scholarly journals Use of an enclosed elk population to assess two non-invasive methods for estimating population size

2021 ◽  
Author(s):  
Jennifer L Brazeal ◽  
Benjamin N Sacks
Keyword(s):  
Field Testing ◽  
Relative Standard Error ◽  
Non Invasive ◽  
Promising Tool ◽  
Genetic Sampling ◽  
Relative Standard ◽  
Cervus Canadensis ◽  
Accuracy Of Results ◽  
Free Ranging ◽  
Future Population

Non-invasive genetic sampling and spatially explicit capture-recapture (SCR) models are used increasingly to estimate abundance of wildlife populations, but have not been adequately tested on gregarious animals such as elk (Cervus canadensis), for which correlated space use and movements violate model assumptions of independence. To evaluate the robustness and accuracy of SCR, and to assess the utility of an alternative non-invasive method for estimating density of gregarious ungulates, we utilized a tule elk (Cervus canadensis nannodes) population of known size within a fenced enclosure on the San Luis National Wildlife Refuge in central California. We evaluated fecal genetic SCR to camera trap-based random encounter model (REM) approaches to density estimation based on comparison to the true abundance. We also subsampled the dataset to explore the effects of varying search effort and elk density on the precision and accuracy of results. We found that SCR outperformed REM methods in the full datasets, and reliably provided accurate (relative bias <10%) and reasonably precise (relative standard error ≤20%) estimates of density at moderately low to high densities (6-17 elk/km2), when the subsampling scenarios yielded a minimum average of 20 recaptures. We also found that the number of samples used to construct detection histories was a reliable predictor of precision, and could be used to establish minimum sampling requirements in future population surveys of elk. Although field-testing in free-ranging populations is needed, our results suggest that non-invasive genetic SCR is a promising tool for future population studies and monitoring of elk and potentially other gregarious ungulates. In contrast, the REM estimate of density was highly inaccurate, imprecise, and highly sensitive to camera parameters.

Long-distance wolf recolonization of France and Switzerland inferred from non-invasive genetic sampling over a period of 10 years

2003 ◽  
Vol 6 (1) ◽  
pp. 83-92 ◽  
Author(s):  
Nathaniel Valière ◽  
Luca Fumagalli ◽  
Ludovic Gielly ◽  
Christian Miquel ◽  
Benoît Lequette ◽  
...  
Keyword(s):  
Long Distance ◽  
Non Invasive ◽  
Genetic Sampling

scholarly journals Using non-invasive sampling methods to determine the prevalence and distribution of Chlamydia pecorum and koala retrovirus in a remnant koala population with conservation importance

2018 ◽  
Vol 45 (4) ◽  
pp. 366 ◽  
Author(s):  
Faye Wedrowicz ◽  
Jennifer Mosse ◽  
Wendy Wright ◽  
Fiona E. Hogan
Keyword(s):  
Native Species ◽  
Conservation Strategies ◽  
The South ◽  
Phascolarctos Cinereus ◽  
Urogenital Infection ◽  
Non Invasive ◽  
Chlamydia Pecorum ◽  
Genetic Sampling ◽  
Pathogen Prevalence ◽  
Koala Retrovirus

