diff --git a/.github/workflows/build.yaml b/.github/workflows/build.yaml
index 842c111..c2e117f 100644
--- a/.github/workflows/build.yaml
+++ b/.github/workflows/build.yaml
@@ -48,6 +48,8 @@ jobs:
             any::rmarkdown
             any::knitr
             any::prettymapr
+            any::sysfonts
+            any::showtext
 
       - name: Publish to GitHub Pages (and render)
         uses: quarto-dev/quarto-actions/publish@v2
diff --git a/R/funcs.R b/R/funcs.R
index e45aead..9468b05 100644
--- a/R/funcs.R
+++ b/R/funcs.R
@@ -1,4 +1,8 @@
 
+sysfonts::font_add_google('Roboto')
+showtext::showtext_auto()
+showtext::showtext_opts(dpi = 200)
+
 # utility functions ---------------------------------------------------------------------------
 
 # get rdata from github
@@ -67,14 +71,15 @@ pyro_plo <- function(yr = 2021, mo = c('Jun', 'Oct')){
   
   m <- m + 
     ggplot2::geom_sf(data = tomap, ggplot2::aes(size = count), fill = 'red', color = 'red', pch = 21, alpha = 0.5, inherit.aes = F) +
-    ggplot2::theme_minimal() + 
+    ggplot2::theme_minimal(base_family = 'Roboto') +
     ggplot2::theme(
       panel.grid = ggplot2::element_blank(), 
       axis.title = ggplot2::element_blank(), 
       axis.text.y = ggplot2::element_text(size = 8), 
       axis.text.x = ggplot2::element_text(size = 8, angle = 30, hjust = 1),
       axis.ticks = ggplot2::element_line(colour = 'grey'),
-      panel.background = ggplot2::element_rect(fill = NA, color = 'black')
+      panel.background = ggplot2::element_rect(fill = NA, color = 'black'), 
+      text = ggplot2::element_text(family = 'Roboto')
     ) +
     ggplot2::scale_size_continuous(range = c(2, 10)) +
     ggplot2::labs(
@@ -84,7 +89,7 @@ pyro_plo <- function(yr = 2021, mo = c('Jun', 'Oct')){
     ) 
   
   m <- m +
-    ggspatial::annotation_scale(location = 'br', unit_category = 'metric')
+    ggspatial::annotation_scale(location = 'br', unit_category = 'metric', text_family = 'Roboto')
   m <- m +
     ggspatial::annotation_north_arrow(location = 'tl', which_north = "true", height = grid::unit(0.75, "cm"), 
                                       width = grid::unit(0.75, "cm"))
@@ -129,10 +134,11 @@ adload_plo <- function(){
     ggplot2::geom_text(ggplot2::aes(label = percent, size = toemph), hjust = -0.25, show.legend = F) +
     ggplot2::scale_fill_manual(values = c('#004F7E', '#958984')) +
     ggplot2::scale_x_continuous(expand = c(0, 0), limits = c(0, 1.1* max(toplo$tn_load / 1000))) +
-    ggplot2::theme_minimal(base_size = 14) +
+    ggplot2::theme_minimal(base_size = 14, base_family = 'Roboto') +
     ggplot2::scale_y_discrete(expand = c(0, 0)) +
     ggplot2::theme(
       panel.grid = ggplot2::element_blank(), 
+      text = ggplot2::element_text(family = 'Roboto')
       # axis.text = ggplot2::element_text(size = 14) 
     ) +
     ggplot2::scale_size_manual(values = c(6, 4)) +
@@ -167,12 +173,13 @@ bacwbid_plo <- function(){
     dplyr::select(-PARAMETER_GROUP, -PARAMETER_ASSESSED) |>
     unique()
   
-  m <- ggplot() +
+  m <- ggplot2::ggplot() +
     annotation_map_tile(zoom = 10, type = 'cartolight', progress = 'none', quiet = T) +
-    ggspatial::annotation_scale(location = 'br', unit_category = 'metric') +
+    ggspatial::annotation_scale(location = 'br', unit_category = 'metric', text_family = 'Roboto') +
     ggspatial::annotation_north_arrow(location = 'tl', which_north = "true", height = grid::unit(0.75, "cm"), width = grid::unit(0.75, "cm")) +
-    geom_sf(data = tbvwbid, fill = 'red', col = 'red', alpha = 0.6) +
-    theme_minimal()
+    ggplot2::geom_sf(data = tbvwbid, fill = 'red', col = 'red', alpha = 0.6) +
+    ggplot2::theme_minimal(base_family = 'Roboto') + 
+    ggplot2::theme(text = ggplot2::element_text(family = 'Roboto'))
   
   return(m)
   
