change catalog urls to match ecodata names

adjusted make rmd function to set the url of each catalog page to its ecodata data name. built catalog with new urls. added catalog page for rec hms.

R/make_rmd.R

@@ -21,8 +21,8 @@ make_rmd <- function(listobject){
   # start to create the Rmd
   #cat(paste0("# ",stringr::str_to_title(indicator_name)),append=T,fill=T,file=con)  
   ### DESCRIPTION, CONTRIBUTORS, AFFILIATION, FAMILY
-#  cat(paste0("# ",listobject$dataname," {#",listobject$indicatorname,"}"),append=T,fill=T,file=con)    
-  cat(paste0("# ",listobject$dataname),append=T,fill=T,file=con)    
+  cat(paste0("# ",listobject$dataname," {#",listobject$indicatorname,"}"),append=T,fill=T,file=con)    
+  #cat(paste0("# ",listobject$dataname),append=T,fill=T,file=con)    
   cat("",append=T,fill=T,file=con) # add space
   cat(paste0("**Description**: ",listobject$description),append=T,fill=T,file=con)
   cat("",append=T,fill=T,file=con) # add space

chapters/HMS_species_distribution.rmd

@@ -1,6 +1,6 @@
-# Cetacean Distribution Shifts
+# Cetacean Distribution Shifts {#HMS_species_distribution}
 
-**Description**: The data presented here are the locations of the center of core habitat for cetacean by season as documented in 2010 versus 2017.
+**Description**: The data presented here are the locations of the center of core habitat for cetaceans by season as documented in 2010 versus 2017.
 
 **Indicator family**: 
 
@@ -16,7 +16,7 @@ knitr::opts_chunk$set(echo = F)
 library(ecodata)
 ```
 ## Introduction to Indicator
-Marine species are being affected by global climate changes, where and in most cases the documented responses include distribution shifts from their historical habitat. In addition, human-caused drivers such as the noise and physical disturbances from oil and gas exploration, fishing, boat traffic and infrastructure such as offshore renewable energy developments, as well as other maritime activities could also result in shifts. [@chavez-rosales_detection_2022] used Northwest Atlantic cetacean location data collected in its changing environment to investigate if their habitats are changing, and if so, to what extent.
+Marine species are being affected by global climate changes, and in most cases the documented responses include distribution shifts from their historical habitat. In addition, human-caused drivers such as the noise and physical disturbances from oil and gas exploration, fishing, boat traffic and infrastructure such as offshore renewable energy developments, as well as other maritime activities could also result in shifts. [@chavez-rosales_detection_2022] used Northwest Atlantic cetacean location data collected in its changing environment to investigate if their habitats are changing, and if so, to what extent.
 
 A climate vulnerability assessment is published for Atlantic and Gulf of Mexico marine mammal populations [@lettrich_vulnerability_2023].
 
@@ -57,8 +57,8 @@ Shifting species distributions alter both species interactions and fishery inter
 
 **Variable definitions**
 
-1) Time=time period of centroid location.  2) species=cetacean species.  3) season.  4) wlat=latitude of centroid.  
-5) wlon=longitude of centroid.
+1) Time=time period of centroid location.  2) species=cetacean species.  3) season.  
+4) wlat=latitude of centroid.  5) wlon=longitude of centroid.
 
 ```{r vars_HMS_species_distribution}
 # Pull all var names

chapters/SAV.rmd

@@ -1,4 +1,4 @@
-# Submerged Aquatic Vegetation
+# Submerged Aquatic Vegetation {#SAV}
 
 **Description**: The data provided here are the 1984-2022 area distribution and percent coverage of submerged aquatic vegetation in the Chesapeake Bay and its tributaries that area measured and calculated from photo-interpreted aerial imagery taken during surveys conducted in the growing season.
 

chapters/abc_acl.rmd

@@ -1,4 +1,4 @@
-# ABC or ACL for Managed Stocks
+# ABC or ACL for Managed Stocks {#abc_acl}
 
 **Description**: Mid-Atlantic Council catch limits (e.g., ABC or ACL) and associated total catch estimate by year for each species and sector (commercial or recreational, as appropriate).
 

