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Remove beta diversity analysis
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‎01_Summary_Calculations.R

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@@ -213,10 +213,6 @@ BRLEAF_SUMM_SITE <- BLEAF_META %>%
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inner_join(GRFLORA_SITE) %>%
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inner_join(GRFLORA_AWI_SITE)
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BRLEAF_SUMM_SITE <- BRLEAF_SUMMARY %>% group_by(SITE_NO, YEAR) %>%
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summarise(MEAN_ALPHA = mean(SPECIES_RICH), .groups = "drop") %>%
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right_join(BRLEAF_SUMM_SITE) %>%
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mutate(BETA = SPECIES_RICH/MEAN_ALPHA)
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write.csv(BRLEAF_SUMM_SITE, "Outputs/Site level richness.csv",
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row.names = FALSE)

‎02_ChangeOverTime.Rmd

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@@ -727,30 +727,7 @@ awisite_emm %>%
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labs(y = "Proportion of AWI in site richness")
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```
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# Site-level Beta Diversity
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```{r gauss model sample prior v2}
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mod_pr <- prior(normal(4,1), class = "b", coef = "YR1971") +
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prior(normal(4,1), class = "b", coef = "YR2001") +
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prior(normal(4,1), class = "b", coef = "YR2022") +
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prior(normal(0,1), class = "b", coef = "YDAY") +
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prior(student_t(5, 0, 1), class = "sd")
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```
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```{r site rich mod run}
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site_beta_mod <- brm(BETA ~ -1 + YR + YDAY + (1|SITE),
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data = BRLEAF_SUMM_SITE, family = "gaussian",
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prior = mod_pr, cores = 4, warmup = 2000, iter = 6000, thin = 4,
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file = paste0(model_loc, "SITEBETA"))
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par_summary(site_beta_mod)
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```
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```{r site beta mod plots}
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mcmc_plot(site_beta_mod, type = "rank_overlay")
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pp_check(site_beta_mod, type = "ecdf_overlay", ndraws = 20)
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pp_check(site_beta_mod, type = "stat_2d")
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resid_bysite(site_beta_mod)
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```
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```{r emmeans site beta pairwise comparison table}

‎03_AshDieback.Rmd

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@@ -847,63 +847,4 @@ awisite_mod %>%
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```
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# Site-level beta diversity
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```{r gauss model prior v2}
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mod_pr <- prior(normal(4,1), class = "b", coef = "YR1971") +
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prior(normal(4,1), class = "b", coef = "YR2001") +
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prior(normal(4,1), class = "b", coef = "YR2022") +
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prior(normal(0,1), class = "b", coef = "YDAY") +
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prior(normal(0,1), class = "b", coef = "ASHDIEBACK") +
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prior(normal(0,1), class = "b", coef = "YR2001:ASHDIEBACK") +
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prior(normal(0,1), class = "b", coef = "YR2022:ASHDIEBACK") +
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prior(student_t(5, 0, 1), class = "sd")
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```
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```{r site beta mod run}
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site_beta_mod <- brm(BETA ~ -1 + YR*ASHDIEBACK + YDAY + (1|SITE),
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data = BRLEAF_SUMM_SITE, family = "gaussian",
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prior = mod_pr, cores = 4, warmup = 2000, iter = 6000, thin = 4,
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file = paste0(model_loc, "SITEBETA"))
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par_summary(site_beta_mod)
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```
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```{r site beta mod plots}
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mcmc_plot(site_beta_mod, type = "rank_overlay")
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pp_check(site_beta_mod, type = "ecdf_overlay", ndraws = 20)
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resid_bysite(site_beta_mod)
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```
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```{r cond effect site beta plot}
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plot(conditional_effects(site_beta_mod, "ASHDIEBACK:YR"),
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plot = FALSE)[[1]] +
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labs(x = "Proportion of plots with ash dieback",
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y = "Site level species richness") +
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scale_fill_manual(name = "Year",
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values = c("#56B4E9","#CC79A7","#D55E00"),
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aesthetics = c("fill","colour"))
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```
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```{r emtrends site beta}
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emtrends(site_beta_mod, ~ YR, var = "ASHDIEBACK") %>%
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knitr::kable(digits = 3, caption = "Ash dieback trend")
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```
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```{r emmeans site beta plot}
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sitebeta_emm <- emmeans(site_beta_mod, ~ ASHDIEBACK + YR,
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at = list(ASHDIEBACK = c(0,0.2,0.7)))
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sitebeta_emm %>%
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gather_emmeans_draws() %>%
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mutate(Year = as.numeric(as.character(YR)),
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.value = exp(.value),
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ASHDIEBACK = as.character(ASHDIEBACK)) %>%
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ggplot(aes(x = Year, y = .value, colour = ASHDIEBACK, fill = ASHDIEBACK)) +
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stat_lineribbon(alpha = 1/4) +
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scale_fill_manual(values = two_cols,
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aesthetics = c("colour","fill"),
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name = "Ash Dieback") +
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theme(axis.text = element_text(size = 12), axis.title = element_text(size = 14)) +
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labs(y = "Site level beta diversity")
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```

