# Searles Valley, CA Plant Wax Carbon, Hydrogen Isotopes, GDGTs, and Pollen Data from the Latest Pleistocene and Modern Taxa #----------------------------------------------------------------------- # World Data Service for Paleoclimatology, Boulder # and # NOAA Paleoclimatology Program #----------------------------------------------------------------------- # Template Version 4.0 # Encoding: UTF-8 # NOTE: Please cite original publication, NOAA Landing Page URL, dataset and publication DOIs (where available), and date accessed when using downloaded data. # If there is no publication information, please cite investigator, study title, NOAA Landing Page URL, and date accessed. # # Description/Documentation lines begin with '#' followed by a space # Data lines have no '#' # # NOAA_Landing_Page: https://www.ncei.noaa.gov/access/paleo-search/study/36393 # Landing_Page_Description: NOAA Landing Page of this file's parent study, which includes all study metadata. # # Study_Level_JSON_Metadata: https://www.ncei.noaa.gov/pub/data/metadata/published/paleo/json/noaa-lake-36393.json # Study_Level_JSON_Description: JSON metadata of this data file's parent study, which includes all study metadata. # # Data_Type: Paleolimnology # # Dataset_DOI: 10.25921/nmse-3986 # # Science_Keywords: air temperature reconstruction, glacial, interglacial, last glacial maximum, precipitation reconstruction #--------------------------------------- # Resource_Links # # Data_Download_Resource: https://www.ncei.noaa.gov/pub/data/paleo/paleolimnology/northamerica/usa/california/peaple2022/peaple2022-plants.txt # Data_Download_Description: NOAA Template File; SLAPP-SRLS17-1A/B Plants Data # #--------------------------------------- # Contribution_Date # Date: 2022-04-28 #--------------------------------------- # File_Last_Modified_Date # Date: 2023-03-24 #--------------------------------------- # Title # Study_Name: Searles Valley, CA Plant Wax Carbon, Hydrogen Isotopes, GDGTs, and Pollen Data from the Latest Pleistocene and Modern Taxa #--------------------------------------- # Investigators # Investigators: Peaple, Mark; Bhattacharya, Tripti; Lowenstein, Tim; McGee, David; Olson, Kristian; Stroup, Justin; Tierney, Jessica; Feakins, Sarah #--------------------------------------- # Description_Notes_and_Keywords # Description: # Provided Keywords: biomarker, plant wax, carbon isotopes, hydrogen isotopes, pollen, GDGT #--------------------------------------- # Publication # Authors: Peaple, Mark D., Tripti Bhattacharya, Tim K. Lowenstein, David McGee, Kristian J. Olson, Justin S. Stroup, Jessica E. Tierney, Sarah J. Feakins # Published_Date_or_Year: 2022-10-01 # Published_Title: Biomarker and pollen evidence for late Pleistocene pluvials in the Mojave Desert # Journal_Name: Paleoceanography and Paleoclimatology # Volume: 37 # Edition: # Issue: 10 # Pages: # Report_Number: e2022PA004471 # DOI: 10.1029/2022PA004471 # Online_Resource: # Full_Citation: # Abstract: The climate of the southwestern North America has experienced profound changes between wet and dry phases over the past 200 kyr. To better constrain the timing, magnitude and paleoenvironmental impacts of these changes in hydroclimate, we conducted a multiproxy biomarker study from samples collected from a new 76 m sediment core (SLAPP-SRLS17) drilled in Searles Lake, California. Here, we use biomarkers and pollen to reconstruct vegetation, lake conditions and climate. We find that