@@ -214,10 +221,11 @@ intertidal_plo <- function(curyr = 2020){
                        color = 'white', fontface = 'bold') +
     ggplot2::facet_wrap(~name) +
     ggplot2::coord_polar('y', start = 0) +
-    ggplot2::theme_void() +
+    ggplot2::theme_void(base_family = 'Roboto') +
     ggplot2::scale_fill_manual(values = c('#028576', '#427355', '#76923C')) + 
     ggplot2::theme(
       legend.position = 'bottom', 
+      text = ggplot2::element_text(family = 'Roboto'),
       strip.text = ggplot2::element_text(size = 15), 
       legend.text = ggplot2::element_text(size = 13)
     ) +  
@@ -249,7 +257,7 @@ cchasites_plo <- function(){
   
   m <- ggplot2::ggplot() +
     ggspatial::annotation_map_tile(zoom = 10, type = 'cartolight', quiet = T, progress = 'none') +
-    ggspatial::annotation_scale(location = 'bl', unit_category = 'metric') +
+    ggspatial::annotation_scale(location = 'bl', unit_category = 'metric', text_family = 'Roboto') +
     ggspatial::annotation_north_arrow(location = 'tr', which_north = "true", height = grid::unit(0.75, "cm"), width = grid::unit(0.75, "cm")) +
     ggplot2::geom_sf(data = tomap, inherit.aes = F, size = 2) +
     ggrepel::geom_text_repel(data = tomap, ggplot2::aes(label = site, x = lon, y = lat), inherit.aes = F) +
@@ -257,7 +265,10 @@ cchasites_plo <- function(){
       x = NULL, 
       y = NULL
     ) +
-    ggplot2::theme_minimal() +
+    ggplot2::theme_minimal(base_family = 'Roboto') +
+    ggplot2::theme(
+      text = ggplot2::element_text(family = 'Roboto')
+    ) +
     ggplot2::coord_sf(xlim = dat_ext[c(1, 3)], ylim = dat_ext[c(2, 4)], expand = FALSE, crs = 4326)
   
   return(m)
@@ -288,7 +299,7 @@ tdlcrk_plo <- function(maxyr = 2022){
   
   m <- ggplot2::ggplot() +
     ggspatial::annotation_map_tile(zoom = 10, type = 'cartolight', quiet = T, progress = 'none') +
-    ggspatial::annotation_scale(location = 'bl', unit_category = 'metric') +
+    ggspatial::annotation_scale(location = 'bl', unit_category = 'metric', text_family = 'Roboto') +
     ggspatial::annotation_north_arrow(location = 'tr', which_north = "true", height = grid::unit(0.75, "cm"), width = grid::unit(0.75, "cm")) +
     ggplot2::geom_sf(data = tomap, ggplot2::aes(col = score, fill = score), inherit.aes = F, linewidth = 0.75) +
     ggplot2::scale_color_manual(values = cols) +
@@ -299,7 +310,10 @@ tdlcrk_plo <- function(maxyr = 2022){
       color = NULL, 
       fill = NULL
     ) +
-    ggplot2::theme_minimal() +
+    ggplot2::theme_minimal(base_family = 'Roboto') +
+    ggplot2::theme(
+      text = ggplot2::element_text(family = 'Roboto')
+    ) +
     ggplot2::coord_sf(xlim = dat_ext[c(1, 3)], ylim = dat_ext[c(2, 4)], expand = FALSE, crs = 4326)
   
   return(m)
@@ -343,12 +357,13 @@ scallop_plo <- function(){
       x = NULL, 
       y = 'Scallops found'
     ) +
-    ggplot2::theme_minimal() +
+    ggplot2::theme_minimal(base_family = 'Roboto') +
     ggplot2::theme(
       axis.text.x = ggplot2::element_text(angle = 45, hjust = 1),
       panel.grid.major.x = ggplot2::element_blank(),
       panel.grid.minor.x = ggplot2::element_blank(),
-      panel.grid.minor.y = ggplot2::element_blank()
+      panel.grid.minor.y = ggplot2::element_blank(),
+      text = ggplot2::element_text(family = 'Roboto')
     )
   
   return(p)
@@ -389,7 +404,7 @@ fim_plo <- function(){
       x = NULL, 
       y = 'Number per set'
     ) +
-    ggplot2::theme_minimal() + 
+    ggplot2::theme_minimal(base_family = 'Roboto') + 
     ggplot2::theme(
       legend.position = 'none', 
       panel.grid.minor.y = ggplot2::element_blank(), 
@@ -397,7 +412,8 @@ fim_plo <- function(){
       # panel.grid.major.x = ggplot2::element_blank(),
       panel.grid.minor.x = ggplot2::element_blank(),
       axis.title.y = ggplot2::element_text(size = 12), 
-      axis.text.x = ggplot2::element_text(size = 11)
+      axis.text.x = ggplot2::element_text(size = 11), 
+      text = ggplot2::element_text(family = 'Roboto')
     )
   
