spacodi.calc(spacodiR)
spacodi.calc()所属R语言包：spacodiR
measuring spatial and phylogenetic structuring of diversity in communities
测量空间的多样性和系统发育结构在社区
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Considering species-, phylogenetic-, or trait-diversities, this function measures diversity structuring of community samples.
考虑物种，系统发育，或性状的多样性，这种的功能测量多样性结构的社区样本。
用法----------Usage----------
spacodi.calc(sp.plot, phy = NULL, sp.traits = NULL, all.together = TRUE, prune = TRUE, pairwise = FALSE, ...)
参数----------Arguments----------
参数：sp.plot
a community dataset in spacodiR format (see as.spacodi)
社区spacodiR格式的数据集（见as.spacodi）
参数：phy
a phylogenetic tree of class phylo or evolutionary distance matrix between species (see cophenetic.phylo)
类phylo或物种之间的进化距离矩阵的进化树（见cophenetic.phylo）
参数：sp.traits
a species-by-trait(s) dataframe or a species traits distance matrix (see dist)
一个物种的性状（S）数据框，或一个物种性状的距离矩阵（见dist）
参数：all.together
Boolean; whether to treat all traits together or separately
布尔是否将所有性状的共同或单独
参数：prune
Boolean; whether to dynamically prune datasets if mismatches occur
布尔是否动态剪枝数据集，如果搭配不当发生
参数：pairwise
Boolean; whether to return pairwise diversity measures amongst all plots
布尔是否返回成对的多样性的措施，其中包括所有的图
参数：...
additional arguments to be passed to match.spacodi.data
被传递match.spacodi.data的其他参数
Details
详细信息----------Details----------
spacodi.calc <STRONG>requires</STRONG> a community dataset (species-by-plots matrix; sp.plot) of numerical abundance, relative abundance, or presence | absence for plots. spacodi.calc returns statistics of diversity partitioning of plots, considering species diversity and, if additional information is provided, <STRONG>either</STRONG> trait or phylogenetic diversities among plots. If phy=NULL and sp.traits=NULL, a measure of partitioning for species diversity will be returned.
spacodi.calc<STRONG>要求</ STRONG>的社区数据集（物种图矩阵; sp.plot|缺席图）的数值丰度，相对丰度，或存在。 spacodi.calc返回统计的多样性分区图，考虑物种多样性，如果提供更多信息，<STRONG>无论是</ STRONG>的特征或图之间的系统发育多样性。如果phy=NULL和sp.traits=NULL，分区物种多样性的措施，将被退回。
In treating each pair of plots as a community unto its own, pairwise=TRUE will return estimates for diversity structuring for all pairwise combinations of plots.
在每对图作为一个社会对自己的治疗，pairwise=TRUE将返回图为两两组合的多样性结构的估计。
If a phylogeny or trait dataset is supplied with species that are not present in the community dataset (i.e., sp.plot) or vice versa, the user has the option to dynamically prune these datasets to match (prune=TRUE). If prune=FALSE and dataset mismatches occur, the function will inevitably return NaN where plots have fewer than two distinct species sampled.
