# Umbanhowar fire data from Bayan Nuur, western Mongolia - IMPD MNBYN001 #----------------------------------------------------------------------- # World Data Center for Paleoclimatology, Boulder # and # NOAA Paleoclimatology Program #----------------------------------------------------------------------- # NOTE: Please cite original publication, online resource and date accessed when using this data. # If there is no publication information, please cite Investigator, title, online resource and date accessed. # # Description/Documentation lines begin with # # Data lines have no # # # Online_Resource: http://www.ncdc.noaa.gov/paleo/study/20411 # Online_Resource: http://www1.ncdc.noaa.gov/pub/data/paleo/firehistory/charcoal/asia/mnbyn001.txt # # Archive: Fire History # # Parameter_Keywords: #--------------------------------------- # Contribution_Date # Date: 2016-08-01 #--------------------------------------- # Title # Study_Name: Umbanhowar fire data from Bayan Nuur, western Mongolia - IMPD MNBYN001 #--------------------------------------- # Investigators # Investigators: Umbanhowar, Charles #--------------------------------------- # Description and Notes # Description: # Provided Keywords: fire, paleoclimate, climate, charcoal #--------------------------------------- # Publication # Authors: Umbanhowar, C.E., Shinneman, A.L.C., Tserenkhand, G., Hammon, E.R., Lor, P., and Nail, K. # Published_Date_or_Year: 2009 # Published_Title: Regional fire history based on charcoal analysis of sediments from nine lakes in western Mongolia. # Journal_Name: The Holocene # Volume: 19 # Edition: # Issue: # Pages: 611-624 # Report Number: # DOI: # Online_Resource: # Full_Citation: # Abstract: Fires are common in grassland regions of the world, and the frequency and severity of fire is linked to climate-driven changes in fuel loads. Western Mongolia is dominated by grasslands but the fire history of this region is largely unknown. We reconstructed modern fire (48 lakes) and historical fires (9 lakes) using sediment charcoal. Modern fuel loads were estimated using a combination of clipped plots, satellite-based estimates of annual aboveground net primary productivity (NPP) and NPP modeled from annual temperature and precipitation. Loss-on-ignition and environmental magnetics of lake sediments were analyzed as proxies for climate. We found little evidence for modern or historical fire in the landscape, as charcoal was absent from the surface sediments of 34 of 48 lakes. Charcoal influxes were uniformly low, averaging from 0.002 to 0.028 mm2/cm2 per yr, over the past 1200 years at nine lakes, and the past 6000-5000 years at two of the lakes with longer sediment records. In the modern landscape, livestock grazing has eliminated most of the fuels necessary to carry a fire, as measured fuel loads (27.3+-4.9 g/m2) were only ~20% of aboveground annual NPP estimated using MODIS Imagery or modeled from climate data. The historical absence of fire may indicate a longer history of intensive grazing than sometimes assumed, and cultural prohibitions against burning may also play a role. Regional summary indicated a >50% decrease in charcoal influxes since AD 1600 at most sites which may be related to lower temperatures or greater aridity during the 'Little Ice Age'. Alternatively this decrease in charcoal influxes may reflect increases in livestock