specaccum(vegan)
specaccum()所属R语言包：vegan
Species Accumulation Curves
物种累积曲线
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Function specaccum finds species accumulation curves or the number of species for a certain number of sampled sites or individuals.
函数specaccum发现物种积累曲线或物种的数量为一定数目的采样的网站或个人。
用法----------Usage----------
specaccum(comm, method = "exact", permutations = 100,
conditioned =TRUE, gamma = "jack1", ...)
## S3 method for class 'specaccum'
plot(x, add = FALSE, ci = 2, ci.type = c("bar", "line", "polygon"),
col = par("fg"), ci.col = col, ci.lty = 1, xlab,
ylab = x$method, ylim, xvar = c("sites", "individuals"), ...)
## S3 method for class 'specaccum'
boxplot(x, add = FALSE, ...)
fitspecaccum(object, model, method = "random", ...)
## S3 method for class 'fitspecaccum'
plot(x, col = par("fg"), lty = 1, xlab = "Sites",
ylab = x$method, ...)
## S3 method for class 'specaccum'
predict(object, newdata, interpolation = c("linear", "spline"), ...)
## S3 method for class 'fitspecaccum'
predict(object, newdata, ...)
参数----------Arguments----------
参数：comm
Community data set.
社区数据集。
参数：method
Species accumulation method (partial match). Method "collector" adds sites in the order they happen to be in the data, "random" adds sites in random order, "exact" finds the expected (mean) species richness, "coleman" finds the expected richness following Coleman et al. 1982, and "rarefaction" finds the mean when accumulating individuals instead of sites.
种积累方法（部分匹配）。方法"collector"增加了网站中的顺序发生的数据，"random"以随机顺序添加网站，"exact"发现的期望（平均）物种丰富度，"coleman"发现Coleman等人之后的预期全面地了解顾客。 1982年，"rarefaction"发现，平均时积累的个人，而不是网站。
参数：permutations
Number of permutations with method = "random".
数排列与method = "random"。
参数：conditioned
Estimation of standard deviation is conditional on the empirical dataset for the exact SAC
估计的标准差是有条件的经验数据集的确切SAC
参数：gamma
Method for estimating the total extrapolated number of species in the survey area by function specpool
在调查区域的功能specpool推断估计总种数的方法
参数：x
A specaccum result object
Aspecaccum的结果对象
参数：add
Add to an existing graph.
添加到现有的图形。
参数：ci
Multiplier used to get confidence intervals from standard deviation (standard error of the estimate). Value ci = 0 suppresses drawing confidence intervals.
乘数置信区间，标准差（标准误差的估计）。值ci = 0抑制绘制置信区间。
参数：ci.type
Type of confidence intervals in the graph: "bar" draws vertical bars, "line" draws lines, and "polygon" draws a shaded area.
图中的置信区间类型："bar"画竖线，"line"画线，和"polygon"吸引了阴影区域。
参数：col
Colour for drawing lines.
画线的颜色。
参数：ci.col
Colour for drawing lines or filling the "polygon".
颜色画线或填充的"polygon"的。
参数：ci.lty
Line type for confidence intervals or border of the "polygon".
置信区间的线路类型或边界的"polygon"。
参数：xlab,ylab
Labels for x (defaults xvar) and y axis.
标签x（默认xvar）y轴。
参数：ylim
the y limits of the plot.
在y限制的图。
参数：xvar
Variable used for the horizontal axis: "individuals" can be used only with method = "rarefaction".
使用的变量为横轴：，"individuals"可以只用method = "rarefaction"。
参数：object
Either a community data set or fitted specaccum model.
无论是社会设置或安装specaccum模型的数据。
参数：model
Nonlinear regression model (nls). See Details.
非线性回归模型（nls）。查看详细信息。
参数：lty
line type code (see par.
线路类型代码（见par。
参数：newdata
Optional data used in prediction interpreted as number of sampling units (sites). If missing, fitted values are returned.
预测中使用的可选数据解释为抽样单位（点）。如果缺少，拟合值被返回。
参数：interpolation
Interpolation method used with newdata.
插值方法用于newdata。
参数：...
Other parameters to functions.
