Ecological forecasts for marine resource management during climate extremes.

Forecasting weather has become commonplace, but as society faces novel and uncertain environmental conditions there is a critical need to forecast ecology. Forewarning of ecosystem conditions during climate extremes can support proactive decision-making, yet applications of ecological forecasts are still limited. We showcase the capacity for existing marine management tools to transition to a forecasting configuration and provide skilful ecological forecasts up to 12 months in advance. The management tools use ocean temperature anomalies to help mitigate whale entanglements and sea turtle bycatch, and we show that forecasts can forewarn of human-wildlife interactions caused by unprecedented climate extremes. We further show that regionally downscaled forecasts are not a necessity for ecological forecasting and can be less skilful than global forecasts if they have fewer ensemble members. Our results highlight capacity for ecological forecasts to be explored for regions without the infrastructure or capacity to regionally downscale, ultimately helping to improve marine resource management and climate adaptation globally.

Impacts of marine heatwaves on top predator distributions are variable but predictable.

Marine heatwaves cause widespread environmental, biological, and socio-economic impacts, placing them at the forefront of 21st-century management challenges. However, heatwaves vary in intensity and evolution, and a paucity of information on how this variability impacts marine species limits our ability to proactively manage for these extreme events. Here, we model the effects of four recent heatwaves (2014, 2015, 2019, 2020) in the Northeastern Pacific on the distributions of 14 top predator species of ecological, cultural, and commercial importance. Predicted responses were highly variable across species and heatwaves, ranging from near total loss of habitat to a two-fold increase. Heatwaves rapidly altered political bio-geographies, with up to 10% of predicted habitat across all species shifting jurisdictions during individual heatwaves. The variability in predicted responses across species and heatwaves portends the need for novel management solutions that can rapidly respond to extreme climate events. As proof-of-concept, we developed an operational dynamic ocean management tool that predicts predator distributions and responses to extreme conditions in near real-time.

Species redistribution creates unequal outcomes for multispecies fisheries under projected climate change.

Climate change drives species distribution shifts, affecting the availability of resources people rely upon for food and livelihoods. These impacts are complex, manifest at local scales, and have diverse effects across multiple species. However, for wild capture fisheries, current understanding is dominated by predictions for individual species at coarse spatial scales. We show that species-specific responses to localized environmental changes will alter the collection of co-occurring species within established fishing footprints along the U.S. West Coast. We demonstrate that availability of the most economically valuable, primary target species is highly likely to decline coastwide in response to warming and reduced oxygen concentrations, while availability of the most abundant, secondary target species will potentially increase. A spatial reshuffling of primary and secondary target species suggests regionally heterogeneous opportunities for fishers to adapt by changing where or what they fish. Developing foresight into the collective responses of species at local scales will enable more effective and tangible adaptation pathways for fishing communities.

Widespread habitat loss and redistribution of marine top predators in a changing ocean.

The Northwest Atlantic Ocean and Gulf of Mexico are among the fastest warming ocean regions, a trend that is expected to continue through this century with far-reaching implications for marine ecosystems. We examine the distribution of 12 highly migratory top predator species using predictive models and project expected habitat changes using downscaled climate models. Our models predict widespread losses of suitable habitat for most species, concurrent with substantial northward displacement of core habitats >500 km. These changes include up to >70% loss of suitable habitat area for some commercially and ecologically important species. We also identify predicted hot spots of multi-species habitat loss focused offshore of the U.S. Southeast and Mid-Atlantic coasts. For several species, the predicted changes are already underway, which are likely to have substantial impacts on the efficacy of static regulatory frameworks used to manage highly migratory species. The ongoing and projected effects of climate change highlight the urgent need to adaptively and proactively manage dynamic marine ecosystems.

Building use-inspired species distribution models: Using multiple data types to examine and improve model performance.

