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75 results for “ecological range”

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edi52/100

Demographic, seed ecology, and range wide survey datasets for Chrysopsis highlandsensis 1999-2022

Chrysopsis highlandsensis (Highlands Goldenaster; Asteraceae) is a state endangered herb found primarily within pyrogenic scrub communities in south-central Florida. These datasets span 24 yrs of demographic monitoring across ten populations, 7 seed ecology experiments, and a repeated range wide survey conducted every 5 yr from 2005-2020.

openCC (other)Sep 2025View details →
edi52/100

Map of ecological sites and ecological states for the USDA Jornada Experimental Range

This data package includes an ArcMap geodatabase: a polygon feature class, associated attribute table and metadata. The spatial data, JERStateMap_v1.gdb.zip, represents the ecological sites and states on the Jornada Experimental Range. The attribute table for the spatial data, JERStateMap.csv, and a summary of the spatial metadata, JERStateMapMetadata.pdf, are also included.

openCC (other)Feb 2023View details →
dryad40/100

Data from: Species distribution models of the Spotted Wing Drosophila (Drosophila suzukii, Diptera: Drosophilidae) in its native and invasive range reveal an ecological niche shift

<p>The Spotted Wing Drosophila (<em>Drosophila</em> <em>suzukii</em>) is native to Southeast Asia. Since its first detection in 2008 in Europe and North America, it has been a pest to the fruit production industry as it feeds and oviposits on ripening fruit. Here we aim to model the potential geographical distribution of <em>D. suzukii</em>. We performed an extensive literature review to map the current records. In total, 517 documented occurrences (96 native and 421 invasive) were identified spanning 52 countries. Next, we constructed three species distribution models (SDMs) based on occurrence records in: 1) the native range (SDMnative), 2) the invasive range in Europe (SDMEurope) and 3) a global model of all records (SDMglobal). The models aimed to investigate, whether this species will be able to occupy additional ecological niches beyond its native range and expand its current geographic distribution both globally and in Europe. The SDMs were generated using Maximum Entropy algorithms (Maxent) based on present occurrence records and bioclimatic variables (WorldClim). Predictions of habitat suitability vary greatly depending on the origins of occurrence records. According to all models, precipitation and low temperatures were key limiting factors for the distribution of <em>D. suzukii</em>, which suggests that this species requires a humid environment with mild winters in order to establish a permanent population in its invasive range. Several regions in the invasive range, not presently occupied by this species, were predicted highly suitable, especially in northern Europe, suggesting that <em>D. suzukii</em> is not occupying its full fundamental niche yet. Synthesis and applications. Based on these models of potential geographic distribution of the Spotted Wing Drosophila (<em>Drosophila</em> <em>suzukii</em>), we show a shift in the ecological niche in <em>D. suzukii</em> populations, emphasizing the importance of using presence and local environmental data. Further investigation regarding new occurrences is recommended to secure optimal pest management. Despite a continuing expansion, many countries still lack proper surveillance schemes, and we urge policymakers to initiate appropriate management programs.</p>

opencc-zeroDec 2017View details →
dryad40/100

Data from: Fluctuation of ecological niches and geographic range shifts along chile pepper's domestication gradient

<p>Domestication is an ongoing well-described process. However, while many have stud- ied the changes domestication causes in plant genetics, few have explored its impact on the portion of the geographic landscape in which the plants exist. Therefore, the goal of this study was to understand how the process of domestication changed the geographic space suitable for chile pepper (<em>Capsicum annuum</em>) in its center of origin (domestication). <em>C. annuum</em> is a major crop species globally whose center of domes- tication, Mexico, has been well-studied. It provides a unique opportunity to explore the degree to which ranges of different domestication classes diverged and how these ranges might be altered by climate change. To this end, we created ecological niche models for four domestication classes (wild, semiwild, landrace, modern cultivar) based on present climate and future climate scenarios for 2050, 2070, and 2090. Considering present environment, we found substantial overlap in the geographic niches of all the domestication classes. Yet, environmental and geographic aspects of the current ranges did vary among classes. Wild and commercial varieties could grow in desert conditions, while landraces could not. With projections into the future, habitat was lost asymmetrically, with wild, semiwild, and landraces at greater risk of territorial declines than modern cultivars. Further, we identified areas where future suitability overlap between landraces and wilds is expected to be lost. While range expansion is widely associated with domestication, we found little support of a con- stant niche expansion (either in environmental or geographical space) throughout the domestication gradient in chile peppers in Mexico. Instead, particular domestication transitions resulted in loss, followed by capturing or recapturing environmental or geographic space. The differences in environmental characterization among domes- tication gradient classes and their future potential range shifts increase the need for conservation efforts to preserve landraces and semiwild genotypes</p>

opencc-zeroDec 2023View details →
zenodo40/100

Fig. 1 in Uzbekistan - The Alleged Native Range Of The Invasive Ant Lasius Neglectus (Hymenoptera, Formicidae): Geographical, Ecological And Biological Evidences