dD values of long chain n-alkanes are dominated by glacial to interglacial changes that match nearby Devils Hole calcite d18O variability, suggesting both archives predominantly reflect precipitation isotopes. However, precipitation isotopes do not simply covary with evidence for wet-dry changes in vegetation and lake conditions, indicating a partial disconnect between large scale atmospheric circulation tracked by precipitation isotopes and landscape moisture availability. Increased crenarchaeol production and decreased evidence for methane cycling reveal a 10 kyr interval of a fresh, productive and well-mixed lake during Termination II, corroborating evidence for a paleolake highstand from shorelines and spillover deposits in downstream Panamint Basin during the end of the penultimate (Tahoe) glacial (140–130 ka). At the same time brGDGTs yield the lowest temperature estimates (mean months above freezing = 9 ± 3°C) of the 200 kyr record. These limnological conditions are not replicated elsewhere in the 200 kyr record, suggesting that the Heinrich stadial 11 highstand was wetter than that during the last glacial maximum and Heinrich 1 (18–15 ka). #--------------------------------------- # Publication # Authors: Peaple, Mark D., Jessica E. Tierney, David McGee, Tim K. Lowenstein, Tripti Bhattacharya, Sarah J. Feakins # Published_Date_or_Year: 2021-03-23 # Published_Title: Identifying plant wax inputs in lake sediments using machine learning # Journal_Name: Organic Geochemistry # Volume: 156 # Edition: # Issue: # Pages: # Report_Number: 104222 # DOI: 10.1016/j.orggeochem.2021.104222 # Online_Resource: # Full_Citation: # Abstract: This study aims to evaluate whether machine learning techniques can be successfully applied to process the complex information contained within the molecular abundance distributions of plant wax n-alkane and n-alkanoic acid homologous series. We trained five vegetation identification models using plant wax chain length distributions from modern plants in the Mojave Desert (hyperarid) and the San Bernardino Mountains (conifer forest) and previously published data for macrophytes from Blood Pond (USA) and Mt Kenya (Kenya). All vegetation identification models proved accurate (mean classification accuracy = 0.81) at classifying the modern plant wax chain length distributions into desert plants, conifer and macrophyte categories. We then applied the models to fossil waxes extracted from a 76 m lacustrine sediment core drilled in Searles Valley, CA with an approximate age range of 10 to 150 kyrs (SLAPP-SRLS17) to reconstruct the proportion of desert plants, conifer woodland and lake vegetation. We compared our machine learning models with a previously published linear mixing model and validated our modelled plant type distributions by comparing the results with the archaeol caldarchaeol ecometric (ACE), a proxy for lake salinity, measured in the same core. We found a moderate positive correlation (r = 0.40) between the modelled desert plant proportion and high lake salinity in our models as well as a negative correlation (r = –0.45) between modelled macrophyte plants and ACE, validating the ability of the machine learning techniques to detect both xeric and macrophyte plant communities. Our results suggest that machine learning of plant wax molecular abundance distributions has potential to reconstruct past plant communities, given information from two compound classes and highly