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20 results for “canopy gaps”
Data from paper: "Large-scale variations in the dynamics of Amazon forest canopy gaps from airborne lidar data and opportunities for tree mortality estimates"
<p>Data from the paper:</p> <p>Dalagnol, R. <em>et al.</em> Large-scale variations in the dynamics of Amazon forest canopy gaps from airborne lidar data and opportunities for tree mortality estimates. <em>Sci Rep</em> <strong>11, </strong>1388 (2021). https://doi.org/10.1038/s41598-020-80809-w</p> <p>Link: https://www.nature.com/articles/s41598-020-80809-w</p> <p> </p> <p>This repository contains:</p> <p>1) Data frame with data from static and dynamic gaps used in Figure 2 (Dalagnol_2020_Data_Multitemporal_gaps.csv). Each row is the aggregated measurement at 5-km resolution. The site component referes to the five site studied with multitemporal data. Site order from 1 to 5 is DUC, TAP, FN1, BON and TAL.</p> <p>2) Data frame with data from static gaps and environmental factors used in Table 1, Figure 3, 4, 5 (Dalagnol_2020_Data_Singledate_gaps_Modeling.csv). Each row is the aggregated measurement of one site observed by airborne lidar data.</p> <p>3) Raster file at 5-km resolution with dynamic gap fraction estimates presented in Figure 5 (dynamic_gap_fraction_amazon.tif).</p> <p> </p> <p>If you need anything else, please contact the corresponding author: Ricardo Dalagnol (ricds@hotmail.com).</p>
Canopy gap sizes across the Brazilian Amazon
<p>This data frame contains the raw gap data used to study the gap size-frequency distributions across the Brazilian Amazon in:</p> <p>Reis, C., Jackson, T., et al 2022. Forest disturbance and growth processes are reflected in the geographic distribution of large canopy gaps across the Brazilian Amazon. Journal of Ecology. </p> <p>They gaps were extracted from the EBA LiDAR data set https://zenodo.org/record/4968706#.YygSGHZKg5s</p>
Annual measurements of vegetation canopy and basal gap intercepts from the three Conmod Pilot study locations at Jornada Basin LTER, 2008-2016
This data package contains annual measurements of vegetation canopy and basal gap sizes from transects at the Connectivity Modifier (Conmod) Pilot study on the Jornada Experimental Range from 2008-2016. There were 3 sites for this study: Gravelly Ridges, Aeolian, and Dona Ana. Within each site, there were 8 study plots, 4 of which were treatment plots where connectivity modules (conmods) were installed to decrease gap sizes between perennial vegetation. The plots were 8 x 8 meters and had an 8 x 8 meter buffer zone on both sides of the plot (upwind and downwind). Beginning in 2008, vegetation canopy and basal gap sizes were collected annually in all plots using the gap intercept method. These data were collected in 2008-2010, 2012 and 2016. At each plot, four parallel 24-meter transects crossing the upwind buffer, the plot, and the downwind buffer were measured. These parallel transects were spaced at 0.8, 2.8, 4.3, and 7.2 meter intervals across the plot and buffer areas. This study is complete (finished in 2016) and was the pilot study to the newer Cross Scale Interactions Study.
Canopy gap survey at El Verde
The survey of gaps at El Verde covers about 35 ha, including the 9 ha grid. We defined a treefall gap at El Verde as a hole in the forest canopy extending down to an average height of about 3 m or less above ground. The edge of a gap was delineated by the vertical projection of the edge of the canopy foliage. We measured the dimensions ofs present in the 35-ha study site in August 1989, one month before Hurricane Hugo. For each gap we measured L, the longest axis of the gap (distance between edges), and W, the longest axis perpendicular to L, and then approximated gap area as that of an ellipse: Area = p LW/4 (Runkle 1992). Only openings ³ 20 m2; were counted as gaps. 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.
Sapling regeneration within canopy gaps in a temperate montane riparian forest.
