Ecology

Citizen science program “Hanamaru-maruhana national census”We asked citizens to take bee photographs and send them by e-mails in citizen science program “Hanamaru-Maruhana national census (Bumble bee national census in English)” (http://hanamaruproject.s1009.xrea.com/hanamaru_project/index_E.html)8. We gave citizens previous notice that their photographs were going to be used for scientific studies, and for other non-profit activities on our homepage and flyers. From 2013 to 2016, we collected roughly 5000 photographs taken by citizens. Citizens sent photographs of various bee species, but most of them were bumble bees and honey bees. They have interspecific similarity and intraspecific variation, making it difficult for non-experts to identify species. Since species identification was not a requirement for participants, most citizens sent bee photographs without species identification. These bees were identified by one of the authors, J. Yokoyama. These bees are relatively easy for experts to identify because only two honey bee species and 16 bumble bee species inhabit the Japanese archipelago excluding the Kurile Islands. The consistency of species identification by J. Yokoyama was 95% for 15 bumble bee species, and 97.7% for major six bumble bee species in our test using 100 bumble bee photographs8.Bee photographs used for deep learningFrom bee species observed in citizen science program “Hanamaru-maruhana national census (Bumble bee national census in English)”, we selected two honey bee species and 10 bumble bee species having interspecific similarity and intraspecific variation. Two honey bee species consisted of Apis cerana Fabricius, and A. mellifera Linnaeus. 10 bumble bee species consisted of Bombus consobrinus Dahlbom, B. diversus Smith, B. ussurensis Radoszkowski, B. pseudobaicalensis Vogt, B. honshuensis Tkalcu, B. ardens Smith, B. beaticola Tkalcu, B. hypocrita Perez, B. ignitus Smith, and B. terrestris Linnaeus. To increase training data of B. pseudobaicalensis, we added photographs of B. deuteronymus Schulz to photographs of B. pseudobaicalensis because they can rarely be distinguished using only photographic images (see http://hanamaruproject.s1009.xrea.com/hanamaru_project/identification_E.html for the details of their color patterns). We primarily used photographs taken by citizens from 2013 to 2015 in the citizen science program, but also used photographs taken by citizens in 2016 if the number of photographs for a certain class was small.We cropped a bee part as a rectangle image from a photograph to reduce background effects. We increased the number of photographs by data augmentation (Fig. S1 in Appendix S1 in Supplementary information). Please see Appendix S1 in Supplementary information for the details of “Data augmentation.” We assigned 70, 10, and 20% of the total data of the training dataset, validation dataset, and test dataset, respectively. Please see Appendix S1 in Supplementary information for the details of “Data split and training parameters”.Deep convolutional neural network (DCNN)In this study, we chose a deep convolutional neural network Xception, as it provides a good balance between the accuracy of the model on one hand and a smaller network size on the other. We adopted transfer learning21,22 and data augmentation23 to solve the issue of a shortage of photographs. The Xception network has a depth of 126 layers (including activation layers, normalization layers etc.) out of which 36 are convolution layers. In this study, we employed the pretrained Xception V1 model provided on the Keras homepage. Please see Appendix S1 in Supplementary information for the details of “Xception”, and “Transfer learning.” For the training, we chose a learning rate of 0.0001 and a momentum of 0.9.Species identification by biologistsWe asked 50 biologists to identify the species present in nine photographs selected randomly from the photograph dataset using a questionnaire form. Their professions were forth undergraduate student (16%), Master’s student (14%), Ph.D. student (12%), Postdoctoral fellow (26%), Assistant professor (6%), Associate professor (12%), Professors (6%), and others (8%). Their research organisms were honey bees (6%), bumble bees (14%), bees (6%), insects (12%), plants and insects (12%), plants (22%), and others such as fishes, reptiles, and mammals (28%). 