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1. Fungal Planet description sheets: 1284–1382

   https://doi.org/10.3767/persoonia.2021.47.06  

   Crous, P.W. ; Osieck, E.R. ; Jurjevi, Ž ; Boers, J. ; Van Iperen, A.L. ; Starink-Willemse, M. ; Dima, B. ; Balashov, S. ; Bulgakov, T.S. ; Johnston, P.R. ; et al ( December 2021 , Persoonia - Molecular Phylogeny and Evolution of Fungi)

   Novel species of fungi described in this study include those from various countries as follows: Antartica , Cladosporium austrolitorale from coastal sea sand. Australia , Austroboletus yourkae on soil, Crepidotus innuopurpureus on dead wood, Curvularia stenotaphri from roots and leaves of Stenotaphrum secundatum and Thecaphora stajsicii from capsules of Oxalis radicosa. Belgium , Paraxerochrysium coryli (incl. Paraxerochrysium gen. nov.) from Corylus avellana. Brazil , Calvatia nordestina on soil, Didymella tabebuiicola from leaf spots on Tabebuia aurea, Fusarium subflagellisporum from hypertrophied floral and vegetative branches of Mangifera indica and Microdochium maculosum from living leaves of Digitaria insularis. Canada , Cuphophyllus bondii fromagrassland. Croatia , Mollisia inferiseptata from a rotten Laurus nobilis trunk. Cyprus , Amanita exilis oncalcareoussoil. Czech Republic , Cytospora hippophaicola from wood of symptomatic Vaccinium corymbosum. Denmark , Lasiosphaeria deviata on pieces of wood and herbaceousdebris. Dominican Republic , Calocybella goethei among grass on a lawn. France (Corsica) , Inocybe corsica onwetground. France (French Guiana) , Trechispora patawaensis on decayed branch of unknown angiosperm tree and Trechispora subregularis on decayed log of unknown angiosperm tree. Germany , Paramicrothecium sambuci (incl. Paramicrothecium gen. nov.)ondeadstemsof Sambucus nigra. India , Aureobasidium microtermitis from the gut of a Microtermes sp. termite, Laccaria diospyricola on soil and Phylloporia tamilnadensis on branches of Catunaregam spinosa . Iran , Pythium serotinoosporum from soil under Prunus dulcis. Italy , Pluteus brunneovenosus on twigs of broad leaved trees on the ground. Japan , Heterophoma rehmanniae on leaves of Rehmannia glutinosa f. hueichingensis. Kazakhstan , Murispora kazachstanica from healthy roots of Triticum aestivum. Namibia , Caespitomonium euphorbiae (incl. Caespitomonium gen. nov.)from stems of an Euphorbia sp. Netherlands , Alfaria junci, Myrmecridium junci, Myrmecridium juncicola, Myrmecridium juncigenum, Ophioceras junci, Paradinemasporium junci (incl. Paradinemasporium gen. nov.), Phialoseptomonium junci, Sporidesmiella juncicola, Xenopyricularia junci and Zaanenomyces quadripartis (incl. Zaanenomyces gen. nov.), fromdeadculmsof Juncus effusus, Cylindromonium everniae and Rhodoveronaea everniae from Evernia prunastri, Cyphellophora sambuci and Myrmecridium sambuci from Sambucus nigra, Kiflimonium junci, Saro cladium junci, Zaanenomyces moderatricis academiae and Zaanenomyces versatilis from dead culms of Juncus inflexus, Microcera physciae from Physcia tenella, Myrmecridium dactylidis from dead culms of Dactylis glomerata, Neochalara spiraeae and Sporidesmium spiraeae from leaves of Spiraea japonica, Neofabraea salicina from Salix sp., Paradissoconium narthecii (incl. Paradissoconium gen. nov.)from dead leaves of Narthecium ossifragum, Polyscytalum vaccinii from Vaccinium myrtillus, Pseudosoloacrosporiella cryptomeriae (incl. Pseudosoloacrosporiella gen. nov.)fromleavesof Cryptomeria japonica, Ramularia pararhabdospora from Plantago lanceolata, Sporidesmiella pini from needles of Pinus sylvestris and Xenoacrodontium juglandis (incl. Xenoacrodontium gen. nov. and Xenoacrodontiaceae fam. nov.)from Juglans regia . New Zealand , Cryptometrion metrosideri from twigs of Metrosideros sp., Coccomyces pycnophyllocladi from dead leaves of Phyllocladus alpinus, Hypoderma aliforme from fallen leaves Fuscopora solandri and Hypoderma subiculatum from dead leaves Phormium tenax. Norway , Neodevriesia kalakoutskii from permafrost and Variabilispora viridis from driftwood of Picea abies. Portugal , Entomortierella hereditatis from abio film covering adeteriorated limestone wall. Russia , Colpoma junipericola from needles of Juniperus sabina, Entoloma cinnamomeum on soil in grasslands, Entoloma verae on soil in grasslands, Hyphodermella pallidostraminea on a dry dead branch of Actinidia sp., Lepiota sayanensis onlitterinamixedforest, Papiliotrema horticola from Malus communis , Paramacroventuria ribis (incl. Paramacroventuria gen. nov.)fromleaves of Ribes aureum and Paramyrothecium lathyri from leaves of Lathyrus tuberosus. South Africa , Harzia combreti from leaf litter of Combretum collinum ssp. sulvense, Penicillium xyleborini from Xyleborinus saxesenii , Phaeoisaria dalbergiae from bark of Dalbergia armata, Protocreopsis euphorbiae from leaf litter of Euphorbia ingens and Roigiella syzygii from twigs of Syzygium chordatum . Spain , Genea zamorana on sandy soil, Gymnopus nigrescens on Scleropodium touretii, Hesperomyces parexochomi on Parexochomus quadriplagiatus, Paraphoma variabilis from dung, Phaeococcomyces kinklidomatophilus from a blackened metal railing of an industrial warehouse and Tuber suaveolens in soil under Quercus faginea. Svalbard and Jan Mayen , Inocybe nivea associated with Salix polaris. Thailand , Biscogniauxia whalleyi oncorticatedwood. UK , Parasitella quercicola from Quercus robur. USA , Aspergillus arizonicus from indoor air in a hospital, Caeliomyces tampanus (incl. Caeliomyces gen. nov.)fromoffice dust, Cippumomyces mortalis (incl. Cippumomyces gen. nov.)fromatombstone, Cylindrium desperesense from air in a store, Tetracoccosporium pseudoaerium from air sample in house, Toxicocladosporium glendoranum from air in a brick room, Toxicocladosporium losalamitosense from air in a classroom, Valsonectria portsmouthensis from airinmen'slockerroomand Varicosporellopsis americana from sludge in a water reservoir. Vietnam , Entoloma kovalenkoi on rotten wood, Fusarium chuoi inside seed of Musa itinerans , Micropsalliota albofelina on soil in tropical evergreen mixed forest sand Phytophthora docyniae from soil and roots of Docynia indica. Morphological and culture characteristics are supported by DNA barcodes. 

