LimOmega(ToxLim)
LimOmega()所属R语言包：ToxLim
LIM OMEGA Bioaccumulation Model
LIM OMEGA生物蓄积性模型
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Solves a LIMOMEGA model
解决了LIMOMEGA模型
Uncertainty ranges of specific ingestion and production rates, and of assimilation efficiency are estimated with a LIM, and used to set Kup,food and Kout+dil in OMEGA, as explained in detail in De Laender et al (2009). If the LIM is solved using the Markow Chain Monte Carlo approach developed by Van den Meersche et al (2009), uncertainty ranges for Kup,food and Kout+dil and thus for the internal concentrations can be estimated.
特定的摄食率和生产的不确定性范围的，和同化效率与LIM估计，用于设置杯子，食品和中KOUT + DIL OMEGA，在在联邦各州等人（2009）详细解释。如果LIM解决内部的浓度，从而可估计使用马可夫链蒙特卡罗方法的开发范登Meersche等人（2009）的不确定性范围引致，食品和KOUT的的+ DIL。
用法----------Usage----------
LimOmega (lim=NULL, flowmatrix=NULL,
INST, KINE, EXPO, DOC=NULL,
DET, DIC, WW_KINE=7.596535e-08,
SS_KINE=0.079508, Growth=0, k=0.25, Q=1,
logKow=6, Cwater=10, Koc_Kow=0.41,
LIPID_INST=0.0053, LIPID_KINE=0.02,
OC =0.028, rH2O = 1.1e-5, rH2O_0 = 2.8e-3,
rCH2 = 68, g_0 = 200 )
参数----------Arguments----------
参数：lim
a list that contains the linear inverse model specification, when NULL then flowmatrix should be specified.
一个列表，包含的线性反比型号规格，当NULL然后flowmatrix应该被指定。
参数：flowmatrix
a flow matrix, with flows *from* as rows, flows *to* as columns. The matrix should be square; its column and row names should contain the names of the food web components; they should be equal. If NULL, then created from the lim
一个流量矩阵，*行*与流量，流向*到*列。的矩阵应该是方形的，它的列名和列名应包含食品Web组件的名字，他们应该是平等的。如果NULLlim，然后创建
参数：INST
the names of those food web compartments in lim that are assumed to be in rapid (instantaneous) equilibrium with water.
的名字，这些食物网的隔间，在lim被假定为是在快速（瞬时）与水平衡。
参数：KINE
the names of those food web compartments in lim for which uptake/loss kinetics are explicitly modelled.
这些食物网的隔间，在lim明确建模的吸收/损失动力学的名字。
参数：EXPO
the names of all lim externals that do not represent dissolved inorganic carbon.
所有lim，并不代表溶解无机碳的外部的名称。
参数：DOC
the name of the lim food web compartment that represents dissolved organic carbon; the default is no such compartment.
lim食物网隔间，溶解有机碳的名称，默认是没有这样的隔间。
参数：DET
the name of the lim food web compartment that represents detritus.
lim食物网隔间，代表碎屑的名称。
参数：DIC
the name of lim food web compartment that represents dissolved inorganic carbon.
的名称lim溶解无机碳的食物网室。
参数：WW_KINE
wet weights of KINE individuals, in same order as in KINE: [kg wet weight].
KINE个人的湿重，在相同的顺序在KINE：[千克湿重。
参数：SS_KINE
standing stocks of KINE individuals, in same order as in KINE: [g C/m2].
站在股票的KINE个人，在相同的顺序在KINE：[G贮量。
参数：Growth
the rate of change of the KINE food web compartments: [/d].
的变化率KINE食物网室：[/ D]。
参数：k
allometric shape factor [-].
异速生长形状因子[ - ]。
参数：Q
correction factor; default (1) is for cold blooded, use 10 for warm blooded animals: [-].
修正系数;默认（1）是冷血的，使用10温血动物：[ - ]。
参数：logKow
10-base logarithm of octanol water partition coefficient of the chemical that is accumulating: [log10 (L/kg)].
10碱基对数的辛醇水分配系数的化学物质，是积累：[LOG10（L /公斤）。
参数：Cwater
dissolved concentration of the chemical that is accumulating: [microg/L].
