Miscellaneous lesions of the head, skull, teeth, trunk, appendages, skin and genital tract were observed in 120 of 930 long-beaked common dolphins Delphinus capensis taken in fisheries off Peru between 1985 and 2000. Seven subsamples were defined according to the varying field sampling protocols. Forty-two dolphins showed at least 2 types of injuries or diseases affecting 1 or more organs. The majority (5 of 7) of traumas encountered were diagnosed as caused by violent, fisheriesrelated interactions, and the skin in 20.4% of specimens (n = 54) showed healed scars from such interactions. Prevalences of malformations and traumas of crania (n = 103) were 2.9 and 1.9%, respectively. Lytic cranial lesions were present in 31.1% of dolphins (n = 103) and accounted for 84.2% of all bone injuries. Skull damage diagnostic for Crassicauda sp. infestation was encountered in 26.5% of dolphins (n = 98) and did not differ among sex and age classes. Crassicauda sp. and tooth infections were responsible for, respectively, 78.8 and 6.1% of the lytic lesions. Adult dolphins showed a high prevalence of worn and broken teeth (35%, n = 20) as well as damaged alveoli (20%, n = 70). Prevalence of 'paired teeth', a congenital condition, was 9.4% (n = 32). Lesions of the head, body and appendages were present in 10 dolphins and included traumas, deformations (e.g. scoliokyphosis and brachygnathia) and chronic mastitis. Ovarian cysts suggestive of follicular cysts were observed in 1 of 24 females. Chronic orchitis affected 1 of 78 males. Of 12 dolphins 2 had vesicular lesions of the penis. Prevalence of cutaneous lesions, abnormalities and scars ranged between 1.8% (n = 56) and 48.2% (n = 27).

Species distribution models that predict species occurrence or density by quantifying relationships with environmental variables are used for a variety of scientific investigations and management applications. For endangered species, such as large whales, models help to understand the ecological factors influencing variability in distributions and to assess potential risk from shipping, fishing, and other human activities. Systematic surveys record species presence and absence, as well as the associated search effort, but are very expensive. Presence-only data consisting only of sightings can increase sample size, but may be biased in both geographical and niche space. We built generalized additive models (GAMs) using presence-absence sightings data and maximum entropy models (Maxent) using the same presence-absence sightings data, and also using presence-only sightings data, for four large whale species in the eastern tropical Pacific Ocean: humpback (Megaptera novaeangliae), blue (Balaenoptera musculus), Bryde's (Balaenoptera edeni), and sperm whales (Physeter macrocephalus). Environmental variables were surface temperature, surface salinity, thermocline depth, stratification index, and seafloor depth. We compared predicted distributions from each of the two model types. Maxent and GAM model predictions based on systematic survey data are very similar, when Maxent absences are selected from the survey trackline data. However, we show that spatial bias in presence-only Maxent predictions can be caused by using pseudo-absences instead of observed absences and by the sampling biases of both opportunistic data and stratified systematic survey data with uneven coverage between strata. Predictions of uncommon large whale distributions from Maxent or other presence-only techniques may be useful for science or management, but only if spatial bias in the observations is addressed in the derivation and interpretation of model predictions.

No abstract

No abstract

No abstract