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2. The spider tree of life: phylogeny of Araneae based on target‐gene analyses from an extensive taxon sampling

   https://doi.org/10.1111/cla.12182  

   Wheeler, Ward C. ; Coddington, Jonathan A. ; Crowley, Louise M. ; Dimitrov, Dimitar ; Goloboff, Pablo A. ; Griswold, Charles E. ; Hormiga, Gustavo ; Prendini, Lorenzo ; Ramírez, Martín J. ; Sierwald, Petra ; et al ( December 2016 , Cladistics)

   We present a phylogenetic analysis of spiders using a dataset of 932 spider species, representing 115 families (only the family Synaphridae is unrepresented), 700 known genera, and additional representatives of 26 unidentified or undescribed genera. Eleven genera of the orders Amblypygi, Palpigradi, Schizomida and Uropygi are included as outgroups. The dataset includes six markers from the mitochondrial (12S, 16S,COI) and nuclear (histone H3, 18S, 28S) genomes, and was analysed by multiple methods, including constrained analyses using a highly supported backbone tree from transcriptomic data. We recover most of the higher‐level structure of the spider tree with good support, including Mesothelae, Opisthothelae, Mygalomorphae and Araneomorphae. Several of our analyses recover Hypochilidae and Filistatidae as sister groups, as suggested by previous transcriptomic analyses. The Synspermiata are robustly supported, and the families Trogloraptoridae and Caponiidae are found as sister to the Dysderoidea. Our results support the Lost Tracheae clade, including Pholcidae, Tetrablemmidae, Diguetidae, Plectreuridae and the family Pacullidae (restored status) separate from Tetrablemmidae. The Scytodoidea include Ochyroceratidae along with Sicariidae, Scytodidae, Drymusidae and Periegopidae; our results are inconclusive about the separation of these last two families. We did not recover monophyletic Austrochiloidea and Leptonetidae, but our data suggest that both groups are more closely related to the Cylindrical Gland Spigot clade rather than to Synspermiata. Palpimanoidea is not recovered by our analyses, but also not strongly contradicted. We find support for Entelegynae and Oecobioidea (Oecobiidae plus Hersiliidae), and ambiguous placement of cribellate orb‐weavers, compatible with their non‐monophyly. Nicodamoidea (Nicodamidae plus Megadictynidae) and Araneoidea composition and relationships are consistent with recent analyses. We did not obtain resolution for the titanoecoids (Titanoecidae and Phyxelididae), but the Retrolateral Tibial Apophysis clade is well supported. Penestomidae, and probably Homalonychidae, are part of Zodarioidea, although the latter family was set apart by recent transcriptomic analyses. Our data support a large group that we call the marronoid clade (including the families Amaurobiidae, Desidae, Dictynidae, Hahniidae, Stiphidiidae, Agelenidae and Toxopidae). The circumscription of most marronoid families is redefined here. Amaurobiidae include the Amaurobiinae and provisionally Macrobuninae. We transfer Malenellinae (Malenella, from Anyphaenidae), Chummidae (Chumma) (new syn.) and Tasmarubriinae (Tasmarubrius,TasmabrochusandTeeatta, from Amphinectidae) to Macrobuninae. Cybaeidae are redefined to includeCalymmaria,Cryphoeca,EthobuellaandWillisius(transferred from Hahniidae), andBlabommaandYorima(transferred from Dictynidae). Cycloctenidae are redefined to includeOrepukia(transferred from Agelenidae) andPakehaandParavoca(transferred from Amaurobiidae). Desidae are redefined to include five subfamilies: Amphinectinae, withAmphinecta,Mamoea,Maniho,ParamamoeaandRangitata(transferred from Amphinectidae); Ischaleinae, withBakalaandManjala(transferred from Amaurobiidae) andIschalea(transferred from Stiphidiidae); Metaltellinae, withAustmusia,Buyina,Calacadia,Cunnawarra,Jalkaraburra,Keera,Magua,Metaltella,PenaoolaandQuemusia; Porteriinae (new rank), withBaiami,Cambridgea,CorasoidesandNanocambridgea(transferred from Stiphidiidae); and Desinae, withDesis, and provisionallyPoaka(transferred from Amaurobiidae) andBarahna(transferred from Stiphidiidae).Argyronetais transferred from Cybaeidae to Dictynidae.Cicurinais transferred from Dictynidae to Hahniidae. The generaNeoramia(from Agelenidae) andAorangia,MarplesiaandNeolana(from Amphinectidae) are transferred to Stiphidiidae. The family Toxopidae (restored status) includes two subfamilies: Myroinae, withGasparia,Gohia,Hulua,Neomyro,Myro,OmmatauxesisandOtagoa(transferred from Desidae); and Toxopinae, withMidgeeandJamara, formerly Midgeeinae,new syn.(transferred from Amaurobiidae) andHapona,Laestrygones,Lamina,ToxopsandToxopsoides(transferred from Desidae). We obtain a monophyletic Oval Calamistrum clade and Dionycha; Sparassidae, however, are not dionychans, but probably the sister group of those two clades. The composition of the Oval Calamistrum clade is confirmed (including Zoropsidae, Udubidae, Ctenidae, Oxyopidae, Senoculidae, Pisauridae, Trechaleidae, Lycosidae, Psechridae and Thomisidae), affirming previous findings on the uncertain relationships of the “ctenids”AncylometesandCupiennius, although a core group of Ctenidae are well supported. Our data were ambiguous as to the monophyly of Oxyopidae. In Dionycha, we found a first split of core Prodidomidae, excluding the Australian Molycriinae, which fall distantly from core prodidomids, among gnaphosoids. The rest of the dionychans form two main groups, Dionycha part A and part B. The former includes much of the Oblique Median Tapetum clade (Trochanteriidae, Gnaphosidae, Gallieniellidae, Phrurolithidae, Trachelidae, Gnaphosidae, Ammoxenidae, Lamponidae and the Molycriinae), and also Anyphaenidae and Clubionidae.Orthobulais transferred from Phrurolithidae to Trachelidae. Our data did not allow for complete resolution for the gnaphosoid families. Dionycha part B includes the families Salticidae, Eutichuridae, Miturgidae, Philodromidae, Viridasiidae, Selenopidae, Corinnidae and Xenoctenidae(new fam., includingXenoctenus,ParavulsorandOdo, transferred from Miturgidae, as well asIncasoctenusfrom Ctenidae). We confirm the inclusion ofZora(formerly Zoridae) within Miturgidae.

    

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3. Phosphorus availability and leaching losses in annual and perennial cropping systems in an upper US Midwest landscape

   https://doi.org/10.5061/dryad.8sf7m0cpx  

   Hussain, Mir Zaman ; Hamilton, Stephen ; Robertson, G. Philip ; Basso, Bruno ( January 2021 , Dryad)