Species distribution models (SDMs) are becoming an important tool for marine conservation and management. Yet while there is an increasing diversity and volume of marine biodiversity data for training SDMs, little practical guidance is available on how to leverage distinct data types to build robust models. We explored the effect of different data types on the fit, performance and predictive ability of SDMs by comparing models trained with four data types for a heavily exploited pelagic fish, the blue shark (Prionace glauca), in the Northwest Atlantic: two fishery dependent (conventional mark-recapture tags, fisheries observer records) and two fishery independent (satellite-linked electronic tags, pop-up archival tags). We found that all four data types can result in robust models, but differences among spatial predictions highlighted the need to consider ecological realism in model selection and interpretation regardless of data type. Differences among models were primarily attributed to biases in how each data type, and the associated representation of absences, sampled the environment and summarized the resulting species distributions. Outputs from model ensembles and a model trained on all pooled data both proved effective for combining inferences across data types and provided more ecologically realistic predictions than individual models. Our results provide valuable guidance for practitioners developing SDMs. With increasing access to diverse data sources, future work should further develop truly integrative modeling approaches that can explicitly leverage the strengths of individual data types while statistically accounting for limitations, such as sampling biases.

Scaling of Activity Space in Marine Organisms across Latitudinal Gradients.

AbstractUnifying models have shown that the amount of space used by animals (e.g., activity space, home range) scales allometrically with body mass for terrestrial taxa; however, such relationships are far less clear for marine species. We compiled movement data from 1,596 individuals across 79 taxa collected using a continental passive acoustic telemetry network of acoustic receivers to assess allometric scaling of activity space. We found that ectothermic marine taxa do exhibit allometric scaling for activity space, with an overall scaling exponent of 0.64. However, body mass alone explained only 35% of the variation, with the remaining variation best explained by trophic position for teleosts and latitude for sharks, rays, and marine reptiles. Taxon-specific allometric relationships highlighted weaker scaling exponents among teleost fish species (0.07) than sharks (0.96), rays (0.55), and marine reptiles (0.57). The allometric scaling relationship and scaling exponents for the marine taxonomic groups examined were lower than those reported from studies that had collated both marine and terrestrial species data derived using various tracking methods. We propose that these disparities arise because previous work integrated summarized data across many studies that used differing methods for collecting and quantifying activity space, introducing considerable uncertainty into slope estimates. Our findings highlight the benefit of using large-scale, coordinated animal biotelemetry networks to address cross-taxa evolutionary and ecological questions.

An anchovy ecosystem indicator of marine predator foraging and reproduction.

Forage fishes are key energy conduits that transfer primary and secondary productivity to higher trophic levels. As novel environmental conditions caused by climate change alter ecosystems and predator-prey dynamics, there is a critical need to understand how forage fish control bottom-up forcing of food web dynamics. In the northeast Pacific, northern anchovy (Engraulis mordax) is an important forage species with high interannual variability in population size that subsequently impacts the foraging and reproductive ecology of marine predators. Anchovy habitat suitability from a species distribution model (SDM) was assessed as an indicator of the diet, distribution and reproduction of four predator species. Across 22 years (1998-2019), this anchovy ecosystem indicator (AEI) was significantly positively correlated with diet composition of all species and the distribution of common murres (Uria aalge), Brandt's cormorants (Phalacrocorax penicillatus) and California sea lions (Zalophus californianus), but not rhinoceros auklets (Cerorhinca monocerata). The capacity for the AEI to explain variability in predator reproduction varied by species but was strongest with cormorants and sea lions. The AEI demonstrates the utility of forage SDMs in creating ecosystem indicators to guide ecosystem-based management.

Revenue loss due to whale entanglement mitigation and fishery closures.

Whale entanglements with fishing gear, exacerbated by changing environmental conditions, pose significant risk to whale populations. Management tools used to reduce entanglement risk, for example temporary area restrictions on fishing, can have negative economic consequences for fishing communities. Balancing whale protection with sustaining productive fisheries is therefore a challenge experienced worldwide. In the California Current Ecosystem, ecosystem indicators have been used to understand the environmental dynamics that lead to increased whale entanglement risk in a lucrative crab fishery. However, an assessment of socio-economic risk for this fishery, as in many other regions, is missing. We estimate retrospectively the losses from ex-vessel revenue experienced by commercial Dungeness crab fishers in California during two seasons subject to whale entanglement mitigation measures using a Linear-Cragg hurdle modeling approach which incorporated estimates of pre-season crab abundance. In the 2020 fishing season, our results suggest total revenues would have been $14.4 million higher in the Central Management Area of California in the absence of closures and other disturbances. In the 2019 fishing season, our results suggest ex-vessel revenues would have been $9.4 million higher in the Central Management Area and $0.3 million higher in the Northern Management Area. Our evaluation should motivate the development of strategies which maximize whale protection whilst promoting productive, sustainable and economically-viable fisheries.

