#scilit — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #scilit, aggregated by home.social.
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Simplifying process models to reduce processing time and feed other models, soil temperature with depth at a daily resolution is well (within 1-2 degrees) approximated with simplified with biomass, air temperature, and thermal diffusion. Parton 1984 https://journals.lww.com/soilsci/abstract/1984/08000/predicting_soil_temperatures_in_a_shortgrass.1.aspx #SciLit #ReducedComplexityModel #SoilTemperatureResponse #soil
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Simplifying process models to reduce processing time and feed other models, soil temperature with depth at a daily resolution is well (within 1-2 degrees) approximated with simplified with biomass, air temperature, and thermal diffusion. Parton 1984 https://journals.lww.com/soilsci/abstract/1984/08000/predicting_soil_temperatures_in_a_shortgrass.1.aspx #SciLit #ReducedComplexityModel #SoilTemperatureResponse #soil
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Simplifying process models to reduce processing time and feed other models, soil temperature with depth at a daily resolution is well (within 1-2 degrees) approximated with simplified with biomass, air temperature, and thermal diffusion. Parton 1984 https://journals.lww.com/soilsci/abstract/1984/08000/predicting_soil_temperatures_in_a_shortgrass.1.aspx #SciLit #ReducedComplexityModel #SoilTemperatureResponse #soil
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Simplifying process models to reduce processing time and feed other models, soil temperature with depth at a daily resolution is well (within 1-2 degrees) approximated with simplified with biomass, air temperature, and thermal diffusion. Parton 1984 https://journals.lww.com/soilsci/abstract/1984/08000/predicting_soil_temperatures_in_a_shortgrass.1.aspx #SciLit #ReducedComplexityModel #SoilTemperatureResponse #soil
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Simplifying process models to reduce processing time and feed other models, soil temperature with depth at a daily resolution is well (within 1-2 degrees) approximated with simplified with biomass, air temperature, and thermal diffusion. Parton 1984 https://journals.lww.com/soilsci/abstract/1984/08000/predicting_soil_temperatures_in_a_shortgrass.1.aspx #SciLit #ReducedComplexityModel #SoilTemperatureResponse #soil
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Communicating models and their outputs is often challenging. PAVE (Purpose, Assumptions, Validity, and Exploration) is a semi-structured description of computational and mathematical models designed to bridge the communication boundary between modelers and non-modelers. Bell et al 2026 https://doi.org/10.1093/biosci/biag010 #Models #HowToScience #SciLit
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Communicating models and their outputs is often challenging. PAVE (Purpose, Assumptions, Validity, and Exploration) is a semi-structured description of computational and mathematical models designed to bridge the communication boundary between modelers and non-modelers. Bell et al 2026 https://doi.org/10.1093/biosci/biag010 #Models #HowToScience #SciLit
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Communicating models and their outputs is often challenging. PAVE (Purpose, Assumptions, Validity, and Exploration) is a semi-structured description of computational and mathematical models designed to bridge the communication boundary between modelers and non-modelers. Bell et al 2026 https://doi.org/10.1093/biosci/biag010 #Models #HowToScience #SciLit
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Communicating models and their outputs is often challenging. PAVE (Purpose, Assumptions, Validity, and Exploration) is a semi-structured description of computational and mathematical models designed to bridge the communication boundary between modelers and non-modelers. Bell et al 2026 https://doi.org/10.1093/biosci/biag010 #Models #HowToScience #SciLit
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Communicating models and their outputs is often challenging. PAVE (Purpose, Assumptions, Validity, and Exploration) is a semi-structured description of computational and mathematical models designed to bridge the communication boundary between modelers and non-modelers. Bell et al 2026 https://doi.org/10.1093/biosci/biag010 #Models #HowToScience #SciLit
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NASA's #data collection has undergone massive shifts in lifecycle management, #FAIR_data, technological trends, and policy. Evolving from 1980s magnetic tapes to a network of over 30 online repositories, the tech trends are easiest to identify. Adoption of #DataPipeline and #DataStandards an ongoing focus. #DataGovernance and #DataRescue are emerging. NASA #DataStewardship navigates rapid technology and long-term science.
