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102 results for “edaphism”

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dryad32/100

The contribution of the edaphic factor as a driver of recent plant diversification in a Mediterranean biodiversity hotspot

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publicOct 2020View details →
dryad32/100

Data from: Mycorrhizal symbiosis pathway and edaphic fertility frame root economics space among tree species

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publicAug 2022View details →
dryad32/100

Data from: Using digital soil maps to infer edaphic affinities of plant species in Amazonia: problems and prospects

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publicOct 2017View details →
dryad32/100

Data from: Edaphic factors determining the occurrence of herbaceous legumes in Amazonian savannas

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publicApr 2017View details →
dryad32/100

What defines insularity for plants in edaphic islands?

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publicMay 2021View details →
dryad28/100

Data from: Edaphic properties enable facilitative and competitive interactions resulting in fairy circle formation

Millions of generally regularly spaced, roughly circular barren patches called fairy circles occur in a narrow band ca. 100 km inland of the south-west African coast. These generally have conspicuously taller peripheral grasses in a shorter grass matrix. The origins of these fairy circles are controversial, but one possibility is that they are self-organizing emergent vegetation patterns that are the consequence of interplay between positive (facilitative) and negative (competitive) interactions between grasses. We hypothesized that the coarse textured sand on which fairy circles occur creates a hydraulically and nutritionally connected landscape, in which neighbouring fairy circles competitively influence each other over several metres, while providing opportunity for focusing of resources around the peripheral grasses. To test our hypotheses we conducted three main groups of analyses: 1) We measured grass biomass to assess facilitative and competitive effects of the component grasses; 2) Across a region with fairy circles we measured the size and density of fairy circles and correlated that with water infiltration rates into soil; 3) We measured the capacity of soil to conduct water pulses and 15N tracers. We found evidence of facilitative interactions in the periphery of the fairy circles and competitive suppression of the matrix grass proximal to the periphery. Across the region, fairy circle size was positively correlated with soil infiltration rates and negatively with precipitation. This suggests that fairy circles emerge in soils with high capacity for water flux that enables landscape hydraulic connectivity. Water- and 15N-pulse experiments showed that edaphic resources were highly mobile, moving up to 7.5 metres over a period of 1–3 weeks. We concluded that the evidence is consistent with an emergent vegetation pattern explanation for the origins of fairy circles and that the circles are more closely associated with a highly connective edaphic environment, rather than with particular biota.

opencc-zeroDec 2015View details →
zenodo28/100

FIGURE 23 in Geoparnus rhinoceros sp. nov., a new edaphic dryopid with unusual sexual dimorphism (Coleoptera: Dryopidae)

FIGURE 23. Known distribution of Geoparnus rhinoceros sp. nov. in Sarawak.

opennotspecifiedDec 2007View details →
zenodo28/100

FIGURE 1 in Geoparnus rhinoceros sp. nov., a new edaphic dryopid with unusual sexual dimorphism (Coleoptera: Dryopidae)

FIGURE 1. Habitus of Geoparnus rhinoceros sp. nov., male.

opennotspecifiedDec 2007View details →
zenodo28/100

FIGURES 1–2 in Confirmation of occurrence of Trechus Clairville, 1806 in the Baltic amber forests, with description of a flightless edaphic species, and remarks on Trechoides Motschulsky, 1856 (Coleoptera: Carabidae: Trechini)

FIGURES 1–2. Trechus balticus sp. n., holotype. Fig. 1, dorsal aspect. Fig. 2, ventral aspect.

opennotspecifiedDec 2015View details →
zenodo28/100

Data from: Data transformations cause altered edaphic-climatic controls and reduced predictability on soil carbon decomposition rates

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opencc-by-4.0Jun 2024View details →
zenodo28/100

Fig. 3 in Saproxylic weevils and edaphic beetles as indicators of environmental quality of relict forests in Piedmont lowlands (Coleoptera)

Fig. 3 – Scatter graph of study areas, relative to abundance data; × = sampling plots of Vaj (v), △ = sampling plots of Partecipanza (p), ○ = sampling plots of Merlino (m), + = sampling plots of Stupinigi (s).

opencc-by-4.0Dec 2022View details →
zenodo28/100

Figure 2 in Effects of soil core handling, transport and storage on numbers and body sizes of edaphic predatory mites (Gamasina)

