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Thursday, November 12, 2020 | History

2 edition of Estimation of the effect of intensive logging on ungulates (cervids) in the White River drainage found in the catalog.

Estimation of the effect of intensive logging on ungulates (cervids) in the White River drainage

G. Schuerholz

Estimation of the effect of intensive logging on ungulates (cervids) in the White River drainage

  • 238 Want to read
  • 7 Currently reading

Published by Pacific Forestry Centre in Victoria, B.C .
Written in English

    Subjects:
  • Ungulates -- British Columbia -- White River Watershed.,
  • Logging -- Environmental aspects -- British Columbia -- White River Watershed.

  • Edition Notes

    Statementby G. Schuerholz, P. McNamee and M.R.C. Massie.
    SeriesInformation report / Pacific Forestry Centre -- BC-X-303., Information report (Pacific Forestry Centre) -- BC-X-303.
    ContributionsMcNamee, Peter J., Massie, M. R. C., Pacific Forestry Centre.
    The Physical Object
    Pagination35 p. :
    Number of Pages35
    ID Numbers
    Open LibraryOL18159125M
    ISBN 100662163729


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Estimation of the effect of intensive logging on ungulates (cervids) in the White River drainage by G. Schuerholz Download PDF EPUB FB2

Get this from a library. Estimation of the effect of intensive logging on ungulates (cervids) in the White River drainage. [G Schuerholz; M R C Massie; Peter James McNamee; Pacific Forestry Centre.].

High-density populations of large ungulates are now widespread. However, the perception of overabundance only appears when it produces a problem for humans, such as a loss of plant diversity.

Critical tipping points, where ungulates started to have a negative effect on forest regeneration, were found at an ungulate metabolic weight density of kg km −2 for forest regeneration, kg km −2 for forest structure, and kg km −2 for forest functioning, which is roughly equivalent to 10, 13 and 23 roe deer per km −2.

Forest Cited by:   Likewise, heavy selective logging reduced the density of primates in tropical Africa, while lower-intensity logging had no effect (Chapman et al., ). Additional work is needed in Borneo and other tropical areas to detect thresholds in logging intensity beyond which density or habitat use of carnivores (or other susceptible taxa) by: 1.

In this review, we focus on how males can affect the population dynamics of ungulates (i) by being a component of population density (and thereby affecting interpretation of log‐linear models), and (ii) by considering the mechanisms by which males can actively affect the demographic rates of by: The impact experienced over the last years has been the most devastating.

For example, at end of XIX and the beginning of XX centuries, as a result of intensive game husbandry in the Belovezhskaya forests, the territory suffered from overgrazing by an excessive numbers of ungulates. Effects of intensive harvesting on moose reproduction.

and J. Clobert. Estimating. The effect of trophy hunting on ungulate behaviours was examined by comparing the behaviours of the. Logging and its effects on the ecosystem are complex. Forest Management. The U.S. Forest Service manages its lands to allow use of this renewable resource.

Their mission involves managing the forests for their productivity. Oftentimes, logging replaces natural forces that would be in play in forest ecosystems.

For instance, in some forest. To quantify support for our models estimating the effect of serostatus on pregnancy probability, we used Widely Applicable Information Criterion (WAIC) (Vehtari, Gelman, & Gabry, ; Watanabe, ) and Akaike model weight.

All models were run for. Biodiversity loss; The loss of forests throughout the world through illegal logging is a huge object of concern from a biodiversity point of view. Already endangered species of flora and fauna are being pushed closer to extinction due to widespread habitat destruction and modern Estimation of the effect of intensive logging on ungulates book extinction rate has reached – times the biological normal, which equates to 1.

The accuracy of three methods (pellet group count, inverse line transect method and track count) for estimating the density of ungulate population was assessed, based on a wapiti population with the known size in the enclosure of hm2 on Tonghe Hunting Farm, Heilongjiang province, China, during – The estimation of population density using the pellet group count method was the.