如果亲缘关系或特征数据集提供的物种，在社会上的数据集不存在（即sp.plot），反之亦然，用户可以选择动态剪枝这些数据集来匹配（prune=TRUE） 。如果prune=FALSE和数据集不匹配时，该函数将不可避免地返回NaN图有少于两个不同的物种采样。
For proper display, please view the package manual online (http://cran.r-project.org/web/packages/spacodiR/spacodiR.pdf)
为了正确显示，请查看包手动在线（http://cran.r-project.org/web/packages/spacodiR/spacodiR.pdf）
GLOBAL MEASURES
全球性措施
N: number of local communities sampled
N：当地社区的采样数
n_k: number of individuals sampled in local community k
n_k：个人在当地社区k采样数
f_{ik}: observed relative abundance of species i in the local community k (∑_i{f_{ik}=1})
f_{ik}：观察到的物种的相对丰度i在当地社区k（∑_i{f_{ik}=1}）
p_{ik}: presence (1) or absence (0) of species i in the local community k
δ_{ij}: phyletic or functional (trait) distance between species i and j
δ_{ij}：种i和j的种类繁多或功能（特征）之间的距离
INDICES
指数
indices using species abundances: Mean phyletic or functional distance between two individuals in the same local community is expressed as follows:
指数的物种丰度：是指两个人在同一个本地社区的种类繁多或功能之间的距离表示如下：
This measure is sample-size corrected by the term (\frac{n_k}{n_k-1}) and is only applied where data are counts of individuals (not where data represent a relative measure of species abundances). Mean functional or phyletic distance between individuals of different species in the same local community is computed as follows:
这项措施是样本量的术语校正（\frac{n_k}{n_k-1}），并只适用于个人（而不是数据的物种丰度的相对测量）的数据计算得出的。在同当地社区的不同物种的个体之间的平均距离的功能或种类的计算方法如下：
Rao's quadratic entropy within samples (average inter-individual distance among samples) is computed either with (D_S) or without (D_S*) sample-size correction:
Rao的二次熵计算样品（样品间的个体间平均距离）内使用（D_S）或无（D_S*）样品尺寸校正：
Rao's quadratic entropy among samples (average distance between individuals from different samples) is as follows, including or excluding intraspecific comparisons (respectively):
饶的二次熵在样本（个人不同的样本之间的平均距离），包括或不包括种内比较（分别）如下：
P_{ST} integrates both species turnover and phylogenetic turnover, weighting species according to local abundances.
P_{ST}集成了两个物种的营业额及系统发育营业额，权重品种根据当地的丰度。
for phylogenetic (P_{ST}) or functional (T_{ST}) distances between individuals.
系统发育（P_{ST}）或功能（T_{ST}）个人之间的距离。
I_{ST} is a measure of species turnover accounting for local abundances, but with different properties than measures of species turnover based on species sharing. It is the analogue of G_{ST} in population genetics.
I_{ST}品种成交占当地丰度是衡量的，但比措施的物种共享的基础上成交品种具有不同的属性。这是模拟群体遗传学的G_{ST}。
in the special case of spatial partitioning of species diversity, where δ_{ij}=0 if i=j and where δ_{ij}=1 if i \neq j
在特殊情况下的物种多样性的空间分割，其中δ_{ij}=0如果i=j和δ_{ij}=1如果i \neq j
B_{ST} and U_{ST} integrate only phylogenetic or functional (phenotypic) turnover, respectively, weighting species according to local abundances.
B_{ST}和U_{ST}整合系统发育或功能（表型）的营业额，分别，权重品种根据当地的丰度。
for phylogenetic (B_{ST}) or functional (U_{ST}) distances between individuals, excluding intraspecific comparisons.
的亲缘（B_{ST}）或功能（U_{ST}个人，不包括种内比较）之间的距离。
indices using species occurrences: If we let p_{ik}=1 where species i occurs in sample k and p_{ik}=0 otherwise, we compute the following local measure of phyletic or functional distinctiveness:
指数用种发生的：如果我们让p_{ik}=1种i发生在样品k和p_{ik}=0否则，种类繁多或功能独特，我们计算以下措施：
Δ_k is the mean interspecific distance in local community k and mean distance between distinct species within local communities is then
Δ_k是在当地社区k和当地社区内不同的物种之间的平均距离间的平均距离是那么
Mean distance between distinct species among local communities is:
不同的物种在当地社区之间的距离平均为：
This formula corrects a typographic error in eq. 16 of Hardy and Senterre (2007) where j \neq i were missing.
