{"abstract":"Destroyed patches are still colonised.","category":"Ecological population dynamics","checks":7,"contract":"Occupancy p: p += c*p*(1-D-p) - e*p each year, clamped to [0, 1-D]; equilibrium max(0, 1-D-e/c); return [equilibrium rounded 6, trajectory rounded 6]; None for c<=0, e<0 or D outside [0,1).","evaluation_group":"w2-ecopop-levins-metapopulation","failed_approach":"Scaling colonisation by 1-D does not remove destroyed patches from the target pool.","family":"w2-ecopop-levins-metapopulation-habitat-loss-in-colonisation","id":"FA-65576","implementations":{"attempt":{"sha256":"6a143a9d25b02f4171e22db593fe976b12fdef540a211390799212dc67158fa9","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\nimport math\nN = 1\nobservations = []\ndef solve(c, e, destroyed, p0, years):\n    if c <= 0 or e < 0 or not 0 <= destroyed < 1:\n        return None\n    eq = max(0.0, 1 - destroyed - e / c)\n    p = p0\n    traj = []\n    for _ in range(years):\n        p = p + c * p * (1 - p) * (1 - destroyed) - e * p\n        p = min(max(p, 0.0), 1 - destroyed)\n        traj.append(round(p, 6))\n    return [round(eq, 6), traj]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression: butterfly network',\n   (0.5, 0.1, 0.2, 0.1, 6),\n   [0.6, [0.125, 0.154687, 0.18913, 0.227984, 0.27039, 0.314952]]),\n  ('control: intact habitat',\n   (0.4, 0.1, 0.0, 0.05, 5),\n   [0.75, [0.064, 0.081562, 0.103369, 0.130106, 0.162367]]),\n  ('regression: heavy destruction extinction',\n   (0.3, 0.2, 0.5, 0.3, 6),\n   [0.0, [0.258, 0.225131, 0.198669, 0.176895, 0.158663, 0.143177]]),\n  ('regression: overshoot clamp', (2.5, 0.05, 0.3, 0.6, 3), [0.68, [0.7, 0.665, 0.689937]]),\n  ('regression: no extinction', (0.6, 0.0, 0.1, 0.2, 4), [0.9, [0.284, 0.388966, 0.508231, 0.627697]]),\n  ('control: invalid destruction', (0.5, 0.1, 1.0, 0.1, 3), None),\n  ('control: empty network', (0.5, 0.1, 0.2, 0.0, 3), [0.6, [0.0, 0.0, 0.0]])],\n [('regression: butterfly network',\n   (0.5, 0.1, 0.2, 0.1, 6),\n   [0.6, [0.125, 0.154687, 0.18913, 0.227984, 0.27039, 0.314952]]),\n  ('control: intact habitat',\n   (0.4, 0.1, 0.0, 0.05, 5),\n   [0.75, [0.064, 0.081562, 0.103369, 0.130106, 0.162367]]),\n  ('regression: overshoot clamp', (2.5, 0.05, 0.3, 0.6, 3), [0.68, [0.7, 0.665, 0.689937]]),\n  ('regression: no extinction', (0.6, 0.0, 0.1, 0.2, 4), [0.9, [0.284, 0.388966, 0.508231, 0.627697]]),\n  ('control: invalid destruction', (0.5, 0.1, 1.0, 0.1, 3), None),\n  ('control: empty network', (0.5, 0.1, 0.2, 0.0, 3), [0.6, [0.0, 0.0, 0.0]]),\n  ('regression: high turnover',\n   (1.2, 0.8, 0.25, 0.4, 5),\n   [0.083333, [0.248, 0.198995, 0.171376, 0.15327, 0.140407]])],\n [('regression: butterfly network',\n   (0.5, 0.1, 0.2, 0.1, 6),\n   [0.6, [0.125, 0.154687, 0.18913, 0.227984, 0.27039, 0.314952]]),\n  ('control: intact habitat',\n   (0.4, 0.1, 0.0, 0.05, 5),\n   [0.75, [0.064, 0.081562, 0.103369, 0.130106, 0.162367]]),\n  ('regression: heavy destruction extinction',\n   (0.3, 0.2, 0.5, 0.3, 6),\n   [0.0, [0.258, 0.225131, 0.198669, 0.176895, 0.158663, 0.143177]]),\n  ('regression: overshoot clamp', (2.5, 0.05, 0.3, 0.6, 3), [0.68, [0.7, 0.665, 0.689937]]),\n  ('control: invalid destruction', (0.5, 0.1, 1.0, 0.1, 3), None),\n  ('control: empty network', (0.5, 0.1, 0.2, 0.0, 3), [0.6, [0.0, 0.0, 0.0]]),\n  ('regression: high turnover',\n   (1.2, 0.8, 0.25, 0.4, 5),\n   [0.083333, [0.248, 0.198995, 0.171376, 0.15327, 0.140407]])],\n [('control: intact habitat',\n   (0.4, 0.1, 0.0, 0.05, 5),\n   [0.75, [0.064, 0.081562, 0.103369, 0.130106, 0.162367]]),\n  ('regression: heavy destruction extinction',\n   (0.3, 0.2, 0.5, 0.3, 6),\n   [0.0, [0.258, 0.225131, 0.198669, 0.176895, 0.158663, 0.143177]]),\n  ('regression: overshoot clamp', (2.5, 0.05, 0.3, 0.6, 3), [0.68, [0.7, 0.665, 0.689937]]),\n  ('regression: no extinction', (0.6, 0.0, 0.1, 0.2, 4), [0.9, [0.284, 0.388966, 0.508231, 0.627697]]),\n  ('control: invalid destruction', (0.5, 0.1, 1.0, 0.1, 3), None),\n  ('control: empty network', (0.5, 0.1, 0.2, 0.0, 3), [0.6, [0.0, 0.0, 0.0]]),\n  ('regression: high turnover',\n   (1.2, 0.8, 0.25, 0.4, 5),\n   [0.083333, [0.248, 0.198995, 0.171376, 0.15327, 0.140407]])],\n [('regression: butterfly network',\n   (0.5, 0.1, 0.2, 0.1, 6),\n   [0.6, [0.125, 0.154687, 0.18913, 0.227984, 0.27039, 0.314952]]),\n  ('control: intact habitat',\n   (0.4, 0.1, 0.0, 0.05, 5),\n   [0.75, [0.064, 0.081562, 0.103369, 0.130106, 0.162367]]),\n  ('regression: heavy destruction extinction',\n   (0.3, 0.2, 0.5, 0.3, 6),\n   [0.0, [0.258, 0.225131, 0.198669, 0.176895, 0.158663, 0.143177]]),\n  ('regression: no extinction', (0.6, 0.0, 0.1, 0.2, 4), [0.9, [0.284, 0.388966, 0.508231, 0.627697]]),\n  ('control: invalid destruction', (0.5, 0.1, 1.0, 0.1, 3), None),\n  ('control: empty network', (0.5, 0.1, 0.2, 0.0, 3), [0.6, [0.0, 0.0, 0.0]]),\n  ('regression: high turnover',\n   (1.2, 0.8, 0.25, 0.4, 5),\n   [0.083333, [0.248, 0.198995, 0.171376, 0.15327, 0.140407]])]]\nfor label, args, expected in fixtures[N - 1]:\n    check(label, solve(*args), expected)\nprint(json.dumps({\"observations\": observations, \"passed\": all(x[\"passed\"] for x in observations)}, ensure_ascii=False))\nraise SystemExit(0 if all(x[\"passed\"] for x in observations) else 1)\n"},"broken":{"sha256":"9d5d6fa5b0db6e2e4de59f7846c1b1666232c052becde6f1bc20330b4b351155","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\nimport math\nN = 1\nobservations = []\ndef solve(c, e, destroyed, p0, years):\n    if c <= 0 or e < 0 or not 0 <= destroyed < 1:\n        return None\n    eq = max(0.0, 1 - destroyed - e / c)\n    p = p0\n    traj = []\n    for _ in range(years):\n        