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58 results for “vegetative growth”
Long-term growth, mortality and regeneration of trees in permanent vegetation plots in the Pacific Northwest, 1910 to present
A network of more than 130 permanent vegetation plots provides long-term information on patterns and rates of forest succession in most of the major forest zones of the Pacific Northwest. The plot network extends from the coast to the Cascades in western Oregon and Washington and east to ponderosa pine forests in the Oregon Cascades. Most of the permanent plots were established during two intervals: from 1910 to 1948, and from 1970 to 1989. The earlier plots were established by U.S. Forest Service researchers to quantify timber growth in young stands of important commercial species and to help answer other applied forestry questions. The more recent period of plot establishment began under the Coniferous Forest Biome program of the International Biological Program during the 1970s, and continued under the Long-term Ecological Research program. A broader set of objectives motivated plot establishment since 1970, especially quantification of composition, structure, and population and ecosystem dynamics of natural forests. Plots have one of three spatial arrangements: (1) contiguous rectangles subjectively placed within an area of homogeneous forest; (2) circular plots subjectively placed within an area of homogeneous forest; and (3) circular plots systematically located on long transects to sample an entire watershed, ridge, or reserve. Rectangular study areas are mostly 1.0 ha or 0.4 ha (1.0 ac) in size (slope-corrected). Circular plots are 0.1 ha (0.247 ac), not corrected for slope. The tree stratum is the focus of work in closed-forest study areas. All trees larger than a minimum diameter (5 cm for most areas) are permanently tagged. Plots are censused every 5 or 6 years. Attributes measured or assessed at each census include tree diameter, tree vigor, and the condition of the crown and stem. The same attributes are recorded for trees (ingrowth) that have exceeded the minimum diameter since the previous census. In many plots tree locations are surveyed to provide a
Phenology and Vegetation Growth in Prospect Hill Soil Warming Experiment at Harvard Forest 1992-1993
As the mean annual temperature of northeast North America rises as a component of global climatic change, it is important to understand how the predominant vegetation of the region will be affected. Existing experimental and correlative evidence from field sites suggests that temperature rise will significantly modify soil processes, nutrient availability, and plant growth. We investigated the responses of temperate deciduous forest vegetation to artificial soil warming at 20 sampling dates during the 1992 and 1993 growing season. We explored whether soil warming measurably altered growth and the temporal dynamics of leaf and fruit production in 26 species of three contrasting plant growth forms (herbaceous perennials, shrubs, and canopy trees). We hypothesized that soil warming would exert differential effects on emergence, phenology, leaf expansion rates, growth, photosynthesis, and vegetative and sexual reproduction among species, with implications for changing community structure in these forests. Timing of leaf emergence and flower production was not affected by treatment in saplings; however, mature trees and shrubs leafed out slightly earlier and in larger numbers in heated plots. Soil warming significantly enhanced relative growth in stem diameters of woody plants, especially shrubs, in 1992. This effect was less pronounced in 1993. Species richness was lower in heated plots than in intact control plots in both years; disturbed but unheated control plots showed the lowest species richness of all plots. Changes in relative abundance of herbaceous species from 1992 to 1993 were not significantly affected by treatment. Rank abundances of species were more stable between years in the heated and disturbance-control plots than in the intact plots. Total density of herbaceous species was highest in heated plots during April and May of both years, reflecting greatly accelerated emergence of two dominant species, Maianthemum canadense and Uvularia sessilifolia, due t
Towers Forestry Plot, Long-term Vegetation Monitoring in a 1-ha old-growth Rainforest, La Selva Research Station, OTS, Sarapiquí, Heredia, Costa Rica, 2010–2020
The Towers Plot is a 1-hectare permanent vegetation plot established in 2010 under the canopy towers at La Selva Research Station, Sarapiquí, Heredia, Costa Rica. The plot was created by the Organization for Tropical Studies (OTS) to monitor long-term changes in forest structure, composition, and dynamics in an old-growth tropical rainforest. All woody stems with a diameter at breast height (DBH) of 10 cm or greater—including trees, palms, and lianas—were tagged, mapped, and measured following standardized procedures. Censuses were conducted between 2010 and 2020 to document growth, mortality, and recruitment. The dataset includes taxonomic identifications, stem diameter measurements, spatial coordinates within the plot, and metadata describing field methods and species composition. The plot was established beneath three canopy towers that had been previously constructed through the NSF-funded Major Research Instrumentation (MRI) project, NSF 0722741, which provided key infrastructure for canopy and environmental research at La Selva. This proximity created a valuable opportunity to integrate vegetation monitoring with existing environmental instrumentation. Johana Hurtado, coordinator of the Tropical Ecology, Assessment and Monitoring (TEAM) project at La Selva, collaborated with OTS staff in the establishment of the plot, ensuring methodological consistency with other tropical forest monitoring sites. This dataset provides a comprehensive record of woody plant diversity and forest structure in a lowland old-growth Neotropical rainforest. It supports research on forest dynamics, carbon storage, and ecosystem change. The overall monitoring project is ongoing; this data package contains observations from 2010 through 2020.
