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USGS2018

The potential for citizen science to produce reliable and useful information in ecology

We examined features of citizen science that influence data quality, inferential power, and usefulness in ecology. As background context for our examination, we considered topics such as ecological sampling (probability based, purposive, opportunistic), linkage between sampling technique and statistical inference(designbased,modelbased),andscientificparadigms(confirmatory,exploratory).Wedistinguished several types of citizen science investigations, from intensive research with rigorous protocols targeting clearly articulated questions to mass-participation internet-based projects with opportunistic data collection lacking samplingdesign,andexaminedoverarchingobjectives,design,analysis,volunteertraining,andperformance. We identified key features that influence data quality: project objectives, design and analysis, and volunteer training and performance. Projects with good designs, trained volunteers, and professional oversight can meet statistical criteria to produce high-quality data with strong inferential power and therefore are well suited for ecological research objectives. Projects with opportunistic data collection, little or no sampling design, and minimal volunteer training are better suited for general objectives related to public education or data exploration because reliable statistical estimation can be difficult or impossible. In some cases, statistically robust analytical methods, external data, or both may increase the inferential power of certain opportunistically collected data. Ecological management, especially by government agencies, frequently requires data suitable for reliable inference. With standardized protocols, state-of-the-art analytical methods, and well-supervised programs, citizen science can make valuable contributions to conservation by increasing the scope of species monitoring efforts. Data quality can be improved by adhering to basic principles of data collection and analysis, designing studies to provide the data quality required, and including suitable statistical expertise, thereby strengthening the science aspect of citizen science and enhancing acceptance by the scientific community and decision makers.

Conservation Biology↗
USGS2019

Effects of life history and reproduction on recruitment time lags in reintroductions of rare plants

Reintroductions are important components of conservation and recovery programs for rare plant species, but their long‐term success rates are poorly understood. Previous reviews of plant reintroductions focused on short‐term (e.g., ≤3 years) survival and flowering of founder individuals rather than on benchmarks of intergenerational persistence, such as seedling recruitment. However, short‐term metrics may obscure outcomes because the unique demographic properties of reintroductions, including small size and unstable stage structure, could create lags in population growth. We used time‐to‐event analysis on a database of unusually well‐monitored and long‐term (4–28 years) reintroductions of 27 rare plant species to test whether life‐history traits and population characteristics of reintroductions create time‐lagged responses in seedling recruitment (i.e., recruitment time lags [RTLs]), an important benchmark of success and indicator of persistence in reintroduced populations. Recruitment time lags were highly variable among reintroductions, ranging from <1 to 17 years after installation. Recruitment patterns matched predictions from life‐history theory with short‐lived species (fast species) exhibiting consistently shorter and less variable RTLs than long‐lived species (slow species). Long RTLs occurred in long‐lived herbs, especially in grasslands, whereas short RTLs occurred in short‐lived subtropical woody plants and annual herbs. Across plant life histories, as reproductive adult abundance increased, RTLs decreased. Highly variable RTLs were observed in species with multiple reintroduction events, suggesting local processes are just as important as life‐history strategy in determining reintroduction outcomes. Time lags in restoration outcomes highlight the need to scale success benchmarks in reintroduction monitoring programs with plant life‐history strategies and the unique demographic properties of restored populations. Drawing conclusions on the long‐term success of plant reintroduction programs is premature given that demographic processes in species with slow life‐histories take decades to unfold.

Conservation Biology↗
USGS2019

The dilemma of pest suppression in the conservation of endangered species

In the conservation of endangered species, active suppression of a population of one native species to benefit another native species poses particular challenges. Obvious examples include predator control and nest parasite reduction. Less obvious is the control of blood-feeding arthropods. We present a case study on the effect of blood-feeding black flies (Simulium spp.) on reintroduced Whooping Cranes (Grus americana). Our intent is to provide a transferrable, science-driven approach for determining the effects of blood-feeding arthropods on endangered vertebrates, and demonstrate an approach for guiding selection of management actions for managers faced with competing objectives. A multi-year experiment demonstrated that black flies reduce nest success in reintroduced cranes by driving the birds off their nests during incubation. Deciding how to respond, however, is complicated because the target black flies are native species that serve important ecological functions. We suggest that a decision-analytic approach can inspire the development of creative management alternatives and facilitate a transparent process that evaluates trade-offs among competing objectives. Recognizing that these decisions involve trade-offs, which must be weighed in the context of each case, is crucial to identifying alternatives that best balance multiple management objectives. Given the uncertainty about the population dynamics of blood-feeding arthropods, an adaptive management approach will offer substantial benefits.