   Excessive phosphorus (P) applications to croplands can contribute to eutrophication of surface waters through surface runoff and subsurface (leaching) losses. We analyzed leaching losses of total dissolved P (TDP) from no-till corn, hybrid poplar (Populus nigra X P. maximowiczii), switchgrass (Panicum virgatum), miscanthus (Miscanthus giganteus), native grasses, and restored prairie, all planted in 2008 on former cropland in Michigan, USA. All crops except corn (13 kg P ha−1 year−1) were grown without P fertilization. Biomass was harvested at the end of each growing season except for poplar. Soil water at 1.2 m depth was sampled weekly to biweekly for TDP determination during March–November 2009–2016 using tension lysimeters. Soil test P (0–25 cm depth) was measured every autumn. Soil water TDP concentrations were usually below levels where eutrophication of surface waters is frequently observed (> 0.02 mg L−1) but often higher than in deep groundwater or nearby streams and lakes. Rates of P leaching, estimated from measured concentrations and modeled drainage, did not differ statistically among cropping systems across years; 7-year cropping system means ranged from 0.035 to 0.072 kg P ha−1 year−1 with large interannual variation. Leached P was positively related to STP, which decreased over the 7 years in all systems. These results indicate that both P-fertilized and unfertilized cropping systems may leach legacy P from past cropland management. Experimental details The Biofuel Cropping System Experiment (BCSE) is located at the W.K. Kellogg Biological Station (KBS) (42.3956° N, 85.3749° W; elevation 288 m asl) in southwestern Michigan, USA. This site is a part of the Great Lakes Bioenergy Research Center (www.glbrc.org) and is a Long-term Ecological Research site (www.lter.kbs.msu.edu). Soils are mesic Typic Hapludalfs developed on glacial outwash54 with high sand content (76% in the upper 150 cm) intermixed with silt-rich loess in the upper 50 cm55. The water table lies approximately 12–14 m below the surface. The climate is humid temperate with a mean annual air temperature of 9.1 °C and annual precipitation of 1005 mm, 511 mm of which falls between May and September (1981–2010)56,57. The BCSE was established as a randomized complete block design in 2008 on preexisting farmland. Prior to BCSE establishment, the field was used for grain crop and alfalfa (Medicago sativa L.) production for several decades. Between 2003 and 2007, the field received a total of ~ 300 kg P ha−1 as manure, and the southern half, which contains one of four replicate plots, received an additional 206 kg P ha−1 as inorganic fertilizer. The experimental design consists of five randomized blocks each containing one replicate plot (28 by 40 m) of 10 cropping systems (treatments) (Supplementary Fig. S1; also see Sanford et al.58). Block 5 is not included in the present study. Details on experimental design and site history are provided in Robertson and Hamilton57 and Gelfand et al.59. Leaching of P is analyzed in six of the cropping systems: (i) continuous no-till corn, (ii) switchgrass, (iii) miscanthus, (iv) a mixture of five species of native grasses, (v) a restored native prairie containing 18 plant species (Supplementary Table S1), and (vi) hybrid poplar. Agronomic management Phenological cameras and field observations indicated that the perennial herbaceous crops emerged each year between mid-April and mid-May. Corn was planted each year in early May. Herbaceous crops were harvested at the end of each growing season with the timing depending on weather: between October and November for corn and between November and December for herbaceous perennial crops. Corn stover was harvested shortly after corn grain, leaving approximately 10 cm height of stubble above the ground. The poplar was harvested only once, as the culmination of a 6-year rotation, in the winter of 2013–2014. Leaf emergence and senescence based on daily phenological images indicated the beginning and end of the poplar growing season, respectively, in each year. Application of inorganic fertilizers to the different crops followed a management approach typical for the region (Table 1). Corn was fertilized with 13 kg P ha−1 year−1 as starter fertilizer (N-P-K of 19-17-0) at the time of planting and an additional 33 kg P ha−1 year−1 was added as superphosphate in spring 2015. Corn also received N fertilizer around the time of planting and in mid-June at typical rates for the region (Table 1). No P fertilizer was applied to the perennial grassland or poplar systems (Table 1). All perennial grasses (except restored prairie) were provided 56 kg N ha−1 year−1 of N fertilizer in early summer between 2010 and 2016; an additional 77 kg N ha−1 was applied to miscanthus in 2009. Poplar was fertilized once with 157 kg N ha−1 in 2010 after the canopy had closed. Sampling