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Figure 4. Alpheus brasileiro Anker, 2012. A in Growth, age at sexual maturity, longevity and natural mortality of Alpheus brasileiro (Caridea: Alpheidae) from the south-eastern coast of Brazil
Figure 4. Alpheus brasileiro Anker, 2012. A, Cohorts identified during sampling describing the growth of each sex. B, Bertalanffy´s equation parameters estimated for males and females. The central line = mean; external lines = prediction intervals (95%).
Figure 5. Alpheus brasileiro Anker, 2012. Logistic curve interpolation where 50 in Growth, age at sexual maturity, longevity and natural mortality of Alpheus brasileiro (Caridea: Alpheidae) from the south-eastern coast of Brazil
Figure 5. Alpheus brasileiro Anker, 2012. Logistic curve interpolation where 50% of females reach functional sexual maturity (CL50).
Figure 3. Alpheus brasileiro Anker, 2012 in Growth, age at sexual maturity, longevity and natural mortality of Alpheus brasileiro (Caridea: Alpheidae) from the south-eastern coast of Brazil
Figure 3. Alpheus brasileiro Anker, 2012. Size–frequency distribution of individuals both sexually immature (2.5 to 4.5 mm CL) and sexually mature (5.5 to 9.5 mm CL). Undifferentiated individuals (white bars), males (black bars) and females (dark grey bars). The values of morphological sexual maturity (4.9 and 4.7 mm CL for males and females respectively) are from the study of population structure and relative growth with the same population (Pescinelli et al., 2018a).
Figure 2. A in Growth, age at sexual maturity, longevity and natural mortality of Alpheus brasileiro (Caridea: Alpheidae) from the south-eastern coast of Brazil
Figure 2. A, Lateral view of an ovigerous female of Alpheus brasileiro Anker, 2012; B, sampling area at the intertidal zone of the estuary of Cananéia, São Paulo, south–eastern Brazil.
Figure 1 in Growth, age at sexual maturity, longevity and natural mortality of Alpheus brasileiro (Caridea: Alpheidae) from the south-eastern coast of Brazil
Figure 1. Location of the study area, water represented by dark grey in the map of the intertidal estuarine zone of Cananéia, São Paulo, south–eastern Brazil. Adapted from Pescinelli et al. (2017a).
Fig. 2 in Investigation of Ichthyophthirius multifiliis infection in fish from natural water bodies in the Lhasa and Nagqu regions of Tibet
Fig. 2. Pairwise comparisons of locality. Localities: BZ, Boqu Zangbo (river); CEL, Cuoe lake; CNL, Cuona lake; CW, Chabalang Wetland; LR, Lhasa River; LW, Lalu Wetland; SL, Selincuo Lake ZZ, Za'gya Zangbo (river). *: Indicates a significant difference between location 1 and location 2.
Fig. 2 in Natural history of Zoonotic Babesia: Role of wildlife reservoirs
Fig. 2. Babesia parasites in human erythrocytes. (a) B. divergens, (b) B. venatorum, (c) Babesia sp. MO1 from Kentucky, (d) B. microti, (e) B. duncani, (f) Babesia sp. KO1 from Korea. (1) Paired piriforms; (2) Tetrads; (3) Ring forms. The figure was reprinted with permission from Elsevier first published in Gray et al. (2010). The parasites shown in Fig. 2a, b, c, e, and f were assembled from original photographs, first published as follows: (a) Hunfeld et al., 2008; (b) Häselbarth et al., 2007; (c) Beattie et al., 2002; (e) Kjemtrup et al., 2002; (f) Kim et al., 2007.
Fig. 1 in Investigation of Ichthyophthirius multifiliis infection in fish from natural water bodies in the Lhasa and Nagqu regions of Tibet
Fig. 1. The map shows the sampling locations of fish in Tibet: 1. North shore of Selincuo (89.112679E, 32.102116N, 4558 m altitude); 2. Za'gya Zangbo (river) (90.723403E, 32.437662N, 5060 m altitude); 3. Boqu Zangbo (river) (89.292002E, 31.606048N, 4579 m altitude); 4. Boqu estuary (89.354410E, 31.762732N, 4554 m altitude); 5. Cuona lake (91.547087E, 32.012987N, 4726 m altitude); 6. Cuoe lake (91.545788E, 31.474142N, 4541 m altitude); 7. Lalu Wetland (91.099541E, 29.668837N, 4989 m altitude); 8. Chabalang Wetland (90.832207E, 29.380565N, 3590 m altitude).