溶解浓度的化学物质，是积累：[微克/ L]。
参数：Koc_Kow
ratio of Koc (organic carbon water partitioning coefficient) over Kow, of the chemical that is accumulating
科威特石油公司（有机碳水分配系数）比过水分配系数，积累的化学物质，
参数：LIPID_INST
proportion of wet weight that is lipid for the INST food web compartments, either one value or one value per INST: [-].
湿重的比例，是脂质INST食物网车厢，任何一个值或一个值，每INST：[ - ]。
参数：LIPID_KINE
proportion of wet weight that is lipid for the KINE food web compartments, either one value or one value per KINE: [-].
湿重的比例，是脂质KINE食物网车厢，任何一个值或一个值，每KINE：[ - ]。
参数：OC
proportion of wet weight that is organic carbon in INST food web compartments: [-].
湿重的比例，是有机碳的INST的食物网车厢：[ - ]。
参数：rH2O
water layer diffusion resistance for uptake (loss) of chemical from food (through egestion): [d kg^(-k)].
水层的扩散阻力吸收（亏损）从食物中的化学（通过排遗作用）：[d kg^(-k)]。
参数：rH2O_0
water layer diffusion resistance for absorption (excretion) of chemical from (to) water: [d kg^(-k)].
水层吸收的扩散阻力（排泄），化学（给）水：[d kg^(-k)]。
参数：rCH2
lipid layer permeation resistance: [d/kg^k].
脂质层渗透阻力：[d/kg^k]。
参数：g_0
water absorption - excretion coefficient: [kg^(k)/d].
水吸收 - 排泄系数：[kg^(k)/d]。
Details
详细信息----------Details----------
The OMEGA model (Hendriks et al 2001) estimates the rate of change of the concentration Ci of a nonbiotransforming chemical in compartment i by taking into account the chemical uptake rates through feeding and directly from water, the chemical dilution rate through production and the rates of egestion with faeces and excretion to water.
OMEGA模型（Hendriks等人2001）次估计的浓度的变化率的化学品在隔室nonbiotransforming i由考虑到化学吸收速率通过馈送和直接从水，通过生产的化学稀释率排遗作用的粪便和水的排泄率。
While OMEGA initially was developed to represent food chains, it was extended with multiple food sources in De Laender et al (2009).
虽然OMEGA最初是代表食品链，它延长多的食物来源，在联邦各州等人（2009年）。
The set of differential equations for all m compartments in a food web was cast in matrix notation as:
食物网中的所有m车厢微分方程组被扔在矩阵表示为：
where C is the internal concentration vector, dC/dt is the rate of change of the internal concentration vector, K_{up,food} is a m * m matrix with chemical uptake rates through feeding (d-1), containing elements kup,food,ji on row i, column j, K_{up,water} the uptake rates directly from water (L kg-1 d-1) is a column vector with m elements and K_{out+dil} the chemical dilution rate through production, the rates of egestion with faeces and excretion to water (d-1), a m * m diagonal matrix with elements kout,eg,i + kdil,pr,i + kout,water,i.
其中C是内部的浓度向量，DC / dt是内部集中矢量的变化率，K_{up,food}是上午* m矩阵与喂养（D-1）的的化学吸收率通过，包含的元素杯子，食品，吉第i行，第j列，K_{up,water}直接从水中吸收率（L KG-1 D-1）是一个列向量，m个元素和K_{out+dil}的化学稀释率到生产，排遗作用的粪便和排泄水（D-1），上午* M的对角矩阵的元素KOUT，例如，我+ kdil，公关，我：+ KOUT，水，我。
Expressions for rate coefficients (kup,food,ji; kup,water,i; kout,eg,i; kdil,pr,i; kout,water,i) that regulate chemical uptake and loss processes and how these relate to the carbon flows predicted by the LIM framework can be found in Table S1 of the Supporting Information (SI) of De Laender et al (2009).
