ALBERT

Description: While nascent oceanic lithosphere at slow to fast spreading mid-ocean ridges (MOR) is relatively well studied, much less is known about the lithospheric structure and properties at ultraslow MORs. Here we present microearthquake data from a 1 year ocean bottom seismometer deployment at the amagmatic, oblique supersegment of the ultraslow spreading Southwest Indian Ridge. A refraction seismic experiment was performed to constrain upper lithosphere P-velocities and results were used to construct a 1D velocity model for earthquake location. Earthquake foci were located individually and subsequently relocated relative to each other to sharpen the image of seismically active structures. Frequent earthquake activity extends to 31 km beneath the seafloor, indicating an exceptionally thick brittle lithosphere and an undulating brittle-ductile transition that implies significant variations in the along-axis thermal structure of the lithosphere. We observe a strong relation between petrology, microseismicity distribution, and topography along the ridge axis: Peridotite-dominated areas associate with deepest hypocenters, vast volumes of lithosphere that deforms aseismically as a consequence of alteration, and the deepest axial rift valley. Areas of basalt exposure correspond to shallower hypocenters, shallower and more rugged axial seafloor. Focal mechanisms deviate from pure extension and are spatially variable. Earthquakes form an undulating band of background seismicity and do not delineate discrete detachment faults as common on slow spreading ridges. Instead, the seismicity band sharply terminates to the south, immediately beneath the rift boundary. Considering the deep alteration, large steep boundary faults might be present but are entirely aseismic.

Description: The concept of homogenous response units (HRU) was designed as a general concept for the delineation of basic spatial units. Only those characteristics of landscape, which are relatively stable over time (even under climate change) and largely unsusceptible to anthropogenic influence, were selected. The HRU can be seen as a basic spatial framework for the implementation of climate change and land management alternative scenarios into global modeling and therefore is a basic input for delineation of landscape units. HRUs are defined based on classifications of altitude (five classes: 1 (0 - 300m), 2 (300 - 600m), 3 (600 - 1100m), 4 (1100 - 2500m), 5 (〉 2500m)), slope (seven classes(degrees): 1 (0 - 3), 2 (3 - 6), 3 (6 - 10), 4 (10 - 15), 5 (15 - 30), 6 (30 - 50), 7 (〉 50)) and soil composition (five classes: 1 (sandy), 2 (loamy), 3 (clay), 4 (stony), 5 (peat)). e.g. HRU111 refers to Altitude class 1: 0-300m; Slope class 1: 0-3 degrees; and Soil class 1: sandy. Areas of non-soil are assigned 88. HRUs have a spatial resolution of approximately 10 km**2.

Description: The DTRF2014 is a realization of the the fundamental Earth-fixed coordinate system, the International Terrestrial Reference System (ITRS). It has been computed by the Deutsches Geodätisches Forschungsinstitut der Technischen Universität München (DGFI-TUM). The DTRF2014 consists of station positions and velocities of 1712 globally distributed geodetic observing stations of the observation techniques VLBI, SLR, GNSS and DORIS. Additionally, for the first time, non-tidal atmospheric and hydrological loading is considered in the solution. The DTRF2014 was released in August 2016 and incorporates observation data of the four techniques up 2014. The observation data were processed and submitted by the corresponding technique services: IGS (International GNSS Service, http://igscb.jpl.nasa.gov) IVS (International VLBI Service, http://ivscc.gsfc.nasa.gov) ILRS (International Laser Ranging Service, http://ilrs.gsfc.nasa.gov) IDS (International DORIS Service, http://ids-doris.org). The DTRF2014 is an independent ITRS realization. It is computed on the basis of the same input data as the realizations JTRF2014 (JPL, Pasadena) and ITRF2014 (IGN, Paris). The three realizations of the ITRS differ conceptually. While DTRF2014 and ITRF2014 are based on station positions at a reference epoch and velocities, the JTRF2014 is based on time series of station positions. DTRF2014 and ITRF2014 result from different combination strategies: The ITRF2014 is based on the combination of solutions, the DTRF2014 is computed by the combination of normal equations. The DTRF2014 comprises 3D coordinates and coordinate changes of 1347 GNSS-, 113 VLBI-, 99 SLR- and 153 DORIS-stations. The reference epoch is 1.1.2005, 0h UTC. The Earth Orientation Parameters (EOP) - that means the coordinates of the terrestrial and the celestial pole, UT1-UTC and the Length of Day (LOD) - were simultaneously estimated with the station coordinates. The EOP time series cover the period from 1979.7 to 2015.0. The station names are the official IERS identifiers: CDP numbers or 4-character IDs and DOMES numbers (http://itrf.ensg.ign.fr/doc_ITRF/iers_sta_list.txt). The DTRF2014 solution is available in one comprehensive SINEX file and four technique-specific SINEX files, see below. A detailed description of the solution is given on the website of DGFI-TUM (http://www.dgfi.tum.de/en/science-data-products/dtrf2014/). More information can be made available by request.

Description: This dataset includes earthquake location results from a seismological experiment including Ocean Bottom Seismometer (OBS) and land stations on the Cycladic islands in the southern Aegean.

Description: We provide a catalog of microseismicity recorded during a 32-days long deployment of ocean bottom seismometer (OBS) at the southern Fonualei Rift and Spreading Center in the Lau Basin, southwestern Pacific.

