A simple model for ferret population dynamics and control in semi-arid New Zealand habitats

2001 ◽  
Vol 28 (1) ◽  
pp. 87 ◽  
Author(s):  
N. D. Barlow ◽  
G. L. Norbury
Keyword(s):  
Population Dynamics ◽  
New Zealand ◽  
Current Density ◽  
Average Density ◽  
Intrinsic Rate Of Increase ◽  
Data Sets ◽  
Data Set ◽  
Rate Of Increase ◽  
Semi Arid ◽  
Over Time

Introduced ferrets (Mustela furo) in New Zealand are subject to population control to reduce their threat to native fauna and the incidence of bovine tuberculosis (Tb) in livestock. To help in evaluating control options and to contribute to a multi-species model for Tb dynamics, a simple Ricker model was developed for ferret population dynamics in a semi-arid environment. The model was based on two data sets and suggested an intrinsic rate of increase for ferrets of 1.0–1.3 year–1 and a carrying capacity of 0.5–2.9 km–2. There was evidence for direct density-dependence in both data sets and the effect appeared to act mainly on recruitment. Dependence of the rate of increase of predators on the density of wild rabbits (Oryctolagus cuniculus) was exhibited in one of the two data sets, together with a numerical response relating current density of predators asymptotically to current density of rabbits, their primary prey. Predators in this data set included both cats and ferrets, estimated from spotlight counts, but the other data set demonstrated a direct proportionality between predator (cat and ferret) spotlight counts and minimum ferrets known to be alive by trapping. The model suggested, firstly, that populations are hard to suppress by continuous culling, with at least a 50% removal per year necessary to effect a suppression of 50% in long-term average density. Secondly, if control is episodic rather than continuous, culling in autumn gives a greater degree of suppression over time (280%, accumulated over time) than culling in spring (180%). A differential equation version of the model provides a component for a general Anderson/May bovine Tb/wildlife (possum/deer/ferret) model.

The social wasp Vespula germanica (Fabricius) (Hymenoptera: Vespidae) population dynamics in England over 39 years.

2018 ◽  
Vol 154 (2) ◽  
pp. 149-155
Author(s):  
Michael Archer
Keyword(s):  
Population Dynamics ◽  
Population Dynamic ◽  
Ecological Factors ◽  
Social Wasp ◽  
Data Sets ◽  
Data Set ◽  
Vespula Germanica ◽  
The Social ◽  
Minimum Number ◽  
Suction Traps

1. Yearly records of worker Vespula germanica (Fabricius) taken in suction traps at Silwood Park (28 years) and at Rothamsted Research (39 years) are examined. 2. Using the autocorrelation function (ACF), a significant negative 1-year lag followed by a lesser non-significant positive 2-year lag was found in all, or parts of, each data set, indicating an underlying population dynamic of a 2-year cycle with a damped waveform. 3. The minimum number of years before the 2-year cycle with damped waveform was shown varied between 17 and 26, or was not found in some data sets. 4. Ecological factors delaying or preventing the occurrence of the 2-year cycle are considered.

PSVI-8 Meta-regression Analysis to Determine the Relationship Between Growing Pig Body Weight and Variation

2021 ◽  
Vol 99 (Supplement_1) ◽  
pp. 218-219
Author(s):  
Andres Fernando T Russi ◽  
Mike D Tokach ◽  
Jason C Woodworth ◽  
Joel M DeRouchey ◽  
Robert D Goodband ◽  
...  
Keyword(s):  
Body Weight ◽  
Regression Analysis ◽  
Sample Size ◽  
Polynomial Regression ◽  
Data Sets ◽  
Regression Equations ◽  
Prediction Equations ◽  
Data Set ◽  
Rate Of Increase ◽  
The Relationship

