Intraguild processes drive space-use patterns in a large-bodied marine predator community.

Interspecific interactions, including predator-prey, intraguild predation (IGP) and competition, may drive distribution and habitat use of predator communities. However, elucidating the relative importance of these interactions in shaping predator distributions is challenging, especially in marine communities comprising highly mobile species. We used individual-based models (IBMs) to predict the habitat distributions of apex predators, intraguild (IG) prey and prey. We then used passive acoustic telemetry to test these predictions in a subtropical marine predator community consisting of eight elasmobranch (i.e. shark and ray) species in Bimini, The Bahamas. IBMs predicted that prey and IG prey will preferentially select habitats based on safety over resources (food), with stronger selection for safe habitat by smaller prey. Elasmobranch space-use patterns matched these predictions. Species with predator-prey and asymmetrical IGP (between apex and small mesopredators) interactions showed the clearest spatial separation, followed by asymmetrical IGP among apex and large mesopredators. Competitors showed greater spatial overlap although with finer-scale differences in microhabitat use. Our study suggests space-use patterns in elasmobranchs are at least partially driven by interspecific interactions, with stronger spatial separation occurring where interactions include predator-prey relationships or IGP.

Prey encounters and spatial memory influence use of foraging patches in a marine central place forager.

Given the patchiness and long-term predictability of marine resources, memory of high-quality foraging grounds is expected to provide fitness advantages for central place foragers. However, it remains challenging to characterize how marine predators integrate memory with recent prey encounters to adjust fine-scale movement and use of foraging patches. Here, we used two months of movement data from harbour seals (Phoca vitulina) to quantify the repeatability in foraging patches as a proxy for memory. We then integrated these data into analyses of fine-scale movement and underwater behaviour to test how both spatial memory and prey encounter rates influenced the seals' area-restricted search (ARS) behaviour. Specifically, we used one month's GPS data from 29 individuals to build spatial memory maps of searched areas and archived accelerometery data from a subset of five individuals to detect prey catch attempts, a proxy for prey encounters. Individuals were highly consistent in the areas they visited over two consecutive months. Hidden Markov models showed that both spatial memory and prey encounters increased the probability of seals initiating ARS. These results provide evidence that predators use memory to adjust their fine-scale movement, and this ability should be accounted for in movement models.

Individual-Level Memory Is Sufficient to Create Spatial Segregation among Neighboring Colonies of Central Place Foragers.

AbstractCentral place foragers often segregate in space, even without signs of direct agonistic interactions. Using parsimonious individual-based simulations, we show that for species with spatial cognitive abilities, individual-level memory of resource availability can be sufficient to cause spatial segregation in the foraging ranges of colonial animals. The shapes of the foraging distributions are governed by commuting costs, the emerging distribution of depleted resources, and the fidelity of foragers to their colonies. When colony fidelity is weak and foragers can easily switch to colonies located closer to favorable foraging grounds, this leads to space partitioning with equidistant borders between neighboring colonies. In contrast, when colony fidelity is strong-for example, because larger colonies provide safety in numbers or individuals are unable to leave-it can create a regional imbalance between resource requirements and resource availability. This leads to nontrivial space-use patterns that propagate through the landscape. Interestingly, while better spatial memory creates more defined boundaries between neighboring colonies, it can lower the average intake rate of the population, suggesting a potential trade-off between an individual's attempt for increased intake and population growth rates.

Within Reach? Habitat Availability as a Function of Individual Mobility and Spatial Structuring.