Fig. 1. Collection sites of Lasius neglectus in Uzbekistan (1–20) and Tajikistan (21). Note: numbering of collection sites as in table 1; the bold line encircles the assumed native range of L. neglectus.

opencc-by-4.0May 2020View details →
zenodo40/100

Fig. 3 in A small parasitoid of fire ants, Pseudacteon obtusitus (Diptera: Phoridae): native range ecology and laboratory rearing

Fig. 3. Frequency distribution of Solenopsis invicta head size from which Pseudacteon obtusitus emerged, sorted by gender and sample yr. Insert: frequency distribution of Pseudacteon obtusitus thoraces sorted by gender and sample yr.

opencc-by-4.0Apr 2020View details →
zenodo40/100

Fig. 1 in A small parasitoid of fire ants, Pseudacteon obtusitus (Diptera: Phoridae): native range ecology and laboratory rearing

Fig. 1. Monthly phenology of Pseudacteon obtusitus across mo and yr at Corrientes Province, Argentina.

opencc-by-4.0Apr 2020View details →
zenodo40/100

Fig. 2 in A small parasitoid of fire ants, Pseudacteon obtusitus (Diptera: Phoridae): native range ecology and laboratory rearing

Fig. 2. Relative percent abundance of Pseudacteon obtusitus categorized by the time of d (morning until 12:00 P.M., 12:00 to 3:00 P.M., afer 3:00 P.M.) and sample mo (Apr, May, Jun, Sep, Oct, Nov, Jan).

opencc-by-4.0Apr 2020View details →
dryad40/100

Data from: The importance of biotic interactions in distribution models of wild bees depends on the type of ecological relations, spatial scale and range

<p>Studies have found that biotic information can play an important role in shaping the distribution of species even at large scales. However, results from species distribution models are not always consistent among studies, and the underlying factors that influence the importance of biotic information to distribution models, are unclear. 2. We studied wild bees and plants, and cleptoparasite bees and their hosts in the Netherlands to evaluate how the inclusion of their biotic interactions affects the performance of species distribution models. We assessed model performance through spatial block cross-validation and by comparing models with interactions to models where the interacting species were randomized. Finally, we evaluated how, (i) spatial resolution, (ii) taxonomic rank (genus or species), (iii) degree of specialization, (iv) distribution of the biotic factor, (v) bee body size and (vi) type of biotic interaction, affect the importance of biotic interactions in shaping the distribution of wild bee species using generalized linear models. 3. We found that the models of wild bees improved when the biotic factor was included. The model performance improved the most for parasitic bees. Spatial resolution, taxonomic rank, distribution range of the biotic factor, and degree of specialization of the modelled species all influenced the importance of the biotic interaction to the models. 4. We encourage researchers to include biotic interactions in species distribution models, especially for specialized species and when the biotic factor has a limited distribution range. However, before adding the biotic factor we suggest considering different spatial resolutions and taxonomic ranks of the biotic factor. We recommend using single species or genus data as a biotic factor in the models of specialist species and for the generalist species, we recommend using an approximate measure of interactions, such as flower richness.</p>

opencc-zeroJul 2024View details →
zenodo40/100

Fig. 6 in Feeding and reproductive ecology of Cichla piquiti Kullander & Ferreira, 2006 within its native range, Lajeado reservoir, rio Tocantins basin

Fig. 6. Temporal variation in body condition and fat storage for immature (a and c respectively) and adult fish (b and d respectively of Cichla piquiti). These figures show adjusted means ±SE derived from an Analysis of Covariance (see Table 4).

opencc-by-4.0Sep 2015View details →
zenodo40/100

Fig. 5 in Feeding and reproductive ecology of Cichla piquiti Kullander & Ferreira, 2006 within its native range, Lajeado reservoir, rio Tocantins basin

Fig. 5. Variation in reproductive effort of Cichla piquiti over time (mean ±SE), measured as the gonad-somatic index (GSI, %) calculated separately for males and females.

opencc-by-4.0Sep 2015View details →
zenodo40/100

Fig. 4 in Feeding and reproductive ecology of Cichla piquiti Kullander & Ferreira, 2006 within its native range, Lajeado reservoir, rio Tocantins basin

Fig. 4. Reproductive activity of Cichla piquiti, measured as the percentage of individuals in different reproductive phases within periods. Numbers above bars indicate sample size.

opencc-by-4.0Sep 2015View details →
zenodo40/100

Fig. 2 in Feeding and reproductive ecology of Cichla piquiti Kullander & Ferreira, 2006 within its native range, Lajeado reservoir, rio Tocantins basin

Fig. 2. Nonmetric multidimensional scaling (NMDS) applied to investigate variation in the diet of Cichla piquiti according to periods, sex (m = males; f = females) and maturity (I = immature; A = adult).