Context Pathogenic infections are an important consideration for the conservation of native species, but obtaining such data from wild populations can be expensive and difficult. Two pathogens have been implicated in the decline of some koala (Phascolarctos cinereus) populations: urogenital infection with Chlamydia pecorum and koala retrovirus subgroup A (KoRV-A). Pathogen data for a wild koala population of conservation importance in South Gippsland, Victoria are essentially absent. Aims This study uses non-invasive sampling of koala scats to provide prevalence and genotype data for C. pecorum and KoRV-A in the South Gippsland koala population, and compares pathogen prevalence between wild koalas and koalas in rescue shelters. Methods C. pecorum and KoRV-A provirus were detected by PCR of DNA isolated from scats collected in the field. Pathogen genetic variation was investigated using DNA sequencing of the C. pecorum ompA and KoRV-A env genes. Key results C. pecorum and KoRV-A were detected in 61% and 27% of wild South Gippsland individuals tested, respectively. KoRV-A infection tended to be higher in shelter koalas compared with wild koalas. In contrast with other Victorian koala populations sampled, greater pathogen diversity was present in South Gippsland. Conclusions In the South Gippsland koala population, C. pecorum is widespread and common whereas KoRV appears less prevalent than previously thought. Further work exploring the dynamics of these pathogens in South Gippsland koalas is warranted and may help inform future conservation strategies for this important population. Implications Non-invasive genetic sampling from scats is a powerful method for obtaining data regarding pathogen prevalence and diversity in wildlife. The use of non-invasive methods for the study of pathogens may help fill research gaps in a way that would be difficult or expensive to achieve using traditional methods.

scholarly journals Lidar arc scan uncertainty reduction through scanning geometry optimization

2016 ◽  
Vol 9 (4) ◽  
pp. 1653-1669 ◽  
Author(s):  
Hui Wang ◽  
Rebecca J. Barthelmie ◽  
Sara C. Pryor ◽  
Gareth. Brown
Keyword(s):  
Theoretical Model ◽  
Wind Speed ◽  
Wind Energy ◽  
Turbulence Intensity ◽  
Wind Direction ◽  
Energy Production ◽  
Elevation Angle ◽  
Relative Standard Error ◽  
Power Performance ◽  
Relative Standard

Abstract. Doppler lidars are frequently operated in a mode referred to as arc scans, wherein the lidar beam scans across a sector with a fixed elevation angle and the resulting measurements are used to derive an estimate of the n minute horizontal mean wind velocity (speed and direction). Previous studies have shown that the uncertainty in the measured wind speed originates from turbulent wind fluctuations and depends on the scan geometry (the arc span and the arc orientation). This paper is designed to provide guidance on optimal scan geometries for two key applications in the wind energy industry: wind turbine power performance analysis and annual energy production prediction. We present a quantitative analysis of the retrieved wind speed uncertainty derived using a theoretical model with the assumption of isotropic and frozen turbulence, and observations from three sites that are onshore with flat terrain, onshore with complex terrain and offshore, respectively. The results from both the theoretical model and observations show that the uncertainty is scaled with the turbulence intensity such that the relative standard error on the 10 min mean wind speed is about 30 % of the turbulence intensity. The uncertainty in both retrieved wind speeds and derived wind energy production estimates can be reduced by aligning lidar beams with the dominant wind direction, increasing the arc span and lowering the number of beams per arc scan. Large arc spans should be used at sites with high turbulence intensity and/or large wind direction variation.

scholarly journals Genetic Structure and Gene Flow in Eastern Grey Kangaroos in an Isolated Conservation Reserve

Diversity ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 570
Author(s):  
Miriam A. Zemanova ◽  
Daniel Ramp
Keyword(s):  
Gene Flow ◽  
Clustering Algorithm ◽  
Population Control ◽  
Current Conservation ◽  
Non Invasive ◽  
Conservation Property ◽  
Genetic Sampling ◽  
Grey Kangaroo ◽  
Conservation Concern ◽  
Genetic Assessment

Dispersal is a key process for population persistence, particularly in fragmented landscapes. Connectivity between habitat fragments can be easily estimated by quantifying gene flow among subpopulations. However, the focus in ecological research has been on endangered species, typically excluding species that are not of current conservation concern. Consequently, our current understanding of the behaviour and persistence of many species is incomplete. A case in point is the eastern grey kangaroo (Macropus giganteus), an Australian herbivore that is subjected to considerable harvesting and population control efforts. In this study, we used non-invasive genetic sampling of eastern grey kangaroos within and outside of the Mourachan Conservation Property to assess functional connectivity. In total, we genotyped 232 samples collected from 17 locations at 20 microsatellite loci. The clustering algorithm indicated the presence of two clusters, with some overlap between the groups within and outside of the reserve. This genetic assessment should be repeated in 10–15 years to observe changes in population structure and gene flow over time, monitoring the potential impact of the planned exclusion fencing around the reserve.

