Identifying predictable foraging habitats for a wide-ranging marine predator using ensemble ecological niche models

Aim Ecological niche modelling can provide valuable insight into species' environmental preferences and aid the identification of key habitats for populations of conservation concern. Here, we integrate biologging, satellite remote-sensing and ensemble ecological niche models (EENMs) to identify predictable foraging habitats for a globally important population of the grey-headed albatross (GHA) Thalassarche chrysostoma. Location Bird Island, South Georgia; Southern Atlantic Ocean. Methods GPS and geolocation-immersion loggers were used to track at-sea movements and activity patterns of GHA over two breeding seasons (n = 55; brood-guard). Immersion frequency (landings per 10-min interval) was used to define foraging events. EENM combining Generalized Additive Models (GAM), MaxEnt, Random Forest (RF) and Boosted Regression Trees (BRT) identified the biophysical conditions characterizing the locations of foraging events, using time-matched oceanographic predictors (Sea Surface Temperature, SST; chlorophyll a, chl-a; thermal front frequency, TFreq; depth). Model performance was assessed through iterative cross-validation and extrapolative performance through cross-validation among years. Results Predictable foraging habitats identified by EENM spanned neritic ( 0.5 mg m−3) and frequent manifestation of mesoscale thermal fronts. Our results confirm previous indications that GHA exploit enhanced foraging opportunities associated with frontal systems and objectively identify the APFZ as a region of high foraging habitat suitability. Moreover, at the spatial and temporal scales investigated here, the performance of multi-model ensembles was superior to that of single-algorithm models, and cross-validation among years indicated reasonable extrapolative performance. Main conclusions EENM techniques are useful for integrating the predictions of several single-algorithm models, reducing potential bias and increasing confidence in predictions. Our analysis highlights the value of EENM for use with movement data in identifying at-sea habitats of wide-ranging marine predators, with clear implications for conservation and management

Retrospective analysis of measures to reduce large whale entanglements in a lucrative commercial fishery

Recovering marine animal populations and climate-driven shifts in their distributions are colliding with growing ocean use by humans. One such example is the bycatch of whales in commercial fishing, which poses a significant threat to the conservation and continued recovery of these protected animals and is a major barrier to sustainable fisheries. Long-lasting solutions to this problem need to be robust to variability in ecological dynamics while also addressing socio-cultural and economic concerns. We assessed the efficacy of gear reductions as an entanglement mitigation strategy during 2019 and 2020 in the highly valuable Dungeness crab fishery (Washington State, USA) in terms of changes in the entanglement risk to protected blue and humpback whales, and in terms of economic consequences for the fishery. Using a combination of fishery logbooks, landings data, and whale habitat models, we found that in the two seasons with mandatory crab pot reductions, entanglement risk was reduced by up to 20 % for blue whales, and 78 % for humpback whales, compared to seasons with no regulations. Spatio-temporal variability in the distribution of each whale species was a key factor in determining risk. Importantly, the conservation measure did not have a substantial negative effect on fleet-level fishery performance metrics, despite a reduction in fishing effort. Results indicated that a simple, fixed management strategy achieved the desired conservation goals in an economically sustainable way. Our findings underscore the value of carefully considering the dynamic nature of species\u27 spatial distributions and key social and economic impacts that together determine conservation efficacy

Context-dependent lateralized feeding strategies in blue whales.

Lateralized behaviors benefit individuals by increasing task efficiency in foraging and anti-predator behaviors [1-4]. The conventional lateralization paradigm suggests individuals are left or right lateralized, although the direction of this laterality can vary for different tasks (e.g. foraging or predator inspection/avoidance). By fitting tri-axial movement sensors to blue whales (Balaenoptera musculus), and by recording the direction and size of their rolls during lunge feeding events, we show how these animals differ from such a paradigm. The strength and direction of individuals' lateralization were related to where and how the whales were feeding in the water column. Smaller rolls (≤180°) predominantly occurred at depth (>70 m), with whales being more likely to rotate clockwise around their longest axis (right lateralized). Larger rolls (>180°), conversely, occurred more often at shallower depths (<70 m) and were more likely to be performed anti-clockwise (left lateralized). More acrobatic rolls are typically used to target small, less dense krill patches near the water's surface [5,6], and we posit that the specialization of lateralized feeding strategies may enhance foraging efficiency in environments with heterogeneous prey distributions

Towards a global understanding of the drivers of marine and terrestrial biodiversity

Understanding the distribution of life’s variety has driven naturalists and scientists for centuries, yet this has been constrained both by the available data and the models needed for their analysis. Here we compiled data for over 67,000 marine and terrestrial species and used artificial neural networks to model species richness with the state and variability of climate, productivity, and multiple other environmental variables. We find terrestrial diversity is better predicted by the available environmental drivers than is marine diversity, and that marine diversity can be predicted with a smaller set of variables. Ecological mechanisms such as geographic isolation and structural complexity appear to explain model residuals and also identify regions and processes that deserve further attention at the global scale. Improving estimates of the relationships between the patterns of global biodiversity, and the environmental mechanisms that support them, should help in efforts to mitigate the impacts of climate change and provide guidance for adapting to life in the Anthropocene

Western Gull Foraging Behavior as an Ecosystem State Indicator in Coastal California

