cull-data

Kill data from hunting operations (n = 9; August 2008−2011) that occurred at approximately 6-month intervals over the first 18 months of the study (3 operations), then at 3-month intervals (6 operations)

ground-disturbance-rates

Rates of feral pig ground disturbance from the Waitakere Ranges, Auckland, New Zealand. Taken from yearly monitoring of disturbance transects from 2008-201

transect-disturbance

The percentage of ground disturbed by feral pigs along each (arbitrarily named A-W) 200m ground disturbance monitoring transect.Transects were monitored four times (November 2008, September 2009, December 2010 and August 2011

Location of the Waitakere Ranges study site on the North Island of New Zealand.

<p>The study site was divided into three hunting blocks for the purposes of organising the pig control programme. The Landsat image is sourced from the U.S. Geological Survey’s EarthExplorer <a href="http://earthexplorer.usgs.gov/" target="_blank">http://earthexplorer.usgs.gov/</a> and is freely available public domain data. The outline of New Zealand is sourced from the LINZ Data Service <a href="https://data.linz.govt.nz/" target="_blank">https://data.linz.govt.nz/</a> and is licensed by LINZ for re-use under the Creative Commons Attribution 3.0 New Zealand licence.</p

Estimate of the initial density of pigs within the Waitakere ranges based on a catch-effort methodology.

<p>The catch-effort population estimate and uncertainty was used to define a log-normal distribution to describe the likely range of possible initial population density. Estimates for the first hunting session have been excluded from the analyses, as they are likely to violate the assumption of constant catchability.</p

Changes in percentage ground area disturbed by wild pigs on 23 monitoring transects.

<p>Transect were (arbitrarily named A−W) at ground disturbance monitoring sessions in (A) 2008, (B) 2009, (C) 2010, and (D) 2011.</p

The relationship ground disturbance and recovery rates and pig density.

<p>(A) Annual rate of ground disturbance (<i>m</i>). (B) Annual rate of ground disturbance recovery (<i>n</i>). Pig density was a proportion of the estimated carrying capacity (<i>N</i>/<i>K</i>) for data combined across all three hunting blocks.</p

The relationship between hunting efficiency and density of pigs for each hunting session and hunting block.

<p>The relationship between hunting efficiency and density of pigs for each hunting session and hunting block.</p

Predictions of pig density, ground disturbance, and accumulated cost for five different hunting regimes.

<p>The values for pig density and ground disturbance are the mean and standard deviation derived from 1000 model runs.</p

Risk factors for obesity in adult survivors of childhood cancer: A report from the childhood cancer survivor study

Purpose: Many Childhood Cancer Survivor Study (CCSS) participants are at increased risk for obesity. The etiology of their obesity is likely multifactorial but not well understood. Patients and Methods: We evaluated the potential contribution of demographic, lifestyle, treatment, and intrapersonal factors and self-reported pharmaceutical use to obesity (body mass index ≥ 30 kg/m 2) among 9,284 adult (\u3e 18 years of age) CCSS participants. Independent predictors were identified using multivariable regression models. Interrelationships were determined using structural equation modeling (SEM). Results: Independent risk factors for obesity included cancer diagnosed at 5 to 9 years of age (relative risk [RR], 1.12; 95% CI, 1.01 to 1.24; P = .03), abnormal Short Form-36 physical function (RR, 1.19; 95% CI, 1.06 to 1.33; P \u3c .001), hypothalamic/pituitary radiation doses of 20 to 30 Gy (RR, 1.17; 95% CI, 1.05 to 1.30; P = .01), and paroxetine use (RR, 1.29; 95% CI, 1.08 to 1.54; P = .01). Meeting US Centers for Disease Control and Prevention guidelines for vigorous physical activity (RR, 0.90; 95% CI, 0.82 to 0.97; P = .01) and a medium amount of anxiety (RR, 0.86; 95% CI, 0.75 to 0.99; P = .04) reduced the risk of obesity. Results of SEM (N = 8,244; comparative fit index =0.999; Tucker Lewis index = 0.999; root mean square error of approximation = 0.014; weighted root mean square residual = 0.749) described the hierarchical impact of the direct predictors, moderators, and mediators of obesity. Conclusion: Treatment, lifestyle, and intrapersonal factors, as well as the use of specific antidepressants, may contribute to obesity among survivors. A multifaceted intervention, including alternative drug and other therapies for depression and anxiety, may be required to reduce risk. © 2011 by American Society of Clinical Oncology