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Tree Map for Census at the Luquillo Forest Dynamics Plot (LFDP), Puerto Rico
This data set shows the Tag number, Quadrat location, Species code, diameter and XY coordinates of stems >=10 cm D130 present at the time of Hurricane Hugo and in the first census. The data set is composed of two files both with the same file structure. In LFDP_C1treemap.txt the diameters (Fdiam) are as recorded in the field data. In LFDP_C1TREEMAPa.txt the stem diameters (Fdiam) were calculated to allocate "missed" stems (stems >=10 cm D130) that were found in survey 2, 3 or Census 2 to Census 1 survey 1. We calculated the diameter the stem would have had, if it had been recorded at the same time the quadrat it was located in was assessed, in the appropriate survey for that stem size. To extrapolate the stem size back in time, we used the actual growth rate of that individual stem if more than one measurement was available. If only one diameter measurement was available we used the median growth rate for that species in the appropriate size class stems >=10, <30 cm D130). In our publications we will combine data sets LFDP_C1treemap.txt and LFDP_C1TREEMAPa.txt to make Census 1 and to reconstruct the forest for stems >= 10 cm D130 at the time of Hurricane Hugo. We have divided the data into two separate files to ensure that when stem diameters are compared to future censuses the diameter data in LFDP_C1TREEMAPa.txt are not used to calculate growth rates. The last corrections to the Census 1 data were made in May 2001. The National Science Foundation requires that data from projects it funds are posted on the web two years after any data set has been organized and "cleaned". The data from each census of the LFDP will be updated at intervals as each survey of the LFDP shows errors in the previous data collection. After posting on the web, researchers who are not part of the project are then welcome to use the data. Given the enormous amount of time, effort and resources required to manage the LFDP, obtain these data, and ensure data accuracy, LFDP Princi
Canopy height profile starting 1992, 1994 and 1996 of the Luquillo Forest Dynamics Plot (LFDP), Puerto Rico
File LFDP_canopy contain the canopy heights for the Luquillo forest Dynamics plot. The first measurement started in 1992, and it was planned to measure the canopy height profile every 2 years. So far censuses starting in 1992, 1994, and 1996 have been completed. In the 1992 census the canopy height profile at points along the East and North limits of the plot were not included. In 1994 and 1996 these extra points were assessed. The National Science Foundation requires that data from projects it funds are posted on the web two years after any data set has been organized and "cleaned". The data from each census of the LFDP will be updated at intervals as each survey of the LFDP shows errors in the previous data collection. After posting on the web, researchers who are not part of the project are then welcome to use the data. Given the enormous amount of time, effort and resources required to manage the LFDP, obtain these data, and ensure data accuracy, LFDP Principal Investigators request that researchers intending to use this data comply with the requests below. Through complying with these requests we can ensure that the data are interpreted correctly, analyses are not repeated unnecessarily, beneficial collaboration between users is promoted and the Principle Investigators investment in this project is protected. Submit to the LFDP PIs a short (1 page) description of how you intend to use the data; · Invite LFDP PIs to be co-authors on any publication that uses the data in a substantial way (some PIs may decline and other LFDP scientists may need to be included); If the LFDP PIs are not co-authors, send the PIs a draft of any paper using LFDP data, so that the PIs may comment upon it; In the methods section of any publication using LFDP data, describe that data as coming from the "Luquillo Forest Dynamics Plot, part of the Luquillo Experimental Forest Long-Term Ecological Research Program"; Acknowledge in any publication using LFDP data the "The Luquillo Experim
Frog abundance in fertilization plots
Population estimates and body sizes of E. coqui were collected on fertilization, litter removal, and control plots. Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecological Research Program. Additional support provided by the University of Puerto Rico and the International Institute of Tropical Forestry, USDA Forest Service.
Canopy invertebrate near El Verde and the Long Term Elevation Plots
We study long-term responses of insects and other arthropods to various disturbances and environmental changes, as well as important roles in ecosystem processes. Five tree species in 1991, six during 1992-1995, and seven since 1997 were selected to represent early and late successional forests at El Verde. These trees were sampled in both gap and non-gap plots resulting from Hurricane Hugo. During the past 27 years, these plots have been subjected to multiple disturbances, including Hurricane Georges in 1998 and major droughts in 1994, 1997 and 2002, in addition to several minor hurricanes and droughts. Each of these disturbances has influenced the arthropod community. This project is ongoing. Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecological Research Program. Additional support provided by the University of Puerto Rico and the International Institute of Tropical Forestry, USDA Forest Service.
Sabana pasture permanent plot vegetation sampling
Permanent plot data is expected to show these temporal patterns: (1) rapid increases in percent cover and tree stem density, and (2) rapid turnover from early to late successional plant species. Plant-plant competition should show quick increases in intensity with native grass species and exotic as top competitors. These may lead to exclusion of some trees common after landslide disturbance. Spatial patterns of invading trees should include edge effects due to dispersal limitation with clumping of bird-dispersed species before the first five years after cow exclusion. Because of intact soil and low vegetation in the pasture trees should grow, as measured by biomass(productivity), height, and basal diameter increases, significantly faster compared to colonization of landslides. Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecological Research Program. Additional support provided by the University of Puerto Rico and the International Institute of Tropical Forestry, USDA Forest Service.
MCR LTER: Coral Reefs: Coral recruitment to 25 m2 plots on the forereef surrounding Moorea, French Polynesia, 2011-2015
These data report the number of Pocilloporid, Acroporid and Poritiid corals recruiting annually to permanent 5 m X 5 m plots established at a depth of approximately 10 m on the forereef of Moorea, French Polynesia. Plots were established following an outbreak (2007-2010) of the corallivorous crown-of-thorns seastars (Acanthaster planci) and the close passage of Cyclone Oli to Moorea in February, 2010. These two perturbations resulted in a significant loss of live coral coral from the forereef on an island-wide scale (crown-of-thorns) and the loss of habitat structural complexity from forereef habitats on Moorea's north shore (Cyclone Oli). See Adam, T.C. et al. 2011 "Herbivory, connectivity and ecosystem resilience: response of a coral reef to a large-scale perturbation" PLoS One e23717 for a more complete description of the system, the nature and magnitudes of the perturbations and the short-term response by the coral community to the perturbations. Data were obtained by counting all Pocilloporid, Acroporid and Poritiid coral recruits < 3 cm in colony diameter observed within 25 5 m x 5 m plots established at four sites in a depth of approximately 10 m on the forereef of Moorea, French Polynesia. Two sites, Resilience 1 (R1) containing five 5 m x 5 m plots and Resilience 2 (R2) containing ten 5 m x 5 m plots were established along the north shore of the island. Two additional sites, Resilience 4 (R4) and Resilience 5 (R5), each containing five 5 m x 5 m plots were established on the southeast and southwest shores of the island, respectively. The locations of the plots are permanently marked using stainless steel eye-bolts cemented into the reef matrix so that counts of coral recruits can be made repeatedly within the same plots on an annual basis. This dataset, knb-lter-mcr.5023, is a subset of a larger dataset, knb-lter-mcr.7008, and has been produced in support of a manuscript submission. The parent dataset, knb-lter-mcr.7008, contains additional data on the numb
MCR LTER: Coral Reef Resilience: Benthic Dynamics on 5m by 5m Plots on the Forereef, 2009 - 2011
These data describe the dynamics of corals, invertebrates, and fishes on 5 m X 5 m plots on the forereef following an outbreak of corallivorous crown-of-thorns seastars (Acanthaster planci) that caused mass coral mortality (see Adam et al. 2011). Twenty plots were first established at Resilience 2 during July 2009. Half of these plots were randomly assigned to a structure removal treatment and all dead coral structure was removed by divers, while the other half remained unmanipulated. Following the establishment of these plots, in February 2010 this site was impacted strongly by tropical cyclone Oli with the result that most of the structure was removed from all plots. Consequently, during July 2010, a structure/no structure experiment was initiated on ten plots (5 removals and 5 controls) at a site not impacted by Cyclone Oli (Resilience 3). Finally, during July 2011, five unmanipulated plots were established at each of four additional sites (Resilience 1, 4, 5, 6) so that community trajectories could be compared among sites. Counts of fishes, invertebrates, and corals are made regularily (at least annually). Coral and invertebrate counts are each separated into two data tables to reflect slightly different methodology. Initial coral counts included counts (and size estimates) of all stony corals, while later counts focused on corals from three genera, Pocillopora, Acropora, and Porites. Initial counts of invertebrates did not include information on size; all invertebrates were measured in later counts. In addition to in situ counts, all plots are photographed annually in 0.5 m by 0.5 m segments (e.g., 100 photos per plot). This material is based upon work supported by the U.S. National Science Foundation under Grant No. OCE 16-37396 (and earlier awards) as well as a generous gift from the Gordon and Betty Moore Foundation. Research was completed under permits issued by the French Polynesian Government (Délégation à la Recherche) and the Haut-commissariat de la Rép
Plant & lichen species composition data for Saddle Nodal Plots, 1971 - ongoing.