scholarly journals Systemic immune‐inflammation index has prognostic significance in pancreatic carcinoma patients: a meta-analysis

2021 ◽  
Author(s):  
Xiaocheng Li ◽  
Huapeng Lin ◽  
Renbin Ouyang ◽  
Yaowei Yang ◽  
Jing Peng
Keyword(s):  
Pancreatic Carcinoma ◽  
Fixed Effects ◽  
Meta Analysis ◽  
Prognostic Significance ◽  
Prognostic Indicator ◽  
Cochrane Library ◽  
Cancer Specific Survival ◽  
Non Invasive ◽  
Promising Tool ◽  
Immune Inflammation

Abstract Background Systemic immune-inflammation index (SII) is reportedly a prognostic indicator for several malignancies, including pancreatic carcinoma, although there exists no consensus regarding its significance. In the current study, we used a systematically meta-analysis to evaluate the association between SII and prognosis in pancreatic carcinoma patients. Methods We screened PubMed, Embase and Cochrane Library databases, through May 2020, and retrieved studies describing the prognostic role of SII in pancreatic carcinoma. We calculated pooled hazard ratio (HR) and 95% confidence interval (CI) using a random or fixed effects models to reveal the correlation between SII and prognosis. Results A total of 4 studies, comprising 1,749 patients, met our inclusion criteria and were therefore eligible for inclusion. Our meta-analysis showed that elevated SII indicated significantly worse overall survival in patients with pancreatic carcinoma (HR: 1.43, 95% CI: 1.24–1.65, P < 0.001), with subgroup analyses, stratified by the TNM stage and treatment, further validating these results. In addition, patients with high SII had poorer cancer-specific survival (HR: 2.32, 95% CI: 1.55–3.48, P < 0.001). However, we found no significant associations between SII with disease-free and relapse-free survival. Conclusions These findings indicate that SII is a potential non-invasive and promising tool for predicting clinical outcomes of pancreatic carcinoma patients. However, further studies using adequate designs and larger sample sizes are required to validate our findings.

scholarly journals Mucus: aiding elasmobranch conservation through non-invasive genetic sampling

2013 ◽  
Vol 21 (3) ◽  
pp. 215-222 ◽  
Author(s):  
L Lieber ◽  
S Berrow ◽  
E Johnston ◽  
G Hall ◽  
J Hall ◽  
...  
Keyword(s):  
Non Invasive ◽  
Genetic Sampling

Non-invasive genetic sampling

1998 ◽  
Vol 13 (1) ◽  
pp. 26-27 ◽  
Author(s):  
Pierre Taberlet ◽  
Lisette P Waits
Keyword(s):  
Non Invasive ◽  
Genetic Sampling

scholarly journals Population Pharmacokinetics of Fluconazole in Young Infants

2008 ◽  
Vol 52 (11) ◽  
pp. 4043-4049 ◽  
Author(s):  
K. C. Wade ◽  
D. Wu ◽  
D. A. Kaufman ◽  
R. M. Ward ◽  
D. K. Benjamin ◽  
...  
Keyword(s):  
Fixed Effects ◽  
Compartment Model ◽  
Volume Of Distribution ◽  
Relative Standard Error ◽  
Data Set ◽  
Mixed Effect ◽  
Young Infants ◽  
Relative Standard ◽  
Population Pk ◽  
The Impact