其他函数的参数。
Details
详细信息----------Details----------
Species accumulation curves (SAC) are used to compare diversity properties of community data sets using different accumulator functions. The classic method is "random" which finds the mean SAC and its standard deviation from random permutations of the data, or subsampling without replacement (Gotelli & Colwell 2001). The "exact" method finds the expected SAC using the method that was independently developed by Ugland et al. (2003), Colwell et al. (2004) and Kindt et al. (2006). The unconditional standard deviation for the exact SAC represents a moment-based estimation that is not conditioned on the empirical data set (sd for all samples > 0), unlike the conditional standard deviation that was developed by Jari Oksanen (not published, sd=0 for all samples). The unconditional standard deviation is based on an estimation of the total extrapolated number of species in the survey area (a.k.a. gamma diversity), as estimated by function specpool. Method "coleman" finds the expected SAC and its standard deviation following Coleman et al. (1982). All these methods are based on sampling sites without replacement. In contrast, the method = "rarefaction" finds the expected species richness and its standard deviation by sampling individuals instead of sites. It achieves this by applying function rarefy with number of individuals corresponding to average number of individuals per site.
物种累积曲线（SAC）是用来比较的社区数据集的分集属性使用不同的累加器功能。经典的方法是"random"发现的平均SAC及其标准差的数据随机排列，无需更换（戈泰利和Colwell 2001）或二次采样。 "exact"方法发现的预期SAC使用的方法完全自主开发的位于Ugland等。 （2003年），科尔韦尔等。 （2004）和：金特等。 （2006年）。无条件标准差的确切SAC是一个基于矩估计是没有条件的实证数据集（SD为所有样品> 0），不同的条件标准差，是由杰瑞奥克萨宁（不公开，SD = 0对所有样品）。无条件标准差是根据估计的总推算调查区的物种（又名丙多样性），估计功能specpool。方法"coleman"查找预期SAC及其标准差后，科尔曼等人。 （1982）。所有这些方法都无需更换采样点的基础上。在对比，method = "rarefaction"的发现预期的物种丰富度及其标准差的采样，而不是个人的网站。它实现了应用功能rarefy数相当于平均每个站点的个人的个人。
The function has a plot method. In addition, method = "random" has summary and boxplot methods.
的功能有plot方法。此外，method = "random"summary和boxplot方法。
Function predict can return the values corresponding to newdata using linear (approx) or spline (spline) interpolation. The function cannot extrapolate with linear interpolation, and with spline the type and sensibility of the extrapolation depends on argument method which is passed to spline. If newdata is not given, the function returns the values corresponding to the data.
函数predict可以返回对应的值newdata使用线性（approx）或样条曲线（spline）插。的功能不能使用线性插值外推，并与样条曲线的类型和感性的推断依赖于参数传递给method spline。 newdata如果没有给出，该函数返回的值相对应的数据。
Function fitspecaccum fits a nonlinear (nls) self-starting species accumulation model. The input object can be a result of specaccum or a community in data frame. In the latter case the function first fits a specaccum model and then proceeds with fitting the a nonlinear model. The function can apply a limited set of nonlinear regression models suggested for species-area relationship (Dengler 2009). All these are selfStart models. The permissible alternatives are "arrhenius" (SSarrhenius), "gleason" (SSgleason), "gitay" (SSgitay), "lomolino" (SSlomolino) of vegan package. In addition the following standard R models are available: "asymp" (SSasymp), "gompertz" (SSgompertz), "michaelis-menten") (SSmicmen), "logis" (SSlogis), "weibull" (SSweibull). See these functions for model specification and details.
函数fitspecaccum适合的非线性（nls）自启动种成藏模式。输入objectspecaccum或社区在数据框的结果。在后一种情况下，功能适合specaccum模型，然后继续进行拟合非线性模型。该功能可以适用于有限的一组非线性回归模型的种 - 面积关系（Dengler 2009）的建议。所有这些都是selfStart模型。允许的替代品是"arrhenius"（SSarrhenius）"gleason"（SSgleason）"gitay"（SSgitay）"lomolino"（ SSlomolino）vegan包。此外，下列标准的R型号可供选择："asymp"（SSasymp）"gompertz"（SSgompertz）"michaelis-menten"）（SSmicmen）， "logis"（SSlogis）"weibull"（SSweibull）。型号规格及详细信息，请参阅这些功能。
Function predict uses predict.nls, and you can pass all arguments to that function. In addition, fitted, residuals and coef work on the result object.
函数predict使用predict.nls，，你可以通过该函数的所有参数。此外，fitted，residuals和coef做的结果对象。
Nonlinear regression may fail for any reason, and some of the fitspecaccum models are fragile and may not succeed.
非线性回归可能会因任何原因而失败，和一些fitspecaccum模型是脆弱的，可能不会成功。
值----------Value----------
Function specaccum returns an object of class "specaccum", and fitspecaccum a model of class "fitspecaccum" that adds a few items to the "specaccum" (see the end of the list below):
功能specaccum返回一个类的对象"specaccum"和fitspecaccum一个模型类"fitspecaccum"增加了一些项目的"specaccum"（看不到尽头的下面的列表）：
参数：call
Function call.