Fig. 1 in Natural history of Zoonotic Babesia: Role of wildlife reservoirs
Fig. 1. Phylogenetic tree of Babesia and related piroplasms with zoonotic species bolded. The tree was constructed using neighbor-joining analysis of full-length 18S rRNA gene sequences extracted from GenBank (accession numbers listed for each species). For zoonotic representatives, the endemic country or region is listed in parentheses.
Natural history specimens collected and/or identified and deposited.
Natural history specimen data collected and/or identified by Richard Wettstein, <a href="http://www.wikidata.org/entity/Q78599">http://www.wikidata.org/entity/Q78599</a>. Claims or attributions were made on Bionomia, <a href="http://bionomia.net">https://bionomia.net</a> using specimen data from the Global Biodiversity Information Facility, <a href="https://gbif.org">https://gbif.org</a>.
Natural history specimens collected and/or identified and deposited.
Natural history specimen data collected and/or identified by Karl Moritz Ernst Gustav Wilhelm Adametz, <a href="http://www.wikidata.org/entity/Q64946788">http://www.wikidata.org/entity/Q64946788</a>. Claims or attributions were made on Bionomia, <a href="http://bionomia.net">https://bionomia.net</a> using specimen data from the Global Biodiversity Information Facility, <a href="https://gbif.org">https://gbif.org</a>.
Natural history specimens collected and/or identified and deposited.
Natural history specimen data collected and/or identified by Antoine-Tristan Danty d'Isnard, <a href="http://www.wikidata.org/entity/Q585551">http://www.wikidata.org/entity/Q585551</a>. Claims or attributions were made on Bionomia, <a href="http://bionomia.net">https://bionomia.net</a> using specimen data from the Global Biodiversity Information Facility, <a href="https://gbif.org">https://gbif.org</a>.
Resilience assessment in complex natural systems
<p>Ecological resilience is the capability of an ecosystem to maintain the same structure and function and to avoid crossing catastrophic tipping points (i.e. irreversible regime shifts). While fundamental for management, concrete ways to estimate and interpret resilience in real ecosystems are still lacking. Here, we develop an empirical approach to estimate resilience based on the stochastic cusp model derived from catastrophe theory. The cusp model models tipping points derived from a cusp bifurcation. We extend cusp in order to identify the presence of stable and unstable states in complex natural systems. Our Cusp Resilience Assessment (CUSPRA) has three characteristics: i) it provides estimates on how likely a system is to cross a tipping point (in the form of a cusp bifurcation) characterized by hysteresis, ii) it assesses resilience in relation to multiple external drivers, and iii) it produces straightforward results for ecosystem-based management. We validate our approach using simulated data and demonstrate its application using empirical time-series of an Atlantic cod population and of marine ecosystems in the North Sea and the Mediterranean Sea. We show that CUSPRA is a powerful method to empirically estimate resilience in support of a sustainable management of our adapting ecosystems under global climate change.</p>
Fig. 2 in Leguminosae no Parque Natural Municipal de Jacarenema, Vila Velha, Espírito Santo, Brasil
Fig. 2. Comparação entre a diversidade de Leguminosae nas restingas do Brasil. 1. Plano de Manejo do Parque Natural Municipal de Jacarenema, ES (Gomes 2002); 2. Reserva de Camburi, ES (Pereira & Assis 2000); 3. Morada do Sol, ES (Valadares et al. 2011); 4. Parque Estadual de Itaúnas, ES (Souza et al. 2016); 5. Parque Estadual Paulo César Vinha, ES (Chagas et al. 2014, Peterle et al. 2015, Weiler Jr. 1998); 6. Reserva Ecológica Estadual de Jacarepiá, RJ (Sá 1992); 7. Área de Proteção Ambiental da Massambaba, RJ (Araújo et al. 2009); 8. Bertioga, SP (Martins et al. 2008); 9. Reserva Particular do Patrimônio Natural de Maracaípe, PE (Almeida Jr et al. 2009); 10. Área de Proteção Ambiental de Guadalupe, PE (Cantarelli et al. 2012); 11. Parque Nacional Serra de Itabaiana, SE (Dantas et al. 2010); 12. Ceará (Santos-Filho et al. 2011); 13. Piauí (Santos-Filho 2009).
