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Fig. 2 in A new dracunculus species (Nematoda: Dracunculoidea) in neotropical otters (Lontra longicaudis) from Argentina: morphological and molecular characterization

Fig. 2. Neotropical otters (Lontra longicaudis) dead and Dracunculus parasites in subcutaneous tissues.

Fig. 2 in Molecular and morphological confirmation of Profilicollis altmani as the cause of acanthocephalan peritonitis in California sea otters (Enhydra lutris nereis)

Fig. 2. Maximum likelihood phylogeny generated from the concatenation of sequences of loci B, C, D. Species analyzed include: Adineta vaga, Profilicollis altmani (sample haplotype 1 and GenBank (gb)), Profilicollis botulus/Profilicollis major (sample haplotypes 1 and 2), Polymorphus minutus, and Corynosoma enhydri. Branch lengths are scaled to phylogenetic distance and nodes are labeled with bootstrap support values (n = 100 replicates).

Fig. 1 in Molecular and morphological confirmation of Profilicollis altmani as the cause of acanthocephalan peritonitis in California sea otters (Enhydra lutris nereis)

Fig. 1. Four acanthocephalan morphotypes and their prior identities observed in necropsied sea otters. (A) Corynosoma enhydri adult, (B) Profilicollis altmani, (C) Profilicollis kenti, (D) Profilicollis major. Modified from Hennessy (1972).

Fig. 3 in Molecular and morphological confirmation of Profilicollis altmani as the cause of acanthocephalan peritonitis in California sea otters (Enhydra lutris nereis)

Fig. 3. Maximum likelihood phylogeny generated from the concatenation of sequences of loci B and D. Species analyzed include: Adineta vaga, Profilicollis botulus/Profilicollis major (sample haplotypes 1 and 2 and GenBank (gb)), Polymorphus obtusus, Polymorphus minutus, Polymorphus trochus, Corynosoma enhydri, Polymorphus brevis, Profilicollis bullocki, and Profilicollis altmani (sample haplotype 1 and GenBank). Branch lengths are scaled to phylogenetic distance and nodes are labeled with bootstrap support values (n = 100 replicates).

Fig. 4 in Otterly diverse - A high diversity of Dracunculus species (Spirurida: Dracunculoidea) in North American river otters (Lontra canadensis)

Fig. 4. Large clusters of Dracunculus insignis in paws (A) and joint (B) of North American river otter (Lontra canadensis) from Missouri, USA.

Fig. 3 in Otterly diverse - A high diversity of Dracunculus species (Spirurida: Dracunculoidea) in North American river otters (Lontra canadensis)

Fig. 3. Surgical removal of a Clade 2 Dracunculus sp. (FL15-33934) from a North American river otter (Lontra canadensis) from Florida, USA.

Fig. 1 in Otterly diverse - A high diversity of Dracunculus species (Spirurida: Dracunculoidea) in North American river otters (Lontra canadensis)

Fig. 1. Distribution of Dracunculus spp. in North American river otters (Lontra canadensis) in North America. Species identifications are based on molecular identification or male morphology.

Fig. 2 in Otterly diverse - A high diversity of Dracunculus species (Spirurida: Dracunculoidea) in North American river otters (Lontra canadensis)

Fig. 2. Posterior end of a male worm of a Clade 1 Dracunculus sp. (NC-otter8C) from a North American river otter (Lontra canadensis) from North Carolina showing the paired spicules (A), gubernaculum (B, C), and the bulbous posterior end of the tail (D).

Fig. 5 in Otterly diverse - A high diversity of Dracunculus species (Spirurida: Dracunculoidea) in North American river otters (Lontra canadensis)

Fig. 5. Genetic relationships of Dracunculus spp. from North American river otters (Lontra canadensis) compared with other Dracunculus spp. based on partial cytochrome c oxidase subunit 1 gene sequences. The text in bold in the figure represents specimens analyzed in this study. Sequences with an asterisk (*) were derived from river otters (current and previous studies).

opencc-by-4.0Sep 2016View details →

Fig. 2 in Diet of the smooth-coated otter Lutrogale perspicillata (Geoffroy, 1826) at natural and modified sites in Singapore

Fig. 2. Linear fit of vertebrae length and total length of cichlids caught in Serangoon Reservoir (SR).

opencc-by-4.0Sep 2016View details →

Fig. 3 in Diet of the smooth-coated otter Lutrogale perspicillata (Geoffroy, 1826) at natural and modified sites in Singapore

Fig. 3. Frequency distribution of the size classes of fish vertebrae represented in spraints in Serangoon Reservoir (SR) and Sungei Buloh Wetland Reserve (SBWR).