Bugbee, K., & Ramachandran, R. (2025) https://doi.org/10.1029/2025EA004413 #SciLit
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NASA's #data collection has undergone massive shifts in lifecycle management, #FAIR_data, technological trends, and policy. Evolving from 1980s magnetic tapes to a network of over 30 online repositories, the tech trends are easiest to identify. Adoption of #DataPipeline and #DataStandards an ongoing focus. #DataGovernance and #DataRescue are emerging. NASA #DataStewardship navigates rapid technology and long-term science.
Bugbee, K., & Ramachandran, R. (2025) https://doi.org/10.1029/2025EA004413 #SciLit
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NASA's #data collection has undergone massive shifts in lifecycle management, #FAIR_data, technological trends, and policy. Evolving from 1980s magnetic tapes to a network of over 30 online repositories, the tech trends are easiest to identify. Adoption of #DataPipeline and #DataStandards an ongoing focus. #DataGovernance and #DataRescue are emerging. NASA #DataStewardship navigates rapid technology and long-term science.
Bugbee, K., & Ramachandran, R. (2025) https://doi.org/10.1029/2025EA004413 #SciLit
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NASA's #data collection has undergone massive shifts in lifecycle management, #FAIR_data, technological trends, and policy. Evolving from 1980s magnetic tapes to a network of over 30 online repositories, the tech trends are easiest to identify. Adoption of #DataPipeline and #DataStandards an ongoing focus. #DataGovernance and #DataRescue are emerging. NASA #DataStewardship navigates rapid technology and long-term science.
Bugbee, K., & Ramachandran, R. (2025) https://doi.org/10.1029/2025EA004413 #SciLit
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NASA's #data collection has undergone massive shifts in lifecycle management, #FAIR_data, technological trends, and policy. Evolving from 1980s magnetic tapes to a network of over 30 online repositories, the tech trends are easiest to identify. Adoption of #DataPipeline and #DataStandards an ongoing focus. #DataGovernance and #DataRescue are emerging. NASA #DataStewardship navigates rapid technology and long-term science.
Bugbee, K., & Ramachandran, R. (2025) https://doi.org/10.1029/2025EA004413 #SciLit
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Operationalize CARE data governance by 1) centering relationships both individual and institutional, 2) practicing ongoing learning and assessment of governance, 3) collaborative permitting including shared protocols, and 4) documentation of governance reflected in metadata and naming. Jennings et al 2025 https://doi.org/10.1038/s41467-024-53480-2 #DataGovernance #CAREData #OperationalEthics #SciLit
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Operationalize CARE data governance by 1) centering relationships both individual and institutional, 2) practicing ongoing learning and assessment of governance, 3) collaborative permitting including shared protocols, and 4) documentation of governance reflected in metadata and naming. Jennings et al 2025 https://doi.org/10.1038/s41467-024-53480-2 #DataGovernance #CAREData #OperationalEthics #SciLit
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Operationalize CARE data governance by 1) centering relationships both individual and institutional, 2) practicing ongoing learning and assessment of governance, 3) collaborative permitting including shared protocols, and 4) documentation of governance reflected in metadata and naming. Jennings et al 2025 https://doi.org/10.1038/s41467-024-53480-2 #DataGovernance #CAREData #OperationalEthics #SciLit
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Operationalize CARE data governance by 1) centering relationships both individual and institutional, 2) practicing ongoing learning and assessment of governance, 3) collaborative permitting including shared protocols, and 4) documentation of governance reflected in metadata and naming. Jennings et al 2025 https://doi.org/10.1038/s41467-024-53480-2 #DataGovernance #CAREData #OperationalEthics #SciLit
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Operationalize CARE data governance by 1) centering relationships both individual and institutional, 2) practicing ongoing learning and assessment of governance, 3) collaborative permitting including shared protocols, and 4) documentation of governance reflected in metadata and naming. Jennings et al 2025 https://doi.org/10.1038/s41467-024-53480-2 #DataGovernance #CAREData #OperationalEthics #SciLit
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The ARID project scoped a possible new #dryland focused project area for NASA. Emerging high resolution spatial-temporal satellite and other data products provides new prospectives on the pulse-y hydrology that governs drylands. Drylands make up a large socially-important biome and right holder #engagement needs to be prioritized to provide #ActionableScience. Feldman etal 2024 https://doi.org/10.1029/2024EF004811 #SciLit
