Abstract Knowledge of when species remain in specified areas is essential for survey design, conservation, and management. Using species occurrence data to predict persistence in space and time (i.e., presence of one or more individuals of the species of interest within a defined spatial area over a duration of a specified number of days) may be possible with extensive survey effort and complex modeling, but such requirements pose challenges. Here, we present a method for estimating wildlife spatiotemporal persistence by (1) filtering data to contain detections and all surveys occurring 7 days following each detection within a spatial buffer around each detection (i.e., spatiotemporal detection buffer), (2) identifying redetections in each spatiotemporal detection buffer, and (3) grouping detection buffers temporally and spatially for bootstrap resampling. Our method avoids the need for mechanistic models of animal behavior while accommodating survey effort that may, at times, be sparse. We illustrate the approach using spatiotemporal data from 2010 to 2020 vessel‐based and aerial surveys of the North Atlantic right whale (Eubalaena glacialis), an endangered species that experiences various anthropogenic threats that are the focus of significant management actions. Our analyses suggested that persistence probabilities of North Atlantic right whales varied across time and space, which could guide management measures associated with forecasting or nowcasting spatiotemporal persistence for new detections. Our method can be applied to any species with repeated survey data and could facilitate dynamic management practices that effectively target conservation efforts. The presented method is especially helpful for rapid decision‐making.

Infectious diseases have detrimental impacts across wildlife taxa. Despite this, we often lack information on the complex spatial and contact structures of host populations, reducing our ability to understand disease spread and our preparedness for epidemic response. This is also prevalent in the marine environment, where rapid habitat changes due to anthropogenic disturbances and human-induced climate change are heightening the vulnerability of marine species to disease. Recognizing these risks, we leveraged a collated dataset to establish a data-driven epidemiological metapopulation model for Tamanend’s bottlenose dolphins ( Tursiops erebennus ), whose populations are periodically impacted by deadly respiratory disease. We found their spatial distribution and contact is heterogeneous throughout their habitat and by ecotype, which explains differences in past infection burdens. With our metapopulation approach, we demonstrate spatial hotspots for epidemic risk during migratory seasons and that populations in some central estuaries would be the most effective sentinels for disease surveillance. These mathematical models provide a generalizable, non-invasive tool that takes advantage of routinely collected wildlife data to mechanistically understand disease transmission and inform disease surveillance tactics. Our findings highlight the heterogeneities that play a crucial role in shaping the impacts of infectious diseases, and how a data-driven understanding of these mechanisms enhances epidemic preparedness.

Anthropogenic global change is occurring at alarming rates, leading to increased urgency in the ability to monitor wildlife health in real time. Monitoring sentinel marine species, such as bottlenose dolphins, is particularly important due to extensive anthropogenic modifications to their habitats. The most common non-invasive method of monitoring cetacean health is documentation of skin lesions, often associated with poor health or disease, but the current methodology is inefficient and imprecise. Recent advancements in technology, such as machine learning, can provide researchers with more efficient ecological monitoring methods to address health questions at both the population and the individual levels. Our work develops a machine learning model to classify skin lesions on the understudied Tamanend's bottlenose dolphins (Tursiops erebennus) of the Chesapeake Bay, using manual estimates of lesion presence in photographs. We assess the model's performance and find that our best model performs with a high mean average precision (65.6 %-86.8 %), and generally increased accuracy with improved photo quality. We also demonstrate the model's ability to address ecological questions across scales by generating model-based estimates of lesion prevalence and testing the effect of gregariousness on health status. At the population level, our model accurately estimates a prevalence of 72.1 % spot and 27.3% fringe ring lesions, with a slight underprediction compared to manual estimates (82.2 % and 32.1 %). On the other hand, we find that individual-level analyses from the model predictions may be more sensitive to data quality, and thus, some individual scale questions may not be feasible to address if data quality is inconsistent. Manually, we do find that lesion presence in individuals suggests a positive relationship between lesion presence and gregariousness. This work demonstrates that object detection models on photographic data are reasonably successful, highly efficient, and provide initial estimates on the health status of understudied populations of bottlenose dolphins.

