Temporal resolutions in species distribution models of highly mobile marine animals: Recommendations for ecologists and managers

Exploring the impact of temporal resolution on detecting shifts in the invasive species niche: Insights from Lessepsian fishes

In this study, we estimate the niche overlap between native and invaded ranges of 36 Lessepsian fish, focusing on how this estimate might vary in relation to the temporal resolution of sea surface temperature and salinity, which are the main niche axes determining their distribution. Specifically, we wanted to address the following questions: (i) Does the choice of temporal averaging method of variables influence the estimation of niche overlap for individual variables? (ii) Does this temporal resolution effect persist when conducting bivariate niche estimations? Niches overlap was estimated by calculating two indices and these analyses were repeated at two temporal resolutions, matching observations to the classic 'multidecadal' average of environmental conditions and to the corresponding annual average of records. Results are compared with verify whether differences can be detected in the magnitude of niche commonality measured at annual or multidecadal temporal resolution. The findings show that the temporal resolution of the data significantly influences estimates of overlap in the thermal niche. Specifically, our analysis indicates a considerable disparity between native and invasive niche regions for most species, particularly when evaluated over multidecadal periods compared with matching occurrence data to the annual mean values of years the occurrence was observed, that is matching occurrence data to a common average of 'present' conditions or to the annual mean values of years of observation. In particular, the largest overlaps between native and invaded niches occur along the salinity axis, regardless of temporal resolution. When considering both temperature and salinity together, the results remain unaffected by the temporal resolution of the environmental data. Almost 30% of the species show a different niche in their introduced range, and for the other species, the overlap between native and invaded ranges was reduced with respect to the univariate analyses.

The importance of temporal scale in distribution modeling of migratory Caspian Kutum, Rutilus frisii

The choice of temporal resolution has high importance in ecological modeling, which can greatly affect the identification of the main drivers of an organism's distribution, considering the spatiotemporal dynamism of environmental predictors as well as organisms' abundance. The present study aimed to identify the spatiotemporal distribution patterns of Caspian Kutum, Rutilus frisii, along the southern coast of the Caspian Sea, north of Iran, evaluating multiple temporal resolutions of data. The boosted regression trees (BRT) method was used to model fish catch distribution using a set of environmental predictors. Three temporal scales of data, including seasonal, sub-seasonal, and monthly time frames over the catch season (October-April), were considered in our modeling analyses. The monthly models, utilizing more detailed data scales, exhibited the highest potential in identifying the overall distribution patterns of the fish, compared to temporally-coarse BRT models. The best models were the BRTs fitted using data from March and April, which represented the final months of the catch season with the highest catch levels. In the monthly models, the main determinants of the Kutum's aggregation points were found to be dynamic variables including sea surface temperature, particulate organic and inorganic carbon, as opposed to static topographic parameters such as distance to river inlets. Seasonal and sub-seasonal models identified particulate inorganic matter and distance to river inlets as the predictors with the highest influence on fish distribution. The geographical distributions of fish biomass hotspots revealed the presence of a stable number of fish aggregation hotspot points along the eastern coast, while some cold-spot points were identified along the central and western coasts of the Caspian Sea. Our findings indicate that utilizing fine time scales in modeling analyses can result in a more reliable explanation and prediction of fish distribution dynamics. The investigated approach allows for the identification of intra-seasonal fluctuations in environmental conditions, particularly dynamic parameters, and their relationship with fish aggregation.

Tracking seabird migration in the tropical Indian Ocean reveals basin-scale conservation need

