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1,659 results for “structured population”
Fig. 6 in Population structure and reproductive behavior of Sinaloa cichlid Cichlasoma beani (Jordan, 1889) in a tropical reservoir
Fig. 6. (a) Relationship between relative condition index and surface temperature; (b) Relationship of condition index and percentage of Sinaloa cichlid Cichlasoma beani females in Stages IV and V of the maturity scale of Nikolsky (1963) in the Aguamilpa Reservoir, Mexico.
Fig. 5 in Iheringichthys labrosus (Siluriformes: Pimelodidae) in the Piquiri River, Paraná, Brazil: population structure and some aspects of its reproductive biology
Fig. 5. Bimonthly variation of the mean values of the condition factor for females (a) and males (b) of Iheringichthys labrosus in the Piquiri River from November 2002 to September 2003. (SD = Standard deviation).
Fig. 1 in Microsatellite variation and population genetic structure of a neotropical endangered Bryconinae species Brycon insignis Steindachner, 1877: implications for its conservation and sustainable management
Fig. 1. Location of sampling sites of Brycon insignis in drainages in Southeastern Brazil. Power Company Hatchery (PCH), São João River (SJR), Paraíba do Sul River (PSR), Imbé River (IMR), Muriaé River (MUR) and Itabapoana River (ITR).
Population genetic structure Arctosa sanctaerosae
<p>The continued increase in the number of tourists visiting the Northern Gulf Coast (NGC), USA, in the last century, and the resulting sprawl of large cities along the coast, has degraded and fragmented the available habitat of Arctosa sanctaerosae, a wolf spider endemic to the secondary dunes of the white sandy beaches of the NGC. In addition to anthropogenic disturbance to this coastal region, hurricanes are an additional and natural perturbation to the ecosystem. The data presented here explore the status of populations of this species spanning the entire known range and the factors influencing population demography including anthropogenic disturbance and severe tropical storms. Using microsatellite markers, we were able to document the genetic structure of Arctosa sanctaerosae, including current and historical patterns of migration. These results combined with ecological and census data reveal the characteristics that have influenced population persistence: ecological variables affecting the recovery of the population clusters after severe tropical storms, genetic fragmentation due to anthropogenic disturbance, and their interaction. These findings demonstrate the significance that the high traffic beach communities of the NGC and their impact on the once intact contiguous dune ecosystem have on recovery after severe tropical storms. Contemporary modeling methods that compare current and historical levels of gene flow suggest Arctosa sanctaerosae has experienced a single, contiguous population subdivision, and the isolates reduced in size since the onset of commercial development of the NGC. These results point to the need for monitoring of the species and increased protection for this endangered habitat. </p>
The impact of estimator choice: Disagreement in clustering solutions across K estimators for Bayesian analysis of population genetic structure across a wide range of empirical datasets
<p class="CxSpFirst">The software program STRUCTURE is one of the most cited tools for determining population structure. To infer the optimal number of clusters from STRUCTURE output, the Δ<i>K</i> method is often applied. However, a recent study relying on simulated microsatellite data suggested that this method has a downward bias in its estimation of <i>K</i> and is sensitive to uneven sampling. If this finding holds for empirical datasets, conclusions about the scale of gene flow may have to be revised for a large number of studies. To determine the impact of method choice, we applied recently described estimators of <i>K</i> to re-estimate genetic structure in 41 empirical microsatellite datasets; 15 from a broad range of taxa and 26 focused on a diverse phylogenetic group, coral. We compared alternative estimates of <i>K</i> (Puechmaille statistics) with traditional (Δ<i>K</i> and posterior probability) estimates and found widespread disagreement of estimators across datasets. Thus, one estimator alone is insufficient for determining the optimal number of clusters regardless of study organism or evenness of sampling scheme. Subsequent analysis of molecular variance (AMOVA) between clustering solutions did not necessarily clarify which solution was best. To better infer population structure, we suggest a combination of visual inspection of STRUCTURE plots and calculation of the alternative estimators at various thresholds in addition to Δ<i>K</i>. Differences between estimators could reveal patterns with important biological implications, such as the potential for more population structure than previously estimated, as was the case for many studies reanalyzed here.</p>
Figure 7 from: Grabowski RC, Simões SM, Castilho AL (2014) Population structure, sex ratio and growth of the seabob shrimp Xiphopenaeus kroyeri (Decapoda, Penaeidae) from coastal waters of southern Brazil. In: Wehrtmann IS, Bauer RT (Eds) Proceedings of the Summer Meeting of the Crustacean Society and the Latin American Association of Carcinology, Costa Rica, July 2013. ZooKeys 457: 253-269. https://doi.org/10.3897/zookeys.457.6682
Figure 7 - Xiphopenaeus kroyeri. Mean growth curve estimated for females collected in an area adjacent to Babitonga Bay, from July 2010 through June 2011, based on the von Bertalanffy growth model. Outer lines: 95% prediction interval.