Organisms need access to particular habitats for their survival and reproduction. However, even if all necessary habitats are available within the broader environment, they may not all be easily reachable from the position of a single individual. Many species distribution models consider populations in environmental (or niche) space, hence overlooking this fundamental aspect of geographical accessibility. Here, we develop a formal way of thinking about habitat availability in environmental spaces by describing how limitations in accessibility can cause animals to experience a more limited or simply different mixture of habitats than those more broadly available. We develop an analytical framework for characterizing constrained habitat availability based on the statistical properties of movement and environmental autocorrelation. Using simulation experiments, we show that our general statistical representation of constrained availability is a good approximation of habitat availability for particular realizations of landscape-organism interactions. We present two applications of our approach, one to the statistical analysis of habitat preference (using step-selection functions to analyze harbor seal telemetry data) and a second that derives theoretical insights about population viability from knowledge of the underlying environment. Analytical expressions for habitat availability, such as those we develop here, can yield gains in analytical speed, biological realism, and conceptual generality by allowing us to formulate models that are habitat sensitive without needing to be spatially explicit.

Mapping Underwater Sound in the Dutch Part of the North Sea.

The European Union requires member states to achieve or maintain good environmental status for their marine territorial waters and explicitly mentions potentially adverse effects of underwater sound. In this study, we focused on producing maps of underwater sound from various natural and anthropogenic origins in the Dutch North Sea. The source properties and sound propagation are simulated by mathematical methods. These maps could be used to assess and predict large-scale effects on behavior and distribution of underwater marine life and therefore become a valuable tool in assessing and managing the impact of underwater sound on marine life.

Advancing our thinking in presence-only and used-available analysis.

1. The problems of analysing used-available data and presence-only data are equivalent, and this paper uses this equivalence as a platform for exploring opportunities for advancing analysis methodology. 2. We suggest some potential methodological advances in used-available analysis, made possible via lessons learnt in the presence-only literature, for example, using modern methods to improve predictive performance. We also consider the converse - potential advances in presence-only analysis inspired by used-available methodology. 3. Notwithstanding these potential advances in methodology, perhaps a greater opportunity is in advancing our thinking about how to apply a given method to a particular data set. 4. It is shown by example that strikingly different results can be achieved for a single data set by applying a given method of analysis in different ways - hence having chosen a method of analysis, the next step of working out how to apply it is critical to performance. 5. We review some key issues to consider in deciding how to apply an analysis method: apply the method in a manner that reflects the study design; consider data properties; and use diagnostic tools to assess how reasonable a given analysis is for the data at hand.

Quantifying the effect of habitat availability on species distributions.

1. If animals moved randomly in space, the use of different habitats would be proportional to their availability. Hence, deviations from proportionality between use and availability are considered the tell-tale sign of preference. This principle forms the basis for most habitat selection and species distribution models fitted to use-availability or count data (e.g. MaxEnt and Resource Selection Functions). 2. Yet, once an essential habitat type is sufficiently abundant to meet an individual's needs, increased availability of this habitat type may lead to a decrease in the use/availability ratio. Accordingly, habitat selection functions may estimate negative coefficients when habitats are superabundant, incorrectly suggesting an apparent avoidance. Furthermore, not accounting for the effects of availability on habitat use may lead to poor predictions, particularly when applied to habitats that differ considerably from those for which data have been collected. 3. Using simulations, we show that habitat use varies non-linearly with habitat availability, even when individuals follow simple movement rules to acquire food and avoid risk. The results show that the impact of availability strongly depends on the type of habitat (e.g. whether it is essential or substitutable) and how it interacts with the distribution and availability of other habitats. 4. We demonstrate the utility of a variety of existing and new methods that enable the influence of habitat availability to be explicitly estimated. Models that allow for non-linear effects (using b-spline smoothers) and interactions between environmental covariates defining habitats and measures of their availability were best able to capture simulated patterns of habitat use across a range of environments. 5. An appealing aspect of some of the methods we discuss is that the relative influence of availability is not defined a priori, but directly estimated by the model. This feature is likely to improve model prediction, hint at the mechanism of habitat selection, and may signpost habitats that are critical for the organism's fitness.

Generalized functional responses for species distributions.