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The ARID project scoped a possible new #dryland focused project area for NASA. Emerging high resolution spatial-temporal satellite and other data products provides new prospectives on the pulse-y hydrology that governs drylands. Drylands make up a large socially-important biome and right holder #engagement needs to be prioritized to provide #ActionableScience. Feldman etal 2024 https://doi.org/10.1029/2024EF004811 #SciLit
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The ARID project scoped a possible new #dryland focused project area for NASA. Emerging high resolution spatial-temporal satellite and other data products provides new prospectives on the pulse-y hydrology that governs drylands. Drylands make up a large socially-important biome and right holder #engagement needs to be prioritized to provide #ActionableScience. Feldman etal 2024 https://doi.org/10.1029/2024EF004811 #SciLit
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The ARID project scoped a possible new #dryland focused project area for NASA. Emerging high resolution spatial-temporal satellite and other data products provides new prospectives on the pulse-y hydrology that governs drylands. Drylands make up a large socially-important biome and right holder #engagement needs to be prioritized to provide #ActionableScience. Feldman etal 2024 https://doi.org/10.1029/2024EF004811 #SciLit
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The ARID project scoped a possible new #dryland focused project area for NASA. Emerging high resolution spatial-temporal satellite and other data products provides new prospectives on the pulse-y hydrology that governs drylands. Drylands make up a large socially-important biome and right holder #engagement needs to be prioritized to provide #ActionableScience. Feldman etal 2024 https://doi.org/10.1029/2024EF004811 #SciLit
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Training PhD students often follows ‘magician’s apprentice’ approach where advisors taking hands-on/off approach but rarely have a more nuanced language to discuss the advising journey. Wagner etal 2017 https://www.facetsjournal.com/doi/10.1139/facets-2015-0013 introduces stages 1) enthusiastic beginner, 2) discouraged learner, 3) cautious performer, and 4) self-reliant achiever. They frame roles and strategies for each stage for both the mentor and mentee and provide worksheets in their SI. #HowToScience #Mentoring #SciLit
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Training PhD students often follows ‘magician’s apprentice’ approach where advisors taking hands-on/off approach but rarely have a more nuanced language to discuss the advising journey. Wagner etal 2017 https://www.facetsjournal.com/doi/10.1139/facets-2015-0013 introduces stages 1) enthusiastic beginner, 2) discouraged learner, 3) cautious performer, and 4) self-reliant achiever. They frame roles and strategies for each stage for both the mentor and mentee and provide worksheets in their SI. #HowToScience #Mentoring #SciLit
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Training PhD students often follows ‘magician’s apprentice’ approach where advisors taking hands-on/off approach but rarely have a more nuanced language to discuss the advising journey. Wagner etal 2017 https://www.facetsjournal.com/doi/10.1139/facets-2015-0013 introduces stages 1) enthusiastic beginner, 2) discouraged learner, 3) cautious performer, and 4) self-reliant achiever. They frame roles and strategies for each stage for both the mentor and mentee and provide worksheets in their SI. #HowToScience #Mentoring #SciLit
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Training PhD students often follows ‘magician’s apprentice’ approach where advisors taking hands-on/off approach but rarely have a more nuanced language to discuss the advising journey. Wagner etal 2017 https://www.facetsjournal.com/doi/10.1139/facets-2015-0013 introduces stages 1) enthusiastic beginner, 2) discouraged learner, 3) cautious performer, and 4) self-reliant achiever. They frame roles and strategies for each stage for both the mentor and mentee and provide worksheets in their SI. #HowToScience #Mentoring #SciLit
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Training PhD students often follows ‘magician’s apprentice’ approach where advisors taking hands-on/off approach but rarely have a more nuanced language to discuss the advising journey. Wagner etal 2017 https://www.facetsjournal.com/doi/10.1139/facets-2015-0013 introduces stages 1) enthusiastic beginner, 2) discouraged learner, 3) cautious performer, and 4) self-reliant achiever. They frame roles and strategies for each stage for both the mentor and mentee and provide worksheets in their SI. #HowToScience #Mentoring #SciLit