函数调用。
参数：method
Accumulator method.
累加器的方法。
参数：sites
Number of sites. For method = "rarefaction" this is the number of sites corresponding to a certain number of individuals and generally not an integer, and the average number of individuals is also returned in item individuals.
站点数量。对于method = "rarefaction"“”这是网站的数量对应于一定数量的个人，一般不是整数，个人的平均数量也将返回项individuals。
参数：richness
The number of species corresponding to number of sites. With method = "collector" this is the observed richness, for other methods the average or expected richness.
相应的网站数量的物种的数量。 method = "collector"“”这是所观察到的丰富性，为其他方法的平均预期丰富。
参数：sd
The standard deviation of SAC (or its standard error). This is NULL in method = "collector", and it is estimated from permutations in method = "random", and from analytic equations in other methods.
标准偏差的SAC（或标准错误）。这是NULL中method = "collector"，估计method = "random"，分析方程，在其他方法中的排列。
参数：perm
Permutation results with method = "random" and NULL in other cases. Each column in perm holds one permutation.
排列method = "random"和NULL在其他情况下的结果。中的每一列perm拥有一个排列。
参数：fitted, residuals, coefficients
Only in fitspecacum: fitted values, residuals and nonlinear model coefficients. For method = "random" these are matrices with a column for each random accumulation.
只有在fitspecacum：拟合值，残差和非线性模型系数。对于method = "random"这些都是为每个随机堆积的列的矩阵。
参数：models
Only in fitspecaccum: list of fitted nls models (see Examples on accessing these models).
只有在fitspecaccum：装nls模型（见例访问这些模型）。
注意----------Note----------
The SAC with method = "exact" was developed by Roeland Kindt, and its standard deviation by Jari Oksanen (both are unpublished). The method = "coleman" underestimates the SAC because it does not handle properly sampling without replacement. Further, its standard deviation does not take
SACmethod = "exact"是由罗兰金特杰瑞奥克萨宁（均为未发表），其标准偏差。 method = "coleman"低估了的SAC，因为它不妥善处理，不放回抽样。此外，其标准偏差不采取
（作者）----------Author(s)----------
Roeland Kindt <a href="mailto:r.kindt@cgiar.org">r.kindt@cgiar.org</a> and Jari Oksanen.
参考文献----------References----------
Y. (1982). Randomness, area and species richness. Ecology 63: 1121–1133.
extrapolating, and comparing incidence-based species accumulation curves. Ecology 85: 2717–2727.
relationship best? A review and empirical evaluation. Journal of Biogeography 36, 728–744.
procedures and pitfalls in measurement and comparison of species richness. Ecol. Lett. 4, 379–391.
curves. Manuscript.
richness at varying scales in western Kenya: planning for agroecosystem diversification. Biodiversity and Conservation, online first: DOI 10.1007/s10531-005-0311-9
species-accumulation curve and estimation of species richness. Journal of Animal Ecology 72: 888–897.
参见----------See Also----------
rarefy and rrarefy are related individual based models. Other accumulation models are poolaccum for extrapolated richness, and renyiaccum and tsallisaccum for diversity indices. Underlying graphical functions are boxplot, matlines, segments and polygon.
rarefy和rrarefy都与单独的模型。其他成藏模式poolaccum推断丰富，renyiaccum和tsallisaccum多样性指数。相关的图形功能是boxplot，matlines，segments和polygon。
实例----------Examples----------
data(BCI)
sp1 <- specaccum(BCI)
sp2 <- specaccum(BCI, "random")
sp2
summary(sp2)
plot(sp1, ci.type="poly", col="blue", lwd=2, ci.lty=0, ci.col="lightblue")
boxplot(sp2, col="yellow", add=TRUE, pch="+")
## Fit Lomolino model to the exact accumulation[＃适合Lomolino的模型的确切积累的]
mod1 <- fitspecaccum(sp1, "lomolino")
coef(mod1)
fitted(mod1)
plot(sp1)
## Add Lomolino model using argument 'add'[＃新增使用Lomolino模型参数“添加”，]
plot(mod1, add = TRUE, col=2, lwd=2)
## Fit Arrhenius models to all random accumulations[＃适合所有的随机堆积的阿累尼乌斯模型]
mods <- fitspecaccum(sp2, "arrh")
plot(mods, col="hotpink")
boxplot(sp2, col = "yellow", border = "blue", lty=1, cex=0.3, add= TRUE)
## Use nls() methods to the list of models[＃使用免入息审查贷款计划（）方法的型号列表]
sapply(mods$models, AIC)
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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。
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发表于 2012-10-1 15:13:33
