Survival, density, and abundance of common bottlenose dolphins in Barataria Bay (USA) following the Deepwater Horizon oil spill

To assess potential impacts of the Deepwater Horizon oil spill in April 2010, we conducted boat-based photo-identification surveys for common bottlenose dolphins Tursiops truncatus in Barataria Bay, Louisiana, USA (~230 km2, located 167 km WNW of the spill center). Crews logged 838 h of survey effort along pre-defined routes on 10 occasions between late June 2010 and early May 2014. We applied a previously unpublished spatial version of the robust design capture-recapture model to estimate survival and density. This model used photo locations to estimate density in the absence of study area boundaries and to separate mortality from permanent emigration. To estimate abundance, we applied density estimates to saltwater (salinity > ~8 ppt) areas of the bay where telemetry data suggested that dolphins reside. Annual dolphin survival varied between 0.80 and 0.85 (95% CIs varied from 0.77 to 0.90) over 3 yr following the Deepwater Horizon spill. In 2 non-oiled bays (in Florida and North Carolina), historic survival averages approximately 0.95. From June to November 2010, abundance increased from 1300 (95% CI ± ~130) to 3100 (95% CI ± ~400), then declined and remained between ~1600 and ~2400 individuals until spring 2013. In fall 2013 and spring 2014, abundance increased again to approximately 3100 individuals. Dolphin abundance prior to the spill was unknown, but we hypothesize that some dolphins moved out of the sampled area, probably northward into marshes, prior to initiation of our surveys in late June 2010, and later immigrated back into the sampled area.Publisher PDFPeer reviewe

Temporal and spatial aspects of bottlenose dolphin occurrence in coastal and estuarine waters near Charleston, South Carolina

The spatial and temporal occurrence of Atlantic bottlenose dolphins (Tursiops truncatus) in the coastal and estuarine waters near Charleston, SC were evaluated. Sighting and photographic data from photo-identification (ID), remote biopsy, capture-release and radio-tracking studies, conducted from 1994 through 2003, were analyzed in order to further delineate residence patterns of Charleston area bottlenose dolphins. Data from 250 photo-ID, 106 remote biopsy, 15 capture-release and 83 radio-tracking surveys were collected in the Stono River Estuary (n = 247), Charleston Harbor (n = 86), North Edisto River (n = 54), Intracoastal Waterway (n = 26) and the coastal waters north and south of Charleston Harbor (n = 41). Coverage for all survey types was spatially and temporally variable, and in the case of biopsy, capture-release and radio-tracking surveys, data analyzed in this report were collected incidental to other research. Eight-hundred and thirty-nine individuals were photographically identified during the study period. One-hundred and fifteen (13.7%) of the 839 photographically identified individuals were sighted between 11-40 times, evidence of consistent occurrence in the Charleston area (i.e., site fidelity). Adjusted sighting proportions (ASP), which reflect an individual’s sighting frequency in a subarea relative to other subareas after adjusting for survey effort, were analyzed in order to evaluate dolphin spatial occurrence. Forty-three percent (n = 139) of dolphins that qualified for ASP analyses exhibited a strong subarea affiliation while the remaining 57% (n = 187) showed no strong subarea preference. Group size data were derived from field estimates of 2,342 dolphin groups encountered in the five Charleston subareas. Group size appeared positively correlated with degree of “openness” of the body of water where dolphins were encountered; and for sightings along the coast, group size was larger during summer months. This study provides valuable information on the complex nature of bottlenose dolphin spatial and temporal occurrence near Charleston, SC. In addition, it helps us to better understand the stock structure of dolphins along the Atlantic seaboard

An expert-based system to predict population survival rate from health data

This work was supported by the Office of Naval Research Marine Mammal Biology Program [grant number N00014-17-1-2868].Timely detection and understanding of causes for population decline are essential for effective wildlife management and conservation. Assessing trends in population size has been the standard approach but we propose that monitoring population health could prove more effective. We collated data from seven bottlenose dolphin (Tursiops truncatus) populations in southeastern U.S. to develop the Veterinary Expert System for Outcome Prediction (VESOP), which estimates survival probability using a suite of health measures identified by experts as indices for inflammatory, metabolic, pulmonary, and neuroendocrine systems. VESOP was implemented using logistic regression within a Bayesian analysis framework, and parameters were fit using records from five of the sites that had a robust stranding network and frequent photographic identification (photo-ID) surveys to document definitive survival outcomes. We also conducted capture-mark-recapture (CMR) analyses of photo-ID data to obtain separate estimates of population survival rates for comparison with VESOP survival estimates. VESOP analyses found multiple measures of health, particularly markers of inflammation, were predictive of 1- and 2-year individual survival. The highest mortality risk one year following health assessment related to low alkaline phosphatase, with an odds ratio of 10.2 (95% CI 3.41-26.8), while 2-year mortality was most influenced by elevated globulin (9.60; 95% CI 3.88-22.4); both are markers of inflammation. The VESOP model predicted population-level survival rates that correlated with estimated survival rates from CMR analyses for the same populations (1-year Pearson's r = 0.99; p = 1.52e-05, 2-year r = 0.94; p = 0.001). While our proposed approach will not detect acute mortality threats that are largely independent of animal health, such as harmful algal blooms, it is applicable for detecting chronic health conditions that increase mortality risk. Random sampling of the population is important and advancement in remote sampling methods could facilitate more random selection of subjects, obtainment of larger sample sizes, and extension of the approach to other wildlife species.Publisher PDFPeer reviewe

