Animal movement studies are conducted for many reasons including basic scientific discovery, as tools for education and outreach, to address management and conservation questions, as part of environmental assessments, to determine the success or failure of management or conservation interventions, and for long-term monitoring of environmental change. Theoretical, methodological and technological advances have provided insights into aquatic animal behavior amid constantly-changing environmental conditions that could not be obtained using traditional conceptual frameworks and methods (Nathan et al., 2008; Costa et al., 2012; Hussey et al., 2015). This paper complements recent reviews discussing key achievements (Hussey et al., 2015) and key questions (Costa et al., 2012) in the study of aquatic movement ecology, and comprehensive reviews of how movement data have been used successfully in conservation decision-making and practice (for fish, see Cooke et al., 2016 and Crossin et al., accepted; for seabirds see Burger and Shaffer, 2008 and Lascelles et al., 2016), or how their use could be improved (McGowan and Possingham, 2016; McGowan et al., 2016).

A framework for linking movement ecology with wildlife management and conservation was recently introduced by Allen and Singh (2016) and adapted by McGowan and Possingham (2016) to illustrate how information about movement attributes of species can enhance conservation planning. We submit that many conservation issues can benefit from a more pro-active and strategic approach to integrating movement ecology with conservation efforts given the dynamic nature of aquatic ecosystems in space and time. We also discuss recent criticisms of the ability of movement data to aid conservation efforts. We review five key challenges to maximizing the conservation impact of movement ecology information in aquatic conservation, and we propose strategies for overcoming them. Two challenges focus on the conduct of movement science, one on building a culture of data openness, and two on practical applications of movement information. The challenges, while similar to other fields of study, are nonetheless critical to aquatic conservation, and management:

Disciplinary divides: Inadequate integration of terrestrial and aquatic movement science limits scientific advances and practical applications.

The goal of movement ecologists in all ecosystems is similar: gain a better understanding of animal distribution and resource use by collecting individual-level location data. Despite inherent differences, more integration between movement ecology studies in aquatic and terrestrial ecosystems will enhance methods, ecological knowledge, effort efficiency, and conservation or management.

Effective conservation and management of terrestrial and aquatic species requires a full understanding of changes in habitat use and movement patterns as organisms age/grow. However, the ability to study movement throughout the complete life history of species and full lifetime of individuals remains a great challenge, hampered in many cases by small body sizes, long lifetimes, and challenging habitats for tracking of individuals. In aquatic systems, technologies have expanded from inexpensive traditional mark-recapture tagging approaches (Kohler and Turner, 2008) to coordinated electronic telemetry efforts costing millions of dollars and scaled to cover ocean basins (Block et al., 2011; Cooke et al., 2011; Hussey et al., 2015). Innovative tags have enabled movement studies throughout a greater range of life stages and for longer durations (Hazen et al., 2012; Pinnix et al., 2013; Mansfield et al., 2014; Lu et al., 2016). New platforms (moored buoys, autonomous marine vehicles) are extending the reach of acoustic telemetry studies, with the potential for global networks of oceanographic, and other infrastructure (Hayes et al., 2013). In addition, existing data highlight the need to recognize differences in movement patterns among individuals, life stages, and segments of populations (Secor, 1999).

When tracking is not technologically feasible or is cost-prohibitive, other solutions are needed to understand the consequences of movement for conservation. For example, biogeochemical tracers in hard body parts can provide records of environmental conditions throughout part or all of an individual's lifetime (including larval stages of fish, mollusks, and other taxa) from which habitats used and trophic level can be inferred (Rubenstein and Hobson, 2004; Thorrold et al., 2007; McMahon et al., 2013). Model simulations can provide insights into movement patterns when behavioral responses to environmental conditions are known (e.g., Criales et al., 2015). As we move to an ecosystem based management framework, the costs of acquiring movement data may be reduced by focusing studies on flagship species (Douglas and Verissimo, 2013), but this approach deserves careful evaluation using multi-species tracking datasets (Harrison, 2012).

Animal movement studies are most often conducted by individuals or small research teams doing time-limited work on a single species within a restricted geographic range. While this has been valuable, it fails to unlock the full potential of the data (Nguyen et al., 2017). Archiving ecological data provides a historic record against which future studies can be compared, makes the information available for cross-species comparisons, allows secondary analysis of data that may differ from the vision of the original investigators, and provides other benefits to science and society (Whitlock, 2011). Although synthesizing and archiving data is challenging (Thomas, 2009; Tenopir et al., 2011), collaborations (Block et al., 2011), and data repositories (e.g., http://www.Movebank.org, http://www.seabirdtracking.org/, http://motus.org/, https://animaltracking.aodn.org.au/, http://oceantrackingnetwork.org/, https://ioos.noaa.gov/project/atn/) have fostered immense knowledge growth. Limitations still exist including the lack of common metadata and data standards; the need for secure data storage systems with long-term funding for development, staffing, and regional network building; and common frameworks for quality control and sufficient annotation of archived data. A remaining challenge is to develop a culture of data sharing (Vision, 2010; Whitlock, 2011; Vines et al., 2013) that reverses the traditional scientific view that data are not public but rather belong to the investigator who conducted the study (Nguyen et al., 2017). However, collaborating scientists are more prolific publishers, and the scale and scope of their collaborative work makes it more impactful (e.g., Piwowar et al., 2007; Young et al., 2013).