of subsurface soil water and soil for P determination Subsurface soil water samples were collected beneath the root zone (1.2 m depth) using samplers installed at approximately 20 cm into the unconsolidated sand of 2Bt2 and 2E/Bt horizons (soils at the site are described in Crum and Collins54). Soil water was collected from two kinds of samplers: Prenart samplers constructed of Teflon and silica (http://www.prenart.dk/soil-water-samplers/) in replicate blocks 1 and 2 and Eijkelkamp ceramic samplers (http://www.eijkelkamp.com) in blocks 3 and 4 (Supplementary Fig. S1). The samplers were installed in 2008 at an angle using a hydraulic corer, with the sampling tubes buried underground within the plots and the sampler located about 9 m from the plot edge. There were no consistent differences in TDP concentrations between the two sampler types. Beginning in the 2009 growing season, subsurface soil water was sampled at weekly to biweekly intervals during non-frozen periods (April–November) by applying 50 kPa of vacuum to each sampler for 24 h, during which the extracted water was collected in glass bottles. Samples were filtered using different filter types (all 0.45 µm pore size) depending on the volume of leachate collected: 33-mm dia. cellulose acetate membrane filters when volumes were less than 50 mL; and 47-mm dia. Supor 450 polyethersulfone membrane filters for larger volumes. Total dissolved phosphorus (TDP) in water samples was analyzed by persulfate digestion of filtered samples to convert all phosphorus forms to soluble reactive phosphorus, followed by colorimetric analysis by long-pathlength spectrophotometry (UV-1800 Shimadzu, Japan) using the molybdate blue method60, for which the method detection limit was ~ 0.005 mg P L−1. Between 2009 and 2016, soil samples (0–25 cm depth) were collected each autumn from all plots for determination of soil test P (STP) by the Bray-1 method61, using as an extractant a dilute hydrochloric acid and ammonium fluoride solution, as is recommended for neutral to slightly acidic soils. The measured STP concentration in mg P kg−1 was converted to kg P ha−1 based on soil sampling depth and soil bulk density (mean, 1.5 g cm−3). Sampling of water samples from lakes, streams and wells for P determination In addition to chemistry of soil and subsurface soil water in the BCSE, waters from lakes, streams, and residential water supply wells were also sampled during 2009–2016 for TDP analysis using Supor 450 membrane filters and the same analytical method as for soil water. These water bodies are within 15 km of the study site, within a landscape mosaic of row crops, grasslands, deciduous forest, and wetlands, with some residential development (Supplementary Fig. S2, Supplementary Table S2). Details of land use and cover change in the vicinity of KBS are given in Hamilton et al.48, and patterns in nutrient concentrations in local surface waters are further discussed in Hamilton62. Leaching estimates, modeled drainage, and data analysis Leaching was estimated at daily time steps and summarized as total leaching on a crop-year basis, defined from the date of planting or leaf emergence in a given year to the day prior to planting or emergence in the following year. TDP concentrations (mg L−1) of subsurface soil water were linearly interpolated between sampling dates during non-freezing periods (April–November) and over non-sampling periods (December–March) based on the preceding November and subsequent April samples. Daily rates of TDP leaching (kg ha−1) were calculated by multiplying concentration (mg L−1) by drainage rates (m3 ha−1 day−1) modeled by the Systems Approach for Land Use Sustainability (SALUS) model, a crop growth model that is well calibrated for KBS soil and environmental conditions. SALUS simulates yield and environmental outcomes in response to weather, soil, management (planting dates, plant population, irrigation, N fertilizer application, and tillage), and genetics63. The SALUS water balance sub-model simulates surface runoff, saturated and unsaturated water flow, drainage, root water uptake, and evapotranspiration during growing and non-growing seasons63. The SALUS model has been used in studies of evapotranspiration48,51,64 and nutrient leaching20,65,66,67 from KBS soils, and its predictions of growing-season evapotranspiration are consistent with independent measurements based on growing-season soil water drawdown53 and evapotranspiration measured by eddy covariance68. Phosphorus leaching was assumed insignificant on days when SALUS predicted no drainage. Volume-weighted mean TDP concentrations in leachate for each crop-year and for the entire 7-year study period were calculated as the total dissolved P leaching flux (kg ha−1) divided by the total drainage (m3 ha−1). One-way ANOVA with time (crop-year) as the fixed factor was conducted to compare