Infectious diseases cause mass mortalities in wildlife populations globally, but the impact of host sociality on the spread of pathogens is often unknown. While host behaviors drive pathogen transmission, these behaviors vary individually which impacts both individual- and population-level disease outcomes. For example, delphinid species are regularly affected by serious respiratory diseases, but a lack of social behavior data means the structure of vulnerability in these ecosystem sentinels is poorly understood. To assess the role of variable social behavior on disease risk empirically, we collected behavioral data from two wild bottlenose dolphin populations (Tursiops spp.), developed network models that synthesize transmission contacts, and used an epidemiological model to predict disease consequences. We find that contacts are highly structured by age and sex, and that individuals preferentially contact others in their own demographic group. These patterns, in turn, drive heterogeneity in infection risk, which we support using empirical data from a past disease outbreak. Our work characterizes the impact of social dynamics on infectious disease risk, which can inform the structure of vulnerability for future epizootics across diverse delphinid species.

Vessel strikes are a substantial source of mortality for large whales worldwide and may pose conservation threats for small populations. Model-based estimates of mortality rates, which inform management strategies to reduce vessel strike mortality, typically assume a reduced likelihood that a whale-vessel collision will be lethal to the whale at slower vessel speeds. In this study, we reviewed and updated available data on observed whale-vessel interactions in U.S. waters and developed a new model characterizing the probability that an interaction will be lethal to the whale as a function of vessel speed, length (as a proxy for mass), and whale taxon. We found a significant effect of vessel size class on the probability of lethality. In addition, decreasing vessel speeds reduced the likelihood of a lethal outcome for all vessel size classes, but this effect was strongest for vessels less than 108m in length. The probability that a strike by a very large ocean-going vessel will be lethal exceeded 0.80 at all speeds above 5 knots. Whale taxon also affected both the likelihood of a lethal strike and the effect of vessel speed. Humpback whales (Megaptera novaeangliae) had significantly lower rates of lethal strikes compared to other large whales. This difference may be associated with data limitations, differing behavioral responses between species, varying vessel types between regions or differences in body composition and blubber thickness. The model is consistent with biophysical models that demonstrate a high rate of strike lethality for large vessels with high masses. Vessel speed restrictions are one of the primary approaches to reduce the risk of vessel strikes to whales in the face of continued industrialization of the oceans, and the model presented here will help better inform management efforts.

Vessel strikes are a critical threat to endangered North Atlantic right whales (Eubalaena glacialis), significantly contributing to their elevated mortality. Accurate estimates of these mortality rates are essential for developing effective management strategies to aid in the species’ recovery. This study enhances existing vessel strike models by incorporating detailed regional data on vessel traffic characteristics as well as whale distribution and behavior. Our model assesses the spatial and temporal variability in vessel strike risk along the U.S. east coast apportioned into three vessel length classes (26–65 feet, 65–350 feet, > 350 feet). By including regional right whale depth distributions and parameterizing potential whale avoidance based on factors such as descent rate, bottom depth, and vessel speed and size, the model provides a refined estimation of mortality risk. We also address the underrepresentation of smaller vessel activity via a correction factor, offering a more accurate annual mortality risk estimate for each vessel size class. These findings highlight that vessels > 350 feet in length pose the greatest risk to right whales. Simulations of reduced vessel speeds indicate that speed measures can mitigate mortality rates; however, residual risk remains even at speeds of 10 knots or less suggesting limitations to this mitigation approach.

Infectious respiratory diseases have detrimental impacts across wildlife taxa, particularly in marine species. Despite this vulnerability, we lack information on the complex spatial and contact structures of marine populations which reduces our ability to understand disease spread and our preparedness for epidemic response. We leveraged a collated dataset to establish the first data-driven epidemiological model on a cetacean species, the Tamanends bottlenose dolphin (Tursiops erebennus), whose populations are periodically impacted by deadly respiratory disease in the northwest Atlantic. We found their spatial distribution and contact is heterogeneous along the coastline and varies by ecotype, which explains differences in infection burdens observed in past outbreaks. We also determined that outbreaks beginning in northern parts of their habitat during migratory seasons have the highest epidemic risk and that dolphins in North Carolina estuaries would be the best sentinels for disease surveillance. Our mathematical model provides a generalizable, non-invasive tool that takes advantage of routinely collected marine mammal data to mechanistically understand disease transmission and inform disease surveillance tactics for marine sentinels. Our findings highlight the heterogeneities that play a crucial role in shaping the impacts of infectious diseases in wildlife, and how a data-driven understanding of these mechanisms can enhance epidemic preparedness. ### Competing Interest Statement The authors have declared no competing interest.

