In brouwern/DRmencia: Data and code to replicate analyses for Latta, Brouwer, et al. 2018. PeerJ.

knitr::opts_chunk$set(echo = TRUE)

ann_caps$status.focals[which(ann_caps$spp.code == "LOST")] <- NA

ann_caps$status.focals[which(ann_caps$spp.code == "WOTH")] <- "mig"
ann_caps$status.focals[which(ann_caps$spp.code == "PALM")] <- "mig"
ann_caps$status.focals[which(ann_caps$spp.code == "MAWA")] <- "mig"
ann_caps$status.focals[which(ann_caps$spp.code == "INBU")] <- "mig"
ann_caps$status.focals[which(ann_caps$spp.code == "TEWA")] <- "mig"
ann_caps$status.focals[which(ann_caps$spp.code == "NOPA")] <- "mig"
ann_caps$status.focals[which(ann_caps$spp.code == "LOWA")] <- "mig"
ann_caps$status.focals[which(ann_caps$spp.code == "BWWA")] <- "mig"
ann_caps$status.focals[which(ann_caps$spp.code == "HOWA")] <- "mig"
ann_caps$status.focals[which(ann_caps$spp.code == "GRCA")] <- "mig"
ann_caps$status.focals[which(ann_caps$spp.code == "RBGR")] <- "mig"
ann_caps$status.focals[which(ann_caps$spp.code == "SUTA")] <- "mig"
ann_caps$status.focals[which(ann_caps$spp.code == "YRWA")] <- "mig"


ann_caps$status.focals[which(ann_caps$spp.code == "YBCU")] <- "res"
ann_caps$status.focals[which(ann_caps$spp.code == "SSHA")] <- "res"
ann_caps$status.focals[which(ann_caps$spp.code == "SBMU")] <- "res"
ann_caps$status.focals[which(ann_caps$spp.code == "SBAN")] <- "res"
ann_caps$status.focals[which(ann_caps$spp.code == "RTSO")] <- "res"
ann_caps$status.focals[which(ann_caps$spp.code == "NOPO")] <- "res"
ann_caps$status.focals[which(ann_caps$spp.code == "HITR")] <- "res"
ann_caps$status.focals[which(ann_caps$spp.code == "GRAK")] <- "res"
ann_caps$status.focals[which(ann_caps$spp.code == "WFQD")] <- "res"
ann_caps$status.focals[which(ann_caps$spp.code == "ZEND")] <- "res"
ann_caps$status.focals[which(ann_caps$spp.code == "HIWO")] <- "res"
ann_caps$status.focals[which(ann_caps$spp.code == "MACU")] <- "res"
ann_caps$status.focals[which(ann_caps$spp.code == "AMKE")] <- "res"

ann_caps$status.focals[which(ann_caps$spp.code == "HIPE")] <- "res"
ann_caps$status.focals[which(ann_caps$spp.code == "KWQD")] <- "res"
ann_caps$status.focals[which(ann_caps$spp.code == "RUQD")] <- "res"

ann_caps$status.focals[which(ann_caps$spp.code == "BWVI")] <- "res"

ann_caps$status.focals[which(ann_caps$spp.code == "HISP")] <- "res"
ann_caps$status.focals[which(ann_caps$spp.code == "COGD")] <- "res"
ann_caps$status.focals[which(ann_caps$spp.code == "ANPI")] <- "res"
ann_caps$status.focals[which(ann_caps$spp.code == "BLGR")] <- "res"
ann_caps$status.focals[which(ann_caps$spp.code == "BLPW")] <- "res"
ann_caps$status.focals[which(ann_caps$spp.code == "BUOW")] <- "res"

Reshape for general community analyses

library(vegan)

spp_matrix_by_stat <- dcast(data = ann_caps,
      formula = site + year + 
                year.num + site.age + 
                site.age.init + 
                site.age.cent +
        status.focals ~ spp.code,
      value.var = "spp.code",
        fun.aggregate = length)

#isoalte colnames that are spp
i.spp.names <- grep("[A-Z][A-Z][A-Z][A-Z]",names(spp_matrix_by_stat))

with(spp_matrix_by_stat,table(site, site.age))

#isolate predictoras
community_dat_by_stat <- spp_matrix_by_stat[,-i.spp.names]


convert2.zero <- function(x){ifelse(x > 0,1,0)}

temp <- spp_matrix_by_stat[,i.spp.names]
temp <- apply(temp,2,convert2.zero)

specnumber(temp)

community_dat_by_stat$spp.rich <- rowSums(temp)

community_dat_by_stat2<-dcast(data = community_dat_by_stat,
      formula = site + year + 
                year.num + site.age + 
                site.age.init + 
                site.age.cent ~ status.focals,
      value.var = "spp.rich",
      fun.aggregate = sum)

community_dat_by_stat2$mig.prcnt <- with(community_dat_by_stat2,
                                         (mig/(mig+res)))

ggplot(data = community_dat_by_stat2,
       aes(y = mig.prcnt,
           x = site,
           color = year,
           shape = site)) + geom_point() +geom_smooth()

community_dat_by_stat$site <- factor(community_dat_by_stat$site,
                        levels =c("La Cueva","La Caoba",
                                  "Morelia","El Corral","Aceitillar"))

ggplot(data = community_dat_by_stat,
       aes(y = spp.rich,
           x = site,
           color = status.focals)) +
  geom_point() + facet_wrap(~status.focals)


summary(glm(cbind()))

brouwern/DRmencia documentation built on May 6, 2019, 12:24 p.m.