<p>This is a dataset of sapling regeneration within canopy gaps in a temperate montane riparian forest.</p> <p>The followings are details of each file.</p> <p><strong>GapSeedlings_v1.0.0.csv</strong></p> <ul> <li><code>Plot</code> Integer. The ID of plots, some plots include more than one gap.</li> <li><code>Gap</code> Factor. The ID of gaps.</li> <li><code>Quadrat</code> Integer. The ID of quadrats within a gap.</li> <li><code>stemID</code> Character. The ID of stems.</li> <li><code>Sp.</code> Factor. The species names.</li> <li><code>Family</code> Factor. The family name of the species.</li> <li><code>Substrate</code> Factor. Established substrates. NA means that it was not recorded.</li> <li><code>Heightyyyy</code> Numeric. Vertical heights of trees (cm) in yyyy. The individuals with <code>CensusIn2020</code> = 0, their <code>Height2020</code> is NA because they had not been censused in 2020.</li> <li><code>Lengthyyyy</code> Numeric. Length of trees (cm) in yyyy. The individuals with <code>CensusIn2020</code> = 0, their <code>Length2020</code> is NA because they had not been censused in 2020.</li> <li><code>DBH1_yyyy</code>, <code>DBH2_yyyy</code> Numeric. Diameter at breast height (mm) in yyyy. DBH1 and DBH2 were measured to cross at right angles. The individuals with <code>CensusIn2020</code> = 0, their <code>DBH2020_1</code> and <code>DBH2020_2</code> are NA because they had not been censused in 2020.</li> <li><code>Cmtyyyy</code> Character. Comments in yyyy.</li> <li><code>CensusIn2020</code> Factor. 1 means that the plot was censused in 2020, 0 does not.<br> </li> </ul> <p><strong>Map_Gaps.pdf</strong><br> <code>p. 1</code>: The overall picture of the positional relations between each gap.<br> <code>pp. 2-19</code>: The details of gaps.</p> <p> </p> <p><strong>Metadata_GapSeedlings.txt</strong><br> Metadata of "<strong>GapSeedlings_v0.1.0.csv</strong>".<br> It is the same as this description.</p>
Canopy gaps facilitate upslope shifts in montane conifers but not in temperate deciduous trees in the Northeastern United States
<p>Many montane tree species are expected to migrate upslope as climate warms, but it is not clear if forest canopy gaps, which can facilitate tree seedling recruitment, serve as an important mechanism driving tree species range shifts. Patterns of tree seedling establishment can inform us about early stages of tree species migrations and are critical to examine in the context of global climate change.</p> <p>We contrasted elevational distributions of tree seedlings both within and outside of forest canopy gaps with the distributions of conspecific adults and saplings across the deciduous-coniferous ecotone on ten mountains in four states of the northeastern United States. We tested if seedling distributions of four dominant tree species (<em>Abies balsamea, Picea rubens, Acer saccharum</em>, and<em> Fagus grandifolia</em>) were shifted upslope of conspecific adult and sapling distributions. We also examined if this shift was facilitated by canopy gaps and what environmental drivers affected species distributions.</p> <p>There was limited seedling recruitment of dominant tree species at the temperate-coniferous ecotone, which we attributed to (i) an observed downslope shift of seedling distributions of the low-elevation deciduous species (<em>Acer saccharum, Fagus grandifoli</em>a) and (ii) an upslope shift in seedling distributions of the high-elevation conifers (<em>Abies balsamea, Picea rubens</em>). The upslope shift of conifer seedlings contrasts with our previous research at these sites which observed downslope shifts of sapling distributions in <em>Picea rubens</em>, suggesting that seedlings may be responding to more recent climate warming. Canopy gaps in high-elevation conifer forests facilitated these upslope shifts by promoting conifer seedling recruitment. However, gaps at lower elevations did not play a significant role in seedling recruitment or the observed downslope shifts of the dominant deciduous species. Climate was the dominant predictor of adult tree distributions whereas both climate and soil were important predictors of seedling distributions.</p> <p><strong><em>Synthesis</em></strong>. Our study illustrates that tree seedlings have the potential for monitoring the early stages of tree species migrations, and particularly so in canopy gaps in high-elevation conifer forests. Further, we stress that species range shifts are sensitive to local scale heterogeneity in light availability (i.e., canopy gaps) and other non-climatic factors.</p>
