occ.time(simba)
occ.time()所属R语言包：simba
Track species occurrence
追踪物种出现
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Calculate the change in occurence of species on plots in general or on specific plots. Allows for the tracking of temporal changes in species abundance throughout an area or the simple quantification and comparison of species occurences between time steps.
计算在一般或具体图图上的变化，物种出现的位置。允许在一个区域或简单量化和比较物种出现的时间步长之间的物种丰度的时空变化跟踪。
用法----------Usage----------
occ.time(x, y, times = NULL, adjust = TRUE, gen.occ = FALSE,
perc = TRUE, nc.acc = FALSE, ...)
occ.tmp(x, y, adjust=TRUE, gen.occ=FALSE, perc=TRUE,
nc.acc=FALSE, ...)
参数----------Arguments----------
参数：x
Species data in matrix or database-format representing species occurrence at time step one or throughout a time series. The latter means that you have a table with three columns where the columns represent plots, species and occurence information (in this order!). These are typically exported from a database. When times are given and data represents more than one time steps it has to be in database format. Conversion is handled automatically - if three columns are in the table it is assumed to be in database format. When there are only three species give the data in database-format. If there are many plots and/or species, internal matrix conversion might be quite slow.
物种中的数据代表物种出现在时间步长的一个或整个一个时间序列的矩阵或数据库格式。后者意味着你有一个表有三列，列代表plots，species和occurence信息（按照这个顺序）。这些通常是从数据库中导出。当times和数据代表一个以上的时间步长，它是在数据库格式。转换是自动处理的 - 如果表中有三列，它被认为是在数据库格式。当有只有3种给数据库中的数据格式。如果有许多图和/或物种，内部矩阵转换可能会很慢。
参数：y
Species data in matrix or database-format representing species occurrence at time step two. Obsolete when times are given. Otherwise the same as for x applies.
种数据在矩阵或数据库格式代表物种出现在第二个时间步长。作废时times。否则的相同x的适用。
参数：times
When there are more than two timesteps. A vector describing the timesteps which has to be coercible to a factor. If your data comes from a database and contains species records for different time-steps, just export the time information with the species data. If you have single matrices for each time step, you could reshape them to database format via liste and concatenate these or calculate each time step alone.
当有两个以上的时间步长。一个向量描述的时间步转换的一个因素。如果您的数据是从数据库中包含不同的时间步长的物种记录，只是出口的物种数据的时间信息。如果你有一个矩阵每一个时间步，你可以将他们重塑到数据库格式通过liste，串联或单独计算每个时间步长。
参数：adjust
Do not change the default behaviour (TRUE) unless you know what you do. Would spare some calculation time if set to FALSE, when your species data do not need adjustment, which means that in both or all time steps, there are exactly the same species and the same plots. However in most cases it will be more convenient to rely on the function (see details).
，除非你知道你做什么，不要改变默认的行为（TRUE）。将腾出一些计算时间，如果设置为FALSE，当你种的数据并不需要调整，这意味着在两个或全部的时间步长，是完全一样的物种和相同图。然而，在大多数情况下，这将是更加方便依赖的功能（见详情）。
参数：gen.occ
Triggers if general occurrence is regarded or specific occurrence. The latter is default (gen.occ=FALSE) and it means that it is calculated on which exact plots a species is changing. When set to TRUE only general occurence is regarded and it is calculated on how many plots a species occurs more or less then before. See details.
触发器，如果一般被视为或具体的事件发生。后者是默认（gen.occ = FALSE），这意味着它的计算哪个具体图的物种正在发生变化。当设置为TRUE，只能进行一般发生“，被认为是和它的计算方法上有许多图的物种发生或多或少前。查看详细信息。
参数：perc
If output shall be in percentage of species. Defaults to TRUE.
如果输出为物种的百分比。默认为true。
参数：nc.acc
Per default, species which are not changing on a plot are counted as single species (also when they do not change on more than one plot). This can be changed when setting nc.acc = TRUE. Then each occurence of species which has not changed is counted.
每默认情况下，在一块土地上是不会改变的物种都算作单种时，他们不改变一个以上的图。这是可以改变设置nc.acc= TRUE。每一个出现的位置并没有改变物种数。
参数：...
Further arguments to functions.