这个公式修正式印刷错误。 16 Hardy和Senterre（2007）j \neq i人失踪。
Π_{ST} expresses phylogenetic turnover without accounting for species local abundances (it is a presence-absence version of B_{ST}):
Π_{ST}表示亲缘种当地的丰度（它是一个存在不存在版本不占营业额B_{ST}）：
assumptions:
假设：
N is much is much smaller than the total number of local communities constituting the whole community of which the sampled local communities are representative (this justifies that Δ_T and Δ_T are estimated excluding pairs of species from the same local community)
N多的是远小于总数的当地社区构成整个社会的采样地方社区代表（这证明这Δ_T和Δ_T估计不包括对种从同一本地社会）
n_k is much smaller than the total number of individuals constituting local community k (this justifies the \frac{n_k}{n_k-1} correction factors)
n_k是当地社区的个人构成的总数远小于k（这证明了\frac{n_k}{n_k-1}校正因素）
值----------Value----------
A named list of at least one element (Ist) is returned. The size of the returned list is wholly dependent upon given arguments.
至少有一个元素的命名列表（Ist）返回。在返回的列表的大小是完全依赖于给定的参数。
SPECIES DIVERSITY STRUCTURING
物种多样性结构
Ist: a measure of local species identity excess between individuals, expressing species turnover. It is a form of spatial partition of Gini-Simpson diversity (equivalent to Fst in population genetics). Ist considers <STRONG>only</STRONG> abundances (or presences) in the species-by-plots matrix.
Ist：本地物种之间的身份多余的个人，衡量表达物种的营业额。它是一种空间划分的基尼Simpson多样性（相当于Fst群体遗传学）。 Ist认为<STRONG> </ STRONG>的物种图矩阵中的丰度（或存在）。
PHYLOGENETIC DIVERSITY STRUCTURING
系统发育多样性结构
Pst: a measure of local phyletic proximity excess between individuals, expressing species + phylogenetic turnover. It is a form of spatial partition of Rao's quadratic entropy (equivalent to Nst in population genetics). Tst is the analogue for trait data, estimating the spatial partitioning of mean trait-divergence between individuals.
Pst：衡量个人之间的本地的种类繁多接近多余的，表示物种+系统发育营业额。它是一种形式的空间划分饶的二次熵（相当于Nst群体遗传学）。 Tst特征数据，估计是模拟的空间分割的平均个人特质之间的分歧。
Bst: a measure of local phyletic proximity excess between individuals of distinct species, expressing phylogenetic turnover (independently of species turnover). Ust is the analogue for trait data, estimating the spatial partitioning of mean trait-divergence between individuals that belong to distinct species.
Bst：衡量个人之间的不同的物种，表达系统发育营业额（独立的物种营业额）的本地的种类繁多接近多余的。 Ust特征数据，估计是模拟的空间分割的平均个人属于不同的物种性状之间的分歧。
PIst: Bst analogue for presence/absence data, expressing phylogenetic turnover (independently of species turnover). TAUst is the analogue for trait data, estimating mean trait-divergence between distinct species.
PIst：BST的模拟存在/不存在的数据，表达系统发育营业额（独立物种的营业额）。 TAUst是模拟特征数据，估计平均特质在不同的物种之间的分歧。
TRAIT DIVERSITY STRUCTURING
TRAIT多样性结构
Measures analogous to those under PHYLOGENETIC DIVERSITY STRUCTURING can be computed from trait data. For trait data, these analogues are Tst (see Pst), Ust (see Bst), and TAUst (see PIst). Note: elsewhere, Ust will be referred to as T*st but here has been renamed to avoid issues of indexing in R. Trait values are not assumed to follow any particular model of evolution; rather, distances between observed species traits are expected to be uniform in distribution.
的措施类似于PHYLOGENETIC DIVERSITY STRUCTURING下的可以计算从性状数据。性状数据，这些类似物是Tst（见Pst）Ust（见Bst），和TAUst（见PIst）。注：在别处，Ust将被称为T*st但在这里已经改名为避免这些问题的的R.特质值的索引是被假定为遵循任何特定模型的演化，而是之间的距离观测到的物种特征预期的分布是均匀的。
If all.together=TRUE, all traits will be used to generate distance a distance matrix for sampled species. Where all.together=FALSE is used, output is generated for each trait independently.
