In 2005, root ingrowth donuts were established on the Sevilleta NWR to monitor below ground biomass under different conditions and to compare estimates of root production between root ingrowth donut and mini-rhizonton tube methods at four sites on the east side of the refuge. Soil and roots are collected from the "donuts" annually in late fall after the growing season, and structures are then re-established in situ for consecutive harvests for the following years. Each structure allows roots to be harvested at two depths (0-15 and 15-30cm) to estimate root production, or "below ground net primary productivity".
Below-Ground Net Primary Production (BNPP): Root Ingrowth Donuts in Chihuahuan Desert Grassland and Creosote Shrubland at the Sevilleta National Wildlife Refuge, New MexicoSubmitted by administrator on Wed, 09/15/2010 - 9:28am
In 2005, annually harvested root ingrowth donut structures were co-located with previously established mini-rhizotron tubes established at four sites on McKenzie Flats located on the east side of Sevilleta NWR: 10 replicate structures in both burned and unburned blue and black grama dominated grassland plots at Deep Well, 10 replicates each on nitrogen fertilization plots and respective control plots on McKenzie Flats(20 total), 10 replicates in creosote dominated shrubland at the Five Points Creosote Core site and in 2011, 13 structures were put in the Monsoon site. Roots and soil are harvested annually in late fall after the growing season, and structures are reestablished in situ for consecutive harvests each year. Each structure allows roots to be harvested at two depths (0-15 and 15-30 cm) to estimate root production, or below ground net primary productivity. In order to compare estimates of root production from two methods, root ingrowth donuts were collocated with mini-rhizotron tubes at all localities except for the burned grassland plot at Deep Well.
Additional Information on the personnel associated with the Data Collection / Data Processing
Sevilleta Field Crew Employee History
Megan McClung, April 2013-present, Stephanie Baker, October 2010-Present, John Mulhouse, August 2009-Present, Amaris Swann, August 25, 2008-January 2013, Maya Kapoor, August 9, 2003-January 21, 2005 and April 2010-March 2011, Terri Koontz, February 2000-August 2003 and August 2006-August 2010, Yang Xia, January 31, 2005-April 2009, Karen Wetherill, February 7, 2000-August 2009, Michell Thomey, September 3, 2005-August 2008, Jay McLeod, January 2006-August 2006, Charity Hall, January 31, 2005-January 3, 2006, Tessa Edelen, August 15, 2004-August 15, 2005, Seth Munson, September 9, 2002-June 2004, Caleb Hickman, September 9, 2002-November 15, 2004, Heather Simpson, August 2000-August 2002, Chris Roberts, September 2001-August 2002, Mike Friggens, 1999-September 2001, Shana Penington, February 2000-August 2000.
23 Jan 2009All data sets (2005-2008) were combined and checked for errors in excel and exported into Navicat. From the 2007 data, I converted the dry root mass from grams to milligrams and changed depth data to be 0-15 and 15-30 cm. QA/QC'd data. I deleted data line from DWB sample 7, depth 15-30 cm with volume 2600 ml because it was a duplicate. I also changed the depth of DWB sample 12, depth 15-30 cm with volume 2000 to the depth 0-15 cm because the depth 15-30 cm was duplicated. -Changed missing data on volume and weight due to plant being dead to -888. -Changed missing data on volume and weight due to human error to -999. --A. Swann
The varied topography and large elevation gradients that characterize the arid and semi-arid Southwest create a wide range of climatic conditions - and associated biomes - within relatively short distances. This creates an ideal experimental system in which to study the effects of climate on ecosystems. Such studies are critical givien that the Southwestern U.S. has already experienced changes in climate that have altered precipitation patterns (Mote et al. 2005), and stands to experience dramatic climate change in the coming decades (Seager et al. 2007; Ting et al. 2007).