total annual drainage rates, P leaching rates, volume-weighted mean TDP concentrations, and maximum aboveground biomass among the cropping systems over all seven crop-years as well as with TDP concentrations from local lakes, streams, and groundwater wells. When a significant (α = 0.05) difference was detected among the groups, we used the Tukey honest significant difference (HSD) post-hoc test to make pairwise comparisons among the groups. In the case of maximum aboveground biomass, we used the Tukey–Kramer method to make pairwise comparisons among the groups because the absence of poplar data after the 2013 harvest resulted in unequal sample sizes. We also used the Tukey–Kramer method to compare the frequency distributions of TDP concentrations in all of the soil leachate samples with concentrations in lakes, streams, and groundwater wells, since each sample category had very different numbers of measurements. Individual spreadsheets in “data table_leaching_dissolved organic carbon and nitrogen.xls” 1.    annual precip_drainage 2.    biomass_corn, perennial grasses 3.    biomass_poplar 4.    annual N leaching _vol-wtd conc 5.    Summary_N leached 6.    annual DOC leachin_vol-wtd conc 7.    growing season length 8.    correlation_nh4 VS no3 9.    correlations_don VS no3_doc VS don Each spreadsheet is described below along with an explanation of variates. Note that ‘nan’ indicate data are missing or not available. First row indicates header; second row indicates units 1. Spreadsheet: annual precip_drainage Description: Precipitation measured from nearby Kellogg Biological Station (KBS) Long Term Ecological Research (LTER) Weather station, over 2009-2016 study period. Data shown in Figure 1; original data source for precipitation (https://lter.kbs.msu.edu/datatables/7). Drainage estimated from SALUS crop model. Note that drainage is percolation out of the root zone (0-125 cm). Annual precipitation and drainage values shown here are calculated for growing and non-growing crop periods. Variate    Description year    year of the observation crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” precip_G    precipitation during growing period (milliMeter) precip_NG    precipitation during non-growing period (milliMeter) drainage_G    drainage during growing period (milliMeter) drainage_NG    drainage during non-growing period (milliMeter)      2. Spreadsheet: biomass_corn, perennial grasses Description: Maximum aboveground biomass measurements from corn, switchgrass, miscanthus, native grass and restored prairie plots in Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2009-2015. Data shown in Figure 2.   Variate    Description year    year of the observation date    day of the observation (mm/dd/yyyy) crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” replicate    each crop has four replicated plots, R1, R2, R3 and R4 station    stations (S1, S2 and S3) of samplings within the plot. For more details, refer to link (https://data.sustainability.glbrc.org/protocols/156) species    plant species that are rooted within the quadrat during the time of maximum biomass harvest. See protocol for more information, refer to link (http://lter.kbs.msu.edu/datatables/36) For maize biomass, grain and whole biomass reported in the paper (weed biomass or surface litter are excluded). Surface litter biomass not included in any crops; weed biomass not included in switchgrass and miscanthus, but included in grass mixture and prairie. fraction    Fraction of biomass biomass_plot    biomass per plot on dry-weight basis (Grams_Per_SquareMeter) biomass_ha    biomass (megaGrams_Per_Hectare) by multiplying column biomass per plot with 0.01 3. Spreadsheet: biomass_poplar Description: Maximum aboveground biomass measurements from poplar plots in Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2009-2015. Data shown in Figure 2. Note that poplar biomass was estimated from crop growth curves until the poplar was harvested in the winter of 2013-14. Variate    Description year    year of the observation method    methods of poplar biomass sampling date    day of the observation (mm/dd/yyyy) replicate    each crop has four replicated plots, R1, R2, R3 and R4 diameter_at_ground    poplar diameter (milliMeter) at the ground diameter_at_15cm    poplar diameter (milliMeter) at 15 cm height biomass_tree    biomass per plot (Grams_Per_Tree) biomass_ha    biomass (megaGrams_Per_Hectare) by multiplying biomass per tree with 0.01 4. Spreadsheet: annual N leaching_vol-wtd conc Description: Annual leaching rate (kiloGrams_N_Per_Hectare) and volume-weighted mean N concentrations (milliGrams_N_Per_Liter) of nitrate (no3) and dissolved organic nitrogen (don) in the leachate samples collected from corn, switchgrass, miscanthus, native grass, restored prairie and poplar plots in Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2009-2016. Data for nitrogen leached and volume-wtd mean N concentration shown in Figure 3a and Figure 3b, respectively. Note that ammonium (nh4) concentration were much lower and often undetectable (<0.07 milliGrams_N_Per_Liter). Also note that in 2009 and 2010 crop-years, data from some replicates are missing.    