numbers or increased local concentrations because of restrictions on the movement of animals coincident with the establishment of Manchu rule in the late seventeenth century. #--------------------------------------- # Funding_Agency # Funding_Agency_Name: # Grant: #--------------------------------------- # Site Information # Site_Name: Bayan Nuur # Location: Asia # Country: Mongolia # Northernmost_Latitude: 48.4631 # Southernmost_Latitude: 48.4631 # Easternmost_Longitude: 95.1604 # Westernmost_Longitude: 95.1604 # Elevation: 1540 #--------------------------------------- # Data_Collection # Collection_Name: MNBYN001-CHAR # First_Year: 3136.363636425 # Last_Year: -55.3 # Time_Unit: cal yr BP # Core_Length: # Notes: #--------------------------------------- # Species # Species_Name: # Common_Name: # Tree_Species_Code: #--------------------------------------- # Chronology_Information # Chronology: # # Short name What Units Data type # ID_DATE_INFO NaN NaN # ID_SITE Site ID NaN C # CORE_NAME Name of core NaN C # AVG_DEPTH (cm) Average depth of aged sample cm N # THICKNESS Thickness of sample cm N # ID_DATE_TYPE NaN NaN C # AGE_CALIB Calibrated age NaN N # AGE_C14 Carbon-14 Age NaN N # ERROR positive/negative error NaN N # LAB_NUM Lab number NaN N # ID_MAT_DATED NaN NaN NaN # ID_COMMENTS NaN NaN C # AGE_BASIS Used for age model? NaN C # # ID_DATE_INFO ID_SITE CORE_NAME AVG_DEPTH (m) THICKNESS ID_DATE_TYPE AGE_CALIB AGE_C14 ERROR LAB_NUM ID_MAT_DATED ID_COMMENTS AGE_BASIS # Bayan 1401 1 Pb -55 # Bayan 1402 1 Pb -53 # Bayan 1404 1 Pb -46 # Bayan 1405 1 Pb -42 # Bayan 1407 1 Pb -31 # Bayan 1408 1 Pb -24 # Bayan 1409 1 Pb -16 # Bayan 1410 1 Pb 3 # Bayan 1411 1 Pb 22 # Bayan 1412 1 Pb 44 # Bayan 1413 1 Pb 73 # Bayan 1414 1 Pb 90 # Bayan 1415 1 Pb 114 # Bayan 1479.5 5 Corrected radiocarbon date 2000 2050 45 132982 charcoal YES # Bayan 1567.5 5 Corrected radiocarbon date 3000 2875 50 129274 charcoal YES #--------------------------------------- # Variables # Data variables follow that are preceded by "##" in columns one and two. # Variables list, one per line, shortname-tab-longname components (9 components: what, material, error, units, seasonality, archive, detail, method, C or N for Character or Numeric data) ## depth-cm-top Depth top,,,cm ,,,,,N ## depth-cm-bottom Depth bottom,,,cm ,,,,,N ## age-calBP Age,,,calendar years BP,,,,,N ## char>180um Charcoal ,wet sediment,,count,,fire history,> 180 um,,N ## vol-wetsed Volume,wet sediment,,cm3,,fire history,used for charcoal counts,,N #------------------------ # Data # Data lines follow (have no #) # Data line format - tab-delimited text, variable short name as header # Missing Value: depth-cm-top depth-cm-bottom age-calBP char>180um vol-wetsed 1400 1401 -55.30 1 1.0 1401 1402 -52.80 0 1.0 1402 1403 -49.40 1 1.0 1403 1404 -46.00 1 1.0 1404 1405 -42.00 0 1.0 1405 1406 -36.65 0 1.0 1406 1407 -31.30 1 1.0 1407 1408 -24.30 1 1.0 1408 1409 -15.70 0 1.0 1409 1410 3.30 0 1.0 1410 1411 21.60 0 1.0 1411 1412 44.20 0 1.0 1412 1413 72.50 0 1.0 1413 1414 90.10 0 1.0 1414 1415 96.19 0 1.0 1415 1416 130.81 0 1.0 1416 1417 165.42 0 1.0 1417 1418 200.04 0 1.0 1418 1419 234.65 0 1.0 1419 1420 269.27 0 1.0 1420 1421 303.88 2 1.0 1421 1422 338.50 0 1.0 1422 1423 373.11 0 1.0 1423 1424 407.72 1 1.0 1424 1425 442.34 4 1.0 1425 1426 476.95 0 1.0 1426 1427 511.57 0 1.0 1427 1428 546.18 0 1.0 1428 1429 580.80 