   return(p)
@@ -423,7 +439,7 @@ waterbird_plo <- function(){
   
   m <- ggplot2::ggplot() +
     ggspatial::annotation_map_tile(zoom = 10, type = 'cartolight', quiet = T, progress = 'none') +
-    ggspatial::annotation_scale(location = 'br', unit_category = 'metric') +
+    ggspatial::annotation_scale(location = 'br', unit_category = 'metric', text_family = 'Roboto') +
     ggspatial::annotation_north_arrow(location = 'tl', which_north = "true", height = grid::unit(0.75, "cm"), width = grid::unit(0.75, "cm")) +
     ggplot2::geom_sf(data = tomap, ggplot2::aes(fill = status), col = 'black', pch = 21, inherit.aes = F, size = 3) +
     # ggplot2::scale_color_manual(values = cols) +
@@ -434,9 +450,10 @@ waterbird_plo <- function(){
       color = NULL, 
       fill = NULL
     ) +
-    ggplot2::theme_minimal() +
+    ggplot2::theme_minimal(base_family = 'Roboto') +
     ggplot2::theme(
-      legend.position = 'top'
+      legend.position = 'top',
+      text = ggplot2::element_text(family = 'Roboto')
     )
   
   return(m)
@@ -496,21 +513,24 @@ gadsum_plo <- function(h = 5.5, w = 30, padding = 0, rows = 5){
     dplyr::mutate(
       x = rep(seq(0, (!!w + padding) * cols - 1, !!w + padding), times = rows),
       y = rep(seq(0, (!!h + padding) * rows - 1, !!h + padding), each = cols),
-      info = stringr::str_wrap(info, 75)
+      info = stringr::str_wrap(info, 80)
     )
   
   p <- ggplot2::ggplot(toplo, ggplot2::aes(x, y, height = h, width = w, label = info)) +
     ggplot2::geom_tile(ggplot2::aes(fill = name)) +
-    ggplot2::geom_text(fontface = "bold", size = 12,
+    ggplot2::geom_text(fontface = "bold", size = 6,
                        ggplot2::aes(label = value, x = x - w/2.2, y = y + h/4, color = name), hjust = 0) +
-    ggplot2::geom_text(size = 7, lineheight = 0.5,
+    ggplot2::geom_text(size = 3.3, lineheight = 1.2,
                        ggplot2::aes(color = name, label = info, x = x - w/2.2, y = y - h/6), hjust = 0) +
     ggplot2::coord_fixed() +
     ggplot2::scale_fill_brewer(type = "cont", palette = "Blues", direction = -1) +
     ggplot2::scale_color_manual(values = toplo$txtcols) +
-    ggplot2::geom_text(size = 32, ggplot2::aes(label = icon, family = font_family,
+    ggplot2::geom_text(size = 17, ggplot2::aes(label = icon, family = font_family,
                                                x = x + w/2.5, y = y + h/14), alpha = 0.25) +
-    ggplot2::theme_void() +
+    ggplot2::theme_void(base_family = 'Roboto') +
+    ggplot2::theme(
+      text = ggplot2::element_text(family = 'Roboto')
+    ) +
     ggplot2::guides(
       fill = 'none', 
       color = 'none'
@@ -566,12 +586,13 @@ seagrassph_plo <- function(){
       x = NULL, 
       fill = NULL
     ) +
-    ggplot2::theme_minimal() +
+    ggplot2::theme_minimal(base_family = 'Roboto') +
     ggplot2::theme(
       legend.position = 'top', 
       panel.grid.minor = ggplot2::element_blank(), 
       axis.text.x = ggplot2::element_text(size = 11), 
-      legend.text = ggplot2::element_text(size = 11)
+      legend.text = ggplot2::element_text(size = 11),
+      text = ggplot2::element_text(family = 'Roboto')
     )
   