chapters/aggregate_biomass.rmd

@@ -1,4 +1,4 @@
-# Aggregate Survey Biomass
+# Aggregate Survey Biomass {#aggregate_biomass}
 
 **Description**: Aggregate biomass from Northeast Fisheries Science Center (NEFSC) bottom trawl survey.
 

chapters/aquaculture.rmd

@@ -1,4 +1,4 @@
-# Aquaculture Production
+# Aquaculture Production {#aquaculture}
 
 **Description**: Oyster production: number of oysters harvested from aquaculture.
 

chapters/bennet.rmd

@@ -1,4 +1,4 @@
-# Bennet Indicator
+# Bennet Indicator {#bennet}
 
 **Description**: The data presented here are changes in revenue ($ real) split into a price indicator and a volume indicator. The sum of the price and the volume indicator is equal to the revenue change relative to a base year, which is 1982.
 

chapters/bottom_temp.rmd

@@ -1,4 +1,4 @@
-# Bottom Temperature - in situ
+# Bottom Temperature - in situ {#bottom_temp}
 
 **Description**: The data presented here are time series of regional average bottom temperature anomalies from ship-based measurements made on the Northeast Continental Shelf.
 
@@ -45,7 +45,7 @@ Temporal scale: Annual
 
 **Synthesis Theme**:
 
-
+- [X] Multiple System Drivers
 
 
 ```{r autostats_bottom_temp}

chapters/bottom_temp_comp.rmd

@@ -1,4 +1,4 @@
-# Bottom temperature - Seasonal Anomaly
+# Bottom temperature - Seasonal Anomaly {#bottom_temp_comp}
 
 **Description**: The data are seasonal bottom temperature anomaly time series for each EPU
 
@@ -7,7 +7,7 @@
 - [X] Oceanographic
 
 
-**Contributor(s)**: Joseph Caracappa, Hubert duPontavice, Vincent Saba, Zhuomin Chen
+**Contributor(s)**: Joseph Caracappa, Hubert du Pontavice, Vincent Saba, Zhuomin Chen
 
 **Affiliations**: NEFSC
 

chapters/bottom_temp_seasonal_gridded.rmd

@@ -1,4 +1,4 @@
-# Bottom temperature - Seasonal Gridded
+# Bottom temperature - Seasonal Gridded {#bottom_temp_seasonal_gridded}
 
 **Description**: Seasonal mean bottom temperatures on the Northeast Continental Shelf between 1959 and 2023 in a 1/12° grid.
 

chapters/calanus_variation.rmd

@@ -1,4 +1,4 @@
-# Seasonal Variation of Calanus finmarchicus
+# Seasonal Variation of Calanus finmarchicus {#calanus_variation}
 
 **Description**: Abundance of late copepodid stages of the planktonic copepod, Calanus finmarchicus, measured during seasonal surveys between 1977 and 2019. Data from NOAA EcoMon/MARMAP program
 
@@ -26,8 +26,6 @@ Historically, the high abundance of C. finmarchicus in the GOM combined with the
 This phenology indicator shows the change in abundance of the planktonic copepod, Calanus finmarchicus over a mean annual cycle in Wilkinson Basin, the primary overwintering habitat of this species in the western Gulf of Maine. The data are provided by the NOAA EcoMon/MARMAP survey, which has sampled stations along the Northeast U.S. Shelf, including the Gulf of Maine, seasonally (2-6 times per year) in nearly all years since 1977. The 333 µm mesh plankton nets used by the survey quantitatively capture only the late copepodid stages (C3-adult) of C. finmarchicus, but these stages nevertheless are representative of the seasonal variation in abundance of the population. This indicator serves as a baseline that can be used to interpret future changes in wGoM C. finmarchicus abundance.
 
 ## Key Results and Visualizations
-Calanus finmarchicus phenology figure (uploaded with data) here
-