Variate    Description crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” crop-year    year of the observation replicate    each crop has four replicated plots, R1, R2, R3 and R4 no3 leached    annual leaching rates of nitrate (kiloGrams_N_Per_Hectare) don leached    annual leaching rates of don (kiloGrams_N_Per_Hectare) vol-wtd no3 conc.    Volume-weighted mean no3 concentration (milliGrams_N_Per_Liter) vol-wtd don conc.    Volume-weighted mean don concentration (milliGrams_N_Per_Liter) 5. Spreadsheet: summary_N leached Description: Summary of total amount and forms of N leached (kiloGrams_N_Per_Hectare) and the percent of applied N lost to leaching over the seven years for corn, switchgrass, miscanthus, native grass, restored prairie and poplar plots in Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2009-2016. Data for nitrogen amount leached shown in Figure 4a and percent of applied N lost shown in Figure 4b. Note the fraction of unleached N includes in harvest, accumulation in root biomass, soil organic matter or gaseous N emissions were not measured in the study. Variate    Description crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” no3 leached    annual leaching rates of nitrate (kiloGrams_N_Per_Hectare) don leached    annual leaching rates of don (kiloGrams_N_Per_Hectare) N unleached    N unleached (kiloGrams_N_Per_Hectare) in other sources are not studied % of N applied N lost to leaching    % of N applied N lost to leaching 6. Spreadsheet: annual DOC leachin_vol-wtd conc Description: Annual leaching rate (kiloGrams_Per_Hectare) and volume-weighted mean N concentrations (milliGrams_Per_Liter) of dissolved organic carbon (DOC) in the leachate samples collected from corn, switchgrass, miscanthus, native grass, restored prairie and poplar plots in Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2009-2016. Data for DOC leached and volume-wtd mean DOC concentration shown in Figure 5a and Figure 5b, respectively. Note that in 2009 and 2010 crop-years, water samples were not available for DOC measurements.     Variate    Description crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” crop-year    year of the observation replicate    each crop has four replicated plots, R1, R2, R3 and R4 doc leached    annual leaching rates of nitrate (kiloGrams_Per_Hectare) vol-wtd doc conc.    volume-weighted mean doc concentration (milliGrams_Per_Liter) 7. Spreadsheet: growing season length Description: Growing season length (days) of corn, switchgrass, miscanthus, native grass, restored prairie and poplar plots in the Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2009-2015. Date shown in Figure S2. Note that growing season is from the date of planting or emergence to the date of harvest (or leaf senescence in case of poplar).   Variate    Description crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” year    year of the observation growing season length    growing season length (days) 8. Spreadsheet: correlation_nh4 VS no3 Description: Correlation of ammonium (nh4+) and nitrate (no3-) concentrations (milliGrams_N_Per_Liter) in the leachate samples from corn, switchgrass, miscanthus, native grass, restored prairie and poplar plots in Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2013-2015. Data shown in Figure S3. Note that nh4+ concentration in the leachates was very low compared to no3- and don concentration and often undetectable in three crop-years (2013-2015) when measurements are available. Variate    Description crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” date    date of the observation (mm/dd/yyyy) replicate    each crop has four replicated plots, R1, R2, R3 and R4 nh4 conc    nh4 concentration (milliGrams_N_Per_Liter) no3 conc    no3 concentration (milliGrams_N_Per_Liter)   9. Spreadsheet: correlations_don VS no3_doc VS don Description: Correlations of don and nitrate concentrations (milliGrams_N_Per_Liter); and doc (milliGrams_Per_Liter) and don concentrations (milliGrams_N_Per_Liter) in the leachate samples of corn, switchgrass, miscanthus, native grass, restored prairie and poplar plots in Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2013-2015. Data of correlation of don and nitrate concentrations shown in Figure S4 a and doc and don concentrations shown in Figure S4 b. Variate    Description crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” year    year of the observation don    don concentration (milliGrams_N_Per_Liter) no3     no3 concentration (milliGrams_N_Per_Liter) doc    doc concentration (milliGrams_Per_Liter) 

