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276 results for “integrated assessment”
Supplementary material 1 from: Burkhard B, Maes J, Potschin-Young MB, Santos-Martín F, Geneletti D, Stoev P, Kopperoinen L, Adamescu CM, Adem Esmail B, Arany I, Arnell A, Balzan M, Barton DN, van Beukering P, Bicking S, Borges PAV, Borisova B, Braat L, M Brander LM, Bratanova-Doncheva S, Broekx S, Brown C, Cazacu C, Crossman N, Czúcz B, Daněk J, Groot R, Depellegrin D, Dimopoulos P, Elvinger N, Erhard M, Fagerholm N, Frélichová J, Grêt-Regamey A, Grudova M, Haines-Young R, Inghe O, Kallay TK, Kirin T, Klug H, Kokkoris IP, Konovska I, Kruse M, Kuzmova I, Lange M, Liekens I, Lotan A, Lowicki D, Luque S, Marta-Pedroso C, Mizgajski A, Mononen L, Mulder S, Müller F, Nedkov S, Nikolova M, Östergård H, Penev L, Pereira P, Pitkänen K, Plieninger T, Rabe S, Reichel S, Roche PK, Rusch G, Ruskule A, Sapundzhieva A, Sepp K, Sieber IM, Šmid Hribar M, Stašová S, Steinhoff-Knopp B, Stępniewska M, Teller A, Vackar D, van Weelden M, Veidemane K, Vejre H, Vihervaara P, Viinikka A, Villoslada M, Weibel B, Zulian G (2018) Mapping and assessing ecosystem services in the EU - Lessons learned from the ESMERALDA approach of integration. One Ecosystem 3: e29153. https://doi.org/10.3897/oneeco.3.e29153
List of ESMERALDA poject partners
Integrative taxonomy of the cycad-associated weevils of the Tranes group, with a revision of Tranes Schoenherr, a key to all taxa and an assessment of host specificity in the group (Coleoptera: Curculionidae: Molytinae)
<p>Unedited photos used in the taxonomic research, NT_Alignment for phylogenetic analysis and Unrooted Tree File</p>
Data from: An integrated assessment model of seabird population dynamics: can individual heterogeneity in susceptibility to fishing explain abundance trends in Crozet wandering albatross?
1. Seabirds have been incidentally caught in distant-water longline fleets operating in the Southern Ocean since at least the 1970s, and breeding numbers for some populations have shown marked trends of decline and recovery concomitant with longline fishing effort within their distributions. However, lacking is an understanding of how forms of among-individual heterogeneity may interact with fisheries bycatch and influence population dynamics. 2. We develop a model that uses comprehensive data on the spatial and temporal distributions of fishing effort and seabird foraging to estimate temporal overlaps, fishery catchability and consequent bycatch. We apply a population model that is structured by age, sex, life stage and spatially to Crozet Island wandering albatross and explore how heterogeneity in susceptibility to capture may have influenced the population's demography over time. 3. A model where some birds were assumed to be more susceptible to fisheries bycatch was able to successfully replicate the observed trend in breeding pairs. Considerably poorer fits were found without this assumption. Results suggested that the more susceptible birds may have been removed from the population by the 1990s. 4. The model was also able to highlight areas, times and fleets prone to increased bycatch. Knowledge of these factors should assist fisheries and conservation management bodies to quantify and reduce seabird bycatch through spatial management and fleet-specific mitigation efforts. 5. Synthesis and application. Many seabirds show complex life histories that make them highly susceptible to additional incidental mortality from fishing vessels. By applying a population model that integrates key aspects of seabird and fishery dynamics, we were able to explain the observed trends in the breeding population of Crozet wandering albatross and identify key areas and fleets where further mitigation may be required. In addition, the potential removal of a category of birds that shows increased susceptibility to capture has important implications for the conservation management of this population and other iconic species incidentally caught by large-scale commercial fisheries.
