Publications & Results
|Resource Title||Brief Summary|
|Qualitative Data Recommendations for Research Institutions||
Feb 08, 2018
This is a two-page summary of key opportunities and challenges for sharing and re-using qualitative data in socio-environmental synthesis, with recommendations for actions that research institutions can take to encourage and support qualtiative data sharing and re-use.
|Qualitative Data Recommendations for Researchers||
Feb 08, 2018
This is a two-page summary of key opportunities and challenges for sharing and re-using qualitative data in socio-environmental synthesis, with recommendations for actions that individual researchers and research teams can take to encourage and support qualtiative data sharing and re-use.
|Qualitative data sharing and re-use for socio-environmental systems research: A synthesis of opportunities, challenges, resources and approaches||
Feb 01, 2018
This white paper discusses opportunities, challenges, resources and approaches for qualitative data sharing and re-use for socio-environmental research. The content and findings of the paper are a synthesis and extension of discussions that began during a workshop funded by the National Socio-Environmental Synthesis Center (SESYNC) and held at the Center Feb. 28-March 2, 2017.
|Qualitative data sharing and synthesis for sustainability science||
Nov 25, 2019
Article published in Nature Sustainability.
|Quantifying ecological and social drivers of ecological surprise||
May 02, 2018
Article published in Journal of Applied Ecology.
|Quantifying ecosystem service flows at multiple scales across the range of a long-distance migratory species||
Apr 21, 2018
Article published in Ecosystem Services.
|Quantifying Nutrient Budgets for Sustainable Nutrient Management||
Feb 19, 2020
Article published in Global Biogeochemical Cycles
|Quantifying the return on investment of social and ecological data for conservation planning||
Dec 19, 2019
Article published in Environmental Research Letters.
Jun 15, 2016
Many computing-intensive processes in R involve the repeated evaluation of a function over many items or parameter sets. These so-called embarrassingly parallel calculations can be run serially with the
The rslurm package simplifies the process of distributing this type of calculation across a computing cluster that uses the SLURM workload manager. Its main function,
|Racial coastal formation: The environmental injustice of colorblind adaptation planning for sea-level rise||
Oct 17, 2017
Article published in Geoforum.