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openCC (other)Oct 2020View details →

Soil salinity at GCE-LTER vegetation monitoring plots in October 2019

Soil samples were collected in conjunction with Fall 2019 plant monitoring at half of the permanent vegetation monitoring plots in the creekbank and midmarsh zones at 10 GCE study sites. Pore-water salinity was determined by analysis of supernatant salinity in dried soil samples hydrated with a measured volume of deionized water.

openCC (other)Apr 2022View details →

Quadrat vegetation cover data on 1m x 1m plots from the long-term Small Mammal Exclusion Study (SMES) at Jornada Basin LTER, 1995-2020

This data package contains vegetation cover from plots with various levels of herbivore exclusion on the Jornada Experimental Range (JER) and Chihuahuan Desert Rangeland Research Center (CDRRC) in Dona Ana County, southern New Mexico, USA. Study sites were established in 1995; one in black grama grassland and the other in creosotebush shrubland to compare the impact of herbivores on ecosystem processes between these vegetation types. Parallel studies were established at the Sevilleta LTER site (New Mexico, USA) and Mapimi Biosphere Reserve (Durango, Mexico). Each study site is 1 km by 0.5 km in area. Four replicate experimental blocks were randomly located at the grassland study site to measure vegetation responses using exclusion treatments including a) all mammalian herbivores, including cattle, lagomorphs, and rodents, b) lagomorphs and cattle only, c) cattle only, and d) control accessible to all herbivores. Because grazing cattle are excluded from the entire creosote site, only three replicate experimental blocks were randomly located there including a) all mammalian herbivores, including lagomorphs, and rodents, b) lagomorphs only, and c) control accessible to all herbivores. Thirty-six sampling points were positioned at 5.8-meter intervals on a systematically located 6 by 6 point grid within each plot. A permanent one-meter by one-meter vegetation measurement quadrat is located at each of the 36 points. At each quadrat, percent cover by individual plant species is measured. Other measurements include height (cm) of each species in the quadrat, and plant condition (living or dead). Data were collected in the spring and fall of every year from 1995 to 2005. After 2005, sampling frequency changed to every 5 years in the fall. This study is ongoing.

openCC (other)Mar 2023View details →

Aboveground vegetation cover and biomass in plots with experimentally altered precipitation variability at the Jornada Basin LTER site, 2009-ongoing

This dataset contains cover and biomass data collected starting in 2012 for a long-term precipitation variability manipulation experiment at the Jornada Basin LTER site in southern New Mexico, U.S.A. The study was designed to assess the effect of interannual variability in precipitation on average aboveground net primary productivity (ANPP) in Chihuahuan Desert grasslands. The study began in 2009, has five annual precipitation treatments, and contains 50 plots (10 per treatment). This experiment uses precipitation shelters and irrigation treatments to manipulate water inputs to 2.5 x 2.5 meter plots in a desert grassland. There are high, low, and ambient (control) precipitation variability treatments. Ambient plots receive natural precipitation each year, while variability treatments alternate between 20% and 180% (high variability), or 50% and 150% (low variability) of ambient precipitation each year. Plant cover measurements are made annually in each plot, from which biomass or net primary production are derived. This is an ongoing study and the dataset will be updated yearly.

openCC (other)Nov 2025View details →

Aboveground vegetation cover and biomass in plots with experimentally altered precipitation and nutrient inputs at the Jornada Basin LTER site, 2006-ongoing

This dataset contains cover and biomass data collected starting in 2006 for a long-term precipitation and nutrient manipulation experiment at the Jornada Basin LTER site in southern New Mexico, U.S.A. This experiment uses precipitation shelters and irrigation treatments to manipulate water inputs, and fertilization treatments to alter nitrogen input to 2.5 x 2.5 meter plots in a desert grassland. Plant cover measurements are made annually in each plot, from which biomass or net primary production are derived. This is an ongoing study and the dataset will be updated yearly.

zenodo48/100

CzechVeg-ESy: Expert system for automatic classification of vegetation plots from the Czech Republic