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Agroecosystem is a promising shift in how we feed ourselves that has been under developed outside of academia for a number of political and economic reasons. Scientists, food security advocates, and social justice organizations need to rethink how we can leverage an integrated understanding of social and ecological systems to feed ourselves in the future. (Ong etal 2024 https://doi.org/10.1038/s43016-024-01006-w)
#agroecosystem #ecology #agricultural #TheoryOfChange #SciLit
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Agroecosystem is a promising shift in how we feed ourselves that has been under developed outside of academia for a number of political and economic reasons. Scientists, food security advocates, and social justice organizations need to rethink how we can leverage an integrated understanding of social and ecological systems to feed ourselves in the future. (Ong etal 2024 https://doi.org/10.1038/s43016-024-01006-w)
#agroecosystem #ecology #agricultural #TheoryOfChange #SciLit
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Agroecosystem is a promising shift in how we feed ourselves that has been under developed outside of academia for a number of political and economic reasons. Scientists, food security advocates, and social justice organizations need to rethink how we can leverage an integrated understanding of social and ecological systems to feed ourselves in the future. (Ong etal 2024 https://doi.org/10.1038/s43016-024-01006-w)
#agroecosystem #ecology #agricultural #TheoryOfChange #SciLit
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Agroecosystem is a promising shift in how we feed ourselves that has been under developed outside of academia for a number of political and economic reasons. Scientists, food security advocates, and social justice organizations need to rethink how we can leverage an integrated understanding of social and ecological systems to feed ourselves in the future. (Ong etal 2024 https://doi.org/10.1038/s43016-024-01006-w)
#agroecosystem #ecology #agricultural #TheoryOfChange #SciLit
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Agroecosystem is a promising shift in how we feed ourselves that has been under developed outside of academia for a number of political and economic reasons. Scientists, food security advocates, and social justice organizations need to rethink how we can leverage an integrated understanding of social and ecological systems to feed ourselves in the future. (Ong etal 2024 https://doi.org/10.1038/s43016-024-01006-w)
#agroecosystem #ecology #agricultural #TheoryOfChange #SciLit
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New study: "Non-selective databases (#Dimensions, #OpenAlex, #Scilit, and #TheLens) index a greater amount of retracted literature than do databases that rely their indexation on venue selection (#PubMed, #Scopus, and #WoS)…The high coverage of OpenAlex and Scilit could be explained by the inaccurate labeling of retracted documents in #Scopus, Dimensions, and The Lens."
https://link.springer.com/article/10.1007/s11192-024-05034-y -
New study: "Non-selective databases (#Dimensions, #OpenAlex, #Scilit, and #TheLens) index a greater amount of retracted literature than do databases that rely their indexation on venue selection (#PubMed, #Scopus, and #WoS)…The high coverage of OpenAlex and Scilit could be explained by the inaccurate labeling of retracted documents in #Scopus, Dimensions, and The Lens."
https://link.springer.com/article/10.1007/s11192-024-05034-y -
New study: "Non-selective databases (#Dimensions, #OpenAlex, #Scilit, and #TheLens) index a greater amount of retracted literature than do databases that rely their indexation on venue selection (#PubMed, #Scopus, and #WoS)…The high coverage of OpenAlex and Scilit could be explained by the inaccurate labeling of retracted documents in #Scopus, Dimensions, and The Lens."
https://link.springer.com/article/10.1007/s11192-024-05034-y -
New study: "Non-selective databases (#Dimensions, #OpenAlex, #Scilit, and #TheLens) index a greater amount of retracted literature than do databases that rely their indexation on venue selection (#PubMed, #Scopus, and #WoS)…The high coverage of OpenAlex and Scilit could be explained by the inaccurate labeling of retracted documents in #Scopus, Dimensions, and The Lens."
https://link.springer.com/article/10.1007/s11192-024-05034-y -
New study: "Non-selective databases (#Dimensions, #OpenAlex, #Scilit, and #TheLens) index a greater amount of retracted literature than do databases that rely their indexation on venue selection (#PubMed, #Scopus, and #WoS)…The high coverage of OpenAlex and Scilit could be explained by the inaccurate labeling of retracted documents in #Scopus, Dimensions, and The Lens."