表达式，规范化学品的吸收和衰减过程以及如何将这些涉及到碳流率系数（杯子，食品，辛弃疾，杯子，水，我KOUT，例如，我kdil，公关，我KOUT，水，I）预测的LIM框架的发现表S1的支持信息（SI），联邦各州等人（2009）。
Internal concentrations in small particles such as microzooplankton, phytoplankton, detritus, protozoa, and bacteria (collectively termed INST in this package), are assumed to be in rapid equilibrium with the water phase and may be calculated as
内部的小颗粒，如微型浮游动物，浮游植物，碎屑，原生动物，细菌（统称为INST在此包中）的浓度，被假定为在与水相的快速平衡，并可以被计算为
where cINST* denotes the concentration vector for model compartments that are in instant equilibrium with the surrounding water (microg kg-1 wet weight), OCINST their organic carbon fraction (-), and KOC, the organic carbon-water partition coefficient (L kg-1), calculated as 0.41KOW, with KOW the octanol-water partition coefficient.
cINST*表示的浓度向量的模型室，即时平衡与周围的水（微克公斤（湿重）），OCINST其有机碳组分（ - ），和KOC ，有机碳水分配系数（L KG-1），计算公式为0.41KOW，KOW的辛醇 - 水分配系数。
For background on inverse modelling, we refer to the documents of the LIM package.
逆建模的背景，我们指的LIM包中的文件。
值----------Value----------
a list containing:
一个列表，其中包含：
<table summary="R valueblock"> <tr valign="top"><td>BAF_LC </td> <td> The bioaccumulation factor, after lipid normalisation. units [mg (kg lipid)-1 / mg L-1] </td></tr> <tr valign="top"><td>BCF_OC </td> <td> The bioconcentration factor predicted BCF after organic carbon normalisation for INST food web compartments. units [mg (kg OC)-1 / mg L-1]. Because OC is the primary absorbing matrix for persistent organic chemicals in INST, OC normalised BCFs will be equal among INST food web compartments. </td></tr> </table>
<table summary="R valueblock"> <tr valign="top"> <TD>BAF_LC </ TD> <TD>的富集系数，后脂标准化。单位毫克（千克脂）-1 /毫克L-1] </ TD> </ TR> <tr valign="top"> <TD> BCF_OC </ TD> <TD>的生物富集系数预测BCF后INST食物网室有机碳归一化。单元[毫克（公斤OC）-1 /毫克L-1]。由于OC是主要的吸收基质持久性有机物质在INST，OC标准化的生物浓缩系数将等于INST食物网室之间。 </ TD> </ TR> </ TABLE>
（作者）----------Author(s)----------
Frederik de Laender <frederik.delaender@ugent.be>
Karline Soetaert <k.soetaert@nioo.knaw.nl>
参考文献----------References----------
De Laender, F., Van Oevelen, D., Middelburg, J.J. and Soetaert, K., 2009. Incorporating Ecological Data and Associated Uncertainty in Bioaccumulation Modeling: Methodology Development and Case Study. Environ. Sci. Technol., 2009, 43 (7), 2620-2626.
Hendriks, A.J., van der Linde, A., Cornelissen, G., Sijm, D., 2001. The power of size. 1. Rate constants and equilibrium ratios for accumulation of organic substances related to octanol-water partition ratio and species weight. Environ. Toxicol. Chem. 20, 1399 - 1420.
Van den Meersche, K., Soetaert, K., Van Oevelen, D., 2009. xsample(): An R Function for Sampling Linear Inverse Problems. J. Stat. Soft. 30, 1-15.
参见----------See Also----------
LIMlake, LIMlakeFish, LIMbarents, the input food webs.
LIMlake，LIMlakeFish，LIMbarents，的输入食物网。
实例----------Examples----------
#------------------------------------------------------------------[-------------------------------------------------- ----------------]