   return(p)
diff --git a/_site/docs/communities/cc1.html b/_site/docs/communities/cc1.html
index c62adb6..da183de 100644
--- a/_site/docs/communities/cc1.html
+++ b/_site/docs/communities/cc1.html
@@ -350,8 +350,8 @@ <h3 data-anchor-id="background">BACKGROUND:</h3>
 <h3 data-anchor-id="activities">ACTIVITIES</h3>
 <div class="cell">
 <div class="cell-output-display">
-<div class="reactable html-widget html-fill-item" id="htmlwidget-d6f6c68c266099a387ff" style="width:auto;height:auto;"></div>
-<script type="application/json" data-for="htmlwidget-d6f6c68c266099a387ff">{"x":{"tag":{"name":"Reactable","attribs":{"data":{"datin...1.":["CC-1.1","CC-1.2","CC-1.3","CC-1.4","CC-1.5"]},"columns":[{"id":".details","name":"","type":null,"sortable":false,"resizable":false,"filterable":false,"searchable":false,"width":45,"align":"center","details":[{"name":"div","attribs":{},"children":[{"name":"h3","attribs":{},"children":["Description"]},{"name":"p","attribs":{},"children":["Identify coastal habitats most vulnerable to impacts of climate change and potential buffer areas upslope of coastal habitats (see BH-8). Identify effective methods to improve the resiliency of vulnerable bay habitats to climate change stressors such as sea level rise, increasing air/water temperatures, and changes in precipitation patterns (see WQ-3 and BH-1)."]},{"name":"h3","attribs":{},"children":["Responsible Parties"]},{"name":"p","attribs":{},"children":["TBEP (lead), TBRPC, SWFWMD, USFWS, local governments"]},{"name":"h3","attribs":{},"children":["Timeframe"]},{"name":"p","attribs":{},"children":["Habitat Master Plan Update completed in 2020 (BH-1); 5-year Reasonable Assurance Plan adopted in 2022 (WQ-1); new  C-CAP mapping project initiated in 2024."]},{"name":"h3","attribs":{},"children":["Cost and funding sources"]},{"name":"p","attribs":{},"children":["$$ CWA Section 320 funds, RESTORE Act, local partners"]},{"name":"h3","attribs":{},"children":["Location"]},{"name":"p","attribs":{},"children":["Baywide"]},{"name":"h3","attribs":{},"children":["Benefit / Metric"]},{"name":"p","attribs":{},"children":["Evaluation of coastal and adjacent upland habitat quality and methods for conservation and restoration appropriate to projected sea level rise scenarios."]},{"name":"h3","attribs":{},"children":["Results"]},{"name":"p","attribs":{},"children":["Better information for management decisions on critical bay habitats."]},{"name":"h3","attribs":{},"children":["Deliverables"]},{"name":"p","attribs":{},"children":["Updated list of vulnerable areas to be prioritized for acquisition and restoration activities. Report on best practices for habitat conservation and restoration in the face of sea level rise."]}]},{"name":"div","attribs":{},"children":[{"name":"h3","attribs":{},"children":["Description"]},{"name":"p","attribs":{},"children":["Continue to implement Critical Coastal Habitat Assessment monitoring at permanent transects to track long-term changes from climate change and other stressors to coastal habitats and species (see BH-1)."]},{"name":"h3","attribs":{},"children":["Responsible Parties"]},{"name":"p","attribs":{},"children":["TBEP (lead), FWRI, local government and agency partners"]},{"name":"h3","attribs":{},"children":["Timeframe"]},{"name":"p","attribs":{},"children":["Third Critical Coastal Habitat Assessment initiated in 2023, continuing  every 3-5 years"]},{"name":"h3","attribs":{},"children":["Cost and funding sources"]},{"name":"p","attribs":{},"children":["$$$ CWA Section 320 funds, grants"]},{"name":"h3","attribs":{},"children":["Location"]},{"name":"p","attribs":{},"children":["Permanent transects throughout the bay"]},{"name":"h3","attribs":{},"children":["Benefit / Metric"]},{"name":"p","attribs":{},"children":["Evaluation of change in habitat extent and quality over time."]},{"name":"h3","attribs":{},"children":["Results"]},{"name":"p","attribs":{},"children":["Proactive management decisions for critical bay habitats that consider climate change, land use changes and effects from other factors."]},{"name":"h3","attribs":{},"children":["Deliverables"]},{"name":"p","attribs":{},"children":["Final report of initial baseline monitoring, then reports evaluating successive changes observed every five years."]}]},{"name":"div","attribs":{},"children":[{"name":"h3","attribs":{},"children":["Description"]},{"name":"p","attribs":{},"children":["Support and assist with purchase, protection and/or restoration of priority sites to serve as climate change refuges and upslope buffers for critically important habitats and species. Support adoption of land management strategies such as rolling easements, coastal construction setbacks and living shorelines (see BH-1)."]