进一步函数的参数。
Details
详细信息----------Details----------
If you compare species data among time steps there will be most likely different numbers of species (and often also different numbers of plots for which information is available). The function takes care of this and you can give any species matrices you want. If one plot is the same, it will calculate what changed on this plot. There will be an error message if no plot is shared. The function relies on plot and species names!! As in a database - they must be unique!!
如果你比较物种之间的数据的时间步长将最有可能不同的物种数量（往往也不同图的信息是可用的）。该功能需要照顾，你可以给你想要的任何物种矩阵。如果有一个图是一样的，它会计算是什么改变了这个图。共享将是一个错误消息，如果没有图。的功能依赖于图和种名！在数据库中 - 他们必须是唯一的！
With the resulting named vector or table it is easy to draw a barplot tracking the changing occurrence of plants. Walter et al. (2005) used such plots to illuminate the changing (and increasing) occurrence of plant species on Alpine summits due to climate change.
用所得名为向量或表很容易绘制barplot跟踪的变化发生的植物。 Walter等。 （2005年），用于照亮的植物种类的变化（增加）发生的阿尔卑斯首脑会议，由于气候变化的图。
However they only considered change in general occurrence. We added the possibility to track changes on the specific plots. If a species is occuring on 5 plots at time one and on 4 plots at time two one can't be shure that this species changed occurrence on only one plot. If it occurrs partly on different plots then before it will contribute to loss and gain respectively in this function when gen.occ is set to FALSE.
然而，他们只考虑一般发生变化。我们添加了可以跟踪更改的具体图。如果一个物种在时间1和4块在时间上发生5图不能舒尔，这个物种改变发生在只有一个图。如果发病在一定程度上不同的图，然后才将有助于损耗和增益分别在这个函数中时gen.occ设置为FALSE。
值----------Value----------
Returns a named vector or a table (when multiple time steps are evaluated at once) with information on change in species occurence. The names tell on how many plots a certain species has changed. The values tell how many species (or percent of species) exhibit this change. Additionally the number of matching plots and species for each comparison are given back.
返回一个已命名的矢量表（当多个步骤进行计算，一次）的物种发生“变化的信息。的名字告诉多少绘制某些物种已经改变。值告诉多少物种（或物种％）表现出这种变化。此外，每个比较匹配的图和物种的数量。
Per default nice output is given. However, the table can be accessed for printing whith *\$bac (see Example for Details). A plotting method will be added in the near future.
每默认情况下，很好的输出。不过，该表可访问的印刷蒙山* \ $ BAC（见详情例）。在不久的将来将被添加绘图方法。
（作者）----------Author(s)----------
Gerald Jurasinski <a href="mailto:gerald.jurasinski@uni-rostock.de">gerald.jurasinski@uni-rostock.de</a>
参考文献----------References----------
参见----------See Also----------
to calculate similarity based on plant species occurrence between time steps see sim.tmp
计算的基础上植物物种出现的时间步长之间的相似性看sim.tmp
实例----------Examples----------
## load included data[＃负载数据]
data(bernina)
## how species changed occurrence between first recording[＃物种如何改变发生之间的第一次记录]
## and last recording?[＃和最后的录音？]
# construct a species matrix that only contains the species[构建一个只包含的物种的物种矩阵]
# that occurred on the summits at the first recording[在第一次记录发生的首脑会议]
first <- veg[summits$year=="1907",]
first <- first[,colSums(first)>0]
# make right summit names[做出正确的首脑会议名称]
row.names(first) <- as.character(summits$summit[summits$year=="1907"])
# construct a species matrix that only contains the species[构建一个只包含的物种的物种矩阵]
# that occurred on the summits at the last recording[在最后的记录上发生的高峰]
last <- veg[summits$year=="2003",]
last <- last[,colSums(last)>0]
# make right summit names[做出正确的首脑会议名称]
row.names(last) <- as.character(summits$summit[summits$year=="2003"])
# see that dimensions of first and last differ[看到的第一个和最后一个的不同的尺寸]
dim(first)
dim(last)
# calculate change in occurrence[计算发生变化]
changed.occurrence <- occ.tmp(first, last)
barplot(changed.occurrence$bac, main="percentage of species
that changed on ... plots")
# try the same but species are not given in percentages[尝试相同的，但物种中没有给出的百分比]
changed.occurrence <- occ.tmp(first, last, perc=FALSE)
barplot(changed.occurrence$bac, main="number of species that
changed on ... plots")
# there is a lot of info in the output[有大量的信息在输出]
changed.occurrence
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。
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发表于 2012-9-30 02:29:52
