search for: algal

...rying to run, which returns with the error code above. > data pond d13C d15N 1 A3 -2.07 6.06 2 F4 -2.39 1.3 3 K3 -2.11 1.70 > tef tefsources tefMeand13C tefSDd13C tefMeand15N tefSDd15N 1 Copepoda 0.4 1.3 3.4 0.99 2 Algal Paste 0.4 1.3 3.4 0.99 3 Amphipoda 0.4 1.3 3.4 0.99 > model1 <- siarmcmcdirichletv4(data, source, tef, concdep = 0, > iterations=500000, burnin=50000, howmany=50000, thinby=15, prior = rep(1, > nrow(sources)), siardata=lis...

Dear all, I want to compare the efficiency of 2 methods in extracting proteins from algal samples. I collected 6 independant algal samples and I extracted 3 by the method 1 and 3 others by the method 2. So I have 2 groups of 3 samples, that are not paired. I would like to know if the results obtained by these 2 methods are significantly different, I hope method 2 to be more efficient th...

Hi, I'm trying to set up R to run a simulation of two populations in which every 3.5 days, the initial value of one of the populations is reset to 1.5. I'm simulation an experiment we did in which we fed Daphnia populations twice a week with algae, so I want the initial value of the algal population to reset to 1.5 twice a week to simulate that feeding. I've use for loops and if/else loops before but I can't figure out how to syntax "if t is in this vector of possible t values, do this command, else, do this command" if that makes sense. Here's what I have (and...

Help! model1 <- siarmcmcdirichletv4(data, source, tef, concdep=0, 500000, 50000) Error in matrix(1, ncol = (numsources + numiso) * numgroups, nrow = (siardata$iterations - : invalid 'ncol' value (too large or NA) In addition: Warning message: In Ops.ordered((numsources + numiso), numgroups) : '*' is not meaningful for ordered factors Previous message, but more problems:

Hi, I am looking at the effect of allelochemicals produced by two freshwater macrophyte species on two different algal species at different days. I am comparing the effect of each macrophyte on each algae at each day. I received help from someone doing the LMEM (Linear mixed-effect models) and he told me to do ANOVA to analyse the LMEM. However, I received these feedback from my examinor; 1. An Analysis of Varianc...

Hi, I am currently trying to do a GLMM on a dataset with percent cover of seagrass (dep. var) and a suite of explanatory variables including algal (AC) and epiphyte cover (EC), rainfall, temperature and sunshine hours. M2=glmer(SG~AC+EC+TP+SS+RF+(1|Location/fSi/fTr), family=binomial,data=data,nAGQ=1) As the dependent variable is percent cover, I used a binomial error structure. I also have a random effect due to nested of the data collectio...

I am trying to investigate the interaction term in the below. The paradigm in aquatic systems is that algal production is either nitrogen (TIN) or Phosphorus limited, and I am trying to investigate this- what is the best way to go about investigating the interaction term. I have some thoughts on the above, but I will withhold them to see what others think. Thanks for your help. d <- (structure(lis...

...flasks with culture medium with algae) were randomly divided into 3 groups ("c", "t1", "t2"). There is no need for inclusion of the random effect of the intercept, because the nine sample units are homogeneous among each other (samples taken from the same culture). The algal concentration was measured every two days for 10 days. The goal is to test differences between treatments. I estimated a model with only the intercept and the interaction Group * Day to test which is the best: library(nlme) library(lme4) Day = rep(c(0,2,4,6,8,10),each=9) Group = rep(c("c&quo...

Consider the following situation: we have quantified algal concentrations for a variety of species using many samples at each of three years. It seems to make sense to generate a line plot (matplot-like), with each species plotted as a separate line, with the points connected to emphasize the temporal pattern. The problem: lots of overlapping error bar...

Hi, I'm trying to analyse a hierachical design and am running into some trouble. Clearly I don't fully understand "Error" and I was hoping someone could set me straight. We measure percentage algal cover in each of 5 quadrats from each of 16 patches where 4 treatments are randomly allocated to a patch. First suppose patches are coded 1 to 16. then the following gives the results I would expect. > Algae <- c(0, 0, 0, 6, 2, 0, 0, 0, 0, 0, 0, 0, 0, 4, 1, 0, + 0, 0, 13, 0, 23,...

...ced or unbalanced experimental designs." (I presume 'This' refers to aov) and "|aov| is designed for balanced designs, and the results can be hard to interpret without balance" So, do I use it for unbalanced designs? Thanks, AJ -- Dr Albertus J. Smit (Marine Ecologist/Algal Biologist) School of Biology and Conservation Science Faculty of Science University of KwaZulu-Natal Westville Campus P/B X54001 Durban 4000 South Africa Tel. (031) 260 7472 Fax (031) 260 7364 -------------------------------------------------------------------- Please find our disclaimer at http...

Dear Rich, It depends how the data is generated. Although I am not an expert in ecology, I can explain it based on a biomedical example. Certain variables are generated geometrically (exponentially), e.g. MIC or Titer. MIC = Minimum Inhibitory Concentration for bacterial resistance Titer = dilution which still has an effect, e.g. serially diluting blood samples; Obviously, diluting the