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4. Triple Oxygen (δ18O, Δ17O), Hydrogen (δ2H), and Iron (δ56Fe) Stable Isotope Signatures Indicate a Silicate Magma Source and Magmatic-Hydrothermal Genesis for Magnetite Orebodies at El Laco, Chile

   https://doi.org/10.5382/econgeo.4760  

   Childress, T. ( November 2020 , Economic geology)

   null (Ed.)

   The Plio-Pleistocene El Laco iron oxide-apatite (IOA) orebodies in northern Chile are some of the most enigmatic mineral deposits on Earth, interpreted to have formed as lava flows or by hydrothermal replacement, two radically different processes. Field observations provide some support for both processes, but ultimately fail to explain all observations. Previously proposed genetic models based on observations and study of outcrop samples include (1) magnetite crystallization from an erupting immiscible Fe- and P-rich (Si-poor) melt and (2) metasomatic replacement of andesitic lava flows by a hypogene hydrothermal fluid. A more recent investigation of outcrop and drill core samples at El Laco generated data that were used to develop a new genetic model that invokes shallow emplacement and surface venting of a magnetite-bearing magmatic-hydrothermal fluid suspension. This fluid, with rheological properties similar to basaltic lava, would have been mobilized by decompression- induced collapse of the volcanic edifice. In this study, we report oxygen, including 17O, hydrogen, and iron stable isotope ratios in magnetite and bulk iron oxide (magnetite with minor secondary hematite and minor goethite) from five of seven orebodies around the El Laco volcano, excluding San Vicente Bajo and the minor Laquito deposits. Calculated values of δ18O, Δ17O, δD, and δ56Fe fingerprint the source of the ore-forming fluid(s): Δ17Osample = δ17Osample – δ18Osample * 0.5305. Magnetite and bulk iron oxide (magnetite variably altered to goethite and hematite) from Laco Sur, Cristales Grandes, and San Vicente Alto yield δ18O values that range from 4.3 to 4.5‰ (n = 5), 3.0 to 3.9‰ (n = 5), and –8.5 to –0.5‰ (n = 5), respectively. Magnetite samples from Rodados Negros are the least altered samples and were also analyzed for 17O as well as conventional 16O and 18O, yielding calculated δ18O values that range from 2.6 to 3.8‰ (n = 9) and Δ17O values that range from –0.13 to –0.07‰ (n = 5). Bulk iron oxide from Laco Norte yielded δ18O values that range from –10.2 to +4.5‰ (avg = 0.8‰, n = 18). The δ2H values of magnetite and bulk iron oxide from all five orebodies range from –192.8 to –79.9‰ (n = 28); hydrogen is present in fluid inclusions in magnetite and iron oxide, and in minor goethite. Values of δ56Fe for magnetite and bulk iron oxide from all five orebodies range from 0.04 to 0.70‰ (avg = 0.29‰, σ = 0.15‰, n = 26). The iron and oxygen isotope data are consistent with a silicate magma source for iron and oxygen in magnetite from all sampled El Laco orebodies. Oxygen (δ18O Δ +4.4 to –10.2‰) and hydrogen (δ 2H ≃ –79.9 to –192.8‰) stable isotope data for bulk iron oxide samples that contain minor goethite from Laco Norte and San Vicente Alto reveal that magnetite has been variably altered to meteoric values, consistent with goethite in equilibrium with local δ18O and δ2H meteoric values of ≃ –15.4 and –211‰, respectively. The H2O contents of iron oxide samples from Laco Norte and San Vicente Alto systematically increase with increasing abundance of goethite and decreasing values of δ18O and δ2H. The values of δ2H (≃ –88 to –140‰) and δ18O (3.0–4.5‰) for magnetite samples from Cristales Grandes, Laco Sur, and Rodados Negros are consistent with growth of magnetite from a degassing silicate melt and/or a boiling magmatic-hydrothermal fluid; the latter is also consistent with δ18O values for quartz, and salinities and homogenization temperatures for fluid inclusions trapped in apatite and clinopyroxene coeval with magnetite. The sum of the data unequivocally fingerprint a silicate magma as the source of the ore fluids responsible for mineralization at El Laco and are consistent with a model that explains mineralization as the synergistic result of common magmatic and magmatic-hydrothermal processes during the evolution of a caldera-related explosive volcanic system. 