Data for linked disturbance in the temperate forest: earthworms, deer, and canopy gaps
<p>Despite the large body of theory concerning multiple disturbances, there have been relatively few attempts to test the theoretical assumptions of how and if disturbances interact. Of particular importance is whether disturbance events are linked, as this can influence the probability and intensity of ecological change. Disturbances are linked when one disturbance event increases or decreases the likelihood or extent of another. To this end, we used two long-term, multi-disturbance experiments in northern Wisconsin to determine whether earthworm invasion is linked to canopy gap creation and white-tailed deer browsing. These three disturbances are common and influential within North American temperate forests, making any interactions among them particularly important to understand. We expected both deer and canopy gaps to favor invasive earthworms, particularly species that live close to or on the soil surface. However, we found only partial support for our hypotheses, as both deer exclosures and canopy gaps decreased earthworms in each experiment. Further, earthworm density increased the most over time in areas far from the gap center and in areas with deer present. Deer exclosures primarily decreased <em>Aporrectodea</em> and <em>Lumbricus</em> species, while gaps decreased <em>Dendrobaena</em> and <em>Lumbricus</em> species. Our findings show that earthworm invasion is linked to deer presence and gap-creating disturbances, which provides new insight toward multiple disturbance theory, aboveground-belowground dynamics, and temperate forest management.</p>
Multiple disturbances, multiple legacies: Fire, canopy gaps and deer jointly change the forest seed bank
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Data for linked disturbance in the temperate forest: earthworms, deer, and canopy gaps
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Canopy gaps facilitate upslope shifts in montane conifers but not in temperate deciduous trees in the Northeastern United States
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Snow pit dataset from "Comparison of snowpack structure in gaps and under the canopy in a humid boreal forest"
<p>This original dataset contains snow pit measurements collected at Montmorency Forest (47.29°N, 71.17°W) from 22 November, 2018 to 6 June, 2019. The study site is a balsam fir – whit birch stand on a 12° slope of north-east aspect. The dataset is described in the publication “<strong><em>Comparison of snowpack structure in gaps and under the canopy in a humid boreal forest</em></strong>” from Bouchard et al., 2022. In this dataset you can find:</p> <p> </p> <ul> <li>inside forest gaps: <ul> <li>26 snow height measurements (26 data points)</li> <li>26 snowpack stratigraphy (380 data points)</li> <li>26 snow temperature profiles (427 data points)</li> <li>26 snow density profiles (803 data points)</li> <li>2 snow specific surface area (SSA) profiles (97 data points)</li> </ul> </li> </ul> <p> </p> <ul> <li>under the canopy: <ul> <li>26 snow height measurements (26 data points)</li> <li>26 snowpack stratigraphy (227 data points)</li> <li>26 snow temperature profiles (325 data points)</li> <li>26 snow density profiles (623 data points)</li> <li>2 snow SSA profiles (89 data points)</li> </ul> </li> </ul> <p> </p> <p>For density measurements, the height value corresponds to the center of the 3-cm thick box cutter. For the SSA, the value is measured optically at the top of the sample. This value is representative of the top 1 cm of the snow sample, as this is the typical e-folding depth of 1310 nm radiation in snow. Grain type codes for the snowpack stratigraphy corresponds to the <em>International Classification for Seasonal Snow </em>(Fierz et al., 2009):</p> <p> </p> <ul> <li>PP: Precipitation particle</li> <li>DF: Decomposed and Fragmented precipitation particles</li> <li>RG: Rounded Grains</li> <li>FC: Faceted Crystals</li> <li>DH: Depth Hoar</li> <li>MFpc: Melt Forms – rounded polycrystals</li> <li>MFcl: Melt Forms – clustered rounded grains</li> <li>MFcr: Melt Forms – melt-freeze crusts</li> <li>IF: Ice Formations</li> </ul>