Figs. 3A-R. A. Alysicarpus vaginalis – Folha. B-D. Chamaecrista rotundifolia var. rotundifolia. B in Leguminosae no Parque Natural Municipal de Jacarenema, Vila Velha, Espírito Santo, Brasil
Figs. 3A-R. A. Alysicarpus vaginalis – Folha. B-D. Chamaecrista rotundifolia var. rotundifolia. B. Folíolo; C. Flor; D. Fruto. E-G. Zornia glabra. E. Folíolos; F. Inflorescência; G. Fruto. H, I. Stylosanthes gracilis. H. Estípulas; I. Folha; J. Stylosanthes scabra - Folha. K. Crotalaria maypurensis - Estípula. L, M. Crotalaria pallida. L. Fruto; M. Estípula. N. Ancistrotropis peduncularis - Fruto. O, P. Desmodium adscendens; O. Fruto; P. Flor. Q. Rhynchosia phaseoloides - Fruto. R. Centrosema virginianum Flor.
Figs. 5A-O. A in Leguminosae no Parque Natural Municipal de Jacarenema, Vila Velha, Espírito Santo, Brasil
Figs. 5A-O. A. Dalbergia ecastaphyllum - Inflorescência; B-D. Zollernia glabra. B. Fruto; C. Inflorescência; D. Fruto. E. Hymenaea fariana - Folha. F, I. Swartzia simplex. F. Folha; I. Fruto. G, H. Sophora tomentosa. G. Folha; H. Fruto. J. Machaerium lanceolatum - Fruto. K. Leptolobium tenuifolium - Fruto. L. Andira nitida - Fruto. M. Swartzia apetala - Fruto. N. Machaerium hirtum - Ramo armado. O. Mimosa pudica - Ramo aculeado.
Figs. 4A-Q. A. Canavalia parviflora - Fruto. B, C. Aeschynomene brasiliana. B in Leguminosae no Parque Natural Municipal de Jacarenema, Vila Velha, Espírito Santo, Brasil
Figs. 4A-Q. A. Canavalia parviflora - Fruto. B, C. Aeschynomene brasiliana. B. Estípula; C. Fruto. D-F. Chamaecrista ramosa. D. Estípula; E. Flor; F. Fruto. G. Chamaecrista nictitans subsp. patellaria - Nectário foliar. H. Chamaecrista nictitans subsp. disadena - Nectário foliar. I. Senna appendiculata - Nectário foliar. J. Chamaecrista ensiformis - Nectário foliar. K. Inga edulis - Nectário foliar. L. Chamaecrista ensiformis - Flor. M. Inga edulis - Flor. N. Zygia latifolia var. glabrata - Fruto. O. Inga edulis - Fruto. P. Inga laurina- Inflorescência. Q. Inga subnuda - Inflorescência.
Natural history specimens collected and/or identified and deposited.
Natural history specimen data collected and/or identified by G.F. Laundon, <a href="http://www.wikidata.org/entity/Q21518420">http://www.wikidata.org/entity/Q21518420</a>. Claims or attributions were made on Bionomia, <a href="http://bionomia.net">https://bionomia.net</a> using specimen data from the Global Biodiversity Information Facility, <a href="https://gbif.org">https://gbif.org</a>.
Natural history specimens collected and/or identified and deposited.
Natural history specimen data collected and/or identified by William A. Wimsatt, <a href="http://www.wikidata.org/entity/Q8004083">http://www.wikidata.org/entity/Q8004083</a>. Claims or attributions were made on Bionomia, <a href="http://bionomia.net">https://bionomia.net</a> using specimen data from the Global Biodiversity Information Facility, <a href="https://gbif.org">https://gbif.org</a>.
Natural history specimens collected and/or identified and deposited.
Natural history specimen data collected and/or identified by Pavel Švanda, <a href="http://www.wikidata.org/entity/Q95166421">http://www.wikidata.org/entity/Q95166421</a>. Claims or attributions were made on Bionomia, <a href="http://bionomia.net">https://bionomia.net</a> using specimen data from the Global Biodiversity Information Facility, <a href="https://gbif.org">https://gbif.org</a>.
ScienceDex guides
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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.