2 1.0 1429 1430 615.41 0 1.0 1430 1431 650.03 0 1.0 1431 1432 684.64 3 1.0 1432 1433 719.26 1 1.0 1433 1434 753.87 0 1.0 1434 1435 788.49 1 1.0 1435 1436 823.10 0 1.0 1436 1437 857.72 1 1.0 1437 1438 892.33 0 1.0 1438 1439 926.94 1 1.0 1439 1440 961.56 0 1.0 1440 1441 996.17 0 1.0 1441 1442 1030.79 0 1.0 1442 1443 1065.40 1 1.0 1443 1444 1100.02 2 1.0 1444 1445 1134.63 0 1.0 1445 1446 1169.25 1 1.0 1446 1447 1203.86 0 1.0 1447 1448 1238.48 1 1.0 1448 1449 1273.09 1 1.0 1449 1450 1307.71 0 1.0 1450 1451 1342.32 0 1.0 1451 1452 1376.94 1 1.0 1452 1453 1411.55 1 1.0 1453 1454 1446.17 0 1.0 1454 1455 1480.78 0 1.0 1455 1456 1515.39 1 1.0 1456 1457 1550.01 2 1.0 1457 1458 1584.62 0 1.0 1458 1459 1619.24 2 1.0 1459 1460 1653.85 2 1.0 1460 1461 1688.47 2 1.0 1461 1462 1723.08 2 1.0 1462 1463 1757.70 0 1.0 1463 1464 1792.31 0 1.0 1464 1465 1826.93 0 1.0 1465 1466 1861.54 0 1.0 1466 1467 1896.16 0 1.0 1467 1468 1930.77 3 1.0 1468 1469 1965.39 1 1.0 1469 1470 2000.00 1 1.0 1470 1471 2011.36 2 1.0 1471 1472 2022.73 1 1.0 1472 1473 2034.09 0 1.0 1473 1474 2045.45 3 1.0 1474 1475 2056.82 2 1.0 1475 1476 2068.18 0 1.0 1476 1477 2079.55 3 1.0 1477 1478 2090.91 1 1.0 1478 1479 2102.27 1 1.0 1479 1480 2113.64 2 1.0 1480 1481 2125.00 1 1.0 1481 1482 2136.36 1 1.0 1482 1483 2147.73 1 1.0 1483 1484 2159.09 0 1.0 1484 1485 2170.45 1 1.0 1485 1486 2181.82 0 1.0 1486 1487 2193.18 2 1.0 1487 1488 2204.55 5 1.0 1488 1489 2215.91 5 1.0 1489 1490 2227.27 3 1.0 1490 1491 2238.64 1 1.0 1491 1492 2250.00 2 1.0 1492 1493 2261.36 2 1.0 1493 1494 2272.73 0 1.0 1494 1495 2284.09 1 1.0 1495 1496 2295.45 2 1.0 1496 1497 2306.82 1 1.0 1497 1498 2318.18 2 1.0 1498 1499 2329.55 0 1.0 1499 1500 2340.91 0 1.0 1500 1501 2352.27 0 1.0 1501 1502 2363.64 3 1.0 1502 1503 2375.00 2 1.0 1503 1504 2386.36 4 1.0 1504 1505 2397.73 4 1.0 1505 1506 2409.09 3 1.0 1506 1507 2420.45 3 1.0 1507 1508 2431.82 3 1.0 1508 1509 2443.18 1 1.0 1509 1510 2454.55 6 1.0 1510 1511 2465.91 6 1.0 1511 1512 2477.27 4 1.0 1512 1513 2488.64 2 1.0 1513 1514 2500.00 5 1.0 1514 1515 2511.36 4 1.0 1515 1516 2522.73 4 1.0 1516 1517 2534.09 2 1.0 1517 1518 2545.45 8 1.0 1518 1519 2556.82 2 1.0 1519 1520 2568.18 1 1.0 1520 1521 2579.55 1 1.0 1521 1522 2590.91 2 1.0 1522 1523 2602.27 1 1.0 1523 1524 2613.64 0 1.0 1524 1525 2625.00 2 1.0 1525 1526 2636.36 0 1.0 1526 1527 2647.73 1 1.0 1527 1528 2659.09 4 1.0 1528 1529 2670.45 0 1.0 1529 1530 2681.82 2 1.0 1530 1531 2693.18 0 1.0 1531 1532 2704.55 1 1.0 1532 1533 2715.91 1 1.0 1533 1534 2727.27 2 1.0 1534 1535 2738.64 4 1.0 1535 1536 2750.00 1 1.0 1536 1537 2761.36 1 1.0 1537 1538 2772.73 0 1.0 1538 1539 2784.09 3 1.0 1539 1540 2795.45 4 1.0 1540 1541 2806.82 2 1.0 1541 1542 2818.18 2 1.0 1542 1543 2829.55 0 1.0 1543 1544 2840.91 5 1.0 1544 1545 2852.27 2 1.0 1545 1546 2863.64 1 1.0 1546 1547 2875.00 0 1.0 1547 1548 2886.36 0 1.0 1548 1549 2897.73 1 1.0 1549 1550 2909.09 3 1.0 1550 1551 2920.45 1 1.0 1551 1552 2931.82 0 1.0 1552 1553 2943.18 0 1.0 1553 1554 2954.55 4 1.0 1554 1555 2965.91 2 1.0 1555 1556 2977.27 5 1.0 1556 1557 2988.64 0 1.0 1557 1558 3000.00 3 1.0 1558 1559 3011.36 3 1.0 1559 1560 3022.73 4 1.0 1560 1561 3034.09 2 1.0 1561 1562 3045.45 0 1.0 1562 1563 3056.82 1 1.0 1563 1564 3068.18 0 1.0 1564 1565 3079.55 1 1.0 1565 1566 3090.91 1 1.0 1566 1567 3102.27 0 1.0 1567 1568 3113.64 0 1.0 1568 1569 3125.00 2 1.0 1569 1570 3136.36 0 1.0