Wisconsin↗
USGS2019

Trends in biodiversity and habitat quantification tools used for market‐based conservation in the United States

Market-based conservation mechanisms are designed to facilitate conservation and mitigation actions for habitat and biodiversity. Their potential is partly hindered, however, by issues surrounding the quantification tools used to assess habitat quality and functionality. Specifically, a lack of transparency and standardization in tool development and gaps in tool availability are cited concerns. To address these issues, we collected information about tools used in United States conservation mechanisms such as eco-label and payments for ecosystem services (PES) programs, conservation banking, and habitat exchanges. We summarized information about tools and explored trends among and within mechanisms using criteria detailing geographic, ecological, and technical features of tools. We identified 69 tools that assessed at least 34 species and 39 habitat types. Where tools reported pricing, 98% were freely available. Most tools required a moderate or greater level of user skill. More tools were applied to states along the west coast of the United States than elsewhere and the level of tool transferability varied markedly among mechanisms. Tools most often incorporated conditions at numerous spatial scales, frequently addressed multiple risks to site viability, and required from 1 to 83 data inputs. Finally, average tool complexity estimates were similar among all mechanisms except PES programs. Our results illustrate the diversity among tools in their ecological features, data needs, and geographic application, supporting concerns about a lack of standardization. However, consistency among tools in user skill requirements, the incorporation of multiple spatial scales, and complexity highlight important commonalities that could serve as a starting point for establishing more standardized tool development and feature incorporation processes. Greater standardization in tool design may not only expand market participation, but may also facilitate a needed assessment of the effectiveness of market-based conservation.

Conservation Biology↗
USGS2019

A network approach to prioritize conservation efforts for migratory birds

Habitat loss can trigger migration network collapse by isolating migratory birds’ breeding grounds from non-breeding grounds. Theoretically, habitat loss can have vastly different impacts depending on the site’s importance within the migratory corridor. However, migration network connectivity and the impacts of site loss are not completely understood. Here we used GPS tracking data from four bird species in the Asian flyways to construct migration networks, and proposed a framework for assessing network connectivity for migratory species. We used a node removal process to identify stopover sites with the highest impact on connectivity. In general, migration networks with fewer stopover sites were more vulnerable to habitat loss. Node removal in order from the highest to lowest degree of habitat loss yielded an increase of network resistance similar to random removal. In contrast, resistance increased more rapidly when removing nodes in order from the highest to lowest betweenness value. We quantified the risk of migration network collapse and identified crucial sites by first selecting sites with large contributions to network connectivity, and then identifying which of those sites were likely to be removed from the network (i.e., sites experiencing habitat loss). Among these crucial sites, 42% were not designated as protected areas. Setting priorities for site protection should account for the site’s position within the migration network, rather than only site-specific characteristics. Our framework for assessing migration network connectivity enables site prioritization for conservation of migratory species.

Conservation Biology↗
USGS2019

Application of multiple-population viability analysis to evaluate species recovery alternatives

Population viability analysis (PVA) is a powerful conservation tool, but one that remains unapproachable for many species. This is particularly true for species with multiple, broadly-distributed populations for which collecting suitable data can be challenging. A recently-developed method of multiple population viability analysis (MPVA), however, addresses many limitations of traditional PVA. We build on previous development of MPVA for Lahontan cutthroat trout (LCT), a species listed under the US Endangered Species Act which is distributed broadly across habitat fragments in the Great Basin, USA. We simulated potential management scenarios and assessed their effects on population sizes and extinction risks in 211 streams where LCT exist or may be reintroduced.