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.
Geographical variation in vegetative growth and sexual reproduction of the invasive Spartina alterniflora in China
We studied patterns in vegetative growth and sexual reproduction of introduced S. alterniflora at 22 sites at 11 geographic locations over a latitudinal gradient of ~2000 km from Tanggu (39.05 °N, high latitude) to Leizhou (20.90 °N, low latitude) in China. We further evaluated the basis of phenotypic differences by growing plants from across the range in a common garden for 2 growing seasons. We found distinct latitudinal clines in plant height, shoot density, and sexual reproduction across latitude. Some traits exhibited linear relationships with latitude; others exhibited hump-shaped relationships. We identified correlations between plant traits and abiotic conditions such as mean annual temperature, growing degree days, tidal range, and soil nitrogen content. However, geographic variation in all but one trait disappeared in the common garden, indicating that variation largely due to phenotypic plasticity. Only a slight tendency for latitudinal variation in seed set persisted for two years in the common garden, suggesting that plants may be evolving genetic clines for this trait. Note that these data were collected as part of a National Natural Science Foundation of China (NSFC) funded study led by Yihui Zhang in collaboration with GCE-LTER.
Can Artificial Intelligence help in the study of vegetative growth dynamics from herbarium collections? An evaluation of the tropical flora of the French Guiana forest
<p>Dataset was used for the article "Can Artificial Intelligence help in the study of vegetative growth dynamics from herbarium collections? An evaluation of the tropical flora of the French Guiana forest".</p> <p>The related work proposes to study to what extent the use of automated visual analysis techniques, based on deep learning, can help not only to detect relatively rare vegetative structures in herbarium collections but also to automatically classify them by type of growing shoot (continuous or rhythmic).</p> <p>Abstract of the paper:</p> <p>A better knowledge of tree vegetative growth patterns and their relationship to environmental variables is crucial in understanding forest growth dynamics and how climate change may affect them. Generally less studied than reproductive structures, the phenology of tree vegetative growth mainly focuses on the analysis of growing shoots, from vegetative buds development to leaf fall. This growth process usually strongly differs between temperate and tropical regions. In temperate regions, this pattern is quite well known. Low winter temperatures impose a stop of the vegetative growth shoots and lead to the typical expression of an annual growth cycle for the vast majority of tree species. In moist tropical regions, on the other hand, the seasonality is much less marked. In addition, these regions contain a much wider variety of tree species. These two aspects lead to a tremendous diversity of phenological patterns that are still poorly known and understood. In particular, not much is known on the periodicity and timing of growth at individual trees, population, or community levels.</p> <p>The work carried out in this study aims to advance knowledge in this area, focusing more particularly on herbarium scans, as herbarium collections offer the promise of monitoring plant phenology over long time periods. However, such a study requires the ability to detect a sufficiently large number of growing shoots in herbarium collections to draw statistically relevant conclusions, which can be very costly if the work is done manually. Furthermore, herbarium collections traditionally focus on reproductive organs, and herbarium specimens showing growing shoots are pretty rare.</p> <p>We propose in this paper to study to what extent the use of automated visual analysis techniques, based on deep learning, can help not only to detect these relatively rare vegetative structures in herbarium collections but also to automatically classify them by type of growing shoot (continuous or rhythmic). Our results show the relevance of using herbarium data for vegetative phenology research, as well as the potential of deep learning approaches for growth shoot detection.</p>