Fig. 4 in Spatial genetic structure in the vulnerable smooth-coated otter (Lutrogale perspicillata, Mustelidae): towards an adaptive conservation management of the species

Fig. 4. Multidimensional Scaling (MDS) plot (stress: 0.0045) performed using average pairwise TN93 (Tamura & Nei, 1993) distances among investigated Lutrogale perspicillata groups created according to the country of origin of samples (modern + museum DNA and GenBank entries).

Fig. 3. A in Spatial genetic structure in the vulnerable smooth-coated otter (Lutrogale perspicillata, Mustelidae): towards an adaptive conservation management of the species

Fig. 3. A, Lutrogale perspicillata network computed using haplotypes (h) from the 305 bp-long sequence alignment (modern + museum DNA and GenBank entries). A scale to infer the number of sequences for each pie (i.e., haplotype) was provided together with a length bar to compute the number of mutational changes. The colour of each country and the number of each haplotype are indicated. See Table S1 for more details. B, Mismatch Distributions (MD) of the mtDNA pairwise differences (dotted: observed; line: expected) calculated for South East Asia haplogroup (Fig. 3A). Estimates of FS and R2 statistics (with related P values), r (raggedness index) and the outcome of SSD and SSD* test under a model (H0) of sudden demographic and spatial population expansion, respectively, are provided.

Fig. 2 in Spatial genetic structure in the vulnerable smooth-coated otter (Lutrogale perspicillata, Mustelidae): towards an adaptive conservation management of the species

Fig. 2. Photos of MNHN-ZM-MO-2001-350, L. p. perspicillata holotype resident in the mammal collection of the National Museum of Natural History of Paris, France. A, right side, lateral view (bar length = 20 cm); B, left forelimb, lateral view; C, basement, in French "Lutra perspicillata = Lutra leptonix Horsf., loutre de Java par m Diard, mai 1821, la tête est au lab d'anatomie", which can be translated into and interpreted as: "Lutra perspicillata = Lutra leptonix (Horsfield, 1824), Java otter from M. Diard, May 1821, skull is in the lab of anatomy" (see also Material and Methods). Photos courtesy and copyright: © MNHN - RECOLNAT - Laura Flamme - 2014.

Fig. 1 in Spatial genetic structure in the vulnerable smooth-coated otter (Lutrogale perspicillata, Mustelidae): towards an adaptive conservation management of the species

Fig. 1. Lutrogale perspicillata distribution (in yellow; see insets for Iraq and Pakistan) including sampling localities of modern (white circles) and museum (green squares) individuals. As far as the latter are concerned, we reported only sites for which samples were successfully investigated (see Table S1 for the entire sample size of this study; symbol "?" stands for unknown locality). The white stars indicate, in Iraq, the locality (TaqTaq, Kurdistan) where the sample of Omer et al. (2012) was collected, in Cambodia/Thailand and Malaysia, the country/ies of origin of EF472348 and KY117557 GenBank sequence, respectively. In Iraq, Pakistan, and supposedly Java, Indonesia, the green squares indicate localities (when known) of L. p. maxwelli, L. p. sindica, and L. p. perspicillata museum holotypes, respectively. Finally, Naga Hills at the border between Myanmar and India as well as Bahoo-Kalat River Basin between Iran and Pakistan are indicated (see text for more details). The species' geographic range was adapted from IUCN (International Union for Conservation of Nature) 2015. Lutrogale perspicillata. The IUCN Red List of Threatened Species 2019-3 was modified using CorelDraw!12 (2003). Digital images (insets) were obtained from Google Earth 7.1.5.1557 (2015 Google Inc.) and Google Earth map data (Data SIO, NOAA, U.S. Navy, NGA, GEBCO - Image Landsat). Please note that thick dotted lines mark out new borders for L. p. sindica and L. p. perspicillata subspecies as established in this study (see text for more details).

opencc-zeroMar 2023View details →

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Outputs of current speed and sea otter abundance models in Glacier Bay, Alaska