To study long-term changes in alpine tundra plant communities, thirty permanently marked plots were surveyed in 1971. These same plots were surveyed at twenty, thirty, forty and fifty year intervals from the initial sampling date; in 1991, 2001, 2011, and 2021. Due to covid and other events, data for the 50-year time point was collected over three summers, from 2021-2023. Plots are one by ten meters, divided into ten subplot quadrats, and marked with rebar. The presence or absence of each vascular plant species was recorded per plot. The cover was recorded for each species that appeared in a one meter by ten centimeter strip at the base of each quadrat within each plot. The cover of non-vascular plants, soil, rocks, and lichens was also recorded within the strip in most sampling years. Lichen were also surveyed in 1971 and 2021.These data have been used to study the changes in vascular plant and lichen communities and cover across habitats following a moisture gradient on the saddle portion of Niwot Ridge; these habitats include dry fellfield, dry meadow, moist meadow, wet meadow, snow bank, and shrub tundra. While we have observed some changes in species richness and cover in the plots, overall the plant communities seem fairly stable over time. Lichen species richness has increased in some habitats, while some lichen species have been disappearing from others.
Porewater nutrient concentrations from control plots at a Spartina alterniflora-dominated salt marsh at Law's Point, Rowley River, Plum Island Ecosystem LTER, MA.
Porewater samples from a Spartina alterniflora-dominated salt marsh on the Rowley River in the Plum Island Ecosystem (PIE) LTER site were analyzed for salinity as well as ammonium, phosphate, sulfide and chloride concentrations.
Annual primary productivity in control plots at a Spartina alterniflora-dominated salt marsh at Law's Point, Rowley River, Plum Island Ecosystem LTER, MA.
Annual productivity is determined from aboveground biomass data at permanent, high marsh, plots in a Spartina alterniflora-dominated salt marsh on the Rowley River within the Plum Island Ecosystem (PIE) LTER site, MA.
Aboveground biomass from control plots in a Spartina patens-dominated salt marsh at Law's Point, Rowley River, Plum Island Ecosystem LTER, MA.
Aboveground biomass is determined destructively during the growing season at a Spartina patens-dominated salt marsh on the Rowley River within the Plum Island Ecosystem (PIE) LTER site.
Porewater nutrient concentrations from control plots at a Spartina patens-dominated salt marsh at Law's Point, Rowley River, Plum Island Ecosystem LTER, MA.
Porewater samples from a Spartina patens-dominated salt marsh on the Rowley River in the Plum Island Ecosystem (PIE) LTER site were analyzed for salinity as well as ammonium, phosphate, sulfide and chloride concentrations.
Porewater nutrient concentrations from control plots at a Typha sp. dominated brackish marsh on the Upper Parker River, Plum Island Ecosystem LTER, MA.
Porewater samples from a Typha sp.-dominated brackish marsh on the Upper Parker River in the Plum Island Ecosystem (PIE) LTER site were analyzed for salinity as well as ammonium, phosphate, sulfide and chloride concentrations.
Aboveground biomass at control and fertilized plots in a Spartina alterniflora-dominated marsh, Rowley River, Plum Island Ecosystem LTER, MA.
Aboveground biomass is determined non-destructively during the growing season at a Spartina alterniflora-dominated salt marsh on the Rowley River within the Plum Island Ecosystems (PIE) LTER site.
Soil core metrics taken at Space for Time plots across the PIE LTER.
Soil cores were collected and evaluated at three different depth intervals for bulk density, organic matter by loss on ignition (LOI), pore water ammonium, and pore water salinity. These biotic and abiotic factors differ across marsh types and elevations and help to parameterize other measurements of marsh structure and function, as well as provide insight into marsh heterogeneity within a single site.
Tree measurements and summaries of the field plots used to develop Rojo and Montero (1996) yield tables for Pinus sylvestris L. in central Spain
<p>Tree measurements for principal trees and trees marked for thinning and summaries of the Pinus silvestris L. plots measured for the construction of Rojo and Montero (1996) Pinus sylvestris L. yield tables for central Spain. PRM_Functions.R contains R functions implementing parameter recovery methods to transform Rojo and Montero (1996) Pinus sylvestris L. yield tables into a diameter distribution model.</p> <p><strong>Trees.csv: </strong>Comma separated file with headers in the first row. Each record represents a measured tree. Fields:</p> <ul> <li>"PlotID": Identifier of the plot where the tree was measured</li> <li>"Type": Code indicating if the tree was marked for thinning.</li> <li>"ID_tree" Tree_Identifier</li> <li>"DBH1": First Diameter at breast height measurement for the tree.(mm)</li> <li> "DBH2" Second diameter at breast height measurement for the tree. The second measurement was taken in the direction perpendicular to the first measurement. (mm)</li> <li>"DBHmean": Mean of DBH 1 and DBH 2 <strong>and converted to cm</strong> (cm)</li> </ul> <p><strong>Plot_summaries.csv: </strong>Comma separated file with headers in the first row. Data digitized from Annex II of Rojo and Montero (1996). Each record contains different forest attributes of the plot. Fields:</p> <ul> <li>"PlotID": Identifier of the plot where the tree was measured</li> <li>"Age": Age of the plot determined from tree cores (Years)</li> <li>"Ho" Assman Dominant height for the plot (meters)</li> <li>"SiteIndex": Site index for the plot in meters. Site index is defined as the dominant height in meters measured or expected for the plot for an Age of 100 years.</li> <li>"MeanH" Mean tree height (m)</li> <li>"Dg" Quadratic mean diameter (cm)</li> <li>"Do" Dominant diameter. Mean diameter of the 100 largest trees of a hectare (cm)</li> <li>"N" Stand density (trees per hectare)</li> <li>"G" Plot basal area (m<sup>2</sup>/ha)</li> <li>"V" Total plot volume per unit area (m<sup>3</sup>/ha)</li> <li>"DeltaV" Periodic increment of merchantable volume (m<sup>3</sup>/ha)</li> <li>"Bark" Average percentage of total volume that is Bark. (%)</li> </ul> <p><strong>PRM_Functions.R: </strong>R functions to solve parameter recovery systems of equations based on mean and quadratic mean diameter and dominant diameter, quadratic mean diameter and stand density. Details provided as comments.</p> <p><strong>References</strong></p> <p>Rojo Alberto, Montero G (1996) El pino silvestre en la Sierra de Guadarrama: historia y selvicultura de los Pinares de Cercedilla, Navacerrada y Valsain. Ministerio de Agricultura, Pesca y Alimentación, Secretaria General Tecnica, Centro de Publicaciones, Madrid</p>