Biome Transition Along Elevational Gradients in New Mexico (SEON) Net Primary Productivity (NPP) Study at the Sevilleta National Wildlife Refuge, New MexicoSubmitted by amswann on Fri, 01/06/2012 - 10:27am
The varied topography and large elevation gradients that characterize the arid and semi-arid Southwest create a wide range of climatic conditions - and associated biomes - within relatively short distances. This creates an ideal experimental system in which to study the effects of climate on ecosystems. Such studies are critical givien that the Southwestern U.S. has already experienced changes in climate that have altered precipitation patterns (Mote et al. 2005), and stands to experience dramatic climate change in the coming decades (Seager et al. 2007; Ting et al. 2007). Climate models currently predict an imminent transition to a warmer, more arid climate in the Southwest (Seager et al. 2007; Ting et al. 2007). Thus, high elevation ecosystems, which currently experience relatively cool and mesic climates, will likely resemble their lower elevation counterparts, which experience a hotter and drier climate. In order to predict regional changes in carbon storage, hydrologic partitioning and water resources in response to these potential shifts, it is critical to understand how both temperature and soil moisture affect processes such as evaportranspiration (ET), total carbon uptake through gross primary production (GPP), ecosystem respiration (Reco), and net ecosystem exchange of carbon, water and energy across elevational gradients.
We are using a sequence of six widespread biomes along an elevational gradient in New Mexico -- ranging from hot, arid ecosystems at low elevations to cool, mesic ecosystems at high elevation to test specific hypotheses related to how climatic controls over ecosystem processes change across this gradient. We have an eddy covariance tower and associated meteorological instruments in each biome which we are using to directly measure the exchange of carbon, water and energy between the ecosystem and the atmosphere. This gradient offers us a unique opportunity to test the interactive effects of temperature and soil moisture on ecosystem processes, as temperature decreases and soil moisture increases markedly along the gradient and varies through time within sites.
In this study, soil characteristics after a lightning-initiated fire were evaluated. Following the fire in July 1998, 25 experimental plots were established on the eastern edge of MacKenzie Flats at the Sevilleta National Wildlife Refuge. Ten of these plots were located in a Bouteloua gracilis (blue grama)-dominated site, while 15 were established in another area dominated by Bouteloua eriopoda (black grama).
Burn Quadrat Data for the Net Primary Production Study at the Sevilleta National Wildlife Refuge, New MexicoSubmitted by administrator on Wed, 09/15/2010 - 9:28am
In 2003, the U.S. Fish and Wildlife Service conducted a prescribed burn over a large part of the northeastern corner of the Sevilleta National Wildlife Refuge. Following this burn, a study was designed to look at the effect of fire on above-ground net primary productivity (ANPP) (i.e., the change in plant biomass, represented by stems, flowers, fruit and foliage, over time) within three different vegetation types: mixed grass (MG), mixed shrub (MS) and black grama (G). Forty permanent 1m x 1m plots were installed in both burned and unburned (i.e., control) sections of each habitat type. The core black grama site included in SEV129 is used as a G control site for analyses and does not appear in this dataset. The MG control site caught fire unexpectedly in the fall of 2009 and some plots were subsequently moved to the south. For details of how the fire affected plot placement, see Methods below. In spring 2010, sampling of plots 16-25 was discontinued at the MG (burned and control) and G (burned treatment only) sites, reducing the number of sampled plots to 30 at each.
To measure ANPP (i.e., the change in plant biomass, represented by stems, flowers, fruit and foliage, over time), the vegetation variables in this dataset, including species composition and the cover and height of individuals, are sampled twice yearly (spring and fall) at each plot. The data from these plots is used to build regressions correlating biomass and volume via weights of select harvested species obtained in SEV157, "Net Primary Productivity (NPP) Weight Data." This biomass data is included in SEV185, "Seasonal Biomass and Seasonal and Annual NPP for Burn Study Sites."
