search for: veget

...<- matrix(c(0.07,0,0.03,0.00,NA,0.00, 0.09,0.166666667,0.31,0.42,NA,0.00, 0.00,0,0.00,0.00,NA,0.00, 0.00,0,0.00,0.00,NA,0.00, 0.26,0.166666667,0.19,0.00,NA,0.00, 0.58,0.666666667,0.47,0.58,0,0.00), nrow = 6, ncol = 6, dimnames = list(c("Vegetative", "Vegetative with herbivory", "Reproductive", "Reproductive with herbivory", "Dormant", "Dead"), c("Vegetative", "Vegetative with herbivory", "Reproductive",...

...file called worms.txt at =20 http://www.imperial.ac.uk/bio/research/crawley/therbook <http://www.imperial.ac.uk/bio/research/mjcraw/therbook/index.htm>=20 =20 the idea is to extract a subset of the rows, sorted in declining order of worm density, with only the maximum worm density from each vegetation type: =20 worms<-read.table("c:\\temp\\worms.txt",header=3DT) attach(worms) names(worms) [1] "Field.Name" "Area" "Slope" "Vegetation" "Soil.pH"=20=20=20=20=20 [6] "Damp" "Worm.density"...

Hi R listers, I am trying to group distances of nests to the vegetation into classes that are define by (0-5m, 6-10m, 11-15m, 16-20m, 21-25m, 26-30m, 31-35m, 36-40m, 41-45m, 46-50m, 51-55m, 56-60m). Each row is a nest and all the distances to the vegetation is in a column. In plyr, I have tried - below script but I think I am going about this the wrong way and...

First I would like to say thank you for taking the time to read it.Here is my problem. I am running a lmer analysis for binary longitudinal (repeated measures) data. Basically, I manipulated fruits and vegetation to two levels each(present and absent) and I am trying to access how these factors affect mice foraging behavior. The design consist of 12 plots, divided in 3 blocks. So each block has 4 plots assigned to one of the following treatments. Fruit intact and Vegetation intact Fruit intact and...

...zodon intermedius", "Schizodon intermedius", "Schizodon intermedius", "Schizodon intermedius"), Weight = c(0.06, 0.01, 0.01, 0.33, 0.01, 3.5, 0.01, 0.04, 0.01, 0.01, 0.38, 0.29, 0.04, 0.03, 0.11, 0.04, 0.04, 0.03, 0.01, 0.01), Food.item = c("Fish", "Vegetal", "Alga", "MNI", "Sediment", "Fish", "Alga", "MNI", "Alga", "MNI", "Vegetal", "Vegetal", "Vegetal", "Alga", "Vegetal", "Alga", "MNI", "Se...

Hi everyone. I am trying to add a formula to my data using the groupedData function. My experiment consists of randomized block design using fruits, vegetation and time as factors. The idea is to see if fruits, vegetation and time explain the abundance of mice. I am using tree density as a covariate. So I tried to fit the following structure to my data. > traps<-groupedData(mice~tree|plotID,outer=~time*fruit*veget|block,data=trap) but time and...

Hello all, I'm new in R, and I have a data-frame like this (dput information below): Specie Fooditem Occurrence Volume 1 Schizodon vegetal 1 0.05 2 Schizodon sediment 1 0.60 3 Schizodon vegetal 1 0.15 4 Schizodon alga 1 0.05 5 Schizodon sediment 1 0.90 6 Schizodon sediment 1 0.30 7 Schizodon sedime...

...imilar in the forum, so here's my problem (I'm no expert in R nor statistics): I have a data set of 59.000 cases with 9 variables each (fractional coverage of 9 different plant types, such as deciduous broad-leaved temperate trees or evergreen tropical trees etc.), which was generated by a vegetation model. In order to evaluate the quality of the vegetation model's output, I want to compare it to a land-cover data set which has 23 different land-cover types (such as needle leaved evergreen forest, dense broad-leaved forest, barren, etc.). A statistician advised me to use the randomFore...

I am trying to fit a formula to my data, but I just can't find the right way to do it. My experiment consists of manipulating FRUITS and VEGETATION to two levels each(intact or removed) on 12 experimental plots. This leaves me with 4 treatment combinations Fruit intact Vegetation removed Fruit int. Veget int. Fruit rem. Veget rem. Fruit rem. Veget. intac those treatements are distributed accross 3 blocks. Plots were repeated surveye...