Soil profile, climatic, physiographic, overstory and understory data in mixed and monospecific plots of Pinus sylvestris and Pinus pinaster in Spain
<p>This dataset provides valuable environmental information about a triplets’ essay of Scots pine and Maritime pine in Spain. The data characterizes the soil profile (physicochemical parameters of organic and mineral horizons), climate, physiography, understory and overstory.</p> <p>The essay, located in North-Central Spain, consists of eighteen forest plots divided in six triplets. Each triplet includes three circular plots of 15 m-radius located less than 1 km from each other: two monospecific plots dominated by <em>P. sylvestris</em> or <em>P. pinaster</em>, and one mixed plot of both species. In each plot, one pit up to 50 cm depth, one 15 m-radius overstory features inventory and ten understory 1x1 m inventories were carried out. Additionally, physiographic and climatic variables were collected per plot.</p> <p>The file contains information about the 218 environmental variables studied in the eighteen forest plots.</p> <p>Triplet: Triplet to which the plot belongs(1: Triplet 1; 2: Triplet 2; 3: Triplet 3; 4: Triplet 4; 5: Triplet 5; 6: Triplet 6).</p> <p>Stand_type: Type of stand (PS: monospecific stand of <em>Pinus sylvestris</em> L.; PP: monospecific stand of <em>Pinus pinaster</em> Ait.; MM: mixed stand of <em>Pinus sylvestris</em> L.and <em>Pinus pinaster</em> Ait.).</p> <p>Plot: Plot identification (PS01: monospecific stand of <em>Pinus sylvestris</em> L. of triplet 1; PS02: monospecific stand of <em>Pinus sylvestris</em> L. of triplet 2; PS03: monospecific stand of <em>Pinus sylvestris</em> L. of triplet 3; PS04: monospecific stand of <em>Pinus sylvestris</em> L. of triplet 4; PS05: monospecific stand of <em>Pinus sylvestris</em> L. of triplet 5; PS06: monospecific stand of <em>Pinus sylvestris</em> L. of triplet 6; MM01: mixed stand of <em>Pinus sylvestris</em> L.and <em>Pinus pinaster</em> Ait. of triplet 1; MM02: mixed stand of <em>Pinus sylvestris </em>L.and <em>Pinus pinaster</em> Ait. of triplet 2; MM03: mixed stand of <em>Pinus sylvestris</em> L.and <em>Pinus pinaster</em> Ait. of triplet 3; MM04: mixed stand of <em>Pinus sylvestris</em> L.and <em>Pinus pinaster</em> Ait. of triplet 4; MM05: mixed stand of <em>Pinus sylvestris </em>L.and <em>Pinus pinaster</em> Ait. of triplet 5; MM06: mixed stand of <em>Pinus sylvestris </em>L.and <em>Pinus pinaster Ait</em>. of triplet 6; PP01: monospecific stand of <em>Pinus pinaster</em> Ait. of triplet 1; PP02: monospecific stand of <em>Pinus pinaster</em> Ait. of triplet 2; PP03: monospecific stand of <em>Pinus pinaster </em>Ait. of triplet 3; PP04: monospecific stand of <em>Pinus pinaster</em> Ait. of triplet 4; PP05: monospecific stand of <em>Pinus pinaster</em> Ait. of triplet 5; PP06: monospecific stand of<em> Pinus pinaster </em>Ait. of triplet 6).</p> <p>Lat: Plot latitude in degrees.</p> <p>Long: Plot longitude in degrees.</p> <p>Province: Province to which the plot belongs (B: Province of Burgos; Sp: Province of Soria).</p> <p>Municipality: Municipality to which the plot belongs (M: Town of Mamolar; HP: Town of Hontoria del Pinar; N: Town of Navaleno; St: Town of Soria; CP: Town of Cabrejas del Pinar).</p> <p>Forest: Name of the forest where is located the plot (MB: Mata Blanca; MR: Mata Robledo; FP: Fuente del Pardo; PM: Pajar de la molinera; MP: Mojon Pardo; CM: Cueva de Matarubias).</p> <p>Alti: Plot elevation above sea level in m a.s.l.</p> <p>Slope: Slope (gradient) of the plot in percentage.</p> <p>Ori: Plot orientation in degrees.</p> <p>Clim: Climate classification according to Köppen classification (1936) (Cfb: Temperate without a dry season and temperate summer climate; Csb: Temperate with dry summer climate).</p> <p>XR: Accumulated rainfall in one year according to ‘Atlas Agroclimático de Castilla y León-ITACYL-AEMET’ in mm.</p> <p>JR: January rainfall according to ‘Atlas Agroclimático de Castilla y León-ITACYL-AEMET’ mm</p> <p>FR: February rainfall according to ‘Atlas Agroclimático de Castilla y León-ITACYL-AEMET’ in mm.</p> <p>MR: March rainfall according to ‘Atlas Agroclimático de Castilla y León-ITACYL-AEMET’ in mm.</p> <p>AR: April rainfall according to ‘Atlas Agroclimático de Castilla y León-ITACYL-AEMET’ in mm.</p> <p>MyR: May rainfall according to ‘Atlas Agroclimático de Castilla y León-ITACYL-AEMET’ in mm.</p> <p>JnR: June rainfall according to ‘Atlas Agroclimático de Castilla y León-ITACYL-AEMET’ in mm.</p> <p>JlR: July rainfall according to ‘Atlas Agroclimático de Castilla y León-ITACYL-AEMET’ in mm.</p> <p>AgR: August rainfall according to ‘Atlas Agroclimático de Castilla y León-ITACYL-AEMET’ in mm.</p> <p>SR: September rainfall according to ‘Atlas Agroclimático de Castilla y León-ITACYL-AEMET’ in mm.</p> <p>OR: October rainfall according to ‘Atlas Agroclimático de Castilla y León-ITACYL-AEMET’ in mm.</p> <p>NR: November rainfall according to ‘Atlas Agroclimático de Castilla y León-ITACYL-AEMET’ in mm.</p> <p>DR: December rainfall according to ‘Atlas Agroclimático de Castilla y León-ITACYL-AEMET’ in mm.</p> <p>XT: Anual mean temperature according to ‘Atlas Agroclimático de Castilla y León-ITACYL-AEMET’ in ºC.</p> <p>JT: January temperature according to ‘Atlas Agroclimático de Castilla y León-ITACYL-AEMET’ in ºC.</p> <p>FT: February temperature according to ‘Atlas Agroclimático de Castilla y León-ITACYL-AEMET’ in ºC.</p> <p>MT: March temperature according to ‘Atlas Agroclimático de Castilla y León-ITACYL-AEMET’ in ºC.</p> <p>AT: April temperature according to ‘Atlas Agroclimático de Castilla y León-ITACYL-AEMET’ in ºC.</p> <p>MyT: May temperature according to ‘Atlas Agroclimático de Castilla y León-ITACYL-AEMET’ in ºC.</p> <p>JnT: June temperature according to ‘Atlas Agroclimático de Castilla y León-ITACYL-AEMET’ in ºC.</p> <p>JlT: July temperature according to ‘Atlas Agroclimático de Castilla y León-ITACYL-AEMET’ in ºC.</p> <p>AgT: August temperature according to ‘Atlas Agroclimático de Castilla y León-ITACYL-AEMET’ in ºC.</p> <p>ST: September temperature according to ‘Atlas Agroclimático de Castilla y León-ITACYL-AEMET’ in ºC.