If you have developed your model in the Ecopath with Ecosim (EwE)
software package and you now want to bring it into Rpath for analysis,
there are tools available in Rpath to do just that. First,
you need to export your model from EwE to XML format, using EwE’s
File -> Export Model -> To XML menu option to create
a .eiixml file (all EwE functionality described here was tested using
EwE version 6.7.0).
For this example, the Western Bering Sea EwE model available for
download on EcoBase (Aydin et al. 2002) was first imported into EwE,
using EwE’s Import Model menu option, then exported to the file
Western_Bering_Sea.eiixml. We can read in this file and
convert it to an Rpath object using the function
create.rpath.from.eiixml().
# Read in the model
eiixml_file <- system.file("extdata/xml", "Western_Bering_Sea.eiixml", package = "Rpath")
model <- create.rpath.from.eiixml(eiixml_file)Currently, the create.rpath.from.eiixml() will only
import input parameters related to the unbalanced Ecopath model, and
will not import Ecosim information or other supplementary tables.
However, the full set of tables in an .eiixml file can be examined (or
manually imported) using the import.eiixml() helper
function.
The variable model is a list object (an unbalanced
Ecopath model) containing the data objects required to balance your
model and run simulations. There are 4 objects that comprise an
Rpath object:
- model - including basic inputs, detritus fate, other production, and fishery landings/discards.
- diet - a diet matrix, including diet import.
- stanzas - parameters for multi-stanza functional groups.
- pedigree - data pedigree (quality) for the model.
Prepare your imported model for balancing by first calculating
multistanza parameters that are based on age structure (such as B and
Q/B), using the rpath.stanzas() function, then using the
check.rpath.params() function to ensure all of the model’s
parameters are entered (If your model has no multistanza groups,
rpath.stanzas() can be called but will not change the
model). The check.rpath.params() function will make sure
the data was read in correctly, and produce warnings in situations that
might prevent the model from balancing; for example, if a functional
group is missing too many parameters to be balanced, or if diet
compositions for a predator do not sum to 1.
model <- rpath.stanzas(model)
check.rpath.params(model)
#> Rpath parameter file is functional.Model parameters
To compare Rpath balance results with EwE, first balance the model in EwE and use EwE’s “Save to a csv” icon on EwE’s Outputs -> Basic estimates tab (upper right corner). It is recommended that you first increase the precision (digits displayed) in EwE to 8 digits. The following script, using the dplyr library, can then compare the resulting balances.
# dplyr is used to match the Rpath and EwE balance results
library(dplyr, warn.conflicts=F)
# EwE output files - eiixml file and Basic Estimates csv
eiifile <- system.file("extdata/xml", "Western_Bering_Sea.eiixml", package = "Rpath")
csvfile <- system.file("extdata/xml", "Western Bering Sea-Basic estimates.csv", package = "Rpath")
# Load and balance the model in Rpath
unbal <- create.rpath.from.eiixml(eiifile)
unbal <- rpath.stanzas(unbal)
check.rpath.params(unbal)
#> Rpath parameter file is functional.
bal <- rpath(unbal)
# Load the csv file and clean up the format
csv.out <- read.csv(csvfile)
# If there's no stanzas, the total mortality column will be missing from the CSV - add an extra column
if(length(csv.out)<13){csv.out <- data.frame(append(csv.out, list(tm=NA), after=6))}
# cleaned column names matching EwE output
names(csv.out)<- c("X", "Group.name", "Trophic.level", "Hab.area", "Biomass.in.habitat.area",
"Biomass", "Total.mortality", "Production.biomass", "Consumption.biomass",
"Ecotrophic.Efficiency", "Production.consumption", "Biomass.accumulation",
"BA.rate")
# Drop placeholder lines that head stanza groups
csv.out <- csv.out[!is.na(csv.out$X),]
# Clean names to rpath standard
csv.out$group <- janitor::make_clean_names(csv.out$Group.name)
# Create a data frame of rpath (balanced model) output
rpath.dat <- data.frame(group=bal$Group,type=bal$type, tl=bal$TL, biomass=bal$Biomass,
pb=bal$PB,qb=bal$QB, EE=bal$EE, pc=bal$GE,
ba=bal$BA)[c(rpath.living(bal), rpath.detrital(bal)),]
# Join rpath and EwE balance outputs, using dplyr
rpath_ewe_table <- rpath.dat %>%
dplyr::left_join(csv.out, by="group") %>%
dplyr::mutate( biomass_test = abs(biomass-Biomass)/Biomass,
ee_test = abs(EE-Ecotrophic.Efficiency)) %>%
dplyr::select(group, rpath.biomass=biomass, ewe.biomass=Biomass, prop.bio.diff=biomass_test,
rpath.EE=EE, ewe.EE=Ecotrophic.Efficiency, EE.diff=ee_test)
