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325 results for “best practice”
Fig. 13 in Consortium of European TaXonomic Facilities (CETAF) best practices in electronic publishing in taXonomy
Fig. 13. The authorships highlighted in yellow are cited nowhere else in the article and yet they are listed in the references section (Schott & Evans 2016).
Fig. 12 in Consortium of European TaXonomic Facilities (CETAF) best practices in electronic publishing in taXonomy
Fig. 12. Here "Bleeker, 1857" is considered by the authors as a bibliographical reference and listed as such under the references section although it has not been cited elsewhere in the text (Tucker et al. 2016).
Fig. 6 in Consortium of European TaXonomic Facilities (CETAF) best practices in electronic publishing in taXonomy
Fig. 6. Authorships formally presented as references, those in yellow are listed in the references section whereas those in orange are not considered as bibliographic references. A. Musavu Moussavou (2017). B. Mendoza-Garfias et al. (2017).
Fig. 2 in Consortium of European TaXonomic Facilities (CETAF) best practices in electronic publishing in taXonomy
Fig. 2. Here, "Whalen (1989)" is cited in the taxonomic treatment but not listed in the references section (Knapp et al. 2017).
Fig. 11 in Consortium of European TaXonomic Facilities (CETAF) best practices in electronic publishing in taXonomy
Fig. 11. Underlined in blue are the references linked to the bibliography (considered as such because they are cited in an unambiguous way elsewhere in the text) whereas those in black are not linked because they are not listed in the bibliography (Foley et al. 2017).
Fig. 1 in Consortium of European TaXonomic Facilities (CETAF) best practices in electronic publishing in taXonomy
Fig. 1. The reference highlighted in yellow is listed under the references section, even though it has not been cited anywhere else in the article (Coritico et al. 2017).
Fig. 4 in Consortium of European TaXonomic Facilities (CETAF) best practices in electronic publishing in taXonomy
Fig. 4. The references highlighted in orange are not listed in the References section whereas the reference in yellow, because it is recent, is listed (Ardenghi et al. 2016).
Fig. 3 in Consortium of European TaXonomic Facilities (CETAF) best practices in electronic publishing in taXonomy
Fig. 3. Contrary to the example in Fig. 2, and despite it being published in the same journal, here "Cholnoky 1957" is cited only in the taxonomic treatment (and nowhere else in the text) and referenced under the bibliographic section (Jahn et al. 2017).
Fig. 7 in Consortium of European TaXonomic Facilities (CETAF) best practices in electronic publishing in taXonomy
Fig. 7. In this article the reference highlighted in orange indicates a reference that is only cited under taxonomic treatment and listed under the references section; in yellow a reference that is cited elsewhere thus listed under the references section; in blue are the references that should have been listed but are not in the references section (Waite R. & Allmon W.D. 2016).
Fig. 9 in Consortium of European TaXonomic Facilities (CETAF) best practices in electronic publishing in taXonomy
Fig. 9. In this example the references in yellow are not provided in the bibliographic section, but the the one in green is, because it has been formally mentioned elsewhere in the article as a reference (Rakotondrainibe & Jouy 2016).
Fig. 10 in Consortium of European TaXonomic Facilities (CETAF) best practices in electronic publishing in taXonomy
Fig. 10. In this article "Utinomi 1958" is cited only in the taxonomic treatment (but nowhere else in the text) and referenced in the bibliographic section (Yu et al. 2017).
Fig. 5 in Consortium of European TaXonomic Facilities (CETAF) best practices in electronic publishing in taXonomy
Fig. 5. Authorship formally presented as a reference. A. Kim et al. (2017). B. Lanteri & del Rio (2017).
Fig. 8 in Consortium of European TaXonomic Facilities (CETAF) best practices in electronic publishing in taXonomy
Fig. 8. All authorships cited highlighted in yellow are listed in the references section even though they are not cited as a bibliographic reference anywhere else in the text (Pole & McLoughlin 2017).
Agricultural plastic pollution reduces soil function even under best management practices
Open the record for dataset details and reuse information.