14% of the biologists were studying bumble bees, but they did not need to identify all bumble bee species in their researches because only several species inhabit their study areas. We allowed the biologists to see field guide books, illustrated books, and websites. We did not limit the method or time to identify the species of photographs to simulate the species identification of actual citizen science programs as much as possible, except for asking experts. The experiment was approved by the Ethics Committee in Tohoku University, and carried out in accordance with its regulations. Informed consent was obtained from the biologists.Species identification in species class experiment by XceptionWe conducted species class experiment by categorizing photographs into different classes according to species. A total of 3779 original photographs were used in species class experiment (Table S1 in Appendix S1 in Supplementary information). These photographs were classified into 12 classes according to species. We inputted test dataset to Xception, and recorded their predicted classes.Species identification in color class experiment by XceptionWe conducted color class experiment by categorizing photographs into different classes according to intraspecific color differences. Photographs of B. ardens were classified into the following four classes: female B. ardens ardens, B. ardens sakagamii, B. ardens tsushimanus, and male B. ardens (Table S1 in Appendix S1 in Supplementary information). Photographs of B. honshuensis, B. beaticola, B. hypocrita, and B. ignitus were classified into female and male classes. In trial experiments, we had found that the Xception cannot learn images in minor classes if the number of original photographs in the classes was less than 40. No photographs in the class were predicted correctly, and no photographs in the other classes were predicted as the class. Therefore, in color class experiment, we did not use the photographs of minor classes (B. ardens subspecies: B. ardens sakagamii and B. ardens tsushimanus, male B. honshuensis, and male B. beaticola). Therefore, a total of 3681 original photographs were used in color class experiment (Table S1 in Appendix S1 in Supplementary information). They were classified into 15 classes according to intraspecific color differences in addition to species classes. We inputted test dataset to Xception, and recorded their predicted classes. To compare the total accuracy of color class experiment by Xception with those of other experiments, it was normalized using the number of test data including those of the minor classes, assuming that all test data of the minor classes were misidentified.The accuracy of species identificationWe calculated total accuracy, precision, recall, and F-score in each class. Total accuracy is the number of total correct predictions divided by the number of all test datasets. Note that the total accuracy of color class experiment by Xception was normalized using the number of test data including those of the minor classes. It reduces the total accuracy of color class experiment by Xception, and enables to compare with those by biologists and species class experiment by Xception directly. Precision is the number of correct predictions as a certain class divided by the number of all predictions as the class returned by biologists or Xception. Recall, which is equivalent to sensitivity, is the number of correct predictions as a certain class divided by the number of test datasets as the class. F-score is the harmonic average of the precision and recall, (2 × precision × recall)/(precision + recall).To show the effect of interspecific similarity on the accuracy of species identification, we used confusion matrix. The confusion matrix represents the relationship between true and predicted classes. Each row indicates the proportion of predicted classes in a true class. All correct predictions are located in the diagonal of the matrix, wrong predictions are located out of the diagonal. In species identification by biologists, “Others” class represents cases that they wrote no species name or a species name other than two honey bee species and 10 bumble bee species in the answer column. More

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Teasing apart the factors that influence prey choice and foraging tactics in the wild poses formidable logistical challenges because of multiple confounding features. For example, a particular type of prey may be rarely consumed not because of predator aversion, but because that prey type is more difficult to find or to capture than some other kind of prey22. Similarly, predators may key in on specific types of prey based on dietary preferences, prey size, or abundance23,24,25. The method of bait deployment that we adopted circumvents many of those problems, by standardising prey abundance, observability, and ease of capture by the predator. Under these conditions, free-ranging crocodiles from toad-sympatric versus toad-naïve populations showed substantial differences in foraging tactics and bait choice. In toad-naïve populations, crocodiles took equal numbers of treatment (toad) baits and control (chicken) baits, and frequently took baits located on land as well as over water. In contrast, crocodiles in toad-sympatric populations generally avoided toad baits in all locations and foraged primarily in the water rather than on land. Both of these shifts—in prey types and foraging locations—conceivably reduce the vulnerability of crocodiles to fatal ingestion of highly toxic cane toads.The relatively rapid ( More