p = p + c * p * (1 - p) - e * p\n        p = min(max(p, 0.0), 1 - destroyed)\n        traj.append(round(p, 6))\n    return [round(eq, 6), traj]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression: butterfly network',\n   (0.5, 0.1, 0.2, 0.1, 6),\n   [0.6, [0.125, 0.154687, 0.18913, 0.227984, 0.27039, 0.314952]]),\n  ('control: intact habitat',\n   (0.4, 0.1, 0.0, 0.05, 5),\n   [0.75, [0.064, 0.081562, 0.103369, 0.130106, 0.162367]]),\n  ('regression: heavy destruction extinction',\n   (0.3, 0.2, 0.5, 0.3, 6),\n   [0.0, [0.258, 0.225131, 0.198669, 0.176895, 0.158663, 0.143177]]),\n  ('regression: overshoot clamp', (2.5, 0.05, 0.3, 0.6, 3), [0.68, [0.7, 0.665, 0.689937]]),\n  ('regression: no extinction', (0.6, 0.0, 0.1, 0.2, 4), [0.9, [0.284, 0.388966, 0.508231, 0.627697]]),\n  ('control: invalid destruction', (0.5, 0.1, 1.0, 0.1, 3), None),\n  ('control: empty network', (0.5, 0.1, 0.2, 0.0, 3), [0.6, [0.0, 0.0, 0.0]])],\n [('regression: butterfly network',\n   (0.5, 0.1, 0.2, 0.1, 6),\n   [0.6, [0.125, 0.154687, 0.18913, 0.227984, 0.27039, 0.314952]]),\n  ('control: intact habitat',\n   (0.4, 0.1, 0.0, 0.05, 5),\n   [0.75, [0.064, 0.081562, 0.103369, 0.130106, 0.162367]]),\n  ('regression: overshoot clamp', (2.5, 0.05, 0.3, 0.6, 3), [0.68, [0.7, 0.665, 0.689937]]),\n  ('regression: no extinction', (0.6, 0.0, 0.1, 0.2, 4), [0.9, [0.284, 0.388966, 0.508231, 0.627697]]),\n  ('control: invalid destruction', (0.5, 0.1, 1.0, 0.1, 3), None),\n  ('control: empty network', (0.5, 0.1, 0.2, 0.0, 3), [0.6, [0.0, 0.0, 0.0]]),\n  ('regression: high turnover',\n   (1.2, 0.8, 0.25, 0.4, 5),\n   [0.083333, [0.248, 0.198995, 0.171376, 0.15327, 0.140407]])],\n [('regression: butterfly network',\n   (0.5, 0.1, 0.2, 0.1, 6),\n   [0.6, [0.125, 0.154687, 0.18913, 0.227984, 0.27039, 0.314952]]),\n  ('control: intact habitat',\n   (0.4, 0.1, 0.0, 0.05, 5),\n   [0.75, [0.064, 0.081562, 0.103369, 0.130106, 0.162367]]),\n  ('regression: heavy destruction extinction',\n   (0.3, 0.2, 0.5, 0.3, 6),\n   [0.0, [0.258, 0.225131, 0.198669, 0.176895, 0.158663, 0.143177]]),\n  ('regression: overshoot clamp', (2.5, 0.05, 0.3, 0.6, 3), [0.68, [0.7, 0.665, 0.689937]]),\n  ('control: invalid destruction', (0.5, 0.1, 1.0, 0.1, 3), None),\n  ('control: empty network', (0.5, 0.1, 0.2, 0.0, 3), [0.6, [0.0, 0.0, 0.0]]),\n  ('regression: high turnover',\n   (1.2, 0.8, 0.25, 0.4, 5),\n   [0.083333, [0.248, 0.198995, 0.171376, 0.15327, 0.140407]])],\n [('control: intact habitat',\n   (0.4, 0.1, 0.0, 0.05, 5),\n   [0.75, [0.064, 0.081562, 0.103369, 0.130106, 0.162367]]),\n  ('regression: heavy destruction extinction',\n   (0.3, 0.2, 0.5, 0.3, 6),\n   [0.0, [0.258, 0.225131, 0.198669, 0.176895, 0.158663, 0.143177]]),\n  ('regression: overshoot clamp', (2.5, 0.05, 0.3, 0.6, 3), [0.68, [0.7, 0.665, 0.689937]]),\n  ('regression: no extinction', (0.6, 0.0, 0.1, 0.2, 4), [0.9, [0.284, 0.388966, 0.508231, 0.627697]]),\n  ('control: invalid destruction', (0.5, 0.1, 1.0, 0.1, 3), None),\n  ('control: empty network', (0.5, 0.1, 0.2, 0.0, 3), [0.6, [0.0, 0.0, 0.0]]),\n  ('regression: high turnover',\n   (1.2, 0.8, 0.25, 0.4, 5),\n   [0.083333, [0.248, 0.198995, 0.171376, 0.15327, 0.140407]])],\n [('regression: butterfly network',\n   (0.5, 0.1, 0.2, 0.1, 6),\n   [0.6, [0.125, 0.154687, 0.18913, 0.227984, 0.27039, 0.314952]]),\n  ('control: intact habitat',\n   (0.4, 0.1, 0.0, 0.05, 5),\n   [0.75, [0.064, 0.081562, 0.103369, 0.130106, 0.162367]]),\n  ('regression: heavy destruction extinction',\n   (0.3, 0.2, 0.5, 0.3, 6),\n   [0.0, [0.258, 0.225131, 0.198669, 0.176895, 0.158663, 0.143177]]),\n  ('regression: no extinction', (0.6, 0.0, 0.1, 0.2, 4), [0.9, [0.284, 0.388966, 0.508231, 0.627697]]),\n  ('control: invalid destruction', (0.5, 0.1, 1.0, 0.1, 3), None),\n  ('control: empty network', (0.5, 0.1, 0.2, 0.0, 3), [0.6, [0.0, 0.0, 0.0]]),\n  ('regression: high turnover',\n   (1.2, 0.8, 0.25, 0.4, 5),\n   [0.083333, [0.248, 0.198995, 0.171376, 0.15327, 0.140407]])]]\nfor label, args, expected in fixtures[N - 1]:\n    check(label, solve(*args), expected)\nprint(json.dumps({\"observations\": observations, \"passed\": all(x[\"passed\"] for x in observations)}, ensure_ascii=False))\nraise SystemExit(0 if all(x[\"passed\"] for x in observations) else 1)\n"},"fixed":{"sha256":"12a4edf58c8258450fd7b9b977b8de459903628d8b2925bd34b6aef7732ebe6a","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\nimport math\nN = 1\nobservations = []\ndef solve(c, e, destroyed, p0, years):\n    if c <= 0 or e < 0 or not 0 <= destroyed < 1:\n        return None\n    eq = max(0.0, 1 - destroyed - e / c)\n    p = p0\n    traj = []\n    for _ in range(years):\n        p = p + c * p * (1 - destroyed - p) - e * p\n        p = min(max(p, 0.0), 1 - destroyed)\n        traj.append(round(p, 6))\n    return [round(eq, 6), traj]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression: butterfly network',\n   (0.5, 0.1, 0.2, 0.1, 6),\n   [0.6, [0.125, 0.154687, 0.18913, 0.227984, 0.27039, 0.314952]]),\n  ('control: intact habitat',\n   (0.4, 0.1, 0.0, 0.05, 5),\n   [0.75, [0.064, 0.081562, 0.103369, 0.130106, 0.162367]]),\n  ('regression: heavy destruction extinction',\n   (0.3, 0.2, 0.5, 0.3, 6),\n   [0.0, [0.258, 0.225131, 0.198669, 0.176895, 0.158663, 0.143177]]),\n  ('regression: overshoot clamp', (2.5, 0.05, 0.3, 0.6, 3), [0.68, [0.7, 0.665, 0.689937]]),\n  ('regression: no extinction', (0.6, 0.0, 0.1, 0.2, 4), [0.9, [0.284, 0.388966, 0.508231, 0.627697]]),\n  ('control: invalid destruction', (0.5, 0.1, 1.0, 0.1, 3), None),\n  ('control: empty network', (0.5, 0.1, 0.2, 0.0, 3), [0.6, [0.0, 0.0, 0.0]])],\n [('regression: butterfly network',\n   (0.5, 0.1, 0.2, 0.1, 6),\n   [0.6, [0.125, 0.154687, 0.18913, 0.227984, 0.27039, 0.314952]]),\n  ('control: intact habitat',\n   (0.4, 0.1, 0.0, 0.05, 5),\n   [0.75, [0.064, 0.081562, 0.103369, 0.130106, 0.162367]]),\n  ('regression: overshoot clamp', (2.5, 0.05, 0.3, 0.6, 3), [0.68, [0.7, 0.665, 0.689937]]),\n  ('regression: no extinction', (0.6, 0.0, 0.1, 0.2, 4), [0.9, [0.284, 0.388966, 0.508231, 0.627697]]),\n  ('control: invalid destruction', (0.5, 0.1, 1.0, 0.1, 3), None),\n  ('control: empty network', (0.5, 0.1, 0.2, 0.0, 3), [0.6, [0.0, 0.0, 0.0]]),\n  ('regression: high turnover',\n   (1.2, 0.8, 0.25, 0.4, 5),\n   [0.083333, [0.248, 0.198995, 0.171376, 0.15327, 0.140407]])],\n [('regression: butterfly network',\n   (0.5, 0.1, 0.2, 0.1, 6),\n   [0.6, [0.125, 0.154687, 0.18913, 0.227984, 0.27039, 0.314952]]),\n  ('control: intact habitat',\n   (0.4, 0.1, 0.0, 0.05, 5),\n   [0.75, [0.064, 0.081562, 0.103369, 0.130106, 0.162367]]),\n  ('regression: heavy destruction extinction',\n   (0.3, 0.2, 0.5, 0.3, 6),\n   [0.0, [0.258, 0.225131, 0.198669, 0.176895, 0.158663, 0.143177]]),\n  ('regression: overshoot clamp', (2.5, 0.05, 0.3, 0.6, 3), [0.68, [0.7, 0.665, 0.689937]]),\n  ('control: invalid destruction', (0.5, 0.1, 1.0, 0.1, 3), None),\n  ('control: empty network', (0.5, 0.1, 0.2, 0.0, 3), [0.6, [0.0, 0.0, 0.0]]),\n  ('regression: high turnover',\n   (1.2, 0.8, 0.25, 0.4, 5),\n   [0.083333, [0.248, 0.198995, 0.171376, 0.15327, 0.140407]])],\n [('control: intact habitat',\n   (0.4, 0.1, 0.0, 0.05, 5),\n   [0.75, [0.064, 0.081562, 0.103369, 0.130106, 0.162367]]),\n  ('regression: heavy destruction extinction',\n   (0.3, 0.2, 0.5, 0.3, 6),\n   [0.0, [0.258, 0.225131, 0.198669, 0.176895, 0.158663, 0.143177]]),\n  ('regression: overshoot clamp', (2.5, 0.05, 0.3, 0.6, 3), [0.68, [0.7, 0.665, 0.689937]]),\n  ('regression: no extinction', (0.6, 0.0, 0.1, 0.2, 4), [0.9, [0.284, 0.388966, 0.508231, 0.627697]]),\n  ('control: invalid destruction', (0.5, 0.1, 1.0, 0.1, 3), None),\n  ('control: empty network', (0.5, 0.1, 0.2, 0.0, 3), [0.6, [0.0, 0.0, 0.0]]),\n  ('regression: high turnover',\n   (1.2, 0.8, 0.25, 0.4, 5),\n   [0.083333, [0.248, 0.198995, 0.171376, 0.15327, 0.140407]])],\n [('regression: butterfly network',\n   (0.5, 0.1, 0.2, 0.1, 6),\n   [0.6, [0.125, 0.154687, 0.18913, 0.227984, 0.27039, 0.314952]]),\n  ('control: intact habitat',\n   (0.4, 0.1, 0.0, 0.05, 5),\n   [0.75, [0.064, 0.081562, 0.103369, 0.130106, 0.162367]]),\n  ('regression: heavy destruction extinction',\n   (0.3, 0.2, 0.5, 0.3, 6),\n   [0.0, [0.258, 0.225131, 0.198669, 0.176895, 0.158663, 0.143177]]),\n  ('regression: no extinction', (0.6, 0.0, 0.1, 0.2, 4), [0.9, [0.284, 0.388966, 0.508231, 0.627697]]),\n  ('control: invalid destruction', (0.5, 0.1, 1.0, 0.1, 3), None),\n  ('control: empty network', (0.5, 