Other researchers involved with collecting samples/data: Megan McClung (04/2013-present), Stephanie Baker (SRB; 09/2010-present), John Mulhouse (JMM; 08/2010-present), Amaris Swann (ALS; 08/2008-01/2013), Maya Kapoor (MLK; 08/2003-01/2005, 05/2010-03/2011), Terri Koontz (TLK; 02/2000-08/2003, 08/2006-08/2010), Yang Xia (YX; 01/2005-03/2010), Karen Wetherill (KRW; 02/2000-08/2009); Michell Thomey (MLT; 09/2005-08/2008); Seth Munson (SMM; 09/2002-06/2004), Jay McLeod (JRM; 01/2006-08/2006); Caleb Hickman (CRH; 09/2002-11/2004), Charity Hall (CLH; 01/2005-01/2006); Tessa Edelen (MTE, 08/2004-08/2005).
01/13/2011-Burn NPP quad data was QA/QC'd and put in Navicat. Matadata updated and compiled from 2004-2010. The mixed-grass unburned plot was moved to the south after the original plot burned unexpectedly in the fire of August 2009. (JMM) 11/28/2009-Burn NPP quad data was QA/QC'd and put in Navicat. Metadata updated and complied from 2004-2009. Mixed-grass unburned data (Fall 2009) was not collected due to unexpected fire at Sevilleta LTER in Aug 2009. (YX) 01/14/09-Metadata updated and compiled from 2004-2008 data. As of 2007, winter measurements are longer being taken. (YX) 12/20/2008-This data was QAQC'd in MySQL. I checked for duplicates and missing quads. (YX)
Comparative Hydraulic Performance of Piñon and Juniper in a Rainfall Manipulation Experiment at the Sevilleta National Wildlife Refuge, New MexicoSubmitted by srbaker on Thu, 01/19/2012 - 10:38am
From 2000-2003, extreme drought across the Southwestern US resulted in widespread tree mortality: piñon pine (Pinus edulis) experienced up to 95% mortality while juniper (Juniperus monosperma) mortality was 25% or less at surveyed sites. Field data have shown repeatedly that piñon typically exhibits isohydric regulation of leaf water potential, maintaining relatively constant leaf water potentials even as soil water potentials fluctuate, while juniper is anisohydric, allowing leaf water potential to decline during drought. The goal of this study was to elucidate functional consequences of these two contrasting hydraulic strategies. The study was conducted in the context of a rainfall manipulation experiment in piñon-juniper woodland at the Sevilleta National Wildlife Refuge and LTER in central New Mexico, USA, sampling trees in irrigation (~150% ambient rainfall), drought (50% ambient), cover control (ambient rainfall with similar drought infrastructure) and ambient control plots. To quantify tissue and shoot level hydraulic performances we measured sapwood area-specific (KS, kg•m-1•s-1•MPa-1) and leaf area-specific (KL, g•m-1•s-1•MPa-1) hydraulic conductivity in similar sized distal branches, and we calculated AS:AL (sapwood area to leaf area ratio) to compare shoot level allocation.
Samples collected at predawn and midday both exhibited significant trends between species and across treatments. Between species, juniper possessed significantly higher KS compared to piñon in all plots except irrigation, and higher KL than piñon in all plots. Across treatments, irrigated juniper exhibited higher KS and KL relative to ambient and droughted plants, while irrigated piñon exhibited higher KS relative to ambient, drought and cover control plants, and irrigated and ambient piñon had higher KL than droughted and cover control plants. Junipers did not modify AS:AL across treatments, while irrigated piñon had significantly lower AS:AL compared to all other plots. Thus, under current climatic conditions in the Sevilleta, piñon and juniper achieve similar shoot hydraulic performances, but through different strategies: juniper maximizes xylem conductivity, while piñon maximizes xylem supply to leaves. If climate change in the Southwest results in increased aridity, piñon could be vulnerable to extirpation from its current distribution in lower elevation PJ woodlands, as juniper demonstrates superior hydraulic capability at both the tissue and shoot level under drought conditions.