},{"name":"h3","attribs":{},"children":["Responsible Parties"]},{"name":"p","attribs":{},"children":["SWFWMD, USFWS, FDEP, other state, federal and local government land acquisition programs and land trusts; FDOT, CSX, TECO and other entities that own or manage linear properties, easements or infrastructure, as appropriate"]},{"name":"h3","attribs":{},"children":["Timeframe"]},{"name":"p","attribs":{},"children":["Ongoing. Habitat Master Plan Update completed in 2020"]},{"name":"h3","attribs":{},"children":["Cost and funding sources"]},{"name":"p","attribs":{},"children":["$$$–$$$$ federal, state, regional and local land acquisition programs, grants"]},{"name":"h3","attribs":{},"children":["Location"]},{"name":"p","attribs":{},"children":["Baywide"]},{"name":"h3","attribs":{},"children":["Benefit / Metric"]},{"name":"p","attribs":{},"children":["Restored and protected habitat used by fish and wildlife and for recreational opportunities resilient to near-term sea level rise projections."]},{"name":"h3","attribs":{},"children":["Results"]},{"name":"p","attribs":{},"children":["Increased quantity and quality of climate-resilient coastal habitats."]},{"name":"h3","attribs":{},"children":["Deliverables"]},{"name":"p","attribs":{},"children":["Annual reporting of protected and restored habitat, as required by the Government Performance and Results Act."]}]},{"name":"div","attribs":{},"children":[{"name":"h3","attribs":{},"children":["Description"]},{"name":"p","attribs":{},"children":["Continue to identify carbon sequestration benefits and economic incentives to preserve coastal habitats through voluntary carbon markets or other mechanisms. Assist land management agencies in developing site management plans that maximize carbon sequestration benefits of appropriate coastal habitats held in preservation or conservation. Support legislation to allow carbon credits on sovereign submerged and other publicly owned lands."]},{"name":"h3","attribs":{},"children":["Responsible Parties"]},{"name":"p","attribs":{},"children":["Restore America’s Estuaries, TBEP, academic institutions, SWFMWD, local governments, FDEP"]},{"name":"h3","attribs":{},"children":["Timeframe"]},{"name":"p","attribs":{},"children":["Ongoing"]},{"name":"h3","attribs":{},"children":["Cost and funding sources"]},{"name":"p","attribs":{},"children":["$$$ External grants, TBERF, EPA CRE"]},{"name":"h3","attribs":{},"children":["Location"]},{"name":"p","attribs":{},"children":["Baywide"]},{"name":"h3","attribs":{},"children":["Benefit / Metric"]},{"name":"p","attribs":{},"children":["Evaluation of blue carbon cost-benefit solutions."]},{"name":"h3","attribs":{},"children":["Results"]},{"name":"p","attribs":{},"children":["Better information for management decisions and incentives for conserving and restoring critical bay habitats."]},{"name":"h3","attribs":{},"children":["Deliverables"]},{"name":"p","attribs":{},"children":["Updated report on blue carbon storage potential for Tampa Bay habitats. Site management plans for maximizing carbon sequestration benefits of coastal habitats."]}]},{"name":"div","attribs":{},"children":[{"name":"h3","attribs":{},"children":["Description"]},{"name":"p","attribs":{},"children":["Enhance community understanding of the potential impacts of climate change on coastal habitats, and encourage actions by state and local entities and citizens to help adapt to or mitigate effects. Develop metrics to measure citizen outreach effectiveness."]},{"name":"h3","attribs":{},"children":["Responsible Parties"]},{"name":"p","attribs":{},"children":["Florida Sea Grant, local government sustainability programs, TBEP, UF/IFAS Extension, St. Petersburg College Sea Level Rise Group"]},{"name":"h3","attribs":{},"children":["Timeframe"]},{"name":"p","attribs":{},"children":["Ongoing"]},{"name":"h3","attribs":{},"children":["Cost and funding sources"]},{"name":"p","attribs":{},"children":["$$ Operating budgets of partner organizations; CWA Section 320 funds and/or Bay Mini-Grants for TBEP activities, other grants"]},{"name":"h3","attribs":{},"children":["Location"]},{"name":"p","attribs":{},"children":["Baywide"]},{"name":"h3","attribs":{},"children":["Benefit / Metric"]},{"name":"p","attribs":{},"children":["Public education and outreach programs with metrics for engagement and behavior change."]},{"name":"h3","attribs":{},"children":["Results"]},{"name":"p","attribs":{},"children":["Citizen engagement in habitat restoration volunteer projects and behavior changes to adopt recommended mitigation actions."]},{"name":"h3","attribs":{},"children":["Deliverables"]},{"name":"p","attribs":{},"children":["Educational outreach materials and program metrics."]}]}]},{"id":"datin...1.","name":"Activities","type":"character"}],"dataKey":"81e560294ae5fd00d3d705525c3a2b63"},"children":[]},"class":"reactR_markup"},"evals":[],"jsHooks":[]}</script>
