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Visual surveys are a common method of obtaining data for ecological studies, including studies that develop models (e.g. species distribution models). In the case of transect or non-transect line surveys, data must often be partitioned into spatiotemporal units (i.e. samples) before being modelled. This processing typically follows one of three approaches —the grid, segment and point approaches— each with its own variations. Currently, processing of visual survey data is done in custom scripts that can be time-consuming and technically demanding to develop, which hinders the development of ecological models. This issue is exacerbated if multiple approaches and/or variations are to be applied. Here, we present sampley, a user-friendly Python package for processing visual survey data into samples. It operates on various common formats and filetypes, ensuring its applicability to diverse datasets and compatibility with other software. It can process data by multiple variations of the grid, segment and point approaches. As this processing follows a straightforward sequence of stages and involves a limited number of functions, it is easy to learn and use. The combination of these traits will increase efficiency and reproducibility of survey data processing and allow researchers to readily trial different methods. In this paper, we provide a description of the package — the types of data that can be processed, the approaches and variations available and the stages involved in processing. An example application, based on a mock dataset consisting of survey tracks, sightings and in situ environmental data, is also provided with descriptions of each stage. 

North Atlantic right whales are a critically endangered species of baleen whale facing threats from vessel strikes, fishing gear entanglement, and anthropogenic climate change. Following the declaration of an Unusual Mortality Event in 2017, there has been a push for increased conservation efforts propelled through policy activity in the United States and Canada. Policy diffusion literature suggests that a policy window opens after a focusing event occurs, like an Unusual Mortality Event, and that policy networks between states will facilitate the spread of legislation. This study examines databases of proposed legislation related to North Atlantic right whales from the United States Congress from 1993 to 2024, and 14 East Coast state legislatures bordering the Atlantic Ocean from 2000 to 2024. There were 49 bills introduced in Congress and 56 bills introduced in 5 East Coast state legislatures over the assessed time period. Both federal and state legislative data indicated that a policy window opened in 2017. However, text analysis of identified bills indicated no evidence of policy diffusion between states or from states to the federal government. Instead, we find that states with Democratic-controlled legislatures propose more action-oriented policies while states with Republican-controlled legislatures propose signaling policies. This suggests that under federalism, states react to policy windows in a variety of ways based on the goals of their constituents, informing how stakeholders should lobby for conservation policies in the future. 

Understanding a population’s distribution depends on observing the presence and movement of individuals throughout their range. For highly mobile marine species, these observations typically rely on high effort monitoring programs. Tracking enough individuals to understand trends in movement behavior is not always logistically feasible, and animals are less likely to be observed in migratory or transitional habitats. To optimize observation data we built a Brownian bridge movement model to generate spatially and temporally explicit space use estimations of individuals along tracks created from intermittent sightings of North Atlantic right whales from 1980 to 2022. Right whales can be identified by unique callosities and markings, providing a non-invasive opportunity to link sightings to individual movement. This model generated location probability estimates of medium- and large-scale movements in biologically plausible habitats. A total of 351,214 d of occurrence distributions were calculated from 67,840 sightings attributed to 806 individuals, representing more than a five-fold increase in individual spatial information. From 1980 to 2022, the model generated space use estimates for at least one whale on 75.7% of days, compared to the underlying visual sightings data, which only provided observations on 38.7% of days. Model outputs compared to tracks of tagged whales demonstrated proficiency estimating space use across regions. The occurrence distributions produced depict known changes in seasonal and decadal space use and estimate transitional space use where observations are sparse. These methods improve spatial distribution predictions in intermittently observed animals and expand the utility of stationary sightings without constraining predictions to historical relationships with the environment. 

Baleen whales are key consumers in marine habitats that serve as vectors of nutrients, but their populations have been slow to recover from past commercial whaling due to their low reproductive rates and ongoing anthropogenic threats. Climate impacts have become central to the demography and habitat use of baleen whales, and conservation efforts must account for these impacts to be effective. However, knowledge of baleen whale climate responses is lacking, and current survey effort is insufficient to capture changes in migration and habitat use for many species. Due to their unique combination of ecological and life history characteristics, baleen whales are particularly vulnerable to climate change and their climate responses should be expected to differ fundamentally from those of other marine consumers. These characteristics include the need for both large quantities and high densities of prey, the need to accumulate large energy reserves seasonally, as well as highly migratory movements and the reliance on high-latitude foraging areas with narrow seasonal windows in resource availability. Climate responses in baleen whales may involve abrupt changes in foraging habitat in contrast to more gradual poleward shifts observed in other species, changes in the timing, extent or tendency for migration, and changes in energy accumulation or fitness. Recognizing that climate impacts may differ from other species is critical to measuring and anticipating changes to baleen whale populations in the face of ongoing climate change, and to effectively managing their populations in the future. North Atlantic right whales (Eubalena glacialis), arguably the best studied baleen whale species at a population scale, exemplify expectations for baleen whale climate responses and the implications for future management and conservation. Right whales have shown abrupt changes to traditional patterns of habitat use and migratory behavior, with major implications for the effectiveness of existing protections. Understanding and detecting baleen whale climate responses and effectively guiding management in the face of ongoing change will require increased survey effort and novel methods to survey remote habitats; improved knowledge of mechanisms of prey aggregation and climate impacts on these processes; and continued development and refinement of mechanistic models and dynamic management strategies.