Recommendations for quantifying and reducing uncertainty in climate projections of species distributions.

Projecting the future distributions of commercially and ecologically important species has become a critical approach for ecosystem managers to strategically anticipate change, but large uncertainties in projections limit climate adaptation planning. Although distribution projections are primarily used to understand the scope of potential change-rather than accurately predict specific outcomes-it is nonetheless essential to understand where and why projections can give implausible results and to identify which processes contribute to uncertainty. Here, we use a series of simulated species distributions, an ensemble of 252 species distribution models, and an ensemble of three regional ocean climate projections, to isolate the influences of uncertainty from earth system model spread and from ecological modeling. The simulations encompass marine species with different functional traits and ecological preferences to more broadly address resource manager and fishery stakeholder needs, and provide a simulated true state with which to evaluate projections. We present our results relative to the degree of environmental extrapolation from historical conditions, which helps facilitate interpretation by ecological modelers working in diverse systems. We found uncertainty associated with species distribution models can exceed uncertainty generated from diverging earth system models (up to 70% of total uncertainty by 2100), and that this result was consistent across species traits. Species distribution model uncertainty increased through time and was primarily related to the degree to which models extrapolated into novel environmental conditions but moderated by how well models captured the underlying dynamics driving species distributions. The predictive power of simulated species distribution models remained relatively high in the first 30 years of projections, in alignment with the time period in which stakeholders make strategic decisions based on climate information. By understanding sources of uncertainty, and how they change at different forecast horizons, we provide recommendations for projecting species distribution models under global climate change.

Global seasonal forecasts of marine heatwaves.

Marine heatwaves (MHWs)-periods of exceptionally warm ocean temperature lasting weeks to years-are now widely recognized for their capacity to disrupt marine ecosystems1-3. The substantial ecological and socioeconomic impacts of these extreme events present significant challenges to marine resource managers4-7, who would benefit from forewarning of MHWs to facilitate proactive decision-making8-11. However, despite extensive research into the physical drivers of MHWs11,12, there has been no comprehensive global assessment of our ability to predict these events. Here we use a large multimodel ensemble of global climate forecasts13,14 to develop and assess MHW forecasts that cover the world's oceans with lead times of up to a year. Using 30 years of retrospective forecasts, we show that the onset, intensity and duration of MHWs are often predictable, with skilful forecasts possible from 1 to 12 months in advance depending on region, season and the state of large-scale climate modes, such as the El Niño/Southern Oscillation. We discuss considerations for setting decision thresholds based on the probability that a MHW will occur, empowering stakeholders to take appropriate actions based on their risk profile. These results highlight the potential for operational MHW forecasts, analogous to forecasts of extreme weather phenomena, to promote climate resilience in global marine ecosystems.

Trade-offs between bycatch and target catches in static versus dynamic fishery closures.

While there have been recent improvements in reducing bycatch in many fisheries, bycatch remains a threat for numerous species around the globe. Static spatial and temporal closures are used in many places as a tool to reduce bycatch. However, their effectiveness in achieving this goal is uncertain, particularly for highly mobile species. We evaluated evidence for the effects of temporal, static, and dynamic area closures on the bycatch and target catch of 15 fisheries around the world. Assuming perfect knowledge of where the catch and bycatch occurs and a closure of 30% of the fishing area, we found that dynamic area closures could reduce bycatch by an average of 57% without sacrificing catch of target species, compared to 16% reductions in bycatch achievable by static closures. The degree of bycatch reduction achievable for a certain quantity of target catch was related to the correlation in space and time between target and bycatch species. If the correlation was high, it was harder to find an area to reduce bycatch without sacrificing catch of target species. If the goal of spatial closures is to reduce bycatch, our results suggest that dynamic management provides substantially better outcomes than classic static marine area closures. The use of dynamic ocean management might be difficult to implement and enforce in many regions. Nevertheless, dynamic approaches will be increasingly valuable as climate change drives species and fisheries into new habitats or extended ranges, altering species-fishery interactions and underscoring the need for more responsive and flexible regulatory mechanisms.

Equity in science: advocating for a triple-blind review system.

We propose 'triple-blind review' for peer-reviewed journals - a process that keeps author identities and affiliations blind to manuscript editors until after first appraisal. Blinded appraisal will help to reduce the biases that negatively affect under-represented and minority scientists, ultimately better supporting equity in scientific publishing.