The Antarctic scallop Adamussium colbecki is one of the few species of benthic organisms that we routinely observed in the icy upper reaches of the shallow anchor-ice zone in Explorer’s Cove, in western McMurdo Sound, Antarctica (Supplementary Movie 1). They inhabit both the deep, ice-free zones and the shallowest, iciest areas27 where they can even be found sitting atop the thick, growing anchor-ice blanket (Fig. 1c–e). The external surfaces of this benthic bivalve (hereafter referred to as “shell”) appear to remain ice-free, while rocks and other inanimate materials in the scallops’ vicinity are completely covered with ice (Supplementary Movie 1). In possessing an inanimate calcitic shell, this species may provide a unique example of a marine invertebrate that avoids cryofouling by truly passive means.Similar to the well-studied locales in southeastern McMurdo Sound17,26, diver observations in Explorer’s Cove (2015, 2017, 2018, by PAC) revealed that the prevalence and thickness of the anchor-ice formations are highest in the shallowest locales and decreased with increasing depth of the seabed. From the underside of the surface sea ice (~2–3 m) to about 6 m depth, anchor ice formed a 60-cm-thick mat, covering greater than 90% of the seabed (Zone 1, Fig. 1c). From ~6 to 20 m depth, the anchor-ice cover was patchier, appearing to cover only 30–50% of the seabed (Zone 2; Fig. 1d). Anchor ice was never observed at depths below ~20 m (Zone 3; Fig. 1e). This depth may demarcate the maximum depth of supercooling occurrence in the study area (Fig. 1b). Live scallops were found to be distributed in all three zones. At the shallowest depths, aggregations of scallops were common even atop the growing anchor-ice blanket (Fig. 1c and Supplementary Movie 1). Interestingly, the shells of live scallops were never observed to be cryofouled during ~30 research dives completed during the peak anchor-ice growth periods in Austral spring (October to December of 2015, 2017, and 2018), nor did any scallops appear to be frozen to the actively growing anchor-ice matrix on which they sat.Demonstrating the potential dangers of cryofouling for Antarctic scallops is non-trivial because the scallops themselves appear to naturally avoid cryofouling. However, on numerous occasions, PAC documented cryofouling on bush sponges (Homaxinella balfourensis) that had colonized the external shell surfaces of Antarctic scallops. In these observations, the growth of ice24 on the epizoic sponges caused involuntary flotation of the host scallops due to the buoyancy28 of the ice attached to the sponge (Supplementary Movie 2). This resulted in the transport of both species to the underside of the growing sea-ice cover above, where they presumably froze in and died (Fig. 2a–f). Strikingly, the shells of cryofouled sponge-colonized scallops themselves, as well as uncolonized scallops in their immediate vicinity, appeared to remain devoid of ice. These observations suggest that the scallops themselves must be cryofouling-avoidant compared to the sponge, as well as to non-biogenic minerals in their vicinity (rocks, sand, and fine sediment) (Supplementary Movie 2).Fig. 2: Sea sponge-colonized Antarctic scallops demonstrate the potential dangers for organisms that do not avoid cryofouling.a–c Unless colonized by the cryofouling-susceptible bush sponge (H. balfourensis), Antarctic scallops appear to be unaffected by cryofouling, even in areas where underwater ice growth is prevalent (Zones 1 and 2). d–h Photographic images depicting the progression of cryofouling-induced uplift (by buoyant ice) of sponge-colonized scallops in Zone 2. The negative consequence of cryofouling for scallops becomes apparent only when its surfaces have been colonized by the bush sponge H. balfourensis, which readily accrete ice. g When a sufficient volume of ice has accreted on the sponge, both species are rafted to the underside of the sea ice by buoyant flotation, where both appear to freeze in and die. Scallop is freezing into the underside of the sea ice. Scallop shell exteriors appear to be free of icing even after arriving at the underside of the sea ice. Note: Scallops arriving and freezing into the underside of the sea ice will eventually be enveloped by further sea ice growth. Scale bars indicated are