Abstract The swine industry has been constantly evolving to select animals with improved performance traits and to minimize variation in body weight (BW) in order to meet packer specifications. Therefore, understanding variation presents an opportunity for producers to find strategies that could help reduce, manage, or deal with variation of pigs in a barn. A systematic review and meta-analysis was conducted by collecting data from multiple studies and available data sets in order to develop prediction equations for coefficient of variation (CV) and standard deviation (SD) as a function of BW. Information regarding BW variation from 16 papers was recorded to provide approximately 204 data points. Together, these data included 117,268 individually weighed pigs with a sample size that ranged from 104 to 4,108 pigs. A random-effects model with study used as a random effect was developed. Observations were weighted using sample size as an estimate for precision on the analysis, where larger data sets accounted for increased accuracy in the model. Regression equations were developed using the nlme package of R to determine the relationship between BW and its variation. Polynomial regression analysis was conducted separately for each variation measurement. When CV was reported in the data set, SD was calculated and vice versa. The resulting prediction equations were: CV (%) = 20.04 – 0.135 × (BW) + 0.00043 × (BW)2, R2=0.79; SD = 0.41 + 0.150 × (BW) - 0.00041 × (BW)2, R2 = 0.95. These equations suggest that there is evidence for a decreasing quadratic relationship between mean CV of a population and BW of pigs whereby the rate of decrease is smaller as mean pig BW increases from birth to market. Conversely, the rate of increase of SD of a population of pigs is smaller as mean pig BW increases from birth to market.

scholarly journals Faculty Publishing Productivity: Comparisons over Time

2006 ◽  
Vol 67 (3) ◽  
pp. 230-239 ◽  
Author(s):  
John M. Budd
Keyword(s):  
Academic Librarians ◽  
Tenure Track ◽  
Data Set ◽  
Part Time Faculty ◽  
Time Period ◽  
Rate Of Increase ◽  
Part Time ◽  
Per Capita ◽  
Time Faculty ◽  
Over Time

Concerns about higher education abound, and these include concerns about productivity. The present study extends two previous examinations of faculty publishing productivity covering the years 1991 to 1993 and 1995 to 1997. Both members of ARL and a group of institutions included in ACRL’s data set are included. For both groups there are some increases in mean total numbers of publications, although the rate of increase has decreased since the second time period. Per capita rates of publication demonstrate an even flatter pattern. In recent years, there have been some changes in the dynamics of universities’ faculties; there are more part-time faculty and more faculty who are not on the tenure track. These factors, coupled with the publishing data, point to activities that all academic librarians should be aware of.

Disparities Across Time: Exploring Absenteeism Patterns between Cohorts of Students with Disabilities

2020 ◽  
Vol 122 (11) ◽  
pp. 1-32
Author(s):  
Michael A. Gottfried ◽  
Vi-Nhuan Le ◽  
J. Jacob Kirksey
Keyword(s):  
Students With Disabilities ◽  
Social Needs ◽  
Data Sets ◽  
Chronic Absenteeism ◽  
Data Set ◽  
Full Day Kindergarten ◽  
Effective Interventions ◽  
Nationally Representative ◽  
Single Data ◽  
Over Time

Background It is of grave concern that kindergartners are missing more school than students in any other year of elementary school; therefore, documenting which students are absent and for how long is of upmost importance. Yet, doing so for students with disabilities (SWDs) has received little attention. This study addresses this gap by examining two cohorts of SWDs, separated by more than a decade, to document changes in attendance patterns. Research Questions First, for SWDs, has the number of school days missed or chronic absenteeism rates changed over time? Second, how are changes in the number of school days missed and chronic absenteeism rates related to changes in academic emphasis, presence of teacher aides, SWD-specific teacher training, and preschool participation? Subjects This study uses data from the Early Childhood Longitudinal Study (ECLS), a nationally representative data set of children in kindergarten. We rely on both ECLS data sets— the kindergarten classes of 1998–1999 and 2010–2011. Measures were identical in both data sets, making it feasible to compare children across the two cohorts. Given identical measures, we combined the data sets into a single data set with an indicator for being in the older cohort. Research Design This study examined two sets of outcomes: The first was number of days absent, and the second was likelihood of being chronically absent. These outcomes were regressed on a measure for being in the older cohort (our key measure for changes over time) and numerous control variables. The error term was clustered by classroom. Findings We found that SWDs are absent more often now than they were a decade earlier, and this growth in absenteeism was larger than what students without disabilities experienced. Absenteeism among SWDs was higher for those enrolled in full-day kindergarten, although having attended center-based care mitigates this disparity over time. Implications are discussed. Conclusions Our study calls for additional attention and supports to combat the increasing rates of absenteeism for SWDs over time. Understanding contextual shifts and trends in rates of absenteeism for SWDs in kindergarten is pertinent to crafting effective interventions and research geared toward supporting the academic and social needs of these students.