Conservation Biology↗
USGS2020

The changing sociocultural context of wildlife conservation

We introduced a multilevel model of value shift to describe the changing social context of wildlife conservation. Our model depicts how cultural-level processes driven by modernization (e.g., increased wealth, education, and urbanization) affect changes in individual-level cognition that prompt a shift from domination to mutualism wildlife values. Domination values promote beliefs that wildlife should be used primarily to benefit humans, whereas mutualism values adopt a view that wildlife are part of one's social network and worthy of care and compassion. Such shifts create emergent effects (e.g., new interest groups) and challenges to wildlife management organizations (e.g., increased conflict) and dramatically alter the sociopolitical context of conservation decisions. Although this model is likely applicable to many modernized countries, we tested it with data from a 2017–2018 nationwide survey (mail and email panel) of 43,949 residents in the United States. We conducted hierarchical linear modeling and correlational analysis to examine relationships. Modernization variables had strong state-level effects on domination and mutualism. Higher levels of education, income, and urbanization were associated with higher percentages of mutualists and lower percentages of traditionalists, who have strong domination values. Values affected attitudes toward wildlife management challenges; for example, states with higher proportions of mutualists were less supportive of lethal control of wolves ( Canis lupus ) and had lower percentages of active hunters, who represent the traditional clientele of state wildlife agencies in the United States. We contend that agencies will need to embrace new strategies to engage and represent a growing segment of the public with mutualism values. Our model merits testing for application in other countries.

Conservation Biology↗
USGS2020

Effects of body size on estimation of mammalian area requirements

Accurately quantifying species’ area requirements is a prerequisite for effective area-based conservation. This typically involves collecting tracking data on species of interest and then conducting home-range analyses. Problematically, autocorrelation in tracking data can result in space needs being severely underestimated. Based on the previous work, we hypothesized the magnitude of underestimation varies with body mass, a relationship that could have serious conservation implications. To evaluate this hypothesis for terrestrial mammals, we estimated home-range areas with global positioning system (GPS) locations from 757 individuals across 61 globally distributed mammalian species with body masses ranging from 0.4 to 4000 kg. We then applied block cross-validation to quantify bias in empirical home-range estimates. Area requirements of mammals <10 kg were underestimated by a mean approximately15%, and species weighing approximately100 kg were underestimated by approximately50% on average. Thus, we found area estimation was subject to autocorrelation-induced bias that was worse for large species. Combined with the fact that extinction risk increases as body mass increases, the allometric scaling of bias we observed suggests the most threatened species are also likely to be those with the least accurate home-range estimates. As a correction, we tested whether data thinning or autocorrelation-informed home-range estimation minimized the scaling effect of autocorrelation on area estimates. Data thinning required an approximately93% data loss to achieve statistical independence with 95% confidence and was, therefore, not a viable solution. In contrast, autocorrelation-informed home-range estimation resulted in consistently accurate estimates irrespective of mass. When relating body mass to home range size, we detected that correcting for autocorrelation resulted in a scaling exponent significantly >1, meaning the scaling of the relationship changed substantially at the upper end of the mass spectrum.

Conservation Biology↗
USGS2021

Improving inferences about private land conservation by accounting for incomplete reporting

Private lands provide key habitat for imperiled species and are core components of function protected area networks; yet, their incorporation into national and regional conservation planning has been challenging. Identifying locations where private landowners are likely to participate in conservation initiatives can help avoid conflict and clarify trade-offs between ecological benefits and sociopolitical costs. Empirical, spatially explicit assessment of the factors associated with conservation on private land is an emerging tool for identifying future conservation opportunities. However, most data on private land conservation are voluntarily reported and incomplete, which complicates these assessments. We used a novel application of occupancy models to analyze the occurrence of conservation easements on private land. We compared multiple formulations of occupancy models with a logistic regression model to predict the locations of conservation easements based on a spatially explicit social-ecological systems framework. We combined a simulation experiment with a case study of easement data in Idaho and Montana (United States) to illustrate the utility of the occupancy framework for modeling conservation on private land. Occupancy models that explicitly accounted for variation in reporting produced estimates of predictors that were substantially less biased than estimates produced by logistic regression under all simulated conditions. Occupancy models produced estimates for the 6 predictors we evaluated in our case study that were larger in magnitude, but less certain than those produced by logistic regression. These results suggest that occupancy models result in qualitatively different inferences regarding the effects of predictors on conservation easement occurrence than logistic regression and highlight the importance of integrating variable and incomplete reporting of participation in empirical analysis of conservation initiatives. Failure to do so can lead to emphasizing the wrong social, institutional, and environmental factors that enable conservation and underestimating conservation opportunities in landscapes where social norms or institutional constraints inhibit reporting.