Core Site Quadrat Data for the Net Primary Production Study at the Sevilleta National Wildlife Refuge, New MexicoSubmitted by administrator on Wed, 09/15/2010 - 9:28am
This dataset is part of a long-term study at the Sevilleta LTER measuring net primary production (NPP) across four distinct ecosystems: creosote-dominant shrubland (Site C, est. winter 1999), black grama-dominant grassland (Site G, est. winter 1999), blue grama-dominant grassland (Site B, est. winter 2002), and pinon-juniper woodland (Site P, est. winter 2003). Net primary production is a fundamental ecological variable that quantifies rates of carbon consumption and fixation. Estimates of NPP are important in understanding energy flow at a community level as well as spatial and temporal responses to a range of ecological processes.
Above-ground net primary production is the change in plant biomass, represented by stems, flowers, fruit and and foliage, over time and incoporates growth as well as loss to death and decomposition. To measure this change the vegetation variables in this dataset, including species composition and the cover and height of individuals, are sampled twice yearly (spring and fall) at permanent 1m x 1m plots within each site. A third sampling at Site C is performed in the winter. The data from these plots is used to build regressions correlating biomass and volume via weights of select harvested species obtained in SEV157, "Net Primary Productivity (NPP) Weight Data." This biomass data is included in SEV182, "Seasonal Biomass and Seasonal and Annual NPP for Core Research Sites."
This dataset is designated as NA-US-011 in the Global Index of Vegetation-Plot Databases (GIVD). To aid tracking of the use of databases in this index, please also reference this number when citing this data. The GIVD report for SEV129 can be found in: Biodiversity and Ecology 4 - Vegetation Databases for the 21st Century (2012) by J. Dengler et al.
Other researchers involved with collecting samples/data: Megan McClung (MAM; 04/2013-present), Stephanie Baker (SRB; 09/2010-present), John Mulhouse (JMM; 08/2009-present), Amaris Swann (ALS; 08/2008-01/2013), Maya Kapoor (MLK; 08/2003 - 01/2005, 05/2010 - 03/2011), Terri Koontz (TLK; 02/2000 - 08/2003, 08/2006 - 08/2010), Yang Xia (YX; 01/2005 - 03/2010), Karen Wetherill (KRW; 02/2000 - 08/2009); Michell Thomey (MLT; 09/2005 - 08/2008), Heather Simpson (HLS; 08/2000 - 08/2002), Chris Roberts (CR; 09/2001- 08/2002), Shana Penington (SBP; 01/2000 - 08/2000), Seth Munson (SMM; 09/2002 - 06/2004), Jay McLeod (JRM; 01/2006 - 08/2006); Caleb Hickman (CRH; 09/2002 - 11/2004), Charity Hall (CLH; 01/2005 - 01/2006), Mike Friggens (MTF; 1999 - 09/2001), Tessa Edelen (MTE, 08/2004 - 08/2005).
