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Figure 4 in Decapod abundance and species richness in the bycatch of Xiphopenaeus kroyeri (Heller, 1862) fishery, Santa Catarina, southern Brazil

Figure 4. Temperature variation along the seasons of the year. Samples were taken from July 2010 through June 2011, in the adjacent area from the Babitonga Bay, Santa Catarina State, Brazil.

Figure 3 in Decapod abundance and species richness in the bycatch of Xiphopenaeus kroyeri (Heller, 1862) fishery, Santa Catarina, southern Brazil

Figure 3. Quotient between the carcino-bycatch and Xiphopenaeus kroyeri abundance. Samples were taken from July 2010 through June 2011 in the adjacent area from the Babitonga Bay, Santa Catarina State, Brazil. Black circles indicate deviations from a 1:1 expected proportion (Binomial test, p<0.05).

Figure 5 in Decapod abundance and species richness in the bycatch of Xiphopenaeus kroyeri (Heller, 1862) fishery, Santa Catarina, southern Brazil

Figure 5. Biplot of the axes from the Redundancy Analysis (RDA). Spatial variation of the biological and environmental variables from July 2010 through June 2011 in the adjacent area from Babitonga Bay, SC. Arrows indicate the strength of the relation between the axes and the environmental factors (O.M= Organic matter content; Phi=Substrate granulometry).

Figure 2 in Decapod abundance and species richness in the bycatch of Xiphopenaeus kroyeri (Heller, 1862) fishery, Santa Catarina, southern Brazil

Figure 2. Relative composition (%) of individuals comprised in the carcino-bycatch, sorted by different taxonomic categories, from the artisanal Xiphopenaeus kroyeri fishery. Samples were taken from July 2010 through June 2011 in the adjacent area from the Babitonga Bay, Santa Catarina State, Brazil.

FIG. 6 in From folkloric belief to fishery bycatch: contrasting cryptozoological and euhemeristic interpretations of Australian sea serpents

FIG. 6. — String of A, fishing-net floats, which, if nonlethally entangled around an actively swimming animal and bobbing up and down on the water surface might be misinterpreted as the long tail of a presumed sea serpent, especially if the UMO was also pulling a "mane" of intertwined fishing-net and accumulations of seaweed or other natural or anthropogenic debris; B, cork pieces used to buoy a gillnet;C, wooden casks used to suspend a purse-seine. Photo credits: R. France (taken at Battle Harbour National Historic District, Battle Harbour, Newfoundland and Labrador [A]; Cape Ann Museum, Massachusetts [B]); nineteenth-century illustration reproduced from France 2019a [C].

FIG. 3 in From folkloric belief to fishery bycatch: contrasting cryptozoological and euhemeristic interpretations of Australian sea serpents

FIG. 3. — Illustrations of the many-humped, string-of-buoys Gloucester Sea Serpent observed by hundreds over a period of weeks in Massachusetts in the nineteenth century. Further details of these sightings as well as other illustrations are presented in France (2019a, b).

FIG. 2 in From folkloric belief to fishery bycatch: contrasting cryptozoological and euhemeristic interpretations of Australian sea serpents

FIG. 2. — Unidentified marine objects seen in waters around Australia in A, 1900 (anecdote 19, Wide World Magazine); B, 1913 (anecdote 28, Sunday Times); C, 1939 (anecdote 67, Cryptozoology); D, 1981 (Papua New Guinea waters; Smith 2020). Anecdote numbers correspond to those from Smith (2020). The illustration of the New Guinea UMO depicts the classic manyhumped, string-of-buoys "sea serpent" seen repeatedly around the world, which could, as has been suggested for other regions, be an actual string of entangled buoys from a fishing net. The 1913 Australian UMO was observed to sport a beard and dorsal crest, both traits which have been suggested to indicate presence of entangled fishing gear for other UMOs. Clearly the coils or loops elevated above the surface of the water that were observed for the 1900 and 1939 UMOs are biologically impossible and consequently represent a train of anthropogenic material.

FIG. 4 in From folkloric belief to fishery bycatch: contrasting cryptozoological and euhemeristic interpretations of Australian sea serpents

FIG. 4. — Pre-plastic maritime equipment forming the backbone of the long tails of putative sea serpents.A-F, early to mid twentieth-century fishing ropes and nets constructed of natural fibre (hemp); G, H, remarkably preserved hemp ropes retrieved from a 400 year-old sunken Basque whaling ship. Photo credits: R. France (taken at the Fisheries Museum of the Atlantic,Lunenburg, Nova Scotia [A, B]; the Maritime Museum of the Atlantic, Halifax, Nova Scotia [C, D]; Battle Harbour National Historic District, Battle Harbour, Newfoundland and Labrador [E, F] [see France 2019a for other, similar photos as well as nineteenth-century illustrations of the same]); Red Bay National Historic Site & UNESCO World Heritage Site, Red Bay, Newfoundland and Labrador (G, H).