Figure 6 from: Grabowski RC, Simões SM, Castilho AL (2014) Population structure, sex ratio and growth of the seabob shrimp Xiphopenaeus kroyeri (Decapoda, Penaeidae) from coastal waters of southern Brazil. In: Wehrtmann IS, Bauer RT (Eds) Proceedings of the Summer Meeting of the Crustacean Society and the Latin American Association of Carcinology, Costa Rica, July 2013. ZooKeys 457: 253-269. https://doi.org/10.3897/zookeys.457.6682
Figure 6 - Xiphopenaeus kroyeri. Mean growth curve estimated for males collected in an area adjacent to Babitonga Bay, from July 2010 through June 2011, based on the von Bertalanffy growth model. Outer lines: 95% prediction interval.
Figure 4 from: Grabowski RC, Simões SM, Castilho AL (2014) Population structure, sex ratio and growth of the seabob shrimp Xiphopenaeus kroyeri (Decapoda, Penaeidae) from coastal waters of southern Brazil. In: Wehrtmann IS, Bauer RT (Eds) Proceedings of the Summer Meeting of the Crustacean Society and the Latin American Association of Carcinology, Costa Rica, July 2013. ZooKeys 457: 253-269. https://doi.org/10.3897/zookeys.457.6682
Figure 4 - Xiphopenaeus kroyeri. Selected cohorts for growth analysis and number of males collected each month from July 2010 through June 2011 in an area adjacent to Babitonga Bay, southern Brazil.
Figure 5 from: Grabowski RC, Simões SM, Castilho AL (2014) Population structure, sex ratio and growth of the seabob shrimp Xiphopenaeus kroyeri (Decapoda, Penaeidae) from coastal waters of southern Brazil. In: Wehrtmann IS, Bauer RT (Eds) Proceedings of the Summer Meeting of the Crustacean Society and the Latin American Association of Carcinology, Costa Rica, July 2013. ZooKeys 457: 253-269. https://doi.org/10.3897/zookeys.457.6682
Figure 5 - Xiphopenaeus kroyeri. Selected cohorts for growth analysis and number of females collected each month from July 2010 through June 2011 in an area adjacent to Babitonga Bay, southern Brazil.
Figure 3 from: Grabowski RC, Simões SM, Castilho AL (2014) Population structure, sex ratio and growth of the seabob shrimp Xiphopenaeus kroyeri (Decapoda, Penaeidae) from coastal waters of southern Brazil. In: Wehrtmann IS, Bauer RT (Eds) Proceedings of the Summer Meeting of the Crustacean Society and the Latin American Association of Carcinology, Costa Rica, July 2013. ZooKeys 457: 253-269. https://doi.org/10.3897/zookeys.457.6682
Figure 3 - Xiphopenaeus kroyeri. Monthly sex ratio (estimate ± standard error) of adults collected from July 2010 through June 2011 in an area adjacent to Babitonga Bay, southern Brazil. Black circles indicate significant deviation from a 1:1 sex ratio (Binomial test, p < 0.05).
Figure 1 from: Grabowski RC, Simões SM, Castilho AL (2014) Population structure, sex ratio and growth of the seabob shrimp Xiphopenaeus kroyeri (Decapoda, Penaeidae) from coastal waters of southern Brazil. In: Wehrtmann IS, Bauer RT (Eds) Proceedings of the Summer Meeting of the Crustacean Society and the Latin American Association of Carcinology, Costa Rica, July 2013. ZooKeys 457: 253-269. https://doi.org/10.3897/zookeys.457.6682
Figure 1 - Map of the study area, Babitonga Bay, southern Brazil (Santa Catarina state), indicating locations and depths of the sampling sites.
Figure 2 from: Grabowski RC, Simões SM, Castilho AL (2014) Population structure, sex ratio and growth of the seabob shrimp Xiphopenaeus kroyeri (Decapoda, Penaeidae) from coastal waters of southern Brazil. In: Wehrtmann IS, Bauer RT (Eds) Proceedings of the Summer Meeting of the Crustacean Society and the Latin American Association of Carcinology, Costa Rica, July 2013. ZooKeys 457: 253-269. https://doi.org/10.3897/zookeys.457.6682
Figure 2 - Xiphopenaeus kroyeri. Distribution of the percentage of juveniles and adults by size classes (CL, mm) observed for individuals collected from July 2010 through June 2011 in an area adjacent to Babitonga Bay, southern Brazil.
Figure 2 from: Virgilio M, Delatte H, Nzogela YB, Simiand C, Quilici S, De Meyer M, Mwatawala M (2015) Population structure and cryptic genetic variation in the mango fruit fly, Ceratitis cosyra (Diptera, Tephritidae). In: De Meyer M, Clarke AR, Vera MT, Hendrichs J (Eds) Resolution of Cryptic Species Complexes of Tephritid Pests to Enhance SIT Application and Facilitate International Trade. ZooKeys 540: 525-538. https://doi.org/10.3897/zookeys.540.9618
Figure 2 - Individual Bayesian assignments. STRUCTURE sequential individual assignments of 348 specimens of Ceratitis cosyra from 13 African countries.