01/12/2010 - Data was QA/QC'd and put in Navicat. Metadata was updated and compiled for 1999-2010. (JMM) 11/29/2009 - Data was QA/QC'd and put in Navicat. Metadata was updated and compiled for 1999-2009. Note: In fall of 2009, data from site G, webs 2, 3, and& 4 (plot N) was not collected due to unexpected fire at Sevilleta LTER sites. (YX) 01/05/2009 - Metadata was updated and compiled for 1999 - 2008. (YX) 01/06/2009 - As of 2007, winter season was no longer measured except at site C (creosotebush only). (YX) 12/05/2009 - NPP data from 1999-2008 was QA/QC'd in MySQL. 2006 (krw). In 2003, site B was added. In 2004, the number of quads was reduced to 40 per site (quads 2 and 4 at each plot are no longer read). I checked for duplicates and missing quads. These most often happened when a recorder mislabeled a particular quad. I also checked every plant code against the USDA Plants database online at http://plants.usda.gov/. All plant codes that have had nomenclature changes were updated. All previously unknown plants that have since been identified were also updated. All unknown plants that will never be identified were left in the database. All types were corrected. A list of codes not in the USDA list that are still in the data are as follows NONE = no plants in quad, OPUN = opuntia seedlings, SPOR = lumped Sporobolus spp (SPAI, SPCO4, SPCR, SPFL2), STEM = bare stem measurements for LATR2, U2 and UKFO18 and UKFO57 = unknowns that will never be identified, UKFO80 = unknown that has not yet been identified. A list of updates and the reason for the changes are below along with comments where identification is uncertain:OLD CODE,NEW CODE,NUMBER_ROWS_AFFECTED,REASON_FOR_CHANGEPOOL,POOL,2,TYPO-999,BOER4,3,ERROR_IN_DATA_MANAGEMENT ALLI1,ALMA4,2,IDENTIFIED_UKFO AMAR2,AMPA,8,IDENTIFIED_UKFO AMAR3,ACNE,9,IDENTIFIED_UKFO AMAR4,AMPA,4,IDENTIFIED_UKFO APIA1,CYMO,2,IDENTIFIED_UKFO ARDR4,ARLUL2,45,BELIEVED_MISIDENTIFICATION ARLUA,ARLUL2,3,BELIEVED_MISIDENTIFICATION ASTE13,SCMU6,31,IDENTIFIED_UKFO ASTE5,UKSH5,4,STILL_UNKNOWN ASTE7,TOAN,1,PROBABLE_IDENTIFICATION_FROM_UKFO_DESCRIPTION ASTRA,ASMIM,1,BEST_GUESS_FROM_DESCRIPTION BRAS1,LEDED,1,PROBABLE_IDENTIFICATION_FROM_UKFO_DESCRIPTION BRAS2,DRGL5,54,IDENTIFIED_UKFOBR BR2,BRCA3,4,ONLY_CHANGE_TO_BRCA3_AFTER_NEW_PJ_PLOT_DESIGN BREU,BREUC2,1,TYPO BRIC1,BRBR2,1,IDENTIFIED_UKFO BRIC3,BREUC2,5,IDENTIFIED_UKFO BRIC4,BREUC2,1,PROBABLE_IDENTIFICATION_FROM_UKFO_DESCRIPTION BRIC5,UKSH5,1,"KNOWN_FROM_LOCATION,_STILL_UNKNOWN" CACT,OPUN,4,"IN_ROW_ID_13908,_13919,_AND_184 47_CHANGE_COVER_TO_1,_THESE_ARE_LENGTH_BY_WIDTH_MEASUREMENTS,_OPUTIA_SPP_SEEDLINGS" CACT1,CACT1,0,NEVER_TO_BE_IDENTIFIED