Expertní systém pro automatickou klasifikaci fytocenologických snímků z České republiky  [popis a instrukce v če&scaron;tině jsou uvedeny níže] *************************************************************************************************************** CzechVeg-ESy is an expert system for automatic classification of vegetation plots from the Czech Republic to the vegetation types defined in the monograph Vegetation of the Czech Republic (<a href="https://www.sci.muni.cz/botany/vegsci/vegetace.php?page=monograph&lang=en">Chytrý 2007-2013</a>). It is delivered in two main versions: The main version 1 (v1) is the original version used for the vegetation classification in that monograph, described in detail in its English Summary (<a href="https://www.sci.muni.cz/botany/chytry/Vegetation-Czech-Rep-Summary.pdf">Chytrý 2007</a>). Its subversions (indicated by dates) contains corrections of minor errors and species nomenclature. This version only classifies vegetation to the phytosociological associations. The main version 2 (v2) uses the same classification system as accepted in the Vegetation of the Czech Republic, but includes more advanced functions to provide more accurate classification. Moreover, it is hierarchical, performing classification not only to associations but also to alliances and classes (for the plots not classified at lower levels). Each version is delivered in two variants. The basic variant (CzechVeg-ESy-basic-v1.txt) assigns vegetation plots to associations following their formal definitions created using the Cocktail method (<a href="https://doi.org/10.2307/3236796">Bruelheide 2000</a>) modified by <a href="https://www.sci.muni.cz/botany/chytry/Koci_etal2003_JVS.pdf">Kočí et al (2003)</a>. These definitions are based on the presence of sociological species groups and the dominance of selected species. The expert system evaluates individual vegetation plots and assigns them to the associations. A classification process is considerably faster when the basic variant is used, as opposed to the full variant. The full variant (file CzechVeg-ESy-full-v1.txt) performs the same functions as the basic variant, but in addition, it can also assign the plots not classified by formal definitions based on their numerical similarity to the plots that fulfil the requirements of the formal definitions. Most of such plots can be considered as untypical from the phytosociological point of view, i.e. with poor correspondence to any of the defined vegetation types, in most cases because of the lack of ecologically specialized species. The method of similarity-based assignment is the Frequency-Positive Fidelity Index (FPFI) described in <a href="https://www.sci.muni.cz/botany/chytry/Koci_etal2003_JVS.pdf">Kočí et al. (2003)</a> and <a href="https://doi.org/10.1007/s11258-004-5798-8">Tichý (2005)</a>. Instructions for using CzechVeg-ESy version 1 <ol> <li>Vegetation plots have to be stored in the TURBOVEG 2 program (<a href="https://www.synbiosys.alterra.nl/turboveg/">https://www.synbiosys.alterra.nl/turboveg/</a>) with the species list Czechia-Slovakia-2015 (contained in the file TurbovegSlBackup_Czechia_slovakia_2015.zip), which is largely compatible with the older species lists called Czechia-Slovakia-2012 and Central-Europe.</li> <li>Export plots from TURBOVEG 2 to a CC! file (Export / Other formats / JUICE input files) and import this file to the JUICE program (<a href="https://www.sci.muni.cz/botany/juice/">https://www.sci.muni.cz/botany/juice/</a>) using the species list in the file Checklist-Danihelka-et-al-2012-ver-2019-07-06.txt, which converts the plant nomenclature to correspond with the Checklist of vascular plants of the Czech Republic (<a href="http://www.preslia.cz/P123Danihelka.pdf">Danihelka et al. 2012</a>).</li> <li>Select Analysis / Expert system in the JUICE program.</li> <li>Upload the expert system file (either CzechVeg-ESy-basic-v1.txt or CzechVeg-ESy-full-v1.txt) by pressing Load ES File button.</li> <li>Modify species nomenclature by pressing the Modify Species Names button.</li> <li>If there are juvenile species in the herb layer in the plots to be analysed, delete them by pressing Delete Juveniles button.</li> <li>In some cases, narrow species concepts were changed to broader concepts, resulting in repetitions of the same names in the table. These must be merged using the Merge Same Spec. Names button. This will also merge records of the same species in different vegetation layers because the expert system assumes that each species name is contained only once in the same plot.