Idaho, Montana↗
USGS2021

Using expert knowledge to support Endangered Species Act decision‐making for data‐deficient species

Many questions relevant to conservation decision making are characterized by extreme uncertainty due to lack of empirical data and complexity of the underlying ecological processes, leading to a rapid increase in the use of structured protocols to elicit expert knowledge. Published ecological applications often employ a modified Delphi method, where experts provide judgments anonymously and mathematical aggregation techniques are used to combine judgments. The Sheffield Elicitation Framework (SHELF) differs in its behavioral approach to synthesizing individual judgments into a fully specified probability distribution for an unknown quantity. This study demonstrates the remote use of the SHELF protocol for an extinction risk assessment of three subterranean aquatic species petitioned for listing under the US Endangered Species Act. Experts were provided an empirical threat assessment for each known locality using video conferencing and asked for judgments on the probability of population persistence over four generations using online submission forms and R‐shiny apps available through the SHELF package. Despite large uncertainty for all populations, results reveal key differences between species’ risk of extirpation based on spatial variation in dominant threats, local land use and management practices, and microhabitat use. The resulting probability distributions provide decision makers with a full picture of uncertainty that is consistent with the probabilistic nature of risk assessments, and discussions during the behavioral aggregation stage clearly document dominant threats (e.g., development, timber harvest, animal agriculture, and cave visitation) and their interactions with local cave geology and species’ habitat preferences. Our virtual implementation of the SHELF protocol demonstrates the flexibility of this approach for conservation applications operating on budgets and timelines that can limit in‐person meetings of geographically dispersed experts.

Conservation Biology↗
USGS2021

The scope and severity of white-nose syndrome on hibernating bats in North America

Assessing the scope and severity of threats is necessary for evaluating impacts on populations to inform conservation planning. Quantitative threat assessment often requires monitoring programs that provide reliable data over relevant spatial and temporal scales, yet such programs can be difficult to justify until there is an apparent stressor. Leveraging efforts of wildlife management agencies to record winter counts of hibernating bats, we collated data for 5 species from over 200 sites across 27 U.S. states and 2 Canadian provinces from 1995 to 2018 to determine the impact of white-nose syndrome (WNS), a deadly disease of hibernating bats. We estimated declines of winter counts of bat colonies at sites where the invasive fungus that causes WNS ( Pseudogymnoascus destructans ) had been detected to assess the threat impact of WNS. Three species undergoing species status assessment by the U.S. Fish and Wildlife Service ( Myotis septentrionalis , Myotis lucifugus , and Perimyotis subflavus ) declined by more than 90%, which warrants classifying the severity of the WNS threat as extreme based on criteria used by NatureServe. The scope of the WNS threat as defined by NatureServe criteria was large (36% of Myotis lucifugus range) to pervasive (79% of Myotis septentrionalis range) for these species. Declines for 2 other species ( Myotis sodalis and Eptesicus fuscus ) were less severe but still qualified as moderate to serious based on NatureServe criteria. Data-sharing across jurisdictions provided a comprehensive evaluation of scope and severity of the threat of WNS and indicated regional differences that can inform response efforts at international, national, and state or provincial jurisdictions. We assessed the threat impact of an emerging infectious disease by uniting monitoring efforts across jurisdictional boundaries and demonstrated the importance of coordinated monitoring programs, such as the North American Bat Monitoring Program (NABat), for data-driven conservation assessments and planning.

Conservation Biology↗
USGS2021

A framework for allocating conservation resources among multiple threats and actions

Land managers decide how to allocate resources among multiple threats that can be addressed through multiple possible actions. Additionally, these actions vary in feasibility, effectiveness, and cost. We sought to provide a way to optimize resource allocation to address multiple threats when multiple management options are available, including mutually exclusive options. Formulating the decision as a combinatorial optimization problem, our framework takes as inputs the expected impact and cost of each threat for each action (including do nothing) and for each overall budget identifies the optimal action to take for each threat. We compared the optimal solution to an easy to calculate greedy algorithm approximation and a variety of plausible ranking schemes. We applied the framework to management of multiple introduced plant species in Australian alpine areas. We developed a model of invasion to predict the expected impact in 50 years for each species‐action combination that accounted for each species’ current invasion state (absent, localized, widespread); arrival probability; spread rate; impact, if present, of each species; and management effectiveness of each species‐action combination. We found that the recommended action for a threat changed with budget; there was no single optimal management action for each species; and considering more than one candidate action can substantially increase the management plan's overall efficiency. The approximate solution (solution ranked by marginal cost‐effectiveness) performed well when the budget matched the cost of the prioritized actions, indicating that this approach would be effective if the budget was set as part of the prioritization process. The ranking schemes varied in performance, and achieving a close to optimal solution was not guaranteed. Global sensitivity analysis revealed a threat's expected impact and, to a lesser extent, management effectiveness were the most influential parameters, emphasizing the need to focus research and monitoring efforts on their quantification.

