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The Bay of Bengal (BoB) generally exhibits surface oligotrophy due to nutrient limitation induced by strong salinity stratification. Nevertheless, there are hotspots of high chlorophyll in the BoB where the monsoonal forcings are strong enough to break the stratification; one such region is the southern BoB, east of Sri Lanka. A recent field programme conducted during the summer monsoon of 2016, as a part of the Bay of Bengal Boundary Layer Experiment (BoBBLE), provides a unique high-resolution dataset of the vertical distribution of chlorophyll in the southern BoB using ocean gliders along with shipboard conductivity–temperature–depth (CTD) measurements. Observations were carried out for a duration of 12–20 days, covering the dynamically active regions of the Sri Lanka Dome (SLD) and the Southwest Monsoon Current (SMC). Mixing and upwelling induced by the monsoonal wind forcing enhanced surface chlorophyll concentrations (0.3–0.7 mg m−3). Prominent deep chlorophyll maxima (DCM; 0.3–1.2 mg m−3) existed at intermediate depths (20–50 m), signifying the contribution of subsurface productivity to the biological carbon cycling in the BoB. The shape of chlorophyll profiles varied in different dynamical regimes; upwelling was associated with sharp and intense DCM, whereas mixing resulted in a diffuse and weaker DCM. Within the SLD, open-ocean Ekman suction favoured a substantial increase in chlorophyll. Farther east, where the thermocline was deeper, enhanced surface chlorophyll was associated with intermittent mixing events. Remote forcing by the westward propagating Rossby waves influenced the upper-ocean dynamics and chlorophyll distribution in the southern BoB. Stabilizing surface freshening events and barrier-layer formation often inhibited the generation of surface chlorophyll. The pathway of the SMC intrusion was marked by a distinct band of chlorophyll, indicating the advective effect of biologically rich Arabian Sea waters. The region of the monsoon current exhibited the strongest DCM as well as the highest column-integrated chlorophyll. Observations suggest that the persistence of DCM in the southern BoB is promoted by surface oligotrophy and shallow mixed layers. Results from a coupled physical–ecosystem model substantiate the dominant role of mixed layer processes associated with the monsoon in controlling the nutrient distribution and biological productivity in the southern BoB. The present study provides new insights into the vertical distribution of chlorophyll in the BoB, emphasizing the need for extensive in situ sampling and ecosystem model-based efforts for a better understanding of the biophysical interactions and the potential climatic feedbacks.

Insect pollination underpins apple production but the extent to which different pollinator guilds supply this service, particularly across different apple varieties, is unknown. Such information is essential if appropriate orchard management practices are to be targeted and proportional to the potential benefits pollinator species may provide. Here we use a novel combination of pollinator effectiveness assays (floral visit effectiveness), orchard field surveys (flower visitation rate) and pollinator dependence manipulations (pollinator exclusion experiments) to quantify the supply of pollination services provided by four different pollinator guilds to the production of four commercial varieties of apple. We show that not all pollinators are equally effective at pollinating apples, with hoverflies being less effective than solitary bees and bumblebees, and the relative abundance of different pollinator guilds visiting apple flowers of different varieties varies significantly. Based on this, the taxa specific economic benefits to UK apple production have been established. The contribution of insect pollinators to the economic output in all varieties was estimated to be £92.1M across the UK, with contributions varying widely across taxa: solitary bees (£51.4M), honeybees (£21.4M), bumblebees (£18.6M) and hoverflies (£0.7M). This research highlights the differences in the economic benefits of four insect pollinator guilds to four major apple varieties in the UK. This information is essential to underpin appropriate investment in pollination services management and provides a model that can be used in other entomolophilous crops to improve our understanding of crop pollination ecology.