rpath_ewe_table
#> group rpath.biomass ewe.biomass prop.bio.diff rpath.EE
#> 1 baleen_whales 0.391000 0.391000 0.000000e+00 0.9891304348
#> 2 toothed_whales 0.042000 0.042000 2.380952e-08 0.0000000000
#> 3 sperm_whales 0.020000 0.020000 0.000000e+00 0.0000000000
#> 4 walrus_bearded_seals 0.262000 0.262000 3.816794e-08 0.4284351145
#> 5 seals 0.097000 0.097000 3.092783e-08 0.5962199313
#> 6 steller_sea_lions 0.035000 0.035000 0.000000e+00 0.3500000000
#> 7 seabirds 0.010000 0.010000 2.000000e-08 0.0000000000
#> 8 adult_pollock 15.000000 15.000000 0.000000e+00 0.9497486121
#> 9 juvenile_pollock 3.757000 3.757000 7.985095e-09 0.4800152741
#> 10 pacific_cod 3.187000 3.187000 1.255099e-08 0.3541614076
#> 11 p_halibut 0.083000 0.083000 3.614458e-08 0.9878137841
#> 12 greenland_turbot 0.058000 0.058000 3.448276e-08 0.9465517241
#> 13 arrowtooth_flounder 0.052000 0.052000 1.923077e-08 0.8895514435
#> 14 small_flatfish 0.992000 0.992000 2.016129e-08 0.7397461896
#> 15 skates 0.271000 0.271000 0.000000e+00 0.3782287823
#> 16 sculpins_rockfish 0.677000 0.677000 1.477105e-08 0.9444742460
#> 17 macrouridae 1.156000 1.156000 1.730104e-08 0.6748010381
#> 18 zoarcidae 0.900000 0.900000 2.222222e-08 0.9880651111
#> 19 tanner_crab 0.083000 0.083000 3.614458e-08 0.3979768578
#> 20 snow_crab 0.249000 0.249000 0.000000e+00 0.8712332284
#> 21 king_crab 0.119000 0.119000 0.000000e+00 0.8268279357
#> 22 shrimp 2.105753 2.105753 4.777329e-09 0.9000000000
#> 23 epifauna 114.962000 114.961998 1.739705e-08 0.2450068922
#> 24 infauna 125.687000 125.686996 3.182509e-08 0.2740845025
#> 25 benthic_amphipods 13.812000 13.812000 2.172024e-08 0.9944898735
#> 26 pacific_herring 0.787000 0.787000 0.000000e+00 0.8228223326
#> 27 pacific_salmon 0.039000 0.039000 2.564102e-08 0.3907632487
#> 28 cephalopods 4.830000 4.830000 1.656315e-08 0.9109046695
#> 29 forage_fish 19.419371 19.419371 3.826047e-08 0.9000000000
#> 30 jellyfish 1.400000 1.400000 1.428571e-08 0.0164664762
#> 31 large_zooplankton 120.740000 120.739998 1.656452e-08 0.5520143674
#> 32 copepods 122.620000 122.620003 2.446583e-08 0.9742557243
#> 33 phytoplankton 15.000000 15.000000 0.000000e+00 0.7382177445
#> 34 pelagic_detritus 0.000000 NA NA Inf
#> 35 benthic_detritus 0.000000 NA NA Inf
#> 36 detrital_pool 6930.982701 NA NA 0.0001562706
#> ewe.EE EE.diff
#> 1 0.98913050 6.521739e-08
#> 2 0.00000000 0.000000e+00
#> 3 0.00000000 0.000000e+00
#> 4 0.42843521 9.549618e-08
#> 5 0.59622002 8.872852e-08
#> 6 0.35000011 1.100000e-07
#> 7 0.00000000 0.000000e+00
#> 8 0.94974858 3.209067e-08
#> 9 0.48001531 3.589832e-08
#> 10 0.35416141 2.425322e-09
#> 11 0.98781377 1.409639e-08
#> 12 0.94655168 4.413793e-08
#> 13 0.88955140 4.350962e-08
#> 14 0.73974621 2.036136e-08
#> 15 0.37822881 2.771218e-08
#> 16 0.94447428 3.403988e-08
#> 17 0.67480099 4.806228e-08
#> 18 0.98806512 8.888889e-09
#> 19 0.39797691 5.216867e-08
#> 20 0.87123322 8.413654e-09
#> 21 0.82682788 5.571429e-08
#> 22 0.90000021 2.100000e-07
#> 23 0.24500690 7.818710e-09
#> 24 0.27408451 7.461256e-09
#> 25 0.99449003 1.565455e-07
#> 26 0.82282239 5.739009e-08
#> 27 0.39076331 6.128221e-08
#> 28 0.91090471 4.047966e-08
#> 29 0.89999992 8.000000e-08
#> 30 0.01646648 3.809524e-09
#> 31 0.55201441 4.260628e-08
#> 32 0.97425568 4.431013e-08
#> 33 0.73821777 2.547578e-08
#> 34 NA NA
#> 35 NA NA
#> 36 0.00015627 6.081843e-10Differences between Rpath and EwE balances
Rpath was tested using the 150+ models available on EcoBase. In general, differences between Rpath and EwE were within 1.0e-7 of each other for any given estimated EE, B, or P/B, with differences due to numerical precision of inputs. Stanza groups may show differences of up to 1.0e-3 due to accumulated differences summing across age groups. However, there are some specific differences in functionality in some models:
- Q/B - Rpath does not currently estimate Q/B as part of the main balancing (i.e. to estimate Q/B, both P/B and PC must be supplied).
- Interdetrital flows - For models with three or more stages of interdetrital flows (that is, if detritus fate specifies thart Detritus A -> Detritus B -> Detritus C), results may differ between Rpath and EwE. Two-stage detrital flows (Detritus A -> Detritus B) give matching results.
- Rpath will not currently estimate BA. In cases where all of B, EE, and P/B are supplied, Rpath will not estimate BA or make changes to the model, and may produce inconsistent results if one of those paramters isn’t set to NA.
- Rpath does not currently support BA rate, only total BA. If your model has a BA rate, it is recommended that you calculate the total BA in EwE (as an output), and enter that value into Rpath.