Understanding marine predator distributions is an essential component of arresting their catastrophic declines.1,2,3,4 In temperate, polar, and upwelling seas, predictable oceanographic features can aggregate migratory predators, which benefit from site-based protection.5,6,7,8 In more oligotrophic tropical waters, however, it is unclear whether environmental conditions create similar multi-species hotspots. We track the non-breeding movements and habitat preferences of a tropical seabird assemblage (n = 348 individuals, 9 species, and 10 colonies in the western Indian Ocean), which supports globally important biodiversity.9,10,11,12 We mapped species richness from tracked populations and then predicted the same diversity measure for all known Indian Ocean colonies. Most species had large non-breeding ranges, low or variable residency patterns, and specific habitat preferences. This in turn revealed that maximum species richness covered >3.9 million km2, with no focused aggregations, in stark contrast to large-scale tracking studies in all other ocean basins.5,6,7,13,14 High species richness was captured by existing marine protected areas (MPAs) in the region; however, most occurred in the unprotected high seas beyond national jurisdictions. Seabirds experience cumulative anthropogenic impacts13 and high mortality15,16 during non-breeding. Therefore, our results suggest that seabird conservation in the tropical Indian Ocean requires an ocean-wide perspective, including high seas legislation.17 As restoration actions improve the outlook for tropical seabirds on land18,19,20,21,22 and environmental change reshapes the habitats that support them at sea,15,16 appropriate marine conservation will be crucial for their long-term recovery and whole ecosystem restoration.

Surface and subsurface oceanographic features drive forage fish distributions and aggregations: Implications for prey availability to top predators in the US Northeast Shelf ecosystem

Forage fishes are a critical food web link in marine ecosystems, aggregating in a hierarchical patch structure over multiple spatial and temporal scales. Surface-level forage fish aggregations (FFAs) represent a concentrated source of prey available to surface- and shallow-foraging marine predators. Existing survey and analysis methods are often imperfect for studying forage fishes at scales appropriate to foraging predators, making it difficult to quantify predator-prey interactions. In many cases, general distributions of forage fish species are known; however, these may not represent surface-level prey availability to predators. Likewise, we lack an understanding of the oceanographic drivers of spatial patterns of prey aggregation and availability or forage fish community patterns. Specifically, we applied Bayesian joint species distribution models to bottom trawl survey data to assess species- and community-level forage fish distribution patterns across the US Northeast Continental Shelf (NES) ecosystem. Aerial digital surveys gathered data on surface FFAs at two project sites within the NES, which we used in a spatially explicit hierarchical Bayesian model to estimate the abundance and size of surface FFAs. We used these models to examine the oceanographic drivers of forage fish distributions and aggregations. Our results suggest that, in the NES, regions of high community species richness are spatially consistent with regions of high surface FFA abundance. Bathymetric depth drove both patterns, while subsurface features, such as mixed layer depth, primarily influenced aggregation behavior and surface features, such as sea surface temperature, sub-mesoscale eddies, and fronts influenced forage fish diversity. In combination, these models help quantify the availability of forage fishes to marine predators and represent a novel application of spatial models to aerial digital survey data.

Phytoplankton life strategies, phenological shifts and climate change in the North Atlantic Ocean from 1850 to 2100

Significant phenological shifts induced by climate change are projected within the phytoplankton community. However, projections from current Earth System Models (ESMs) understandably rely on simplified community responses that do not consider evolutionary strategies manifested as various phenotypes and trait groups. Here, we use a species-based modelling approach, combined with large-scale plankton observations, to investigate past, contemporary and future phenological shifts in diatoms (grouped by their morphological traits) and dinoflagellates in three key areas of the North Atlantic Ocean (North Sea, North-East Atlantic and Labrador Sea) from 1850 to 2100. Our study reveals that the three phytoplanktonic groups exhibit coherent and different shifts in phenology and abundance throughout the North Atlantic Ocean. The seasonal duration of large flattened (i.e. oblate) diatoms is predicted to shrink and their abundance to decline, whereas the phenology of slow-sinking elongated (i.e. prolate) diatoms and of dinoflagellates is expected to expand and their abundance to rise, which may alter carbon export in this important sink region. The increase in prolates and dinoflagellates, two groups currently not considered in ESMs, may alleviate the negative influence of global climate change on oblates, which are responsible of massive peaks of biomass and carbon export in spring. We suggest that including prolates and dinoflagellates in models may improve our understanding of the influence of global climate change on the biological carbon cycle in the oceans.