Locally adaptive temperature response of vegetative growth in Arabidopsis thaliana
<p>We investigated early vegetative growth of natural <em>Arabidopsis thaliana</em> accessions in cold, non-freezing temperatures, similar to temperatures these plants naturally encounter in fall at northern latitudes.</p> <p>Dataset includes:<br> - rosette area measurements over 3 weeks in a 16ºC and a 6ºC treatment. First phenoptying time point is at 14 days after stratification. Measurements were take twice per day.<br> These data are in file <a href="https://zenodo.org/api/files/54fc7139-99a8-4e7f-af87-d6754031f5d9/rawdata_combined_annotation.txt?versionId=7b707f81-723f-4059-b72b-9dfb9f5ddd2e">rawdata_combined_annotation.txt</a> and go together with <a href="https://zenodo.org/api/files/54fc7139-99a8-4e7f-af87-d6754031f5d9/outliers.csv?versionId=7287c919-1ed1-4b65-8e25-a75bb312c8fa">outliers.csv</a>, which contains outlying datapoints.</p> <p>- Seed Size measurements.<br> These data are in file <a href="https://zenodo.org/api/files/54fc7139-99a8-4e7f-af87-d6754031f5d9/seed_size_swedes_lab_updated.csv?versionId=fb739477-862b-45cb-8074-7a1d8e1650bb">seed_size_swedes_lab_updated.csv </a><br> </p> <p>The remainnig files are required to rerun the analyses and recreate figures.<br> Scripts to do so can be found in https://github.com/picla/growth_16C_6C/</p> <p><a href="https://zenodo.org/api/files/54fc7139-99a8-4e7f-af87-d6754031f5d9/1001genomes-accessions.csv?versionId=ee605038-bd9e-448f-9c96-1a8e980c1755">1001genomes-accessions.csv</a>: lists all accession from the 1001genomes project and their respective subpopulations.</p> <p><a href="https://zenodo.org/api/files/54fc7139-99a8-4e7f-af87-d6754031f5d9/2029_modified_MN_SH_wc2.0_30s_bilinear.csv?versionId=73c6c2bf-97bd-425f-bf7e-14b5a7cb162f">2029_modified_MN_SH_wc2.0_30s_bilinear.csv</a>: contains climate data for each accession, downloaded and prcocessed from www.worldclim.org</p> <p><a href="https://zenodo.org/api/files/54fc7139-99a8-4e7f-af87-d6754031f5d9/metabolic_distance.csv?versionId=8456f998-d0dc-4a80-b96f-c0c66c1c9731">metabolic_distance.csv</a>: contains the metabolic distance as calculated in Weiszmann et al. (https://www.biorxiv.org/content/10.1101/2020.09.24.311092v1)</p> <p><a href="https://zenodo.org/api/files/54fc7139-99a8-4e7f-af87-d6754031f5d9/RNAseq_samples.txt?versionId=6ae1518b-1a70-440d-b0bd-0ccdcb66665e">RNAseq_samples.txt</a>: sample description of the RNA-seq samples (data is downloadable from <a href="http://www.ncbi.nlm.nih.gov/bioproject/807069">http://www.ncbi.nlm.nih.gov/bioproject/807069)</a></p> <p><a href="https://zenodo.org/api/files/54fc7139-99a8-4e7f-af87-d6754031f5d9/ZAT12_downregulated_table10.csv?versionId=c6f7aa54-cb07-4378-a5a0-de12c6979b9b">ZAT12_downregulated_table10.csv</a>, <a href="https://zenodo.org/api/files/54fc7139-99a8-4e7f-af87-d6754031f5d9/ZAT12_upregulated_table9.csv?versionId=911a2aa2-f08f-4a20-85de-cfa7c58b73a8">ZAT12_upregulated_table9.csv</a>, <a href="https://zenodo.org/api/files/54fc7139-99a8-4e7f-af87-d6754031f5d9/CBF_regulon_DOWN_ParkEtAl2015.txt">CBF_regulon_DOWN_ParkEtAl2015.txt</a>, <a href="https://zenodo.org/api/files/54fc7139-99a8-4e7f-af87-d6754031f5d9/CBF_regulon_UP_ParkEtAl2015.txt?versionId=f7cacbda-eea6-4ac9-8f71-5ba74e3a67c4">CBF_regulon_UP_ParkEtAl2015.txt, </a><a href="https://zenodo.org/api/files/54fc7139-99a8-4e7f-af87-d6754031f5d9/CBF2_downregulated_table8.csv">CBF2_downregulated_table8.csv, </a><a href="https://zenodo.org/api/files/54fc7139-99a8-4e7f-af87-d6754031f5d9/CBF2_upregulated_table7.csv">CBF2_upregulated_table7.csv, </a><a href="https://zenodo.org/api/files/54fc7139-99a8-4e7f-af87-d6754031f5d9/HSFC1_regulon_ParkEtAl2015.txt">HSFC1_regulon_ParkEtAl2015.txt</a>: these files list genes that are involve din cold acclimation as described by Park et al. (https://onlinelibrary.wiley.com/doi/10.1111/tpj.12796), and Vogel et al.(https://onlinelibrary.wiley.com/doi/10.1111/j.1365-313X.2004.02288.x).