The Critically Endangered North Atlantic right whale Eubalaena glacialis entered a population decline around 2011. To save this species without closing the ocean to human activities requires detailed information about its intra-annual density patterns that can be used to assess and mitigate human-caused risks. Using 2.9 million km of visual line-transect survey effort from the US Atlantic and Canadian Maritimes conducted in 2003-2020 by 11 institutions, we modeled the absolute density (ind. km-2) of the species using spatial, temporal, and environmental covariates at a monthly time step. We accounted for detectability differences between survey platforms, teams, and conditions, and corrected all data for perception and availability biases, accounting for platform differences, whale dive behavior, group composition, and group size. We produced maps of predicted density and evaluated our results using independently collected passive acoustic monitoring (PAM) data. Densities correlated positively (r = 0.46, ρ = 0.58, τ = 0.46) with acoustic detection rates obtained at 492 stationary PAM recorders deployed across the study area (mean recorder duration = 138 d). This is the first study to quantify the concurrence of visual and acoustic observations of the species in US waters. We summarized predictions into mean monthly density and uncertainty maps for the 2003-2009 and 2010-2020 eras, based on the significant changes in the species’ spatial distribution that began around 2010. The results quantify the striking distribution shifts and provide effort- and bias-corrected density surfaces to inform risk assessments, estimations of take, and marine spatial planning.

Methods to evaluate strategies to reduce the risk of vessels striking whales are needed to balance species protections with economic consequences. Previously used simplistic methods do not include important elements of vessel-strike risk. More complex methods often include parameters that have not been estimated for whales. Additionally, the whale and vessel metrics used in all methods are important because they may lead to biases in estimated risk reductions. We build a simple metric, Total PLETHd, from three components: (1) the relationship between vessel speed and the probability that a strike is lethal (PLETH), (2) vessel transit distance, and (3) whale distributions. Total PLETHd is calculated by multiplying estimates of whale distribution by the sum of transit distance multiplied by transit PLETH. We use this metric to assess risk reductions for North Atlantic right, humpback, fin, and sei whales on the United States East Coast. We found that a 10 kt speed restriction was necessary for reducing risk and that speed restrictions applied in broad areas defined by whale habitat were almost as effective as restrictions applied throughout all East Coast waters. While our areas were primarily defined to protect right whales, our results suggest they also protect humpback, fin, and sei whales. Total PLETHd represents an improvement over previous methods for estimating risk reductions because it addresses limitations in these methods. It can be used to estimate risk reductions for multiple species associated with management strategies, including changing vessel routes and implementing speed restrictions in different areas and time periods.

Dolphin morbillivirus has caused mass mortalities in dolphin populations globally. Given their role as ecosystem sentinels, mass mortalities among these populations can be detrimental. Morbillivirus is transmitted through respiratory droplets and occurs when dolphins breathe synchronously, a variable social behavior. To assess the role of variable social behavior on disease risk empirically, we collected behavioral data from wild bottlenose dolphins ( Tursiops erebennus ), develop network models that synthesize transmission contacts, and use an epidemiological model to predict disease consequences. We find that juveniles have more contacts than adults, adult males have more contacts than adult females, and that individuals preferentially contact others in their own demographic group. These patterns translate to higher infection risk for juveniles and adult males, which we validate using data from a morbillivirus outbreak. Our work characterizes the impact of bottlenose dolphin social dynamics on infectious disease risk and informs the structure of vulnerability for future epizootics.### Competing Interest StatementThe authors have declared no competing interest.

As demands for wildlife tourism increase, provisioning has become a popular means of providing up-close viewing to the public. At Monkey Mia, Shark Bay, Australia, up to five adult female Indo-Pacific bottlenose dolphins (Tursiops aduncus) visit a 100 m stretch of beach daily to receive fish handouts. In 2011, a severe marine heatwave (MHW) devastated seagrass and fish populations in Shark Bay. Offspring survival declined precipitously among seagrass specialists (dolphins that forage disproportionately in seagrass habitat). As all provisioned dolphins at the site are seagrass specialists, we examined how provisioned and non-provisioned seagrass specialists responded to the MHW. Using 27 years of data we compare habitat use, home range size, calf mortality, and predation risk between provisioned and non-provisioned females and their offspring before and after the MHW. Our results show that provisioned females have extremely small home ranges compared to non-provisioned females, a pattern attributable to their efforts to remain near the site of fish handouts. However, weaned offspring (juveniles) born to provisioned females who are not provisioned themselves also had much smaller home ranges, suggesting a persistent maternal effect on their behavior. After the MHW, adult females increased their use of seagrass habitats, but not their home range size. Provisioned females had significantly lower calf mortality than non-provisioned females, a pattern most evident pre-MHW, and, in the first 5 years after the MHW (peri-MHW, 2011–2015), calf mortality did not significantly increase for either group. However, the ecosystem did not recover, and post-MHW (2016–2020), calf mortality was substantially higher, regardless of provisioning status. With few survivors, the impact of the MHW on juvenile mortality post-weaning is not known. However, over three decades, juvenile mortality among offspring of provisioned vs. non-provisioned females did not statistically differ. Thus, the survival benefits accrued to calves in the provisioned group likely cease after weaning. Finally, although shark attack rates on seagrass specialists did not change over time, elevated predation on calves cannot be ruled out as a cause of death post-MHW. We discuss our results as they relate to anthropogenic influences on dolphin behavioral plasticity and responses to extreme climate events.