Flexible use of a dynamic energy landscape buffers a marine predator against extreme climate variability.

Animal migrations track predictable seasonal patterns of resource availability and suitable thermal habitat. As climate change alters this 'energy landscape', some migratory species may struggle to adapt. We examined how climate variability influences movements, thermal habitat selection and energy intake by juvenile Pacific bluefin tuna (Thunnus orientalis) during seasonal foraging migrations in the California Current. We tracked 242 tuna across 15 years (2002-2016) with high-resolution archival tags, estimating their daily energy intake via abdominal warming associated with digestion (the 'heat increment of feeding'). The poleward extent of foraging migrations was flexible in response to climate variability, allowing tuna to track poleward displacements of thermal habitat where their standard metabolic rates were minimized. During a marine heatwave that saw temperature anomalies of up to +2.5°C in the California Current, spatially explicit energy intake by tuna was approximately 15% lower than average. However, by shifting their mean seasonal migration approximately 900 km poleward, tuna remained in waters within their optimal temperature range and increased their energy intake. Our findings illustrate how tradeoffs between physiology and prey availability structure migration in a highly mobile vertebrate, and suggest that flexible migration strategies can buffer animals against energetic costs associated with climate variability and change.

Where did they not go? Considerations for generating pseudo-absences for telemetry-based habitat models.

BACKGROUND: Habitat suitability models give insight into the ecological drivers of species distributions and are increasingly common in management and conservation planning. Telemetry data can be used in habitat models to describe where animals were present, however this requires the use of presence-only modeling approaches or the generation of 'pseudo-absences' to simulate locations where animals did not go. To highlight considerations for generating pseudo-absences for telemetry-based habitat models, we explored how different methods of pseudo-absence generation affect model performance across species' movement strategies, model types, and environments. METHODS: We built habitat models for marine and terrestrial case studies, Northeast Pacific blue whales (Balaenoptera musculus) and African elephants (Loxodonta africana). We tested four pseudo-absence generation methods commonly used in telemetry-based habitat models: (1) background sampling; (2) sampling within a buffer zone around presence locations; (3) correlated random walks beginning at the tag release location; (4) reverse correlated random walks beginning at the last tag location. Habitat models were built using generalised linear mixed models, generalised additive mixed models, and boosted regression trees. RESULTS: We found that the separation in environmental niche space between presences and pseudo-absences was the single most important driver of model explanatory power and predictive skill. This result was consistent across marine and terrestrial habitats, two species with vastly different movement syndromes, and three different model types. The best-performing pseudo-absence method depended on which created the greatest environmental separation: background sampling for blue whales and reverse correlated random walks for elephants. However, despite the fact that models with greater environmental separation performed better according to traditional predictive skill metrics, they did not always produce biologically realistic spatial predictions relative to known distributions. CONCLUSIONS: Habitat model performance may be positively biased in cases where pseudo-absences are sampled from environments that are dissimilar to presences. This emphasizes the need to carefully consider spatial extent of the sampling domain and environmental heterogeneity of pseudo-absence samples when developing habitat models, and highlights the importance of scrutinizing spatial predictions to ensure that habitat models are biologically realistic and fit for modeling objectives.

Performance evaluation of cetacean species distribution models developed using generalized additive models and boosted regression trees.

Species distribution models (SDMs) are important management tools for highly mobile marine species because they provide spatially and temporally explicit information on animal distribution. Two prevalent modeling frameworks used to develop SDMs for marine species are generalized additive models (GAMs) and boosted regression trees (BRTs), but comparative studies have rarely been conducted; most rely on presence-only data; and few have explored how features such as species distribution characteristics affect model performance. Since the majority of marine species BRTs have been used to predict habitat suitability, we first compared BRTs to GAMs that used presence/absence as the response variable. We then compared results from these habitat suitability models to GAMs that predict species density (animals per km2) because density models built with a subset of the data used here have previously received extensive validation. We compared both the explanatory power (i.e., model goodness of fit) and predictive power (i.e., performance on a novel dataset) of the GAMs and BRTs for a taxonomically diverse suite of cetacean species using a robust set of systematic survey data (1991-2014) within the California Current Ecosystem. Both BRTs and GAMs were successful at describing overall distribution patterns throughout the study area for the majority of species considered, but when predicting on novel data, the density GAMs exhibited substantially greater predictive power than both the presence/absence GAMs and BRTs, likely due to both the different response variables and fitting algorithms. Our results provide an improved understanding of some of the strengths and limitations of models developed using these two methods. These results can be used by modelers developing SDMs and resource managers tasked with the spatial management of marine species to determine the best modeling technique for their question of interest.

