| Code category | Code label |
|---|---|
| Data bridge | Management scale aligns with system needs |
| Data bridge | Target species data availability |
| Data bridge | Access to advanced technology and techniques |
| Data bridge | Data transparency |
| Data bridge | Abiotic data availability |
| Data bridge | Resource use data availability |
| Social bridge | Resource availability |
| Social bridge | Pre-existing conditions |
| Social bridge | Adoption incentives |
| Social bridge | Feasibility |
| Social bridge | Co-management and communication |
| Ecological bridge | Expected climate change induced range shifts |
| Ecological bridge | Distinct habitat preferences |
| Ecological bridge | Biotic indicators of target species presence |
| Ecological bridge | Abiotic indicators of target species presence |
| Ecological bridge | Highly mobile target species |
| Ecological bridge | Life history information available for target species |
| Ecological bridge | Fine-scale management appropriate for target species |
DOM bridges and barriers: systematic review and end-user survey
Literature Review
Selecting the literature that was included in this systematic review
In September 2024, a systematic search was completed using Web of Science to identify articles that discussed dynamic ocean management (DOM). Articles or documents published after this date were not included in this review. Articles were selected if they described factors contributing to the “success” of DOM, also termed here as a “bridge”, or that noted factors that should be addressed prior to using DOM approaches or support tools, also termed here as a “barrier”. In this systematic review, we coded bridges and barriers that were related to implemented or recommended DOM voluntary programs and/or enforced regulations, as well as those that were related to tool development (e.g., species spatial modeling tools such as EcoCast) that support dynamic management approaches.
During the initial search, the following table of terms were used. The “NEAR/5” operator was used to refine the search and ensure each of the terms in a given character string were found within one word of each other:
| Search term |
|---|
| Dynamic ocean management |
| Dynamic spatial management |
| Adaptive ocean management |
| Dynamic ocean closures |
Works from the primary (i.e., peer-reviewed journals) and grey literature (e.g., theses, book chapters) were included, and this initial search resulted in 292 articles. Abstracts were skimmed for relevance, and a total of 141 articles were saved for further inspection An additional search using the NOAA Federal Register was also completed. Here, documents such as policy reports and planning documents were selected. This search resulted in 483 documents. The abstracts or content summaries for each of these documents were skimmed for relevance, and an additional 10 documents were saved for a full read through. Articles were excluded if DOM was mentioned or recommended, but there was no discussion as to why. Articles were also excluded if they discussed changes or updates to environmental data sources or remote sensing tools used to develop models supporting DOM, but DOM approaches were not specifically applied, recommended, or reviewed. Specific inclusion and exclusion criteria are described here:
| Inclusion | Exclusion |
|---|---|
| All cases where adaptive or near-real time forms of management or tools that support this form of management were discussed, even if the specific term ‘Dynamic Ocean Management’ was not explicitly used. | The term ‘DOM’ was mentioned, or even recommended, but there was no discussion as to why (e.g. SDM studies that suggest DOM applications as a next step for their model) |
| All cases where near real-time SDM tools or fleet-wide communication to avoid negative species interactions. | Articles that involved changes or updates to environmental data stores or remote sensing tools used for developing SDM tools to support DOM, but DOM was not specifically applied, recommended, or reviewed. |
The 151 articles were read by two reviewers and went through a final pass for determining inclusion. Articles that were referenced that seemed to discuss relevant topics were skimmed and their inclusion was determined. The final list of works analyzed for the review included 118 articles (i.e., primary literature, student theses, policy reports, and textbook chapters).