Aerial abundance estimates for two sympatric dolphin species at a regional scale using distance sampling and density surface modeling

Monitoring wildlife populations over scales relevant to management is critical to supporting conservation decision-making in the face of data deficiency, particularly for rare species occurring across large geographic ranges. The Pilbara region of Western Australia is home to two sympatric and morphologically similar species of coastal dolphins—the Indo-pacific bottlenose dolphin (Tursiops aduncus) and Australian humpback dolphin (Sousa sahulensis)—both of which are believed to be declining in numbers and facing increasing pressures from the combined impacts of environmental change and extensive industrial activities. The aim of this study was to develop spatially explicit models of bottlenose and humpback dolphin abundance in Pilbara waters that could inform decisions about coastal development at a regional scale. Aerial line transect surveys were flown from a fixed-wing aircraft in the austral winters of 2015, 2016, and 2017 across a total area of 33,420 km2. Spatio-temporal patterns in dolphin density were quantified using a density surface modeling (DSM) approach, accounting for imperfect detection as well as both perception and availability bias. We estimated the abundance of bottlenose dolphins at 3,713 (95% CI = 2,679–5,146; average density of 0.189 ± 0.046 SD individuals per km2) in 2015, 2,638 (95% CI = 1,670–4,168; 0.159 ± 0.135 individuals per km2) in 2016 and 1,635 (95% CI = 1,031–2,593; 0.101 ± 0.103 individuals per km2) in 2017. Too few humpback dolphins were detected in 2015 to model abundance, but their estimated abundance was 1,546 (95% CI = 942–2,537; 0.097 ± 0.03 individuals per km2) and 2,690 (95% CI = 1,792–4,038; 0.169 ± 0.064 individuals per km2) in 2016 and 2017, respectively. Dolphin densities were greatest in nearshore waters, with hotspots in Exmouth Gulf, the Dampier Archipelago, and Great Sandy Islands. Our results provide a benchmark on which future risk assessments can be based to better understand the overlap between pressures and important dolphin habitats in tropical northwestern Australia.

Delayed response to environmental conditions and infra-seasonal dynamics of the short-beaked common dolphin distribution

Cetaceans adjust their distribution and abundance to encountered conditions across years and seasons, but we poorly understand such small-scale changes for many species, especially in winter. Crucial challenges confront some populations during this season, such as the high levels of fisheries-induced mortality faced by the common dolphin (Delphinus delphis) in the Northeast Atlantic shelves. For such species, understanding the winter fine-scale dynamics is crucial. We aimed to identify the dolphin distribution drivers during the winters of 2020 and 2021, with a focus on determining the lag between changes in oceanographic conditions and dolphin distribution. The changes were related to temporal delays specific to the nature and cascading effects that oceanographic processes had on the trophic chain. By determining the most important conditions and lags to dolphin distributions, we shed light on the poorly understood intrusions of dolphins within coastal waters during winter: they displayed a strong preference for the coastal-shelf waters front and extensively followed its spatial variations, with their overall densities increasing over the period and peaking in March-April. The results presented here provide invaluable information on the winter distribution dynamics and should inform management decisions to help reduce the unsustainable mortalities of this species in the by-catch of fisheries.

The distribution, ecology and predicted habitat use of the Critically Endangered angelshark (Squatina squatina) in coastal waters of Wales and the central Irish Sea

The angelshark (Squatina squatina) has the northernmost range of any angel shark species, but there is limited information on its distribution, habitat use and ecology at higher latitudes. To address this, Angel Shark Project: Wales gathered 2231 S. squatina records and 142 anecdotal resources from fishers, coastal communities and archives. These spanned the coastal waters of Wales and the central Irish Sea and were dated from 1812 to 2020, with 97.62% of records within 11.1 km (6 nm) of the coast. Commercial, recreational and charter boat fishers provided the majority of S. squatina records (97.18%), with significantly more sightings from three decades (1970s, 1980s and 1990s) and in the months of September, June, August and July (in descending order). The coastal area between Bardsey Island and Strumble Head had the most S. squatina records (n = 1279), with notable concentrations also found in Carmarthen Bay, Conwy Bay and the Outer Severn Estuary. Species distribution models (SDM) identified four environmental variables that had significant influence on S. squatina distribution, depth, chlorophyll-a concentration, sea surface temperature (SST) and salinity, and these varied between the quarters (Q) of the year. SDM model outputs predicted a larger congruous area of suitable habitat in Q3 (3176 km² ) compared to Q2 (2051 km² ), with suitability along the three glacial moraines (Sarn Badrig, Sarn-y-Bwch and Sarn Cynfelyn) strongly presented. Comparison of modelled environmental variables at the location of S. squatina records for each Q identified reductions in depth and salinity, and increases in chlorophyll-a and SST when comparing Q2 or Q3 with Q1 or Q4. This shift may suggest S. squatina are making seasonal movements to shallow coastal waters in Q2 and Q3. This is supported by 23 anecdotal resources and may be driven by reproductive behaviour, as there were 85 records of S. squatina individuals ≤60 cm in the dataset, inferred as recently born or juvenile life-history stages. The results have helped fill significant evidence gaps identified in the Wales Angelshark Action Plan and immediate next research steps are suggested.