‎04_Deer.Rmd

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@@ -853,57 +853,3 @@ awisite_emm %>%
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theme(axis.text = element_text(size = 12), axis.title = element_text(size = 14)) +
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labs(y = "Site-level AWI proportion")
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```
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# Site level beta diversity
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```{r gauss model sample prior site level}
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mod_pr <- prior(normal(4,1), class = "b", coef = "YR1971") +
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prior(normal(4,1), class = "b", coef = "YR2001") +
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prior(normal(4,1), class = "b", coef = "YR2022") +
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prior(normal(0,1), class = "b", coef = "YDAY") +
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prior(normal(0,1), class = "b", coef = "moDEER") +
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prior(normal(0,1), class = "b", coef = "moDEER:YR2001") +
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prior(normal(0,1), class = "b", coef = "moDEER:YR2022") +
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prior(dirichlet(1), class = "simo", coef = "moDEER1") +
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prior(dirichlet(1), class = "simo", coef = "moDEER:YR20011") +
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prior(dirichlet(1), class = "simo", coef = "moDEER:YR20221") +
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prior(student_t(5, 0, 1), class = "sd")
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```
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```{r site beta mod run}
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site_beta_mod <- brm(BETA ~ -1 + YR*mo(DEER) + YDAY + (1|SITE),
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data = BRLEAF_SUMM_SITE, family = "gaussian",
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prior = mod_pr, cores = 4, warmup = 2000, iter = 6000, thin = 4,
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file = paste0(model_loc, "SITEBETA"))
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par_summary(site_beta_mod)
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```
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```{r site beta mod plots}
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mcmc_plot(site_beta_mod, type = "rank_overlay")
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pp_check(site_beta_mod, type = "ecdf_overlay", ndraws = 20)
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resid_bysite(site_beta_mod)
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```
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```{r emmeans site beta pairwise comparison table}
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sitebeta_emm <- emmeans(site_beta_mod, ~ DEER | YR)
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pairs(sitebeta_emm, type = "response") %>%
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knitr::kable(digits = 3, caption = "Site level beta diversity on response-scale")
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```
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```{r emmeans site beta plot}
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sitebeta_emm %>%
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gather_emmeans_draws() %>%
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mutate(Year = as.numeric(as.character(YR)),
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.value = exp(.value)) %>%
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ggplot(aes(x = Year, y = .value, colour = DEER, fill = DEER)) +
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stat_lineribbon(alpha = 1/4) +
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scale_fill_manual(values = two_cols,
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aesthetics = c("colour","fill"),
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name = "Deer Risk") +
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theme(axis.text = element_text(size = 12), axis.title = element_text(size = 14)) +
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labs(y = "Site-level Species Beta Diversity")
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```
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‎05_AshDiebackandDeer.Rmd

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@@ -866,61 +866,3 @@ awisite_emm %>%
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```
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# Site level beta diversity
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```{r gauss model sample prior site level}
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mod_pr <- prior(normal(4,1), class = "b", coef = "YR1971") +
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prior(normal(4,1), class = "b", coef = "YR2001") +
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prior(normal(4,1), class = "b", coef = "YR2022") +
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prior(normal(0,1), class = "b") +
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prior(dirichlet(1), class = "simo", coef = "moDEER1") +
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prior(dirichlet(1), class = "simo", coef = "moDEER:YR20011") +
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prior(dirichlet(1), class = "simo", coef = "moDEER:YR20221") +
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prior(dirichlet(1), class = "simo", coef = "moDEER:YR2001:ASHDIEBACK1") +
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prior(dirichlet(1), class = "simo", coef = "moDEER:YR2022:ASHDIEBACK1") +
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prior(student_t(5, 0, 1), class = "sd")
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```
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```{r site beta mod run}
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site_beta_mod <- brm(BETA ~ -1 + YR*mo(DEER)*ASHDIEBACK + YDAY + (1|SITE),
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data = BRLEAF_SUMM_SITE, family = "gaussian",
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prior = mod_pr, cores = 4, warmup = 2000, iter = 6000, thin = 4,
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file = paste0(model_loc, "SITEBETA"))
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par_summary(site_beta_mod)
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```
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```{r site beta mod plots}
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mcmc_plot(site_beta_mod, type = "rank_overlay")
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pp_check(site_beta_mod, type = "ecdf_overlay", ndraws = 20)
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resid_bysite(site_beta_mod)
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```
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```{r emtrends site beta}
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emtrends(site_beta_mod, ~ DEER + YR, var = "ASHDIEBACK") %>%
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knitr::kable(digits = 3, caption = "Ash dieback trend")
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```
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904-
```{r emmeans site beta pairwise comparison table}
905-
sitebeta_emm <- emmeans(site_beta_mod, ~ YR | DEER + ASHDIEBACK,
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at = list(ASHDIEBACK = c(0,0.2,0.7)))
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pairs(sitebeta_emm, type = "response") %>%
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knitr::kable(digits = 3, caption = "Site level richness on response-scale")
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```
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911-
```{r emmeans site beta plot}
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sitebeta_emm %>%
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gather_emmeans_draws() %>%
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mutate(Year = as.numeric(as.character(YR)),
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.value = exp(.value),
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ASHDIEBACK = as.character(ASHDIEBACK)) %>%
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ggplot(aes(x = Year, y = .value, colour = ASHDIEBACK, fill = ASHDIEBACK)) +
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stat_lineribbon(alpha = 1/4) +
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scale_fill_manual(values = two_cols,
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aesthetics = c("colour","fill"),
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name = "Ash Dieback") +
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facet_wrap(~DEER) +
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theme(axis.text = element_text(size = 11), strip.text = element_text(size = 12),
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legend.text = element_text(size = 10), axis.title = element_text(size = 14)) +
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labs(y = "Site-level Beta Diversity")
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```

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