For estimating overall ungulate herbivory pressure (i.e. on both vegetative and reproductive plant structures), we compared the volume of fer shrubs in ungulate-excluded and ungulate-exposed plots.

To this end, we randomly selected 15 (in ) and 4 to 6 (in andrespectively) fer individuals in ungulated-exposed (open) and ungulate-excluded plots (fenced). The logistic regression model equates the logit transform, the log-odds of the probability of a success, to the linear component: log ˇi 1 ˇi = XK k=0 xik k i = 1;2;;N (1) Parameter Estimation The goal of logistic regression is to estimate the K+1 unknown parameters in Eq.

This is done with maximum likelihood estimation which entails. However, the reality may be drastically different elsewhere. For example, in areas with a higher human population, intensive logging, or commercial bushmeat hunting, specific studies will be needed to evaluate the effect of timber activities on wild mammal populations in each area.

The activity of feral ungulates such as pigs, goats, and deer has resulted in extensive biodiversity loss in Hawaii.

These animals were introduced by the Polynesians as domesticated livestock, and now play a destructive role in the local ecosystem. effect of all discontinuities, regardless of orienta­ tion, by the logging procedure (fig.

For the unique case in which a discontinuity cuts a piece of core parallel to its axis, the discontinuity is counted as a single discontinuity in the calculation. Similarly, when using the English system of. This is the first introductory statistics text to use an estimation approach from the start to help readers understand effect sizes, confidence intervals (CIs), and meta-analysis (‘the new statistics’).

It is also the first text to explain the new and exciting Open Science practices, which encourage replication and enhance the trustworthiness of research. In addition, the book explains. Sample size determination is an essential step in planning a clinical study. It is critical to understand that different study designs need different methods of sample size estimation.

Although there is a vast literature discussing sample size estimation, incorrect or improper formulas continue to be applied. This article reviews basic statistical concepts in sample size estimation, discusses. You can read in Cox and Oakes book Section Here we need to think of the distribution function F(t) as an (in nite dimensional) parameter, and we try to nd the F^ (or S^ = 1 F^) that maximizes a nonparametric likelihood.

Such a MLE is called a NPMLE. As. Estimating the contributions of population density and climatic fluctuations to interannual variation in survival of Soay sheep. J Anim Ecol. ; – doi: /jx. Mysterud A, Ostbye E. Cover as a habitat element for temperate ungulates: effects on habitat selection and demography.

Rangelands provide 10% of the global meat supply and support an estimated million pastoralists and the herds of nearly 1 billion camelids, cattle, and smaller livestock, in addition to yaks, horses, reindeer, and other ungulates.

The effects of grazing on rangeland biodiversity include the removal of biomass, trampling and destruction of. In robust statistics, robust regression is a form of regression analysis designed to overcome some limitations of traditional parametric and non-parametric sion analysis seeks to find the relationship between one or more independent variables and a dependent n widely used methods of regression, such as ordinary least squares, have favourable properties if their.

The statistical significance of the maternal effect on JW was assessed using a likelihood ratio test (Meyer ) to compare model 1 with a simpler model in which the maternal genetic effect was omitted. The difference in log‐likelihood scores, multiplied by −2, is distributed as χ 2 with one degree of freedom.

Furthermore, we estimate this effect for each subject, regardless of which treatment was actually received. Averages of these effects over all the subjects in the data estimate the ATE.

We could also use figure 4 to motivate a prediction of the outcome that each subject would obtain for each treatment level, regardless of the treatment recieved. Interpreting Beta: how to interpret your estimate of your regression coefficients (given a level-level, log-level, level-log, and log-log regression).

Assumptions before we may interpret our results. The Gauss–Markov assumptions* hold (in a lot of situations these assumptions may be relaxed - particularly if you are only interested in an approximation - but for now assume they strictly hold).