CADR6,HODR,630,NAME_CHANGE CAJA6,POJA5,8,NAME_CHANGE CHAL2,CHAL11,2,CODE_REDUNDANCY CHAM,CHMI7,1,IDENTIFIED_UKFO CHCO2,CHCO,5,ONLY_AT_SITE_MS CHEN1,TECO,58,IDENTIFIED_UKFO CHGO2,CHCO2,1,TYPO CHLA2,CHLA10,127,CODE_REDUNDANCY COAR4,VINE,10,"BAD_IDENTIFICATIONS,_I_RECOMMEND_LUMPING" COAU,COAU2,1,TYPO COEQ,VINE,3,"BAD_IDENTIFICATIONS,_I_RECOMMEND_LUMPING" CONV1,VINE,3,"BAD_IDENTIFICATIONS,_I_RECOMMEND_LUMPING" CONV3,VINE,7,"BAD_IDENTIFICATIONS,_I_RECOMMEND_LUMPING" CONV4,VINE,6,"BAD_IDENTIFICATIONS,_I_RECOMMEND_LUMPING" CRAB,PAOB,2,IDENTIFIED_UKFO CYMO,HYFIC,4,ONLY_AT_SITE_B DAJA,DABR,7,ONLY_AT_SITE_P DEOBO,DEPI,675,BELIEVED_MISIDENTIFICATION DEWO?,DEWO,1,CONFIRMED_ID ECFEF,ECCOC,2,BELIEVED_MISIDENTIFICATION ECFEF2,OPUN,1,ONLY_AT_PIS4 ECFEF2,ECCOC,3,ONLY_AT_SITE_P ECFEF2,ECFEF3,2,NAME_CHANGE ERCI,ERCI6,11,ONLY_ON_5/26/04_SITE_P ERCI6,ERCI,21,ALL_SITE_B ERDI2,ERFL,17,BELIEVED_MISIDENTIFICATION ERDI4,ERFL,32,BELIEVED_MISIDENTIFICATION ERRO2,ERPO4,1,ONLY_AT_SITE_P ERPU8,DAPU7,2006,NAME_CHANGE SCIND,ESVIV,3,ONLY_AT_MG EUGL3,CHGL13,1,NAME_CHANGE FABA1,LUBR2,1,PROBABLE_IDENTIFICATION_FROM_UKFO_DESCRIPTION FABA3,LOPL2,4,IDENTIFIED_UKFOF ORB1,FORB1,0,STILL_UNKNOWN FORB3,DIWI2,3,IDENTIFIED_UKFO GARR1,GACO5,2,IDENTIFIED_UKFO HEOB,HENA,9,BELIEVED_MISIDENTIFICATION HIJA,PLJA,1350,NAME_CHANGE HOGL2,HODR,985,BELIEVED_MISIDENTIFICATION HYVE,MILI3,1,ONLY_AT_SITE_P IPCO2,VINE,116,"BAD_IDENTIFICATIONS,_I_RECOMMEND_LUMPING" IPCO3,VINE,5,"BAD_IDENTIFICATIONS,_I_RECOMMEND_LUMPING" IPLE,VINE,1,"BAD_IDENTIFICATIONS,_I_RECOMMEND_LUMPING" IPLO,IPLO2,3,TYPO JF1,GACO5,2,PROBABLE_IDENTIFICATION_FROM_UKFO_DESCRIPTION JF3,PLPA2,13,PROBABLE_IDENTIFICATION_FROM_UKFO_DESCRIPTION JF5,POOL,1,MOST_COMMON_PORTULACA JG1,ARPUP6,2,PROBABLE_IDENTIFICATION_FROM_UKFO_DESCRIPTION JG2,BOGR2,4,"GRASS_SEEDLINGS,_LIKELY_BOGR2" JUM0,JUMO,1,SPELLED_WITH_A_ZERO KRLA,KRLA2,5,TYPO_NO_KRLA_AT_SITE_MS LARER,LAOCO,204,BELIEVED_MISIDENTIFICATION LITH1,LIIN2,3,IDENTIFIED_UKFO MAGR10,MAPIP,24,"BAD_IDENTIFICATIONS,_I_RECOMMEND_LUMPING" MIMU,MIOX,5,ONLY_FOR_P2R6 MUMI,MUTO2,1,QUESTIONABLE MUSQ,MOSQ,97,CODE_REDUNDANCY NEIN,ECIN2,12,NAME_CHANGE NYCT1,BOSP,1,IDENTIFIED_UKFO NYCT2,MILI3,14,IDENTIFIED_UKFO OEAL,OECAC2,17,"BAD_IDENTIFICATIONS,_I_RECOMMEND_LUMPING" OECEC2,OECAC2,806,CODE_REDUNDANCY ONAG1,GASUN,16,IDENTIFIED_UKFO OPEN,OPEN3,31,TYPO OPMAC,OPMA8,10,TYPO OPUN,OPUN,3,"IN_ROW_ID_19570,_20831,_AND_21055_CHANGE_COVER_TO_1,_THESE_ARE_LENGTH_BY_WIDTH_MEASUREMENTS,_OPUTIA_SPP_SEEDLINGS" OPUN1,OPUN,1,"IN_ROW_ID_38109,_THIS_IS_A_SEEDLING,_CHANGE_COVER_TO_1" PEPA20,SCPA10,1,NAME_CHANGE PF1,DRCUC,24,PROBABLE_IDENTIFICATION_FROM_UKFO_DESCRIPTION