Habitat Connectivity

Habitat connectivity data layers. Currently CDFW BIOS + Schloss/Cameron data.

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Visibility: Public
Owner: Carl Boettiger
Created: 25 Jul 2026
Last Updated: 25 Jul 2026

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Contents

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Analytics

Habitat Connectivity

Habitat connectivity data layers. Currently CDFW BIOS + Schloss/Cameron data.

Contents

root

Details

Visibility: Public
Owner: Carl Boettiger
Created: 25 Jul 2026
Last Updated: 25 Jul 2026

Analytics

28 days

Downloads

494

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4.5 GB

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28-day downloads

17 Jul 2026

13 Aug 2026

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README

public-connectivity

Landscape connectivity & climate-resilience datasets for California, from the California Biodiversity Network (CBN) and partners. All products are cloud-native and served from NRP S3 (https://s3-west.nrp-nautilus.io/public-connectivity/).

Dataset	Source	Products	License
`regional-connectivity-linkages`	Beier et al. 2006 — South Coast Missing Linkages (CDFW BIOS ds419)	GeoParquet, PMTiles, H3 hex (res 8)	CC-BY-4.0
`wildlife-movement-barriers`	CDFW 2024 — Terrestrial Wildlife Connectivity Barriers (BIOS ds2867)	GeoParquet, PMTiles, H3 hex (res 8)	CC-BY-4.0
`climate-migration-routes`	Schloss et al. 2022 (Dryad `d7wm37q1m`)	COG, H3 hex (res 9)	CC0-1.0
`present-day-connectivity/flow`	Cameron et al. 2022 (Dryad `7sqv9s4v3`)	COG, H3 hex (res 9)	CC0-1.0
`present-day-connectivity/categories`	Cameron et al. 2022 (Dryad `7sqv9s4v3`)	COG, H3 hex (res 9)	CC0-1.0

All layers are in OGC:CRS84 / EPSG:4326. The three raster sources were reprojected from their native ESRI:102003 (USA Contiguous Albers) / sphere Web-Mercator projections to EPSG:4326 (categorical layers with nearest-neighbor; the continuous flow index with bilinear).

Vector — regional-connectivity-linkages (Beier 2006)

11 South Coast Missing Linkages polygons (e.g. Tehachapi, Sierra Madre – Castaic).

DuckDB:

MapLibre GL JS (PMTiles — note the source-layer is regional-connectivity-linkages):

H3 hex (res 8). Area columns are per-feature totals repeated on every cell — never SUM them on hex; dedup by _cng_fid, or compute area from COUNT(DISTINCT h8) × cell_area_at_res_8:

Vector — wildlife-movement-barriers (CDFW 2024)

204 linear infrastructure segments (roads/highways) that CDFW identified as barriers to terrestrial wildlife movement across California, with priority rankings for 2020/2022/2024 and remediation status. Source: CDFW BIOS ds2867 (priorities as of June 2024). Geometry is lines (LineString / MultiLineString); each segment was hexed to H3 resolution 8 by buffering it by the H3 cell circumradius before polyfill.

DuckDB — top-priority barriers by length:

MapLibre GL JS (PMTiles — note the source-layer is wildlife-movement-barriers):

H3 hex (res 8). Length_kilometers is a per-feature total repeated on every cell a barrier covers — never SUM it on hex; dedup by Barrier_ID (one row per barrier) or _cng_fid first, or count barriers with COUNT(DISTINCT Barrier_ID):

Priority_2020/Priority_2022/Priority_2024 take values Barrier, Priority Barrier, Top Priority Barrier, Remediated (NULL = not assessed that cycle). Target_Species is a free-text, comma-separated list of focal species. CDFW_Region is 1–6 (comma-joined for barriers spanning multiple regions). SUMMARY_LINK is a per-barrier CDFW summary PDF.

Rasters

H3 hex tables have columns <value>, h9 (native res 9), h0 (partition key). One row per H3 cell.

climate-migration-routes (Schloss 2022) — categorical, 13 classes

Connectivity class per cell (mode reducer). Classes: 0 limited/none; 100–103 Diffuse (intact); 200–203 Intensified (multiple linkages); 300–303 Channelized (present-day linkage); +1/+2/+3 = HADGEM2-ES / CNRM-CM5 / both climate-model linkages. See classification:classes on the COG band.

COG (titiler / categorical colormap): https://s3-west.nrp-nautilus.io/public-connectivity/climate-migration-routes-cog.tif

present-day-connectivity/flow (Cameron 2022) — continuous index 0–100

Current-flow connectivity index (mean reducer).