US academic libraries' staffing and expenditure trends (1996–2016)

2020 ◽  
Vol 41 (4/5) ◽  
pp. 247-268 ◽  
Author(s):  
Starr Hoffman ◽  
Samantha Godbey
Keyword(s):  
Academic Libraries ◽  
The United States ◽  
Data Sets ◽  
Size Category ◽  
Data Set ◽  
Content Type ◽  
Education Statistics ◽  
Trends Over Time ◽  
Doctoral Institutions ◽  
Over Time

PurposeThis paper explores trends over time in library staffing and staffing expenditures among two- and four-year colleges and universities in the United States.Design/methodology/approachResearchers merged and analyzed data from 1996 to 2016 from the National Center for Education Statistics for over 3,500 libraries at postsecondary institutions. This study is primarily descriptive in nature and addresses the research questions: How do staffing trends in academic libraries over this period of time relate to Carnegie classification and institution size? How do trends in library staffing expenditures over this period of time correspond to these same variables?FindingsAcross all institutions, on average, total library staff decreased from 1998 to 2012. Numbers of librarians declined at master’s and doctoral institutions between 1998 and 2016. Numbers of students per librarian increased over time in each Carnegie and size category. Average inflation-adjusted staffing expenditures have remained steady for master's, baccalaureate and associate's institutions. Salaries as a percent of library budget decreased only among doctoral institutions and institutions with 20,000 or more students.Originality/valueThis is a valuable study of trends over time, which has been difficult without downloading and merging separate data sets from multiple government sources. As a result, few studies have taken such an approach to this data. Consequently, institutions and libraries are making decisions about resource allocation based on only a fraction of the available data. Academic libraries can use this study and the resulting data set to benchmark key staffing characteristics.

A Ccomparison of sedigraph and pipette methods for soil particle-size analysis

Soil Research ◽  
1993 ◽  
Vol 31 (4) ◽  
pp. 407 ◽  
Author(s):  
GD Buchan ◽  
KS Grewal ◽  
JJ Claydon ◽  
RJ Mcpherson
Keyword(s):  
Particle Size ◽  
New Zealand ◽  
Particle Size Analysis ◽  
Size Analysis ◽  
Data Sets ◽  
Regression Equations ◽  
Total Iron Content ◽  
Data Set ◽  
X Ray ◽  
The Difference

The X-ray attenuation (Sedigraph) method for particle-size analysis is known to consistently estimate a finer size distribution than the pipette method. The objectives of this study were to compare the two methods, and to explore the reasons for their divergence. The methods are compared using two data sets from measurements made independently in two New Zealand laboratories, on two different sets of New Zealand soils, covering a range of textures and parent materials. The Sedigraph method gave systematically greater mass percentages at the four measurement diameters (20, 10, 5 and 2 �m). For one data set, the difference between clay (<2 �m) percentages from the two methods is shown to be positively correlated (R2 = 0.625) with total iron content of the sample, for all but one of the soils. This supports a novel hypothesis that the typically greater concentration of Fe (a strong X-ray absorber) in smaller size fractions is the major factor causing the difference. Regression equations are presented for converting the Sedigraph data to their pipette equivalents.