</p> <p>OT: October temperature according to ‘Atlas Agroclimático de Castilla y León-ITACYL-AEMET’ in ºC.</p> <p>NT: November temperature according to ‘Atlas Agroclimático de Castilla y León-ITACYL-AEMET’ in ºC.</p> <p>DT: December temperature according to ‘Atlas Agroclimático de Castilla y León-ITACYL-AEMET’ in ºC.</p> <p>Par_mat: Soil parental material according to Spanish Geological Map on a 1M scale. (IGME , 2015) (SM: Sandstones and Marls).</p> <p>Geo_age: Geological age of plot according to Spanish Geological Map on a 1M scale. (IGME, 2015) (Mz: Mesozoic age).</p> <p>Soil: Soil type according to Soil-Survey-Staff (2014) (TpDx: Typic Dystroxerept; TpHx:: Typic Humixerept; AqHx:: Aquic humixerept)</p> <p>Litter_B: Total Leaf Litter Biomass in Mg/ha.</p> <p>FF_Th: Forest floor Thickness in cm.</p> <p>Fs: Percentage of Fresh to Total Leaf Litter in %.</p> <p>Fr: Percentage of Fragmented to Total Leaf Litter in %.</p> <p>Hm: Percentage of Humified to Total Leaf Litter in %.</p> <p>GH1: Fist genetic soil horizon according to Soil Survey-Staff (2014) (Ah: Mineral horizon with accumulation of organic matter. This horizon is formed at the soil surface or below an O horizon).</p> <p>GH2: Second genetic soil horizon according to Soil Survey-Staff (2014) (AB: Transition horizon between A and B. A is a mineral horizon formed at the surface or below an O horizon, B is a subsurface horizon in which the structure of the rock is obliterated; AC: Transition horizon between A and C. A is a mineral horizon formed at the surface or below an O horizon; C is a mineral horizon, excluding hard bedrock, that is little affected by pedogenetic processes; Bw: Mineral B horizon where the development of color or structure are its more important diagnostic characteristics).</p> <p>GH3: Third genetic soil horizon according to Soil Survey-Staff (2014) (Bw: Mineral B horizon where the development of color or structure are its more important diagnostic characteristics; C: Mineral horizon, excluding hard bedrock, that is little affected by pedogenetic processes; Cg: Mineral horizon in which a distinct pattern of mottling occurs that reflects alternating conditions of oxidation and reduction of sesquioxides, caused by seasonal surface waterlogging).</p> <p>Th_H1: Thickness of the first soil horizon in cm.</p> <p>Th_H2: Thickness of the second soil horizon in cm.</p> <p>Th_H3: Thickness of the third soil horizon in cm.</p> <p>moistCol_H1: Wet matrix color (Hue Value/Chroma) of the first soil horizon according to Munsell soil color chards (10YR2/1: black; 10YR2/2: very dark brown; 10YR3/1: very dark grey; 10YR3/2: very dark greyish brown; 10YR4/1: dark grey; 10YR6/3: pale brown).</p> <p>moistCol_H2: Wet matrix colour (Hue Value/Chroma) of the second soil horizon according to Munsell soil color chards (5YR5/8: yellowish red; 7.5YR4/6: strong brown; 10YR3/2: very dark greyish brown; 10YR4/1: dark grey; 10YR4/2: dark greyish brown; 10YR4/4: dark yellowish brown with chroma 4; 10YR4/6: dark yellowish brown with chroma 6; 10YR5/3: brown; 10YR5/4: yellowish brown with chroma 4; 10YR5/6: yellowish brown with chroma 6; 10YR5/8: yellowish brown with chroma 8; 10YR6/4: light yellowish brown; 10YR6/6: brownish yellow).</p> <p>moistCol_H3: Wet matrix colour (Hue Value/Chroma) of the third soil horizon according to Munsell soil color chards (5YR4/6: yellowish red; 10YR4/4: dark yellowish brown with chroma 4; 10YR4/6: dark yellowish brown with chroma 6; 10YR5/8: yellowish brown; 10YR6/1: grey).</p> <p>dryCol_H1:Dry matrix color (Hue Value/Chroma) of the first soil horizon according to Munsell soil color chards (10YR4/1: dark grey; 10YR4/2: dark greyish brown; 10YR5/1: grey with value 5; 10YR5/2: greyish brown; 10YR5/3: brown; 10YR6/1: grey with value 6; 10YR6/2: light yellowish brown; 10YR7/2: light grey).</p> <p>dryCol_H2: Dry matrix color (Hue Value/Chroma) of the second soil horizon according to Munsell soil color chards (7.5YR6/6: redish brown; 10YR4/1: dark grey; 10YR6/1: grey with value 6; 10YR6/2: light yellowish brown with chroma 2; 10YR6/3: pale brown; 10YR6/4: light yellowish brown with chroma 4; 10YR6/6: brownish yellow; 10YR7/3: very pale brown with value 7 and choma 3; 10YR7/4: very pale brown withvalue 7 and choma 4; 10YR8/4: very pale brown with value 8 and choma 4).</p> <p>dryCol_H3: Dry matrix color (Hue Value/Chroma) of the third soil horizon according to Munsell soil color chards (5YR5/6: yellowish red; 7.5YR5/6: strong brown; 10YR6/4: light yellowish brown; 10YR6/6: brownish yellow; 10YR7/4: very pale brown; 10YR8/1: white).</p> <p>Sand_H1: Percentage of sand of the first soil horizon determined by the pipette method (Van-Reeuwijk 2002) according to Soil Survey Staff (2014) in % weight/weight.</p> <p>Sand_H2: Percentage of sand of the second soil horizon determined by the pipette method (Van-Reeuwijk 2002) according to Soil Survey Staff (2014) in % weight/weight.</p> <p>Sand_H3: Percentage of sand of the third soil horizon determined by the pipette method (Van-Reeuwijk 2002) according to Soil Survey Staff (2014) in % weight/weight.</p> <p>Silt_H1: Percentage of silt of the first soil horizon determined by the pipette method (Van-Reeuwijk 2002) according to Soil Survey Staff (2014) in % weight/weight.</p> <p>Silt_H2: Percentage of silt of the second soil horizon determined by the pipette method (Van-Reeuwijk 2002) according to Soil Survey Staff (2014) in % weight/weight.</p> <p>Silt_H3: Percentage of silt of the third soil horizon determined by the pipette method (Van-Reeuwijk 2002) according to Soil Survey Staff (2014) in % weight/weight.</p> <p>Clay_H1: Percentage of clay of the first soil horizon determined by the pipette method (Van-Reeuwijk 2002) according to Soil Survey Staff (2014) in % weight/weight.</p> <p>Clay_H2: Percentage of clay of the second soil horizon determined by the pipette method (Van-Reeuwijk 2002) according to Soil Survey Staff (2014) in % weight/weight.</p> <p>Clay_H3: Percentage of clay of the third soil horizon determined by the pipette method (Van-Reeuwijk 2002) according to Soil Survey Staff (2014) in % weight/weight.</p> <p>Tex_H1: Textural class of the first soil horizon according to Soil Survey Staff (2014) (SL: Sandy Loam; L: Loam).</p> <p>Tex_H2: Textural class of the second soil horizon according to Soil Survey Staff (2014) (SL: Sandy Loam; L: Loam).</p> <p>Tex_H3: Textural class of the third soil horizon according to Soil Survey Staff (2014) (SL: Sandy Loam; L: Loam; CL: Clay loam; C: Clay).</p> <p>Stones_H1: Coarse soil material (> 2 mm) of the first soil horizon in % weight/weight.