Study Abroad Strengths-Based Curriculum: Advancing Self-Reflection and Relationship-Building Leadership Skills

Immersion in a strengths-based, study abroad program provided extensive opportunity for leadership growth. Navigating the unknown added to the challenge students experienced during their student-organized activities. The purpose of this qualitative study was to explore how a strengths-based curricula design advanced the leadership competency levels of self-reflection and relationship building during a graduate, short-term study abroad program. The findings show before and during the program, self-reflection led to thoughtful discussions, which led to valuing differences. Self-reflection contributed to deeper self-awareness of how an individual’s primary strengths and blind spots led to mutual respect. On-going mutual respect enhanced relationships through appreciation for diversity. The strengths-based knowledge aided in acknowledging and valuing differences in one another, which positively impacted relationships

Leadership As We Know It

Leadership as We Know it is a collection of insights into modern leadership compiled by graduate students in Winona State University’s Leadership Education program during the Spring 2019 semester in a course aptly titled, Change Leadership. Each chapter was penned by one of 20 unique class members who offer their vision of leadership based upon their eclectic personal backgrounds and professional experiences, whose fields include athletics, business, education, and more. These diverse narratives offer something for everyone; whether it be a veteran or blossoming leader eager to continue their growth and evolution. Leadership as We Know it provides accounts from seasoned professionals who oversee their own organizational departments as well as emerging leaders just beginning their careers. Throughout these unique stories, clear patterns will emerge for the reader in what it takes to inspire change and provide authentic leadership for followers.https://openriver.winona.edu/leadershipeducationbooks/1003/thumbnail.jp

Global dataset of soil organic carbon in tidal marshes

International audienceAbstract Tidal marshes store large amounts of organic carbon in their soils. Field data quantifying soil organic carbon (SOC) stocks provide an important resource for researchers, natural resource managers, and policy-makers working towards the protection, restoration, and valuation of these ecosystems. We collated a global dataset of tidal marsh soil organic carbon (MarSOC) from 99 studies that includes location, soil depth, site name, dry bulk density, SOC, and/or soil organic matter (SOM). The MarSOC dataset includes 17,454 data points from 2,329 unique locations, and 29 countries. We generated a general transfer function for the conversion of SOM to SOC. Using this data we estimated a median (± median absolute deviation) value of 79.2 ± 38.1 Mg SOC ha −1 in the top 30 cm and 231 ± 134 Mg SOC ha −1 in the top 1 m of tidal marsh soils globally. This data can serve as a basis for future work, and may contribute to incorporation of tidal marsh ecosystems into climate change mitigation and adaptation strategies and policies

Global dataset of soil organic carbon in tidal marshes.

