocheirodon theloura (kolthe), Moenkhausia sp. (moesp), Phalloceros harpagos (phahar), Planaltina myersi (plamye), Rhamdia quelen (rhaque) and Rivulus pictus (rivpic)..
Fig. 1 in Trophic structure of a fish community in Bananal stream subbasin in Brasília National Park, Cerrado biome (Brazilian Savanna), DF
Fig. 1. Localization of the Brasília National Park in the Distrito Federal and distribution of sampling sites in the Bananal stream subbasin, Paranoá Lake basin, DF.
Fig. 5 in Trophic structure of a fish community in Bananal stream subbasin in Brasília National Park, Cerrado biome (Brazilian Savanna), DF
Fig. 5. Feeding items distributed according to the frequency of fish species occurrence (axis X) and relative abundance (axis Y), based upon the method proposed by Amundsen et al (1996): Moenkhausia sp., Phalloceros harpagos, Planaltina myersi, Rhamdia quelen and Rivulus pictus. The number of analyzed stomachs is shown in parentheses.
Fig. 4 in Trophic structure of a fish community in Bananal stream subbasin in Brasília National Park, Cerrado biome (Brazilian Savanna), DF
Fig. 4. Feeding items distributed according to the frequency of fish species occurrence (axis X) and relative abundance (axis Y), based upon the method proposed by Amundsen et al (1996): Aspidoras fuscoguttatus, Astyanax sp., Characidium xanthopterum, Hasemania sp., Hyphessobrycon balbus, Heptapterus sp., Knodus moenkhausii and Kolpotocheirodon theloura. The number of analyzed stomachs is shown in parentheses.
Fig. 2 in Trophic structure of a fish community in Bananal stream subbasin in Brasília National Park, Cerrado biome (Brazilian Savanna), DF
Fig. 2. General view of sites 1 to 7 sampled at the Bananal stream subbasin, Paranoá Lake basin, DF.
Fig. 3. Non-metric multidimensional scaling analysis for the 13 in Trophic structure of a fish community in Bananal stream subbasin in Brasília National Park, Cerrado biome (Brazilian Savanna), DF
Fig. 3. Non-metric multidimensional scaling analysis for the 13 more abundant fish species' diet found in the Bananal stream subbasin, Paranoá Lake basin, DF. Indication of four groups A, B, C and D. Species abbreviations: Aspidoras fuscoguttatus (aspfus), Astyanax sp. (astsp), Characidium xanthopterum (chaxan), Hasemania sp. (hassp), Hyphessobrycon balbus (hypbal), Heptapterus sp. (hepsp), Knodus moenkhausii (knomoe), Kolpotocheirodon theloura (kolthe), Moenkhausia sp. (moesp), Phalloceros harpagos (phahar), Planaltina myersi (plamye), Rhamdia quelen (rhaque) and Rivulus pictus (rivpic).
LT-Brazil: A database of leaf traits across biomes and vegetation types in Brazil
<p><span>Motivation: Leaf traits represent an important component of plant functional strategies, and those related to carbon fixation and nutrient acquisition form the leaf economics spectrum. However, observations of functional leaf traits are underrepresented in tropical regions in comparison with those in temperate areas. Brazil, a country with continental scale and vast biodiversity is a timely example, where many biomes are impacted by human activities and climate change. However, leaf traits relevant to understand vegetation responses to these impacts remain poorly quantified for many species found in the country. We compiled an extensive data set of four functional leaf traits for native woody species occurring in the Brazilian territory. In addition to trait observations, sampling dates and geo-references were compiled and climatic parameters and soil properties of each sampling site were extracted from several databases.</span></p> <p><span>Main types of variables contained: The LT-Brazil data set contains 3479, 1216, 775, and 775 clean observations of leaf mass per area, leaf nitrogen (N) concentration per unit mass, leaf phosphorus (P) concentration per unit mass, and leaf N : P ratio, respectively, from native woody species, encompassing information of biome, vegetation, taxonomic data, geographical coordinates, climatic parameters, as well as soil properties.</span></p> <p><span>Spatial location and grain: We compiled trait observations from 223 sites under native vegetation distributed in all main biomes (i.e., Amazônia, Caatinga, Cerrado, Mata Atlântica, Pampa, and Pantanal) across the Brazilian territory.</span></p> <p><span>Time period and grain: The data represent information published and/or sampled during the last 25 years.</span></p> <p><span>Major taxa and level of measurement: Our compilation was focused on trait data observed for native woody species, excluding monocots, palm trees, herbs, and hemiparasitic plants. Thus, 108, 478, and 1321 botanical families, genera, and species were included, covering <em>c.</em> 9% of the woody angiosperm flora of Brazil.</span></p> <p>Software format: Data are provided as comma-separated value (.csv) files.</p>
Data for: Changes in evapotranspiration, transpiration and evaporation across natural and managed landscapes in the Amazon, Cerrado and Pantanal biomes
<p>This dataset contains measurements of evapotranspiration and other meteorological variables (net radiation, air temperature, vapor pressure deficit, etc) from nine eddy covariance towers located in different ecosystems in the Amazon (natural Amazon forest, cropland and pastureland), Cerrado (natural savannah, irrigated and rainfed croplands) and Pantanal (natural forest, pastureland) biomes. It also contains estimates of transpiration that were calculated using two different approaches, the transpiration estimation algorithm (TEA) and the underlying water use efficiency method (uWUE).</p>