Decision-support tools for dynamic management.

Spatial management is a valuable strategy to advance regional goals for nature conservation, economic development, and human health. One challenge of spatial management is navigating the prioritization of multiple features. This challenge becomes more pronounced in dynamic management scenarios, in which boundaries are flexible in space and time in response to changing biological, environmental, or socioeconomic conditions. To implement dynamic management, decision-support tools are needed to guide spatial prioritization as feature distributions shift under changing conditions. Marxan is a widely applied decision-support tool designed for static management scenarios, but its utility in dynamic management has not been evaluated. EcoCast is a new decision-support tool developed explicitly for the dynamic management of multiple features, but it lacks some of Marxan's functionality. We used a hindcast analysis to compare the capacity of these 2 tools to prioritize 4 marine species in a dynamic management scenario for fisheries sustainability. We successfully configured Marxan to operate dynamically on a daily time scale to resemble EcoCast. The relationship between EcoCast solutions and the underlying species distributions was more linear and less noisy, whereas Marxan solutions had more contrast between waters that were good and poor to fish. Neither decision-support tool clearly outperformed the other; the appropriateness of each depends on management purpose, resource-manager preference, and technological capacity of tool developers. Article impact statement: Marxan can function as a decision-support tool for dynamic management scenarios in which boundaries are flexible in space and time.

Herramientas de Apoyo para la Toma de Decisiones en el Manejo Dinámico Resumen El manejo espacial es una estrategia valiosa para llevar hacia adelante los objetivos regionales para la conservación de la naturaleza, el desarrollo económico y la salud humana. Uno de los retos del manejo espacial es la navegación a través de la priorización de múltiples caracteres. Este reto se vuelve más pronunciado dentro de los escenarios de manejo dinámico, en los cuales los límites son flexibles en el tiempo y en el espacio como respuesta a las cambiantes condiciones biológicas, ambientales o socioeconómicas. Para implementar el manejo dinámico, se necesitan herramientas de apoyo para la toma de decisiones para guiar a la priorización espacial conforme la distribución de los caracteres se modifica bajo condiciones cambiantes. Marxan es una herramienta de apoyo para la toma de decisiones utilizada ampliamente y diseñada para escenarios de manejo estático, pero su utilidad para el manejo dinámico no ha sido evaluada. EcoCast es una nueva herramienta de apoyo para la toma de decisiones desarrollada explícitamente para el manejo dinámico de múltiples caracteres, pero carece de algunas funcionalidades que tiene Marxan. Usamos un análisis de información retrospectiva para comparar la capacidad de estas dos herramientas para priorizar a cuatro especies marinas en un escenario de manejo dinámico con respecto a la sustentabilidad de las pesquerías. Configuramos exitosamente la herramienta Marxan para que operara dinámicamente con respecto a una escala diaria de tiempo y así se asemejara a EcoCast. La relación entre las soluciones de EcoCast y las distribuciones subyacentes de las especies fue más lineal y menos ruidosa, mientras que las soluciones de Marxan tuvieron un mayor contraste entre las aguas que eran buenas y aquellas que eran pobres para los peces. Ninguna de las dos herramientas de apoyo para la toma de decisiones tuvo un mejor desempeño que la otra; la pertinencia de cada una depende del propósito del manejo, la preferencia del administrador de los recursos y la capacidad tecnológica de quienes desarrollan la herramienta.

The influence of ontogenetic diet variation on consumption rate estimates: a marine example.

Consumption rates are the foundation of trophic ecology, yet bioenergetics models used to estimate these rates can lack realism by not incorporating the ontogeny of diet. We constructed a bioenergetics model of a marine predatory fish (tailor, Pomatomus saltatrix) that incorporated high-resolution ontogenetic diet variation, and compared consumption estimates to those derived from typical bioenergetics models that do not consider ontogenetic diet variation. We found tailor consumption was over- or under-estimated by ~5-25% when only including the most common prey item. This error was due to a positive relationship between mean prey energy density and predator body size. Since high-resolution diet data isn't always available, we also simulated how increasing dietary information progressively influenced consumption rate estimates. The greatest improvement in consumption rate estimates occurred when diet variation of 2-3 stanzas (1-2 juvenile stanzas, and adults) was included, with at least 5-6 most common prey types per stanza. We recommend increased emphasis on incorporating the ontogeny of diet and prey energy density in consumption rate estimates, especially for species with spatially segregated life stages or variable diets. A small-moderate increase in the resolution of dietary information can greatly benefit the accuracy of estimated consumption rates. We present a method of incorporating variable prey energy density into bioenergetics models.