如果all.together=TRUE，所有性状将被用于生成距离的距离矩阵的采样的物种。凡all.together=FALSE被用来生成，输出独立地为每个性状。
INTERPRETATION
释义
spatial clustering: species within plots are more phylogenetically related on average than species from distinct plots where Pst > Ist, Bst > 0, or PIst > 0. Species are functionally more similar locally than those from distinct plots where Tst > Ist, Ust > 0, or TAUst > 0
spatial clustering：图内的物种系统发育相关物种的平均比从不同的图 Pst > Ist， Bst > 0或 PIst > 0。从不同的图比本地种功能更类似于 Tst > Ist， Ust > 0或 TAUst > 0
spatial overdispersion: species within plots are less phylogenetically related on average than species from distinct plots where Pst < Ist, Bst < 0, or PIst < 0. Species are functionally less similar locally than are species from distinct plots where Tst < Ist, Ust < 0, or TAUst < 0
spatial overdispersion：图内的物种系统发育相关的物种平均比从不同的图 Pst < Ist， Bst < 0或 PIst < 0。物种在功能上是大致相同的本地种，从不同的图， Tst < Ist， Ust < 0或 TAUst < 0
（作者）----------Author(s)----------
Olivier Hardy, Timothy Paine, and Jonathan Eastman
参考文献----------References----------
phylogenetic structure of communities by an additive partitioning of phylogenetic diversity. Journal of Ecology 95:493-506.
structure of local communities: statistical performances of different null models and test statistics on a locally neutral community. Journal of Ecology 96:914-926.
phylogenetic structuring. Journal of Ecology 96:849-852.
参见----------See Also----------
match.spacodi.data; as.spacodi
match.spacodi.data; as.spacodi
实例----------Examples----------
# load a species-by-plots matrix, along with a tree[加载一个物种的图的矩阵，沿树]
data(sp.example)
attributes(sp.example)
attach(sp.example)
spl
phy
# community diversity statistics of Hardy and Senterre (2007): tree-based[群落多样性的哈代和Senterre的（2007）的统计数据：树]
spacodi.calc(sp.plot = spl, phy = phy)
# community diversity statistics: trait-based with pairwise comparisons[群落多样性的统计特征为基础的两两比较]
spacodi.calc(sp.plot = spl, phy = phy, pairwise=TRUE)
# community diversity for a pair of traits[一对群落多样性特征]
spacodi.calc(sp.plot = spl, sp.traits = trt, all.together=TRUE)
# community diversity for a pair of traits, each singly[一对性状，每一个单独的群落多样性]
spacodi.calc(sp.plot = spl, sp.traits = trt, all.together=FALSE)
# Ist: using abundance data only [北京时间：使用丰度数据]
spacodi.calc(sp.plot = spl)
# calculations with missing taxa between tree and sp.plot[缺少类群间树和sp.plot的计算]
# excluding the last five species in sp.plot, [不包括最后5种在sp.plot，]
spacodi.calc(sp.plot = spl[1:15,], phy = phy, prune=TRUE)
# as before but with 'manual' pruning of the datasets[像以前一样，但与“手动”修剪数据集的]
match.spacodi.data(sp.plot=spl[1:15,],phy=phy) -> prn.data
spacodi.calc(sp.plot=prn.data$sp.plot, phy=prn.data$sp.tree)
prn.data$sp.plot
prn.data$sp.tree
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注：
注1：为了方便大家学习，本文档为生物统计家园网机器人LoveR翻译而成，仅供个人R语言学习参考使用，生物统计家园保留版权。
注2：由于是机器人自动翻译，难免有不准确之处，使用时仔细对照中、英文内容进行反复理解，可以帮助R语言的学习。
注3：如遇到不准确之处，请在本贴的后面进行回帖，我们会逐渐进行修订。
|
发表于 2012-9-30 12:16:43