approximates.Full size imageCryofouling of Antarctic scallops could potentially be deleterious in multiple ways beyond that resulting in buoyant uplift and relatively rapid death. For example, ice adhered to a scallop’s shell could impact their swimming and escape behaviors or occlude water flow paths necessary for filter-feeding. In this case, if the Antarctic scallops do not possess anti-cryofouling capabilities, a larger proportion of the population may likely suffer from the same hazards posed by icing to epizoic sponges: ice growth, involuntary flotation, and likely death when merged into the sea ice. Given that no observations of a cryofouled live scallop exist, the icing process on scallops may be different, posing lower risks for accumulation and flotation. The negative consequences on both feeding and motility functionalities (Fig. 2c–h) associated with cryofouling suggest that for organisms inhabiting areas of supercooled seawater, the selection pressure to evolve passive or active anti-icing strategies could be relatively strong.The ability of surfaces to avoid in-air icing is influenced by properties like micro-structuring, surface roughness, hydrophobicity, chemical composition, or specific topological patterns4,5. Figure 3a–e shows the morphological characterization of the shells of the Antarctic scallop. In contrast to two non-Antarctic control species (bay scallop and sea scallop), the shells of the Antarctic scallop are macroscopically smooth, with only minute, elevated concentric growth rings and gently undulated primary ridges apparent to the naked eye. Scanning electron microscopy (SEM) images of the Antarctic scallop shells revealed a highly structured surface29 with concentric growth rings that separate micro-ridges and micro-valleys, forming a distinctive, regular hierarchical texture (Fig. 3f–h). That is, the areas between growth rings are defined by a series of relatively uniform radial micro-ridges. The shell surfaces of the two control species did not exhibit any ordered or repeating microstructures (Supplementary Figs. 2 and 3). For the Antarctic scallop, the spacing between concentric growth rings and radial micro-ridges along a line from the umbo to the margin were determined to be ~250 and ~10 µm wide, respectively. These features are not strictly uniform over the shell and may vary up to an order of magnitude, with the spacing of features increasing as a function of distance from the umbo. The microscopic surface features of larger (older) shells were slightly abraded, with surface wear appearing to increase towards the umbo–the oldest portion of the shell.Fig. 3: Surface characteristics of the Antarctic scallop’s shell features.a–c Terminology and schematics of features on the shell surface, a, b in-plane, and c section view. d, e Macroscopic images in visible light of the Antarctic scallop’s shell surface without magnification. The shell is covered by a thin, proteinaceous covering (periostracum), under which the calcitic material lies throughout the thickness of the shell. Radial rounded, primary ridges, and concentric growth rings are visible. f–h Scanning electron micrographs showing increasing magnification. f Concentric growth rings separating repeating series of g radial micro-ridges (c. 20 µm peak-to-peak). h Small protuberances are irregularly dispersed throughout the radial micro-valleys (Supplementary Fig. 3). Shells are oriented with the umbo at the top in all panels, except c. Shells of temperate control species are substantially rougher and less ordered than those of the Antarctic scallop (Supplementary Fig. 2).Full size imageNext, we determined the elemental composition and roughness at different positions on the shell surface. Energy-dispersive X-ray spectroscopy revealed that the shell surface predominately consists of oxygen, carbon, calcium, traces of silicon, sodium, aluminum, and magnesium (Supplementary Fig. 4). These findings are consistent with a typical calcitic shell (CaCO3) laminated with proteinaceous periostracum. Surface composition was found to be identical at different locations of the analyses, including along concentric growth rings, micro-ridges, or the micro-valleys in between. The surface roughness was determined using atomic force microscopy (AFM) and revealed that the peaks of the concentric growth rings were the roughest (RMS roughness of 135 ± 57 nm), followed by the radial micro-ridges (RMS roughness of 96 ± 3 nm). In contrast, valley floors between these micro-ridges were relatively smooth (RMS roughness of 38 ± 9 nm), interrupted only by small protuberances (nano-grains, diameter of 83 ± 26 nm) that were irregularly dispersed throughout the radial micro-valleys.In nature, unwanted ice accretion on surfaces can occur