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5. Rhizobiome of ‘Ōhi‘a Lehua (Metrosideros polymorpha) Offers Insight into Plant-Microbe-Invertebrate Interactions in the Subsurface

   https://doi.org/10.3897/aca.6.e108263  

   Engel, Annette ; Steck, Mireille ; Paterson, Audrey ; Van Gieson, Amir ; Porter, Megan ; Chong, Rebecca ( October 2023 , ARPHA Conference Abstracts)

   Chi Fru, Ernest ; Chik, Alex ; Colwell, Fredrick ; Dittrich, Maria ; Engel, Annette ; Keenan, Sarah ; Meckenstock, Rainer ; Omelon, Christopher ; Purkamo, Lotta ; Weisener, Chris (Ed.)

   Roots are common features in basaltic lava tube caves on the island of Hawai‘i. For the past 50 years, new species of cave-adapted invertebrates, including cixiid planthoppers, crickets, thread-legged bugs, and spiders, have been discovered from root patches in lava tubes on different volcanoes and across variable climatic conditions. Assessing vegetation on the surface above lava tube passages, as well as genetic characterization of roots from within lava tubes, suggest that most roots belong to the native pioneer tree, ‘ōhi‘a lehua (Metrosideros polymorpha). Planthoppers are the primary consumers of sap at the base of the subsurface food web. However, root physicochemistry and rhizobiome microbial diversity and functional potential have received little attention. This study focuses on characterizing the ‘ōhi‘a rhizobiome, accessed from free-hanging roots inside lava tubes. Using these results, we can begin to evaluate the development and evolution of plant-microbe-invertebrate relationships.

   We explored lava tubes formed in flows of differing elevations and ages, from about 140 to 3000 years old, on Mauna Loa, Kīlauea, and Hualālai volcanoes on Hawai‘i Island. Invertebrate diversity was evaluated from root galleries and non-root galleries, in situ fluid physicochemistry was measured, and root and bare rock fluids (e.g., water, sap) were collected to determine major ion concentrations, as well as non-purgeable organic carbon (NPOC) and total nitrogen (TN) content. To verify root identity, DNA was extracted, and three sets of primers were used. After screening for onlyMetrosiderosspp., the V4 region of the 16S rRNA gene was sequenced and taxonomy was assigned.

   Root fluids were viscous and ranged in color from clear to yellow to reddish orange. Root fluids had 2X to 10X higher major ion concentrations compared to rock water. The average root NPOC and TN concentrations were 192 mg/L and 5.2 mg/L, respectively, compared to rock water that had concentrations of 6.8 mg/L and 1.8 mg/L, respectively. Fluids from almost 300 root samples had pH values that ranged from 2.2 to 5.6 (average pH 4.63) and were lower than rock water (average pH 6.39). Root fluid pH was comparable to soil pH from montane wet forests dominated by ‘ōhi‘a (Selmants et al. 2016), which can grow in infertile soil with pH values as low as 3.6. On Hawai‘i, rain water pH averages 5.2 at sea level and systematically decreases with elevation to pH 4.3 at 2500 m (Miller and Yoshinaga 2012), but root fluid pH did not correlate with elevation, temperature, relative humidity, inorganic and organic constituents, or age of flow. Root fluid acidity is likely due to concentrated organic compounds, sourced as root exudates, and this habitat is acidic for the associated invertebrates.

   From 62 root samples, over 66% were identified to the genusMetrosideros. A few other identifications of roots from lava tube systems where there had been extensive clear-cutting and ranching included monkey pod tree, coconut palm,Ficusspp., and silky oak.

   The 16S rRNA gene sequence surveys revealed that root bacterial communities were dominated by few groups, including Burkholderiaceae, as well as Acetobacteraceae, Sphingomonadaceae, Acidobacteriaceae, Gemmataceae, Xanthobacteraceae, and Chitinophagaceae. However, most of the reads could not be classified to a specific genus, which suggested that the rhizobiome harbor novel diversity. Diversity was higher from wetter climates. The root communities were distinct from those described previously from ‘ōhi‘a flowers and leaves (Junker and Keller 2015) and lava tube rocky surfaces (Hathaway et al. 2014) where microbial groups were specifically presumed capable of heterotrophy, methanotrophy, diazotrophy, and nitrification. Less can be inferred for the rhizobiome metabolism, although most taxa are likely aerobic heterotrophs. Within the Burkholderiaceae, there were high relative abundances of sequences affiliated with the genusParaburkholderia, which includes known plant symbionts, as well as the acidophilic generaAcidocellaandAcidisomafrom the Acetobacteraceae, which were retrieved predominately from caves in the oldest lava flows that also had the lowest root pH values. It is likely that the bacterial groups are capable of degrading exudates and providing nutritional substrates for invertebrate consumers that are not provided by root fluids (i.e., phloem) alone.

   As details about the biochemistry of ‘ōhi‘a have been missing, characterizing the rhizobiome from lava tubes will help to better understand potential plant-microbe-invertebrate interactions and ecological and evolutionary relationships through time. In particular, the microbial rhizobiome may produce compounds used by invertebrates nutritionally or that affect their behavior, and changes to the rhizobiome in response to environmental conditions may influence invertebrate interactions with the roots, which could be important to combat climate change effects or invasive species introductions.

    

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