</p> <p><strong>Material and Methods</strong></p> <p><em><strong>Rosette growth</strong></em></p> <p>Seeds of 249 natural accessions (Suppl. Data 1) of <em>Arabidopsis thaliana</em> described in the 1001 genomes project <a href="https://paperpile.com/c/UDgV3V/DUBI">(1001 Genomes Consortium 2016)</a> were sown on sieved (6 mm) substrate (Einheitserde ED63). Pots were filled with 71.5 g ±1.5 g of soil to assure homogenous packing. The prepared pots were all covered with blue mats <a href="https://paperpile.com/c/UDgV3V/1WUv">(Junker et al. 2014)</a> to enable a robust performance of the high-throughput image analysis algorithm. Seeds were stratified (4 days at 4ºC in darkness) after which they germinated and left to grow for 2 weeks at 21ºC (relative humidity: 55 %; light intensity: 160 µmol m-2 s-1; 14 h light). The temperature treatments were started by transferring the seedlings to either 6 °C or 16 °C. To simulate natural conditions temperatures fluctuated diurnally between 16-21 °C, 0.5-6 °C and 8-16 °C for the 21 °C initial growth conditions and the 6 °C and 16 °C treatments, respectively (<a href="https://docs.google.com/document/d/1Bmr7p24ZMh4yPFVV5oPeH2-T5S41TOFDS3au8JhtwsU/edit#fig_design">Fig.2</a>). Light intensity was kept constant at 160 µmol m-2 s-1 throughout the experiment. Relative humidity was set at 55% but in colder temperatures it rose uncontrollably to maximum 95%. Daylength was 9h during the 16°C and 6°C treatments.</p> <p>Each temperature treatment was repeated in three independent experiments. Five replicate plants were grown for every genotype per experiment. Plants were randomly distributed across the growth chamber with an independent randomisation pattern for each experiment. During the temperature treatments (14 DAS – 35 DAS), plants were photographed twice a day (1 hour. after/before lights switched on/off), using an RGB camera (IDS uEye UI-548xRE-C; 5MP) mounted to a robotic arm. At 35 DAS, whole rosettes were harvested, immediately frozen in liquid nitrogen and stored at -80 °C until further analysis. Rosette areas were extracted from the plant images using Lemnatec OS (LemnaTec GmbH, Aachen, Germany) software.</p> <p><em><strong>Seed size</strong></em></p> <p>We used the seeds produced by <a href="https://paperpile.com/c/UDgV3V/Jqsd">(Kerdaffrec et al. 2016)</a> and limited our measurements to the set of 123 Swedish accessions that overlapped with our growth dataset. After seed stratification for four days at 4ºC in darkness, mother plants were grown for 8 weeks at 4ºC under long-day conditions (16h light; 8h dark) to ensure proper vernalization. Temperature was raised to 21ºC (light) and 16ºC (dark) for flowering and seed ripening. Seeds were kept in darkness at 16ºC and 30% relative humidity, from the harvest until seed size measurements. For each genotype three replicates were pooled and about 200-300 seeds were sprinkled on 12 x 12 cm square, transparent Petri dishes. Image acquisition was performed as described in <a href="https://paperpile.com/c/UDgV3V/WH1e">(Exposito-Alonso et al. 2018)</a> by scanning dishes on a cluster of eight Epson V600 scanners. The resulting 1200 dpi .tiff images were analyzed in the Fiji software. Images were converted to 8-bit binary images and thresholded with the <em>setAutoThreshold("Defaultdark”) </em>command, and seed area was measured in squared mm by running the <em>Analyse Particles</em> command (inclusion parameters: size=0.04-0.25 circularity=0.70-1.00).</p> <p> </p> <p> </p> <p> </p> <p> </p>
Oregon Wolfe Barley (Hordeum vulgare) Informative & Spectacular Subset (ISS) vegetative stage growth data
<p>Oregon Wolfe Barley Informative & Spectacular Subset (ISS) was raised at the Ag Alumni Seed Phenotyping Facility (AAPF) at Purdue University (West Lafayette, Indiana, USA) for 42 days. There were 18 genotypes, with two replicates for each genotype (total plants: 36). AAPF is a controlled environment high-throughput phenotyping facility with automated imaging and irrigation systems. A virtual tour of AAPF can be found at <a href="https://ag.purdue.edu/aapf/virtual-tour.html">https://ag.purdue.edu/aapf/virtual-tour.html</a>.