With accelerating climate variability and change, novel approaches are needed to warn managers of changing ecosystem state and to identify appropriate management actions. One strategy is using indicator species—like seabirds as ecosystem sentinels—to monitor changes in marine environments. Here, we explore the utility of western gulls (Larus occidentalis) breeding on Southeast Farallon Island as a proxy of ecosystem state in coastal California by investigating the interannual variability in gull foraging behavior from 2013 to 2019 in relation to upwelling conditions, prey abundances, and overlap with humpback whales (Megaptera novaeangliae) as gulls frequently feed in association with whales. Western gulls have a flexible diet and forage on land and at-sea. We combined gull GPS tracking data during the incubation phase, ecosystem survey data on multiple predator and prey species, and derived oceanographic upwelling products. When foraging at sea, gulls overlapped with cool upwelled waters. During 2015–2017, 25% more gull foraging trips visited land than in other years, where land trips were on average ∼8 h longer and 40% further than sea trips, which coincided with high compression of coastally upwelled waters (habitat compression) in 2015–2016. Gull foraging behavior was related to local prey abundances, where more foraging occurred near shore or on land when prey abundances were low. However, visual surveys indicated that ∼70% of humpback whale observations co-occurred with gulls, and the year with the most foraging on land (2017) corresponded to regionally low relative whale abundances, suggesting gull movement patterns could be an indicator of whale presence. Further, both whales and gulls forage near-shore under high upwelling habitat compression and low krill abundance. Hence, the deployment of year-round tags on gulls with the capability of near real-time data accessibility could provide important fine-scale metrics for conservation and management of the threatened yet recovering eastern Pacific humpback whale population between infrequent and coarse surveys. Entanglement in fishing gear and ship strikes are major inhibitors to whale recovery and have increased concomitantly with human use of ocean resources. Moreover, as climate variability and change increase, novel indicators should be explored and implemented to inform marine spatial planning and protect species across multiple scales from new risks

Feeding performance by sympatric blue and fin whales exploiting a common prey resource

A major focus in macroecology is to understand the mechanisms that drive differences in habitat, morphology, and behavior in closely related species (Brown 1995). Within this paradigm, energy use and prey acquisition play a fundamental role in affecting behavior, especially with respect to foraging patterns and predator‐prey interactions. Because resources may occur in discrete regions and are often limited, sympatric organisms that feed in similar ways partition resources, when they are limited, both to avoid competition and maximize energy gain (Pianka 1974, Schoener 1983). Baleen whales (Mysticeti) comprise more than a dozen species that have evolved a bulk‐filter feeding strategy that enables the efficient exploitation of low trophic level oceanic resources. Although mysticetes are opportunistic predators that feed on diverse prey types, from schooling fish to small copepods, many sympatric baleen whale species, including blue (Balaenoptera musculus) and fin whales (Balaenoptera physalus), target the similar resources. What remains unknown, however, is whether resources are partitioned when baleen whales and prey overlap in both time and space.This is the publisher’s final pdf. The article is copyrighted by the Society for Marine Mammalogy and published by John Wiley & Sons Ltd. It can be found at: http://onlinelibrary.wiley.com/journal/10.1111/%28ISSN%291748-769

Listening to farmers

Extension officers in the Pacific are working with farmers to produce DVDs, printed guides and radio and TV programmes in order strengthen rural economie

Integrating Dynamic Subsurface Habitat Metrics Into Species Distribution Models

Species distribution models (SDMs) have become key tools for describing and predicting species habitats. In the marine domain, environmental data used in modeling species distributions are often remotely sensed, and as such have limited capacity for interpreting the vertical structure of the water column, or are sampled in situ, offering minimal spatial and temporal coverage. Advances in ocean models have improved our capacity to explore subsurface ocean features, yet there has been limited integration of such features in SDMs. Using output from a data-assimilative configuration of the Regional Ocean Modeling System, we examine the effect of including dynamic subsurface variables in SDMs to describe the habitats of four pelagic predators in the California Current System (swordfish Xiphias gladius, blue sharks Prionace glauca, common thresher sharks Alopias vulpinus, and shortfin mako sharks lsurus oxyrinchus). Species data were obtained from the California Drift Gillnet observer program (1997-2017). We used boosted regression trees to explore the incremental improvement enabled by dynamic subsurface variables that quantify the structure and stability of the water column: isothermal layer depth and bulk buoyancy frequency. The inclusion of these dynamic subsurface variables significantly improved model explanatory power for most species. Model predictive performance also significantly improved, but only for species that had strong affiliations with dynamic variables (swordfish and shortfin mako sharks) rather than static variables (blue sharks and common thresher sharks). Geospatial predictions for all species showed the integration of isothermal layer depth and bulk buoyancy frequency contributed value at the mesoscale level (\u3c 100 km) and varied spatially throughout the study domain. These results highlight the utility of including dynamic subsurface variables in SDM development and support the continuing ecological use of biophysical output from ocean circulation models

Characterizing Habitat Suitability for a Central‐Place Forager in a Dynamic Marine Environment

Characterizing habitat suitability for a marine predator requires an understanding of the environmental heterogeneity and variability over the range in which a population moves during a particular life cycle. Female California sea lions (Zalophus californianus) are central‐place foragers and are particularly constrained while provisioning their young. During this time, habitat selection is a function of prey availability and proximity to the rookery, which has important implications for reproductive and population success. We explore how lactating females may select habitat and respond to environmental variability over broad spatial and temporal scales within the California Current System. We combine near‐real‐time remotely sensed satellite oceanography, animal tracking data (n = 72) from November to February over multiple years (2003–2009) and Generalized Additive Mixed Models (GAMMs) to determine the probability of sea lion occurrence based on environmental covariates. Results indicate that sea lion presence is associated with cool (\u3c14°C), productive waters, shallow depths, increased eddy activity, and positive sea‐level anomalies. Predictive habitat maps generated from these biophysical associations suggest winter foraging areas are spatially consistent in the nearshore and offshore environments, except during the 2004–2005 winter, which coincided with an El Niño event. Here, we show how a species distribution model can provide broadscale information on the distribution of female California sea lions during an important life history stage and its implications for population dynamics and spatial management