Coding the bridges and barriers as identified in the literature
Two reviewers went through each of the 118 articles to identify text that was related to DOM bridges that were linked to the approach’s success or were used as justification as to why DOM would be a good fit for that system/conservation problem. The reviewers also identified the barriers that hindered the efficacy of DOM or must be considered prior to its application. Through this effort, 19 “bridge” and 10 “barrier” categories were determined in the literature. “Bridge” and “barrier” factors were organized into four broader theme groups: ecological, social, and data. A table of the full list of codes/themes from the literature are depicted here. Please note that this is a draft of codes and that the sunburst diagrams need to be revised. I am also happy to modify the code/factor terminology throughout the study review process.
| Code category | Code label |
|---|---|
| Data barrier | Gaps and inaccuracy |
| Data barrier | Management scales do not align with system needs |
| Data barrier | Model abuse |
| Ecological barrier | Need for multispecies management |
| Data barrier | Climate change adding uncertainty to target species habitat use |
| Social barrier | Indirect socioeconomic consequences |
| Social barrier | Discontinuity |
| Social barrier | Poor communication and outreach |
| Social barrier | Poor program implementation |
| Social barrier | Cost |
Sankey diagram of literature code heirarchies
Here, each of the codes and their subcodes are presented. The presented percentages represent totals across all codes and codes closer to the top are codes that make up higher percentages of identified codes.
# A tibble: 2 × 2
bridge_barr totals
<chr> <int>
1 Barrier 201
2 Bridge 509# A tibble: 6 × 2
code_cat totals
<chr> <int>
1 Data barrier 86
2 Data bridge 173
3 Ecological barrier 13
4 Ecological bridge 141
5 Social barrier 102
6 Social bridge 195
Visualizing the literature bridges and barrier codes
Below is a first attempt at how to visualize some of the data collected from this review. This first section represents general information about the articles selected for this review (e.g., study location, fisheries or shipping channels involved, species for which the tool or management program was established for). Most of these plots may instead go in the supplemental materials or aid with interpretation.
Study information
Article categories
Code appearance frequencies across articles (n = 118)
The proportions reported in these figures represent the percent of papers that mentioned a subcode within these broader code categories at least once.
Code appearance frequencies within code categories
Here, I have plotted the same information as the previous section, but as a percentage of the overall bridges and barriers groupings. For example, data bridges make up 37% of all bridge codes. The same pattern holds for the other sub-panels. For example, on the ecological page, abiotic indicators account for 22% of all ecological bridge codes.
Code co-occurrence themes
Could consider including code co-occurrence themes as a heat map, or could list the most frequent pairings as a table.
This is a heatmap of all code relationships within articles. The number of co-ocurrences represents the number of times two codes co-occurered together in the same article.
This heatmap represents the same data set as the last figure, but only includes co-occurrence values greater than or equal to 6, which is the 75% quantile of the co-occurrence totals. I have also added boxes around totals greater than 11, which was the 90% quantile of the co-occurrence total data set. Blue text represents data bridges and barriers, grey text represents ecological bridges and barriers, and orange text represents social bridges and barriers.
This is a look at the data bridge and barrier code relations. Totals higher than or equal to 14 (90th quantile for data totals) are outlined in black.Here, red text represents codes that are barriers, and green text represents codes that are bridges.
This is a look at the ecological bridge and barrier code relations. Totals higher than or equal to 5 (90th quantile for ecological totals) are outlined in black.Here, red text represents codes that are barriers, and green text represents codes that are bridges.
This is a look at the social bridge and barrier code relations. Totals higher than or equal to 5 (90th quantile for social totals) are outlined in black.Here, red text represents codes that are barriers, and green text represents codes that are bridges.
Surveys
Survey respondants
Respondant positions
Respondant experience
Code appearance frequencies across surveys (n = 2, not including EcoCast)
The proportions reported in these figures represent the percent of surveys that mentioned a subcode within these broader code categories at least once.
Code appearance frequencies within code categories
Here, I have plotted the same information as the previous section, but as a percentage of the overall bridges and barriers groupings. For example, data bridges make up 37% of all bridge codes. The same pattern holds for the other sub-panels. For example, on the ecological page, abiotic indicators account for 22% of all ecological bridge codes.