</p> <p>Seeds were sown in a 6 L pot with 2.8 L of Profile Porous Ceramic Greens Grade and Berger BM6 each with 10g of Osmocote. Five hundred ml of Turface was laid on top of each pot to avoid effect of algae for RGB data derivation. The growth temperature in the chamber was 72/68 degrees Fahrenheit day/night. Relative humidity was set at 60%. Lighting was 16 h day/8 h night.</p> <p>Plants were imaged with RGB camera from one top and 12 side views three times a week, ranging between 10 days from planting (equivalent to sowing, Dfp) to 42 Dfp. Ground reference data of plant height and tiller count were measured twice a week. </p> <p> </p> <p>RGB imaging data were stored in “OWB_RGB.xlsx”. Datasheet “Information” describes the variables in datasheets for top view, side average view and every side view.</p> <p> </p> <p>Ground reference data for plant height and tiller count were stored in “OWB_ground_reference.xlsx”. Datasheet “Information” describes the variables in datasheet “Data”.</p>
Growth of Heracleum sosnowskyi Manden. plant in indoor conditions after end of vegetation period
<p>Growth of<em> Heracleum sosnowskyi</em> Manden. plant in indoor conditions after end of vegetation period. The period of observation of plant growth from October 2017 to February 2018. The series of images.</p>
Response of Vegetation Canopy Growth to Climate Change in Northeast China
<p>Our study uniquely addresses gaps in existing research by investigating how vegetation canopy changes during various growth phases—development (April-June), maturation (July-August), and senescence (September-October)—and how these changes respond to preseason climatic factors. We highlight significant findings, such as the early advancement of the canopy maturation phase and the delayed senescence, particularly in forested areas. Moreover, we demonstrate that preseason air temperature exerts a considerable influence on canopy growth, with a transition from positive to negative correlations across different phases and vegetation types.The results contribute to understanding vegetation dynamics under climate change and provide actionable insights for sustainable agricultural, forestry, and animal husbandry management.</p>
Data from: Tree growth-forms reveal dominant browsers shaping the vegetation
<p>This data repository belongs to the publication "Tree growth-forms reveal dominant browsers shaping the vegetation" by Churski et al. in Functional Ecology</p> <p>Authors Marcin Churski<sup>1</sup>, Dries P.J. Kuijper<sup>1</sup>, Katharina Semmelmayer<sup>1</sup>, William J. Bond<sup>2</sup>, Joris P.G.M. Cromsigt<sup>3</sup><sup>,</sup><sup>4</sup>, Yan Wang<sup>5</sup> & Tristan Charles-Dominique<sup>6</sup><sup>,</sup><sup>7</sup></p> <p>Author for correspondence: Marcin Churski email: <a href="mailto:mchurski@ibs.bialowieza.pl">mchurski@ibs.bialowieza.pl</a></p> <p><sup>1</sup>Mammal Research Institute Polish Academy of Sciences, ul. Stoczek 1, 17-230 Białowieża; <sup>2</sup>University of Cape Town, HW Pearson Building, University Ave N, Rondebosch, Cape Town, 7701; <sup>3</sup>SLU, Department of Wildlife, Fish and Environmental Studies, 901 83 Umeå, Sweden; <sup>4</sup>Centre for African Conservation Ecology, Department of Zoology, Nelson Mandela University, PO Box 77000, Gqeberha, 6031, South Africa; <sup>5</sup>Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, Helsinki, Finland; <sup>6</sup>AMAP, University of Montpellier, CIRAD, CNRS, INRAE, IRD, Montpellier, France; <sup>7</sup>CNRS UMR7618; Sorbonne University; Institute of Ecology and Environmental Sciences Paris; 4, place Jussieu 75005 PARIS</p> <div> <h4>Summary</h4> <a href="https://github.com/mripasteam/transformers#summary"></a></div> <ul> <li>Plants adopt particular growth-forms when they are exposed to extreme environmental conditions. In this study, we describe a unique woody plant growth-form induced by large mammalian herbivores and discuss that this growth-form could have evolved as a strategy for escaping the browser zone in herbivore driven ecosystems.</li> <li>We analysed responses of key architectural and morphological attributes (branching and thorn density, tree dimensions, presence of flowers and fruits) of three Eurasian spiny tree species (Malus sylvestris, Prunus cerasifera, Pyrus pyraster) to different levels of browsing by large herbivores in the temperate Białowieża Forest, Poland.