Supplementary material 1 from: Pissaridou P, Cantonati M, Bouchez A, Tziortzis I, Dörflinger G, Vasquez MI (2021) How can integrated morphotaxonomy- and metabarcoding-based diatom assemblage analyses best contribute to the ecological assessment of streams? Metabarcoding and Metagenomics 5: e68438. https://doi.org/10.3897/mbmg.5.68438
Table S1
Supplementary material 2 from: Pissaridou P, Cantonati M, Bouchez A, Tziortzis I, Dörflinger G, Vasquez MI (2021) How can integrated morphotaxonomy- and metabarcoding-based diatom assemblage analyses best contribute to the ecological assessment of streams? Metabarcoding and Metagenomics 5: e68438. https://doi.org/10.3897/mbmg.5.68438
Figure S1
Figure 8 from: Aguilar C, Wood P, Cusi J, Guzman A, Huari F, Lundberg M, Mortensen E, Ramirez C, Robles D, Suarez J, Ticona A, Vargas V, Venegas P (2013) Integrative taxonomy and preliminary assessment of species limits in the Liolaemus walkeri complex (Squamata, Liolaemidae) with descriptions of three new species from Peru. ZooKeys 364: 47-91. https://doi.org/10.3897/zookeys.364.6109
Figure 8 - Dorsal (A) and ventral (B) views of the holotype of Liolaemus chavin sp. n. (C) Type locality.
Figure 11 from: Aguilar C, Wood P, Cusi J, Guzman A, Huari F, Lundberg M, Mortensen E, Ramirez C, Robles D, Suarez J, Ticona A, Vargas V, Venegas P (2013) Integrative taxonomy and preliminary assessment of species limits in the Liolaemus walkeri complex (Squamata, Liolaemidae) with descriptions of three new species from Peru. ZooKeys 364: 47-91. https://doi.org/10.3897/zookeys.364.6109
Figure 11 - Geographic distribution of Liolaemus chavin, Liolaemus pachacutec, Liolaemus tacnae, Liolaemus walkeri, and Liolaemus wari.
Figure 7 from: Aguilar C, Wood P, Cusi J, Guzman A, Huari F, Lundberg M, Mortensen E, Ramirez C, Robles D, Suarez J, Ticona A, Vargas V, Venegas P (2013) Integrative taxonomy and preliminary assessment of species limits in the Liolaemus walkeri complex (Squamata, Liolaemidae) with descriptions of three new species from Peru. ZooKeys 364: 47-91. https://doi.org/10.3897/zookeys.364.6109
Figure 7 - Receiver operating characteristic curves and AUC values for A Ancash B Ayacucho C Cusco D Liolaemus tacnae and E Liolaemus walkeri.
Figure 6 from: Aguilar C, Wood P, Cusi J, Guzman A, Huari F, Lundberg M, Mortensen E, Ramirez C, Robles D, Suarez J, Ticona A, Vargas V, Venegas P (2013) Integrative taxonomy and preliminary assessment of species limits in the Liolaemus walkeri complex (Squamata, Liolaemidae) with descriptions of three new species from Peru. ZooKeys 364: 47-91. https://doi.org/10.3897/zookeys.364.6109
Figure 6 - Predicted area and known geographic distribution (A) used to develop distributional models of Ancash (B) Ayacucho (C) Cusco (D) Liolaemus tacnae (E) and Liolaemus walkeri (F).
Figure 10 from: Aguilar C, Wood P, Cusi J, Guzman A, Huari F, Lundberg M, Mortensen E, Ramirez C, Robles D, Suarez J, Ticona A, Vargas V, Venegas P (2013) Integrative taxonomy and preliminary assessment of species limits in the Liolaemus walkeri complex (Squamata, Liolaemidae) with descriptions of three new species from Peru. ZooKeys 364: 47-91. https://doi.org/10.3897/zookeys.364.6109
Figure 10 - Lateral (A) dorsal (B) and ventral (C) views of the holotype of Liolaemus wari sp. n. (D) Type locality.
Figure 5 from: Aguilar C, Wood P, Cusi J, Guzman A, Huari F, Lundberg M, Mortensen E, Ramirez C, Robles D, Suarez J, Ticona A, Vargas V, Venegas P (2013) Integrative taxonomy and preliminary assessment of species limits in the Liolaemus walkeri complex (Squamata, Liolaemidae) with descriptions of three new species from Peru. ZooKeys 364: 47-91. https://doi.org/10.3897/zookeys.364.6109
Figure 5 - First and second principal components (PC) and correspondence axes (CA) of morphometric (A) and meristic (B) data of Ancash, Ayacucho, Cusco, Liolaemus tacnae and Liolaemus walkeri respectively.