Blue whales increase feeding rates at fine-scale ocean features

Marine predators face the challenge of reliably finding prey that is patchily distributed in space and time. Predators make movement decisions at multiple spatial and temporal scales, yet we have a limited understanding of how habitat selection at multiple scales translates into foraging performance. In the ocean, there is mounting evidence that submesoscale (i.e. less than 100 km) processes drive the formation of dense prey patches that should hypothetically provide feeding hot spots and increase predator foraging success. Here, we integrated environmental remote-sensing with high-resolution animal-borne biologging data to evaluate submesoscale surface current features in relation to the habitat selection and foraging performance of blue whales in the California Current System. Our study revealed a consistent functional relationship in which blue whales disproportionately foraged within dynamic aggregative submesoscale features at both the regional and feeding site scales across seasons, regions and years. Moreover, we found that blue whale feeding rates increased in areas with stronger aggregative features, suggesting that these features indicate areas of higher prey density. The use of fine-scale, dynamic features by foraging blue whales underscores the need to take these features into account when designating critical habitat and may help inform strategies to mitigate the impacts of human activities for the species.

Estimating uncertainty in density surface models

Providing uncertainty estimates for predictions derived from species distribution models is essential for management but there is little guidance on potential sources of uncertainty in predictions and how best to combine these. Here we show where uncertainty can arise in density surface models (a multi-stage spatial modelling approach for distance sampling data), focussing on cetacean density modelling. We propose an extensible, modular, hybrid analytical-simulation approach to encapsulate these sources. We provide example analyses of fin whales Balaenoptera physalus in the California Current Ecosystem.

Both real-time and long-term environmental data perform well in predicting shorebird distributions in managed habitat

Highly mobile species, such as migratory birds, respond to seasonal and interannual variability in resource availability by moving to better habitats. Despite the recognized importance of resource thresholds, species-distribution models typically rely on long-term average habitat conditions, mostly because large-extent, temporally resolved, environmental data are difficult to obtain. Recent advances in remote sensing make it possible to incorporate more frequent measurements of changing landscapes; however, there is often a cost in terms of model building and processing and the added value of such efforts is unknown. Our study tests whether incorporating real-time environmental data increases the predictive ability of distribution models, relative to using long-term average data. We developed and compared distribution models for shorebirds in California's Central Valley based on high temporal resolution (every 16 days), and 17-year long-term average surface water data. Using abundance-weighted boosted regression trees, we modeled monthly shorebird occurrence as a function of surface water availability, crop type, wetland type, road density, temperature, and bird data source. Although modeling with both real-time and long-term average data provided good fit to withheld validation data (the area under the receiver operating characteristic curve, or AUC, averaged between 0.79 and 0.89 for all taxa), there were small differences in model performance. The best models incorporated long-term average conditions and spatial pattern information for real-time flooding (e.g., perimeter-area ratio of real-time water bodies). There was not a substantial difference in the performance of real-time and long-term average data models within time periods when real-time surface water differed substantially from the long-term average (specifically during drought years 2013-2016) and in intermittently flooded months or locations. Spatial predictions resulting from the models differed most in the southern region of the study area where there is lower water availability, fewer birds, and lower sampling density. Prediction uncertainty in the southern region of the study area highlights the need for increased sampling in this area. Because both sets of data performed similarly, the choice of which data to use may depend on the management context. Real-time data may ultimately be best for guiding dynamic, adaptive conservation actions, whereas models based on long-term averages may be more helpful for guiding permanent wetland protection and restoration.

