EMPAFunctionAnalysis

R package for the Estuary MPA (EMPA) Level 3 Dashboard data analysis.

How to Run

1. Clone this repo

git clone https://github.com/your-org/empa-l3-data-analysis.git
cd empa-l3-data-analysis

2. Load the package

devtools::load_all(".")

3. Load EMPA data

vegetativecover_data <- read.csv(
  "https://nexus.sccwrp.org/empachecker/export?tablename=tbl_vegetativecover_data"
)
vegetation_sample_metadata <- read.csv(
  "https://nexus.sccwrp.org/empachecker/export?tablename=tbl_vegetation_sample_metadata"
)

4. Load external datasets

cram <- read.csv("inst/extdata/empa_cram.csv")
gis_data <- read.csv("inst/extdata/BufferLandCover_251203.csv")
wetland_extents <- read.csv("inst/extdata/HabitatZones_260224.csv")
ruggedness <- read.csv("inst/extdata/Ruggedness_250702.csv")

5. Run all metrics

all_scores <- score_all_metrics(
  vegetation_sample_metadata = vegetation_sample_metadata,
  vegetativecover_data = vegetativecover_data,
  cram = cram,
  gis_data = gis_data,
  wetland = wetland_extents,
  rugged = ruggedness,
  year = c(2023, 2024, 2025)
)

6. Run individual metrics

Example for CRAM index:

cram_scores <- score_cram_index(
  cram = cram,
  vegetativecover_data = vegetativecover_data
)

Example for native cover:

native_scores <- score_native_cover(
  vegetativecover_data = vegetativecover_data,
  year = c(2023)
)

Metrics

All metric functions return a data frame with columns: estuaryname, siteid, year, function_name, indicator_name, metric_name, metric_score

Static metrics (GIS/wetland inputs) do not include a year column, except score_ruggedness() which does.

function_name	indicator_name	metric_name	R_function_name
Plant	alliances	plant_alliances	`metric-plant-alliances.R` `score_plant_alliances()`
Plant	elevation	ruggedness	`metric-ruggedness.R` `score_ruggedness()`
Plant	habitat	cram_index	`metric-cram-index.R` `score_cram_index()`
Plant	inundation	marsh_plain_inundation	`metric-marsh-plain-inundation.R` `score_marsh_plain_inundation()`
Plant	vegetation	invasive_severity	`metric-invasive-severity.R` `score_invasive_severity()`
Plant	vegetation	native_cover	`metric-native-cover.R` `score_native_cover()`
Plant	vegetation	veg_cover	`metric-veg-cover.R` `score_veg_cover()`
SLR	accretion	sediment_supply	`metric-sediment-supply.R` `score_sediment_supply()`
SLR	habitat	cram_index	`metric-cram-index.R` `score_cram_index()`
SLR	resiliency	buffer_cover	`metric-buffer-cover.R` `score_buffer_cover()`
SLR	resiliency	current_habitat_distribution	`metric-current-habitat-distribution.R` `score_current_habitat_distribution()`
SLR	resiliency	future_habitat_distribution	`metric-future-habitat-distribution.R` `score_future_habitat_distribution()`
SLR	resiliency	perimeter_contiguity	`metric-perimeter_contiguity.R` `score_perimeter_contiguity()`
SLR	resiliency	perimeter_land_cover	`metric-perimeter-land-cover.R` `score_perimeter_land_cover()`
SLR	vegetation	veg_cover	`metric-veg-cover.R` `score_veg_cover()`

Plant

habitat

cram_index

Function: score_cram_index()

Calculation: Filters vegetation data by year (from samplecollectiondate) or do all years. Filters CRAM data by year (from Year_assessment), groups by Site, and averages the index column to produce one site-level score per year. Left-joins averaged CRAM scores onto the vegetation site list. Sites with no CRAM data receive NA. Normalizes using ((empa_index - cram_min) / cram_range) * 100, rounded to 1 decimal place.

Inputs:

cram: CRAM data frame columns Site, Year_assessment, index
vegetativecover_data: Raw vegetation cover data frame columns estuaryname, siteid, samplecollectiondate

Outputs: One row per site per year. metric_score is NA for sites with no CRAM assessment in the selected year.

elevation

ruggedness

Function: score_ruggedness()

Calculation: Passes the pre-computed surface ruggedness index directly through with no transformation. Higher values indicate greater topographic complexity.

Inputs:

rugged: Ruggedness data frame columns estuaryname, siteid, Year, ruggedness

Outputs: One row per site per year.

inundation

marsh_plain_inundation

Function: score_marsh_plain_inundation()

Calculation: Details to be added.

Inputs:

vegetativecover_data: Raw vegetation cover data frame columns estuaryname, siteid, samplecollectiondate

Outputs: One row per site per year. Currently returns NA for all sites.

vegetation

invasive_severity

Function: score_invasive_severity()

Calculation: Extracts year from samplecollectiondate and filters to the requested year(s). Gets distinct invasive species per site and year using the Cal-IPC rating column. Starts at 100 and subtracts penalty points for each unique invasive species: Limited = 5 pts, Moderate = 10 pts, High = 15 pts. Score is floored at 0. Sites with no invasive species score 100.

Inputs:

vegetativecover_data: Raw vegetation cover data frame columns estuaryname, siteid, samplecollectiondate, scientificname, rating

Outputs: One row per site per year.

native_cover

Function: score_native_cover()

Calculation: Extracts year from samplecollectiondate and filters to the requested year(s). Removes records with excluded statuses ("Not recorded", "naturalized"), missing data sentinel (-88), and unknown species (scientificname starting with "unknown"). Sums estimatedcover by site, year, and status, then calculates native species as a percentage of total cover across all statuses. metric_score = percent native.

Inputs:

vegetativecover_data: Raw vegetation cover data frame columns estuaryname, siteid, samplecollectiondate, status, scientificname, estimatedcover

Outputs: One row per site per year.

veg_cover

Function: score_veg_cover()

Calculation: Extracts year from samplecollectiondate and filters to the requested year(s). Removes missing data sentinel (-88). Sums vegetated_cover and non_vegetated_cover across all plots per site and year, then calculates vegetated cover as a percentage of total. metric_score = percent vegetated.

Inputs:

vegetation_sample_metadata: Raw vegetation sample metadata data frame columns estuaryname, siteid, samplecollectiondate, vegetated_cover, non_vegetated_cover

Outputs: One row per site per year.

alliances

plant_alliances

Function: score_plant_alliances()

Calculation: Details to be added.

Inputs:

vegetativecover_data: Raw vegetation cover data frame columns estuaryname, siteid, samplecollectiondate

Outputs: One row per site per year. Currently returns NA for all sites.

SLR

habitat

cram_index

Same function and calculation as Plant > habitat > cram_index. Pass function_name = "SLR".

accretion

sediment_supply

Function: score_sediment_supply()

Calculation: Details to be added.

Inputs:

cram: CRAM data frame used only to obtain the site list

Outputs: One row per site. Static (no year variation). Currently returns NA for all sites.

resiliency

buffer_cover

Function: score_buffer_cover(buffer_size = "500 m", metric_name = "buffer_cover")

Calculation: Filters GIS buffer data to the 500 m buffer. Groups landcover into "natural" (Ag + Natural) vs "Developed". Sums the percent column for natural classes per site. metric_score = percent natural landcover within the 500 m buffer.

Inputs:

gis_data: GIS buffer land cover data frame columns estuaryname, siteid, buffer, landcover, percent