There is growing recognition that environmental managers do not make full use of all available scientific evidence when making decisions (Pullin et al., 2004), tending instead to rely on their experiences or those of their colleagues (Pullin et al., 2004; Young et al., 2016). The reasons for this apparent science-action divide are many (see Cook et al., 2013) and best considered in the context of knowledge mobilization, rooted in principles such as reliability, trust, access, institutional/cultural norms, values, and properties of one's network (Young et al., 2016). Knowing the factors that impede knowledge mobilization can be useful for identifying strategies to effectively employ movement data in decision-making. These factors include the perception of disruptive technology (Young et al., 2016), concerns about data reliability due to low detection efficiency, error in location estimates, or the effect of the tracking device on the animal's behavior, and that the data generated simply fail to provide the information that managers need (Young et al., 2013) even when studies are conducted at the request of managers and engage managers in the research process (e.g., reviewed in Cooke et al., 2016; Crossin et al., accepted).

Movement data generated using biologging tools (Rutz and Hays, 2009) are one of multiple types of scientific evidence. Given the novelty of these tools to managers, it is necessary to understand how the use of information generated by new technologies compares to the use of information provided by more conventional tools or dogma/experience. It is also important to communicate the types of new knowledge that can be generated by electronic tagging that have here-to-fore been unattainable [e.g., determining fate of individual animals (Yergey et al., 2012); identifying behavioral changes using animal movement data (Gurarie et al., 2009); evaluating consistency of behaviors and thus behavioral syndromes in wild animals (Harrison et al., 2015)]. Preparing managers for the capabilities of the technology so that they are ready to receive new, potentially transformative, information may be a useful strategy for helping to ensure that data from electronic tagging studies are more likely to be used by managers. There is a growing suite of “success stories” in application of electronic tagging and tracking techniques to management (e.g., Deguchi et al., 2014, 2016; Crossin et al., accepted) which is promising, but there is also need for additional social science research to better understand (from the perspective of the manager) the relevance of these techniques to contemporary management challenges.

Conservation dollars are limited and are allocated toward a diversity of species, habitats, countries, and activities (McCarthy et al., 2012). Many studies demonstrate that conservation resources are often not optimally allocated (Wu and Boggess, 1999; Wilson et al., 2006). For example, charismatic species (and scientific activities) receive disproportionately more funding than less-charismatic species (Bennett et al., 2015). Animal tracking has arisen as one such charismatic activity that has produced a number of scientific and conservation achievements (Burger and Shaffer, 2008; Block et al., 2011; Lascelles et al., 2016; Crossin et al., accepted).

Since studies of animal movement can be expensive (McGowan et al., 2016), managers with conservation dollars to spend should carefully weigh whether the data obtained through studies of animal movement are worth the cost given actual conservation needs and anticipated return on investment (McGowan and Possingham, 2016). We agree it is important to strategically assess the cost-benefit function of expensive tracking studies. However, funding for both animal movement studies and conservation practice comes from a wide variety of sources for a wide variety of reasons (Evans et al., 2012; Lennox, 2012). Some studies are born of the passion of private individuals, companies, or foundations for species, oceans, or animal migration and others are driven by organizational missions grounded in basic science or education and outreach. We posit that dollars coming from the above sources are often not in play in conservation prioritization discussions and their effect on conservation practice is added value.

It can be difficult to measure the downstream conservation impacts of movement studies that were conducted primarily for other reasons (basic science and discovery, education, etc.). These endeavors have drawn criticism regarding return on investment of expensive satellite tracking studies in the context of specific conservation planning scenarios (see McGowan et al., 2016). However, studies of animal movement include a wide-variety of approaches that provide critical pieces of biological information enabling us to determine species abundance trajectories, ecology of critical life history stages, and acceptable harvest or bycatch rates.

Movement ecology can provide unique insights for addressing difficult conservation and management problems. Technological advances are likely to increase the number and type of species and the range of body sizes followed, and habitats examined in movement studies. Improved data archiving, accessibility, sharing, and collaborative analysis/meta-analysis will increase the use of movement data. However, effective visualization, interpretation and communication of the results of movement studies will be critical to applying movement data in decision-making processes and realizing their full potential for conservation and management.

MO and A-LH were co-leads of manuscript preparation. Each author contributed a draft section of the manuscript and all six authors participated in revision.