Conservation Biology↗
USGS2021

Improving species status assessments under the U.S. Endangered Species Act and implications for multispecies conservation challenges worldwide

Despite its successes, the U.S. Endangered Species Act (ESA) has proven challenging to implement due to funding limitations, workload backlog, and other problems. As threats to species survival intensify and as more species come under threat, the need for the ESA and similar conservation laws and policies in other countries to function efficiently has grown. Attempts by the U.S. Fish and Wildlife Service (USFWS) to streamline ESA decisions include multispecies recovery plans and habitat conservation plans. We address species status assessment (SSA), a USFWS process to inform ESA decisions from listing to recovery, within the context of multispecies and ecosystem planning. Although existing SSAs have a single-species focus, ecosystem-based research can efficiently inform multiple SSAs within a region and provide a foundation for transition to multispecies SSAs in the future. We considered at-risk grassland species and ecosystems within the southeastern United States, where a disproportionate number of rare and endemic species are associated with grasslands. To initiate our ecosystem-based approach, we used a combined literature-based and structured World Café workshop format to identify science needs for SSAs. Discussions concentrated on 5 categories of threats to grassland species and ecosystems, consistent with recommendations to make shared threats a focus of planning under the ESA: (1) habitat loss, fragmentation, and disruption of functional connectivity; (2) climate change; (3) altered disturbance regimes; (4) invasive species; and (5) localized impacts. For each threat, workshop participants identified science and information needs, including database availability, research priorities, and modeling and mapping needs. Grouping species by habitat and shared threats can make the SSA process and other planning processes for conservation of at-risk species worldwide more efficient and useful. We found a combination of literature review and structured discussion effective for identifying the scientific information and analysis needed to support the development of multiple SSAs.

Conservation Biology↗
USGS2021

Applying assessments of adaptive capacity to inform natural-resource management in a changing climate

Adaptive capacity (AC)—the ability of a species to cope with or accommodate climate change—is a critical determinant of species vulnerability. Using information on species’ AC in conservation planning is key to ensuring successful outcomes. We identified connections between a list of species’ attributes (e.g., traits, population metrics, and behaviors) that were recently proposed for assessing species’ AC and management actions that may enhance AC for species at risk of extinction. Management actions were identified based on evidence from the literature, a review of actions used in other climate adaptation guidance, and our collective experience in diverse fields of global-change ecology and climate adaptation. Selected management actions support the general AC pathways of persist in place or shift in space, in response to contemporary climate change. Some actions, such as genetic manipulations, can be used to directly alter the ability of species to cope with climate change, whereas other actions can indirectly enhance AC by addressing ecological or anthropogenic constraints on the expression of a species’ innate abilities to adapt. Ours is the first synthesis of potential management actions directly linked to AC. Focusing on AC attributes helps improve understanding of how and why aspects of climate are affecting organisms, as well as the mechanisms by which management interventions affect a species’ AC and climate change vulnerability. Adaptive-capacity-informed climate adaptation is needed to build connections among the causes of vulnerability, AC, and proposed management actions that can facilitate AC and reduce vulnerability in support of evolving conservation paradigms.