 Seasonal abundance (number m-3) of C. finmarchicus late copepodid stages (mostly stages CIII-CVI) in Wilkinson Basin. X-axis represents time of year, from 1 January (yearday 0) to 31 December (yearday 365). Background gray circles show individual MARMAP/EcoMon abundance data points in Wilkinson Basin between 1977-2019. Solid black line shows the seasonal pattern in mean abundance from the MARMAP/EcoMon data; dotted lines show 2x (top) and ½ (bottom) of the mean abundance. Colored horizontal lines show conceptual model of seasonally variable predominant drivers. Predominant drivers in winter (Jan-Mar: days 1-100) suggested to be a combination of predation mortality and advective loss.
 
 The abundance of late stage Calanus finmarchicus in the western Gulf of Maine is seasonally variable. The highest abundances are observed in May-June, the result of reproduction, the magnitude of which depends on the timing of food availability to females (Stage CVI) in late-winter through spring. By late summer, most of the C. finmarchicus population is present as Stage CV, which overwinters at depth in a dormant state. The number of stage CV and hence the overall population abundance dwindles depending on net losses from advection and vertebrate and invertebrate predators. The abundance reaches its nadir in February-March, when the population is in stage CV or newly molted adult females and males. Note the difference between the late winter and late spring mean abundances is about three orders of magnitude.

chapters/ch_bay_sal.rmd

@@ -1,4 +1,4 @@
-# Chesapeake Bay Salinity
+# Chesapeake Bay Salinity {#ch_bay_sal}
 
 **Description**: This data is collected from the CBIBS buoy system.
 
@@ -49,7 +49,7 @@ The changes in the temperature and salinity have implications in the habitat
 
 ## Get the data
 
-**Point of contact**: [Charles Pellerin ([email protected]](mailto:Charles Pellerin ([email protected]){.email}
+**Point of contact**: [Charles Pellerin ([email protected])](mailto:Charles Pellerin ([email protected])){.email}
 
 **ecodata name**: `ecodata::ch_bay_sal`
 

chapters/ch_bay_temp.rmd

@@ -1,4 +1,4 @@
-# Chesapeake Bay Temperature
+# Chesapeake Bay Temperature {#ch_bay_temp}
 
 **Description**: This data is collected from the CBIBS buoy system.
 

chapters/ches_bay_sst.rmd

@@ -1,4 +1,4 @@
-# Chesapeake Bay Seasonal Sea Surface Temperature Anomaly
+# Chesapeake Bay Seasonal Sea Surface Temperature Anomaly {#ches_bay_sst}
 
 **Description**: Chesapeake Bay Seasonal Sea Surface Temperature Anomaly
 
@@ -61,7 +61,8 @@ In the fall season, there were warmer-than-average temperatures in the Western S
 
 **Variable definitions**
 
-1) sst: sea surface temperature 2023, Celsius 2) sst_climatol: sea surface temperature climatology 2007-2022, Celsius 
+1) sst: sea surface temperature 2023, Celsius 
+2) sst_climatol: sea surface temperature climatology 2007-2022, Celsius 
 3) sst_anomaly: sea surface temperature anomaly 2023 minus 2007-2022, Celsius
 
 ```{r vars_ches_bay_sst}

chapters/ches_bay_synthesis.rmd

@@ -1,4 +1,4 @@
-# Chesapeake Bay 2023 Synthesis
+# Chesapeake Bay 2023 Synthesis {#ches_bay_synthesis}
 
 **Description**: Synthesis of Chesapeake Bay 2023 habitat conditions with implications for managed species
 

chapters/ches_bay_wq.rmd

@@ -1,4 +1,4 @@
-# Chesapeake Bay Water Quality Standards Attainment
+# Chesapeake Bay Water Quality Standards Attainment {#ches_bay_wq}
 
 **Description**: Chesapeake Bay Water Quality Attainment Indicator
 
@@ -61,8 +61,8 @@ Patterns of attainment of individual designated uses are variable (Figure 2). Ac
 