Description: Fog deposition, precipitation, throughfall and stemflow were measured in a windward tropical montane cloud forest near Monteverde, Costa Rica, for a 65-day period during the dry season of 2003. Net fog deposition was measured directly using the eddy covariance (EC) method and it amounted to 1.2 ± 0.1 mm/day (mean ± standard error). Fog water deposition was 5–9% of incident rainfall for the entire period, which is at the low end of previously reported values. Stable isotope concentrations (d18O and d2H) were determined in a large number of samples of each water component. Mass balance-based estimates of fog deposition were 1.0 ± 0.3 and 5.0 ± 2.7 mm/day (mean ± SE) when d18O and d2H were used as tracer, respectively. Comparisons between direct fog deposition measurements and the results of the mass balance model using d18O as a tracer indicated that the latter might be a good tool to estimate fog deposition in the absence of direct measurement under many (but not all) conditions. At 506 mm, measured water inputs over the 65 days (fog plus rain) fell short by 46 mm compared to the canopy output of 552 mm (throughfall, stemflow and interception evaporation). This discrepancy is attributed to the underestimation of rainfall during conditions of high wind.

Description: This data collection contains species-specific aboveground plant biomass that was collected from the Trait Based Experiment in 2012. (Sown plant species, Weed plant biomass, the biomass of dead plant material, and the biomass of unidentified plant material) per plots collected in 2012 from a grassland trait diversity experiment (the Jena Trait Based Experiment). The data collection also contains the traits of the species measured in their monoculture. The experiment consists of 20 plant species that were assigned to one of three species pools: 1. Species that vary along a gradient of spatial leaf and root trait similarity, 2. Species that vary along a gradient of phenological trait similarity and 3. Species that vary along a gradient of both spatial and phenological similarity (see Ebeling et al. 2014). The experiment consists of 138 grassland plots 3 x 3 m in size that was established within the Jena Experiment, Germany, in 2011. Plots vary in plant species richness (1, 2, 4, or 8 species) and functional diversity (1, 2, 3, 4 functional diversity levels, where 1 indicates species are most similar and 4 being most dissimilar in functional traits). Plots were maintained by manual weeding in March, July and September. Biomass was harvested twice in 2012 (during peak standing biomass in late May and in late August) on all experimental plots. Plots were mown to the same height directly following biomass harvest. Plant biomass was harvested by clipping the vegetation at 3 cm above ground in two 0.2 x 0.5 m quadrats per plot. The harvested biomass was sorted into categories: individual species of the sown plant species, 'Weed' plant species (species not sown in a plot), detached 'Dead' plant material, and remaining plant material that could not be assigned to any category ('Rest'). All biomass was dried to constant weight (70°C, 〉= 48 h) and weighed. The data from individual quadrats were averaged. The traits measured are: Flowering initiation, Flowering cessation, specific leaf area (SLA), leaf dry matter content (LDMC), leaf area, maximum canopy height, specific root length (SRL), mean rooting depth (MRD), root mass density (RMD) and root length density (RLD). Flowering initiation and cessation were measured respectively as the week in which flowering was first observed and flowering senesce had completed throughout the plot. Leaf area, leaf fresh mass were measured on approximately five fully expanded leaves from different individuals. These leaves were dried at 65°C for over 48 hours and massed to calculate the specific leaf area (SLA, area per dry mass), and the leaf dry matter content (LDMC, dry mass per fresh mass). Maximum canopy height was measured during peak biomass in May by taking the average of five measurements along a transect. Root traits were measured by taking soil cores, 4 cm in diameter and 40 cm deep and sectioned by depth: 0-5, 5-10, 10-20, 20-30 and 30-40 cm. Roots were washed and roots 〈 2 mm in diameter were stored in 70 % ethanol. Root length was determined by scanning stained roots with neutral red and scanning roots using WinRhizo software. Root traits were only measured in species pool 1 and 2. Roots were then dried at 65°C for over 48 hours and massed to determine the specific root length (SRL, root length per mass), mean rooting depth (MRD, the average depth weighed by root mass per depth), root mass density (RMD, the average root mass per cubic cm volume) and root length density (RLD, root mass per root length).

Description: This data set contains plant species traits: Flowering initiation, Flowering cessation, specific leaf area (SLA), leaf dry matter content (LDMC), leaf area, maximum canopy height, specific root length (SRL), mean rooting depth (MRD), root mass density (RMD) and root length density (RLD). The traits were measured during the summer of 2012 on the plants grown in monoculture within a grassland trait diversity experiment (the Jena Trait Based Experiment). The experiment consists of 20 plant species that were assigned to one of three species pools: 1. Species that vary along a gradient of spatial leaf and root trait similarity, 2. Species that vary along a gradient of phenological trait similarity and 3. Species that vary along a gradient of both spatial and phenological similarity (see Ebeling et al. 2014). The plots were 3 x 3 m in size and established within the Jena Experiment, Germany, in 2011. Plots were maintained by manual weeding in March, July and September. Traits were measured during the summer of 2012. Flowering initiation and cessation were measured respectively as the week in which flowering was first observed and flowering senesce had completed throughout the plot. Leaf area, leaf fresh mass were measured on approximately five fully expanded leaves from different individuals. These leaves were dried at 65 C for over 48 hours and massed to calculate the specific leaf area (SLA, area per dry mass), and the leaf dry matter content (LDMC, dry mass per fresh mass). Maximum canopy height was measured during peak biomass in May by taking the average of five measurements along a transect. Root traits were measured by taking soil cores, 4 cm in diameter and 40 cm deep and sectioned by depth: 0-5, 5-10, 10-20, 20-30 and 30-40 cm. Roots were washed and roots 〈 2 mm in diameter were stored in 70 % ethanol. Root length was determined by scanning stained roots with neutral red and scanning roots using WinRhizo software. Root traits were only measured in species pool 1 and 2. Roots were then dried at 65 C for over 48 hours and massed to determine the specific root length (SRL, root length per mass), mean rooting depth (MRD, the average depth weighed by root mass per depth), root mass density (RMD, the average root mass per cubic cm volume) and root length density (RLD, root mass per root length).