COG: https://s3-west.nrp-nautilus.io/public-connectivity/present-day-connectivity-flow-cog.tif

present-day-connectivity/categories (Cameron 2022) — categorical, 12 classes

Connectivity-strategy category per cell (mode reducer). Classes: 3 Limited movement potential; 4 Permeable (local movement); 19 Impeded; 25,29 Diffuse; 31,35,39 Intensified; 41,45,49 Channelized; 0 background (undocumented in source). See classification:classes on the COG band. COG: https://s3-west.nrp-nautilus.io/public-connectivity/present-day-connectivity-categories-cog.tif

Citations

California Department of Fish and Wildlife (2024). Terrestrial Wildlife Connectivity Barriers (Wildlife Movement Barriers). CDFW BIOS ds2867. https://wildlife.ca.gov/Data/BIOS
Beier, P., et al. (2006). South Coast Missing Linkages. South Coast Wildlands. (CDFW BIOS ds419)
Cameron, D. R., Schloss, C. A., Theobald, D. M., & Morrison, S. A. (2022). A framework to select strategies for conserving and restoring habitat connectivity. Conservation Science and Practice, e12698. https://doi.org/10.1111/csp2.12698
Schloss, C. A., et al. (2022). "No-regrets" pathways for navigating climate change. Ecological Applications. https://doi.org/10.1002/eap.2468

README

public-connectivity

Dataset	Source	Products	License
`regional-connectivity-linkages`	Beier et al. 2006 — South Coast Missing Linkages (CDFW BIOS ds419)	GeoParquet, PMTiles, H3 hex (res 8)	CC-BY-4.0
`wildlife-movement-barriers`	CDFW 2024 — Terrestrial Wildlife Connectivity Barriers (BIOS ds2867)	GeoParquet, PMTiles, H3 hex (res 8)	CC-BY-4.0
`climate-migration-routes`	Schloss et al. 2022 (Dryad `d7wm37q1m`)	COG, H3 hex (res 9)	CC0-1.0
`present-day-connectivity/flow`	Cameron et al. 2022 (Dryad `7sqv9s4v3`)	COG, H3 hex (res 9)	CC0-1.0
`present-day-connectivity/categories`	Cameron et al. 2022 (Dryad `7sqv9s4v3`)	COG, H3 hex (res 9)	CC0-1.0

Vector — regional-connectivity-linkages (Beier 2006)

11 South Coast Missing Linkages polygons (e.g. Tehachapi, Sierra Madre – Castaic).

DuckDB:

MapLibre GL JS (PMTiles — note the source-layer is regional-connectivity-linkages):

H3 hex (res 8). Area columns are per-feature totals repeated on every cell — never SUM them on hex; dedup by _cng_fid, or compute area from COUNT(DISTINCT h8) × cell_area_at_res_8:

Vector — wildlife-movement-barriers (CDFW 2024)

DuckDB — top-priority barriers by length:

MapLibre GL JS (PMTiles — note the source-layer is wildlife-movement-barriers):

Rasters

H3 hex tables have columns <value>, h9 (native res 9), h0 (partition key). One row per H3 cell.

climate-migration-routes (Schloss 2022) — categorical, 13 classes

COG (titiler / categorical colormap): https://s3-west.nrp-nautilus.io/public-connectivity/climate-migration-routes-cog.tif

present-day-connectivity/flow (Cameron 2022) — continuous index 0–100

Current-flow connectivity index (mean reducer).

COG: https://s3-west.nrp-nautilus.io/public-connectivity/present-day-connectivity-flow-cog.tif

present-day-connectivity/categories (Cameron 2022) — categorical, 12 classes

Citations

California Department of Fish and Wildlife (2024). Terrestrial Wildlife Connectivity Barriers (Wildlife Movement Barriers). CDFW BIOS ds2867. https://wildlife.ca.gov/Data/BIOS
Beier, P., et al. (2006). South Coast Missing Linkages. South Coast Wildlands. (CDFW BIOS ds419)
Cameron, D. R., Schloss, C. A., Theobald, D. M., & Morrison, S. A. (2022). A framework to select strategies for conserving and restoring habitat connectivity. Conservation Science and Practice, e12698. https://doi.org/10.1111/csp2.12698
Schloss, C. A., et al. (2022). "No-regrets" pathways for navigating climate change. Ecological Applications. https://doi.org/10.1002/eap.2468

1INSTALL spatial; LOAD spatial;
2SELECT Proj_Name, Area_ha
3FROM read_parquet('https://s3-west.nrp-nautilus.io/public-connectivity/regional-connectivity-linkages.parquet')
4ORDER BY Area_ha DESC;

1INSTALL spatial; LOAD spatial;
2SELECT Proj_Name, Area_ha
3FROM read_parquet('https://s3-west.nrp-nautilus.io/public-connectivity/regional-connectivity-linkages.parquet')
4ORDER BY Area_ha DESC;

1map.addSource('linkages', { type: 'vector', url: 'pmtiles://https://s3-west.nrp-nautilus.io/public-connectivity/regional-connectivity-linkages.pmtiles' });
2map.addLayer({
3  id: 'linkages-fill', type: 'fill',
4  source: 'linkages',
5  'source-layer': 'regional-connectivity-linkages',
6  paint: { 'fill-color': '#2c7fb8', 'fill-opacity': 0.5 }
7});