 **Variable definitions**
 
-Period: Assessment period Year 1: Starting year of the assessment period Year 2: Ending year of the assessment period 
-Total: The overall attainment indicator 
+Period: Assessment period Year 1: Starting year of the assessment period 
+Year 2: Ending year of the assessment period Total: The overall attainment indicator 
 MSN-DO: Estimated attainment of the dissolved oxygen criterion for the migratory spawning and nursery designated use 
 OW-DO: Estimated attainment of the dissolved oxygen criterion for the open water designated use 
 DW-DO: Estimated attainment of the dissolved oxygen criterion for the deep water designated use 

chapters/chl_pp.rmd

@@ -1,8 +1,6 @@
-# Chlorophyll and Primary Production
+# Chlorophyll and Primary Production {#chl_pp}
 
-**Description**: Satellite derived phytoplankton data including chlorophyll concentration, phytoplankton size class, and primary production for the Northeast Continental Shelf and ecological production units.
-
-(To be expanded)
+**Description**: Satellite derived phytoplankton data including chlorophyll concentration, phytoplankton size class, and primary production for the Northeast Continental Shelf and ecological production units.
 
 **Indicator family**: 
 
@@ -18,12 +16,18 @@ knitr::opts_chunk$set(echo = F)
 library(ecodata)
 ```
 ## Introduction to Indicator
-Phytoplankton are the foundation of the marine food web and are the primary food source for zooplankton and filter feeders such as shellfish. Numerous environmental and oceanographic factors interact to drive the abundance, composition, spatial distribution, and productivity of phytoplankton. Satellite derived measurements of chlorophyll, the dominant photosynthetic pigment in phytoplankton, are used to estimate phytoplankton biomass. Phytoplankton growth depends on the availability of carbon dioxide, sunlight and nutrients and their growth rates can be influenced by water temperature, water depth, wind, and grazing pressure.  Primary productivity is a measure of the amount of carbon produced by phytoplankton. The seasonal cycle of phytoplankton size distribution are typically dominated by larger-celled microplankton during the winter-spring and fall bloom periods, while smaller-celled nanoplankton dominate during the warmer summer months.
+Phytoplankton are key biological regulators of the structure and function of most marine ecosystems. They are the foundation of the marine food web and are the primary food source for zooplankton and filter feeders such as shellfish. Numerous environmental and oceanographic factors interact to drive the abundance, composition, spatial distribution, seasonal timing and productivity of phytoplankton. Satellite derived measurements of chlorophyll, the dominant photosynthetic pigment in phytoplankton, are used to estimate total phytoplankton biomass. The size structure of the phytoplankton community influences important biogeochemical and ecological processes, including transfer of energy through the marine food web. Phytoplankton growth depends on the availability of carbon dioxide, sunlight and nutrients and their growth rates can be influenced by water temperature, water depth, wind, and grazing pressure.  Primary productivity is a measure of the amount of carbon produced by phytoplankton. 
 
-(To be expanded)
+The unique physical characteristics of the Northeast U.S. continental shelf help make it among the most productive continental shelf systems in the world influenced by both bottom-up (e.g. nutrient concentrations, light availability, and mixing/stratification) and top-down (e.g. grazing) controls. Phytoplankton biomass, composition, and productivity all have high spatial, seasonal and interannual variability. The most pronounced spatial pattern is the decrease in phytoplankton biomass from the coast to the shelf break. Georges Bank and Nantucket Shoals are shallow regions that are well mixed by tides. This mixing supplies sufficient nutrients to support phytoplankton growth throughout the year. In other regions, blooms of large diatom species occur on a seasonal cycle when growing conditions are ideal.
 
 ## Key Results and Visualizations
-(In development)
+The seasonal cycles of phytoplankton size distribution are typically dominated by larger-celled microplankton during the winter-spring and fall bloom periods, while smaller-celled nanoplankton dominate during the warmer summer months. In 2023, MAB total chlorophyll was below average in early spring, near average through the summer and above average throughout the fall. A peak in primary production occurred in summer, followed by an above average productivity associated with the early fall bloom. Phytoplankton size class distributions were near average for most of the year, except during the early fall bloom.
+
+Total chlorophyll concentrations on Georges Bank were above average for most of the year. The early winter bloom was most likely associated with diatoms, however the above average chlorophyll, primary production and microplankton fraction from April through August can be attributed to the dinoflagellate _Tripos muelleri_. 
+
+Total chlorophyll concentrations in the Gulf of Maine were above average for most of the year. The early winter bloom was most likely associated with diatoms, however the record high chlorophyll, primary production and microplankton fraction from April through August can be attributed to the dinoflagellate _Tripos muelleri_. 
+
+There is high interannual variability of the seasonal phytoplankton cycle.  At the monthly scale, MAB chlorophyll and primary production are increasing during January and there has been a decrease in September chlorophyll, likely due to extension of the [summer stratification](https://noaa-edab.github.io/catalog/transition-dates.html) and delayed fall turnover. Fall and winter chlorophyll and primary production are increasing on Georges Bank and Gulf of Maine.
 
 ### MidAtlantic
 
@@ -117,7 +121,7 @@ Temporal scale: Daily, weekly, monthly, annual, climatology (1998 to current yea
 ```
 