Ecoregional and temporal dynamics of dugong habitat use in a complex coral reef lagoon ecosystem

Mobile marine species display complex and nonstationary habitat use patterns that require understanding to design effective management measures. In this study, the spatio-temporal habitat use dynamics of the vulnerable dugong (Dugong dugon) were modelled from 16 satellite-tagged individuals in the coral reef lagoonal ecosystems of New Caledonia, South Pacific. Dugong residence time was calculated along the interpolated tracks (9371 hourly positions) to estimate intensity of use in three contrasting ecoregions, previously identified through hierarchical clustering of lagoon topographic characteristics. Across ecoregions, differences were identified in dugong spatial intensity of use of shallow waters, deeper lagoon waters and the fore-reef shelf outside the barrier reef. Maps of dugong intensity of use were predicted from these ecological relationships and validated with spatial density estimates derived from aerial surveys conducted for population assessment. While high correlation was found between the two datasets, our study extended the spatial patterns of dugong distribution obtained from aerial surveys across the diel cycle, especially in shallow waters preferentially used by dugongs at night/dusk during high tide. This study has important implications for dugong conservation and illustrates the potential benefits of satellite tracking and dynamic habitat use modelling to inform spatial management of elusive and mobile marine mammals.

Horizontal-vertical movement relationships: Adélie penguins forage continuously throughout provisioning trips

BACKGROUND

Diving marine predators forage in a three-dimensional environment, adjusting their horizontal and vertical movement behaviour in response to environmental conditions and the spatial distribution of prey. Expectations regarding horizontal-vertical movements are derived from optimal foraging theories, however, inconsistent empirical findings across a range of taxa suggests these behavioural assumptions are not universally applicable.

METHODS

Here, we examined how changes in horizontal movement trajectories corresponded with diving behaviour and marine environmental conditions for a ubiquitous Southern Ocean predator, the Adélie penguin. Integrating extensive telemetry-based movement and environmental datasets for chick-rearing Adélie penguins at Béchervaise Island, we tested the relationships between horizontal move persistence (continuous scale indicating low ['resident'] to high ['directed'] movement autocorrelation), vertical dive effort and environmental variables.

RESULTS

Penguins dived continuously over the course of their foraging trips and lower horizontal move persistence corresponded with less intense foraging activity, likely indicative of resting behaviour. This challenges the traditional interpretation of horizontal-vertical movement relationships based on optimal foraging models, which assumes increased residency within an area translates to increased foraging activity. Movement was also influenced by different environmental conditions during the two stages of chick-rearing: guard and crèche. These differences highlight the strong seasonality of foraging habitat for chick-rearing Adélie penguins at Béchervaise Island.

CONCLUSIONS

Our findings advance our understanding of the foraging behaviour for this marine predator and demonstrates the importance of integrating spatial location and behavioural data before inferring habitat use.

A systematic review of spatial habitat associations and modeling of marine fish distribution: A guide to predictors, methods, and knowledge gaps

As species distribution models, and similar techniques, have emerged in marine ecology, a vast array of predictor variables have been created and diverse methodologies have been applied. Marine fish are vital food resources worldwide, yet identifying the most suitable methodology and predictors to characterize spatial habitat associations, and the subsequent distributions, often remains ambiguous. Our objectives were to identify knowledge gaps in fish guilds, identify research themes, and to determine how data sources, statistics, and predictor variables differ among fish guilds. Data were obtained from an international literature search of peer-reviewed articles (2007-2018; n = 225) and research themes were determined based on abstracts. We tested for differences in data sources and modeling techniques using multinomial regressions and used a linear discriminant analysis to distinguish differences in predictors among fish guilds. Our results show predictive studies increased over time, but studies of forage fish, sharks, coral reef fish, and other fish guilds remain sparse. Research themes emphasized habitat suitability and distribution shifts, but also addressed abundance, occurrence, stock assessment, and biomass. Methodologies differed by fish guilds based on data limitations and research theme. The most frequent predictors overall were depth and temperature, but most fish guilds were distinguished by their own set of predictors that focused on their specific life history and ecology. A one-size-fits-all approach is not suitable for predicting marine fish distributions. However, given the paucity of studies for some fish guilds, researchers would benefit from utilizing predictors and methods derived from more commonly studied fish when similar habitat requirements are expected. Overall, the findings provide a guide for determining predictor variables to test and identifies novel opportunities to apply non-spatial knowledge and mechanisms to models.

