Ten simple rules for creating a scientific web application.

The use of scientific web applications (SWApps) across biological and environmental sciences has grown exponentially over the past decade or so. Although quantitative evidence for such increased use in practice is scant, collectively, we have observed that these tools become more commonplace in teaching, outreach, and in science coproduction (e.g., as decision support tools). Despite the increased popularity of SWApps, researchers often receive little or no training in creating such tools. Although rolling out SWApps can be a relatively simple and quick process using modern, popular platforms like R shiny apps or Tableau dashboards, making them useful, usable, and sustainable is not. These 10 simple rules for creating a SWApp provide a foundation upon which researchers with little to no experience in web application design and development can consider, plan, and carry out SWApp projects.

If you build it, they may not come: Understanding factors influencing use of a community resource referral technology.

OBJECTIVE: Identify factors affecting the use of a community resource referral platform among local community-based organizations (CBOs) and test strategies to increase platform use. DATA SOURCES AND STUDY SETTING: Data sources included platform usage data and semi-structured interviews. The study took place in a small city in the Northeastern United States from 2020 to 2022. STUDY DESIGN: We analyzed platform data and conducted interviews with local organizations and organizations in other communities to understand barriers to CBOs' use of the referral platform and identify strategies that might increase use. We then tested 4 strategies and assessed impacts via time trend analysis of platform usage and qualitative interviews. DATA COLLECTION/EXTRACTION METHODS: Platform usage data were obtained from the platform. Semi-structured interviews were conducted with staff and leaders of 36 local CBOs and 9 external organizations. PRINCIPAL FINDINGS: Four years after launch, platform use remained relatively low. None of the tested strategies (data insight reports, a referral hub, tailored training, and a communication campaign) noticeably increased platform use. The main barrier to the use of the platform was the lack of perceived usefulness, mostly because existing processes for identifying resources and referring clients worked well enough and because many organizations were already required to use a client management or referral tool. Additional barriers included the lack of comfort with and, in some cases, active dislike of e-referrals, and lack of comfort with technology tools overall. Organizations that were most likely to find the platform useful and to use it were those that provided referrals for a wide range of needs and whose staff were not already familiar with local resources. CONCLUSIONS: Organizations seeking to implement referral platforms should not assume that local CBOs will automatically take up these platforms. For these platforms to succeed, much more attention needs to be paid to ensuring the platforms provide value to the CBOs they seek to engage.

Social-ecological landscape patterns predict woody encroachment from native tree plantings in a temperate grassland.

Afforestation is often viewed as the purposeful planting of trees in historically nonforested grasslands, but an unintended consequence is woody encroachment, which should be considered part of the afforestation process. In North America's temperate grassland biome, Eastern redcedar (Juniperus virginiana L.) is a native species used in tree plantings that aggressively invades in the absence of controlling processes. Cedar is a well-studied woody encroacher, but little is known about the degree to which cedar windbreaks, which are advocated for in agroforestry programs, are contributing to woody encroachment, what factors are associated with cedar spread from windbreaks, nor where encroachment from windbreaks is occurring in contemporary social-ecological landscapes. We used remotely sensed imagery to identify the presence and pattern of woody encroachment from windbreaks in the Nebraska Sandhills. We used multimodel inference to compare three classes of models representing three hypotheses about factors that could influence cedar spread: (a) windbreak models based on windbreak structure and design elements; (b) abiotic models focused on local environmental conditions; and (c) landscape models characterizing coupled human-natural features within the broader matrix. Woody encroachment was evident for 23% of sampled windbreaks in the Nebraska Sandhills. Of our candidate models, our inclusive landscape model carried 92% of the model weight. This model indicated that encroachment from windbreaks was more likely near roadways and less likely near farmsteads, other cedar plantings, and waterbodies, highlighting strong social ties to the distribution of woody encroachment from tree plantings across contemporary landscapes. Our model findings indicate where additional investments into cedar control can be prioritized to prevent cedar spread from windbreaks. This approach can serve as a model in other temperate regions to identify where woody encroachment resulting from temperate agroforestry programs is emerging.

Early Warnings for State Transitions.

New concepts have emerged in theoretical ecology with the intent to quantify complexities in ecological change that are unaccounted for in state-and-transition models and to provide applied ecologists with statistical early warning metrics able to predict and prevent state transitions. With its rich history of furthering ecological theory and its robust and broad-scale monitoring frameworks, the rangeland discipline is poised to empirically assess these newly proposed ideas while also serving as early adopters of novel statistical metrics that provide advanced warning of a pending shift to an alternative ecological regime. Were view multivariate early warning and regime shift detection metrics, identify situations where various metrics will be most useful for rangeland science, and then highlight known shortcomings. Our review of a suite of multivariate-based regime shift/early warning indicators provides a broad range of metrics applicable to a wide variety of data types or contexts, from situations where a great deal is known about the key system drivers and a regime shift is hypothesized a priori, to situations where the key drivers and the possibility of a regime shift are both unknown. These metrics can be used to answer ecological state-and-transition questions, inform policymakers, and provide quantitative decision-making tools for managers.