...to advise on which package would offer the best approach for producing a model able to predict the probability of species occupation based upon a range of variables, some of them catagorical (eg. ten soil types where the numbers assigned are not related to any qualitative/quantitative continuum or vegetation type) and others continuous such as field size or vegetation height. I have tried using the TREE package but the models produced seem too simplistic and discard most variables with the result that there is no predictive power in the result. I would expect that there will be interactions betw...

...on Hadley's webpage (http://had.co.nz/ggplot2/geom_errorbar.html), but it still doesn't make any sense to me. df <- data.frame(trt = factor(c("intact", "intact", "removed", "removed")), coon = c(0.093, 0.06, 0.057, 0.09), group = factor(c("veget", "fruit", "veget", "fruit")), se = c(0.01, 0.01, 0.02, 0.026)) limits <- aes(ymax = coon + se, ymin=coon - se) p<-ggplot(df, aes(fill=group, y=coon, x=trt)) p+geom_bar(position="dodge",stat="identity") dodge <- position_dodge(width=...

A colleague has just passed me this interesting address: http://cc.oulu.fi/~jarioksa/softhelp/vegan.html "Vegan: R functions for vegetation ecologists" "Vegan package is intended to help vegetation ecologists and other community ecologists to use R. It is not a completely self-contained package, but it complements other R functions. .../... At this first stage, vegan implements some of the functionality of Peter Michi...

I am trying to run an ANCOVA with defined error terms. Thus I have to use AOV and not lm. my response variable is proportion of mice paw prints on track plates. These plates were placed on plots that had vegetation and fruit manipulated to two levels each (present or absent), and were sampled monthly for 14 months (repeated measures). The fully crossed factor design was also blocked. My sample size is just 3 and I cannot run the full model because I would ran out of degrees of freedom. I measured raccoo...

Hello all, I am going slightly mad trying to create a table for running co-correspondence analysis. What I have is seed bank and vegetation data, and my aim is to see if the vegetation found in a site (containing several seed bank samples) can predict the composition of a seed bank sample within that site. So for this I need two tables with matching rows. I have created an empty matrix, where the rows correspond to the seed...

Hi, This is a question regarding technique rather than an R specific issue. I have been asked to evaluate a 30+ year long term continuous survey of bird presence/absence data that has an associated ocular estimate of the vegetation community percent coverage. The data are organized by subpopulations (5), and by year ( 1991 - present). We are interested in gaining understanding on whether bird presence is 1) related to vegetation community cover and 2) whether that relationship is variable over the period of record. Ul...

Hi, I hope someone knows the answer to this or has a real good reference about it (I am using Legendre & Legendre, Numerical Ecology, 1998).... My data is a data.frame with locations as rows and vegetation assemblages / species as columns. I've done a PCA, a correspondance analysis (CA) using ca in ca package and a detrended correspondance analysis (DCA) using decorana from vegan package. As far as i understand what i've done .... the relationships between vegetation categories and locat...

Hello all, I am currently working with rpart to classify vegetation types by spectral characteristics, and am comming up with poor classifications based on the fact that I have some vegetation types that have only 15 observations, while others have over 100. I have attempted to supply prior weights to the dataset, though this does not improve the classificatio...

...ge annual precipitation for the past five years is 127.7mm, and the average annual evaporation is 2623mm); on the other hand, serious deteriorated water quality (about 190,000 tons salinity carried by irrigated water from Shiyang River).* *3. **Traditional theory holds that the restoration of vegetation will increase the evapotranspiration, then leading to groundwater decline.* *4. **Let’s set aside the question of how we desalinated the saline water. * * * *Thank you!* * * *Sincerely,* * * *YU* -- ...........................<?}))><..................... ) ) ) ) ) ( (...

...with NA-values and RDA (R vegan) and an adaptated RDA code due to a specific study design (including a second matrix). I am calculating a RDA for a dependent matrix (different variables for tree performance) and different explanatory variables (species identitiy, diversity, soil data, ground vegetation). I would very much appreciate some help with my txt input file for the vegan function. As for standard RDA's I have different plots (lines, the dependent matrix) and for each plot a value for diversity, soil and vegetation (in columns, the environmental matrix). I additionally have...

...ntil I decide that maybe one will do close to what I want. I wonder if there is any way to improve how these packages are displayed on the site and help with this decision. I wonder if the community as a whole can come up with some broader categories such as Bayesian, spatial statistics, bootstrap, vegetation analysis, circular statistics, robust statistics, etc., and the authors of the package can choose 1 or 2 or how many categories they think their package fits the most. On the web page we can have a list of those very broad categories and within each category we can have in alpha order the pack...