Identifying high-density areas of oysters using species distribution modeling: Lessons for conservation of the native Ostrea edulis and management of the invasive Magallana (Crassostrea) gigas in Sweden

AIM

Understanding spatial patterns of the distribution of adult native oyster, Ostrea edulis, and the invasive Magallana (Crassostrea) gigas is important for management of these populations. The aim of this study was to use ensemble SDM's to (a) identify and predict conservation hotspots, (b) assess the current level of protection for O. edulis, and (c) quantify the amount of overlap between the two species where interactions with M. gigas are most likely.

LOCATION

Skagerrak, Sweden.

METHODS

We used data collected by video at depths from 0.5 to 10 m in 436 sites. Models of occurrence and densities >1 m-2 were fitted and assessed using ensemble methods ("biomod2" package). Models of high-density hotspots were used to predict, map, and quantify areal extent of the species in order to assess the degree of overlap with protected areas and the potential for interactions between the two species.

RESULTS

Both species were widely distributed in the region. Observations of high-density habitats, mainly occurring at depths of ≈3 and 0.5 m for O. edulis and M. gigas, respectively, were found in 4% and 2% of the sites. Models provided useful predictions for both species (AUC = 0.85-0.99; sensitivity = 0.74-1.0; specificity = 0.72-0.97). High-density areas occupy roughly 15 km2 each with substantial overlap between species. 50% of these are protected only by fisheries regulations, 44% are found in Natura 2000 reserves and 6% of the predicted O. edulis enjoys protection in a national park.

MAIN CONCLUSIONS

Data collection by video in combination with SDM's provides a realistic approach for large-scale quantification of spatial patterns of marine population and habitats. O. edulis and M. gigas are common in the area, but a large proportion of the most valuable O. edulis habitats are not found in protected areas. The overlap between species suggests that efforts to manage the invasive M. gigas need to be integrated with management actions to conserve the native O. edulis.

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.

Climate oscillation and the invasion of alien species influence the oceanic distribution of seabirds

Spatial and temporal distribution of seabird transiting and foraging at sea is an important consideration for marine conservation planning. Using at-sea observations of seabirds (n = 317), collected during the breeding season from 2012 to 2016, we built boosted regression tree (BRT) models to identify relationships between numerically dominant seabird species (red-footed booby, brown noddy, white tern, and wedge-tailed shearwater), geomorphology, oceanographic variability, and climate oscillation in the Chagos Archipelago. We documented positive relationships between red-footed booby and wedge-tailed shearwater abundance with the strength in the Indian Ocean Dipole, as represented by the Dipole Mode Index (6.7% and 23.7% contribution, respectively). The abundance of red-footed boobies, brown noddies, and white terns declined abruptly with greater distance to island (17.6%, 34.1%, and 41.1% contribution, respectively). We further quantified the effects of proximity to rat-free and rat-invaded islands on seabird distribution at sea and identified breaking point distribution thresholds. We detected areas of increased abundance at sea and habitat use-age under a scenario where rats are eradicated from invaded nearby islands and recolonized by seabirds. Following rat eradication, abundance at sea of red-footed booby, brown noddy, and white terns increased by 14%, 17%, and 3%, respectively, with no important increase detected for shearwaters. Our results have implication for seabird conservation and island restoration. Climate oscillations may cause shifts in seabird distribution, possibly through changes in regional productivity and prey distribution. Invasive species eradications and subsequent island recolonization can lead to greater access for seabirds to areas at sea, due to increased foraging or transiting through, potentially leading to distribution gains and increased competition. Our approach predicting distribution after successful eradications enables anticipatory threat mitigation in these areas, minimizing competition between colonies and thereby maximizing the risk of success and the conservation impact of eradication programs.