A modified Beer–Lambert–Bouguer law for nonrandom distributions and its application in gap probability calculations for heterogeneous canopies
<p>This repository contains the data, codes and files required to reproduce the results of the manuscript "A modified Beer–Lambert–Bouguer law for nonrandom distributions and its application in gap probability calculations for heterogeneous canopies" submitted to the Journal of Advances in Modeling Earth Systems (JAMES).</p>
Data and Script used in "Effects of canopy gaps on microclimate, soil biological activity and their relationship in a European mixed floodplain forest"
<p>The R code and data provided in this repository allow to reproduce the data carpentry, analysis and visualization of “Effects of canopy gaps on microclimate, soil biological activity and their relationship in a European mixed floodplain forest” (https://doi.org/10.1016/j.scitotenv.2024.173572).</p> <p> </p> <p>Folder structure</p> <p> </p> <p>Data abstracts:</p> <p>Data_abstract_climate.pdf</p> <p>Data_abstract_soil_biotics.pdf</p> <p>Data_abstract_soil_abiotics_openness.pdf</p> <p> </p> <p>Data:</p> <p>Climate_data.xlsx</p> <p>Soil_biotics.xlsx</p> <p>Soil_abiotics_openness.xlsx</p> <p> </p> <p>R Scripts:</p> <p>00-preamble.R loads all required packages</p> <p>01-data-carpentry.R loads all datasets and prepares the analysis of all experimental periods.</p> <p>02-data-analyses-microclimate.R compares understorey air and soil microclimate between forest types and treatments, presents diurnal and seasonal variations and tests the relationship of under- and overstorey openness on microclimate.</p> <p>03-data-analyses-decomposition.R compares decomposition rates and feeding activity between forest types and treatments and models the dependencies of soil biological activity on microclimate and soil abiotic factors.</p> <p> </p> <p>Information of related software and package versions used in the script:<br>R version 4.3.2 (2023-10-31 ucrt)<br>Platform: x86_64-w64-mingw32/x64 (64-bit)<br>Running under: Windows 10 x64 (build 19045)<br>Matrix products: default</p> <p> </p> <p>Contact</p> <p>Please contact me at annalena.lenk@uni-leipzig.de if you have further questions.</p>
Data for: Characterizing individual tree-level snags using airborne lidar-derived forest canopy gaps within closed-canopy conifer forests
<p><span>1. Airborne lidar is often used to calculate forest metrics about trees but it may also provide a wealth of information about the space between trees. Forest canopy gaps are defined by the absence of vegetative structure and serve important roles for wildlife, such as facilitating animal movement. Forest canopy gaps also occur around snags, keystone structures that provide important substrates to wildlife species for breeding, roosting, and foraging.</span></p> <p><span>2. We wanted to test a method for quantifying canopy gaps around individual snags and live trees, with the working hypothesis that snags would have more gaps surrounding them overall than live trees. We evaluated canopy gaps around individual snags (n=270) and live trees (n=2186) and evaluated correlations between canopy structure and snag occurrence in dense conifer stands of the Idaho Panhandle National Forest, USA. We paired airborne lidar with ground reference data collected at fixed-radius plots (n=53) to evaluate local gap structure. The R package ForestGapR was used to quantify canopy gaps throughout the canopy to determine where the differences were greatest. A canopy space profile was created for each tree by mapping gaps (a) vertically every 2 m in height (2–50 m above ground), and (b) horizontally across small (16 m<sup>2</sup>), medium (36 m<sup>2</sup>), and large (64 m<sup>2</sup>) footprint sizes.</span></p> <p><span>3. Our results suggest this method is robust for quantifying canopy gaps around individual trees. The canopy space profiles were distinctly different for snags and live trees, with more canopy gaps within the area surrounding snags relative to live trees. The greatest differences occurred at mid-canopy heights (~20 m above ground) and at the smallest footprint size (16 m<sup>2</sup>).</span></p> <p><span>4. These results show potential to improve understanding of gap dynamics in closed-canopy conifer forests, and we suggest snag modeling could be improved by incorporating lidar-derived canopy gap analyses alongside existing methodologies.</span></p>