</li> <li>When using the full version of the expert system, a threshold similarity value for similarity-based assignment must be specified in the field in the bottom right part of the form. The higher the value, the fewer plots will be assigned, while only those plots will be assigned that have a high similarity to the association. If the threshold value is set to 0, all the plots will be assigned, but some of them may be very dissimilar to the associations which they are assigned to.</li> <li>Run expert system using the Classify Relevé button (a plot marked by a previous mouse click will be classified) or Classify [colour] Relevés button (all the plots of the selected colour will be assigned).</li> <li>If a single plot is classified, species groups present in this plot and the assignment of the plot to an association will be shown. If the plot is not classified, no association will be listed. Occasionally, a plot can be assigned to more than one association. If the full version of the expert system is used, the table will contain a list of associations ranked by decreasing similarity to the plot.</li> <li>If multiple plots are classified, association codes will appear in the header of those plots that were assigned based on the formal definitions. The legends for the codes can be found in a printed version of the Vegetation of the Czech Republic, in its online version (<a href="https://pladias.cz/en/vegetation/">https://pladias.cz/en/vegetation/</a>) or in the expert system txt file. Plots not assigned to any association will be marked with ? and those assigned to more than one association will be marked with +. If the full version of the expert system is used, the output will contain the most similar associations for those plots which have remained unassigned to associations or were assigned to more than one association.</li> <li>Using the formal definition, the expert system normally assigns some plots of a single vegetation stand to a certain association while other plots of the same stand remain unassigned. This means that the stand consists of patches with species composition typical of the given association and patches with a less typical species composition. If different plots from a single relatively homogeneous stand are assigned to different associations, it is appropriate to interpret the stand as transitional between these associations.</li> </ol> This electronic publication of CzechVeg-ESy was supported by the Czech Science Foundation (grant no. 17-15168S). *************************************************************************************************************** CzechVeg-ESy je expertní systém pro automatickou klasifikaci fytocenologických snímků z České republiky do vegetačních typů definovaných v monografii Vegetace České republiky (<a href="https://www.sci.muni.cz/botany/vegsci/vegetace.php?lang=en&page=monograph">Chytrý 2007-2013</a>). Existují dvě hlavní verze tohoto expertního systému: Hlavní verze 1 (v1) je originální verze použitá pro klasifikaci v této národní vegetační monografii, která je podrobně popsaná v její metodické kapitole. Její dílčí verze (označené datem) obsahují opravy drobných chyb a nomenklatury druhů. Tato verze klasifikuje fytocenologické snímky pouze do fytocenologických asociací. Hlavní verze 2 (v2) používá stejný klasifikační systém, jaký byl použit ve Vegetaci České republiky, ale používá pokročilej&scaron;í funkce umožňující přesněj&scaron;í klasifikaci. Tato verze také provádí hierarchickou klasifikaci nejen do asociací, ale také do svazů a tříd (pro snímky nezařazené do niž&scaron;ích jednotek). Každá verze má dvě varianty. Základní varianta (soubor CzechVeg-ESy-basic-v1.txt) přiřazuje fytocenologické snímky do asociací na základě jejich formálních definic vytvořených metodou Cocktail (<a href="https://doi.org/10.2307/3236796">Bruelheide 2000</a>) v úpravě podle práce <a href="https://www.sci.muni.cz/botany/chytry/Koci_etal2003_JVS.pdf">Kočí et al (2003)</a>. Tyto definice jsou založeny na prezenci sociologických skupin druhů a dominanci vybraných druhů. Expertní systém vyhodnocuje každý jednotlivý fytocenologický snímek v datovém souboru a řadí jej do asociace. Klasifikace pomocí základní varianty je výrazně rychlej&scaron;í než klasifikace pomocí plné varianty. Plná varianta (soubor CzechVeg-ESy-full-v1.txt) zaji&scaron;ťuje stejné funkce jako základní varianta, ale navíc klasifikuje i snímky neklasifikované formálními definicemi, a to na základě jejich numerické podobnosti ke skupinám snímků, které vyhovují podmínkám formálních definic asociací. Vět&scaron;inu takových snímků lze považovat z fytocenologického hlediska za netypické porosty, tj. takové, které plně neodpovídají definovaným vegetačním typům, zpravidla