Figure 1 from: Aguilar C, Wood P, Cusi J, Guzman A, Huari F, Lundberg M, Mortensen E, Ramirez C, Robles D, Suarez J, Ticona A, Vargas V, Venegas P (2013) Integrative taxonomy and preliminary assessment of species limits in the Liolaemus walkeri complex (Squamata, Liolaemidae) with descriptions of three new species from Peru. ZooKeys 364: 47-91. https://doi.org/10.3897/zookeys.364.6109
Figure 1 - Concatenated maximum likelihood (-Log L = 8452.31415) tree based on cyt-b and 12S haplotypes of focal taxa (Ancash, Ayacucho Cusco) and species assigned to the alticolor group and outgroups. Bootstrap ≥ 70 (*) and posterior probabilities values are shown above and below branches respectively.
Figure 9 from: Aguilar C, Wood P, Cusi J, Guzman A, Huari F, Lundberg M, Mortensen E, Ramirez C, Robles D, Suarez J, Ticona A, Vargas V, Venegas P (2013) Integrative taxonomy and preliminary assessment of species limits in the Liolaemus walkeri complex (Squamata, Liolaemidae) with descriptions of three new species from Peru. ZooKeys 364: 47-91. https://doi.org/10.3897/zookeys.364.6109
Figure 9 - Lateral (A) dorsal (B) and ventral (C) views of the holotype of Liolaemus pachacutec sp. n. (D) Habitat of Liolaemus pachacutec
Figure 3 from: Aguilar C, Wood P, Cusi J, Guzman A, Huari F, Lundberg M, Mortensen E, Ramirez C, Robles D, Suarez J, Ticona A, Vargas V, Venegas P (2013) Integrative taxonomy and preliminary assessment of species limits in the Liolaemus walkeri complex (Squamata, Liolaemidae) with descriptions of three new species from Peru. ZooKeys 364: 47-91. https://doi.org/10.3897/zookeys.364.6109
Figure 3 - Ventral view showing the color patterns of the belly and tail: A Ancash B Ayacucho C Cusco D Liolaemus tacnae and E Liolaemus walkeri.
Figure 2 from: Aguilar C, Wood P, Cusi J, Guzman A, Huari F, Lundberg M, Mortensen E, Ramirez C, Robles D, Suarez J, Ticona A, Vargas V, Venegas P (2013) Integrative taxonomy and preliminary assessment of species limits in the Liolaemus walkeri complex (Squamata, Liolaemidae) with descriptions of three new species from Peru. ZooKeys 364: 47-91. https://doi.org/10.3897/zookeys.364.6109
Figure 2 - Detailed view of the cloaca region showing absence (A, D) or presence (B, C, E) of precloacal pores: A Ancash B Ayacucho C Cusco D Liolaemus tacnae and E Liolaemus walkeri.
Integrated machine learning and GIS-based bathtub models to assess the future flood risk in the Kapuas River Delta, Indonesia
<p>To use the data and the code, please cite the following article: </p> <p>Joko Sampurno, Randy Ardianto, Emmanuel Hanert; Integrated machine learning and GIS-based bathtub models to assess the future flood risk in the Kapuas River Delta, Indonesia. <em><em>Journal of Hydroinformatics</em></em> 2022; jh2022106. DOI: <a href="https://doi.org/10.2166/hydro.2022.106">https://doi.org/10.2166/hydro.2022.106</a></p>
FIGURE 3 in Integrative taxonomy of a new species of Rhyacodrilus (Annelida: Clitellata: Rhyacodrilinae) from Tibet Plateau rivers, with a preliminary assessment of its phylogenetic position
FIGURE 3. Za'gya Zangbo river near Tangulashan mountains.
Fig. 8 in The integration of MS-based metabolomics and multivariate data analysis allows for improved quality assessment of Zingiber officinale Roscoe
Fig. 8. The influence of drying of ginger on the gingerols and gingerol-related metabolites.
Fig. 6 in The integration of MS-based metabolomics and multivariate data analysis allows for improved quality assessment of Zingiber officinale Roscoe
Fig. 6. The influence of geographical distribution of ginger on metabolites content.
FIGURE 5 in The genus Tibicina Kolenati, 1857 in Morocco (Hemiptera: Cicadidae: Tibicininae): taxonomic assessment from integrative research
FIGURE 5. Male of T. q. pilleti Puissant ssp. n. in calling posture.
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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)
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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.