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860 results for “distribution ecology”
Seeing shapes in clouds: the fallacy of deriving ecological hypotheses from statistical distributions
<p>The explanations behind observations of global patterning in species diversity pre-date the field of ecology itself. The generation of new species-area theories, in particular, far outpaces their falsification, resulting in a centuries-old accumulation in species diversity theories. We use historical assessment and new data analysis to argue that one of the earliest recognized and most consistent patterns in species diversity is not strictly an ecological phenomenon and, when ecological mechanism is invoked, the range of potential mechanisms is too numerous for tractable hypothesis falsification. We provide a historical parallel in that the normal distribution once was treated as a pattern assuming a biological mechanism rather than a statistical distribution that can be generated by biological and non-biological forces. Similarly, power law distributions are ubiquitous in aggregated data, such as the species-area relationship. That nearly identical broad-scale aggregation patterns are observed for both ecological and non-ecological data as a function of area suggest that these broad-scale patterns reflect a statistical distribution that, in itself, cannot be used to discern between or among ecological and non-ecological mechanisms. We argue that by seeking processes in such a ubiquitous pattern, ecologists may read ecological mechanism into statistical patterns, and we suggest that falsifying broad-scale diversity distribution hypotheses should be a greater priority than generating or parameterizing new ones.</p>
The effects of habitat modification on the distribution and feeding ecology of Orthoptera 2015
<b>Description: </b><p>Postdoctoral project</p><p><b>Project: </b>This dataset was collected as part of the following SAFE research project: <a href="https://www.safeproject.net/projects/project_view/4"><b>The effects of habitat modification on the distribution and feeding ecology of Orthoptera</b></a></p><p><b>Funding: </b>These data were collected as part of research funded by: </p><ul><li>Australian Research Council (ARC Discovery Project, DP140101541)</li></ul><p>This dataset is released under the CC-BY 4.0 licence, requiring that you cite the dataset in any outputs, but has the additional condition that you acknowledge the contribution of these funders in any outputs.</p><p></p><p><b>XML metadata: </b>GEMINI compliant metadata for this dataset is available <a href="https://www.safeproject.net/datasets/xml_metadata?id=7011354">here</a></p><p><b>Files: </b>This consists of 1 file: Hardwick_Orthoptera_220811.xlsx</p><p><b>Hardwick_Orthoptera_220811.xlsx</b></p><p>This file contains dataset metadata and 1 data tables:</p><ol><li><p><b>Orthoptera assemblage composition data 2015</b> (described in worksheet OrthopteraAssem)</p><p>Description: Orthoptera assemblage composition data collected at the SAFE Project in 2015. Worksheet contains a site by morphospecies abundance matrix. Orthoptera were collected by sweep netting along a 100m transect at each location. Orthoptera were identified to family and seperated into morphospecies using identification guides. </p><p>Number of fields: 95</p><p>Number of data rows: 48</p><p>Fields: </p><ul><li><b>Date1</b>: Date of the first collection (Field type: date)</li><li><b>Date2</b>: Date of the second collection (Field type: date)</li><li><b>Location</b>: SAFE Project location (2nd order) (Field type: location)</li><li><b>Type</b>: Disturbance gradient (Field type: ordered categorical)</li><li><b>Collector</b>: First initial and last name of person who collected the sample (Field type: categorical)</li><li><b>ACRI01_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>ACRI02_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>ACRI03_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>ACRI04_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>ACRI05_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>ACRI06_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>ACRI07_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>ACRI08_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>ACRI09_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>ACRI10_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>ACRI11_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>ACRI12_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>ACRI13_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>ACRI14_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>ACRI15_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>ACRI16_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>ACRI17_