Effects of Temperature on the Development and Fecundity of Atractomorpha Sinensis (Orthoptera: Pyrgomorphidae)

2020 ◽  
Vol 113 (5) ◽  
pp. 2530-2539
Author(s):  
Wen-bo Li ◽  
Yu Gao ◽  
Juan Cui ◽  
Shu-Sen Shi
Keyword(s):  
Population Dynamics ◽  
Developmental Period ◽  
Biological Characteristics ◽  
Intrinsic Rate Of Increase ◽  
Male Adult ◽  
Developmental Threshold ◽  
Preoviposition Period ◽  
Rate Of Increase ◽  
Threshold Temperatures ◽  
The Impact

Abstract Over the recent years, Atractomorpha sinensis I. Bolivar, has emerged as an important agricultural pest in China. However, the biological characteristics of A. sinensis remain largely unknown, which can hinder the prediction of its population dynamics. Thus, understanding the impact of temperature on the developmental period of A. sinensis is crucial to predict its population dynamics. The biological characteristics of A. sinensis were systematically observed at five different temperatures (16, 20, 24, 28, and 32°C) using the age-stage, two-sex life table method. The results demonstrated that the developmental period, preadult time, adult longevity, adult preoviposition period, and total preoviposition period were significantly reduced when the temperature was elevated from 16 to 32°C. The developmental threshold temperatures of egg, nymph, preoviposition period, female adult, male adult, and generation were 9.14, 10.44, 12.53, 10.97, 12.47, and 10.58°C, respectively, with the corresponding effective accumulated temperatures of 452.31, 575.99, 169.58, 528.13, 340.81, and 1447.95 degree-days. With an increase in temperature, the intrinsic rate of increase (r) and finite rate of increase (λ) were increased, while the mean generation time (T) was shortened. The optimal values of net reproductive rate (R0= 73.00 offspring) and fecundity (244.55 eggs) were determined at 24°C. Similarly, the population trend index (I) of A. sinensis was found to be highest at 24°C. Our findings indicate that A. sinensis has the greatest rate of population growth at 24°C, which can provide a scientific basis for predicting the in-field population dynamics of A. sinensis.

A length-based Bayesian stock assessment model for the New Zealand abalone Haliotis iris

2003 ◽  
Vol 54 (5) ◽  
pp. 619 ◽  
Author(s):  
Paul A. Breen ◽  
Susan W. Kim ◽  
Neil L. Andrew
Keyword(s):  
New Zealand ◽  
Stock Assessment ◽  
Assessment Model ◽  
Data Sets ◽  
Catch Per Unit Effort ◽  
Commercial Catch ◽  
Data Set ◽  
Future Directions ◽  
Common Component ◽  
Joint Posterior Distribution

We describe a length-based Bayesian model for stock assessment of the New Zealand abalone Haliotis iris (paua). We fitted the model to five data sets: catch-per-unit-effort (CPUE) and a fishery-independent survey index, proportions-at-length from both commercial catch sampling and population surveys, and tag–recapture data. We estimated a common component of error and used iterative re-weighting of the data sets to balance the residuals, removing the arbitrary data set weightings used in previous assessments. Estimates at the mode of the joint posterior distribution were used to explore sensitivity of the results to model assumptions and input data; the assessment itself was based on marginal posterior distributions estimated from Markov chain–Monte Carlo simulation. Assessments are presented for two stocks in the south of New Zealand. One may be recovering after recent catch reductions; the other is over-exploited and likely to decline further. Assessment for the first stock was robust; assessment for the second stock was sensitive to the CPUE data and may be too optimistic. We discuss future directions and potential problems with this approach.

scholarly journals What's in an elevation difference? Accuracy and corrections of satellite elevation data sets for quantification of glacier changes