Data for: Characterizing individual tree-level snags using airborne lidar-derived forest canopy gaps within closed-canopy conifer forests
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Canopy size, gap size, plant height, and scaled height in NEAT plots at Jornada Basin LTER, Summer 2017
This data package contains estimates of vegetation indicators derived from UAV overflights and comparable field observatons at the NEAT experiment in the Jornada Basin of southern New Mexico, USA. The purpose of this study is to develop a UAV-based remote sensing method that can estimate vegetation indicators in arid and semiarid rangelands. This method was used to characterize six rangeland indicators (canopy size, bare soil gap size, plant height, scaled height, vegetation cover, and bare soil cover) in a semiarid grass-shrub ecosystem at the NEAT site. The drone-based estimates were validated with field measurements by using the standard transect methods (gap intercept, drop disk, and line-point intercept methods) in the spring and summer of 2017. Further, we use these results to show possible applications of drone-based products on arid and semiarid rangelands: the spatially explicit input of an ecological model, to detect and characterize non-stationarity, and to detect landscape anisotropy.
Legacy effects of canopy gaps on liana abundance 25 years later in a seasonal tropical evergreen forest in northeastern Thailand
<p><span>Liana</span><span>s </span><span>require host trees to reach and stay in the forest canopy, but as seedlings and juveniles, they benefit from canopy gaps created by treefalls</span><span>.</span><span> Here, we evaluated the relative importance of these two aspects, i.e., the availability of potential</span><span> hosts</span><span> vs. the legacy effect of past treefall gaps, on the local abundance of liana stems in a seasonal tropical evergreen forest in the Sakaerat Biosphere Reserve in northeastern Thailand. Within a 2.5-ha plot for forest dynamics monitoring, canopy height was measured in 1993 and 2018 at 5-m intervals to distinguish areas of mature (canopy height </span><span>≥</span><span> 20 m), building (10-20 m), and gap phases (< 10 m). In 2017–2018, we surveyed all liana stems </span><span>≥</span><span> 1 cm in diameter at breast height within 50 subplots (10 m × 10 m each) and recorded their diameter and the diameter of the host tree. Of a total of 445 liana individuals, 242 could be identified at least to the family level, while the others had clear morphological traits of climbing mechanisms. The number of liana stems was higher in areas that had been at the building/gap phase than those at the mature phase in 1993. When this 25-year-old legacy of past gap locations was considered, there was a positive association of local abundance between lianas and trees in areas at the mature phase in 2018. In conclusion, liana abundance reflected a long-term legacy of past treefall gaps more than 25 years earlier in this seasonal evergreen forest.</span></p>
Legacy effects of canopy gaps on liana abundance 25 years later in a seasonal tropical evergreen forest in northeastern Thailand
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Non-local Impacts of Gaps on Submerged Canopy Flow
<p>The folders include all the Vectrino measurements/records used for the paper, "Non-local Impacts of Gaps on Submerged Canopy Flow". Each folder has the the filtered data with the naming convention, '[gapsize]_[dist downstream]_[z(height from bed].mat'. There are separate folders for Set A and Set B experiments, which separate into the medium and fast flow speeds. There are homogenous measurements as well.</p>
Data from: Canopy disturbance and gap partitioning promote the persistence of a pioneer tree population in a near-climax temperate forest of the Qinling Mountains, China
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