</p> <p>Stones_H2: Coarse soil material (> 2 mm) of the second soil horizon in % weight/weight.</p> <p>Stones_H3: Coarse soil material (> 2 mm) of the third soil horizon in % weight/weight.</p> <p>bD_H1: Bulk density of the first soil horizon according to (Van-Reeuwijk 2002) in g/cm<sup>3</sup>.</p> <p>bD_H2: Bulk density of the second soil horizon according to (Van-Reeuwijk 2002) in g/cm<sup>3</sup>.</p> <p>bD_H3: Bulk density of the third soil horizon according to (Van-Reeuwijk 2002) in g/cm<sup>3</sup>.</p> <p>pD_H1: Particle density of the first soil horizon according to (Van-Reeuwijk 2002) in g/cm<sup>3</sup>.</p> <p>pD_H2: Particle density of the second soil horizon according to (Van-Reeuwijk 2002) in g/cm<sup>3</sup>.</p> <p>pD_H3: Particle density of the third soil horizon according to (Van-Reeuwijk 2002) in g/cm<sup>3</sup>.</p> <p>Poro_H1: Porosity of the first soil horizon according to (Van-Reeuwijk 2002) in % vol/vol.</p> <p>Poro_H2: Porosity of the second soil horizon according to (Van-Reeuwijk 2002) in % vol/vol.</p> <p>Poro_H3: Porosity of the third soil horizon according to (Van-Reeuwijk 2002) in % vol/vol.</p> <p>pH_H1: pH (1:2.5 H2O) of the first soil horizon according to (Van-Reeuwijk 2002)</p> <p>pH_H2: pH (1:2.5 H2O) of the second soil horizon according to (Van-Reeuwijk 2002)</p> <p>pH_H3: pH (1:2.5 H2O) of the third soil horizon according to (Van-Reeuwijk 2002)</p> <p>EC_H1: Electrical conductivity of the first soil horizon according to (Van-Reeuwijk 2002) in dS/m.</p> <p>EC_H2: Electrical conductivity of the second soil horizon according to (Van-Reeuwijk 2002) in dS/m.</p> <p>EC_H3: Electrical conductivity of the third soil horizon according to (Van-Reeuwijk 2002) in dS/m.</p> <p>avP_H1: Available phosphorus of the first soil horizon according to Olsen and Sommers (1982) in mg/kg.</p> <p>avP_H2: Available phosphorus of the second soil horizon according to Olsen and Sommers (1982) in mg/kg.</p> <p>avP_H3: Available phosphorus of the third soil horizon according to Olsen and Sommers (1982) in mg/kg.</p> <p>avPstock_H1: Available phosphorus stock of the first soil horizon according to López-Marcos et al. (2019) in Mg/ha.</p> <p>avPstock_H2: Available phosphorus stock of the second soil horizon according to López-Marcos et al. (2019) in Mg/ha.</p> <p>avPstock_H3: Available phosphorus stock of the third soil horizon up to 50 cm depth according to López-Marcos et al. (2019) in Mg/ha.</p> <p>avPstock_50: Available phosphorus stock of whole soil profile up to 50 cm depth according to López-Marcos et al. (2019) in Mg/ha.</p> <p>TN_Fs: Total nitrogen of the fresh forest floor analyzed with a LECO-CHN 2000 elemental analyzer in g/kg</p> <p>TN_Fg: Total nitrogen of the fragmented forest floor analyzed with a LECO-CHN 2000 elemental analyzer in g/kg</p> <p>TN_Hm: Total nitrogen of the humified forest floor analyzed with a LECO-CHN 2000 elemental analyzer in g/kg</p> <p>TN_H1: Total nitrogen of the first soil horizon analyzed with a LECO-CHN 2000 elemental analyzer in g/kg.</p> <p>TN_H2: Total nitrogen of the second soil horizon analyzed with a LECO-CHN 2000 elemental analyzer in g/kg.</p> <p>TN_H3: Total nitrogen of the third soil horizon analyzed with a LECO-CHN 2000 elemental analyzer in g/kg.</p> <p>TNstock_H1: Total nitrogen stock of the first soil horizon according to López-Marcos et al. (2019) in Mg/ha.</p> <p>TNstock_H2: Total nitrogen stock of the second soil horizon according to López-Marcos et al. (2019) in Mg/ha.</p> <p>TNstock_H3: Total nitrogen stock of the third soil horizon up to 50 cm depth according to López-Marcos et al. (2019) in Mg/ha.</p> <p>TNstock_50: Total nitrogen stock of whole soil profile up to 50 cm depth according to López-Marcos et al. (2019) in Mg/ha.</p> <p>TOC_Fs: Total organic carbon of the fresh forest floor analyzed with a LECO-CHN 2000 elemental analyzer in g/kg</p> <p>TOC_Fg: Total organic carbon of the fragmented forest floor analyzed with a LECO-CHN 2000 elemental analyzer in g/kg</p> <p>TOC_Hm: Total organic carbon of the humified forest floor analyzed with a LECO-CHN 2000 elemental analyzer in g/kg</p> <p>TOC_H1: Total organic carbon of the first soil horizon analyzed with a LECO-CHN 2000 elemental analyzer in g/kg.</p> <p>TOC_H2: Total organic carbon of the second soil horizon analyzed with a LECO-CHN 2000 elemental analyzer in g/kg.</p> <p>TOC_H3: Total organic carbon of the third soil horizon analyzed with a LECO-CHN 2000 elemental analyzer in g/kg.</p> <p>TOCstock_H1:Total organic carbon stock of the first soil horizon according to López-Marcos et al. (2019) in Mg/ha.</p> <p>TOCstock_H2: Total organic carbon stock of the second soil horizon according to López-Marcos et al. (2019) in Mg/ha.</p> <p>TOCstock_H3: Total organic carbon stock of the third soil horizon up to 50 cm depth according to López-Marcos et al. (2019) in Mg/ha.</p> <p>TOCstock_50: Total organic carbon stock of whole soil profile up to 50 cm depth according to López-Marcos et al. (2019) in Mg/ha.</p> <p>C/N_Fs: Ratio of total organic carbon to total nitrogen of the fresh forest floor </p> <p>C/N_Fg: Ratio of total organic carbon to total nitrogen of the fragmented forest floor </p> <p>C/N_Hm: Ratio of total organic carbon to total nitrogen of the humified forest floor </p> <p>C/N_H1: Ratio of total organic carbon to total nitrogen of the first soil horizon</p> <p>C/N_H2: Ratio of total organic carbon to total nitrogen of the second soil horizon</p> <p>C/N_H3: Ratio of total organic carbon to total nitrogen of the third soil horizon</p> <p>OxC_H1: Easily oxidizable carbon of the first soil horizon according to Walkley (1947) in mg/kg.</p> <p>OxC_H2: Easily oxidizable carbon of the second soil horizon according to Walkley (1947) in mg/kg.</p> <p>OxC_H3: Easily oxidizable carbon of the third soil horizon according to Walkley (1947) in mg/kg.</p> <p>OxCstock_H1: Easily oxidizable carbon stock of the first soil horizon according to López-Marcos et al. (2019) in Mg/ha.</p> <p>OxCstock_H2: Easily oxidizable carbon stock of the second soil horizon according to López-Marcos et al. (2019) in Mg/ha.</p> <p>OxCstock_H3: Easily oxidizable carbon stock of the third soil horizon up to 50 cm depth according to López-Marcos et al. (2019) in Mg/ha.</p> <p>OxCstock_50: Easily oxidizable carbon stock of whole soil profile up to 50 cm depth according to López-Marcos et al. (2019) in Mg/ha.</p> <p>CEC_H1: Cation exchange capacity of the first soil horizon according to Mehlich (1953) in cmol<sub>+</sub>/kg.