ABSTRACT Fluconazole is being increasingly used to prevent and treat invasive candidiasis in neonates, yet dosing is largely empirical due to the lack of adequate pharmacokinetic (PK) data. We performed a multicenter population PK study of fluconazole in 23- to 40-week-gestation infants less than 120 days of age. We developed a population PK model using nonlinear mixed effect modeling (NONMEM) with the NONMEM algorithm. Covariate effects were predefined and evaluated based on estimation precision and clinical significance. We studied fluconazole PK in 55 infants who at enrollment had a median (range) weight of 1.02 (0.440 to 7.125) kg, a gestational age at birth (BGA) of 26 (23 to 40) weeks, and a postnatal age (PNA) of 2.3 (0.14 to 12.6) weeks. The final data set contained 357 samples; 217/357 (61%) were collected prospectively at prespecified time intervals, and 140/357 (39%) were scavenged from discarded clinical specimens. Fluconazole population PK was best described by a one-compartment model with covariates normalized to median values. The population mean clearance (CL) can be derived for this population by the equation CL (liter/h) equals 0.015 · (weight/1)0.75 · (BGA/26)1.739 · (PNA/2)0.237 · serum creatinine (SCRT)−4.896 (when SCRT is >1.0 mg/dl), and using a volume of distribution (V) (liter) of 1.024 · (weight/1). The relative standard error around the fixed effects point estimates ranged from 3 to 24%. CL doubles between birth and 28 days of age from 0.008 to 0.016 and from 0.010 to 0.022 liter/kg/h for typical 24- and 32-week-gestation infants, respectively. This population PK model of fluconazole discriminated the impact of BGA, PNA, and creatinine on drug CL. Our data suggest that dosing in young infants will require adjustment for BGA and PNA to achieve targeted systemic drug exposures.

Determination of total antioxidant capacity of milk by CUPRAC and ABTS methods with separate characterisation of milk protein fractions

2015 ◽  
Vol 82 (2) ◽  
pp. 177-184 ◽  
Author(s):  
Sema Demirci Çekiç ◽  
Aslı Demir ◽  
Kevser Sözgen Başkan ◽  
Esma Tütem ◽  
Reşat Apak
Keyword(s):  
Antioxidant Capacity ◽  
Total Antioxidant Capacity ◽  
Milk Protein ◽  
Skim Milk ◽  
Protein Fractions ◽  
Relative Standard Error ◽  
Antioxidant Power ◽  
Antioxidant Capacities ◽  
Relative Standard ◽  
Total Antioxidant

Most milk-applied antioxidant assays in literature are based on the isolation and quantification of individual antioxidative compounds, whereas total antioxidant capacity (TAC) gives a more holistic picture due to cooperative action of antioxidants. Recently, the cupric reducing antioxidant capacity (CUPRAC) method has been modified to measure the antioxidant capacities of thiol-containing proteins, where the classical ammonium acetate buffer – that may otherwise precipitate proteins– was replaced with concentrated urea buffer (able to expose embedded thiol groups of proteins to oxidative attack) adjusted to pH 7.0. Thus, antioxidant capacity of milk was investigated with two competing TAC assays, namely CUPRAC and ABTS (2,2′-azinobis(3-ethylbenzothiazoline-6-sulphonic acid))/persulphate, because only these assays were capable of evaluating protein contribution to the observed TAC value. As milk fat caused turbidity, experiments were carried out with skim milk or defatted milk samples. To determine TAC, modified CUPRAC method was applied to whole milk, separated and redissolved protein fractions, and the remaining liquid phase after necessary operations. Both TAC methods were investigated for their dilution sensitivity and antioxidant power assessment of separate milk fractions such as casein and whey. Proteins like β-lactoglobulin and casein (but not simple thiols) exhibited enhanced CUPRAC reactivity with surfactant (SDS) addition. Addition of milk protein fractions to whole skim milk produced significant ‘negative-biased’ deviations (up to −26% relative standard error) from TAC absorbance additivity in the application of the ABTS method, as opposed to that of the CUPRAC method less affected by chemical deviations from Beer's law thereby producing much smaller deviations from additivity (i.e. the property of additivity is valid when the measured TAC of a mixture is equal to the sum of individual antioxidant capacities of its constituents).

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