BLM/USFS Greater Sage-Grouse Siting Screener

Batch sage-grouse habitat screening by coordinate. Give it a list of lat/lon sites and it returns, per site, whether the point falls inside a mapped Greater Sage-Grouse Habitat Management Area, which designation tier applies (PHMA / IHMA / GHMA and the rest), the governing Record of Decision or Resource Management Plan Amendment, an auditable explanation of how the most-restrictive-wins rule chose that answer, plain-language developability guidance, and - critically - which of the seven federal sub-region services actually answered and whether the point is even inside a mapped sub-region at all.

There is no single national BLM sage-grouse layer. This actor federates seven authoritative sub-region Record-of-Decision services and rolls them into one verdict.

Informational screen, not a determination. This is not an official BLM or USFS land-use decision. Confirm any siting, right-of-way or permitting decision with the relevant BLM Field Office or USFS Ranger District and the governing Resource Management Plan.

Who it is for

• Oil, gas and mining operators screening lease blocks and pad locations before a surface-use plan.
• Wind, solar and transmission developers routing around Priority Habitat before spending on survey.
• Right-of-way and linear-infrastructure teams comparing candidate alignments across state lines.
• Environmental and NEPA consultants who need the designation, the tier, and the plan citation in one row.
• Land and mineral analysts scoring a portfolio for permitting friction.

What changed in v1.1 (2026-08-01)

Every existing field is preserved with its original meaning (append-only).

1. A "Non-Habitat" polygon was being reported as a habitat HIT. The USFS Nevada/California service publishes a 378-ring polygon whose own category is the literal string Non-Habitat. v1.0 treated any non-null category as a hit, so a point inside it came back in_habitat: true, habitat_type: "Non-Habitat", with an "unrecognized designation" label and an "unknown" stipulation level. Reproducible live at 38.889751, -117.359478. That is a false positive on the flagship flag - it would send a developer into a BLM consultation the source says is not needed. v1.1 treats these as an explicit statement of absence: in_habitat: false, explicit_non_habitat: true.

2. The live Utah designation was not in the vocabulary. USFS Utah publishes Occupied - Anthro Mountain; v1.0 only had the alias Anthro Mtn. The real value was therefore unrecognised, which meant an unknown label, an unknown stipulation level, and - because unknown codes are sent to the back of the priority order - it lost every most-restrictive-wins comparison. Reproducible live at 39.933747, -110.433488. Added, ranked, and the vocabulary is now closed and asserted at runtime: an unknown designation fails the run rather than being silently ranked last.

3. A total outage used to emit a billable prose clear. The old row template initialised in_habitat: false, overlapping_designation_count: 0 and a developability_note that read, in plain English, "No queried Greater Sage-Grouse Habitat Management Area intersects this point." Nothing overwrote them when a source failed, and checked_sources listed all seven regardless of whether any had answered. A run in which every service errored produced seven confident, billable, wrong clears. Now every source carries its own source_status_<key>, checked_sources lists only sources that actually answered, and the verdict is null - never false - when any source did not answer.

4. A clear outside every mapped sub-region is now labelled UNMAPPED. Greater sage-grouse range includes parts of Montana, Washington and the Dakotas that none of these seven services maps. Each source's live WGS84 extent is now measured and asserted, and every row reports coverage_status, sources_covering_point and subregions_covering_point. Denver, the old "clear control", is in fact outside every mapped extent - which is a different and more honest answer than "clear". Given this actor's history (a service described as national turned out to be Colorado-only), knowing which sub-region answered is the whole point.

5. The nearby search was a bounding box capped at 25 records. A bounding box overshoots a circle by up to 27% at the corners, so "habitat within 10 miles" could include habitat 14 miles away, and the 25-record cap truncated silently. v1.1 uses a true circular search (distance + units) with full paging and an exact server-side count, and reports nearby_records_truncated if a read ever comes up short.

6. Nine columns were fetched on every request and thrown away. Recovered: Prioi_Type (Wyoming: proposed vs existing core), EIS, Status and Population (NW Colorado occupancy and population area), Habitat (preliminary PPH/PGH code), EIS_HAB and Source (BLM Colorado Record of Decision lineage), INDICATOR_SCORE, and PLANID (the BLM Oregon plan name).

7. 67 live drift assertions run before any billable row - layer name, geometry type, habitat field, feature count band, closed vocabulary and WGS84 extent for each of the seven services, plus three positive canaries (including one for each defect above) and a negative control. Any failure stops the run and bills nothing.