Figure 2. Effects of improper core treatment on the body size distribution of predatory mites (Gamasida) extracted from soil samples. Numbers in panel heads are body sizes in micrometers [Mm]. See Fig. 1 for plot labels.

opencc-by-4.0Nov 2022View details →
zenodo28/100

Figure 1 in Effects of soil core handling, transport and storage on numbers and body sizes of edaphic predatory mites (Gamasina)

Figure 1. Effects of improper core treatment on the total abundance of predatory mites (Gamasida) extracted from soil. (A) storage duration, (B) storage temperature, (C) shaking intensity, (D) sample compression, (E) filling of sample containers in extraction apparatus, (F) combination of compression and prolonged storage, and (G) combination of shaking and prolonged storage.

opencc-by-4.0Nov 2022View details →
zenodo28/100

Linked collectors and determiners for: Taxonomic revision of the southern hemisphere pygmy forget-me-not group (Myosotis; Boraginaceae) based on morphological, population genetic and climate-edaphic niche modelling data.

Natural history specimen data linked to collectors and determiners held within, "Taxonomic revision of the southern hemisphere pygmy forget-me-not group (Myosotis; Boraginaceae) based on morphological, population genetic and climate-edaphic niche modelling data". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/32977d5c-8f02-4d26-8f75-ce56bf36f1fa">https://bionomia.net/dataset/32977d5c-8f02-4d26-8f75-ce56bf36f1fa</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/32977d5c-8f02-4d26-8f75-ce56bf36f1fa">https://gbif.org/dataset/32977d5c-8f02-4d26-8f75-ce56bf36f1fa</a>. Formatted as a Frictionless Data package.

opencc-zeroAug 2024View details →
dryad28/100

Data from: Habitat hotspots of common and rare tropical species along climatic and edaphic gradients

1. Understanding coexistence in high biodiversity ecosystems requires knowledge of how rare and common species share the multidimensional environmental space. Climatic and edaphic conditions can provide a plethora of habitats, supporting different compositional and structural communities where species can adapt and differentiate. 2. We used a large dataset consisting of 580 tropical tree species sampled in 163 25×25 m quadrats along an altitudinal gradient covering an area of 160 km2 of tropical rainforest in Jianfengling reserve (Hainan Island, China). For each plot the data include tree species and abundance, altitude and six soil properties from which a two dimensional environmental space was constructed. 3. With this extensive dataset we tested the hypothesis that different combination of environmental factors can generate multiple hotspots on three axes of diversity: species richness, Shannon-equivalent species richness and habitat preference, a measure of evenness in the distribution of individuals across an environmental gradient. 4. We found that humid and cool areas with more nitrogen availability were occupied by richer and more diverse communities of wide range species. Rare (in terms of number of individuals) and range restricted species instead, tended to prefer minor habitats, generally warmer with high potassium, calcium, magnesium and, in particular, phosphorous. As a result, wide and range restricted species were segregated across the environmental space. 5. Synthesis. Our findings indicate rare species tend to occur more frequently where common species are less abundant. A clear pattern of species richness and diversity was driven by a combination of several environmental factors (soil properties and climate). The complexity of the environment not only explains the different species distribution along each habitat, but also determines the relative abundance of each species in the entire community. Although some habitats have low species richness and diversity, they are highly preferred by rare species; therefore biodiversity conservation efforts should consider protecting these fragile ecosystems.

opencc-zeroDec 2014View details →
dryad28/100

High resolution distribution modelling of a threatened short-range endemic plant informed by edaphic factors.

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publicDec 2019View details →
dryad28/100

Data from: Habitat hotspots of common and rare tropical species along climatic and edaphic gradients

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publicJun 2015View details →
dryad28/100

Data from: Edaphic properties enable facilitative and competitive interactions resulting in fairy circle formation

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publicSep 2016View details →
dryad28/100

The contribution of multiple barriers to reproduction between edaphically divergent lineages in the Amazonian tree Protium subserratum (Burseraceae).

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publicOct 2019View details →
zenodo20/100

Conservation genomics and pollination biology of an endangered, edaphic-endemic, octoploid herb: El Dorado bedstraw (Galium californicum subsp. sierrae; Rubiaceae)

<p>Supplementary data.</p>

opencc-by-4.0Sep 2020View details →

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Allen Brain Atlas

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allen-brain-atlas
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Last verified 2026-04-30Open record

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behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
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DANDI Archive for NWB datasets

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dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

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Last verified 2026-04-29Open record

OpenNeuro

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neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record