 ## Implications
-(In development)
+Phytoplankton abundance, productivity, diversity, cell size, phenology, and carbon fluxes are regulated by the local physical and chemical environment and grazing. Interannual and climatological changes in temperature, freshwater inputs (due to ice sheet melting and/or enhanced river discharge), wind direction, and wind speed can alter the circulation patterns, upwelling conditions, and nutrient fluxes, directly affecting the timing, location, species composition of phytoplankton blooms in the NES. As the NES responds to warming, changing phenologies, changing chemistry, and changes in circulation patterns, we must understand how varying biophysical interactions control phytoplankton and subsequently affect fisheries, their habitats and the people, businesses and communities that depend on them.
 
 ## Get the data
 

chapters/cold_pool.rmd

@@ -1,4 +1,4 @@
-# Cold Pool Index
+# Cold Pool Index {#cold_pool}
 
 **Description**: Three annual cold pool indices (and standard error) for ss1959 through 2023
 

chapters/comdat.rmd

@@ -1,4 +1,4 @@
-# Commercial Landings and Revenue
+# Commercial Landings and Revenue {#comdat}
 
 **Description**: Commercial landings and revenue from dealer reports
 

chapters/commercial_div.rmd

@@ -1,4 +1,4 @@
-# Commercial Catch and Fleet Diversity
+# Commercial Catch and Fleet Diversity {#commercial_div}
 
 **Description**: Permit-level species diversity and Council-level fleet diversity.
 

chapters/condition.rmd

@@ -1,4 +1,4 @@
-# Relative condition
+# Relative condition {#condition}
 
 **Description**: NEFSC fall bottom trawl survey relative condition
 

chapters/energy_density.rmd

@@ -1,6 +1,6 @@
-# Forage Fish Energy Density
+# Forage Fish Energy Density {#energy_density}
 
-**Description**: Energy density of alewife, butterfish, sand lance, and Atlantic mackerel varies seasonally, with seasonal estimates both higher and lower than estimates from previous decades. The data presented are the seasonal (Spring and Fall) energy density (kJ/g) for eight important forage species; Alewife, Atlantic Herring, Silver Hake, Northern Sand Lance, Atlantic Mackerel, Butterfish, Northern Shortfin Squid, and Inshore Longfin Squid. Samples are obtained from the NEFSC seasonal bottom trawl surveys and processed int he lab to estimate energy content.
+**Description**: Energy density of alewife, butterfish, sand lance, and Atlantic mackerel varies seasonally, with seasonal estimates both higher and lower than estimates from previous decades. The data presented are the seasonal (Spring and Fall) energy density (kJ/g) for eight important forage species; Alewife, Atlantic Herring, Silver Hake, Northern Sand Lance, Atlantic Mackerel, Butterfish, Northern Shortfin Squid, and Inshore Longfin Squid. Samples are obtained from the NEFSC seasonal bottom trawl surveys and processed in the lab to estimate energy content.
 
 **Indicator family**: 
 
@@ -77,7 +77,7 @@ Source data are NOT publicly available.
 
 ## Accessibility and Constraints
 
-Email [email protected] for further information. Data tables are beign created to make this readily available soon.
+Email [email protected] for further information. Data tables are being created to make this readily available soon.
 
 **tech-doc link**
 <https://noaa-edab.github.io/tech-doc/energy_density.html>