PF2,ARLUL2,15,PROBABLE_IDENTIFICATION_FROM_UKFO_DESCRIPTION PF3,PF3,0,NEVER_TO_BE_IDENTIFIED PF4,PF4,0,NEVER_TO_BE_IDENTIFIED PG1,HENE5,8,PROBABLE_IDENTIFICATION_FROM_UKFO_DESCRIPTION PHHEF,SOJA,3,"BAD_IDENTIFICATIONS,_I_RECOMMEND_LUMPING" POAC1,POAC1,0,NEVER_TO_BE_IDENTIFIED POAC11,POFE,25,PROBABLE_IDENTIFICATION_FROM_UKFO_DESCRIPTION POAC12,PAOB,3,IDENTIFIED_UKFO POAC14,POAC14,0,NEVER_TO_BE_IDENTIFIED POAC7,LYPH,3,IDENTIFIED_UKFO POLY1,CHGR2,98,IDENTIFIED_UKFO PORT1,POOL,1,MOST_COMMON_PORTULACA QUGR3,QUTU2,1244,"BAD_IDENTIFICATIONS,_I_RECOMMEND_LUMPING" SAKA,SATR12,588,BELIEVED_MISIDENTIFICATION SC?,SCPA10,1,GRAMA_CACTUS SCIND,ECIN2,19,NAME_CHANGE SCINI,ECIN2,46,BELIEVED_MISIDENTIFICATION SCSCN2,BOCU,8,BELIEVED_MISIDENTIFICATION SEED2,BELY,6,PROBABLE_IDENTIFICATION_FROM_UKFO_DESCRIPTION SOLA6,SOJA,14,IDENTIFIED_UKFO SOLA7,SOJA,2,IDENTIFIED_UKFO_PHHEF_LUMPED_WITH_SOJA SPAI,SPOR,39,ONLY_IN_SITE_P SPCO4,SPOR,2288,"BAD_IDENTIFICATIONS,_I_RECOMMEND_LUMPING" SPCR,SPOR,3603,"BAD_IDENTIFICATIONS,_I_RECOMMEND_LUMPING" SPFL2,SPOR,2485,"BAD_IDENTIFICATIONS,_I_RECOMMEND_LUMPING" SPHAE,SPWR,5,MOST_LIKELY_SPHAERALCEA SPORO,SPOR,2,"BAD_IDENTIFICATIONS,_I_RECOMMEND_LUMPING" STNE,HENE5,6,NAME_CHANGE STNE2,HENE5,72,NAME_CHANGE U1,MAFE,3,IDENTIFIED_UKFO U2,U2,0,NEVER_TO_BE_IDENTIFIED U3,U3,0,NEVER_TO_BE_IDENTIFIED U4,U4,0,NEVER_TO_BE_IDENTIFIED U5,VUOC,26,IDENTIFIED_UKFO U7,SCLA6,3,IDENTIFIED_UKFO UKAS2,ERFL,7,BEST_GUESS_FROM_DESCRIPTION UKCA,CHFE3,2,MOST_COMMON_CHAEMACYSE_IN_AREA UKCA1,MAHEH2,1,LOOKED_IN_FUTURE__DATA UKFO,SEDI3,1,BEST_GUESS_FROM_DESCRIPTION UKFO10,UKFO10,0,NEVER_TO_BE_IDENTIFIED UKFO13,UKFO13,0,NEVER_TO_BE_IDENTIFIED UKFO15,ARLUL2,2,PROBABLE_IDENTIFICATION_FROM_UKFO_DESCRIPTION UKFO16,BRBR2,3,IDENTIFIED_UKFO UKFO17,UKFO17,0,NEVER_TO_BE_IDENTIFIED UKFO18,UKFO18,0,NEVER_TO_BE_IDENTIFIED UKFO19,GUSA2,3,IDENTIFIED_UKFO UKFO20,SPLE,2,BEST_GUESS_FROM_DESCRIPTION UKFO21,DAJA,1,IDENTIFIED_UKFO UKFO22,SEDI3,1,IDENTIFIED_UKFO UKFO23,MESCS,1,IDENTIFIED_UKFO UKFO31,UKFO31,0,"COULD_BE_BADI,_GLWR_OR_NECA3" UKFO32,SACYH2,1,IDENTIFIED_UKFO UKFO51,UKFO51,0,NEVER_TO_BE_IDENTIFIED UKFO57,UKFO57,0,NEVER_TO_BE_IDENTIFIED UKFO61,THWR,186,IDENTIFIED_UKFO UKFO62,THWR,34,IDENTIFIED_UKFO UKFO7,ZIGR,2,IDENTIFIED_UKFO UKFO72,MILI3,27,PROBABLE_IDENTIFICATION_FROM_UKFO_DESCRIPTION UKFO72?,MILI3,1,PROBABLE_IDENTIFICATION_FROM_UKFO_DESCRIPTION UKFO73,HYVE,4,PROBABLE_IDENTIFICATION_FROM_UKFO_DESCRIPTION UKFO75,UKFO75,0,NEVER_TO_BE_IDENTIFIED UKFO76,UKFO75,3,NEVER_TO_BE_IDENTIFIED UKFO80,UKFO80,0,NOT_YET_IDENTIFIED UKGR2,LYPH,1,BEST_GUESS_FROM_DESCRIPTION UKSH1,SPLE,2,BEST_GUESS_FROM_DESCRIPTION UKSH4,BREUC2,8,IDENTIFIED_UKFO UKSH5,UKSH5,0,NOT_YET_IDENTIFIED