</p> <p>CEC_H2: Cation exchange capacity of the second soil horizon according to Mehlich (1953) in cmol<sub>+</sub>/kg.</p> <p>CEC_H3: Cation exchange capacity of the third soil horizon according to Mehlich (1953) in cmol<sub>+</sub>/kg.</p> <p>Na<sup>+</sup>_H1: Exchangeable sodium of the first soil horizon by means of extracting with 1N ammonium acetate (pH=7) (Schollenberger and Simon 1945) in cmol<sub>+</sub>/kg.</p> <p>Na<sup>+</sup>_H2: Exchangeable sodium of the second soil horizon by means of extracting with 1N ammonium acetate (pH=7) (Schollenberger and Simon 1945) in cmol<sub>+</sub>/kg.</p> <p>Na<sup>+</sup>_H3: Exchangeable sodium of the third soil horizon by means of extracting with 1N ammonium acetate (pH=7) (Schollenberger and Simon 1945) in cmol<sub>+</sub>/kg.</p> <p>Na<sup>+</sup>stock_H1: Exchangeable sodium stock of the first soil horizon according to López-Marcos et al. (2019) in Mg/ha.</p> <p>Na<sup>+</sup>stock_H2: Exchangeable sodium stock of the second soil horizon according to López-Marcos et al. (2019) in Mg/ha.</p> <p>Na<sup>+</sup>stock_H3: Exchangeable sodium stock of the third soil horizon up to 50 cm depth according to López-Marcos et al. (2019) in Mg/ha.</p> <p>Na<sup>+</sup>stock_50: Exchangeable sodium stock of whole soil profile up to 50 cm depth according to López-Marcos et al. (2019) in Mg/ha.</p> <p>K<sup>+</sup>_H1: Exchangeable potassium of the first soil horizon by means of extracting with 1N ammonium acetate (pH=7) (Schollenberger and Simon 1945) in cmol<sub>+</sub>/kg.</p> <p>K<sup>+</sup>_H2: Exchangeable potassium of the second soil horizon by means of extracting with 1N ammonium acetate (pH=7) (Schollenberger and Simon 1945) in cmol<sub>+</sub>/kg.</p> <p>K<sup>+</sup>_H3: Exchangeable potassium of the third soil horizon by means of extracting with 1N ammonium acetate (pH=7) (Schollenberger and Simon 1945) in cmol<sub>+</sub>/kg.</p> <p>K<sup>+</sup>stock_H1: Exchangeable potassium stock of the first soil horizon according to López-Marcos et al. (2019) in Mg/ha.</p> <p>K<sup>+</sup>stock_H2: Exchangeable potassium stock of the second soil horizon according to López-Marcos et al. (2019) in Mg/ha.</p> <p>K<sup>+</sup>stock_H3: Exchangeable potassium stock of the third soil horizon up to 50 cm depth according to López-Marcos et al. (2019) in Mg/ha.</p> <p>K<sup>+</sup>stock_50: Exchangeable potassium stock of whole soil profile up to 50 cm depth according to López-Marcos et al. (2019) in Mg/ha.</p> <p>Ca<sup>+2</sup>_H1: Exchangeable calcium of the first soil horizon by means of extracting with 1N ammonium acetate (pH=7) (Schollenberger and Simon 1945) in cmol<sub>+</sub>/kg.</p> <p>Ca<sup>+2</sup>_H2: Exchangeable calcium of the second soil horizon by means of extracting with 1N ammonium acetate (pH=7) (Schollenberger and Simon 1945) in cmol<sub>+</sub>/kg.</p> <p>Ca<sup>+2</sup>_H3: Exchangeable calcium of the third soil horizon by means of extracting with 1N ammonium acetate (pH=7) (Schollenberger and Simon 1945) in cmol<sub>+</sub>/kg.</p> <p>Ca<sup>+2</sup>stock_H1: Exchangeable calcium stock of the first soil horizon according to López-Marcos et al. (2019) in Mg/ha.</p> <p>Ca<sup>+2</sup>stock_H2: Exchangeable calcium stock of the second soil horizon according to López-Marcos et al. (2019) in Mg/ha.</p> <p>Ca<sup>+2</sup>stock_H3: Exchangeable calcium stock of the third soil horizon up to 50 cm depth according to López-Marcos et al. (2019) in Mg/ha.</p> <p>Ca<sup>+2</sup>stock_50: Exchangeable calcium stock of whole soil profile up to 50 cm depth according to López-Marcos et al. (2019) in Mg/ha.</p> <p>Mg<sup>+2</sup>_H1: Exchangeable magnesium of the first soil horizon by means of extracting with 1N ammonium acetate (pH=7) (Schollenberger and Simon 1945) in cmol<sub>+</sub>/kg.</p> <p>Mg<sup>+2</sup>_H2: Exchangeable magnesium of the second soil horizon by means of extracting with 1N ammonium acetate (pH=7) (Schollenberger and Simon 1945) in cmol<sub>+</sub>/kg.</p> <p>Mg<sup>+2</sup>_H3: Exchangeable magnesium of the third soil horizon by means of extracting with 1N ammonium acetate (pH=7) (Schollenberger and Simon 1945) in cmol<sub>+</sub>/kg.</p> <p>Mg<sup>+2</sup>stock_H1: Exchangeable magnesium stock of the first soil horizon according to López-Marcos et al. (2019) in Mg/ha.</p> <p>Mg<sup>+2</sup>stock_H2: Exchangeable magnesium stock of the second soil horizon according to López-Marcos et al. (2019) in Mg/ha.</p> <p>Mg<sup>+2</sup>stock_H3: Exchangeable magnesium stock of the third soil horizon up to 50 cm depth according to López-Marcos et al. (2019) in Mg/ha.</p> <p>Mg<sup>+2</sup>stock_50: Exchangeable magnesium stock of whole soil profile up to 50 cm depth according to López-Marcos et al. (2019) in Mg/ha.</p> <p>SB_H1: Sum of bases of the first soil horizon by means of extracting with 1N ammonium acetate (pH=7) (Schollenberger and Simon 1945) in cmol<sub>+</sub>/kg.</p> <p>SB_H2: Sum of bases of the second soil horizon by means of extracting with 1N ammonium acetate (pH=7) (Schollenberger and Simon 1945) in cmol<sub>+</sub>/kg.</p> <p>SB_H3: Sum of bases of the third soil horizon by means of extracting with 1N ammonium acetate (pH=7) (Schollenberger and Simon 1945) in cmol<sub>+</sub>/kg.</p> <p>SBstock_H1: Sum of bases stock of the first soil horizon according to López-Marcos et al. (2019) in Mg/ha.</p> <p>SBstock_H2: Sum of bases stock of the second soil horizon according to López-Marcos et al. (2019) in Mg/ha.</p> <p>SBstock_H3: Sum of bases stock of the third soil horizon up to 50 cm depth according to López-Marcos et al. (2019) in Mg/ha.</p> <p>SBstock_50: Sum of bases stock of whole soil profile up to 50 cm depth according to López-Marcos et al. (2019) in Mg/ha.</p> <p>FC_H1: Field capacity of the first soil horizon according to Van-Reeuwijk (2002) in %.</p> <p>FC_H2: Field capacity of the second soil horizon according to Van-Reeuwijk (2002) in %.</p> <p>FC_H3: Field capacity of the third soil horizon according to Van-Reeuwijk (2002)) in %.</p> <p>PWP_H1: Permanent wilting point of the first soil horizon according to Van-Reeuwijk (2002) in %.</p> <p>PWP_H2: Permanent wilting point of the second soil horizon according to Van-Reeuwijk (2002) in %. </p> <p>PWP_H3: Permanent wilting point of the third soil horizon according to Van-Reeuwijk (2002) in %.</p> <p>AW_H1: Available water of the first soil horizon according to Van-Reeuwijk (2002) in %.</p> <p>AW_H2: Available water of the second soil horizon according to MAPA (1994) in %.</p> <p>AW_H3: Available water of the third soil horizon according to Van-Reeuwijk (2002) in %.