Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
233
datasets available to search
ShareScore release 0.9.0
Dataset results
233 results for “seasonal dynamics”
Data from: Predicting the evolutionary dynamics of seasonal adaptation to novel climates in Arabidopsis thaliana
Anticipating the effect of climate change on plants requires understanding its evolutionary consequence on traits and genes in complex realistic environments. How seasonal variation has an impact on the dynamics of adaptation in natural populations remains unclear. We simulated adaptation to different climate change scenarios, grounding our analysis in experimental data and explicitly exploring seasonal variation. Seasonal variation dramatically affected the dynamics of adaptation: Marked seasonality led to genetic differentiation within the population to different seasonal periods, whereas low seasonality led to a single population with fast-evolving fitness. Our results suggest the prevalence of phenotypic plasticity across environmental conditions in determining how climate change will shift selection on traits and loci. In this unpredictable context, maintaining broad genomic diversity is critical.
Figure 3. Chlorophyll-a in First observation and seasonal dynamics of the new invasive planktonic copepod Oithona davisae Ferrari and Orsi, 1984 along the southern Black Sea (Anatolian Coast)
Figure 3. Chlorophyll-a distributions during the sampling period.
Figure 2 in First observation and seasonal dynamics of the new invasive planktonic copepod Oithona davisae Ferrari and Orsi, 1984 along the southern Black Sea (Anatolian Coast)
Figure 2. The average monthly sea surface temperature in 2007 and 2015 (°C).
Figure 3. Chlorophyll-a in First observation and seasonal dynamics of the new invasive planktonic copepod Oithona davisae Ferrari and Orsi, 1984 along the southern Black Sea (Anatolian Coast)
Figure 3. Chlorophyll-a distributions during the sampling period.
Figure 2 in First observation and seasonal dynamics of the new invasive planktonic copepod Oithona davisae Ferrari and Orsi, 1984 along the southern Black Sea (Anatolian Coast)
Figure 2. The average monthly sea surface temperature in 2007 and 2015 (°C).
Data from: Structure of the rare archaeal biosphere and seasonal dynamics of active ecotypes in surface coastal waters
Marine Archaea are important players among microbial plankton and significantly contribute to biogeochemical cycles, but details regarding their community structure and long-term seasonal activity and dynamics remain largely unexplored. In this study, we monitored the inter-annual archaeal community composition of abundant and rare biospheres in northwestern Mediterranean Sea surface waters by pyrosequencing 16S rDNA and rRNA. A detailed analysis of the rare biosphere structure showed that the rare archaeal community was composed of three distinct fractions. One contained the rare Archaea that became abundant at different times within the same ecosystem; these cells were typically not dormant, and we hypothesize that they represent a local seed bank that is specific and essential for ecosystem functioning through cycling seasonal environmental conditions. The second fraction contained cells that were uncommon in public databases and not active, consisting of aliens to the studied ecosystem and representing a non-local seed bank of potential colonizers. The third fraction contained Archaea that were always rare but actively growing; their affiliation and seasonal dynamics were similar to the abundant microbes and could not be considered a seed bank. We also showed that the major archaeal groups, Thaumarchaeota Marine Group-I (MGI) and Euryarchaeota Group-II.B (MGII.B) in winter and Euryarchaeota Group-II.A (MGII.A) in summer, contained different ecotypes with varying activities. Our findings suggest that archaeal diversity could be associated with distinct metabolisms or life strategies, and that the rare archaeal biosphere is composed of a complex assortment of organisms with distinct histories that affect their potential for growth.
