Abstract:
The social ecological system of the United States Virgin Islands is vulnerable to external stressors such as natural hazards and climate change. Achieving sustainability of this system involves coordination between the major ecosystems (forests, guts/ghuts, mangroves, beaches, salt ponds/salt flats, coral reefs, seagrass beds), local resource managers, and resource actors. However, the perceptions of the resource actors towards these ecosystems have not been sufficiently documented, and generally are thought to be limited. This study sought to identify the perceptions of ecosystems in the USVI through surveys of residents of St. Thomas, and then to compare those perceptions to governing documents of the territory. A sample of 384 respondents were surveyed from March 25th, 2024 - May 30th, 2024 to collect perceptions of the seven ecosystems ranging from perceptions of ecosystem services, perceptions of ecosystem health and perceptions of ecosystem importance. The dataset contains anonymized survey data, codes created for sub-themes and themes present in the open ended responses while analyzing the survey data using the qualitative analysis software MAXQDA, and a codebook for the definition of each of the codes.
Suggested Citation:
Dijani Laplace. Community Perceptions of Ecosystems in St. Thomas, U.S Virgin Islands. Distributed by: GRIIDC, Harte Research Institute, Texas A&M University–Corpus Christi. doi:10.7266/jcyz0n9k
Purpose:
This data was acquired for fulfilling the requirements for a Masters Thesis by Dijani Laplace. Citation: Laplace, D. (2024). Community perceptions of ecosystems in St. Thomas, U.S. Virgin Islands (Publication No. 31640863) [Master's Thesis, Texas A&M University-Corpus Christi]. ProQuest Dissertations and Theses Global.
The purpose for acquiring this data for the master's thesis was to establish the community perceptions of ecosystems in the U.S. Virgin Islands, using St. Thomas as the study site, and then determine whether any of those perceptions were reflected in the governing documents of the territory or not.
Methods:
Governing Document Selection and Survey Creation
The initial step of this methodology was to select the governing documents. Governing documents were selected for two major purposes: to create a list of documents to be used for the qualitative portion of this analysis, and to create a rubric to inform the creation of the survey to collect perceptions of residents.
Governing documents included territorial laws, policies, other documents guided in large part by territorial laws or policies or other technical documentation about the territory’s ecosystems and natural resources. They did not include any documents that were not created or commissioned by a territorial government agency, were not created before 2000, any federal documentation, or peer-reviewed literature.
Deductive Content Analysis
Preliminary governing documents were selected after consultation with an employee of the Department of Planning and Natural Resources and were subjected to a deductive content analysis. This analysis was done using the MAXQDA Analytics Pro, which is software that is predominantly used for qualitative analysis involving text, interviews, videos, voice recordings webpages, etc. (Kukartz & Radiker, 2019). The analysis was centered around identifying the presence of four core themes in each preliminary governing document: management terms, ecosystems, ecosystem services, and negative impacts to ecosystems. Sub-themes were created for each theme, and the presence or absence of these sub-themes were used to determine the presence of the overarching theme. The final governing document list consisted of documents were three out of the four themes were present. In total, 20 documents were selected as governing documents, and these documents constituted the qualitative component of this approach that were used later in the integration step.
Survey Distribution
A survey instrument approved by the TAMUCC Institutional Review Board (TAMU-CC IRB-2023-0987) with eight questions about the seven major ecosystems in St. Thomas was distributed to residents of St. Thomas from March 25th to May 30th, 2024. The sampling technique for survey distribution was no non-probabilistic and convenience, majorly to achieve a representative sample (at least 381 respondents at a 95% confidence interval for the population of St. Thomas which is 42,261) and to avoid the low response rate seen in other similar studies in the region (Nunez- Reyez, 2008, Gorstein et al., 2017; Allen et al., 2021; Ware, 2022). The survey consisted of quantitative and qualitative open-ended questions to more accurately capture the perceptions of respondents. A total of 384 surveys were administered majorly via in person intercepts (March 25th – April 27th), direct emails, and email lists. In person surveys were distributed by dividing St. Thomas into three sections, west, central, and east, and visiting popular locations in each section multiple times. In person participants had the option to be taken on paper copies or online using their own smartphones or a tablet provided by the researcher using the online survey tool Qualtrics. All paper surveys were uploaded to Qualtrics at the end of the survey period.
Theme Generation
At the end of the survey period, the 384 surveys were filtered based on if they were at least 67% completed and so any potential bot responses were removed. After filtering, a total of 314 surveys were uploaded into MAXQDA Analytics Pro. The direct quantitative results from the survey were tallied in MAXQDA. The responses to the open-ended questions were analyzed using an inductive thematic analysis. The inductive thematic analysis followed the six-step approach outlined by Braun & Clarke (2012) and Byrne (2022). Each response was initially grouped under one of the seven ecosystems, and then coded to create sub-themes. Each code in MAXQDA represented the occurrence of one sub-theme. Many of the sub-themes for ecosystem services specifically were informed by the Millenium Ecosystem Assessment and definitions from the BlueValue database where applicable. Some sub-themes that shared similarities were group together to formed sub-groups. When the coding process was completed, these sub-themes were grouped under three major themes: perceptions of ecosystem services, ecosystem health, and ecosystem importance. The total frequencies of the sub-themes constituted the quantitative component of this approach and were later in the analysis.