differentiated vegetation types. #--------------------------------------- # Funding_Agency # Funding_Agency_Name: US National Science Foundation # Grant: 1903665, 1903659 #--------------------------------------- # Funding_Agency # Funding_Agency_Name: David and Lucile Packard Foundation # Grant: #--------------------------------------- # Funding_Agency # Funding_Agency_Name: Comer Family Foundation # Grant: #--------------------------------------- # Site_Information # Site_Name: Searles Valley # Location: California # Northernmost_Latitude: 35.707579 # Southernmost_Latitude: 35.707579 # Easternmost_Longitude: -117.312931 # Westernmost_Longitude: -117.312931 # Elevation_m: 493 #--------------------------------------- # Data_Collection # Collection_Name: SLAPP-SRLS17-1A/B Plants Peaple2022 # First_Year: # Last_Year: # Time_Unit: # Core_Length_m: 76.7 # Parameter_Keywords: geochemistry, hydrogen isotopes, carbon isotopes # Notes: #--------------------------------------- # Chronology_Information # Chronology: #--------------------------------------- # Variables # PaST_Thesaurus_Download_Resource: https://www.ncei.noaa.gov/access/paleo-search/skos/past-thesaurus.rdf # PaST_Thesaurus_Download_Description: Paleoenvironmental Standard Terms (PaST) Thesaurus terms, definitions, and relationships in SKOS format. # # Data variables follow that are preceded by "##" in columns one and two. # Variables list, one per line, shortname-tab-var components: what, material, error, units, seasonality, data type, detail, method, C or N for Character or Numeric data) # ## habitat notes,,,,,paleolimnology,,,C,Modern plant habitat; sample plant wax abundances available from Peaple et al.(2021) reference in full ## species notes,,,,,paleolimnology,,,C,Plant species ## number number of samples,,,,,paleolimnology,,,N,Number of samples measured; if >1 then analysis are reported as a mean ## form plant functional type,,,,,paleolimnology,,,C,Life form ## lat latitude,,,degree north,,paleolimnology,,,N, ## long longitude,,,degree east,,paleolimnology,,,N, ## elev collection elevation,,,meter,,paleolimnology,,,N, ## d13Calk25 delta 13C,C25 n-alkane,,per mil VPDB,,paleolimnology,,isotope ratio mass spectrometry,N, ## d13Calk27 delta 13C,C27 n-alkane,,per mil VPDB,,paleolimnology,,isotope ratio mass spectrometry,N, ## d13Calk29 delta 13C,C29 n-alkane,,per mil VPDB,,paleolimnology,,isotope ratio mass spectrometry,N, ## d13Calk31 delta 13C,C31 n-alkane,,per mil VPDB,,paleolimnology,,isotope ratio mass spectrometry,N, ## d13Calk33 delta 13C,C33 n-alkane,,per mil VPDB,,paleolimnology,,isotope ratio mass spectrometry,N, ## d13Calk25err delta 13C,C25 n-alkane,one standard deviation,per mil VPDB,,paleolimnology,,isotope ratio mass spectrometry,N, ## d13Calk27err delta 13C,C27 n-alkane,one standard deviation,per mil VPDB,,paleolimnology,,isotope ratio mass spectrometry,N, ## d13Calk29err delta 13C,C29 n-alkane,one standard deviation,per mil VPDB,,paleolimnology,,isotope ratio mass spectrometry,N, ## d13Calk31err delta 13C,C31 n-alkane,one standard deviation,per mil VPDB,,paleolimnology,,isotope ratio mass spectrometry,N, ## d13Calk33err delta 13C,C33 n-alkane,one standard deviation,per mil VPDB,,paleolimnology,,isotope ratio mass spectrometry,N, ## d13Calkn number of samples,n-alkane,,count,,paleolimnology,,,N,number of carbon isotope replicates ## dDalk27 delta 2H,C27 n-alkane,,per mil VPDB,,paleolimnology,,isotope ratio mass