Figure 1 from: Virgilio M, Delatte H, Nzogela YB, Simiand C, Quilici S, De Meyer M, Mwatawala M (2015) Population structure and cryptic genetic variation in the mango fruit fly, Ceratitis cosyra (Diptera, Tephritidae). In: De Meyer M, Clarke AR, Vera MT, Hendrichs J (Eds) Resolution of Cryptic Species Complexes of Tephritid Pests to Enhance SIT Application and Facilitate International Trade. ZooKeys 540: 525-538. https://doi.org/10.3897/zookeys.540.9618
Figure 1 - Unconstrained and constrained ordination. Principal Component Analysis (PCA) and Discriminant Analysis of Principal Components (DAPC) of 348 Ceratitis cosyra microsatellite genotypes. Specimen groups are labelled inside their 95% inertia ellipses and genotypes are connected to the corresponding group centroids.
Fig. 3 in Spined Loache Settlements Structure (Cobitidae) Of The Eastern Ukraine River Systems And Alternative Character Of Diploid And Polyploid Populations
Fig. 3. Distribution of diploid and polyploid loaches due to erythrocyte size in the populations of the Donets and small rivers of the Sea of Azov.
Population genetic structure associated with a landscape barrier in the Western Grasswren (Amytornis textilis textilis)
<p class="MsoNormal">Dispersal patterns can dictate genetic population structure, and ultimately population resilience, through maintaining gene flow and genetic diversity. However, geographic landforms, such as peninsulas, can impact dispersal patterns and thus be a barrier to gene flow. Here, we use 13,375 genome-wide single-nucleotide polymorphisms (SNPs) to evaluate genetic population structure and infer dispersal patterns of the Western Grasswren (<em>Amytornis textilis textilis</em>; WGW,<em> n </em>= 140)<em> </em>in the Shark Bay region of Western Australia. We found high levels of genetic divergence between subpopulations on the mainland (Hamelin) and narrow peninsula (Peron). In addition, we found evidence of further genetic sub-structuring within the Hamelin subpopulation, with individuals collected from the western and eastern regions of a conservation reserve forming separate genetic clusters. Spatial autocorrelation analysis within each subpopulation revealed significant local-scale genetic structure up to 35 km at Hamelin and 20 km at Peron. In addition, there was evidence of male philopatry in both subpopulations. Our results suggest a narrow strip of land may be acting as a geographic barrier in the WGW, limiting dispersal between a peninsula and mainland subpopulation. In addition, heterogeneous habitat within Hamelin may be restricting dispersal at the local scale. Furthermore, there is evidence to suggest that the limited gene flow is asymmetrical, with directional dispersal occurring from the bounded peninsula subpopulation to the mainland. This study highlights the genetic structure existing within and between some of the few remaining WGW subpopulations, and shows a need for placing equal importance on conservation efforts to maintain them in the future.</p>
Fig. 3 in Comparative analysis of the population structure of Crematogaster subdentata and Lasius neglectus in the primary and secondary ranges (Hymenoptera: Formicidae)
Fig. 3 – Scheme of the foraging areas of Crematogaster subdentata in Rostov-on-Don large accessible nests of C. subdentata in buildings and outside; inaccessible nests of C. subdentata in buildings; trees: Ac – Acer sp., Ae – Aesculus hippocastanum, Aj – Albizia julibrissin, Al – Ailanthus altissima, An – Acer negundo, C – Campsis radicans, Fr – Fraxinus sp., Gl – Gleditsia triacanta, J – Juglans regia, Mn – Morus nigra, Pa – Prunus americana, Pc – Prunus cerasus, Pp – Populus niger, Ps – Prunus spinosa, Ra – Robinia pseudoacacia, Tl – Tilia sp., Ul – Ulmus sp., V – Viburnum sp.
figure 5 in Spatial genetic structure in the Eurasian otter (Lutra lutra) meta-population from its core range in Italy
figure 5 Cumulative current map, based on all possible pairs of sampling locations, representing the amount of current flowing through each pixel. Higher current flow represents higher connectivity, and vice versa.
figure 2 in Spatial genetic structure in the Eurasian otter (Lutra lutra) meta-population from its core range in Italy
figure 2 Definition of the six main river basins by drawing a buffer area of 1 km around all waterways connected to the main rivers: in green, the Cilento basin; in pink, the Agri basin; in blue, the Sinni basin; in red, the Lao basin; in orange, the Basento basin; in violet, the Abatemarco basin. Red spots indicate the location of the collected samples. The bold blue lines highlight the main rivers, while the tiny blue lines show all other waterways.
Computational results for the study "Computational evolution of social norms in well-mixed and group-structured populations"
<p>This is a collection of computational results for "Computational evolution of social norms in well-mixed and group-structured populations."</p> <p>The source code is available at https://github.com/yohm/sim_evo_social_norms</p>
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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.
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.