Fig. 3.2 in Handbook of best practice and standards for 2D+ and 3D imaging of natural history collections
Fig. 3.2. Camera positions of a single rotation when taking pictures of an object.
Fig. 4.1 in Handbook of best practice and standards for 2D+ and 3D imaging of natural history collections
Fig. 4.1. Scorpion pictured in UV fluorescence. Focus stacking image.
Fig. 2.14 in Handbook of best practice and standards for 2D+ and 3D imaging of natural history collections
Fig. 2.14. Picture of a quickly composed image of a mite at 20× magnification.
Best-practice forestry management delivers diminishing returns for coral reefs with increased land-clearing
<p>Protection of coastal ecosystems from deforestation may be the best way to protect coral reefs from sediment runoff. However, given the importance of generating economic activities for coastal livelihoods, the prohibition of development is often not feasible. In light of this, logging codes-of-practice have been developed to mitigate the impacts of logging on downstream ecosystems. However, no studies have assessed whether managed land-clearing can occur in tandem with coral reef conservation goals.</p> <p>This study quantifies the impacts of current land use and the risk of potential logging activities on downstream coral reef condition and fisheries using a novel suite of linked land-sea models, using Kolombangara Island in the Solomon Islands as a case study. Further, we examine the ability of erosion reduction strategies stipulated in logging codes-of-practice to reduce these impacts as clearing extent increases.</p> <p>We found that with present-day land use, reductions in live and branching coral cover and increases in turf algae were associated with exposure to sediment runoff from catchments and log ponds. Critically, reductions in fish grazer abundance and biomass were associated with increasing sediment runoff, a functional group that accounts for ~25% of subsistence fishing. At low clearing extents, although best management practices minimises the exposure of coral reefs to increased runoff, it would still result in 32% of the reef experiencing an increase in sediment exposure. If clearing extent increased, best management practices would have no impact, with a staggering 89% of coral reef area at risk compared to logging with no management.</p> <p>Synthesis and applications: Assessing trade-offs between coastal development and protection of marine resources is a challenge for decision makers globally. Although development activities requiring clearing can be important for livelihoods, our results demonstrate that new logging in intact forest risks downstream resources important for both food and livelihood security. Importantly, our approach allows for spatially-explicit recommendations for where terrestrial management might best complement marine management. Finally, given the critical degradation feedback loops that increased sediment runoff can reinforce on coral reefs, minimising sediment runoff could play an important role in helping coral reefs recover from climate-related disturbances.</p>
Data from: A universal tool for marine metazoan species identification – Towards best practices in proteomic fingerprinting
<p><span>Proteomic fingerprinting using MALDI-TOF mass spectrometry is a well-established tool for identifying microorganisms and has shown promising results for identification of animal species, particularly disease vectors and marine organisms. However, few studies have tested species identification across different orders and classes. In this study, we collected data from 1,246 specimens and 198 species to test species identification in a diverse dataset. We also evaluated different specimen preparation and data processing approaches for machine learning and developed a workflow to optimize classification using random forest. Our results showed high success rates of over 90%, but we also found that the size of the reference library affects classification error. Additionally, we demonstrated the ability of the method to differentiate marine cryptic-species complexes and to distinguish sexes within species.</span></p>
Data from: Advances and shortfalls in applying best practices to global tree-growing efforts
<p>As global tree-growing efforts have escalated in the past decade, copious failures and unintended consequences have prompted many reforestation best practices guidelines. The extent to which organizations have integrated these ecological and socioeconomic recommendations, however, remains uncertain. We reviewed websites of 99 intermediary organizations that promote and fund tree-growing projects to determine how well they report following best practices. Nearly half the organizations stated tree or area planting targets, but only 25% had measurable, time-bound objectives. Most organizations discussed the benefits local communities would receive from trees, but only 38% reported measures of these outcomes. Non-profit organizations with greater prior experience converged more closely on best practices, and their level of scientific expertise was positively associated with clearer project selection standards. Although many tree-growing organizations acknowledge the importance of clear goals, local community involvement, and monitoring, our results raise questions regarding whether long-term benefits are being achieved and emphasize the need for stronger public accountability standards.</p>
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.