Researchers employing resource selection functions (RSFs) and other related methods aim to detect correlates of space-use and mitigate against detrimental environmental change. However, an empirical model fit to data from one place or time is unlikely to capture species responses under different conditions because organisms respond nonlinearly to changes in habitat availability. This phenomenon, known as a functional response in resource selection, has been debated extensively in the RSF literature but continues to be ignored by practitioners for lack of a practical treatment. We therefore extend the RSF approach to enable it to estimate generalized functional responses (GFRs) from spatial data. GFRs employ data from several sampling instances characterized by diverse profiles of habitat availability. By modeling the regression coefficients of the underlying RSF as functions of availability, GFRs can account for environmental change and thus predict population distributions in new environments. We formulate the approach as a mixed-effects model so that it is estimable by readily available statistical software. We illustrate its application using (1) simulation and (2) wolf home-range telemetry. Our results indicate that GFRs can offer considerable improvements in estimation speed and predictive ability over existing mixed-effects approaches.

Counting using deep learning regression gives value to ecological surveys.

Many ecological studies rely on count data and involve manual counting of objects of interest, which is time-consuming and especially disadvantageous when time in the field or lab is limited. However, an increasing number of works uses digital imagery, which opens opportunities to automatise counting tasks. In this study, we use machine learning to automate counting objects of interest without the need to label individual objects. By leveraging already existing image-level annotations, this approach can also give value to historical data that were collected and annotated over longer time series (typical for many ecological studies), without the aim of deep learning applications. We demonstrate deep learning regression on two fundamentally different counting tasks: (i) daily growth rings from microscopic images of fish otolith (i.e., hearing stone) and (ii) hauled out seals from highly variable aerial imagery. In the otolith images, our deep learning-based regressor yields an RMSE of 3.40 day-rings and an [Formula: see text] of 0.92. Initial performance in the seal images is lower (RMSE of 23.46 seals and [Formula: see text] of 0.72), which can be attributed to a lack of images with a high number of seals in the initial training set, compared to the test set. We then show how to improve performance substantially (RMSE of 19.03 seals and [Formula: see text] of 0.77) by carefully selecting and relabelling just 100 additional training images based on initial model prediction discrepancy. The regression-based approach used here returns accurate counts ([Formula: see text] of 0.92 and 0.77 for the rings and seals, respectively), directly usable in ecological research.

The role of environmental variables in structuring landscape-scale species distributions in seafloor habitats.

Ongoing statistical sophistication allows a shift from describing species' spatial distributions toward statistically disentangling the possible roles of environmental variables in shaping species distributions. Based on a landscape-scale benthic survey in the Dutch Wadden Sea, we show the merits of spatially explicit generalized estimating equations (GEE). The intertidal macrozoobenthic species, Macoma balthica, Cerastoderma edule, Marenzelleria viridis, Scoloplos armiger, Corophium volutator, and Urothoe poseidonis served as test cases, with median grain-size and inundation time as typical environmental explanatory variables. GEEs outperformed spatially naive generalized linear models (GLMs), and removed much residual spatial structure, indicating the importance of median grain-size and inundation time in shaping landscape-scale species distributions in the intertidal. GEE regression coefficients were smaller than those attained with GLM, and GEE standard errors were larger. The best fitting GEE for each species was used to predict species' density in relation to median grain-size and inundation time. Although no drastic changes were noted compared to previous work that described habitat suitability for benthic fauna in the Wadden Sea, our predictions provided more detailed and unbiased estimates of the determinants of species-environment relationships. We conclude that spatial GEEs offer the necessary methodological advances to further steps toward linking pattern to process.

Echoes from the past: Regional variations in recovery within a harbour seal population.