https://link.springer.com/article/10.1007/s11192-024-05034-y -
Flat teams drive scientific innovation, moving beyond team size Xu etal 2022 (https://www.pnas.org/doi/pdf/10.1073/pnas.2200927119) looked at reported contribution, contextual authorship records, and author ordering to disentangle + quantify relative leadership contributions. Tall teams maximize immediate benefits to senior leads, flat teams were more innovative. #TeamScience #SciLit
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Flat teams drive scientific innovation, moving beyond team size Xu etal 2022 (https://www.pnas.org/doi/pdf/10.1073/pnas.2200927119) looked at reported contribution, contextual authorship records, and author ordering to disentangle + quantify relative leadership contributions. Tall teams maximize immediate benefits to senior leads, flat teams were more innovative. #TeamScience #SciLit
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Flat teams drive scientific innovation, moving beyond team size Xu etal 2022 (https://www.pnas.org/doi/pdf/10.1073/pnas.2200927119) looked at reported contribution, contextual authorship records, and author ordering to disentangle + quantify relative leadership contributions. Tall teams maximize immediate benefits to senior leads, flat teams were more innovative. #TeamScience #SciLit
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Flat teams drive scientific innovation, moving beyond team size Xu etal 2022 (https://www.pnas.org/doi/pdf/10.1073/pnas.2200927119) looked at reported contribution, contextual authorship records, and author ordering to disentangle + quantify relative leadership contributions. Tall teams maximize immediate benefits to senior leads, flat teams were more innovative. #TeamScience #SciLit
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Flat teams drive scientific innovation, moving beyond team size Xu etal 2022 (https://www.pnas.org/doi/pdf/10.1073/pnas.2200927119) looked at reported contribution, contextual authorship records, and author ordering to disentangle + quantify relative leadership contributions. Tall teams maximize immediate benefits to senior leads, flat teams were more innovative. #TeamScience #SciLit
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Socio-environmental design process for a just climate transition seeking to be community centered and adaptive rather the proscriptive, this approach blends complexity theory with social justice. Enfors-Kaustky etal 2021 https://www.ecologyandsociety.org/vol26/iss2/art39/ #JustTransition #ClimateChange #SciLit
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Socio-environmental design process for a just climate transition seeking to be community centered and adaptive rather the proscriptive, this approach blends complexity theory with social justice. Enfors-Kaustky etal 2021 https://www.ecologyandsociety.org/vol26/iss2/art39/ #JustTransition #ClimateChange #SciLit
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Socio-environmental design process for a just climate transition seeking to be community centered and adaptive rather the proscriptive, this approach blends complexity theory with social justice. Enfors-Kaustky etal 2021 https://www.ecologyandsociety.org/vol26/iss2/art39/ #JustTransition #ClimateChange #SciLit
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Socio-environmental design process for a just climate transition seeking to be community centered and adaptive rather the proscriptive, this approach blends complexity theory with social justice. Enfors-Kaustky etal 2021 https://www.ecologyandsociety.org/vol26/iss2/art39/ #JustTransition #ClimateChange #SciLit
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Socio-environmental design process for a just climate transition seeking to be community centered and adaptive rather the proscriptive, this approach blends complexity theory with social justice. Enfors-Kaustky etal 2021 https://www.ecologyandsociety.org/vol26/iss2/art39/ #JustTransition #ClimateChange #SciLit
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Simplified land carbon model is consistent with global data products and allows for unique structural and parameter uncertainty analysis. Smith et al 2013 https://bg.copernicus.org/articles/10/583/2013/ #LandCarbon #GlobalModel #ModelingMethod #SciLit
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Simplified land carbon model is consistent with global data products and allows for unique structural and parameter uncertainty analysis. Smith et al 2013 https://bg.copernicus.org/articles/10/583/2013/ #LandCarbon #GlobalModel #ModelingMethod #SciLit
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Simplified land carbon model is consistent with global data products and allows for unique structural and parameter uncertainty analysis. Smith et al 2013 https://bg.copernicus.org/articles/10/583/2013/ #LandCarbon #GlobalModel #ModelingMethod #SciLit
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Simplified land carbon model is consistent with global data products and allows for unique structural and parameter uncertainty analysis. Smith et al 2013 https://bg.copernicus.org/articles/10/583/2013/ #LandCarbon #GlobalModel #ModelingMethod #SciLit
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Simplified land carbon model is consistent with global data products and allows for unique structural and parameter uncertainty analysis. Smith et al 2013 https://bg.copernicus.org/articles/10/583/2013/ #LandCarbon #GlobalModel #ModelingMethod #SciLit