opencc-by-4.0Sep 2015View details →
zenodo40/100

Fig. 1 in Feeding and reproductive ecology of Cichla piquiti Kullander & Ferreira, 2006 within its native range, Lajeado reservoir, rio Tocantins basin

Fig. 1. Resource accumulation curves controlled by the number of stomachs of Cichla piquiti analyzed, considering all fish (a), sexes (b), maturity (c) and season (d). Sample size was reduced to 67 stomachs because this analysis considered only resources identified at some independent level, removing unidentified or combined items.

opencc-by-4.0Sep 2015View details →
zenodo40/100

Figs. 13–16 in Drasteria scolopax (Alphéraky, 1892) (Lepidoptera: Erebidae): New data on its range and ecology with description of a new subspecies

Figs. 13–16. Genitalia of Drasteria scolopax (Alphéraky, 1892): 13 — D. scolopax scolopax, lectotype, male, Gumansu; 14 — D. scolopax gilmanovi, paratype, male, Kaltabulak, 19.07.2023; 15 — D. scolopax scolopax, paralectotype, female, Gumansu; 16 — D. scolopax gilmanovi, holotype, female, Kaltabulak, 19.07.2023. Photos 14, 16 — by S. K. Korb, 13, 15 — by A. Yu. Matov Рис. 13–16. ГенитаΛии Drasteria scolopax (Alphéraky, 1892): 13 — D. scolopax scolopax, Λектотип, самец, Гумансу; 14 — D. scolopax gilmanovi, паратип, самец, КаΛтабуΛак, 19.07.2023; 15 — D. scolopax scolopax, параΛектотип, самка, Гумансу; 16 — D. scolopax gilmanovi, гоΛотип, самка, КаΛтабуΛак, 19.07.2023. Фото: 14, 16 — С. К. Корб, 13, 15 — А. Ю. Матов

opencc-by-4.0Dec 2023View details →
zenodo40/100

Figs. 1–12 in Drasteria scolopax (Alphéraky, 1892) (Lepidoptera: Erebidae): New data on its range and ecology with description of a new subspecies

Figs. 1–12. Drasteria scolopax (Alphéraky, 1892), habitus: 1–2 — D. scolopax gilmanovi, holotype, female, Kaltabulak, 19.07.2023; 3–4 — D. scolopax gilmanovi, paratype, female, Kaltabulak, 19.07.2023; 5–6 — D. scolopax gilmanovi, paratype, male, Kaltabulak, 19.07.2023; 7–9 — D. scolopax scolopax, lectotype, male, Gumansu; 10 — D. scolopax scolopax, paralectotype, female, Gumansu; 11–12 — D. scolopax scolopax, males, Altyntag. Photos 1–6 — by S. K. Korb, 7–12 — by A. Yu. Matov Рис. 1–12. Drasteria scolopax (Alphéraky, 1892), габитус: 1–2 — D. scolopax gilmanovi, гоΛотип, самка, КаΛтабуΛак, 19.07.2023; 3–4 — D. scolopax gilmanovi, паратип, самка, КаΛтабуΛак, 19.07.2023; 5–6 — D. scolopax gilmanovi, паратип, самец, КаΛтабуΛак, 19.07.2023; 7–9 — D. scolopax scolopax, Λектотип, самец, Гумансу; 10 — D. scolopax scolopax, параΛектотип, самка, Гумансу; 11–12 — D. scolopax scolopax, самцы, АΛтынтаг. Фотографии 1–6 — С. К. Корб; 7–12 — А. Ю. Матов

opencc-by-4.0Dec 2023View details →
zenodo40/100

Figs. 17–18 in Drasteria scolopax (Alphéraky, 1892) (Lepidoptera: Erebidae): New data on its range and ecology with description of a new subspecies

Figs. 17–18. Drasteria scolopax (Alphéraky, 1892), habitats: 17 — Transalai Mts., Kaltabulak stream; 18 — Alai Mts., Koksu River valley. Photos by P. Y. Gorbunov Рис. 17–18. Drasteria scolopax (Alphéraky, 1892), местообитания: 17 — ЗааΛайский хребет, ручей КаΛтабуΛак; 18 — АΛайский хребет, ΔоΛина реки Коксу. Фотографии П. Ю. Горбунова

opencc-by-4.0Dec 2023View details →
dryad40/100

Data from: Fluctuation of ecological niches and geographic range shifts along chile pepper's domestication gradient

Open the record for dataset details and reuse information.

publicDec 2023View details →
dryad40/100

Data from: The importance of biotic interactions in distribution models of wild bees depends on the type of ecological relations, spatial scale and range

Open the record for dataset details and reuse information.

publicJul 2024View details →
dryad40/100

Data from: Species distribution models of the Spotted Wing Drosophila (Drosophila suzukii, Diptera: Drosophilidae) in its native and invasive range reveal an ecological niche shift

Open the record for dataset details and reuse information.

publicOct 2018View details →

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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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

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