8. The run fails instead of billing when every asset errors, and that gate runs before pushData.

The seven sources, verified live 2026-08-01

Key	Layer	Features	WGS84 extent (lon / lat)
usfs_wy	Wyoming 9-Plan	4	-111.404..-103.999 / 40.556..44.840
usfs_ut	Utah	46	-113.579..-108.699 / 37.388..41.961
usfs_nvca	Nevada / California	4	-118.881..-113.811 / 37.654..42.415
usfs_nwco	NW Colorado	14	-107.219..-106.196 / 39.988..40.974
usfs_idmt	Idaho / SW Montana	3	-116.523..-110.874 / 41.519..46.050
blm_co	BLM Greater Sage Grouse HMA	4	-109.051..-105.643 / 39.200..41.003
blm_or	BLM OR GRSG Polygon Hub	589	-121.323..-117.026 / 41.992..45.188

Feature counts are low because these are dissolved multipart polygons, not parcel-level records. Both counts and extents are asserted at runtime.

Example input

{
  "assets": [
    { "lat": 42.985, "lon": -109.865, "label": "Pinedale Anticline, WY (Priority Habitat)" },
    { "lat": 38.889751, "lon": -117.359478, "label": "Nevada mapped Non-Habitat" },
    { "lat": 39.7392, "lon": -104.9903, "label": "Denver CO (outside every mapped sub-region)" }
  ],
  "radiusMiles": 0,
  "maxAssets": 25
}

Input fields

Field	Type	Description
assets	array	Points to screen: { "lat": number, "lon": number, "label": string } in WGS84 decimal degrees.
radiusMiles	integer	When a point is clear, also search this many miles around it (0-50, default 0). True circular search with an exact count.
maxAssets	integer	Safety cap on assets per run (default 25, max 200).

Output fields

Every field the actor declares is listed below.

Site identity and provenance

Field	Type	Description
asset_label	string	null
asset_lat	number	null
asset_lon	number	null
checked_at	string	null
screen_basis	string	null
disclaimer	string	null
error	string	null

Verdict and audit trail

Field	Type	Description
in_habitat	boolean	null
habitat_type	string	null
habitat_type_label	string	null
habitat_rank	integer	null
stipulation_level	string	null
developability_note	string	null
primary_selection_basis	string	null
overlapping_designation_count	integer	null
overlapping_designations	array	null
explicit_non_habitat	boolean	null
non_habitat_sources	string	null

Governing plan and decision document

Field	Type	Description
managing_source	string	null
managing_agency	string	null
managing_source_url	string	null
applicable_plan	string	null
applicable_plan_from_source	string	null
record_of_decision	string	null
plan_source_note	string	null
eis_subregion	string	null
priority_type	string	null
population_area	string	null
occupancy_status	string	null
preliminary_habitat_code	string	null
indicator_score	number	null

Coverage: which sub-region actually maps this point

Field	Type	Description
coverage_status	string	null
sources_covering_point	array	null
sources_covering_point_count	integer	null
subregions_covering_point	string	null

Nearby habitat (when radiusMiles > 0)

Field	Type	Description
nearby_habitat_checked	boolean	null
nearby_habitat_found	boolean	null
nearby_habitat_types	array	null
nearby_habitat_count_exact	integer	null
nearby_most_restrictive_type	string	null
nearby_most_restrictive_label	string	null
nearby_sources	string	null
radius_miles_used	number	null

Per-source outcome (null means NOT CHECKED)

Field	Type	Description
source_status_usfs_wy	string	null
source_status_usfs_ut	string	null
source_status_usfs_nvca	string	null
source_status_usfs_nwco	string	null
source_status_usfs_idmt	string	null
source_status_blm_co	string	null
source_status_blm_or	string	null
checked_sources	array	null
source_errors	array	null
sources_queried	integer	null
sources_answered	integer	null
sources_failed	integer	null
sources_failed_names	string	null
partial_result	boolean	null

Truncation and upstream health

Field	Type	Description
pip_records_truncated	boolean	null
nearby_records_truncated	boolean	null
drift_checks_passed	integer	null
drift_checks_total	integer	null