Funder: The Nature Conservancy through the Bezos Earth Fund and other donor supportFunder: Nelson Mandela UniversityFunder: State Research Agency of Spain (AEI; CGL2007-64915), the Mancomunidad de los Canales del Taibilla (MCT), and the Science and Technology Agency of the Murcia Region (Seneca Foundation; 00593/PI/04 & 08739/PI/08).Funder: Scottish Government and UK Natural Environment Research Council C-SIDE project (grant NE/R010846/1)Funder: COOLSTYLE/CARBOSTORE projectFunder: New Zealand Ministry for Business, Innovation and Employment Contract #C01X2109Funder: Portuguese national funds from FCT - Foundation for Science and Technology through projects UIDB/04326/2020, UIDP/04326/2020, LA/P/0101/2020, and 2020.03825.CEECINDFunder: German Research Foundation (DFG project number: GI 171/25-1)Funder: State Research Agency of Spain (AEI; CGL2007-64915), the Mancomunidad de los Canales del Taibilla (MCT), the Science and Technology Agency of the Murcia Region (Seneca Foundation; 00593/PI/04 & 08739/PI/08), and a Ramón y Cajal contract from the Spanish Ministry of Science and Innovation (RYC2020-029322-I)Funder: Velux foundation (#28421, Blå Skove – Havets Skove som kulstofdræn)Funder: LIFE ADAPTA BLUES project Ref. LIFE18 CCA/ES/001160Funder: LIFE ADAPTA BLUES project Ref. LIFE18 CCA/ES/001160, support of national funds through Fundação para a Ciência e Tecnologia, I.P. (FCT), under the projects UIDB/04292/2020, UIDP/04292/2020, granted to MARE, and LA/P/0069/2020, granted to the Associate Laboratory ARNETFunder: Financial support provided by the Welsh Government and Higher Education Funding Council for Wales through the Sêr Cymru National Research Network for Low Carbon, Energy and Environment; as well as the Spanish Ministry of Science and Innovation (project PID2020-113745RB-I00) and FEDERFunder: South African Department of Science and Innovation (DSI)—National Research Foundation (NRF) Research Chair in Shallow Water Ecosystems (UID: 84375), and the Nelson Mandela UniversityFunder: I+D+i projects RYC2019-027073-I and PIE HOLOCENO 20213AT014 funded by MCIN/AEI/10.13039/501100011033 and FEDERFunder: Funding support from the Scottish Government and UK Natural Environment Research Council C-SIDE project (grant NE/R010846/1)Funder: Xunta de Galicia (GRC project IN607A 2021-06)Funder: U.S. Army Engineering, Research and Development Center (ACTIONS project, W912HZ2020070)Tidal marshes store large amounts of organic carbon in their soils. Field data quantifying soil organic carbon (SOC) stocks provide an important resource for researchers, natural resource managers, and policy-makers working towards the protection, restoration, and valuation of these ecosystems. We collated a global dataset of tidal marsh soil organic carbon (MarSOC) from 99 studies that includes location, soil depth, site name, dry bulk density, SOC, and/or soil organic matter (SOM). The MarSOC dataset includes 17,454 data points from 2,329 unique locations, and 29 countries. We generated a general transfer function for the conversion of SOM to SOC. Using this data we estimated a median (± median absolute deviation) value of 79.2 ± 38.1 Mg SOC ha-1 in the top 30 cm and 231 ± 134 Mg SOC ha-1 in the top 1 m of tidal marsh soils globally. This data can serve as a basis for future work, and may contribute to incorporation of tidal marsh ecosystems into climate change mitigation and adaptation strategies and policies

Global dataset of soil organic carbon in tidal marshes

Funding: W.E.N.A. and C.S. would like to acknowledge funding support from the Scottish Government and UK Natural Environment Research Council C-SIDE project (grant NE/R010846/1).Tidal marshes store large amounts of organic carbon in their soils. Field data quantifying soil organic carbon (SOC) stocks provide an important resource for researchers, natural resource managers, and policy-makers working towards the protection, restoration, and valuation of these ecosystems. We collated a global dataset of tidal marsh soil organic carbon (MarSOC) from 99 studies that includes location, soil depth, site name, dry bulk density, SOC, and/or soil organic matter (SOM). The MarSOC dataset includes 17,454 data points from 2,329 unique locations, and 29 countries. We generated a general transfer function for the conversion of SOM to SOC. Using this data we estimated a median (± median absolute deviation) value of 79.2±38.1 Mg SOC ha−1 in the top 30cm and 231±134 Mg SOC ha−1 in the top 1m of tidal marsh soils globally. This data can serve as a basis for future work, and may contribute to incorporation of tidal marsh ecosystems into climate change mitigation and adaptation strategies and policies.Publisher PDFPeer reviewe

Database: Tidal Marsh Soil Organic Carbon (MarSOC) Dataset

The repository is formatted in the following structure: - README.md: markdown file with repository description - MarSOC-Dataset.Rproj: R project file - useful when using RStudio - Maxwell_MarSOC_dataset.csv: .csv file containing the final dataset. The data structure is described in the metadata file. It contains 17,454 records distributed amongst 29 countries. - Maxwell_MarSOC_dataset_metadata.csv: .csv file containing the main data file metadata (equivalent to Table 1). - data_paper/: folder containing the list of studies included in the dataset, as well as figures for this data paper (generated from the following R script: ‘reports/04_data_process/scripts/04_data-paper_data_clean.R’). - reports/01_litsearchr/: folder containing .bib files with references from the original naive search, a .Rmd document describing the litsearchr analysis using nodes to go from the naive search to the final search string, and the .bib files from this final search, which were then imported into sysrev for abstract screening. - reports/02_sysrev/: folder with .csv files exported from sysrev after abstract screening. These files contain the included studies with their various labels. - reports/03_data_format/: folder containing all original data, associated scripts, and exported data. - reports/04_data_process/: folder containing data processing scripts to bind and clean the exported data, as well as a script testing the different models for predicting soil organic carbon from organic matter and finalising the equation using all available data. A script testing and removing outliers is also included