Density dependence is a fundamental ecological process. In particular, animal habitat selection and social behavior often affect fitness in a density-dependent manner. The Ideal Free Distribution (IFD) and niche variation hypothesis (NVH) present distinct predictions associated with Optimal Foraging Theory about how the effect of habitat selection on fitness varies with population density. Using caribou ( Rangifer tarandus ) in Canada as a model system, we test competing hypotheses about how habitat specialization, social behavior, and annual reproductive success (co)vary across a population density gradient. Within a behavioral reaction norm framework, we estimate repeatability, behavioral plasticity, and covariance among social behavior and habitat selection to investigate the adaptive value of sociality and habitat selection. In support of NVH, but not the IFD, we find that at high density habitat specialists had higher annual reproductive success than generalists, but were also less social than generalists, suggesting the possibility that specialists were less social to avoid competition. Our study supports niche variation as a mechanism for density-dependent habitat specialization. Social behavior and habitat specialization are often linked through density-dependence and their effects on fitness. Here, the authors show that in caribou, these traits are density-dependent, but only habitat specialization has an effect on fitness.

Floating ice shelves buttress the Antarctic Ice Sheet, which is losing mass rapidly mainly due to ocean-driven melting and the associated disruption to glacial dynamics. The local ocean circulation near ice shelves is therefore important for the prediction of future ice mass loss and related sea-level rise as it determines the water mass exchange, heat transport under the ice shelf and resultant melting. However, the dynamics controlling the near-coastal circulation are not fully understood. A cyclonic (i.e. clockwise) gyre circulation (27 km radius) in front of the Pine Island Ice Shelf has previously been identified in both numerical models and velocity observations. Mooring data further revealed a potential reversal of this gyre during an abnormally cold period. Here we present ship-based observations from 2019 to the west of Thwaites Ice Shelf, revealing another gyre (13 km radius) for the first time in this habitually ice-covered region, rotating in the opposite (anticyclonic, anticlockwise) direction to the gyre near Pine Island Ice Shelf, despite similar wind forcing. We use an idealised configuration of MITgcm, with idealised forcing based on ERA5 climatological wind fields and a range of idealised sea ice conditions typical for the region, to reproduce key features of the observed gyres near Pine Island Ice Shelf and Thwaites Ice Shelf. The model driven solely by wind forcing in the presence of ice can reproduce the horizontal structure and direction of both gyres. We show that the modelled gyre direction depends upon the spatial difference in the ocean surface stress, which can be affected by the applied wind stress curl filed, the percentage of wind stress transferred through the ice, and the angle between the wind direction and the sea ice edge. The presence of ice, either it is fast ice/ice shelves blocking the effect of wind or mobile sea ice enhancing the effect of wind, has the potential to reverse the gyre direction relative to ice-free conditions.

As the largest oligotrophic ocean globally, the North Pacific oligotrophic ocean gyre (NPOG) exhibits pronounced variability on seasonal, decadal, and centennial time scales. Notably, changes in the seasonality of the NPOG are thought to have larger effects on marine ecosystems than changes in its annual mean state. However, the interannual variability of NPOG seasonality and its response to climate processes remain unclear. Here, we investigate the amplitude of the seasonal cycle in NPOG area and its linkage with climate variability and change. Our results show that the El Niño–Southern Oscillation (ENSO) modulated the seasonal maximum of NPOG area in boreal summer, and thus the amplitude of the seasonal cycle during 1998–2021. This is primarily due to ENSO-induced changes in nutrient transport via equatorial upwelling and thermal stratification, as well as changes in the chlorophyll-to-carbon ratio in phytoplankton cells (photoacclimation). Future projections based on Coupled Model Intercomparison Project Phase 5 (CMIP5) modelling results and an Elman neural network indicate a significant decrease in the seasonal amplitude of NPOG area by 2100, attributed to the growing seasonal minimum of NPOG area in winter along the anthropogenic increase in atmospheric CO2. The findings highlight the importance of considering seasonal differences in future research on the interannual variability of oligotrophic gyres and underscore the need for models to distinguish between the effects of climate variability and change.