either by the accumulation of suspended adhesive frazil ice particles or by in situ initiation of ice growth (heterogeneous ice nucleation) on a surface18,25. To test the possibility of preferential ice nucleation, the scallops were subjected to ice nucleation measurements and an in-air frosting assay. Figure 4a, d shows the results of in-air frosting experiments performed using a custom-built apparatus30,31 in an air-filled climate-controlled (20 °C) chamber at controlled humidity (60%). Compared to the temperate control species, ice nucleation on the Antarctic scallop shell occurred later and subsequent ice growth was directed toward specific surface features (Fig. 4a, b and Supplementary Movie 3). Ice appears to accumulate only on the growth rings, leaving ice-free micro-ridges. As the experiment progressed, ice that had nucleated on the growth rings continued to grow vertically, thereby preventing further imaging of the ice-shell interface (Supplementary Movie 3). We observed no inter-ring bridging of ice and nucleated ice crystals grew preferentially upwards while enlarging in size. In contrast, neither control species showed any obvious signs of directed ice nucleation and appeared to frost uniformly over the surface (Fig. 4d, e). These results indicate that the Antarctic scallop may possess an ability to control ice nucleation and directed ice growth on its shell surfaces.Fig. 4: In-air frosting of scallop shells.The progression of ice accumulation was observed for shells placed atop a cold source in a temperature- and humidity-controlled chamber (20 °C, 60% relative humidity). a The Antarctic scallop preferentially directed ice nucleation and subsequent growth to the shell’s growth rings, termed directed frosting. b This patterned ice accumulation may also apply to ice growth in underwater environments, where it could reduce overall ice-shell contact area (c). d Directed frosting was not observed in control species (e.g., Bay scallop), where ice accreted in a patchy or uniform fashion over the entire surface (e). Likewise, such random but homogenously distributed nucleation-growth behaviors are likely to apply for ice growth in underwater environments, with continuous ice mats over the surface of the shell establishing higher overall contact adhesion force (f).Full size imageFor the Antarctic scallop, the mechanism of directed frosting occurs over two sequential steps: (1) initial condensation-frosting on growth rings, followed by (2) continuous frost growth. (1) The presence of sharp/rough edges (such as those on the growth rings), is known to enhance liquid nucleation by reducing the energy barrier32. Since more liquid water resides at the growth rings, here the nucleation of microscopic ice is more likely33. (2) Upon the formation of these microscopic ice domains as ice stripes (on growth rings), the vapor field around the ridges becomes compressed. The compressed vapor field generates locally steeper vapor gradients and thus stronger vapor fluxes towards the ice on the ridges (Fig. 4b). As a consequence, ice growth on the stripes is enhanced compared to the valleys. The vapor transport in the air during frosting is analogous to the heat transport underwater during icing. At the ridges, the latent heat generated is removed more quickly, facilitating accelerated growth34,35. Furthermore, since the vapor pressure of ice is lower than that of water36, the condensed water in the micro-valleys would be redirected to the ridges. This process would result in the micro-valleys being left comparatively free of ice, per Fig. 4a.A caveat remains, as the shell surface temperature during frosting assays (in-air) is significantly lower (c. −10 to −15 °C) than in nature. In its natural habitat, the lowest temperatures experienced by surfaces immersed in seawater (Fig. 4c, f) are rarely much below the equilibrium freezing point (~−1.9 °C), thus making heterogeneous ice nucleation on shells unlikely. However, the ability to direct ice growth may influence the probability of frazil ice adhering and anchoring strongly to the shell surface, thus facilitating easier removal through mechanical or passive environmental forces.We performed ice-adhesion measurements to test whether the apparent cryofouling avoidance of the Antarctic scallop’s shell in nature could arise from reduced adhesion forces between adhered ice and the shell’s surface. If adhesion is sufficiently low, ice could detach and float away under behavioral (movements, locomotion37) and/or environmentally induced forces (physical interactions, water currents, buoyancy of ice), or a combination of the above. This is particularly relevant once a sufficiently high ratio of ice volume to attachment surface area has been achieved. To provide