Modeling population effects of the Deepwater Horizon oil spill on a long-lived species

This research was enabled partly by a grant from The Gulf of Mexico Research Initiative (GOMRI).The 2010 Deepwater Horizon (DWH) oil spill exposed common bottlenose dolphins (Tursiops truncatus) in Barataria Bay, Louisiana to heavy oiling that caused increased mortality and chronic disease and impaired reproduction in surviving dolphins. We conducted photographic surveys and veterinary assessments in the decade following the spill. We assigned a prognostic score (good, fair, guarded, poor, or grave) for each dolphin to provide a single integrated indicator of overall health, and we examined temporal trends in prognostic scores. We used expert elicitation to quantify the implications of trends for the proportion of the dolphins that would recover within their lifetime. We integrated expert elicitation, along with other new information, in a population dynamics model to predict the effects of observed health trends on demography. We compared the resulting population trajectory with that predicted under baseline (no spill) conditions. Disease conditions persisted and have recently worsened in dolphins that were presumably exposed to DWH oil: 78% of those assessed in 2018 had a guarded, poor, or grave prognosis. Dolphins born after the spill were in better health. We estimated that the population declined by 45% (95% CI 14–74) relative to baseline and will take 35 years (95% CI 18–67) to recover to 95% of baseline numbers. The sum of annual differences between baseline and injured population sizes (i.e., the lost cetacean years) was 30,993 (95% CI 6607–94,148). The population is currently at a minimum point in its recovery trajectory and is vulnerable to emerging threats, including planned ecosystem restoration efforts that are likely to be detrimental to the dolphins’ survival. Our modeling framework demonstrates an approach for integrating different sources and types of data, highlights the utility of expert elicitation for indeterminable input parameters, and emphasizes the importance of considering and monitoring long-term health of long-lived species subject to environmental disasters. Article impact statement: Oil spills can have long-term consequences for the health of long-lived species; thus, effective restoration and monitoring are needed.Publisher PDFPeer reviewe

Skin Lesions on Common Bottlenose Dolphins (Tursiops truncatus) from Three Sites in the Northwest Atlantic, USA

Skin disease occurs frequently in many cetacean species across the globe; methods to categorize lesions have relied on photo-identification (photo-id), stranding, and by-catch data. The current study used photo-id data from four sampling months during 2009 to estimate skin lesion prevalence and type occurring on bottlenose dolphins (Tursiops truncatus) from three sites along the southeast United States coast [Sarasota Bay, FL (SSB); near Brunswick and Sapelo Island, GA (BSG); and near Charleston, SC (CHS)]. The prevalence of lesions was highest among BSG dolphins (P = 0.587) and lowest in SSB (P = 0.380), and the overall prevalence was significantly different among all sites (p<0.0167). Logistic regression modeling revealed a significant reduction in the odds of lesion occurrence for increasing water temperatures (OR = 0.92; 95%CI:0.906–0.938) and a significantly increased odds of lesion occurrence for BSG dolphins (OR = 1.39; 95%CI:1.203–1.614). Approximately one-third of the lesioned dolphins from each site presented with multiple types, and population differences in lesion type occurrence were observed (p<0.05). Lesions on stranded dolphins were sampled to determine the etiology of different lesion types, which included three visually distinct samples positive for herpesvirus. Although generally considered non-fatal, skin disease may be indicative of animal health or exposure to anthropogenic or environmental threats, and photo-id data provide an efficient and cost-effective approach to document the occurrence of skin lesions in free-ranging populations

Cisco Systems

Pragmatic General Multicast (PGM) is a reliable multicast transport protocol that runs over a best effort datagram service, such as IP multicast. PGM obtains scalability via hierarchy, forward error correction, NAK (negative acknowledgement) elimination, and NAK suppression. It employs a novel polling scheme for NAK delay tuning to facilitate scaling up and down. This paper describes the architecture of PGM and discusses performance and security issues. We show that PGM has supports asymmetric networks, achieves high network utilization, and is capable of high-speed (&gt;100 Mbps) operation. PGM is currently an IETF experimental RFC that has been implemented in both commercial and academic settings.