</p> <p>WHC_H1: Water holding capacity of the first soil horizon according to López-Marcos et al. (2019) in g/cm<sup>2</sup>.</p> <p>WHC_H2: Water holding capacity of the second soil horizon according to López-Marcos et al. (2019) in g/cm<sup>2</sup>.</p> <p>WHC_H3: Water holding capacity of the third soil horizon up to 50 cm depth according to López-Marcos et al. (2019) in g/cm<sup>2</sup>.</p> <p>WHC_50: Water holding capacity of whole soil profile up to 50 cm depth according to López-Marcos et al. (2019) in g/cm<sup>2</sup>.</p> <p>Pot_veg: Potential vegetation according to Rivas-Martínez (1987) (LfQp: <em>Luzulo forsteri-Querceto pyrenaicae </em>S.; FhQp: <em>Festuco heterophyllae-Querceto pyrenaicae</em> S.; Jht: <em>Junipereto hemisphaerico-thuriferae</em> S.).</p> <p>Cur_veg: Current vegetation according to WMS service of MAPAMA(<a href="http://wms.mapama.es/sig/Biodiversidad">http://wms.mapama.es/sig/Biodiversidad</a>) (ps: <em>Pinus sylvestris</em> L.; pp: <em>Pinus pinaster</em> Ait.; pi: <em>Pinus sylvestris</em> L. and <em>Pinus pinaster</em> Ait.).</p> <p>NT: Stems per hectare of both <em>Pinus </em>species (<em>Pinus sylvestris</em> L. and <em>Pinus pinaster</em> Ait.) in trees/ha.</p> <p>NPs: Stems per hectare of <em>Pinus sylvestris</em> L. in trees/ha.</p> <p>NPp: Stems per hectare of <em>Pinus pinaster</em> Ait. in trees/ha.</p> <p>GT: Basal area per hectare of both <em>Pinus</em> species (<em>Pinus sylvestris</em> L. and <em>Pinus pinaster</em> Ait.) in m<sup>2</sup>/ha.</p> <p>GPs: Basal area per hectare of <em>Pinus sylvestris</em> L. in m<sup>2</sup>/ha.</p> <p>GPp: Basal area per hectare of <em>Pinus pinaster</em> Ait. in m<sup>2</sup>/ha.</p> <p>%PS: Percentage of basal area of <em>Pinus sylvestris</em> L. from total basal area</p> <p>%PP: Percentage of basal area of <em>Pinus pinaster</em> Ait. from total basal area</p> <p>dgT: Quadratic mean diameter of both <em>Pinus </em>species (<em>Pinus sylvestris</em> L. and <em>Pinus pinaster</em> Ait.) in cm.</p> <p>dgPs: Quadratic mean diameter of <em>Pinus sylvestris</em> L. in cm.</p> <p>dgPp: Quadratic mean diameter of <em>Pinus pinaster</em> Ait. in cm.</p> <p>HoT: Dominant height of both <em>Pinus</em> species (<em>Pinus sylvestris</em> L. and <em>Pinus pinaster</em> Ait.) in cm.</p> <p>HoPs: Dominant height of <em>Pinus sylvestris</em> L. in m.</p> <p>HoPp: Dominant height of <em>Pinus pinaster</em> Ait. in m.</p> <p>AgePs: Normal age of <em>Pinus sylvestris</em> L. in years.</p> <p>AgePp: Normal age of <em>Pinus pinaster</em> Ait. In years.</p> <p>SIPs: Site index of <em>Pinus sylvestris</em> L. related at age 100 for total plot according to Rojo and Montero (1999)</p> <p>SIPp: Site index of <em>Pinus pinaster</em> Ait. related at age 100 for total plot according to Bravo-Oviedo et al. (2007)</p> <p>Litter_cov: Cover of leaf litter in %.</p> <p>Vasc: Cover of understory vascular plants in %.</p> <p>Bryo: Cover of understory bryophytes in %.</p> <p>Under_sp: More abundant specie of understory vegetation (Aica: <em>Aira caryophyllea</em> L.; Aruv: <em>Arctostaphylos uva-ursi</em> (L.) Spreng.; Cavu: <em>Calluna vulgaris</em> (L.) Hull; Erar: <em>Erica arborea </em>L.; Erau: <em>Erica australis</em> L.; Pipi: <em>Pinus pinaster</em> Aiton. (seedlings/saplings); Pisy: <em>Pinus sylvestris</em> L. (seedlings/saplings; Ptaq: <em>Pteridium aquilinum</em> (L.) Kuhn)</p> <p>Aqu: Understory cover of family Aquifoliaceae in %.</p> <p>Aste: Understory cover of family Asteraceae in %.</p> <p>Cari: Understory cover of family Cariophyllaceae in %.</p> <p>Cist: Understory cover of family Cistaceae in %.</p> <p>Cupr: Understory cover of family Cupresaceae in %.</p> <p>Eric: Understory cover of family Ericaceae in %.</p> <p>Faba: Understory cover of family Fabaceae in %.</p> <p>Faga: Understory cover of family Fagaceae in %.</p> <p>Junc: Understory cover of family Juncaceae in %.</p> <p>Lili: Understory cover of family Liliaceae in %.</p> <p>Pina: Understory cover of family Pinaceae in %.</p> <p>Poac: Understory cover of family Poaceae in %.</p> <p>Poli: Understory cover of family Poligalaceae in %.</p> <p>Rosa: Understory cover of family Rosaceae in %.</p> <p>Rubi: Understory cover of family Rubiaceae in %.</p> <p>Scro: Understory cover of family Scrofulariaceae in %.</p> <p>Viol: Understory cover of family Violaceae in %.</p> <p>Xant: Understory cover of family Xanthorrhoeaceae in %.</p>
1QIsaa data collection (binarized images, feature files, and plotting scripts) for writer identification test using artificial intelligence and image-based pattern recognition techniques
<p><strong>The Great Isaiah Scroll (1QIsa<sup>a</sup>) data set for writer identification</strong></p> <p>This data set is collected for the ERC project:<br> The Hands that Wrote the Bible: Digital Palaeography and Scribal Culture of the Dead Sea Scrolls<br> PI: Mladen Popović<br> Grant agreement ID: 640497</p> <p>Project website: <a href="https://cordis.europa.eu/project/id/640497">https://cordis.europa.eu/project/id/640497</a><br> <br> <strong>Copyright (c) </strong> University of Groningen, 2021. All rights reserved.<br> <strong>Disclaimer and copyright notice for all data contained on this .tar.gz file:</strong></p> <p><strong>1)</strong> permission is hereby granted to use the data for research purposes. It is not allowed to distribute this data for commercial purposes.</p> <p><strong>2) </strong>provider gives no express or implied warranty of any kind, and any implied warranties of merchantability and fitness for purpose are disclaimed.</p> <p><strong>3) </strong>provider shall not be liable for any direct, indirect, special, incidental, or consequential damages arising out of any use of this data.</p> <p><strong>4) </strong>the user should refer to the first public article on this data set:<br> <br> <em>Popović, M., Dhali, M. A., & Schomaker, L. (2020). Artificial intelligence-based writer identification generates new evidence for the unknown scribes of the Dead Sea Scrolls exemplified by the Great Isaiah Scroll (1QIsa<sup>a</sup>). arXiv preprint arXiv:2010.14476.</em><br> <br> BibTeX:</p> <pre>@article{popovic2020artificial, title={Artificial intelligence based writer identification generates new evidence for the unknown scribes of the Dead Sea Scrolls exemplified by the Great Isaiah Scroll (1QIsaa)}, author={Popovi{\'c}, Mladen and Dhali, Maruf A and Schomaker, Lambert}, journal={arXiv preprint arXiv:2010.14476}, year={2020} }</pre> <p><strong>5) </strong>the recipient should refrain from proliferating the data set to third parties external to his/her local research group. Please refer interested researchers to this site for obtaining their own copy.