Continental-scale animal tracking reveals functional movement classes across marine taxa.

Acoustic telemetry is a principle tool for observing aquatic animals, but coverage over large spatial scales remains a challenge. To resolve this, Australia has implemented the Integrated Marine Observing System's Animal Tracking Facility which comprises a continental-scale hydrophone array and coordinated data repository. This national acoustic network connects localized projects, enabling simultaneous monitoring of multiple species over scales ranging from 100 s of meters to 1000 s of kilometers. There is a need to evaluate the utility of this national network in monitoring animal movement ecology, and to identify the spatial scales that the network effectively operates over. Cluster analyses assessed movements and residency of 2181 individuals from 92 species, and identified four functional movement classes apparent only through aggregating data across the entire national network. These functional movement classes described movement metrics of individuals rather than species, and highlighted the plasticity of movement patterns across and within populations and species. Network analyses assessed the utility and redundancy of each component of the national network, revealing multiple spatial scales of connectivity influenced by the geographic positioning of acoustic receivers. We demonstrate the significance of this nationally coordinated network of receivers to better reveal intra-specific differences in movement profiles and discuss implications for effective management.

Applying acoustic telemetry to understand contaminant exposure and bioaccumulation patterns in mobile fishes.

Contamination in urbanised estuaries presents a risk to human health, and to the viability of populations of exploited species. Assessing animal movements in relation to contaminated areas may help to explain patterns in bioaccumulation, and assist in the effective management of health risks associated with consumption of exploited species. Using polychlorinated dibenzodioxin and polychlorinated dibenzofuran (PCDD/Fs) contamination in Sydney Harbour estuary as a case study, we present a study that links movement patterns resolved using acoustic telemetry to the accumulation of contaminants in mobile fish on a multi-species basis. Fifty-four individuals across six exploited species (Sea Mullet Mugil cephalus; Luderick Girella tricuspidata; Yellowfin Bream Acanthopagrus australis; Silver Trevally Pseudocaranx georgianus; Mulloway Argyrosomus japonicus; Yellowtail Kingfish Seriola lalandi) were tagged with acoustic transmitters, and their movements tracked for up to 3years. There was substantial inter-specific variation in fish distribution along the estuary. The proportion of distribution that overlapped with contaminated areas explained 84-98% of the inter-specific variation in lipid-standardised biota PCDD/F concentration. There was some seasonal variation in distribution along the estuary, but movement patterns indicated that Sea Mullet, Yellowfin Bream, Silver Trevally, and Mulloway were likely to be exposed to contaminated areas during the period of gonadal maturation. Acoustic telemetry allows examination of spatial and temporal patterns in exposure to contamination. When used alongside biota sampling and testing, this offers a powerful approach to assess exposure, bioaccumulation, and potential risks faced by different species, as well as human health risks associated with their consumption.

Australia's continental-scale acoustic tracking database and its automated quality control process.

Our ability to predict species responses to environmental changes relies on accurate records of animal movement patterns. Continental-scale acoustic telemetry networks are increasingly being established worldwide, producing large volumes of information-rich geospatial data. During the last decade, the Integrated Marine Observing System's Animal Tracking Facility (IMOS ATF) established a permanent array of acoustic receivers around Australia. Simultaneously, IMOS developed a centralised national database to foster collaborative research across the user community and quantify individual behaviour across a broad range of taxa. Here we present the database and quality control procedures developed to collate 49.6 million valid detections from 1891 receiving stations. This dataset consists of detections for 3,777 tags deployed on 117 marine species, with distances travelled ranging from a few to thousands of kilometres. Connectivity between regions was only made possible by the joint contribution of IMOS infrastructure and researcher-funded receivers. This dataset constitutes a valuable resource facilitating meta-analysis of animal movement, distributions, and habitat use, and is important for relating species distribution shifts with environmental covariates.