New indicators of ecological resilience and invasion resistance to support prioritization and management in the sagebrush biome, United States
<p>Ecosystem transformations to altered or novel ecological states are accelerating across the globe. Indicators of ecological resilience to disturbance and resistance to invasion can aid in assessing risks and prioritizing areas for conservation and restoration. The sagebrush biome encompasses parts of 11 western states and is experiencing rapid transformations due to human population growth, invasive species, altered disturbance regimes, and climate change. We built on prior use of static soil moisture and temperature regimes to develop new, ecologically relevant and climate-responsive indicators of both resilience and resistance. Our new indicators were based on climate and soil water availability variables derived from process-based ecohydrological models that allow predictions of future conditions. We asked: (1) Which variables best indicate resilience and resistance? (2) What are the relationships among the indicator variables and resilience and resistance categories? (3) How do patterns of resilience and resistance vary across the area? We assembled a large database (n = 24,045) of vegetation sample plots from regional monitoring programs and derived multiple climate and soil water availability variables for each plot from ecohydrological simulations. We used USDA Natural Resources Conservation Service National Soils Survey Information, Ecological Site Descriptions, and expert knowledge to develop and assign ecological types and resilience and resistance categories to each plot. We used random forest models to derive a set of 19 climate and water availability variables that best predicted resilience and resistance categories. Our models had relatively high multiclass accuracy (80% for resilience; 75% for resistance). Top indicator variables for both resilience and resistance included mean temperature, coldest month temperature, climatic water deficit, and summer and driest month precipitation. Variable relationships and patterns differed among ecoregions but reflected environmental gradients; low resilience and resistance were indicated by warm and dry conditions with high climatic water deficits, and moderately high to high resilience and resistance were characterized by cooler and moister conditions with low climatic water deficits. The new, ecologically-relevant indicators provide information on the vulnerability of resources and likely success of management actions and can be used to develop new approaches and tools for prioritizing areas for conservation and restoration actions.</p>
Meta-analysis shows forest soil CO2 effluxes are dependent on the disturbance regime and biome type
<p class="MsoNormal"><span>F</span><span>orest </span><span>s</span><span>oil CO<sub>2</sub> efflux (F</span><span>CO<sub>2</sub></span><span>)</span><span> is a crucial process in global carbon cycling; however, how F</span><span>CO<sub>2</sub></span><span> responds to disturbance regimes in different forest biomes is poorly understood. </span><span>W</span><span>e quantif</span><span>ied</span><span> the effects of disturbance regimes on F</span><span>CO<sub>2</sub></span><span> </span><span>across boreal, temperate, tropical, and</span><span> Mediterranean</span><span> forests</span><span> based on 1240 observations from 380 studies. Globally, climatic perturbations such as elevated CO<sub>2</sub> concentration, warming, and increased precipitation increase F</span><span>CO<sub>2</sub></span><span> </span><span>by 13 to 25%. F</span><span>CO<sub>2</sub></span><span> is increased by forest conversion to grassland and elevated carbon input by forest management practices but reduced by decreased carbon input, fire, and acid rain. Disturbance also changes soil temperature and water content, which in turn affect the direction and magnitude of disturbance influences on F</span><span>CO<sub>2</sub></span><span>. F</span><span>CO<sub>2</sub></span><span> is disturbance- and biome-type dependent, and such effects should be incorporated into earth system models to improve the projection of the feedback between the terrestrial C cycle and climate change.</span></p>
Supplementary Data for the publication "High economic costs of reduced carbon sinks and declining biome stability in Central American forests"
<p>Supplementary data from the DGVM simulations underlying the main figures presented in the publication.</p> <p>Naming convention: {variable}_{aggregation period}-{comparison period [only relevant for bsprob]}_{climate model}-{climate scenario}.tif</p> <p>Variables are:</p> <ul> <li>bsprob-Snell2013ed = biome shift probability (biomization adjusted from Snell et al. 2013) [%]</li> <li>nee = net ecosystem exchange [kgC/m2/year]</li> </ul> <p>Global climate models include GFDL = GFDL-ESM4 and IPSL= IPSL-CM6A-LR. Climate scenarios refer to the shared socioeconomic pathways (SSP) SSP126= SSP1-2.6 and SSP370= SSP3-7.0.</p>