Figure 6 in Within-tree distribution and seasonal dynamics of Eutetranychus banksi and Euseius stipulatus (Acari: Tetranychidae, Phytoseiidae) on citrus: Implications for the biological control of the pest
Figure 6 Proportion of leaves occupied (grey legend) or unoccupied (white legend) by phytoseiids outside the canopy (a), on adaxial side of leaves (b), red coloured phytoseiids on leaves (c), and phytoseiid on fruits (d), whenE. banksi occurred or was absent. Significant differences
Fig. 2 in Ancyrophora gracilis L , 1892 and Actinocephalus permagnus Wellmer, 1910 (Eugregarinorida: Apicomplexa) in natural populations of ground beetles (Coleoptera, Carabidae) - hosts preferences, intensity and seasonal dynamic
Fig. 2. Mean density of Actinocephalus permagnus (AT) and Ancyrophora gracilis (AC) in relation to habitat. Circle – woodland, square – meadow, triangle – arable land
Figure 5 in Spider assemblages and dynamics on a seasonal island in the Pripyat River, Belarus
Figure 5. Activity density dynamics of dominants Oedothorax retusus and Pardosa prativaga in the period of 30 April to 30 May, 2006 and 2007 data combined with number of samples of the 2 study years averaged. The mean number of specimens (□) with arms of standard deviation values.
Figure 2 in Seasonal pattern of population dynamics, spawning activities, and diet composition of sardine (Sardina pilchardus Walbaum) in the eastern Adriatic Sea
Figure 2. Monthly oscillation of the mean sardine length (TL, cm) collected by commercial purse seiners during 2013 (February–November 2013) on Croatian fishing grounds.
Figure 1 in Seasonal pattern of population dynamics, spawning activities, and diet composition of sardine (Sardina pilchardus Walbaum) in the eastern Adriatic Sea
Figure 1. Study area, eastern Adriatic Sea with marked Croatian fishing ground (dark gray) where the samples from the commercial purse seiners were taken during 2013 (February–November 2013).
Figure 4 in Seasonal pattern of population dynamics, spawning activities, and diet composition of sardine (Sardina pilchardus Walbaum) in the eastern Adriatic Sea
Figure 4. Seasonal oscillations (winter: December to February; spring: March to May; summer: June to September; autumn: October to November) of allometric coefficient (b), condition index (Ka), and fullness index (%Jr) of sardines collected by commercial purse seiners during 2013 (February–November 2013) on Croatian fishing grounds.
Fig. 5. A in Temporal dynamics of fruit-feeding butterflies (Lepidoptera: Nymphalidae) in two habitats in a seasonal Brazilian environment
Fig. 5. A) Temporal variation in Nymphalidae species richness captured in the dry and wet seasons and in the 2 transitional periods between those seasons, wet to dry (T.wd) and dry to wet (T.dw), in savanna (Cerrado sensu stricto, ss) and gallery forest habitats in the Fazenda Água Limpa and the Reserva Ecológica do Roncador, Brasília, DF. The rarefaction curves compare the 4 climatic periods—dry (black triangles) and wet (black circles) seasons, and the transitional periods from wet to dry (T.wd, white circles) and from dry to wet (T.dw, white triangles)—in B) gallery forest and C) savanna separately.
Figure 1 in Peculiarities of seasonal dynamics of net primary production and its microzooplankton grazing in the coastal waters of the Black Sea (Sevastopol region)
Figure 1. Map of the sampling stations: 1—the exit from the Quarantine Bay (St.1); 2—Sevastopol Bay (St. 2).
Fig. 2 in Notes on the seasonal dynamics of the coprophagous Hydrophilidae (Coleoptera) in western Turkey, with first record of Megasternum concinnum for Turkish fauna
Fig. 2: Seasonal dynamics of Sphaeridium scarabaeoides, S. marginatum and Cercyon haemorrhoidalis on the studied localities in western Turkey during 2004 and 2006.
Data from: Data from: Seasonal polyphenism of Spotted-wing Drosophila is affected by variation in local abiotic conditions within its invaded range, likely influencing survival and regional population dynamics
Open the record for dataset details and reuse information.
Data from: Synchronized shift of oral, fecal and urinary microbiotas in bats and natural infection dynamics during seasonal reproduction
Open the record for dataset details and reuse information.
Comparative analysis of time-based and quadrat sampling in seasonal population dynamics of intermediate hosts of human schistosomes
Open the record for dataset details and reuse information.
Seasonal and annual dynamics of litterfall
Open the record for dataset details and reuse information.
Data from: Within-season variation in sexual selection in a fish with dynamic sex roles
Open the record for dataset details and reuse information.
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.