kvůli absenci ekologicky specializovaných druhů. Klasifikace na základě podobnosti se počítá pomocí indexu FPFI (Frequency-Positive Fidelity Index), který definovali <a href="https://www.sci.muni.cz/botany/chytry/Koci_etal2003_JVS.pdf">Kočí et al. (2003)</a> a <a href="https://doi.org/10.1007/s11258-004-5798-8">Tichý (2005)</a>. <ol> <li>Fytocenologické snímky určené k analýze musí být uloženy v databázi v programu TURBOVEG 2 (<a href="https://www.synbiosys.alterra.nl/turboveg/">https://www.synbiosys.alterra.nl/turboveg/</a>) s druhovým seznamem Czechia-Slovakia-2015 (soubor TurbovegSlBackup_Czechia_slovakia_2015.zip), který je kompatibilní s druhovými seznamy Czechia-Slovakia-2012 a Central-Europe.</li> <li>Snímky se exportují z programu TURBOVEG 2 do souboru CC! (Export / Other formats / JUICE input files) a tento soubor se importuje do programu JUICE (<a href="https://www.sci.muni.cz/botany/juice/">https://www.sci.muni.cz/botany/juice/</a>) s použitím druhového seznamu v souboru Checklist-Danihelka-et-al-2012-ver-2019-07-06.txt, čímž se nomenklatura konvertuje do nomenklatury odpovídající Seznamu cévnatých rostlin květeny České republiky (<a href="http://www.preslia.cz/P123Danihelka.pdf">Danihelka et al. 2012</a>).</li> <li>V programu JUICE se zvolí menu Analysis / Expert system.</li> <li>Tlačítkem Load ES File se nahraje do paměti soubor s příslu&scaron;ným expertním systémem (buď CzechVeg-ESy-basic-v1.txt, nebo CzechVeg-ESy-full-v1.txt).</li> <li>Tlačítkem Modify Species Names se upraví nomenklatura druhů tak, aby odpovídala nomenklatuře používané expertním systémem.</li> <li>Obsahují-li snímky určené k analýze juvenilní dřeviny v bylinném patru, je potřeba je vymazat tlačítkem Delete Juveniles.</li> <li>Při převodu nomenklatury se v některých případech převedlo už&scaron;í pojetí druhů na &scaron;ir&scaron;í, čímž vznikly v tabulce druhové údaje vedené pod stejnými jmény. Ty je potřeba sloučit tlačítkem Merge Same Spec. Names. Přitom se sloučí i údaje stejného druhu v různých patrech, protože expertní systém předpokládá jen jeden výskyt stejného druhového jména v jednom snímku.</li> <li>Pokud je používána plná (Full) verze expertního systému, je potřeba v okénku vpravo dole nastavit prahovou hodnotu podobnosti pro přiřazování snímků k asociacím pomocí podobnosti. Čím vy&scaron;&scaron;í hodnota, tím méně snímků se přiřadí, ale přiřadí se ty, které se dané asociaci více podobají. Při hodnotě 0 se přiřadí v&scaron;echny snímky, ale některé budou dané asociaci velmi nepodobné.</li> <li>Spustí se běh expertního systému, a to buď tlačítkem Classify Relevé (bude se klasifikovat jeden snímek, na který se předtím kliklo my&scaron;í) nebo Classify [colour] Relevés (budou se klasifikovat v&scaron;echny snímky vybrané barvy).</li> <li>Při klasifikaci jednoho snímku se zobrazí v tabulce druhové skupiny, jejich zastoupení v daném snímku a asociace, do které byl snímek přiřazen pomocí formální definice. Pokud přiřazen nebyl, nezobrazí se žádná asociace. Snímek může být přiřazen i do více než jedné asociace. Při použití plné verze expertního systému se do tabulky vypí&scaron;í asociace v pořadí klesající podobnosti ke snímku, a to u těch snímků, které nebyly přiřazeny do žádné asociace nebo byly přiřazeny do více než jedné asociace.</li> <li>Při klasifikaci více snímků se do záhlaví tabulky vepí&scaron;í kódy asociací u těch snímků, které se přiřadily na základě formálních definic. Převod kódů na jména asociací lze dohledat v ti&scaron;těné verzi Vegetace České republiky, v její online verzi (<a href="https://pladias.cz/en/vegetation/">https://pladias.cz/vegetation/</a>) nebo v textovém souboru expertního systému. U snímků, které se nepřiřadily k žádné asociaci, se v záhlaví zobrazí znak ?. U snímků přiřazených do více než jedné asociace se zobrazí znak +. Při použití plné verze expertního systému se do tabulky vypí&scaron;í nejpodobněj&scaron;í asociace u těch snímků, které nebyly přiřazeny do žádné asociace nebo byly přiřazeny do více než jedné asociace.</li> <li>Expertní systém běžně přiřazuje pomocí formálních definic některé snímky v porostu nebo lokálně rozli&scaron;ovaném rostlinném společenstvu do určité asociace a jiné do žádné asociace, což znamená, že se porost skládá z míst s druhovým složením typickým pro danou asociaci a míst s méně typickým druhovým složením. Pokud expertní systém přiřadí různé snímky z jednoho relativně homogenního porostu k různým asociacím, je vhodné porost interpretovat jako přechodný mezi těmito asociacemi.</li> </ol> Tato elektronická publikace expertního systému CzechVeg-ESy byla podpořena Grantovou agenturou České republiky (grant 17-15168S).

