尽管提供了社区矩阵，纯素dbrda物种得分还是空的 [英] vegan dbrda species scores are empty despite community matrix provided
问题描述
我已经使用素食主义者社区生态软件包在R中执行了基于距离的冗余分析"(dbRDA).我想在dbRDA结果的排序图中显示(鱼类)营养群体对样本之间差异(营养级别鱼群的大量数据)的相对贡献. IE.将箭头和营养级别组名称覆盖到协调图上，其中箭头线的长度指示对相似性的相对贡献.据我所知，应该可以通过vegan::scores()函数进行访问，或将其与dbrda.model$CCA$v对象一起存储.
I have performed "Distance based redundancy analysis" (dbRDA) in R using the vegan community ecology package. I would like to show the relative contribution of (fish) trophic groups to the dissimilarity between samples (abundance data of trophic level fish assemblages) in an ordination plot of the dbRDA results. I.e. Overlay arrows and trophic level group names onto the ordination plot, where the length of the arrow line indicates the relative contribution to dissimilarity. This should be accessible via the vegan::scores() function, or stored with the dbrda.model$CCA$v object, as I understand.
但是，使用dbrda()时物种得分为空(NA).我了解dbrda函数需要在函数内定义社区矩阵，以便提供物种得分.我已经定义了它，但是仍然无法产生物种分数.令我感到困惑的是，当我在纯素包装中使用capscale()时，具有相同的物种-群落和环境变量数据，并在各自的功能中制定相同的公式，就会产生物种评分.素食主义者中的dbrda是否能够产生物种得分?这些分数与capscale产生的分数有什么不同(使用相同的数据和公式时)?我提供了一个数据示例和使用的公式. (我对实际绘制获得的物种得分很有信心-因此将代码限制为产生物种得分.)
However, species scores are empty (NA) when using dbrda(). I understand that the dbrda function requires the community matrix to be defined within the function in order to provide species-scores. I have defined it as such, but still unable to produce the species scores. What puzzles me is that when I use capscale() in the vegan package, with the same species-community and environmental variable data, and formulated the same within the respective functions, species scores are produced. Is dbrda in vegan able to produce species scores? How are these scores different to that produced by capscale (when the same data and formula are used)? I provide an example of my data, and the formula used. (I am fairly confident in actually plotting the species-scores once obtained - so limit the code to producing the species-scores.)
#Community data matrix (comm.dat): site names = row names, trophic level = column names
>head(comm.dat[1:5,1:4])
algae/invertebrates corallivore generalist carnivore herbivore
h_m_r_3m_18 1 0 3 0
h_m_r_3m_22 6 4 8 26
h_m_r_3s_19 0 0 4 0
h_m_r_3s_21 3 0 7 0
l_pm_r_2d_7 1 0 5 0
> str(comm.dat)
num [1:47, 1:8] 1 6 0 3 1 8 11 2 6 9 ...
- attr(*, "dimnames")=List of 2
..$ : chr [1:47] "h_m_r_3m_18" "h_m_r_3m_22" "h_m_r_3s_19" "h_m_r_3s_21" ...
..$ : chr [1:8] "algae/invertebrates" "corallivore" "generalist carnivore" "herbivore" ...
# environmental data (env.dat): Already standardised env data.
>head(env.dat[1:5,1:3])
depth water.level time.in
-0.06017376 1.3044232 -1.7184415
-0.67902862 1.3044232 -1.7907181
-0.99619174 1.3044232 -1.7569890
-1.06581291 1.3044232 -1.7762628
2.39203863 -0.9214933 0.1703884
# Dissimilarity distance: Modified Gower (AltGower) with logbase 10 transformation of the community data matrix
> dis.comm.mGow <- vegan::vegdist(x = decostand(comm.dat, "log", logbase = 10), method = "altGower")
# Distance based RDA model: Trophic level data logbase transformed modified Gower distance, constrained against the interaction of dept and water level (tide), and the interaction of depth and time of day sampled`
> m.dbrda <- dbrda(formula = dis.comm.mGow ~ depth*water.level + depth*time.in, data = env.dat, scaling = 2, add = "lingoes", comm = decostand(comm.dat, "log", logbase = 10), dfun = "altGower")
# Check species scores: PROBLEM: No species level scores available
> m.dbrda$CCA$v
dbRDA1 dbRDA2 dbRDA3 dbRDA4 dbRDA5
[1,] NA NA NA NA NA
# OR pull species scores using scores(): Also does not show species scores...
>scrs <- scores(m.dbrda,display="species"); scrs
dbRDA1 dbRDA2
spe1 NA NA
attr(,"const")
[1] 6.829551
# when replacing dbrda with capscale, species scores are produced, e.g.
> m.cap <- capscale(formula = dis.comm.mGow ~ depth*water.level + depth*time.in, data = env.dat, scaling = 2, add = "lingoes", comm = decostand(comm.dat, "log", logbase = 10), dfun = "altGower")
> m.cap$CCA$v[1:5,1:3]
CAP1 CAP2 CAP3
algae/invertebrates 0.2044097 -0.04598088 -0.37200097
corallivore 0.3832594 0.06416886 -0.27963122
generalist carnivore 0.1357668 -0.08566365 -0.06789812
herbivore 0.5745226 -0.45647341 0.73085661
invertebrate carnivore 0.1987651 0.68036211 -0.19174283
推荐答案
dbrda()函数实际上无法获得物种分数.但是，如果我们在纯素中具有以下功能，则可以添加这些分数:
The dbrda() function really does not get the species scores. However, if we had the following function in vegan, you could add those scores:
#' Add Species Scores to Ordination Results
#'
#' @param object Ordination object
#' @param comm Community data
#'
#' @return Function returns the ordination object amended with species
#' scores.
#'
#' @rdname specscores
#' @export
`specscores` <-
function(object, comm)
{
UseMethod("specscores")
}
#' importFrom vegan decostand
#'
#' @rdname specscores
#' @export
`specscores.dbrda` <-
function(object, comm)
{
comm <- scale(comm, center = TRUE, scale = FALSE)
if (!is.null(object$pCCA) && object$pCCA$rank > 0) {
comm <- qr.resid(object$pCCA$QR, comm)
}
if (!is.null(object$CCA) && object$CCA$rank > 0) {
v <- crossprod(comm, object$CCA$u)
v <- decostand(v, "normalize", MARGIN = 2)
object$CCA$v <- v
comm <- qr.resid(object$CCA$QR, comm)
}
if (!is.null(object$CA) && object$CA$rank > 0) {
v <- crossprod(comm, object$CA$u)
v <- decostand(v, "normalize", MARGIN = 2)
object$CA$v <- v
}
object
}
我不知道我们是否要具有此功能(以及其他方法)，但是如果您在会话中获取它，则可以使用它.
I don't know if we are going to have this function (with other methods), but you can use it if you source it in your session.
这篇关于尽管提供了社区矩阵，纯素dbrda物种得分还是空的的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！
