feat(Q3): wildlife journal query functions

Add get_wildlife_sightings_paginated, get_wildlife_stats, and
get_wildlife_frequency to queries.py with full test coverage.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

vigilar/storage/queries.py

@@ -426,6 +426,65 @@ def get_wildlife_sightings(
         return [dict(r._mapping) for r in rows]
 
 
+# --- Wildlife Journal Queries ---
+
+def get_wildlife_sightings_paginated(
+    engine: Engine,
+    species: str | None = None,
+    threat_level: str | None = None,
+    camera_id: str | None = None,
+    since_ts: float | None = None,
+    until_ts: float | None = None,
+    limit: int = 50,
+    offset: int = 0,
+) -> list[dict[str, Any]]:
+    query = (
+        select(wildlife_sightings).order_by(desc(wildlife_sightings.c.ts))
+        .limit(limit).offset(offset)
+    )
+    if species:
+        query = query.where(wildlife_sightings.c.species == species)
+    if threat_level:
+        query = query.where(wildlife_sightings.c.threat_level == threat_level)
+    if camera_id:
+        query = query.where(wildlife_sightings.c.camera_id == camera_id)
+    if since_ts:
+        query = query.where(wildlife_sightings.c.ts >= since_ts)
+    if until_ts:
+        query = query.where(wildlife_sightings.c.ts < until_ts)
+    with engine.connect() as conn:
+        return [dict(r) for r in conn.execute(query).mappings().all()]
+
+
+def get_wildlife_stats(engine: Engine) -> dict[str, Any]:
+    from sqlalchemy import func
+    with engine.connect() as conn:
+        total = conn.execute(
+            select(func.count()).select_from(wildlife_sightings)
+        ).scalar() or 0
+        species_rows = conn.execute(
+            select(wildlife_sightings.c.species, func.count().label("cnt"))
+            .group_by(wildlife_sightings.c.species)
+        ).mappings().all()
+        per_species = {r["species"]: r["cnt"] for r in species_rows}
+    return {"total": total, "species_count": len(per_species), "per_species": per_species}
+
+
+def get_wildlife_frequency(engine: Engine) -> dict[str, dict[str, int]]:
+    import datetime
+    buckets: dict[str, dict[str, int]] = {
+        "00-04": {}, "04-08": {}, "08-12": {}, "12-16": {}, "16-20": {}, "20-24": {}
+    }
+    with engine.connect() as conn:
+        rows = conn.execute(select(wildlife_sightings)).mappings().all()
+    for r in rows:
+        dt = datetime.datetime.fromtimestamp(r["ts"])
+        bucket_key = list(buckets.keys())[dt.hour // 4]
+        species = r["species"]
+        buckets[bucket_key][species] = buckets[bucket_key].get(species, 0) + 1
+    return buckets
+
+
 # --- Training Images ---
 
 def insert_training_image(