Sea otters are apex predators that can exert considerable influence over the nearshore communities they occupy. Since facing near extinction in the early 1900s, sea otters are making a remarkable recovery in Southeast Alaska, particularly in Glacier Bay, the largest protected tidewater glacier fjord in the world. The expansion of sea otters across Glacier Bay offers both a challenge to monitoring and stewardship and an unprecedented opportunity to study the top-down effect of a novel apex predator across a diverse and productive ecosystem. Our goal was to integrate monitoring data across trophic levels, space, and time to quantify and map the predator-prey interaction between sea otters and butter clams (Saxidomus gigantea), one of the dominant large bivalves in Glacier Bay and a favored prey of sea otters. To do so, we developed a modeling framework to account for both bottom-up and top-down drivers of butter clam abundance and dynamics. For the bottom-up driver, we used the root-mean-square current speed (m/s) predicted by a tidal circulation model of Glacier Bay developed by Drew et al. (2013). For top-down sea otter dynamics, we used the posterior mean sea otter abundance estimates from Lu et al. (2019). This repository contains the current speed raster (100m x 100m resolution) produced by Drew et al. (2013) and the files and model output from Lu et al. (2019) necessary to generate a time series of rasters (400m x 400m resolution raster brick with 26 layers for the years 1993-2018) of estimated posterior mean sea otter abundance. These data layers are used in Leach et al. (2023) to model butter clam dynamics at sampling sites across Glacier Bay.

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Otterly delicious: Spatiotemporal variation in the diet of a recovering population of Eurasian otters (Lutra lutra) revealed through DNA metabarcoding and morphological analysis of prey remains

Eurasian otters are apex predators of freshwater ecosystems and a recovering species across much of their European range; investigating the dietary variation of this predator over time and space therefore provides opportunities to identify changes in freshwater trophic interactions and factors influencing the conservation of otter populations. Here we sampled faeces from 300 dead otters across England and Wales between 2007 and 2016, conducting both morphological analysis of prey remains and dietary DNA metabarcoding. Comparison of these methods showed that greater taxonomic resolution and breadth could be achieved using DNA metabarcoding but combining data from both methodologies gave the most comprehensive dietary description. All otter demographics exploited a broad range of taxa and variation likely reflected changes in prey distributions and availability across the landscape. This study provides novel insights into the trophic generalism and adaptability of otters across Britain, which is likely to have aided their recent population recovery, and may increase their resilience to future environmental changes.

opencc-zeroApr 2023View details →

figure 1 in Spatial genetic structure in the Eurasian otter (Lutra lutra) meta-population from its core range in Italy

figure 1 The area surveyed for collection of otter samples (40° 40' N, 39° 37' N). Red spots indicate the location of the collected samples. The blue lines highlight the main rivers (order 1) and their tributaries (order 2, 3 and 4 according to waterway hierarchy). The continuous red lines represent regional boundaries. In the inset, the current otter distribution (inferred from Balestrieri et al., 2016, modified) is reported in orange and the study area is defined by the black bold square.

figure 4 in Spatial genetic structure in the Eurasian otter (Lutra lutra) meta-population from its core range in Italy

figure 4 Principal Component Analysis (pca) performed on microsatellite genotypes (dots). Circles show the well-defined spatial groups. A) pca according to the belonging of genotypes to the six river basins: the Cilento basin (green dots); the Agri basin (pink dots); the Sinni basin (blue dots); the Lao basin (red dots); the Basento basin (orange dots); the Abatemarco basin (violet dots); black dots indicate the samples outside of the main river basins. Dashed line indicates geographically contiguous but genetically different genotypes. B) pca according to clusters inferred by STRUCTURE: genotypes assigned unambiguously to K2 (green dots), to K3 (yellow dots), to K5 (violet dots). Grey dots represent samples with mixed genotypes assignable to K1 and K4.

figure 3 in Spatial genetic structure in the Eurasian otter (Lutra lutra) meta-population from its core range in Italy

figure 3 Genetic structure and distribution of the Italian otter genotypes in the study area. A) Estimated population structure based on the analysis of 11 microsatellite loci according to STRUCTURE (K = 5). Each bar represents a sample analysed. B) Geographic visualisation of genotypes in the study area performed using QGIS 3.4.1 software with base layers acquired from http://www.pnc.miniambiente. it/. Each circle represents a sample analysed. The colours indicate the percentage of assignment of an individual to each cluster: in blue, K1; in green, K2; in orange, K3; in red, K4; in violet, K5. The bold blue lines highlight the main rivers, while the tiny blue lines show all other waterways.