Terrestrial and marine wildlife populations have been severely reduced by hunting, fishing and habitat destruction, especially in the last centuries. Although management regulations have led to the recovery of some populations, the underlying processes are not always well understood. This study uses a 40-year time series of counts of harbour seals (Phoca vitulina) in the Wadden Sea to study these processes, and demonstrates the influence of historical regional differences in management regimes on the recovery of this population. While the Wadden Sea is considered one ecologically coupled zone, with a distinct harbour seal population, the area is divided into four geo-political regions i.e. the Netherlands, Lower Saxony including Hamburg, Schleswig-Holstein and Denmark. Gradually, seal hunting was banned between 1962 and 1977 in the different regions. Counts of moulting harbour seals and pup counts, obtained during aerial surveys between 1974 and 2014, show a population growth from approximately 4500 to 39,000 individuals. Population growth models were developed to assess if population growth differed between regions, taking into account two Phocine Distemper Virus (PDV) epizootics, in 1988 and 2002 which seriously affected the population. After a slow start prior to the first epizootic, the overall population grew exponentially at rates close to assumed maximum rates of increase in a harbour seal population. Recently, growth slowed down, potentially indicative of approaching carrying capacity. Regional differences in growth rates were demonstrated, with the highest recovery in Netherlands after the first PDV epizootic (i.e. 17.9%), suggesting that growth was fuelled by migration from the other regions, where growth remained at or below the intrinsic growth rate (13%). The seals' distribution changed, and although the proportion of seals counted in the German regions declined, they remained by far the most important pupping region, with approximately 70% of all pups being born there. It is hypothesised that differences in hunting regime, preceding the protection in the 1960's and 1970's, created unbalance in the distribution of breeding females throughout the Wadden Sea, which prevailed for decades. Breeding site fidelity promoted the growth in pup numbers at less affected breeding sites, while recolonisation of new breeding areas would be suppressed by the philopatry displayed by the animals born there. This study shows that for long-lived species, variable management regimes in this case hunting regulations, across a species' range can drive population dynamics for several generations.

Estimating the spatial position of marine mammals based on digital camera recordings.

Estimating the spatial position of organisms is essential to quantify interactions between the organism and the characteristics of its surroundings, for example, predator-prey interactions, habitat selection, and social associations. Because marine mammals spend most of their time under water and may appear at the surface only briefly, determining their exact geographic location can be challenging. Here, we developed a photogrammetric method to accurately estimate the spatial position of marine mammals or birds at the sea surface. Digital recordings containing landscape features with known geographic coordinates can be used to estimate the distance and bearing of each sighting relative to the observation point. The method can correct for frame rotation, estimates pixel size based on the reference points, and can be applied to scenarios with and without a visible horizon. A set of R functions was written to process the images and obtain accurate geographic coordinates for each sighting. The method is applied to estimate the spatiotemporal fine-scale distribution of harbour porpoises in a tidal inlet. Video recordings of harbour porpoises were made from land, using a standard digital single-lens reflex (DSLR) camera, positioned at a height of 9.59 m above mean sea level. Porpoises were detected up to a distance of ∽3136 m (mean 596 m), with a mean location error of 12 m. The method presented here allows for multiple detections of different individuals within a single video frame and for tracking movements of individuals based on repeated sightings. In comparison with traditional methods, this method only requires a digital camera to provide accurate location estimates. It especially has great potential in regions with ample data on local (a)biotic conditions, to help resolve functional mechanisms underlying habitat selection and other behaviors in marine mammals in coastal areas.

Rapid population decline in red knots: fitness consequences of decreased refuelling rates and late arrival in Delaware Bay.

Most populations of migrant shorebirds around the world are in serious decline, suggesting that vital condition-dependent rates such as fecundity and annual survival are being affected globally. A striking example is the red knot (Calidris canutus rufa) population wintering in Tierra del Fuego, which undertakes marathon 30,000 km hemispheric migrations annually. In spring, migrant birds forage voraciously on horseshoe crab eggs in Delaware Bay in the eastern USA before departing to breed in Arctic polar deserts. From 1997 to 2002 an increasing proportion of knots failed to reach threshold departure masses of 180-200 g, possibly because of later arrival in the Bay and food shortage from concurrent over-harvesting of crabs. Reduced nutrient storage, especially in late-arriving birds, possibly combined with reduced sizes of intestine and liver during refuelling, had severe fitness consequences for adult survival and recruitment of young in 2000-2002. From 1997 to 2002 known survivors in Delaware Bay were heavier at initial capture than birds never seen again, annual survival of adults decreased by 37% between May 2000 and May 2001, and the number of second-year birds in wintering flocks declined by 47%. Population size in Tierra del Fuego declined alarmingly from 51,000 to 27,000 in 2000-2002, seriously threatening the viability of this subspecies. Demographic modelling predicts imminent endangerment and an increased risk of extinction of the subspecies without urgent risk-averse management.