Herbaceous vegetation responses to experimental fire in savannas and forests depend on biome and climate
<p>Fire-vegetation feedbacks potentially maintain global savanna and forest distributions. Accordingly, vegetation in savanna and forest ecosystems should have differential responses to fire, but fire response data for herbaceous vegetation has yet to be synthesized across biomes. Here, we examined herbaceous vegetation responses to experimental fire at 30 sites spanning four continents. Across a variety of metrics, herbaceous vegetation increased in abundance where fire was applied, with larger responses to fire in wetter and in cooler and/or less seasonal systems. Compared to forests, savannas were associated with a 4.8 (±0.4) times larger difference in burned versus unburned herbaceous vegetation abundance. In particular, grass cover decreased with fire exclusion in savannas, largely via decreases in C<sub>4</sub> grass cover, whereas changes in fire frequency had a relatively weak effect on grass cover in forests. These differential responses underscore the importance of fire for maintaining the vegetation structure of savannas and forests.</p>
Temperature affects the timing and duration of fungal fruiting patterns across major terrestrial biomes
<p><span>The Earth's ecosystems are affected by a complex interplay of biotic and abiotic factors. While global temperatures increase, associated changes in the fruiting behaviour of fungi remain unknown. Here we analyse 6.1 million fungal fruit body (mushroom) records and show that the major terrestrial biomes exhibit similarities and differences in fruiting events. We observed one main fruiting peak for most years in all biomes. However, in boreal and temperate biomes years with a second peak were prevalent indicating spring and autumn fruiting. Distinct fruiting peaks are spatially synchronized in boreal and temperate biomes, but less defined and longer in the humid tropics. The timing and duration of fungal fruiting are significantly related to temperature mean and variability. Temperature-dependent aboveground fungal fruiting behaviour, which is arguably also representative of belowground processes, suggests that the observed biome-specific differences in fungal phenology will change in space and time when global temperatures continue to increase.</span></p>
Figure 7 in Phylogenetic biome conservatism as a key concept for an integrative understanding of evolutionary history: Galliformes and Falconiformes as study cases
Figure 7. Biome transitions in Falconiformes. The number of recent species is indicated inside the circles. Arrow thickness is proportional to the number of colonizations. The dashed lines indicate only one colonization event. The number of transitions that did not imply colonization (niche conservatism) is indicated as different areas of the circles, classified in four categories. For more details about absolute scores, see Table 3.
Figure 5 in Phylogenetic biome conservatism as a key concept for an integrative understanding of evolutionary history: Galliformes and Falconiformes as study cases
Figure 5. Ancestral biome reconstruction for Falconiformes. Coloured circles represent the ten different biomes implemented in the model (Walter, 1970; Hernández Fernández, 2001); those at the nodes represent the inferred ancestral biome(s); those at the tips correspond to the recent biome distribution of species. Along the time scale, geological and climatic histories are shown, in addition to intercontinental biotic interchanges. Abbreviations: Af, Africa; Au, Australia; EAs, Eurasia; LB, land bridge; NA, North America; SA, South America.
Figure 6 in Phylogenetic biome conservatism as a key concept for an integrative understanding of evolutionary history: Galliformes and Falconiformes as study cases
Figure 6. Colonization dynamics of Falconiformes. Each graph represents the rate of colonization by new lineages for each biome throughout the Cenozoic.
Figure 4 in Phylogenetic biome conservatism as a key concept for an integrative understanding of evolutionary history: Galliformes and Falconiformes as study cases
Figure 4. Biome transitions in Galliformes. The number of recent species is indicated inside the circles. Arrow thickness is proportional to the number of colonizations. The dashed lines indicate only one colonization event. The number of transitions that did not imply colonization (niche conservatism) is indicated as different areas of the circles, classified in five categories. For more details about absolute scores, see Table 2.
Figure 2 in Phylogenetic biome conservatism as a key concept for an integrative understanding of evolutionary history: Galliformes and Falconiformes as study cases
Figure 2. Ancestral biome reconstruction for Galliformes. Coloured circles represent the ten different biomes implemented in the model (Walter, 1970; Hernández Fernández, 2001); those at the nodes represent the inferred ancestral biome(s) occupancy; those at the tips correspond to the recent biome distribution of species. Along the time scale, geological and climatic histories are shown, in addition to intercontinental biotic interchanges. Abbreviations: Af, Africa; Au, Australia; EAs, Eurasia; LB, land bridge; NA, North America; SA, South America.
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.