complementary insight, both in-air and underwater ice-adhesion measurements were performed.The in-air ice-adhesion strength was determined30 by laterally shearing off drops of frozen freshwater from target scallop shells (Supplementary Movie 4). The recorded force curves show that ice adheres less strongly to the Antarctic scallop compared to the control species, the sea and bay scallops, as shown in Fig. 5a. For the Antarctic scallop, the in-air ice-adhesion strength was 145 ± 24 kPa (mean ± SE), ~2–3 times lower than both control species, with adhesion strengths of 335 ± 23 and 405 ± 27 kPa for the sea scallop and bay scallop respectively (Fig. 5a). We further observed that when the frozen drops sheared off the Antarctic scallop, the ice-shell fracture interface exhibited distinct growth ring-patterned fracture lines. In contrast, frozen drops detached from the control species appeared to have a uniform fracture interface (Supplementary Fig. 5 and Supplementary Movie 5). This observation could be explained by the incomplete contact adhesion of the frozen drops to the Antarctic scallop’s shell due to the spacing of small repetitive structural elements on the shell’s surface. As such, the overall area of ice-shell adhesion is reduced, thereby lowering the overall effective adhesion force.Fig. 5: Ice-adhesion measurements for Antarctic, Sea, and Bay scallops.a Displacement (lateral) of ice drops (10 µL) from the surface of shells in a humidity-controlled chamber. Shell temperature: −10 to −15 °C (thickness-dependent). Peak force was achieved immediately before the complete detachment of the drop from the surface. b Displacement (normal) of accreted ice grown in simulated seawater at its freezing point (35 g/L NaCl, c. −2 °C). Mean peak recorded force (dashed lines) ±1 SE (shaded areas) for three repetitions of each experiment are shown. Experimental details are available in the Supplementary Methods and Materials.Full size imageThe strength of ice adhesion (N/m2 or Pa) to shells underwater was determined using a custom-built apparatus. The apparatus determined the forces required for ice detachment when adhered ice was pulled perpendicular to and away from the shell surface. Underwater ice-adhesion experiments were performed in saltwater (35 g/L NaCl), simulating the seawater conditions in Antarctica. A cold source beneath a small section of the shell induced ice growth up to 6 mm in height above the shell surface, (Supplementary Movie 6), thereby encasing a perforated titanium plate (1 cm square, 4 × 2 mm-diameter holes) which was in turn connected to the force probe. The probe was then drawn upwards (normal to the shell, at 30 µm/s, Supplementary Movie 7). As for experiments in air, the recorded force curves in underwater experiments reveal that ice adheres weakly to the Antarctic scallop shell as compared to those of the two control species (Fig. 5b and Supplementary Movie 8). The Antarctic scallop experiences up to 3 times lower ice adhesion (37 ± 7 kPa, mean ± SE) than the sea scallop (112 ± 14 kPa) and more than 6 times lower adhesion than the bay scallop (243 ± 14 kPa) (Fig. 5b). At 37 ± 7 kPa, the Antarctic scallop’s shell shows underwater ice adhesion (normal to the surface) comparable to industrially-developed in-air anti-icing surfaces (1–50 kPa)4. However, if attachment forces in nature approach this value in a static environment (i.e., no water currents or scallop swimming behaviors), ≥3.7 cm3 of ice would need to be attached per mm2 of ice-shell contact area for the passive removal of ice under its own buoyant forces. Therefore, the “passive” removal of ice from Antarctic scallops must result from a combination of surface-to-environment factors. That is, the removal of ice crystals with small contact areas, such as platelet ice with its fine dendritic structure, may be facilitated by drag forces arising in natural water currents or induced by the rapid opening and closing of the scallop’s valves during swimming behaviors37. In these cases, adherent ice on the microstructures of the shell would likely experience the initiation of cracks that would subsequently facilitate ice removal given water movements or other physical disturbances.Whether the cryofouling-avoidant surfaces of the Antarctic scallop’s shell arose under evolutionary selection pressure remains unclear. Based on fossil records, the exclusively Antarctic scallop genus Adamussium first appeared in the early Oligocene, some 33 million years ago (mya)38,39. This time period roughly coincides with the onset of the major glaciation of Antarctica (c. 35 mya). The Antarctic scallop, Adamussium colbecki, appears to have arisen more recently, in the late Pliocene ( More

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