Re: [R-sig-eco] interpretation of interaction between explanatory variables
It's difficult to give definitive advice about what it means, but the simplest approach is to look at what it means: plot the model and see what it looks like. Basically, the interaction says that as the variables both increase, the relationship gets less negative. The details depend on the ranges of the variables, hence plotting the results is helpful. I would write some code, but that would probably mainly show that I'm out of date with R. But you could use expand.grid() to create new data to predict, use predict() to predict it, and then plot it as several lines on one plot (e.g. plot against C.abundances, with one line for each value of C.diversity). Bob On 05/08/2013 02:56 PM, Iris Kröger wrote: Dear list members, I want to analyse the impact of a competitor community (i.e. community abundances on the one hand and community species diversity on the other hand) on mosquito larval populations of species A and B. Each variable on its own has a negative impact on mosquitoes - but when both variables are interacting, there is a positive impact... How can I interpret that? For mosquito A only C.diversity has a significant impact - but the interaction between C.abundances and C.diversity is significant? What does that mean? I used the model: lm (mosquito ~ C.abundances * C.diversity) output Mosquito A: Estimate Std. Error t value Pr(|t|) (Intercept) -0.2120 0.1159 -1.829 0.074855 . C.abundances -0.1277 0.1616 -0.790 0.434067 C.diversity -0.5787 0.1385 -4.178 0.000155 *** C.abundances:C.diversity 0.4096 0.1712 2.393 0.021476 * Output Mosquito B: Estimate Std. Error t value Pr(|t|) (Intercept) -0.2900 0.1220 -2.377 0.02233 * C.abundances -0.3856 0.1701 -2.266 0.02891 * C.diversity -0.3470 0.1458 -2.381 0.02213 * C.abundances:C.diversity 0.5367 0.1801 2.980 0.00489 ** Thanks a lot for your help! Iris [[alternative HTML version deleted]] ___ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology -- Bob O'Hara Biodiversity and Climate Research Centre Senckenberganlage 25 D-60325 Frankfurt am Main, Germany Tel: +49 69 798 40226 Mobile: +49 1515 888 5440 WWW: http://www.bik-f.de/root/index.php?page_id=219 Blog: http://blogs.nature.com/boboh Journal of Negative Results - EEB: www.jnr-eeb.org [[alternative HTML version deleted]] ___ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
[R-sig-eco] anyone using vegan
Hi all, Anyone experienced with vegan, or possibly other R packages for ecological data? I am working with a database that includes relative abundance data that can be exported as densities by locations or date and summered by night as these are bats. So the question is the data format needed to generate rarefaction curves, species association metrics, diversity indices and the rest of the usual ecological analytics in vegan or other R packages that include ecological data processing. Once I have the output from the Access DB defined I can automate generation of the files to open in R and run the required modules. Anyone able to provide some suggestions/guidance? I need to create the export form in Access so that all is in the correct format to be opened in R and the DF is correct for eh package(s). Once processed by vegan etc. then write the results to a file. Tnx. Bruce -- Bruce W. Miller, Ph.D. Conservation Ecologist Neotropical Bat Projects office details 11384 Alpine Road Stanwood, Mi. 49346 Phone (231) 679-6059 ___ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
[R-sig-eco] betapart and nms
I'm working on a large bacterial dataset, 700 samples with ~5600 species (rare species 100 observations have been removed). The samples are from experimental plots from 6 ecozones. I've done nms, betadisp, and permanova using several dissimilarity measures (jaccard, sorenson, Yuen's theta). Ecozone explains the vast majority of the difference between the samples using those measures. I'm really interested in trying to find treatment effects so have also tried betapart-specifically trying to see if nestedness increases in the harsher treatments. Here is where I need input from the list. beta.sim gives a similar ordination to the dissimilarity measures and the expected step down in stress as I increase number of dimensions. However beta.sne is very strange and I don't know how to interpret it. The stress in 1d is 0.6, but drops to 0 in 2d. When I plot the 2d solution I get a horseshoe-it looks like the typical distortion in a PCA of nonlinear data. I've run a lot of NMS on these types of nonnormal, empty, huge matrixes and have never seen this sort of pattern in the ordination and my stress never goes much below .15. I'm not sure how to assess what beta.sne is calculating to help me make sense of this result. I've subsampled my species matrix a few times just to make sure something strange didn't happen with the subsampling. thanks for reading, Kendra Here's what I've run so far ##betapart #subsample matrix in mother to 1950 observations per sample b03_f100_1_1 - read.table(bac_03_f100_sub1, row.names=1, header=T) #convert to presence/abscence b03_f100_1_pa - decostand(b03_f100_1_1, method=pa) #betapart bac03_bp-beta.pair(b03_f100_1_pa, index.family=sorensen ) #nms on betapart objects scree_bsim1-nmds(bac03_bp$beta.sim, mindim=1, maxdim=6, nits=10) #stress: 1d .65, 2d .35, 3d .25, 4d .19 scree_bsne1-nmds(bac03_bp$beta.sne, mindim=1, maxdim=6, nits=10) #stress: 1d .6, 2d 0, 3d 0... bac_bsim_nms- metaMDS(bac03_bp$beta.sim, k=3, trymin=50, trymax=250, wascores=FALSE) bac_bsne_nms- metaMDS(bac03_bp$beta.sne, k=2, trymin=50, trymax=250, wascores=FALSE) -- Kendra Maas Mitchell, Ph.D. Post Doctoral Research Fellow University of British Columbia ___ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