spectrometry,N, ## dDalk29 delta 2H,C29 n-alkane,,per mil VPDB,,paleolimnology,,isotope ratio mass spectrometry,N, ## dDalk31 delta 2H,C31 n-alkane,,per mil VPDB,,paleolimnology,,isotope ratio mass spectrometry,N, ## dDalk33 delta 2H,C33 n-alkane,,per mil VPDB,,paleolimnology,,isotope ratio mass spectrometry,N, ## dDalk27err delta 2H,C27 n-alkane,one standard deviation,per mil VPDB,,paleolimnology,,isotope ratio mass spectrometry,N, ## dDalk29err delta 2H,C29 n-alkane,one standard deviation,per mil VPDB,,paleolimnology,,isotope ratio mass spectrometry,N, ## dDalk31err delta 2H,C31 n-alkane,one standard deviation,per mil VPDB,,paleolimnology,,isotope ratio mass spectrometry,N, ## dDalk33err delta 2H,C33 n-alkane,one standard deviation,per mil VPDB,,paleolimnology,,isotope ratio mass spectrometry,N, ## dDalkn number of samples,n-alkane,,count,,paleolimnology,,,N,number of hydrogen isotope replicates ## d13Cacid24 delta 13C,C24 n-alkanoic acid,,per mil VPDB,,paleolimnology,,isotope ratio mass spectrometry,N, ## d13Cacid26 delta 13C,C26 n-alkanoic acid,,per mil VPDB,,paleolimnology,,isotope ratio mass spectrometry,N, ## d13Cacid28 delta 13C,C28 n-alkanoic acid,,per mil VPDB,,paleolimnology,,isotope ratio mass spectrometry,N, ## d13Cacid30 delta 13C,C30 n-alkanoic acid,,per mil VPDB,,paleolimnology,,isotope ratio mass spectrometry,N, ## d13Cacid32 delta 13C,C32 n-alkanoic acid,,per mil VPDB,,paleolimnology,,isotope ratio mass spectrometry,N, ## d13Cacid24err delta 13C,C24 n-alkanoic acid,one standard deviation,per mil VPDB,,paleolimnology,,isotope ratio mass spectrometry,N, ## d13Cacid26err delta 13C,C26 n-alkanoic acid,one standard deviation,per mil VPDB,,paleolimnology,,isotope ratio mass spectrometry,N, ## d13Cacid28err delta 13C,C28 n-alkanoic acid,one standard deviation,per mil VPDB,,paleolimnology,,isotope ratio mass spectrometry,N, ## d13Cacid30err delta 13C,C30 n-alkanoic acid,one standard deviation,per mil VPDB,,paleolimnology,,isotope ratio mass spectrometry,N, ## d13Cacid32err delta 13C,C32 n-alkanoic acid,one standard deviation,per mil VPDB,,paleolimnology,,isotope ratio mass spectrometry,N, ## d13Cacidn number of samples,n-alkanoic acid,,count,,paleolimnology,,,N,number of carbon isotope replicates ## dDacid24 delta 2H,C24 n-alkanoic acid,,per mil VSMOW,,paleolimnology,,isotope ratio mass spectrometry,N, ## dDacid26 delta 2H,C26 n-alkanoic acid,,per mil VSMOW,,paleolimnology,,isotope ratio mass spectrometry,N, ## dDacid28 delta 2H,C28 n-alkanoic acid,,per mil VSMOW,,paleolimnology,,isotope ratio mass spectrometry,N, ## dDacid30 delta 2H,C30 n-alkanoic acid,,per mil VSMOW,,paleolimnology,,isotope ratio mass spectrometry,N, ## dDacid32 delta 2H,C32 n-alkanoic acid,,per mil VSMOW,,paleolimnology,,isotope ratio mass spectrometry,N, ## dDacid24err delta 2H,C24 n-alkanoic acid,one standard deviation,per mil VSMOW,,paleolimnology,,isotope ratio mass spectrometry,N, ## dDacid26err delta 2H,C26 n-alkanoic acid,one standard deviation,per mil VSMOW,,paleolimnology,,isotope ratio mass spectrometry,N, ## dDacid28err delta 2H,C28 n-alkanoic acid,one standard deviation,per mil VSMOW,,paleolimnology,,isotope ratio mass spectrometry,N, ## dDacid30err delta 2H,C30 n-alkanoic acid,one standard deviation,per mil VSMOW,,paleolimnology,,isotope ratio mass spectrometry,N, ## dDacid32err delta 2H,C32 n-alkanoic acid,one standard deviation,per mil VSMOW,,paleolimnology,,isotope ratio mass spectrometry,N, ## dDacidn number of