opencc-by-4.0Jan 2020View details →

zenodo48/100

Local plot information observed on LandKlif plots during vegetation survey 2019

LandKlif local plot information observed on site during vegetation survey 2019, including vegetation height, slope, aspect, proximity to hedge / forest edge / water, intensity of use (only for meadows), and further information on plot habitat. LandKlif is funded by the Bavarian State Ministry of Science and the Arts within the Bavarian Climate Research Network (bayklif).  Within the five year funding period of bayklif, five interdisciplinary senior research associations and five junior research groups are be financed with a total sum of 18 million Euro. LandKliF, as one of the five interdisciplinary senior research associations, addresses the effects of climate change on biodiversity and ecosystem services in semi-natural, agricultural and urban landscapes.

opencc-by-4.0Mar 2024View details →

openCC (other)Jun 2023View details →

Plot-based vegetation data for a large tract of old--growth hemlock-northern hardwood forest, Marquette Co., Michigan: 1988

In 1987-88 members of the Burton V. Barnes lab at University of Michigan conducted a landscape inventory of portions of the Huron Mountain Club lands (primarily, the self-declared 'Reserved Area') in Powell Township, northern Marquette County, MI. The data-set deposited here, collect under direction of Philip E. Stuart (then a graduate student in the lab) focuses on the ca. 1200 ha of old-growth, mesic hemlock-northern hardwood forests within the larger property. 313 plots (450 m^2) were established at nodes of an approximately 10 chain (~192 m) grid that fell within these forest types. The data-set includes canopy tree measurements, ground-layer cover estimates (for a subpplot), and a number of soil and topographic variables (measured directly and derived). A description of the study and results is published in Simpson et al. 1990. Occasional Papers of the Huron Mountain Wildlife Foundation Number 4, with associated maps.

openOpenAug 2021View details →

[DEPRECATED] Vegetation Plots of the Bonanza Creek LTER Control Plots: Species Count (1975 - 2004) (Reformatted to ecocomDP Design Pattern)

This ecocomDP data package has been deprecated due to issues in the L0 source dataset that prohibits the creation of an L1 ecocomDP dataset. This data package is formatted according to the "ecocomDP", a data package design pattern for ecological community surveys, and data from studies of composition and biodiversity. For more information on the ecocomDP project see https://github.com/EDIorg/ecocomDP/tree/master, or contact EDI https://environmentaldatainitiative.org. This Level 1 data package was derived from the Level 0 data package found here: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-bnz&identifier=175&revision=20 The abstract below was extracted from the Level 0 data package and is included for context: These data are the vegetation datasets for 27 LTER sites in Bonanza Creek Experimental Forest. The 27 sites are divided into three replicates for six primary successional stages on the floodplains (3 replicates X 6 successional stages = 18 sites) and three replicates for three secondary successional stages in the uplands (3 replicates X 3 successional stages = 9 sites). Data include: 1) Visual estimates of percent cover, 2) Stem counts (the number of individuals/species), and 3) Heights (cm) for "tall shrub species" in twenty 4 m2 plots. Shrubs are considered "Tall shrubs" if they are Salix sp., Alnus sp., Rosa acicularis, Viburnum edule, Betula nana, Betula glandulosa, or Rubus idaeus. Initial colonziations plots (FP0s, SL1s, HR1A) were remeasured every year. Early successional plots were remeasured every 2-4 years. Later succesional plots were remeasured approximately every five years. For a detail schedule of plot measurements please see the file: Vegetation Monitoring Schedule.xls Although most sites were established in 1988 some sites have vegetation plots that have been sampled periodically since 1965. In 2006 shrub data collection was changed to a transect method of sampling. These data can be found in the file: <a href="http://www.lte

Vegetation and invertebrate communities in 500 plots in the Duplin and Dean Creek watersheds: ground truth data for matching hyperspectral imagery

We measured characteristics of vegetation (Aster tenuifolius, Batis maritima, Borrichia frutescens, Distichlis spicata, Iva frutescens, Juncus roemerianus, Limonium carolinianum, Salicornia biglovii, Salicornia virginica, Spartina alterniflora, Spartina patens, Sporobolus virginicus), soil (salinity, proportion organic and proportion water) and densities of common gastropods and bivalves in 500 plots in the Duplin and Dean Creek watersheds on Sapelo Island on June 20-26, 2006. Plot locations were determined using a high precision hand-held GPS. These data were used to help ground-truth hyperspectral aerial images collected at the same time by Dr. John Schalles.