Sequence learning underlies many uniquely human behaviours, from complex tool use to language and ritual. To understand whether this fundamental cognitive feature is uniquely derived in humans requires a comparative approach. We propose that the vicarious (but not individual) learning of novel arbitrary sequences represents a human cognitive specialization. To test this hypothesis, we compared the abilities of human children aged 3–5 years and orangutans to learn different types of arbitrary sequences (item-based and spatial-based). Sequences could be learned individually (by trial and error) or vicariously from a human (social) demonstrator or a computer (ghost control). We found that both children and orangutans recalled both types of sequence following trial-and-error learning; older children also learned both types of sequence following social and ghost demonstrations. Orangutans' success individually learning arbitrary sequences shows that their failure to do so in some vicarious learning conditions is not owing to general representational problems. These results provide new insights into some of the most persistent discontinuities observed between humans and other great apes in terms of complex tool use, language and ritual, all of which involve the cultural learning of novel arbitrary sequences. This article is part of the theme issue ‘Ritual renaissance: new insights into the most human of behaviours’.

Does imitation involve specialized mechanisms or general—unspecialized—learning processes? To address this question, preschoolers (3- and 4-year-olds) were assigned to one of four "practice" groups. Before and after the practice phases, each group was tested on a novel Spatial Imitation sequence. During the practice phase, children in the Spatial Imitation group practiced jointly attending, vicariously encoding, and copying the novel spatial sequences. In the Item Imitation group, children practiced jointly attending, vicariously encoding, and copying novel item sequences. In the Trial-and-Error group, children practiced encoding and recalling a series of novel spatial sequences entirely through individual (operant) learning. In the Free Play (no practice) control group, children played a touchscreen drawing game that controlled for practice time on the touchscreen and mirrored some of the same actions and responses used in the experimental conditions. Results of the difference between pre- and post-practice effects on novel spatial imitation sequences showed that only the Spatial Imitation practice group significantly improved relative to the Free Play group. Individual Spatial Trial-and-Error practice did not significantly improve spatial imitation. The effect of Item Imitation practice was intermediate. These results are inconsistent with the hypothesis that general processes alone--or primarily--support imitation learning and is more consistent with a mosaic model that posits an additive—interaction—effect on imitation performance where a more general social cognitive mechanism (i.e., natural pedagogy) gathers the relevant information from the demonstration and another more specialized mechanism (i.e., imitation specific) transforms that information into a matching response.

Long-term studies often rely on natural markings for individual identification across time. The primary method for identification in small cetaceans relies on dorsal fin shape, scars, and other natural markings. However, dorsal fin markings can vary substantially over time and the dorsal fin can become unrecognizable after an encounter with a boat or shark. Although dorsal fins have the advantage in that they always break the water surface when the cetacean breathes, other physical features, such as body scars and pigmentation patterns can supplement. The goal of this study was to explore the use of dorso-lateral pigment patterns to identify wild bottlenose dolphins. We employed photographic pigment matching tests to determine if pigmentation patterns showed (1) longitudinal consistency and (2) bilateral symmetry using a 30 yr photographic database of bottlenose dolphins (Tursiops aduncus). We compared experienced dolphin researchers and inexperienced undergraduate student subjects in their ability to accurately match images. Both experienced and inexperienced subjects correctly matched dolphin individuals at a rate significantly above chance, even though they only had 10 s to make the match. These results demonstrate that pigment patterns can be used to reliably identify individual wild bottlenose dolphins, and likely other small cetacean species at other sites.

Animals’ affiliative behaviour is, in many species, driven by population density. Although the causes of such an effect are probably varied, affiliative social behaviour can sometimes be used to minimise conflict and competition when conspecific density is high. However, individuals might instead use multiple different social tactics (e.g. social avoidance or social preference) in order to optimally minimise competition and social conflict at different local densities. Here, we investigated whether eastern water dragons (Intellegama lesueurii) use alternative social tactics at different local densities. Interestingly, we found that whilst the number of casual associations per individual increased linearly with density, as predicted by our null expectation, the relationship with density differed between social avoidance and social preference. In particular, individuals had more preferential associations at intermediate density but more avoidances at high density. This suggests that both male and female dragons use alternative social tactics according to the density of their social environment, possibly to optimally reduce social conflict.