+<div class="reactable html-widget html-fill-item" id="htmlwidget-8858a41dd8b22a4a0fbb" style="width:auto;height:auto;"></div>
+<script type="application/json" data-for="htmlwidget-8858a41dd8b22a4a0fbb">{"x":{"tag":{"name":"Reactable","attribs":{"data":{"datin...1.":["CC-1.1","CC-1.2","CC-1.3","CC-1.4","CC-1.5"]},"columns":[{"id":".details","name":"","type":null,"sortable":false,"resizable":false,"filterable":false,"searchable":false,"width":45,"align":"center","details":[{"name":"div","attribs":{},"children":[{"name":"h3","attribs":{},"children":["Description"]},{"name":"p","attribs":{},"children":["Identify coastal habitats most vulnerable to impacts of climate change and potential buffer areas upslope of coastal habitats (see BH-8). Identify effective methods to improve the resiliency of vulnerable bay habitats to climate change stressors such as sea level rise, increasing air/water temperatures, and changes in precipitation patterns (see WQ-3 and BH-1)."]},{"name":"h3","attribs":{},"children":["Responsible Parties"]},{"name":"p","attribs":{},"children":["TBEP (lead), TBRPC, SWFWMD, USFWS, local governments"]},{"name":"h3","attribs":{},"children":["Timeframe"]},{"name":"p","attribs":{},"children":["Habitat Master Plan Update completed in 2020 (BH-1); 5-year Reasonable Assurance Plan adopted in 2022 (WQ-1); new  C-CAP mapping project initiated in 2024."]},{"name":"h3","attribs":{},"children":["Cost and funding sources"]},{"name":"p","attribs":{},"children":["$$ CWA Section 320 funds, RESTORE Act, local partners"]},{"name":"h3","attribs":{},"children":["Location"]},{"name":"p","attribs":{},"children":["Baywide"]},{"name":"h3","attribs":{},"children":["Benefit / Metric"]},{"name":"p","attribs":{},"children":["Evaluation of coastal and adjacent upland habitat quality and methods for conservation and restoration appropriate to projected sea level rise scenarios."]},{"name":"h3","attribs":{},"children":["Results"]},{"name":"p","attribs":{},"children":["Better information for management decisions on critical bay habitats."]},{"name":"h3","attribs":{},"children":["Deliverables"]},{"name":"p","attribs":{},"children":["Updated list of vulnerable areas to be prioritized for acquisition and restoration activities. 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index 663329d..725ce45 100644
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@@ -341,8 +341,8 @@ <h3 data-anchor-id="background">BACKGROUND:</h3>
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+<script type="application/json" data-for="htmlwidget-c637bae054f5f507c16b">{"x":{"tag":{"name":"Reactable","attribs":{"data":{"Activity":["WQ-3.1","WQ-3.2","WQ-3.3"]},"columns":[{"id":".details","name":"","type":null,"sortable":false,"resizable":false,"filterable":false,"searchable":false,"width":45,"align":"center","details":[{"name":"div","attribs":{},"children":[{"name":"h3","attribs":{},"children":["Description"]},{"name":"p","attribs":{},"children":["Continue to implement the nutrient management strategy for Tampa Bay to reduce the potential for harmful algal blooms to occur or be exacerbated by nutrient inputs (see Action WQ-1)."]},{"name":"h3","attribs":{},"children":["Responsible Parties"]},{"name":"p","attribs":{},"children":["Tampa Bay Nitrogen Management Consortium, TBEP"]},{"name":"h3","attribs":{},"children":["Timeframe"]},{"name":"p","attribs":{},"children":["Ongoing"]},{"name":"h3","attribs":{},"children":["Cost and funding sources"]},{"name":"p","attribs":{},"children":["$$$ Local government and industry funds to implement nutrient reduction actions"]},{"name":"h3","attribs":{},"children":["Location"]},{"name":"p","attribs":{},"children":["Baywide"]},{"name":"h3","attribs":{},"children":["Benefit / Metric"]},{"name":"p","attribs":{},"children":["Documentation of nutrient loadings and nutrient reductions from projects conducted throughout the watershed."]},{"name":"h3","attribs":{},"children":["Results"]},{"name":"p","attribs":{},"children":["Nutrient reductions will reduce the potential, extent and duration of harmful algal blooms."]},{"name":"h3","attribs":{},"children":["Deliverables"]},{"name":"p","attribs":{},"children":["Periodic documentation of nutrient targets, loadings and attainment of water quality standards."]