Geology Reports⌕ Search
Home/Archive/USGS

USGS · 70238640

Considering science needs to deliver actionable science

Gustavo A. Bisbal·Mitchell J. Eaton
View original source ↗Export metadata ↓

Abstract

Conservation practitioners, natural resource managers, and environmental stewards often seek out scientific contributions to inform decision-making. This body of science only becomes actionable when motivated by decision makers considering alternative courses of action. Many in the science community equate addressing stakeholder science needs with delivering actionable science. However, not all efforts to address science needs deliver actionable science, suggesting that the synonymous use of these two constructs (delivering actionable science and addressing science needs) is not trivial. This can be the case when such needs are conveyed by people who neglect decision makers responsible for articulating a priority management concern and for specifying how the anticipated scientific information will aid the decision-making process. We argue that the actors responsible for articulating these science needs and the process used to identify them are decisive factors in the ability to deliver actionable science, stressing the importance of examining the provenance and the determination of science needs. Guided by a desire to enhance communication and cross-literacy between scientists and decision makers, we identified categories of actors who may inappropriately declare science needs (e.g., applied scientists with and without regulatory affiliation, external influencers, reluctant decision makers, agents in place of decision makers, and boundary organization representatives). We also emphasize the importance of, and general approach to, undertaking needs assessments or gap analyses as a means to identify priority science needs. We conclude that basic stipulations to legitimize actionable science, such as the declaration of decisions of interest that motivate science needs and using a robust process to identify priority information gaps, are not always satisfied and require verification. To alleviate these shortcomings, we formulated practical suggestions for consideration by applied scientists, decision makers, research funding entities, and boundary organizations to help foster conditions that lead to science output being truly actionable.

Explore related subjects

Conservation BiologyArticle

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Gustavo A. Bisbal, Mitchell J. Eaton. 2022-11-07. Considering science needs to deliver actionable science. https://doi.org/10.1111/cobi.14013

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

USGS2026

The collective application of shorebird tracking data to conservation

Addressing urgent conservation issues, such as the drastic declines of North American migratory birds, requires creative, evidence-based, efficient, and collaborative approaches. The abundance of over 50% of monitored North American shorebird populations has declined by over 50% since 1980. To address these declines, we developed a partnership of scientists and practitioners called the Shorebird Science and Conservation Collective (hereafter the collective ). The collective was founded to translate the combined findings of shorebird tracking data into on-the-ground conservation action. With advice from an advisory group, the collective acts as an intermediary whereby dedicated staff collate and analyze data contributions from scientists to support knowledge requests from conservation practitioners. In its first three years, data contributions from 75 organizations include over 7.1 million shorebird observations forming movement paths of 3420 individuals representing 36 species tracked across the Americas and have informed 18 conservation projects spanning education, land and species management, land conservation, and policy requests. Others engaged in translational science from big data could consider similar knowledge-sharing models that prioritize usable data products, foster collaborative engagement between science experts and practitioners, build focused communities around topics or taxonomic groups, and employ a proof-of-concept phase to develop scalable solutions while making progress toward long-term funding to sustain impact. As the volume of scientific data continues to grow, intermediaries, such as the collective, can be vital liaisons to rapidly integrate and interpret research to support conservation action. Dedicated to the memory of Shiloh Schulte and his conservation achievements for shorebirds.

Conservation Biology↗
USGS2026

Scenarios and strategies for future-proofing ecosystem management under climatic novelty

Climate change is driving unprecedented declines in dominant, habitat-forming foundation species across marine and terrestrial ecosystems globally. As climatic novelty becomes the norm, ecosystem reassembly will become increasingly common. Predicting and understanding these transitions, and their implications for future ecosystem functioning, is essential for designing effective forward-looking management strategies. We explored 3 scenarios that describe a range of ecosystem reassembly trajectories following declines in previously dominant habitat-forming taxa: compensation, in which functionally similar subdominant or immigrating taxa maintain ecosystem structure and function; decline, in which no compensation occurs leading to loss of ecosystem structure and function; and transformation, in which the ecosystem present historically can no longer persist and shifts into a fundamentally different ecosystem type with distinct structure and function. This range of potential outcomes highlights the urgent need to assess the ecological feasibility and functional implications of potential management actions. Scientists and managers can work together to quantify local-scale climatic novelty and ecosystem resilience to better predict the most likely reassembly trajectories and identify management interventions that will optimize ecosystem function. This approach would allow for more proactive planning to support persistence of ecosystem structure and function, helping to future-proof ecosystem management in a rapidly changing world.

Conservation Biology↗
USGS2026

Constructed value of information with iterative scoring and parametric uncertainty to identify management-relevant research priorities for a declining raptor species

Constructed value of information (CVoI) is an expert elicitation decision-analytic tool used to prioritize sources of uncertainty based on their potential to improve decision outcomes if resolved. Despite increased application of CVoI, the robustness of CVoI prioritization of sources of uncertainty relative to differences in expert elicitation and scoring methods has not been evaluated. We engaged a group of species experts in a decision-analytic process to elicit uncertainties, framed as alternative hypotheses, about current population declines of the American kestrel ( Falco sparverius ) in the United States. Participants scored 13 hypotheses across 3 CVoI criteria, which are defined as constructed scales. Rather than experts selecting a single score per criterion, we used a likelihood point method to incorporate parametric uncertainty in the scoring process, in which experts were given 100 points to distribute across possible score categories within the criterion-specific constructed scale. Experts provided scores over 2 scoring rounds, with an opportunity to review and discuss initial scores between rounds. We used a Shannon entropy calculation to quantify how evenly participants allotted their points. We used simulation to evaluate the robustness of our prioritization results relative to a scoring method in which participants selected a single score category for each criterion. Participants often spread their points across 2 adjacent scores, reflecting parametric uncertainty. For one third of the hypothesis-scoring round combinations, the prioritization results differed in approximately 50% of simulations. The highest scoring hypotheses related to how the use of artificial versus natural nest cavities affects fecundity or survival, whether winter roosting sites are a limiting factor for population growth, and whether gamebird habitat management may benefit kestrel populations. Our CVoI prioritization framework can be used to develop collaborative research that is directly relevant to a management decision and is an advance in eliciting more representative expert beliefs.

Conservation Biology↗