FIG. 5 in From folkloric belief to fishery bycatch: contrasting cryptozoological and euhemeristic interpretations of Australian sea serpents

FIG. 5. — Pre-plastic maritime material forming the humps of the long tails of putative sea serpents. A, B, blown-glass balls used as floats from the nineteenth-century; C, D, nineteenth-century cork floats; E, F, wooden casks of the type often used as floats on fishing nets. Photos credits: R. France (taken at the Fisheries Museum of the Atlantic, Lunenburg, Nova Scotia [A, D]; the Battle Harbour National Historic District, Battle Harbour, Newfoundland and Labrador [E, F]); the Mystic Seaport Museum Archive and Collections, Mystic, Connecticut (B, C).

FIG. 1 in From folkloric belief to fishery bycatch: contrasting cryptozoological and euhemeristic interpretations of Australian sea serpents

FIG. 1. — Unidentified marine objects (UMOs) representing the "many-humped" or "string-of-buoys" typology of "sea serpents" observed in A, Géographe Bay, Australia, in 1879; B, the Great Barrier Reef, Australia, in 1934. Further details of these sightings and illustrations of other UMOs from the nearby Western Pacific are presented in France (2020a).

opencc-zeroDec 2021View details →

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Behavioral "bycatch" from camera trap surveys yields insights on prey responses to human-mediated predation risk

<p>Human disturbance directly affects animal populations but indirect effects of disturbance on species behaviors are less well understood. Camera traps provide an opportunity to investigate variation in animal behaviors across gradients of disturbance. We used camera trap data to test predictions about predator-sensitive behavior in three ungulate species (caribou Rangifer tarandus; white-tailed deer, Odocoileus virginianus; moose, Alces alces) across two boreal forest landscapes varying in disturbance. We quantified behavior as the number of camera trap photos per detection event and tested its relationship to predation risk between a landscape with greater industrial disturbance and predator abundance (Algar) and a "control" landscape with lower human and predator activity (Richardson). We also assessed the influence of predation risk and habitat on behavior across camera sites within the disturbed Algar landscape. We predicted that animals in areas with greater predation risk (more wolf activity, less cover) would travel faster and generate fewer photos per event, while animals in areas with less predation risk would linger (rest, forage), generating more photos per event. Consistent with predictions, caribou and moose had more photos per event in the landscape where predation risk was reduced. Within the disturbed landscape, no prey species showed a significant behavioral response to wolf activity, but the number of photos per event decreased for white-tailed deer with increasing line of sight (m) along seismic lines (i.e. decreasing visual cover), consistent with a predator-sensitive response. The presence of juveniles was associated with shorter behavioral events for caribou and moose, suggesting greater predator sensitivity for females with calves. Only moose demonstrated a positive association with vegetation productivity (NDVI), suggesting that for other species influences of forage availability were generally weaker than those from predation risk. Behavioral insights can be gleaned from camera trap surveys and provide information about animal responses to predation risk and the indirect impacts of human disturbances.</p>

opencc-by-4.0Mar 2023View details →

Fig. 2 in Vulnerability of elasmobranchs caught as bycatch in the grouper longline fishery in the Gulf of Gabès, Tunisia Abstract

Fig. 2: Productivity, susceptibility and vulnerability scores of elasmobranch species caught by the grouper demersal longline fishery in the Gulf of Gabès. Numbers correspond to elasmobranch species as listed in Table 4. The colors represent the relative vulnerability: the green areas being the lowest, the yellow ones being the moderate and the red areas being the highest.

opencc-by-4.0Mar 2023View details →

Fig. 1 in Vulnerability of elasmobranchs caught as bycatch in the grouper longline fishery in the Gulf of Gabès, Tunisia Abstract

Fig. 1: Map showing the location of the grouper demersal longline sets surveyed during 2016 () and 2017 () in the Gulf of Gabès.

Figure 2 in Using deep-learning for automatic identification of images of marine benthic macro-invertebrate bycatch: a proof of concept

Figure 2. – Three images of organisms obtained by cropping images of lots; from left to right: Chalinidae (Porifera), Polyclinidae (Chordata), Hormatidae (Cnidaria).

Figure 3 in Using deep-learning for automatic identification of images of marine benthic macro-invertebrate bycatch: a proof of concept

Figure 3. – Image of a batch of macro-invertebrate bycatch organisms from Kerguelen Exclusive Economical Zone (Poker 4 survey, 2017), including corals, a crinoïd, an ophiurid, a sea urchin and a brachiopoda; organisms are incomplete and have been quickly spread out over a small plate to take the picture.

Figure 6 in Using deep-learning for automatic identification of images of marine benthic macro-invertebrate bycatch: a proof of concept

Figure 6. – Example of detection and classification obtained with an image including an Ophiuroid, a piece of coral and a sea star with network 2; red squares and annotations have been provided by the computer with no human action.

Figure 5 in Using deep-learning for automatic identification of images of marine benthic macro-invertebrate bycatch: a proof of concept

Figure 5. – Example of detection and classification obtained with an image including Ascidians and a sea star with network 2; red squares and annotations have been provided by the computer with no human action.

opencc-by-4.0Nov 2019View details →

Fig. 1 in The effect of pingers on cetaceans bycatch and target catch in the turbot gillnets in Bulgarian Black Sea

Fig. 1. Ph.phocoena bycatch rate (individuals per km of net and per soak time (days) by years in the control nets.