The influence of topographic and dynamic cyclic variables on the distribution of small cetaceans in a shallow coastal system.

The influence of topographic and temporal variables on cetacean distribution at a fine-scale is still poorly understood. To study the spatial and temporal distribution of harbour porpoise Phocoena phocoena and the poorly known Risso's dolphin Grampus griseus we carried out land-based observations from Bardsey Island (Wales, UK) in summer (2001-2007). Using Kernel analysis and Generalized Additive Models it was shown that porpoises and Risso's appeared to be linked to topographic and dynamic cyclic variables with both species using different core areas (dolphins to the West and porpoises to the East off Bardsey). Depth, slope and aspect and a low variation in current speed (for Risso's) were important in explaining the patchy distributions for both species. The prime temporal conditions in these shallow coastal systems were related to the tidal cycle (Low Water Slack and the flood phase), lunar cycle (a few days following the neap tidal phase), diel cycle (afternoons) and seasonal cycle (peaking in August) but differed between species on a temporary but predictable basis. The measure of tidal stratification was shown to be important. Coastal waters generally show a stronger stratification particularly during neap tides upon which the phytoplankton biomass at the surface rises reaching its maximum about 2-3 days after neap tide. It appeared that porpoises occurred in those areas where stratification is maximised and Risso's preferred more mixed waters. This fine-scale study provided a temporal insight into spatial distribution of two species that single studies conducted over broader scales (tens or hundreds of kilometers) do not achieve. Understanding which topographic and cyclic variables drive the patchy distribution of porpoises and Risso's in a Headland/Island system may form the initial basis for identifying potentially critical habitats for these species.

Harbour porpoises Phocoena phocoena in the eastern Scheldt: a resident stock or trapped by a storm surge barrier?

Coastal protection measures are planned and executed worldwide to combat the effects of global warming and climate change, in particular the acceleration of sea level rise, higher storm surge flooding and extensive coastal inundation. The extent to which these defensive measures may impact coastal and estuarine ecosystems is still poorly understood. Since the building of a storm surge barrier, movement of harbour porpoises Phocoena phocoena in and out of the Eastern Scheldt tidal bay (SW-Netherlands) may be limited. To measure residency, porpoises stranded along the Dutch North Sea coast between 2006 and 2008 were sampled for muscle (n = 102) and bone tissue (n = 118), of which 9 muscle (8.8%) and 12 bone samples (10.2%) were collected from animals stranded within the Eastern Scheldt. Stable carbon (δ(13)C) was analysed to get insight into the habitat use and residency of porpoises in the Eastern Scheldt. Our data showed significantly higher δ(13)C values in the muscle of porpoises stranded within the Eastern Scheldt (µ = -17.7‰, SD = 0.4‰) compared to animals stranded along the Dutch coast (µ = -18.3‰, SD = 0.5‰). This suggests that most porpoises stranded in the Eastern Scheldt foraged there for a longer period. The distinct δ(13)C signature of animals from the Eastern Scheldt was not observed in bone tissue, suggesting a relatively recent shift in habitat use rather than life-long residency of porpoises within the Eastern Scheldt. The high number of strandings within the Eastern Scheldt suggests a higher mortality rate compared to the Dutch coastal zone. Our study indicates that along with other changes in the physical environment, the storm surge barrier may play an important role in determining the residency of porpoises in the Eastern Scheldt, and that the area might act as an ecological trap for porpoises entering it.