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>ACRI18_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>ACRI19_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>ACRI20_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TETR01_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TETR02_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TETR03_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TETR04_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TETR05_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TETR06_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TETR07_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TETR08_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TETR09_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TETR10_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TETR11_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TETR12_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TETR13_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TETR14_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TETR15_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TETR16_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TETR17_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TETR18_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TETR19_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TETR20_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TETR21_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>GRYL01_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>GRYL02_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>GRYL03_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>GRYL04_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>GRYL05_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>GRYL06_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>GRYL07_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>GRYL08_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>GRYL09_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>GRYL10_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>GRYL11_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>GRYL12_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>GRYL13_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>GRYL14_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>GRYL15_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>GRYL16_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>GRYL17_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>GRYL18_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>GRYL19_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>GRYL20_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>GRYL21_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>MOGO01_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>MOGO02_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TRID01_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TRID02_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TRIG01_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TRIG02_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TRIG03_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TRIG04_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TRIG05_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TRIG06_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>UNID01_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>UNID02_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>UNID03_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>UNID04_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>UNID05_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>UNID06_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>UNID07_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>UNID08_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>UNID09_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>UNID10_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>UNID12_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>UNID13_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>UNID14_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>UNID15_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>UNID16_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>UNID17_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>UNID18_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>UNID19_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li></ul></li></ol><p><b>Date range: </b>2015-06-03 to 2015-08-14</p><p><b>Latitudinal extent: </b>4.6359 to 4.7509</p><p><b>Longitudinal extent: </b>116.9549 to 117.6257</p><p><b>Taxonomic coverage: </b><br> All taxon names are validated against the GBIF backbone taxonomy. If a dataset uses a synonym, the accepted usage is shown followed by the dataset usage in brackets. Taxa that cannot be validated, including new species and other unknown taxa, morphospecies, functional groups and taxonomic levels not used in the GBIF backbone are shown in square brackets.