}]},{"name":"div","attribs":{},"children":[{"name":"h3","attribs":{},"children":["Description"]},{"name":"p","attribs":{},"children":["Support additional research on harmful algal bloom species found within the region that are or may emerge as a significant issue in the future (e.g., Pyrodinium bahamense, Pseudo-nitzschia spp., brown tide species such as Aureoumbra lagunensis). 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Old Tampa Bay shallow seagrass bed temperature monitoring initiated in 2023, to be completed in 2027."]},{"name":"h3","attribs":{},"children":["Cost and funding sources"]},{"name":"p","attribs":{},"children":["$$  Programmatic funds; grants"]},{"name":"h3","attribs":{},"children":["Location"]},{"name":"p","attribs":{},"children":["Baywide, especially Old Tampa Bay"]},{"name":"h3","attribs":{},"children":["Benefit / Metric"]},{"name":"p","attribs":{},"children":["Models of phytoplankton life history and trophic dynamics to help predict, prevent and abate harmful algal blooms."]},{"name":"h3","attribs":{},"children":["Results"]},{"name":"p","attribs":{},"children":["Better understanding of what causes HABs will result in better management strategies to avoid them."]},{"name":"h3","attribs":{},"children":["Deliverables"]},{"name":"p","attribs":{},"children":["Research reports documenting relevant trophic and life history dynamics of nuisance algal bloom species relevant to conditions in Tampa Bay."]}]},{"name":"div","attribs":{},"children":[{"name":"h3","attribs":{},"children":["Description"]},{"name":"p","attribs":{},"children":["Continue education about causes and effects of harmful algal blooms in bay waters, focusing on coordinated and timely communications to the public about potential health risks and environmental effects of HABs. Support general boater education and port vessel operations that reduce the potential to import HAB species through ballast or bilge water. 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@@ -532,8 +532,8 @@ <h4 data-anchor-id="land-acquisition-and-protection">Land Acquisition and Protec
 <h3 data-anchor-id="activities">ACTIVITIES</h3>
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 <div class="cell-output-display">
-<div class="reactable html-widget html-fill-item" id="htmlwidget-14c0bf41f3208c611b4c" style="width:auto;height:auto;"></div>
-<script type="application/json" data-for="htmlwidget-14c0bf41f3208c611b4c">{"x":{"tag":{"name":"Reactable","attribs":{"data":{"Activity":["BH-1.1","BH-1.2","BH-1.3","BH-1.4","BH-1.5","BH-1.6"]},"columns":[{"id":".details","name":"","type":null,"sortable":false,"resizable":false,"filterable":false,"searchable":false,"width":45,"align":"center","details":[{"name":"div","attribs":{},"children":[{"name":"h3","attribs":{},"children":["Description"]},{"name":"p","attribs":{},"children":["Update the 2010 Habitat Master Plan to assess progress toward established habitat targets and to set targets for remaining priority coastal habitats as data becomes available. 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Maintenance of database of habitat restoration and protection projects in the Tampa Bay watershed. Updated priority acquisition list for bay and watershed."]}]},{"name":"div","attribs":{},"children":[{"name":"h3","attribs":{},"children":["Description"]},{"name":"p","attribs":{},"children":["[Formerly BH-10.3] Increase participation and involvement from wetland mitigation bankers in achieving freshwater wetland goals. Provide technical GIS tools to identify appropriate locations and types of freshwater wetland creation and mitigation. Highlight economic incentives of performing non-forested wetland mitigation when ecologically beneficial."]},{"name":"h3","attribs":{},"children":["Responsible Parties"]},{"name":"p","attribs":{},"children":["Wetland regulatory agencies such as FDEP, SWFWMD, USACE, EPCHC, TBEP Habitat Restoration Consortium,  and private sector mitigation bankers. GIS tools are available from TBEP. Partners to distribute include wetland regulatory agencies, TBRPC, local governments."]},{"name":"h3","attribs":{},"children":["Timeframe"]},{"name":"p","attribs":{},"children":["Ongoing. Habitat Master Plan GIS data for freshwater wetlands provided to all permitting agencies. Flood protection ecosystem services were valued in the 2023 Economic Valuation Study."]