Conservation Biology↗
USGS2022

An introduction to decision science for conservation

Biodiversity conservation decisions are difficult, especially when they involve differing values, complex multidimensional objectives, scarce resources, urgency, and considerable uncertainty. Decision science embodies a theory about how to make difficult decisions and an extensive array of frameworks and tools that make that theory practical. We sought to improve conceptual clarity and practical application of decision science to help decision makers apply decision science to conservation problems. We addressed barriers to the uptake of decision science, including a lack of training and awareness of decision science; confusion over common terminology and which tools and frameworks to apply; and the mistaken impression that applying decision science must be time consuming, expensive, and complex. To aid in navigating the extensive and disparate decision science literature, we clarify meaning of common terms: decision science , decision theory , decision analysis , structured decision-making , and decision-support tools . Applying decision science does not have to be complex or time consuming; rather, it begins with knowing how to think through the components of a decision utilizing decision analysis (i.e., define the problem, elicit objectives, develop alternatives, estimate consequences, and perform trade-offs). This is best achieved by applying a rapid-prototyping approach. At each step, decision-support tools can provide additional insight and clarity, whereas decision-support frameworks (e.g., priority threat management and systematic conservation planning) can aid navigation of multiple steps of a decision analysis for particular contexts. We summarize key decision-support frameworks and tools and describe to which step of a decision analysis, and to which contexts, each is most useful to apply. Our introduction to decision science will aid in contextualizing current approaches and new developments, and help decision makers begin to apply decision science to conservation problems.

Conservation Biology↗
USGS2022

Quantifying the conservation status and abundance trends of wildlife communities with detection-nondetection data

Effective conservation requires understanding species' abundance patterns and demographic rates across space and time. Ideally, such knowledge should be available for whole communities, as variation in species' dynamics can elucidate factors leading to biodiversity losses. However, collecting data to simultaneously estimate abundance and demographic rates is often prohibitively time-intensive and expensive for communities of species. We developed a “multi-species dynamic N-occupancy model” to estimate unbiased, community-wide relative abundance and demographic rates. Our model uses detection-nondetection data (e.g., repeated presence-absence surveys) to estimate both species- and community-level parameters as well as the effects of environmental factors. We conducted a simulation study that validated our modeling framework, demonstrating how and when such an approach can be valuable. Using data from a network of camera traps across tropical equatorial Africa, we then used our model to evaluate the statuses and trends of a forest-dwelling antelope community. We estimated relative abundance, rates of recruitment (i.e., reproduction and immigration), and apparent survival probabilities for each species' local population. Our analysis indicated that the antelope community was fairly stable in this region (although 17% of populations [species-park combinations] declined over the study period), with variation in apparent survival linked more closely to differences among national parks rather than individual species' life histories. The multi-species dynamic N-occupancy model requires only detection-nondetection data to evaluate the population dynamics of multiple sympatric species and can thus be a valuable tool for conservation efforts seeking to understand the reasons behind recent biodiversity loss.

Conservation Biology↗
USGS2022

Exploring metapopulation-scale suppression alternatives for a global invader in a river network experiencing climate change

Invasive species can dramatically alter ecosystems, but eradication is difficult, and suppression is expensive once they are established. Uncertainties in the potential for expansion and impacts by an invader can lead to delayed and inadequate suppression, allowing for establishment. Metapopulation viability models can aid in planning strategies to improve responses to invaders and lessen invasive species’ impacts, which may be particularly important under climate change. We used a spatially explicit metapopulation viability model to explore suppression strategies for ecologically damaging invasive brown trout ( Salmo trutta ), established in the Colorado River and a tributary in Grand Canyon National Park. Our goals were to estimate the effectiveness of strategies targeting different life stages and subpopulations within a metapopulation; quantify the effectiveness of a rapid response to a new invasion relative to delaying action until establishment; and estimate whether future hydrology and temperature regimes related to climate change and reservoir management affect metapopulation viability and alter the optimal management response. Our models included scenarios targeting different life stages with spatially varying intensities of electrofishing, redd destruction, incentivized angler harvest, piscicides, and a weir. Quasi-extinction (QE) was obtainable only with metapopulation-wide suppression targeting multiple life stages. Brown trout population growth rates were most sensitive to changes in age 0 and large adult mortality. The duration of suppression needed to reach QE for a large established subpopulation was 12 years compared with 4 with a rapid response to a new invasion. Isolated subpopulations were vulnerable to suppression; however, connected tributary subpopulations enhanced metapopulation persistence by serving as climate refuges. Water shortages driving changes in reservoir storage and subsequent warming would cause brown trout declines, but metapopulation QE was achieved only through refocusing and increasing suppression. Our modeling approach improves understanding of invasive brown trout metapopulation dynamics, which could lead to more focused and effective invasive species suppression strategies and, ultimately, maintenance of populations of endemic fishes.

Arizona↗
USGS2022

Considering science needs to deliver actionable science

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.

Conservation Biology↗