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

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

Generation, Annotation and Analysis of First Large-Scale Expressed Sequence Tags from Developing Fiber of Gossypium barbadense L

BACKGROUND: Cotton fiber is the world's leading natural fiber used in the manufacture of textiles. Gossypium is also the model plant in the study of polyploidization, evolution, cell elongation, cell wall development, and cellulose biosynthesis. G. barbadense L. is an ideal candidate for providing new genetic variations useful to improve fiber quality for its superior properties. However, little is known about fiber development mechanisms of G. barbadense and only a few molecular resources are available in GenBank. METHODOLOGY AND PRINCIPAL FINDINGS: In total, 10,979 high-quality expressed sequence tags (ESTs) were generated from a normalized fiber cDNA library of G. barbadense. The ESTs were clustered and assembled into 5852 unigenes, consisting of 1492 contigs and 4360 singletons. The blastx result showed 2165 unigenes with significant similarity to known genes and 2687 unigenes with significant similarity to genes of predicted proteins. Functional classification revealed that unigenes were abundant in the functions of binding, catalytic activity, and metabolic pathways of carbohydrate, amino acid, energy, and lipids. The function motif/domain-related cytoskeleton and redox homeostasis were enriched. Among the 5852 unigenes, 282 and 736 unigenes were identified as potential cell wall biosynthesis and transcription factors, respectively. Furthermore, the relationships among cotton species or between cotton and other model plant systems were analyzed. Some putative species-specific unigenes of G. barbadense were highlighted. CONCLUSIONS/SIGNIFICANCE: The ESTs generated in this study are from the first large-scale EST project for G. barbadense and significantly enhance the number of G. barbadense ESTs in public databases. This knowledge will contribute to cotton improvements by studying fiber development mechanisms of G. barbadense, establishing a breeding program using marker-assisted selection, and discovering candidate genes related to important agronomic traits of cotton through oligonucleotide array. Our work will also provide important resources for comparative genomics, polyploidization, and genome evolution among Gossypium species

A role for the root cap in root branching revealed by the non-auxin probe naxillin

The acquisition of water and nutrients by plant roots is a fundamental aspect of agriculture and strongly depends on root architecture. Root branching and expansion of the root system is achieved through the development of lateral roots and is to a large extent controlled by the plant hormone auxin. However, the pleiotropic effects of auxin or auxin-like molecules on root systems complicate the study of lateral root development. Here we describe a small-molecule screen in Arabidopsis thaliana that identified naxillin as what is to our knowledge the first non-auxin-like molecule that promotes root branching. By using naxillin as a chemical tool, we identified a new function for root cap-specific conversion of the auxin precursor indole-3-butyric acid into the active auxin indole-3-acetic acid and uncovered the involvement of the root cap in root branching. Delivery of an auxin precursor in peripheral tissues such as the root cap might represent an important mechanism shaping root architecture