</p><div> -  Animalia <br> -  -  Arthropoda <br> -  -  -  Insecta <br> -  -  -  -  Orthoptera <br> -  -  -  -  -  [UNID01] <br> -  -  -  -  -  [UNID02] <br> -  -  -  -  -  [UNID03] <br> -  -  -  -  -  [UNID04] <br> -  -  -  -  -  [UNID05] <br> -  -  -  -  -  [UNID06] <br> -  -  -  -  -  [UNID07] <br> -  -  -  -  -  [UNID08] <br> -  -  -  -  -  [UNID09] <br> -  -  -  -  -  [UNID10] <br> -  -  -  -  -  [UNID12] <br> -  -  -  -  -  [UNID13] <br> -  -  -  -  -  [UNID14] <br> -  -  -  -  -  [UNID15] <br> -  -  -  -  -  [UNID16] <br> -  -  -  -  -  [UNID17] <br> -  -  -  -  -  [UNID18] <br> -  -  -  -  -  [UNID19] <br> -  -  -  -  -  Gryllidae <br> -  -  -  -  -  -  [GRYL01] <br> -  -  -  -  -  -  [GRYL02] <br> -  -  -  -  -  -  [GRYL03] <br> -  -  -  -  -  -  [GRYL04] <br> -  -  -  -  -  -  [GRYL05] <br> -  -  -  -  -  -  [GRYL06] <br> -  -  -  -  -  -  [GRYL07] <br> -  -  -  -  -  -  [GRYL08] <br> -  -  -  -  -  -  [GRYL09] <br> -  -  -  -  -  -  [GRYL10] <br> -  -  -  -  -  -  [GRYL11] <br> -  -  -  -  -  -  [GRYL12] <br> -  -  -  -  -  -  [GRYL13] <br> -  -  -  -  -  -  [GRYL14] <br> -  -  -  -  -  -  [GRYL15] <br> -  -  -  -  -  -  [GRYL16] <br> -  -  -  -  -  -  [GRYL17] <br> -  -  -  -  -  -  [GRYL18] <br> -  -  -  -  -  -  [GRYL19] <br> -  -  -  -  -  -  [GRYL20] <br> -  -  -  -  -  -  [GRYL21] <br> -  -  -  -  -  Acrididae <br> -  -  -  -  -  -  [ACRI01] <br> -  -  -  -  -  -  [ACRI02] <br> -  -  -  -  -  -  [ACRI03] <br> -  -  -  -  -  -  [ACRI04] <br> -  -  -  -  -  -  [ACRI05] <br> -  -  -  -  -  -  [ACRI06] <br> -  -  -  -  -  -  [ACRI07] <br> -  -  -  -  -  -  [ACRI08] <br> -  -  -  -  -  -  [ACRI09] <br> -  -  -  -  -  -  [ACRI10] <br> -  -  -  -  -  -  [ACRI11] <br> -  -  -  -  -  -  [ACRI12] <br> -  -  -  -  -  -  [ACRI13] <br> -  -  -  -  -  -  [ACRI14] <br> -  -  -  -  -  -  [ACRI15] <br> -  -  -  -  -  -  [ACRI16] <br> -  -  -  -  -  -  [ACRI17] <br> -  -  -  -  -  -  [ACRI18] <br> -  -  -  -  -  -  [ACRI19] <br> -  -  -  -  -  -  [ACRI20] <br> -  -  -  -  -  Tridactylidae <br> -  -  -  -  -  -  [TRID01] <br> -  -  -  -  -  -  [TRID02] <br> -  -  -  -  -  Trigonidiidae <br> -  -  -  -  -  -  [TRIG01] <br> -  -  -  -  -  -  [TRIG02] <br> -  -  -  -  -  -  [TRIG03] <br> -  -  -  -  -  -  [TRIG04] <br> -  -  -  -  -  -  [TRIG05] <br> -  -  -  -  -  -  [TRIG06] <br> -  -  -  -  -  Tetrigidae <br> -  -  -  -  -  -  [TETR03] <br> -  -  -  -  -  -  [TETR04] <br> -  -  -  -  -  -  [TETR05] <br> -  -  -  -  -  -  [TETR06] <br> -  -  -  -  -  -  [TETR07] <br> -  -  -  -  -  -  [TETR09] <br> -  -  -  -  -  -  [TETR10] <br> -  -  -  -  -  -  [TETR11] <br> -  -  -  -  -  -  [TETR12] <br> -  -  -  -  -  -  [TETR13] <br> -  -  -  -  -  -  [TETR14] <br> -  -  -  -  -  -  [TETR15] <br> -  -  -  -  -  -  [TETR16] <br> -  -  -  -  -  -  [TETR17] <br> -  -  -  -  -  -  [TETR18] <br> -  -  -  -  -  -  [TETR20] <br> -  -  -  -  -  -  [TETR21] <br> -  -  -  -  -  -  <i>Eucriotettix</i> <br> -  -  -  -  -  -  -  [TETR01] <br> -  -  -  -  -  -  <i>Cladonotella</i> <br> -  -  -  -  -  -  -  [TETR19] <br> -  -  -  -  -  -  <i>Boczkitettix</i> <br> -  -  -  -  -  -  -  <i>Boczkitettix borneensis</i> <br> -  -  -  -  -  -  <i>Paratettix</i> <br> -  -  -  -  -  -  -  <i>Paratettix variabilis</i> (as homotypic_synonym: <i>Euparatettix variabilis</i>)<br> -  -  -  -  -  Mogoplistidae <br> -  -  -  -  -  -  [MOGO01] <br> -  -  -  -  -  -  [MOGO02] <br></div><p></p>
Figure 5. d in Taxonomy, distribution, and ecology of crustacean zooplankton in trough waters of Ankara (Turkey)
Figure 5. d) trough used by goats (photo taken 25 June 2011).
Figure 5. b in Taxonomy, distribution, and ecology of crustacean zooplankton in trough waters of Ankara (Turkey)
Figure 5. b) trough made of carping oak tree (photo taken 27 June 2011).
Рис. 2. ЧисΛенность кабанов в разΛичные гоΔы на 10 км маршрута in The ecology and distribution of wild boars (Sus scrofa Linnaeus, 1758) in the foothills of the Martakert Region of the Republic of Artsakh
Рис. 2. ЧисΛенность кабанов в разΛичные гоΔы на 10 км маршрута
Рис. 1. Карта района иссΛеΔований: 1 — Тонашен; 2 — Варнкатаг; 3 — Магавуз in The ecology and distribution of wild boars (Sus scrofa Linnaeus, 1758) in the foothills of the Martakert Region of the Republic of Artsakh
Рис. 1. Карта района иссΛеΔований: 1 — Тонашен; 2 — Варнкатаг; 3 — Магавуз
Fig. 3 in On the distribution and ecology of a rare land snail, Eostrobilops coreana (Pilsbry, 1927) (Gastropoda: Pulmonata: Strobilopsidae)
Fig. 3. Relief of Peschany Peninsula. Photo by L.A. Prozorova, November 1, 2020.