0.1, 0.2, 0.0, 3), [0.6, [0.0, 0.0, 0.0]]),\n  ('regression: high turnover',\n   (1.2, 0.8, 0.25, 0.4, 5),\n   [0.083333, [0.248, 0.198995, 0.171376, 0.15327, 0.140407]])]]\nfor label, args, expected in fixtures[N - 1]:\n    check(label, solve(*args), expected)\nprint(json.dumps({\"observations\": observations, \"passed\": all(x[\"passed\"] for x in observations)}, ensure_ascii=False))\nraise SystemExit(0 if all(x[\"passed\"] for x in observations) else 1)\n"}},"limitations":"Deterministic bounded teaching model with a stipulated contract; not a validated scientific or public-health modelling library. This reproducer isolates one failure mechanism. Results cover the supplied fixtures. Variants within a family share a test contract and should remain grouped when constructing evaluation splits. Related mechanisms with a shared evaluation_group must also remain together; these controlled models are not independent production incidents.","method":"Deterministic executable model with adversarial boundary fixtures.","provenance":{"created_by":"Failure Map","dependencies":"Python standard library","family":"w2-ecopop-levins-metapopulation-habitat-loss-in-colonisation","generated_at":"2026-09-29T14:47:35.304770+00:00","license":"CC0-1.0","python":"3.12.14","seed":1,"split":"open-access"},"relevance":"Population projections set harvest quotas, conservation status and pest-control timing; a wrong update order, boundary or rate conversion silently changes management advice.","repair":"Restore the habitat loss in colonisation rule: `c * p * (1 - destroyed - p)`.","root_cause":"Colonisation targets all empty patches including destroyed ones.","sha256":"d0757399ba52d13d59a726382fef2bf967c6632a03b3af26944bf7d0b27d99c4","title":"Levins metapopulation with habitat destruction: habitat loss in colonisation · case 01","variant":1,"variant_policy":"Five numbered records share a model and may reuse boundary fixtures.","verification":{"attempt":{"elapsed_ms":41.193,"exit_code":1,"observations":[{"actual":[0.6,[0.126,0.15745,0.194768,0.238025,0.28677,0.339906]],"check":"regression: butterfly network","expected":[0.6,[0.125,0.154687,0.18913,0.227984,0.27039,0.314952]],"passed":false},{"actual":[0.75,[0.064,0.081562,0.103369,0.130106,0.162367]],"check":"control: intact habitat","expected":[0.75,[0.064,0.081562,0.103369,0.130106,0.162367]],"passed":true},{"actual":[0.0,[0.2715,0.246868,0.225383,0.206494,0.189774,0.174883]],"check":"regression: heavy destruction extinction","expected":[0.0,[0.258,0.225131,0.198669,0.176895,0.158663,0.143177]],"passed":false},{"actual":[0.68,[0.7,0.7,0.7]],"check":"regression: overshoot clamp","expected":[0.68,[0.7,0.665,0.689937]],"passed":false},{"actual":[0.9,[0.2864,0.396763,0.526007,0.660642]],"check":"regression: no 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