samples,n-alkanoic acid,,count,,paleolimnology,,,N,number of hydrogen isotope replicates #------------------------ # Data: # Data lines follow (have no #) # Data line format - tab-delimited text, variable short name as header # Missing_Values: -999999 habitat species number form lat long elev d13Calk25 d13Calk27 d13Calk29 d13Calk31 d13Calk33 d13Calk25err d13Calk27err d13Calk29err d13Calk31err d13Calk33err d13Calkn dDalk27 dDalk29 dDalk31 dDalk33 dDalk27err dDalk29err dDalk31err dDalk33err dDalkn d13Cacid24 d13Cacid26 d13Cacid28 d13Cacid30 d13Cacid32 d13Cacid24err d13Cacid26err d13Cacid28err d13Cacid30err d13Cacid32err d13Cacidn dDacid24 dDacid26 dDacid28 dDacid30 dDacid32 dDacid24err dDacid26err dDacid28err dDacid30err dDacid32err dDacidn Forest Abies concolor 1 Tree 34.2 116.9 2175.0 -28.26 -29.34 -29.23 -999999 -999999 0.2 0.7 0.5 -999999 -999999 2 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -24.90 -25.38 -999999 -999999 -999999 0.0 0.6 -999999 2 -178.9 -163.2 -999999 -167.8 -999999 0.3 1.1 124.1 0.2 -999999 2.0 Forest Abies concolor 1 Tree 34.2 116.9 2145.0 -28.54 -29.01 -28.29 -999999 -999999 0.1 0.1 0.1 -999999 -999999 2 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -24.36 -24.91 -999999 -999999 -999999 0.1 0.5 -999999 2 -172.6 -160.9 -155.1 -157.7 -999999 0.8 2.4 3.5 1.0 -999999 2.0 Forest Abies concolor 1 Tree 34.2 116.9 2143.0 -27.24 -27.16 -26.86 -999999 -999999 0.0 0.1 0.2 -999999 -999999 2 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -24.01 -24.84 -25.18 -999999 -999999 0.1 0.0 0.4 -999999 2 -999999 -999999 -999999 -168.6 -999999 -999999 -999999 -999999 4.2 -999999 2.0 Desert Artemisia tridentata 1 Shrub 34.3 -116.9 2101.0 -999999 -34.74 -34.64 -999999 -999999 -999999 0.2 0.3 -999999 -999999 -999999 -166.3 -166.5 -999999 -999999 2.1 0.8 -999999 -999999 2 -30.03 -30.79 -31.59 -33.04 -999999 0.4 0.3 0.4 0.4 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 Desert Artemisia tridentata 1 Shrub 34.3 -116.9 2123.0 -999999 -35.13 -34.43 -999999 -999999 -999999 0.3 0.4 -999999 -999999 -999999 -136.3 -146.0 -999999 -999999 0.1 0.8 -999999 -999999 2 -30.37 -31.08 -31.45 -31.97 -999999 0.3 0.2 0.1 0.2 -999999 -999999 -159.0 -152.3 -140.7 -146.4 -999999 3.2 3.6 0.9 0.6 -999999 2.0 Desert Artemisia tridentata 1 Shrub 34.3 -11.7 2071.0 -999999 -34.77 -35.29 -999999 -999999 -999999 0.5 0.6 -999999 -999999 -999999 -150.3 -144.2 -999999 -999999 0.1 0.2 -999999 -999999 2 -31.72 -32.04 -33.33 -33.80 -999999 0.0 0.1 0.1 0.0 -999999 -999999 -165.0 -157.8 -142.3 -139.4 -999999 0.9 1.5 1.2 1.6 -999999 2.0 Desert Atriplex canescens 1 Shrub 35.8 117.4 540.0 -999999 -999999 -22.75 -25.89 -999999 -999999 -999999 0.0 0.1 -999999 2 -166.9 -167.2 -999999 -999999 1.0 1.1 -999999 -999999 2 -999999 -999999 -18.88 -18.76 -21.47 -999999 -999999 0.0 0.0 0.1 2 -999999 -149.0 -158.8 -165.1 -999999 -999999 -999999 -999999 -999999 -999999 -999999 Desert Atriplex canescens 1 Shrub 35.8 117.4 612.0 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -32.44 -32.56 -999999 -999999 -999999 0.2 0.2 2 -999999 -999999 -180.8 -188.5 -999999 -999999 -999999 1.1 1.6 -999999 2.0 Desert Atriplex confertifolia 1 Shrub 35.9 117.3 668.0 -999999 -21.38 -22.00 -24.57 -999999 -999999 0.1 0.1 0.5 -999999 2 -167.1 -167.5 -999999 -999999 0.3 0.6 -999999 -999999 2 -999999 -17.24 -18.47 -18.55 -20.25 -999999 0.1 0.0 0.0 0.2 2 -146.7 -145.7 -153.1 -164.3 -999999 2.7 0.2 0.0 1.2 -999999 2.0 Desert Atriplex hymenelytra 1 Shrub 