Fig. 2 in The ecology and distribution of wild boars (Sus scrofa Linnaeus, 1758) in the foothills of the Martakert Region of the Republic of Artsakh
Fig. 2. The number of wild boars in different years in 10 km route
Prophage-DB: A comprehensive database to explore diversity, distribution, and ecology of prophages
<p><strong>Background:</strong></p> <p>Viruses that infect prokaryotes (phages) constitute the most abundant group of biological agents, playing pivotal roles in microbial systems. They are known to impact microbial community dynamics, microbial ecology, and evolution. Efforts to document the diversity, host range, infection dynamics, and effects of bacteriophage infection on host cell metabolism are still at the surface level. Among phages, some adopt the lysogenic mode of infection, where the genome integrates into the host cell genome, forming a prophage. Prophages enable viral genome replication without host cell lysis and often contribute novel and beneficial traits to the host genome. Despite their importance, research on prophages is limited. Current phage research predominantly focuses on lytic phages, leaving a significant gap in knowledge regarding prophages, including their biology, diversity, and ecological roles.</p> <p><strong>Results:</strong></p> <p>To bridge this gap, the creation of Prophage-DB, a prophage database, aims to address the limited knowledge of these crucial biological entities. To create the database, we identified lysogenic viruses from genomes in three publicly available databases. We applied several state-of-the-art tools in our pipeline to annotate these viruses, cluster them, taxonomically classify them, and detect their respective AMGs. With our approach, we identified over 350,000 prophages and 35,000 auxiliary metabolic genes.</p> <p><strong>Conclusion:</strong></p> <p>By summarizing the collected information we have created a database with extensive metadata regarding phage and host taxonomy, host information, and auxiliary metabolic genes. We identified numerous phages, from a wide variety of archaeal and bacterial hosts, which show a wide environmental distribution. In addition, the identified auxiliary metabolic genes will improve our understanding of them given the context of our study. We estimate this comprehensive prophage database will be a valuable resource for advancing prophage research, offering insights into viral taxonomy, host relationships, auxiliary metabolic genes, and environmental distribution. Its use promises to contribute towards understanding microbial ecosystems and unlocking the mysteries of microbial dark matter.</p>
Figure 2. High-altitude distribution P in Modern Distribution and Ecological-phytocenotic Features of Platanthera chlorantha (Cust.) Rchb. in the Republic of Adygea
Figure 2. High-altitude distribution P. chlorantha.
Figure 3. C in Ecological factors determining the distribution patterns of Cyrtanthus nutans R.A.Dyer (Amaryllidaceae) in northwestern KwaZulu-Natal, South Africa
Figure 3. C. nutans sites located within the Bioresource Groups.
Figure 2 in Ecological factors determining the distribution patterns of Cyrtanthus nutans R.A.Dyer (Amaryllidaceae) in northwestern KwaZulu-Natal, South Africa
Figure 2. Percentage of C. nutans plants per 100 m a.m.s.l. altitude range.
Figure 8 in New data on distribution and ecology of seven species of Euscorpius Thorell, 1876 (Scorpiones: Euscorpiidae)
Figure 8: E. sicanus collecting sites. Eastern Sardinia (Italy): 1. Genna Silana Pass; 2. Baunei.
Figure 2 in New data on distribution and ecology of seven species of Euscorpius Thorell, 1876 (Scorpiones: Euscorpiidae)
Figure 2: E. alpha forest habitat in Cislano (Lombardy, Italy) (photo by Marco Colombo).
Data from: Are drivers of microbial diatom distributions context dependent in human impacted and pristine environments? in Ecological Applicatios (2019)
<p>Species occurrence (0/1) and environmental data from research article "Are drivers of microbial diatom distributions context dependent in human impacted and pristine environments?" in Ecological Applications (2019). </p> <p>Please see more details in the readme-file and the original article. </p>
Datasets associated with: Comparing temperature data sources for use in species distribution models: From in-situ logging to remote sensing. Global Ecology and Biogeography
<p>Data associated with the paper 'Comparing temperature data sources for use in species distribution models: From in-situ logging to remote sensing. Global Ecology and Biogeography' by Lembrechts JJ et al., published in Global Ecology and Biogeography.</p> <p>Contains a dataset containing all extracted and measured temperature variables for all 106 measurement plots (climatedata), as well as the climate and species data used in the Species Distribution Models (SDMs). </p> <p>For details on the content of the table, see the readme-file, for details on methodology, see the original paper. </p>
Figure 1 in Preliminary study on distribution, diversity, and ecological characteristics of nonmarine Ostracoda (Crustacea) from the Erzincan region (Turkey)
Figure 1. Map illustrating the location of the 89 sampling sites randomly selected in Erzincan.
Figure 3 in Distribution and ecology of Ostracoda (Crustacea) from troughs in Turkey
Figure 3. UPGMA clustering groups of 21 species that occurred at least 2 times.
Figure 2 in First record of Rhyacophila pubescens Pictet, 1834 (Trichoptera: Rhyacophilidae) in the Republic of North Macedonia with notes on its ecology and distribution
Figure 2. Head of R. pubescens at dorsal (upper photos) and ventral (lower photos) view.
Figure 1. a in First record of Rhyacophila pubescens Pictet, 1834 (Trichoptera: Rhyacophilidae) in the Republic of North Macedonia with notes on its ecology and distribution
Figure 1. a) Map of the sampling locality; b) Photo of the sampling locality.
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.