Social network analysis is increasingly applied to understand animal groups. However, it is rarely feasible to observe every interaction among all individuals in natural populations. Studies have assessed how missing information affects estimates of individual network positions, but less attention has been paid to metrics that characterize overall network structure such as modularity, clustering coefficient, and density. In cases such as groups displaying fission-fusion dynamics, where subgroups break apart and rejoin in changing conformations, missing information may affect estimates of global network structure differently than in groups with distinctly separated communities due to the influence single individuals can have on the connectivity of the network. Using a bat maternity group showing fission-fusion dynamics, we quantify the effect of missing data on global network measures including community detection. In our system, estimating the number of communities was less reliable than detecting community structure. Further, reliably assorting individual bats into communities required fewer individuals and fewer observations per individual than to estimate the number of communities. Specifically, our metrics of global network structure (i.e., graph density, clustering coefficient, R com ) approached the ‘real’ values with increasing numbers of observations per individual and, as the number of individuals included increased, the variance in these estimates decreased. Similar to previous studies, we recommend that more observations per individual should be prioritized over including more individuals when resources are limited. We recommend caution when making conclusions about animal social networks when a substantial number of individuals or observations are missing, and when possible, suggest subsampling large datasets to observe how estimates are influenced by sampling intensity. Our study serves as an example of the reliability, or lack thereof, of global network measures with missing information, but further work is needed to determine how estimates will vary with different data collection methods, network structures, and sampling periods.

Acoustic telemetry has emerged as a leading approach to infer diel, tidal and lunar rhythmicity in the movements of aquatic organisms in a range of taxa. Typically, studies examine the relative frequency of detections from individuals tagged with acoustic transmitters, and then infer patterns in the species’ behaviour, but studies to date have not controlled for factors that may influence tag detection patterns in the absence of animal behaviour. We compared patterns in acoustic detections from tagged cuttlefishSepia apamaand several fixed-location control tags, and used these data to highlight the danger of misinterpreting patterns in the absence of adequate controls. Cuttlefish and control tags displayed similar detection patterns, and correcting cuttlefish-detection data for the influence of environmental factors resulted in the opposite pattern of cuttlefish activity displayed prior to correction. This study highlights the danger of using acoustic data to infer animal behaviour in the absence of adequate controls.

Host behavior can affect host-pathogen dynamics, and sociality is predicted to increase risk of pathogen exposure. Many species minimize costs of parasitism by only aggregating seasonally, such as during reproductive periods, but colonial species may still be limited in their potential to evade pathogens. Bats are among the most gregarious mammals and females of many temperate species form maternity colonies in summer where they communally raise pups in both natural and anthropogenic roost structures. Social network structure may differ between natural and anthropogenic roosts in ways that affect pathogen dynamics. We used social network analysis to quantify interactions of big brown bats (Eptesicus fuscus) in a tree-roosting colony, where the colony is divided among multiple trees each day, and a building colony, where most of the colony roosts together each day. We simulated transmission of a pathogen throughout both sets of networks. We tested three hypotheses: (1) network metrics differ between pregnancy and lactation; (2) changing network structure between reproductive stages influences predicted pathogen dynamics; and (3) network metrics and predicted pathogen dynamics differ between colonies of bats in trees versus buildings. Network structure was weaker for bats roosting in trees during pregnancy and lactation compared to bats roosting in a building, and our models showed that a hypothetical pathogen would spread more rapidly for bats in the building colony. Our results are important for understanding variation in social tendencies and pathogen transmission among colonies of bats and have implications for conservation and public health. SIGNIFICANCE STATEMENT: Host behavior, particularly social behavior, can affect dynamics of wildlife pathogens. Bats are highly social mammals and females of temperate species form colonies in spring and early summer in tree or building roosts. Thermal characteristics of trees and buildings appear to differ in ways that affect roosting behavior and social interactions. We used social network analyses to quantify interactions of big brown bats in tree and building roosts and simulated consequences for pathogen dynamics. Network structure was weaker for bats roosting in trees with more frequent roost switching and relatively diffuse contacts across the network. Our models showed that a hypothetical pathogen could spread up to four times faster in a building colony compared to a colony of bats roosting in trees. Our results are important for understanding how sociality can influence pathogen dynamics in bats and have implications for conservation and public health.