Spatio-temporal ecological niche modelling of multigenerational insect migrations

Modelling ecological niches of migratory animals requires incorporating a temporal dimension, in addition to space. Here, we introduce an approach to model multigenerational migratory insects using time-partitioned environmental variables (by months and years) and time- and behaviour-partitioned records (breeding records to model reproductive habitat). We apply this methodology to modelling the Palearctic-African migratory cycle of the Painted Lady butterfly (Vanessa cardui), based on data encompassing 36 years (646 breeding sites from 30 countries). Each breeding record is linked to a particular time (month and year), and the associated values of the bioclimatic variables are used for an ensemble modelling strategy, to finally obtain monthly projections. The results show obligated movements, mostly latitudinal, for the species' successive generations across the overall range, and only scattered locations show high probabilities of reproduction year-round. The southernmost reproductive areas estimated for the Palearctic-African migratory pool reach equatorial latitudes from December to February. We thus propose a potential distribution for the winter 'missing generations' that would expand the V. cardui migration cycle to encompass about 15 000 km in latitude, from northernmost Europe to equatorial Africa. In summer, Europe represents the major temporary resource for V. cardui, while January and February show the lowest overall suitability values, and they are potentially the most vulnerable period for the species to suffer yearly bottlenecks. In summary, we demonstrate the potential of the proposed niche modelling strategy to investigate migratory movements of insects.

Whales in warming water: Assessing breeding habitat diversity and adaptability in Oceania's changing climate

In the context of a changing climate, understanding the environmental drivers of marine megafauna distribution is important for conservation success. The extent of humpback whale breeding habitats and the impact of temperature variation on their availability are both unknown. We used 19 years of dedicated survey data from seven countries and territories of Oceania (1,376 survey days), to investigate humpback whale breeding habitat diversity and adaptability to climate change. At a fine scale (1 km resolution), seabed topography was identified as an important influence on humpback whale distribution. The shallowest waters close to shore or in lagoons were favored, although humpback whales also showed flexible habitat use patterns with respect to shallow offshore features such as seamounts. At a coarse scale (1° resolution), humpback whale breeding habitats in Oceania spanned a thermal range of 22.3-27.8°C in August, with interannual variation up to 2.0°C. Within this range, both fine and coarse scale analyses of humpback whale distribution suggested local responses to temperature. Notably, the most detailed dataset was available from New Caledonia (774 survey days, 1996-2017), where encounter rates showed a negative relationship to sea surface temperature, but were not related to the El Niño Southern Oscillation or the Antarctic Oscillation from previous summer, a proxy for feeding conditions that may impact breeding patterns. Many breeding sites that are currently occupied are predicted to become unsuitably warm for this species (>28°C) by the end of the 21st century. Based on modeled ecological relationships, there are suitable habitats for relocation in archipelagos and seamounts of southern Oceania. Although distribution shifts might be restrained by philopatry, the apparent plasticity of humpback whale habitat use patterns and the extent of suitable habitats support an adaptive capacity to ocean warming in Oceania breeding grounds.

Modeling spatiotemporal abundance of mobile wildlife in highly variable environments using boosted GAMLSS hurdle models

Modeling organism distributions from survey data involves numerous statistical challenges, including accounting for zero-inflation, overdispersion, and selection and incorporation of environmental covariates. In environments with high spatial and temporal variability, addressing these challenges often requires numerous assumptions regarding organism distributions and their relationships to biophysical features. These assumptions may limit the resolution or accuracy of predictions resulting from survey-based distribution models. We propose an iterative modeling approach that incorporates a negative binomial hurdle, followed by modeling of the relationship of organism distribution and abundance to environmental covariates using generalized additive models (GAM) and generalized additive models for location, scale, and shape (GAMLSS). Our approach accounts for key features of survey data by separating binary (presence-absence) from count (abundance) data, separately modeling the mean and dispersion of count data, and incorporating selection of appropriate covariates and response functions from a suite of potential covariates while avoiding overfitting. We apply our modeling approach to surveys of sea duck abundance and distribution in Nantucket Sound (Massachusetts, USA), which has been proposed as a location for offshore wind energy development. Our model results highlight the importance of spatiotemporal variation in this system, as well as identifying key habitat features including distance to shore, sediment grain size, and seafloor topographic variation. Our work provides a powerful, flexible, and highly repeatable modeling framework with minimal assumptions that can be broadly applied to the modeling of survey data with high spatiotemporal variability. Applying GAMLSS models to the count portion of survey data allows us to incorporate potential overdispersion, which can dramatically affect model results in highly dynamic systems. Our approach is particularly relevant to systems in which little a priori knowledge is available regarding relationships between organism distributions and biophysical features, since it incorporates simultaneous selection of covariates and their functional relationships with organism responses.