1map.addSource('linkages', { type: 'vector', url: 'pmtiles://https://s3-west.nrp-nautilus.io/public-connectivity/regional-connectivity-linkages.pmtiles' });
2map.addLayer({
3  id: 'linkages-fill', type: 'fill',
4  source: 'linkages',
5  'source-layer': 'regional-connectivity-linkages',
6  paint: { 'fill-color': '#2c7fb8', 'fill-opacity': 0.5 }
7});

1SELECT Proj_Name, COUNT(DISTINCT h8) AS cells
2FROM read_parquet('https://s3-west.nrp-nautilus.io/public-connectivity/regional-connectivity-linkages/hex/h0=*/data_0.parquet')
3GROUP BY 1 ORDER BY 2 DESC;

1SELECT Proj_Name, COUNT(DISTINCT h8) AS cells
2FROM read_parquet('https://s3-west.nrp-nautilus.io/public-connectivity/regional-connectivity-linkages/hex/h0=*/data_0.parquet')
3GROUP BY 1 ORDER BY 2 DESC;

1INSTALL spatial; LOAD spatial;
2SELECT Barrier_ID, Segment_Name, County, Priority_2024, Length_kilometers
3FROM read_parquet('https://s3-west.nrp-nautilus.io/public-connectivity/wildlife-movement-barriers.parquet')
4WHERE Priority_2024 = 'Top Priority Barrier'
5ORDER BY Length_kilometers DESC;

1INSTALL spatial; LOAD spatial;
2SELECT Barrier_ID, Segment_Name, County, Priority_2024, Length_kilometers
3FROM read_parquet('https://s3-west.nrp-nautilus.io/public-connectivity/wildlife-movement-barriers.parquet')
4WHERE Priority_2024 = 'Top Priority Barrier'
5ORDER BY Length_kilometers DESC;

1map.addSource('barriers', { type: 'vector', url: 'pmtiles://https://s3-west.nrp-nautilus.io/public-connectivity/wildlife-movement-barriers.pmtiles' });
2map.addLayer({
3  id: 'barriers-line', type: 'line',
4  source: 'barriers',
5  'source-layer': 'wildlife-movement-barriers',
6  paint: {
7    'line-width': 2,
8    'line-color': [
9      'match', ['get', 'Priority_2024'],
10      'Top Priority Barrier', '#d7301f',
11      'Priority Barrier', '#fc8d59',
12      'Barrier', '#fdcc8a',
13      'Remediated', '#2c7fb8',
14      '#cccccc'
15    ]
16  }
17});

1map.addSource('barriers', { type: 'vector', url: 'pmtiles://https://s3-west.nrp-nautilus.io/public-connectivity/wildlife-movement-barriers.pmtiles' });
2map.addLayer({
3  id: 'barriers-line', type: 'line',
4  source: 'barriers',
5  'source-layer': 'wildlife-movement-barriers',
6  paint: {
7    'line-width': 2,
8    'line-color': [
9      'match', ['get', 'Priority_2024'],
10      'Top Priority Barrier', '#d7301f',
11      'Priority Barrier', '#fc8d59',
12      'Barrier', '#fdcc8a',
13      'Remediated', '#2c7fb8',
14      '#cccccc'
15    ]
16  }
17});

1-- barriers per H3 cell (where wildlife corridors are most pinched)
2SELECT h8, COUNT(DISTINCT Barrier_ID) AS n_barriers
3FROM read_parquet('https://s3-west.nrp-nautilus.io/public-connectivity/wildlife-movement-barriers/hex/h0=*/data_0.parquet')
4GROUP BY h8 ORDER BY n_barriers DESC;

1-- barriers per H3 cell (where wildlife corridors are most pinched)
2SELECT h8, COUNT(DISTINCT Barrier_ID) AS n_barriers
3FROM read_parquet('https://s3-west.nrp-nautilus.io/public-connectivity/wildlife-movement-barriers/hex/h0=*/data_0.parquet')
4GROUP BY h8 ORDER BY n_barriers DESC;

1SELECT connectivity_class, COUNT(*) n
2FROM read_parquet('https://s3-west.nrp-nautilus.io/public-connectivity/climate-migration-routes/hex/h0=*/data_0.parquet')
3GROUP BY 1 ORDER BY 1;

1SELECT connectivity_class, COUNT(*) n
2FROM read_parquet('https://s3-west.nrp-nautilus.io/public-connectivity/climate-migration-routes/hex/h0=*/data_0.parquet')
3GROUP BY 1 ORDER BY 1;

1SELECT MIN(current_flow), MAX(current_flow), AVG(current_flow)
2FROM read_parquet('https://s3-west.nrp-nautilus.io/public-connectivity/present-day-connectivity-flow/hex/h0=*/data_0.parquet');

1SELECT MIN(current_flow), MAX(current_flow), AVG(current_flow)
2FROM read_parquet('https://s3-west.nrp-nautilus.io/public-connectivity/present-day-connectivity-flow/hex/h0=*/data_0.parquet');