Soil salinity and organic content at GCE-LTER vegetation monitoring plots in October 2009

Soil samples were collected in conjunction with Fall 2009 plant monitoring at half of the permanent vegetation monitoring plots in the creekbank and midmarsh zones at 10 GCE study sites. Pore-water salinity was determined by analysis of supernatant salinity in dried soil samples hydrated with a measured volume of deionized water. Organic content was measured gravimetrically by comparing ash-free dry weight and total weight of soil samples.

Soil salinity and water content at GCE-LTER vegetation monitoring plots in October 2010

Soil samples were collected in conjunction with Fall 2010 plant monitoring at half of the permanent vegetation monitoring plots in the creekbank and midmarsh zones at 10 GCE study sites. Pore-water salinity was determined by analysis of supernatant salinity in dried soil samples hydrated with a measured volume of deionized water.

Soil salinity and organic content at GCE-LTER vegetation monitoring plots in October 2011

Soil samples were collected in conjunction with Fall 2011 plant monitoring at half of the permanent vegetation monitoring plots in the creekbank and midmarsh zones at 10 GCE study sites. Pore-water salinity was determined by analysis of supernatant salinity in dried soil samples hydrated with a measured volume of deionized water. Organic content was measured gravimetrically by comparing ash-free dry weight and total weight of soil samples.

Soil salinity at GCE-LTER vegetation monitoring plots in October 2012

Soil salinity at GCE-LTER vegetation monitoring plots in October 2013

Soil samples were collected in conjunction with Fall 2013 plant monitoring at half of the permanent vegetation monitoring plots in the creekbank and midmarsh zones at 10 GCE study sites. Pore-water salinity was determined by analysis of supernatant salinity in dried soil samples hydrated with a measured volume of deionized water.

Soil salinity at GCE-LTER vegetation monitoring plots in October 2014

Soil samples were collected in conjunction with Fall 2014 plant monitoring at half of the permanent vegetation monitoring plots in the creekbank and midmarsh zones at 10 GCE study sites. Pore-water salinity was determined by analysis of supernatant salinity in dried soil samples hydrated with a measured volume of deionized water.

openCC (other)Nov 2023View details →

El Verde Coffee Plantation permanent plot vegetation sampling

Permanent plot data is expected to show (1) rapid increases in percent cover and tree stem density, and (2) rapid turnover from early to late successional plant species. Plant-plant competition indices should show quick increases in intensity with exotics as top competitors which may lead to exclusion of some trees common after landslide and pasture 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. Because of increased nitrogen levels due to plantings of Inga Sp. with coffee, trees should grow, as measured by biomass (productivity), height and basal diameter increases, significantly faster compared to landslide. 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.

openCC (other)Nov 2023View details →

Ecuador old fields 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 exotics 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 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.

openCC (other)Nov 2023View details →

Long-Term Elevation Plots (LTEP) (Altitudinal transects vegetation data along three rivers in the Luquillo Experimental Forest)

The composition of plant communities changes with elevation in the Luquillo Experimental Forest (LEF). The goal of this project is to document the patterns of these changes, and in particular, to determine whether the distributions of individual species are independent of one another, or whether they are related, in either a congruent or a hierarchical manner. Thirty-two permanent vegetation plots, each 50m by 20m are being established in the LEF, with 5 plots along the Icacos river, 11 along the Mamayes river and 16 along the Sonadora stream. The plots were established at every 100m in elevation, starting at 200m above sea level. All woody, free-standing stems greater than 1cm dbh were marked, identified and mapped into 5x5 subquadrats. We anticipated that gradient analysis will show whether the distributions of species are coincident or independent, enabling us to evaluate whether separate, genuine plant communities exist in the LEF. Because the plots are permanent, we also expected that they allow us to better evaluate how different vegetation types, at different elevations, respond to large scale disturbances, especially hurricanes. 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.

openNov 2023View details →

Revegetation of landslides, vegetation <0.1m (Small landslide plots at the Luquillo Experimental Forest)

The purpose of this study is to document the recovery of vegetation on new landslides in the Luquillo Experimental Forest, in particular seedlings less then 1m tall. 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.