},{"name":"h3","attribs":{},"children":["Cost and funding sources"]},{"name":"p","attribs":{},"children":["$–$$ CWA Section 320 for Habitat Master Plan Update; $ for staff time for regulatory agencies"]},{"name":"h3","attribs":{},"children":["Location"]},{"name":"p","attribs":{},"children":["Appropriate freshwater wetland locations throughout the Tampa Bay watershed"]},{"name":"h3","attribs":{},"children":["Benefit / Metric"]},{"name":"p","attribs":{},"children":["Increase percentage of mitigation for non-forested freshwater wetlands within the Tampa Bay watershed."]},{"name":"h3","attribs":{},"children":["Results"]},{"name":"p","attribs":{},"children":["Wetland bankers can help achieve baywide and basin-specific targets, where appropriate and beneficial."]},{"name":"h3","attribs":{},"children":["Deliverables"]},{"name":"p","attribs":{},"children":["Chapter in the Tampa Bay Habitat Master Plan Update on freshwater wetlands."]}]},{"name":"div","attribs":{},"children":[{"name":"h3","attribs":{},"children":["Description"]},{"name":"p","attribs":{},"children":["[Formerly BH-10.4] Examine success of freshwater wetland mitigation at various time scales and recommend improvements to mitigation practices (see Action BH-2)."]},{"name":"h3","attribs":{},"children":["Responsible Parties"]},{"name":"p","attribs":{},"children":["EPCHC (lead), SWFWMD, USF and other wetland permitting agencies (USACE, FDEP)"]},{"name":"h3","attribs":{},"children":["Timeframe"]},{"name":"p","attribs":{},"children":["A long term study was completed in 2017."]},{"name":"h3","attribs":{},"children":["Cost and funding sources"]},{"name":"p","attribs":{},"children":["$$–$$$ EPA Wetland Development Grant, EPCHC staff time"]},{"name":"h3","attribs":{},"children":["Location"]},{"name":"p","attribs":{},"children":["Hillsborough County"]},{"name":"h3","attribs":{},"children":["Benefit / Metric"]},{"name":"p","attribs":{},"children":["Assessment of success and failure rates of freshwater mitigation projects."]},{"name":"h3","attribs":{},"children":["Results"]},{"name":"p","attribs":{},"children":["Recommended improvements in mitigation practices will result in more successful long-term ecological benefits of freshwater wetland mitigation."]},{"name":"h3","attribs":{},"children":["Deliverables"]},{"name":"p","attribs":{},"children":["Final Report, including recommendations."]}]},{"name":"div","attribs":{},"children":[{"name":"h3","attribs":{},"children":["Description"]},{"name":"p","attribs":{},"children":["[Formerly BH-10.5] Incorporate creation of freshwater wetlands as an option for stormwater treatment. Encourage other local governments to adopt a BMP guide similar to the Pinellas County Stormwater Manual, to expand opportunities for wetland protection and creation in urbanized areas."]},{"name":"h3","attribs":{},"children":["Responsible Parties"]},{"name":"p","attribs":{},"children":["Local governments"]},{"name":"h3","attribs":{},"children":["Timeframe"]},{"name":"p","attribs":{},"children":["No timeline established"]},{"name":"h3","attribs":{},"children":["Cost and funding sources"]},{"name":"p","attribs":{},"children":["$–$$ Grants, local government stormwater funds"]},{"name":"h3","attribs":{},"children":["Location"]},{"name":"p","attribs":{},"children":["Baywide"]},{"name":"h3","attribs":{},"children":["Benefit / Metric"]},{"name":"p","attribs":{},"children":["Stormwater manuals incorporating freshwater wetlands as an option for stormwater treatment."]},{"name":"h3","attribs":{},"children":["Results"]},{"name":"p","attribs":{},"children":["Enhanced restoration and creation of freshwater wetland systems in urban areas where natural wetlands are lacking."]},{"name":"h3","attribs":{},"children":["Deliverables"]},{"name":"p","attribs":{},"children":["BMP guides to expand opportunities for wetland protection and creation in urbanized areas."]}]}]},{"id":"Activity","name":"Activities","type":"character"}],"dataKey":"7854e6abcbb717636bce61e9424ed392"},"children":[]},"class":"reactR_markup"},"evals":[],"jsHooks":[]}</script>
+<div class="reactable html-widget html-fill-item" id="htmlwidget-c117ff0b0d8103ee310d" style="width:auto;height:auto;"></div>
+<script type="application/json" data-for="htmlwidget-c117ff0b0d8103ee310d">{"x":{"tag":{"name":"Reactable","attribs":{"data":{"Activity":["BH-1.1","BH-1.2","BH-1.3","BH-1.4","BH-1.5","BH-1.6"]},"columns":[{"id":".details","name":"","type":null,"sortable":false,"resizable":false,"filterable":false,"searchable":false,"width":45,"align":"center","details":[{"name":"div","attribs":{},"children":[{"name":"h3","attribs":{},"children":["Description"]},{"name":"p","attribs":{},"children":["Update the 2010 Habitat Master Plan to assess progress toward established habitat targets and to set targets for remaining priority coastal habitats as data becomes available. 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