35.8 117.4 540.0 -999999 -999999 -20.33 -22.35 -999999 -999999 -999999 0.2 0.4 -999999 2 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 2 -999999 -999999 -17.30 -17.74 -21.25 -999999 -999999 0.1 0.0 0.1 2 -999999 -999999 -150.0 -153.2 -102.8 -999999 -999999 7.1 5.6 -999999 2.0 Desert Cylindropuntia bigelovii 1 Cacti 35.6 117.5 657.1 -999999 -20.48 -19.44 -999999 -999999 -999999 0.0 0.1 -999999 -999999 2 -106.3 -999999 -999999 -999999 6.3 -999999 -999999 -999999 2 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -180.2 -181.0 -157.2 -999999 -999999 0.6 1.0 0.4 -999999 2.0 Desert Echinocactus polycephalus 1 Cacti 35.8 117.4 677.0 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 Desert Ericameria nauseosa 1 Shrub 35.9 117.3 668.0 -999999 -999999 -28.60 -32.73 -999999 -999999 -999999 0.5 0.0 -999999 2 -168.9 -177.9 -999999 -999999 0.4 0.8 -999999 -999999 2 -999999 -25.35 -28.16 -33.95 -35.20 -999999 0.1 0.1 0.1 0.0 2 -203.8 -201.2 -160.1 -162.6 -164.9 0.3 0.6 1.1 0.5 1.8 2.0 Desert Eriogonum pusillum 1 Shrub 35.8 117.4 677.0 -999999 -30.73 -30.77 -999999 -999999 -999999 0.4 0.4 -999999 -999999 2 -100.4 -97.4 -999999 -999999 0.1 0.6 -999999 -999999 2 -999999 -999999 -999999 -30.46 -34.21 -999999 -999999 -999999 0.2 0.8 2 -999999 -999999 -120.6 -55.0 -999999 -999999 -999999 2.1 -999999 -999999 2.0 Desert Ferocactus Cylindraceus 1 Cacti 36.3 117.4 526.5 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -32.30 -999999 -999999 -999999 -999999 0.5 -999999 2 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 Forest Juniperus occidentalis 1 Tree 34.3 116.9 2164.0 -999999 -999999 -999999 -999999 -30.18 -999999 -999999 -999999 -999999 0.1 2 -999999 -999999 -999999 -49.9 -999999 -999999 -999999 0.4 2 -999999 -999999 -24.09 -25.29 -26.29 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 Forest Juniperus occidentalis 1 Tree 34.3 116.9 2163.0 -999999 -999999 -999999 -999999 -30.42 -999999 -999999 -999999 -999999 0.1 2 -999999 -999999 -999999 -27.1 -999999 -999999 -999999 1.5 2 -999999 -999999 -999999 -28.05 -999999 -999999 -999999 -999999 0.7 -999999 2 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 Forest Juniperus occidentalis 1 Tree 34.3 116.9 2137.0 -999999 -999999 -999999 -999999 -32.29 -999999 -999999 -999999 -999999 0.2 2 -999999 -999999 -999999 -111.1 -999999 -999999 -999999 13.4 2 -999999 -999999 -32.40 -30.26 -999999 -999999 -999999 0.5 0.6 -999999 2 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 Forest Juniperus occidentalis 1 Tree 34.3 116.9 2138.0 -999999 -999999 -999999 -999999 -32.06 -999999 -999999 -999999 -999999 0.0 2 -999999 -999999 -999999 -88.4 -999999 -999999 -999999 8.4 2 -999999 -999999 -31.06 -28.92 -27.54 -999999 -999999 0.1 0.6 0.3 2 -999999 -999999 -159.8464 -177.8 -172.0 -999999 -999999 9 0.2 9.4 2.0 Forest Juniperus occidentalis 1 Tree 34.3 116.9 2104.0 -999999 -999999 -999999 -999999 -31.40 -999999 -999999 -999999 -999999 0.5 2 -999999 -999999 -53.0 -110.6 -999999 -999999 -999999 13.4 2 -999999 -999999 -30.89 -29.31 -28.35 -999999 -999999 1.2 0.4 0.5 2 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 -999999 Desert Larrea tridentata 1 Shrub 35.9 117.3 668.0 -999999 -21.38 -22.00 -24.57 -999999 -999999 0.1 0.1 0.5 -999999 2 -163.8 -164.6 -999999 -999999 2.1 3.6 -999999 -999999 2 -999999 -29.25 -30.33 -30.43 -31.38 -999999 0.2 0.3 0.2 0.6 2 -159.7 -163.6 -179.8 -179.6 -999999 0.2 1.8 1.9 4.2 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