## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>", eval = FALSE, warning = FALSE ) ## ----------------------------------------------------------------------------- # library(faunabr) # #Carregar dados # bf <- load_faunabr(data_dir = my_dir, #Pasta onde foi salvo o arquivo com get_faunabr() # data_version = "latest", #Versão mais recente # type = "short") #Versão resumida # #> Loading version 1.3 ## ----------------------------------------------------------------------------- # #Obter as opções disponíveis para filtrar por forma de vida, habitat e origem # fauna_at <- fauna_attributes(data = bf, # attribute = c("lifeForm", "habitat", "origin")) # head(fauna_at$lifeForm) # #> lifeForm # #> 1 colonial # #> 2 comensal # #> 3 ectoparasito # #> 4 ectoparasitoide # #> 5 endoparasito # #> 6 endoparasitoide # # head(fauna_at$habitat) # #> habitat # #> 1 agua_doce # #> 2 aguas_subterraneas # #> 3 arboreo # #> 4 cavernicola # #> 5 fossorial # #> 6 hiporreico # # head(fauna_at$origin) # #> origin # #> 1 criptogenica # #> 2 exotica # #> 3 nativa ## ----------------------------------------------------------------------------- # insects_rj <- select_fauna(data = bf, include_subspecies = FALSE, # phylum = "all", # class = "Insecta", #Insetos # order = "all", # family = "all", # genus = "all", # lifeForm = "all", filter_lifeForm = "in", # habitat = "arboreo", filter_habitat = "in", # states = "RJ", #Rio de Janeiro # filter_states = "in", #Que ocorrem NO RJ # country = "all", filter_country = "in", # origin = "nativa", # taxonomicStatus = "valido") # nrow(insects_rj) # #> [1] 114 ## ----------------------------------------------------------------------------- # #Primeiros 7 valores únicos de Estados onde as espécies ocorrem # unique(insects_rj$states)[1:7] # #> [1] "AC;AM;AP;BA;CE;DF;ES;GO;MA;MG;MS;MT;PA;PE;RJ;RN;RO;RR;SE;SP;TO" # #> [2] "BA;MA;MG;MT;PR;RJ;RS;SC;SP" # #> [3] "ES;MG;PE;PR;RJ;RS;SP" # #> [4] "ES;PR;RJ;SP" # #> [5] "RJ" # #> [6] "RJ;SP" # #> [7] "ES;MG;RJ;RS;SC;SP" ## ----------------------------------------------------------------------------- # insects_rj_only <- select_fauna(data = bf, include_subspecies = FALSE, # phylum = "all", # class = "Insecta", #Insetos # order = "all", # family = "all", # genus = "all", # lifeForm = "all", filter_lifeForm = "in", # habitat = "arboreo", filter_habitat = "in", # states = "RJ", #Rio de Janeiro # filter_states = "only", #Com ocorrência APENAS no RJ # country = "all", filter_country = "in", # origin = "nativa", # taxonomicStatus = "valido") # nrow(insects_rj_only) # #> [1] 22 # unique(insects_rj_only$states) # #> [1] "RJ" ## ----------------------------------------------------------------------------- # insects_south <- select_fauna(data = bf, include_subspecies = FALSE, # phylum = "all", # class = "Insecta", #Insetos # order = "all", # family = "all", # genus = "all", # lifeForm = "all", filter_lifeForm = "in", # habitat = "all", filter_habitat = "in", # states = c("PR", "SC", "RS"), #Estados do Sul do Brasil # filter_states = "in", #EM qualquer um dos estados # country = "all", filter_country = "in", # origin = "nativa", # taxonomicStatus = "valido") # nrow(insects_south) # #> [1] 11461 # # #Primeiros 10 valores únicos de Estados onde as espécies ocorrem # unique(insects_south$states)[1:10] # #> [1] "PR;SP" # #> [2] "BA;MT;RJ;RS" # #> [3] "RS" # #> [4] "PR" # #> [5] "PR;RS" # #> [6] "GO;PA;RO;RR;SC" # #> [7] "MG;PR;SP" # #> [8] "GO;MG;PR;RS;SC" # #> [9] "GO;RJ;SC" # #> [10] "AC;AL;AM;AP;BA;CE;DF;ES;GO;MA;MG;MS;MT;PA;PB;PE;PI;PR;RJ;RN;RO;RR;RS;SC;SE;SP;TO" ## ----------------------------------------------------------------------------- # insects_south_and <- select_fauna(data = bf, include_subspecies = FALSE, # phylum = "all", # class = "Insecta", #Insetos # order = "all", # family = "all", # genus = "all", # lifeForm = "all", filter_lifeForm = "in", # habitat = "all", filter_habitat = "in", # states = c("PR", "SC", "RS"), # filter_states = "and", #PR & SC & RS # country = "all", filter_country = "in", # origin = "nativa", # taxonomicStatus = "valido") # nrow(insects_south_and) # #> [1] 1924 # # #Primeiros 10 valores únicos de Estados onde as espécies ocorrem # unique(insects_south_and$states)[1:10] # #> [1] "GO;MG;PR;RS;SC" # #> [2] "AC;AL;AM;AP;BA;CE;DF;ES;GO;MA;MG;MS;MT;PA;PB;PE;PI;PR;RJ;RN;RO;RR;RS;SC;SE;SP;TO" # #> [3] "AC;AM;MG;MS;MT;PA;PE;PR;RO;RS;SC;SP" # #> [4] "AM;BA;CE;DF;ES;GO;MG;MS;MT;PA;PE;PR;RJ;RS;SC;SP" # #> [5] "AC;AM;AP;BA;CE;DF;ES;GO;MG;MS;MT;PA;PE;PR;RJ;RO;RR;RS;SC;SE;SP;TO" # #> [6] "BA;ES;MG;PR;RJ;RS;SC;SP" # #> [7] "AM;DF;ES;GO;PR;RJ;RR;RS;SC;SP" # #> [8] "ES;GO;MG;PR;RJ;RS;SC;SP" # #> [9] "AC;AM;AP;BA;CE;ES;GO;MA;MG;MT;PA;PR;RJ;RO;RS;SC;SP;TO" # #> [10] "GO;MG;MS;PR;RO;RS;SC;SP" ## ----------------------------------------------------------------------------- # insects_south_only <- select_fauna(data = bf, include_subspecies = FALSE, # phylum = "all", # class = "Insecta", #Insetos # order = "all", # family = "all", # genus = "all", # lifeForm = "all", filter_lifeForm = "in", # habitat = "all", filter_habitat = "in", # states = c("PR", "SC", "RS"), # filter_states = "only", #Apenas no PR & SC & RS # country = "all", filter_country = "in", # origin = "nativa", # taxonomicStatus = "valido") # nrow(insects_south_only) # #> [1] 134 # # #Valor único de Estados onde as espécies ocorrem # unique(insects_south_only$states) # #> [1] "PR;RS;SC" ## ----------------------------------------------------------------------------- # complete_names <- c("Pantera onca (Linnaeus, 1758)", # "Zonotrichia capensis subtorquata Swainson, 1837", # "Mazama bororo Duarte, 1996", # "Mazama jucunda Thomas, 1913", # "Arrenurus tumulosus intercursor", # "Araucaria angustifolia") # #Panthera onca com erros de digitação para ilustrar como a próxima função os corrige # #Araucaria angustifolia (uma planta) foi usada apenas como um exemplo que será utilizado para ilustrar a próxima função # binomial_names <- extract_binomial(species_names = complete_names) # binomial_names # #> [1] "Pantera onca" "Zonotrichia capensis" # #> [3] "Mazama bororo" "Mazama jucunda" # #> [5] "Arrenurus tumulosus" "Araucaria angustifolia" ## ----------------------------------------------------------------------------- # #Checar nomes # checked_names <- check_fauna_names(data = bf, # species = binomial_names, # include_subspecies = FALSE, # max_distance = 0.1) # tibble::tibble(checked_names) #Exibir tabela como tibble # #> # A tibble: 6 x 9 # #> input_name Spelling Suggested_name Distance taxonomicStatus nomenclaturalStatus validName family matches # #> # #> 1 "Zonotrichia capensis" Correct Zonotrichia capensis 0 valido NA NA Passerellidae single # #> 2 "Mazama bororo" Correct Mazama bororo 0 sinonimo NA Mazama jucunda Cervidae single # #> 3 "Mazama jucunda" Correct Mazama jucunda 0 valido NA NA Cervidae single # #> 4 "Arrenurus tumulosus" Correct Arrenurus tumulosus 0 valido NA NA Arrenuridae single # #> 5 "Pantera onca" Probably_incorrect Panthera onca 2 valido NA NA Felidae single # #> 6 "Araucaria angustifolia" Not_found NA NA NA NA NA NA none ## ----------------------------------------------------------------------------- # #Obter apenas nomes validos # valids <- unique(checked_names$validName) # valids <- na.omit(valids) #Remove NAs # # #Subselecionar especies # my_sp <- subset_fauna(data = bf, species = valids, # include_subspecies = FALSE) # tibble::tibble(my_sp) # # A tibble: 4 x 21 # #> species subspecies scientificName validName kingdom phylum class order family genus lifeForm habitat states countryCode origin # #> # #> 1 Panthera onca NA Panthera onca~ NA Animal~ Chord~ Mamm~ Carn~ Felid~ Pant~ "vida_l~ "terre~ AC;AM~ AR;BO;BR;B~ nativa # #> 2 Arrenurus tumulo~ NA Arrenurus (In~ NA Animal~ Arthr~ Arac~ Trom~ Arren~ Arre~ "" "" NA NA NA # #> 3 Mazama jucunda NA Mazama jucund~ NA Animal~ Chord~ Mamm~ Arti~ Cervi~ Maza~ "herbiv~ "terre~ BA;ES~ BR nativa # #> 4 Zonotrichia cape~ NA Zonotrichia c~ NA Animal~ Chord~ Aves Pass~ Passe~ Zono~ "" "" NA NA nativa # # i 5 more variables: nomenclaturalStatus , vernacularName , taxonRank , id , language ## ----------------------------------------------------------------------------- # my_sp2 <- subset_fauna(data = bf, species = valids, # include_subspecies = TRUE) # tibble::tibble(my_sp2) #print data.frame as tibble # #> # A tibble: 14 × 19 # #> species subspecies scientificName validName kingdom phylum class order family genus lifeForm habitat states countryCode #> origin # #> #> # #> 1 Panthera on… "" Panthera onca… "" Animal… Chord… Mamm… Carn… Felid… Pant… "free_l… "terre… AC;AM… argentina;… #> "nati… # #> 2 Arrenurus (… "" Arrenurus (In… "" Animal… Arthr… Arac… Trom… Arren… Arre… "" "" NA brazil "" #> # #> 3 Arrenurus (… "Arrenuru… Arrenurus (In… "" Animal… Arthr… Arac… Trom… Arren… Arre… "" "" NA brazil "" #> # #> 4 Arrenurus (… "Arrenuru… Arrenurus (In… "" Animal… Arthr… Arac… Trom… Arren… Arre… "" "" NA brazil "" #> # #> 5 Mazama jucu… "" Mazama jucund… "" Animal… Chord… Mamm… Arti… Cervi… Maza… "herbiv… "terre… BA;ES… brazil #> "nati… # #> 6 Zonotrichia… "" Zonotrichia c… "" Animal… Chord… Aves Pass… Passe… Zono… "free_l… "" AL;AP… brazil #> "nati… # #> 7 Zonotrichia… "Zonotric… Zonotrichia c… "" Animal… Chord… Aves Pass… Passe… Zono… "free_l… "" AP brazil #> "nati… # #> 8 Zonotrichia… "Zonotric… Zonotrichia c… "" Animal… Chord… Aves Pass… Passe… Zono… "free_l… "" RR brazil #> "nati… # #> 9 Zonotrichia… "Zonotric… Zonotrichia c… "" Animal… Chord… Aves Pass… Passe… Zono… "free_l… "" RR brazil #> "nati… # #> 10 Zonotrichia… "Zonotric… Zonotrichia c… "" Animal… Chord… Aves Pass… Passe… Zono… "free_l… "" BA;MA… brazil #> "nati… # #> 11 Zonotrichia… "Zonotric… Zonotrichia c… "" Animal… Chord… Aves Pass… Passe… Zono… "free_l… "" PA brazil #> "nati… # #> 12 Zonotrichia… "Zonotric… Zonotrichia c… "" Animal… Chord… Aves Pass… Passe… Zono… "free_l… "" AP;PA… brazil #> "nati… # #> 13 Zonotrichia… "Zonotric… Zonotrichia c… "" Animal… Chord… Aves Pass… Passe… Zono… "free_l… "" ES;MG… brazil #> "nati… # #> 14 Zonotrichia… "Zonotric… Zonotrichia c… "" Animal… Chord… Aves Pass… Passe… Zono… "free_l… "" TO brazil #> "nati… # #> # ℹ 4 more variables: taxonomicStatus , nomenclaturalStatus , vernacularName , taxonRank # #> ## ----------------------------------------------------------------------------- # spp <- c("Panthera onca", "Mazama jucunda", "Subulo gouzoubira") # spp_syn <- fauna_synonym(data = bf, species = spp) # spp_syn # #> validName synonym taxonomicStatus # #> 49343 Panthera onca valido # #> 60523 Mazama jucunda Mazama bororo sinonimo # #> 61168 Subulo gouzoubira Mazama gouazoubira sinonimo