</p> <p><strong>Organisation of the data:</strong></p> <p>The .tar.gz file contains three directories: images, features, and plots. The included 'README' file contains all the instructions.</p> <p>The 'images' directory contains NetPBM images of the columns of 1QIsa<sup>a</sup>. The NetPBM format is chosen because of its simplicity. Additionally, there is no doubt about lossy compression in the processing chain. There are two images for each of the Great Isaiah Scroll columns: one is the direct binarized output from the BiNet (<em>arxiv.org/abs/1911.07930</em>) system, and the other one is the manually cleaned version of the binarized output. The file names for the direct binarized output are of the format '1QIsaa_col<columnnr>.pbm', for example, '1QIsaa_col15.pbm'. And, for the cleaned version, the format is '1QIsaa_col<columnnr>_cleaned.pbm', for example, '1QIsaa_col15_cleaned.pbm'. Note: the image files are not in a separate directory; they will be extracted in the same place. However, due to the unique naming, there is no problem extracting them in one single directory.</p> <p>The 'features' directory contains feature files computed for each of the column images. There are two types of feature files: Hinge and Adjoined. They are distinguishable by their extension, for example, '1QIsaa_col15_cleaned.hinge' and '1QIsaa_col15_cleaned.adjoined'. They are also arranged in separate directories for ease of use.</p> <p>The 'plots' directory contains a simple python script to perform PCA on the feature files and then visualize them in a 3D plot. The file takes the location of feature files as an input. The 'README_plot' file contains examples of how-to-run in the terminal.</p> <p><strong>Brief description:</strong><br> According to ImageMagick's' identify' tool, the original images are in grayscale (.jpg) from Brill collection, in '8-bit Gray 256c'. These images pass through multiple preprocessing measures to become suitable for pattern recognition-based techniques. The first step in preprocessing is the image-binarization technique. In order to prevent any classification of the text-column images based on irrelevant background patterns, a specific binarization technique (BiNet) was applied, keeping the original ink traces intact. After performing the binarization, the images were cleaned further by removing the adjacent columns that partially appear on the target columns' images. Finally, few minor affine transformations and stretching corrections were performed in a restrictive manner. These corrections are also targeted for aligning the texts where the text lines get twisted due to the leather writing surface's degradation. Hence, the clean images are there in the directory along with the direct binarized images. No effort has been made to obtain a balanced set in any way.</p> <p><strong>Tools:</strong><br> <strong>Binarization:</strong><br> The BiNet tool is available for scientific use upon request (m.a.dhal(at)rug.nl)</p> <p><strong>Image Morphing:</strong><br> In the original article, data augmentation was performed using image morphing. The tool is available on GitHub:<br> https://github.com/GrHound/imagemorph.c</p> <p><strong>Features for writer identification:</strong><br> Lambert Schomaker<br> http://www.ai.rug.nl/~lambert/allographic-fraglet-codebooks/allographic-fraglet-codebooks.html<br> http://www.ai.rug.nl/~lambert/hinge/hinge-transform.html<br> <em><strong>1. </strong>L. Schomaker & M. Bulacu (2004). Automatic writer identification using connected-component contours and edge-based features of upper-case Western script. IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol 26(6), June 2004, pp. 787 - 798.<br> <strong>2. </strong>Bulacu, M. & Schomaker, L.R.B. (2007). Text-independent Writer Identification and Verification Using Textural and Allographic Features, IEEE Trans. on Pattern Analysis and Machine Intelligence (PAMI), Special Issue - Biometrics: Progress and Directions, April, 29(4), p. 701-717.</em><br> <br> The features (hinge, fraglets) have been combined in a single MS Windows application, GIWIS, which is available for scientific use upon request (l.r.b.schomaker(at)rug.nl)</p> <p><strong>If you have any question, please contact us:</strong><br> Maruf A. Dhali <m.a.dhali(at)rug.nl><br> Lambert Schomaker <l.r.b.schomaker(at)rug.nl><br> Mladen Popović <m.popovic(at)rug.nl></p> <p><strong>Please cite our papers if you use this data set:</strong><br> <em><strong>1.</strong> Popović, M., Dhali, M. A., & Schomaker, L. (2020). Artificial intelligence based writer identification generates new evidence for the unknown scribes of the Dead Sea Scrolls exemplified by the Great Isaiah Scroll (1QIsa<sup>a</sup>). arXiv preprint arXiv:2010.14476.<br> <strong>2. </strong>Dhali, M. A., de Wit, J. W., & Schomaker, L. (2019). Binet: Degraded-manuscript binarization in diverse document textures and layouts using deep encoder-decoder networks. arXiv preprint arXiv:1911.07930.</em></p>
Raw data acquired necessary to produce the plots introduced in the scientific paper: "Upper-limb kinematic reconstruction during stroke robot-aided therapy" (Medical & Biological Engineering & Computing)
<p>These files contain the raw data acquired necessary to produce the plots introduced the Figure 6 of the scientific paper: “Upper-limb kinematic reconstruction during stroke robot-aided therapy” (Medical & Biological Engineering & Computing).</p> <p>Fig. 6 shows the data recorded from two patients performing five forward/backward movements at InMotion2 robot before and after rehabilitation treatment. Mean values of the five execution have been reported in Fig. 6.</p>
Plotting sex differences in global causes of morbidity
<p>Data, code and graphics for causes of disability-adjusted life-years globally, separated by sex and by age-group. Data was downloaded from the World Health Organisation, 2012 records. This was used in a commissioned review article for eLS http://www.els.net/WileyCDA/ , Gilks, William P (October 2016) Sex Differences in Disease Genetics. In: eLS. John Wiley & Sons, Ltd: Chichester. DOI: 10.1002/9780470015902.a0026936 and is also available as an unreviewed, un-edited pre-print on bioarxiv http://dx.doi.org/10.1101/063651 http://biorxiv.org/content/early/2016/07/13/063651</p>
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