diff --git a/dev_scripts/INaturalist_requester.py b/dev_scripts/INaturalist_requester.py
index e69de29..8e46828 100644
--- a/dev_scripts/INaturalist_requester.py
+++ b/dev_scripts/INaturalist_requester.py
@@ -0,0 +1,175 @@
+import requests
+from pathlib import Path
+import csv
+import time
+ 
+# Portland, OR place ID on iNaturalist
+PLACE_ID = 2143
+OUTPUT_FILE = Path(__file__).parent.parent / "wildlife" / "portland_wildlife.csv"
+ 
+TAXON_GROUPS = ["Aves", "Mammalia", "Reptilia", "Amphibia", "Insecta"]
+ 
+FIELDNAMES = [
+    "taxon_id",
+    "scientific_name",
+    "common_name",
+    "kingdom",
+    "phylum",
+    "class",
+    "order",
+    "family",
+    "genus",
+    "iconic_taxon",
+    "observation_count",
+    "photo_url_thumb",
+    "photo_url_med",
+    "wikipedia_url"
+]
+
+def fetch_species_for_group(iconic_taxon: str) -> list[dict]:
+    """Fetch unique species list for one iconic taxon group using species_counts."""
+    results = []
+    page = 1
+ 
+    print(f"Fetching {iconic_taxon}...")
+ 
+    while True:
+        response = requests.get(
+            "https://api.inaturalist.org/v1/observations/species_counts",
+            params={
+                "iconic_taxa": iconic_taxon,
+                "quality_grade": "research",
+                "per_page": 500,
+                "page": page,
+                "place_id" : PLACE_ID,
+            },
+        )
+        response.raise_for_status()
+        data = response.json()
+ 
+        results_page = data.get("results", [])
+        if not results_page:
+            break
+ 
+        for entry in results_page:
+            taxon = entry.get("taxon", {})
+ 
+            # Skip anything that isn't a species (genus-level matches etc.)
+            if taxon.get("rank") != "species":
+                continue
+ 
+            ancestors = {
+                a["rank"]: a["name"]
+                for a in taxon.get("ancestors", [])
+            }
+ 
+            photo = taxon.get("default_photo") or {}
+ 
+            results.append({
+                "taxon_id": taxon.get("id"),
+                "scientific_name": taxon.get("name"),
+                "common_name": taxon.get("preferred_common_name", ""),
+                "kingdom": ancestors.get("kingdom", ""),
+                "phylum": ancestors.get("phylum", ""),
+                "class": ancestors.get("class", ""),
+                "order": ancestors.get("order", ""),
+                "family": ancestors.get("family", ""),
+                "genus": ancestors.get("genus", ""),
+                "iconic_taxon": taxon.get("iconic_taxon_name", ""),
+                "observation_count": entry.get("count", 0),
+                "photo_url_thumb": photo.get("square_url", ""),
+                "photo_url_med": photo.get("medium_url", ""),
+                "wikipedia_url": taxon.get("wikipedia_url", "")
+            })
+ 
+        total = data.get("total_results", 0)
+        fetched_so_far = (page - 1) * 500 + len(results_page)
+        print(f"  Page {page} — {fetched_so_far}/{total} species")
+ 
+        if fetched_so_far >= total:
+            break
+ 
+        page += 1
+        time.sleep(1)  # stay within API rate limits (~1 req/sec)
+ 
+    print(f"  Done — {len(results)} species found for {iconic_taxon}\n")
+    return results
+
+def enrich_with_ancestors(species_list: list[dict]) -> list[dict]:
+    """
+    Batch-fetch full taxon details from /v1/taxa to fill in ancestor fields.
+    The species_counts endpoint omits ancestors, so we fetch them separately.
+    iNaturalist supports up to 30 comma-separated IDs per request.
+    """
+    BATCH_SIZE = 30
+    ids = [str(s["taxon_id"]) for s in species_list]
+    taxon_details = {}
+ 
+    print(f"Enriching {len(ids)} species with ancestor data...")
+ 
+    for i in range(0, len(ids), BATCH_SIZE):
+        batch = ids[i : i + BATCH_SIZE]
+        response = requests.get(
+            f"https://api.inaturalist.org/v1/taxa/{','.join(batch)}",
+        )
+        response.raise_for_status()
+        data = response.json()
+ 
+        for taxon in data.get("results", []):
+            ancestors = {
+                a["rank"]: a["name"]
+                for a in taxon.get("ancestors", [])
+            }
+            taxon_details[taxon["id"]] = {
+                "ancestors": ancestors,
+                "wikipedia_url": taxon.get("wikipedia_url", ""),
+            }
+ 
+        print(f"  Fetched batch {i // BATCH_SIZE + 1}/{-(-len(ids) // BATCH_SIZE)}")
+        time.sleep(1)
+ 
+    # Merge ancestor data back into species list
+    for s in species_list:
+        detail = taxon_details.get(s["taxon_id"], {})
+        ancestors = detail.get("ancestors", {})
+        s["kingdom"]       = ancestors.get("kingdom", "")
+        s["phylum"]        = ancestors.get("phylum", "")
+        s["class"]         = ancestors.get("class", "")
+        s["order"]         = ancestors.get("order", "")
+        s["family"]        = ancestors.get("family", "")
+        s["genus"]         = ancestors.get("genus", "")
+        s["wikipedia_url"] = detail.get("wikipedia_url", "") or s.get("wikipedia_url", "")
+ 
+    print("Enrichment complete.\n")
+    return species_list
+
+if __name__ == "__main__":
+    all_species = []
+ 
+    for group in TAXON_GROUPS:
+        species = fetch_species_for_group(group)
+        all_species.extend(species)
+ 
+    # Deduplicate by taxon_id just in case
+    seen = set()
+    unique_species = []
+    for s in all_species:
+        if s["taxon_id"] not in seen:
+            seen.add(s["taxon_id"])
+            unique_species.append(s)
+ 
+    # Sort by observation count descending — most-seen species first
+    # This makes it easy to cap at top ~200 for the POC
+    unique_species.sort(key=lambda x: x["observation_count"], reverse=True)
+ 
+    # Second pass: fill in ancestor taxonomy from /v1/taxa
+    unique_species = enrich_with_ancestors(unique_species)
+ 
+    print(f"Total unique species: {len(unique_species)}")
+ 
+    with open(OUTPUT_FILE, "w", newline="", encoding="utf-8") as f:
+        writer = csv.DictWriter(f, fieldnames=FIELDNAMES)
+        writer.writeheader()
+        writer.writerows(unique_species)
+ 
+    print(f"Written to {OUTPUT_FILE}")
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