# Three simple examples: the bioaccumulation model for the[三个简单的例子：生物蓄积模型]
# three food webs, estimated once...[三种食物网，估计一次...]
#------------------------------------------------------------------[-------------------------------------------------- ----------------]
LimOmega (lim = LIMlake,
INST=c("DET","DOC","BAC","PHY","NAN","CIL","MIZ"),
KINE= "MEZ", EXPO=c("sed","gr"),
DOC="DOC", DET="DET", DIC="dic",
WW_KINE=7.596535e-08, SS_KINE=0.079508)
LimOmega (lim = LIMlakeFish,
INST=c("DET","DOC","BAC","PHY","NAN","CIL","MIZ"),
KINE=c("MEZ","FIS"), EXPO=c("sed","gr"),
DOC="DOC", DET="DET", DIC="dic",
WW_KINE=c(1.85e-08,1.7e-3),
SS_KINE=c(0.00514800,0.26))
LimOmega (lim = LIMbarents,
INST=c("DIA","PHA","AUT","CIL","HNA","DET","BAC"),
KINE=c("COP","CHA","KRI","CAP","COD","YCO","HER"),
EXPO=c("SED","GRA","GRO"),
DOC="DOC", DET="DET", DIC="DIC",
WW_KINE=c(0.000001,8e-05,0.00006,10e-3,3,1,20e-3),
LIPID_KINE=c(0.01,0.01,0.01,0.03,0.03,0.03,0.03),
LIPID_INST=0.04,
SS_KINE=c(1.79,0.6965,0.003,0.38,0.053,0.006,0.055))
#------------------------------------------------------------------[-------------------------------------------------- ----------------]
# Now performing a monte carlo run on food web structure[现在食物网结构进行蒙地卡罗运行]
#------------------------------------------------------------------[-------------------------------------------------- ----------------]
# 1. Take niter random samples from all possible solutions using a[1。以硝石从所有可能的解决方案，使用随机抽样]
# Markow Chain Monte Carlo approach[马可夫链蒙特卡罗方法]
X0 <- Lsei(LIMlake)$X
niter <- 50
SolXS <- Xsample(LIMlake, iter=niter, type = "mirror",
jmp=NULL, x0=X0, fulloutput = FALSE)
BAFlc_all <- NULL
# 2. For each of these samples: create flowmatrix and run LimOmega[2。对于每个样本：创建flowmatrix和运行LimOmega]
for (i in 1:niter) {
flowmat <- Flowmatrix(LIMlake, SolXS[i,])
LO<- LimOmega (flowmatrix=flowmat,
INST=c("DET","DOC","BAC","PHY","NAN","CIL","MIZ"),
KINE=c("MEZ"), EXPO=c("sed","gr"),
DOC="DOC", DET="DET", DIC="dic",
WW_KINE=7.596535e-08, SS_KINE=0.079508,
Growth=0, k=0.25, Q=1)
BAFlc_all <- c(BAFlc_all,LO$BAF_LC)
}
# 3. show results[3。显示结果]
hist(BAFlc_all)
#------------------------------------------------------------------[-------------------------------------------------- ----------------]
# Same food web structure, different chemical parameters[同样的食物网结构，不同的化学参数]
#------------------------------------------------------------------[-------------------------------------------------- ----------------]
niter <- 100
# a normally distributed sample of log kow[对数正态分布的样本叩头]
lkw <- rnorm(niter,mean=6,sd=0.4)
BAFlc_all <- NULL
BCFoc_all <- NULL
# the flowmatrix on which this is based[这是基于在flowmatrix]
flowmat <- Flowmatrix(LIMlake)
for (i in 1:niter) {
LO<- LimOmega (flowmatrix=flowmat,
INST=c("DET","DOC","BAC","PHY","NAN","CIL","MIZ"),
KINE=c("MEZ"), EXPO=c("sed","gr"),
DOC="DOC", DET="DET", DIC="dic",
WW_KINE=7.596535e-08, SS_KINE=0.079508,
Growth=0, k=0.25, Q=1, logKow = lkw)
BAFlc_all <- c(BAFlc_all,LO$BAF_LC)
BCFoc_all <- c(BCFoc_all,LO$BCF_OC[1])
}
pm <- par(mfrow=c(2,2))
hist(BAFlc_all,main="BAF_LC")
plot(lkw,BAFlc_all,xlab="log Kow",ylab="BAF_LC")
hist(BCFoc_all,main="BCF_OC")
plot(lkw,BCFoc_all,xlab="log Kow",ylab="BCF_OC")
par(mfrow=pm)
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。
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发表于 2012-10-1 11:12:23