Shrub encroachment alters community dynamics and ecosystem functioning worldwide. Grazing increases shrub encroachment as herbivores selectively consume grasses, easing the advancement of shrubs. Diversity decreases with shrub invasion and species richness drops by half when semiarid grasslands become shrublands. A shift in dominance from grasses to shrubs changes community structure and lowers community stability by increasing species turnover. Transition to shrubland also increases regional winter low temperatures by nearly 2˚C. Soil resource distributions change in invaded grasslands as shrubs create islands of fertility and alter nutrient cycles. Soil under plants has higher infiltration rates than interspaces and at the SNWR shrublands have twice as much interspace area than grasslands, leading to higher runoff. Greater runoff also leads to greater soil and nutrient removal.
Shrub encroachment in the Southwest has increased dramatically over the past 150 years and is presumably linked to intensified human impacts. One local example of shrub encroachment is the expansion of creosote (Larrea tridentata) within Chihuahuan Desert grasslands. Chihuahuan Desert grasslands stretch from central Mexico to central New Mexico and are dominated by black grama. Winter low temperatures limit northward creosote expansion. Over the past century winter low temperature have increased 2˚C within some areas of the Southwest. With nighttime temperatures predicted to continue increasing, temperature limitations of creosote distribution may be relaxed.
Within central New Mexico lies the transition between Chihuahuan Desert grassland and Colorado plateau shortgrass steppe, dominated by blue grama. Although temperature and climate are similar at the boundary between these ecosystems, creosote is only found in black grama grasslands and not in blue grama grasslands. Soil texture varies between the two grasslands and has been suggested as a major factor restricting creosote expansion along the transition. However, the affect of soil texture on creosote expansion has not been directly tested. The main research questions were: i) Can creosote germinate in blue grama grasslands? ii) Does grazing influence creosote germination in semiarid grasslands?
East-West C3-C4 Grassland Biomass Fertilizer Plots in a Chihuahuan Desert Grassland at the Sevilleta National Wildlife Refuge, New MexicoSubmitted by amswann on Thu, 12/08/2011 - 11:21am
This dataset contains weights of vegetation biomass collected in fertilizer plots from 1989 through 1992. The data were originally collected to analyze the effects of fertilization on vegetation productivity on the Sevilleta NWR.