Maternal care varies across taxa from brief, minimal care to long-term, intensive care. Mammalian mothers provide extensive and energetically expensive care by definition through pregnancy and lactation, which can extend for years, resulting in behavioural trade-offs between resource acquisition and direct care. In marine environments, mammalian mothers face unique challenges, such as the inability to cache or den their offspring while diving for prey. Dolphin newborns are precocious, accomplishing shallow dives in the first few weeks of life, however, fully mature diving and breath-holding capabilities take years to develop. Consequently, mothers are faced with a trade-off between diving and foraging or remaining close to and protecting their calves at the surface. Here we examined this trade-off, specifically by investigating whether mothers change their dive durations, especially during foraging, as a function of calf age. We used a longitudinal (1988-2014) data set on wild bottlenose dolphins, Tursiops aduncus, in Shark Bay, Western Australia, which included 27 388 dive bouts from mothers (N = 26) and calves (N = 41). Our results show that maternal diving behaviour changes in response to calf age and sex. While both male and female calves increased their dive durations with age as expected, mothers were more likely to adjust their diving behaviour to accommodate female but not male calves, especially when daughters were in close proximity. This is consistent with findings that vertical social learning is more critical for daughters than for sons, and may reflect the sex-specific foraging and social tactics of the males and females more generally. (C) 2018 The Association for the Study of Animal Behaviour. Published by Elsevier Ltd. All rights reserved.

Sex differences in adult behaviour are well documented, but less is known about the ontogeny of these differences. In mammals, the transition to independence, from infancy to the juvenile period, is when these sex differences are likely to become prominent. Here, we examined sex differences in behavioural development among calf and juvenile bottlenose dolphins, Tursiops aduncus, from 2 years preweaning to 2 years postweaning and whether these differences were consistent, or not, with three nonmutually exclusive hypotheses regarding the function of the juvenile period: the social skills, protection/safety and energy allocation hypothesis. All hypotheses received some support, but strikingly so for females. First, sex differences in the nature and quality of juvenile social bonds appear to foreshadow adult association patterns. Juveniles had a greater proportion of same-sex associates than calves. Second, although neither sex increased their number of associates from infancy to juvenility, a pattern that might mitigate predation risk, avoidance between juveniles and adult males suggests that both sexes reduce the likelihood of conspecific aggression. This pattern was more marked for juvenile females. Third, females, but not males, increased foraging rates from late infancy to the early juvenile period, even surpassing typical adult female foraging rates. This is likely related to the future energetic demands of maternal investment and skill development required for specialized foraging tactics, which are female biased in this population. This study provides a first step towards understanding the transition into independence for cetaceans, insight into how sex differences develop and a glimpse into the function of the juvenile period. (C) 2017 The Association for the Study of Animal Behaviour. Published by Elsevier Ltd. All rights reserved.

Network null models are important to drawing conclusions about individual- and population-(or graph) level metrics. While the null models of binary networks are well studied, recent literature on weighted networks suggests that: (1) many so-called 'weighted metrics' do not actually depend on weights, and (2) many metrics that supposedly measure higher-order social structure actually are highly correlated with individual-level attributes. This is important for behavioural ecology studies where weighted network analyses predominate, but there is no consensus on how null models should be specified. Using real social networks, we developed three null models that address two technical challenges in the networks of social animals: (1) how to specify null models that are suitable for 'proportion-weighted networks' based on indices such as the half-weight index; and (2) how to condition on the degree-and strength-sequence and both. We compared 11 metrics with each other and against null-model expectations for 10 social networks of bottlenose dolphin, Tursiops aduncus, from Shark Bay, Australia. Observed metric values were similar to null-model expectations for some weighted metrics, such as centrality measures, disparity and connectivity, whereas other metrics such as affinity and clustering were informative about dolphin social structure. Because weighted metrics can differ in their sensitivity to the degree-sequence or strength-sequence, conditioning on both is a more reliable and conservative null model than the more common strength-preserving null-model for weighted networks. Other social structure analyses, such as community partitioning by weighted Modularity optimization, were much less sensitive to the underlying null-model. Lastly, in contrast to results in other scientific disciplines, we found that many weighted metrics do not depend trivially on topology; rather, the weight distribution contains important information about dolphin social structure. (C) 2015 The Association for the Study of Animal Behaviour. Published by Elsevier Ltd. All rights reserved.