Rapid shifts in distribution and high-latitude persistence of oceanographic habitat revealed using citizen science data from a climate change hotspot

The environmental effects of climate change are predicted to cause distribution shifts in many marine taxa, yet data are often difficult to collect. Quantifying and monitoring species' suitable environmental habitats is a pragmatic approach for assessing changes in species distributions but is underdeveloped for quantifying climate change induced range shifts in marine systems. Specifically, habitat predictions present opportunities for quantifying spatiotemporal distribution changes while accounting for sources of natural climate variation. Here we demonstrate the utility of a marine-based habitat model parameterized using citizen science data and remotely sensed environmental covariates for quantifying shifts in oceanographic habitat suitability over 22 years for a coastal-pelagic fish species in a climate change hotspot. Our analyses account for the effects of natural intra- and interannual climate variability to reveal rapid poleward shifts in core (94.4 km/decade) and poleward edge (108.8 km/decade) oceanographic habitats. Temporal persistence of suitable oceanographic habitat at high latitudes also increased by approximately 3 months over the study period. Our approach demonstrates how marine citizen science data can be used to quantify range shifts, but necessitates shifting focus from species distributions directly, to the distribution of species' environmental habitat preferences.

Multi-scale habitat preference analyses for Azorean blue whales

Blue whales are sighted every year around the Azores islands, which apparently provide an important seasonal foraging area. In this paper we aim to characterize habitat preferences and analyze the temporal distribution of blue whales around São Miguel Island. To do so, we applied Generalized Additive Models to an opportunistic cetacean occurrence dataset and remotely sensed environmental data on bathymetry, sea surface temperature, chlorophyll concentration and altimetry. We provide a brief description of the oceanography of the area, emphasizing its high spatio-temporal variability. In order to capture this dynamism, we used environmental data with two different spatial resolutions (low and high) and three different temporal resolutions (daily, weekly and monthly), thus accounting for both long-term oceanographic events such as the spring bloom, and shorter-term features such as eddies or fronts. Our results show that blue whales have a well-defined ecological niche around the Azores. They usually cross the archipelago from March to June and habitat suitability is highest in dynamic areas (with high Eddy Kinetic Energy) characterized by convergence or aggregation zones where productivity is enhanced. Multi-scale studies are useful to understand the ecological niche and habitat requirements of highly mobile species that can easily react to short-term changes in the environment.

Assessing cetacean surveys throughout the Mediterranean Sea: a gap analysis in environmental space

Heterogeneous data collection in the marine environment has led to large gaps in our knowledge of marine species distributions. To fill these gaps, models calibrated on existing data may be used to predict species distributions in unsampled areas, given that available data are sufficiently representative. Our objective was to evaluate the feasibility of mapping cetacean densities across the entire Mediterranean Sea using models calibrated on available survey data and various environmental covariates. We aggregated 302,481 km of line transect survey effort conducted in the Mediterranean Sea within the past 20 years by many organisations. Survey coverage was highly heterogeneous geographically and seasonally: large data gaps were present in the eastern and southern Mediterranean and in non-summer months. We mapped the extent of interpolation versus extrapolation and the proportion of data nearby in environmental space when models calibrated on existing survey data were used for prediction across the entire Mediterranean Sea. Using model predictions to map cetacean densities in the eastern and southern Mediterranean, characterised by warmer, less productive waters, and more intense eddy activity, would lead to potentially unreliable extrapolations. We stress the need for systematic surveys of cetaceans in these environmentally unique Mediterranean waters, particularly in non-summer months.