2010 ◽  
Vol 4 (4) ◽  
pp. 2013-2077 ◽  
Author(s):  
C. Nuth ◽  
A. Kääb
Keyword(s):  
New Zealand ◽  
Regional Scale ◽  
Statistical Error ◽  
Data Sets ◽  
Methodological Framework ◽  
Data Set ◽  
Aster Gdem ◽  
Elevation Data ◽  
Elevation Changes

Abstract. There is an increasing number of DEMs available worldwide for deriving elevation differences over time, including vertical changes on glaciers. Most of these DEMs are heavily post-processed or merged, so that physical error modelling becomes impossible and statistical error modelling is required instead. We propose a three-step methodological framework for assessing and correcting DEMs to quantify glacier elevation changes: remove DEM shifts, check for elevation-dependent biases, and check for higher-order, sensor-specific biases. An analytic, simple and robust method to co-register elevation data is presented in regions where stable terrain is either plentiful (case study New Zealand) or limited (case study Svalbard). The method is exemplified using the three global elevation data sets available, SRTM, ICESat and the ASTER GDEM, and with automatically generated DEMs from satellite stereo instruments of ASTER and SPOT5-HRS. After three-dimensional co-registration, significant biases related to elevation were found in some of the stereoscopic DEMs. Biases related to the satellite acquisition geometry (along/cross track) were detected at two frequencies in the automatically generated ASTER DEMs. The higher frequency bias seems to be related to satellite \\emph{jitter}, most effective in the back-looking pass of the satellite. The origins of the more significant lower frequency bias is uncertain. ICESat-derived elevations are found to be the most consistent globally available elevation data set available so far. Before performing regional-scale glacier elevation change studies or mosaicking DEMs from multiple individual tiles (e.g. ASTER GDEM), we recommend to co-register all elevation data to ICESat as a global vertical reference system. The proposed methodological framework is exemplified for elevation changes on the Fox, Franz Joseph, Tasman and Murchison glaciers of New Zealand and the glaciers of central Spitsbergen, Svalbard.

scholarly journals State- and County-Level COVID-19 Public Health Orders in California: Constructing a Dataset and Describing Their Timing, Content, and Stricture

2020 ◽  
Author(s):  
Jeremy D. Goldhaber-Fiebert ◽  
Alexander F. Holsinger ◽  
Erin Holsinger ◽  
Elizabeth Long
Keyword(s):  
Public Health ◽  
Search Strategy ◽  
Initial Assessment ◽  
County Level ◽  
Data Set ◽  
Time Period ◽  
Rate Of Increase ◽  
Pharmaceutical Interventions ◽  
Over Time

AbstractWithout vaccines, non-pharmaceutical interventions have been the most widely used approach to controlling the spread of COVID-19 epidemics. Various jurisdictions have implemented public health orders as a means of reducing effective contacts and controlling their local epidemics. Multiple studies have examined the effectiveness of various orders (e.g. use of face masks) for epidemic control. However, orders occur at different timings across jurisdictions and some orders on the same topic are stricter than others. We constructed a county-level longitudinal data set of more than 1,700 public health orders issues by California and its 58 counties pertaining to its 40 million residents. First, we describe methods used to construct the dataset that enables the characterization of the evolution over time of California state- and county-level public health orders dealing with COVID-19 from January 1, 2020 through November 30, 2020. Public health orders are both an interesting and important outcome in their own right and also a key input into analyses looking at how such orders may impact COVID-19 epidemics. To construct the dataset, we developed and executed a search strategy to identify COVID-19 public health orders over this time period for all relevant jurisdictions. We characterized each identified public health order in terms of the timing of when it was announced, went into effect and (potentially) expired. We also adapted an existing schema to describe the topic(s) each public health order dealt with and the level of stricture each imposed, applying it to all identified orders. Finally, as an initial assessment, we examined the patterns of public health orders within and across counties, focusing on the timing of orders, the rate of increase and decrease in stricture, and on variation and convergence of orders within regions.

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