Reading the results correctly

• null is not false. A null in_habitat or developability_note means a source did not answer, so nothing was verified. Check partial_result and sources_failed_names before acting on a row.
• coverage_status is as important as in_habitat. outside_every_mapped_subregion means no federal sub-region service maps that point - it is unmapped, not surveyed and clear. Sage-grouse range extends well beyond the seven mapped sub-regions.
• explicit_non_habitat: true is stronger than a plain clear. It means a source affirmatively maps the point as outside habitat, rather than simply not covering it.
• primary_selection_basis shows the work. When several designations overlap, it names the winner, its rank, everything it beat, and the full ranking order, so the most-restrictive-wins rule can be audited rather than trusted.
• Leks are deliberately not screened. None of these seven federal services publishes lek locations, and state wildlife agencies restrict them. Inventing a lek-proximity field from a source that does not carry one would be a fabricated answer. Lek buffers remain a real permitting factor - get them from the state agency.

Inputs that populate the sparser columns

Several columns come from a single source and are therefore null unless the hit came from that source. Verified live 2026-08-01:

Columns	Populating input
priority_type, eis_subregion	{ "lat": 42.985, "lon": -109.865 } (Wyoming, Proposed Core)
record_of_decision, plan_source_note, indicator_score	{ "lat": 41.0002, "lon": -108.996136 } (BLM Colorado, NWCO_GH_ROD_2020)
occupancy_status, population_area, preliminary_habitat_code	{ "lat": 40.15625, "lon": -106.250525 } (NW Colorado, Occupied / Middle Park / PGH)
applicable_plan_from_source	{ "lat": 42.5145, "lon": -120.3821 } (BLM Oregon, 2021 Greater Sage-grouse Land Use Plan Amendments)
nearby_*	any clear point with radiusMiles above 0, e.g. { "lat": 43.30, "lon": -118.90 } with radiusMiles: 25 (40 polygons within range)
explicit_non_habitat, non_habitat_sources	{ "lat": 38.889751, "lon": -117.359478 }

Each of these mappings is pinned by an offline fixture so it cannot silently rot. sources_failed_names, source_errors and error are null on a healthy run - that is good news, not a dead column.

Use as an MCP tool

This actor is available to AI agents through mcp.apify.com. Every input and output field carries a description, so an agent can call it and reason about the result. It chains with the rest of the energy-siting shelf: pass the same coordinates to the BLM mining-claims, energy-corridor, critical-habitat and EPA nonattainment screeners and join on asset_label.

Typical agent prompt: "Screen these eight well-pad locations for Greater Sage-Grouse habitat, tell me which fall in Priority Habitat, and flag any that no federal sub-region maps at all."

Pricing

Pay per result: $8 per 1,000 result rows ($0.008 per screened site). One row per asset, whether flagged, clear or unmapped. Graduated discounts apply on paid Apify plans (Bronze 20% / Silver 30% / Gold 45% / Platinum 60% / Diamond 70%).

A run that cannot verify the seven services are healthy, or in which every asset failed, fails and bills nothing.

FAQ

Why seven services instead of one national layer? Because no national layer exists. Greater Sage-Grouse habitat was designated sub-region by sub-region through separate Records of Decision, and the data is published the same way. A service listed in some directories as national turned out to be Northwest-Colorado-only - which is precisely why every row now reports which sub-region extents contain the point.

My site came back clear. Is it really clear? Check coverage_status. inside_a_mapped_subregion means all seven services answered and none of them maps habitat there. outside_every_mapped_subregion means the point is beyond the mapped area entirely, which is a much weaker statement.

What does the stipulation level mean? It is a relative indication of permitting burden, not a legal test. high (PHMA) implies seasonal timing limitations, surface-disturbance density caps, lek noise thresholds and net-conservation-gain obligations. The developability_note spells out what the tier normally carries.

Why did my run fail with "Upstream drift detected"? A live assertion about one of the seven services failed - a renamed layer, a collapsed feature count, a shrunken extent, or an unknown habitat designation. The alternative would have been to bill you for a confident wrong answer. The message names the exact check and the exact service.

Does this include leks? No, deliberately. See "Reading the results correctly" above.

Related actors

Same coordinate in, same asset_label out:

• Energy Corridor Section 368 Screener - designated federal energy corridors.
• BLM Mining Claims - active claims on the same federal surface.
• USFWS Critical Habitat Screener - ESA-listed species habitat.
• EPA Nonattainment Air Permit Screener - NAAQS status for the same site.
• Interconnection Queue Tracker - what is already queued nearby.
• Site Due Diligence Bundle - 20 layers in a single call.