Furthermore, the bulk of the current evidence supporting an effect of selective harvest on ungulate species has been obtained from studies of mountain sheep, where extensive pedigrees and assessments of phenotypic and genotypic changes in horn size have demonstrated that harvest can reduce the size of weaponry through time (Coltman, A lumber company must estimate the mean diameter of trees in an area of forest to determine whether or not there is sufficient lumber to harvest.

They need to estimate this to within 1 inch at a confidence level of 99%. Suppose the tree diameters are normally dis. With regards to larger wild ungulates, Schieltz and Rubenstein found more negative (n = 86) than positive (n = 34) ungulate responses overall.

Maximum Likelihood Estimation. Count models are estimated using maximum likelihood. Log likelihood: Computationally, the log of the likelihood function is easier to work with. Analysis proceeds iteratively until the log likelihood converges. Larger (in the closer to zero sense) log likelihoods are Coefficients in log-log regressions ≈ proportional percentage changes: In many economic situations (particularly price-demand relationships), the marginal effect of one variable on the expected value of another is linear in terms of percentage changes rather than absolute changes.

In such cases, applying a natural log or diff-log transformation to both dependent and independent variables may. Stick Estimating: Highly accurate, but incredibly time consuming, stick estimating is the practice of determining total costs by listing, in order, the costs for every single component of a job.

The sheer amount of time it takes to produce a stick estimate invites errors due to. Experiment definition is - test, trial. How to use experiment in a sentence. Sheep (Ovis aries) are quadrupedal, ruminant mammals typically kept as most ruminants, sheep are members of the order Artiodactyla, the even-toed gh the name sheep applies to many species in the genus Ovis, in everyday usage it almost always refers to Ovis ing a little over one billion, domestic sheep are also the most numerous species of sheep.

The GEE procedure fits generalized linear models for longitudinal data by using the generalized estimating equations (GEE) estimation method of Liang and Zeger (). The GEE method fits a marginal model to longitudinal data and is commonly used to analyze longitudinal data when the population-average effect is of interest.

Based on this average, and the estimate of 2, wolves in Minnesota, wolves kill the equivalent of ab to 48, adult-sized deer per year. In comparison, Minnesota hunters take aro deer per year in wolf range (overfor the entire state) and several thousand are killed during collisions with vehicles.

A study on density estimate and habitat association of Cape buffalo (Syncerus caffer caffer) in Jorgo-Wato Protected Forest, Ethiopia, was carried out from encompassing the wet and dry density of Cape buffalo was estimated indirectly through faecal standing crop and faecal accumulation rate dung count methods.

Lagged explanatory variables are commonly used in political science in response to endogeneity concerns in observational data. There exist surprisingly few formal analyses or theoretical results, however, that establish whether lagged explanatory variables are effective in surmounting endogeneity concerns and, if so, under what conditions.

The Amur tiger population reached its peak in the mids when all suitable habitat was occupied. A die-off of wild boar due to disease in and a fall in red deer and roe deer numbers due to exceptional snowfalls in led to food shortages for tigers, forcing them into settlements in search of food, and of course also into confrontation with humans (according to official data.

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An odds ratio of 1 is equivalent to a coefficient estimate of 0 in a linear regression and implies that the explanatory (or predictor) variable has no effect on the response variable. The estimated odds ratio of suggests that the odds of purchase increase by % for each dollar increase in coupon value.

The waterlogging due to rising water table, particularly along the rivers, rendering soil unfit for cultivation, covers million hectare land. Similarly, increased dependence on intensive agriculture and irrigation also resulted in salination, alkalination and water logging in the some irrigated area of the country.Join the Kickstart Prevention starts today.

Join the Day Vegan Kickstart. Day Kickstart. In his book Making It Count, Stanley Lieberson devoted a whole chapter to arguing against the nearly universal presumption that causal effects are he meant is that for both theorists and data analysts, there is usually an implicit assumption that if a one-unit increase in variable X produces a change of B units in variable Y, then a one-unit decrease in X will result in a.