search for: herbivore

....Invert.Abundance, Predatory.Fish.Abundance, Prev.Year.Herbivorous.Invert.Abundance, Prev.Year.Herbivorous.Fish.Abundance, Herbivorous.Invert.Abundance, Herbivorous.Fish.Abundance, Kelp.Abundance, Prev.Year.Kelp.Abundance, Mean.Temp.C, Prev.Year.Herbivore.Abundance) #na.rm=TRUE to deal with a few rows of missing data fish.invert.covar<-var(fish.invert.data, na.rm=TRUE) fish.invert.model<-specify.model() Prev.Year.Predatory.Invert.Abundance -> Prev.Year.Herbivorous.Invert.Abundance, pred.invert.top.down, NA Predatory.Invert.Abundance -...

Greetings. I'm a Master's student working on an analysis of herbivore damage on plants. I have a tried running a glm with one categorical predictor (aphid abundance) and a binomial response (presence/absence of herbivore damage). My predictor has four categories: high, medium, low, and none. I used the "ordered" function to sort my categories for a glm. ah...

...ar all, I'm quite sure that this is a stupid question, but I'll ask anyway. I want to perform an ANCOVA with two continuous factors and three categorical factors. Plant population growth rate (GR) = dependent variable Seed reduction due to herbivory (SR) = continuous explanatory variable Herbivore species (HS, 2 levels) = categorical explanatory variable Population (Pop, 24 levels) = categorical explanatory variable Population size (Popsize) = continuous explanatory variable Year (Year, 16 levels) = categorical explanatory variable My model is technically simple: model<-aov(GR~SR*HS*Pop...

...ase kindly advise how to modify the code. thank you. (It works with panel.bwplot.intermediate.hh) Elaine code library(HH) # data input dataN <-read.csv("H:/R_data/Mig_bird_586.csv",header=T, row.names=1) dim(dataN) dataN[1,] str(dataN) diet.code <- c("Herbivore", "Omnivore", "Carnivore") Diet.colors <- c("forestgreen", "darkblue","red2") levels(dataN$Diet) <- diet.code # graph par(mai=c(1.03,1.03,0.4,0.4)) par(new=T) xyplot(GE_distance~Diet, data=dataN, xlab=list(&quo...

...want to draw a xyplot. Its dots will have three colors: red for meat, green for vegetable, and blue for both. I used the code below but could not make the dot in the same group show the same color. Please kindly advise how to modify it. Thank you. code library (lattice) diet.code <- c("Herbivore", "Omnivore", "Carnivore") Diet.colors <- c("forestgreen", "darkblue","red2") levels(dataN$Diet) <- diet.code # graph par(mai=c(1.03,1.03,0.4,0.4)) par(new=T) xyplot(GE_distance~Diet, data=dataN, xlab=list(&quo...

Dear members of the R help list, I want to do a hierarchical glm with binomial family but am unsure about how to write the syntax which involves nesting. I want to test whether the risk of being attacked by Herbivores for Meadowsweet plants is significantly dependent on the Distance to heterospecific source plants. Dependent variable = Herbivory (yes/no) Explanatory continuous variable = Distance to heterospecific source plant Distance should be nested within Subpopulation which in turn should be nested withi...

...si(link="log", variance="mu")) par(mfrow=c(2,2)) plot(model2) to test the effect of grazing exclusion of feral horses for a Phd with following factors: Treatment - 3 levels which are grazed controls (C), ungrazed horse exclosures (H)with 3 wire strand fence to allow other herbivores but not horses and ungrazed full netting exclosures to exclude all herbivores (A) Site - 6 levels for 6 Sites which are considered fixed Time - 6 levels also for 6 different monitoring or time periods which is where the repeated measures comes in In SPSS there is the option for Bartlett's...

...si(link="log", variance="mu")) par(mfrow=c(2,2)) plot(model2) to test the effect of grazing exclusion of feral horses for a Phd with following factors: Treatment - 3 levels which are grazed controls (C), ungrazed horse exclosures (H)with 3 wire strand fence to allow other herbivores but not horses and ungrazed full netting exclosures to exclude all herbivores (A) Site - 6 levels for 6 Sites which are considered fixed Time - 6 levels also for 6 different monitoring or time periods which is where the repeated measures comes in In SPSS there is the option for Bartlett's...

...lose to this access spur. So I do three analyses when relevant, one looking at the three factors and then taking site out and replacing it with graze and then dam. It is a grazing exclusion experiment to test effects of feral horse grazing on a number of variables whereby C=controls so open to all herbivores, HE= Horses excluded but allowing other herbivores such as macropods, rabbits, and AHE= is a fully enclosed high wire fence excluding all herbivores. One treatment exclosure type was erected at each site but within these 30m2 exclosures there were two randomly located 5x6m plots so that is why th...

Dear All! It's now weeks that I'm going crazy with R, and as I'm a new user I now ask for help (also because I still have only a few days to finish..)... So shortly I describe you my Experiment in which I was looking for the decomposition of herbivore dung under different treatments: I made a box design experiment which is structured in the following way: I collected dung from 2 species (Wildebeest and Giraffe) and put for each species 8 pellets in different pots. I used 2 water treatments for the pots: wet (by adding water) and dry and two sha...

...ons (> 10 observations per parameter is what you are ideally looking for). b) Have a look at Anderson and Burnham's book of 2002 about multi model inference if you want to understand how to proper use AIC. What I'm doing for my analysis at the moment (count data of two species, host and herbivore): 1) I checked which of my parameters explained the abundance of the species , using GLMs and bootstrapping of an LR-test to check if the model with the parameter is better than one without the parameter ( one way to deal with outliers and extrema) 2) Then I build all combinations of those parame...

CRAN (and crantastic) updates this week New packages ------------ * disclapmix (0.1) Maintainer: Mikkel Meyer Andersen Author(s): Mikkel Meyer Andersen and Poul Svante Eriksen License: GPL-2 http://crantastic.org/packages/disclapmix disclapmix makes inference in a mixture of Discrete Laplace distributions using the EM algorithm. * EstSimPDMP (1.1) Maintainer: Unknown Author(s):

...28f6446fo7770d24a6cb0d995@mail.gmail.com> Content-Type: text/plain; charset=ISO-8859-1 Dear members of the R help list, I want to do a hierarchical glm with binomial family but am unsure about how to write the syntax which involves nesting. I want to test whether the risk of being attacked by Herbivores for Meadowsweet plants is significantly dependent on the Distance to heterospecific source plants. Dependent variable = Herbivory (yes/no) Explanatory continuous variable = Distance to heterospecific source plant Distance should be nested within Subpopulation which in turn should be nested withi...

...text/plain; charset="iso-8859-1" Dear All! It's now weeks that I'm going crazy with R, and as I'm a new user I now ask for help (also because I still have only a few days to finish..)... So shortly I describe you my Experiment in which I was looking for the decomposition of herbivore dung under different treatments: I made a box design experiment which is structured in the following way: I collected dung from 2 species (Wildebeest and Giraffe) and put for each species 8 pellets in different pots. I used 2 water treatments for the pots: wet (by adding water) and dry and two sha...