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##' Some example ideas for a species-specific Ecosystem Summary. Currently | ||
##' ignored in .Rbuildignore as developing. | ||
##' | ||
##' Doing a herring example for now, based on Jennifer's manuscript. | ||
##' Figure 11 gives the indicators that were identified in one or more | ||
##' pressure-respose model. The ones we already have in pacea are: | ||
##' * PDO | ||
##' * SST_Spring - Mar-May, 1982-2019. Satellite measured sea surface temperature, | ||
##' from AVHRR satellite | ||
##' https://www.avl.class.noaa.gov/release/data_available/avhrr/index.htm - | ||
##' website not working, 24/9/24. | ||
##' ##' * SST_Summer - Apr-Jul, 1982-2019 | ||
##' * SST_Fall - Sept-Nov, 1981-2019 | ||
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##' * Upwelling (maybe not) | ||
##' | ||
##' | ||
##' Do not have | ||
##' * copepdods and total zooplankton in HG | ||
##' * humpback whales | ||
##' * Steller SeaLion | ||
##' * hakeAcoustic_B - could get | ||
##' * Arrowtooth, dogfish, cod, IPHC catch rates | ||
##' * herring-related | ||
##' @param species species of interest, might need stock also. Could save the | ||
##' list of desired variables as a data list object, to then apply to the | ||
##' relevant calculation and plotting functions. | ||
##' @return | ||
##' @export | ||
##' @author Andrew Edwards | ||
##' @examples | ||
##' \dontrun{ | ||
##' | ||
##' } | ||
ecosystem_summary <- function(species = "herring-example"){ | ||
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par(mfcol = c(4, 2)) | ||
years <- range(dplyr::filter(herring_recruitment, | ||
region == "HG") %>% | ||
select(year)) | ||
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x_lim = c(lubridate::dmy(paste0("0101", min(years))), # day-month-year | ||
lubridate::dmy(paste0("0101", max(years)))) | ||
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plot(herring_recruitment, | ||
region = "HG", | ||
xlim = x_lim) | ||
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plot(pdo, | ||
xlim = x_lim) | ||
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# For quickness for now, let's just look at buoy data for buoys within the | ||
# study area defined in the manuscript. | ||
# For now just eyeballing which buoys to use, easiest to id by names: | ||
names_hg <- c("Central Dixon Entrance", | ||
"South Moresby", # is maybe just outside, but relevant? | ||
"North Hecate Strait", | ||
"South Hecate Strait", | ||
"West Sea Otter", | ||
"East Dellwood Knolls") # also maybe just outside | ||
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stn_id_hg <- dplyr::filter(buoy_metadata, | ||
name %in% names_hg)$stn_id # not necessarily in | ||
# same order as stn_id_hg. Though think | ||
# will be given how I first listed the | ||
# names above. TODO | ||
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buoy_sst_hg <- dplyr::filter(buoy_sst, | ||
stn_id %in% stn_id_hg) # generalise variable | ||
# names at some point to not be HG | ||
# specific TODO | ||
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# Usual style of plot: | ||
#for(i in 1:length(stn_id_hg)){ | ||
# plot(buoy_sst_hg, | ||
# stn_id = stn_id_hg[1]) %>% print() | ||
#} | ||
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# Want to calculate mean for each time period | ||
buoy_sst_hg_spring <- list() | ||
for(i in 1:length(stn_id_hg)){ | ||
buoy_sst_hg_spring[[i]] <- | ||
dplyr::filter(buoy_sst_hg, | ||
stn_id %in% stn_id_hg[i], | ||
lubridate::month(date) %in% c(3, 4, 5)) %>% | ||
dplyr::mutate(year = lubridate::year(date)) %>% | ||
dplyr::group_by(year) %>% | ||
summarise(mean = mean(sst, | ||
na.rm = TRUE)) | ||
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# TODO add a check for how many days in the period, like in quality control | ||
# for buoy_sst. | ||
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plot(buoy_sst_hg_spring[[i]], | ||
xlim = range(years), | ||
main = paste0("Mean spring SST, ", | ||
names_hg[i]), | ||
type = "o") | ||
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} | ||
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} |
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