</li> <li>Under high browsing pressure, studied trees displayed two distinct forms of the crown: a bottom sterile part developing into a densely branched structure with high density of thorns (‘cage-form’), and an upper reproductive part that escaped from herbivore control (‘escaped-form’). The size of cage-form influenced the feeding behaviour of red deer (Cervus elaphus) by increasing the time deer spend foraging and increasing the bite rate. The height at which cages started to escape and their diameter matched with foraging reach of red deer.</li> <li>Synthesis. We argue that the frequency and cage dimensions of this woody growth-form in the landscape could inform on the type and intensity of recent herbivory. Moreover, its distinctive inducibility suggests that this growth-form did not emerge recently under anthropogenic pressure but could be the legacy of ancient herbivory effects. Observational evidence suggests that this growth-form emerged in several herbivore-driven systems around the globe and may be used to identify the dominant herbivores that control vegetation structure in these ecosystems.</li> </ul> <p>Data</p> <p>The table 'cage_traits.csv' contains data on morphological traits measured on individual trees and was used to describe the key architectural attributes defining the cage and escape forms (trapped branches vs. escaped branches), test if the cage form is induced by mammalian herbivores or not and if the dimensions of the cage form could inform on which animal induced them.</p> <div> <pre><code>Column headers description: N_Protocol: Tree ID Status: if the tree individual grow taller than animal reach (escaped or trapped) Species: tree species Branch_N: observed branch ID Length: branch length (cm) N_Thorns: number of thorns N_Twigs: number of twigs Longest_thorn: the length of longest thorn on the branch (mm) N_browsed_Twigs: Number of browsed twigs (1) vs non browsed (0) twigs on a branch Branch_esc: branch position, "escape" indicates the branch growing on the escaped part of a tree FlowerOrFruit: flower or fruit number found on the branch BDI: branch density index. It is calculated by twigs number divided by branch length Thorn_density:Thorn number divided by branch length BrowRate: observed number of browsed_Twigs divided by branch length Bite: 1 indicates the branch was browsed, 0 indicated the branch was not browsed. browsing_environment: if the tree is exposed to high browsing environment or not. </code></pre> <div> </div> </div> <p>The table 'foraging_time_barplot.csv' contains camera trap data on total foraging time of all the animal on all the tree species and was used to answer the question how the presence of cage form affect herbivore foraging behaviour. This data set was specifically used to produce the bar plot in Figure 5C.</p> <div> <pre><code>Column headers description: N_Protocol : Tree ID animal_species : observed animal species Species: tree species Foraging_time: observed total foraging time. </code></pre> <div> </div> </div> <p>The table 'foraging_time.csv' contains camera trap data on total foraging time of all the animal on all the tree species and was used to answer the question how the presence of cage form affect herbivore foraging behaviour.</p> <div> <pre><code>Column headers description: N_Protocol: Tree ID Total_foraging_time: total record foraging time per tree individual Total_bite_rate : bite rate per tree individual Bite_rate : bite rate per tree branch BDI: branch density index. Foraging_time_av: record foraging time per tree branch Surface: the surface of the crown </code></pre> <div> </div> </div> <p>The table 'escape_height.csv' contains data on individual tree heights in relation to their status (escaped vs trapped). This data set was used to test if the dimensions of the cage form could inform on which animal induced them.</p> <div> <pre><code>Column headers description: N_Protocol: Tree ID Status: if the tree individual grow taller than animal reach Species: Tree species Height: Tree height</code></pre> </div>
Data from: Vegetation dynamics 1946–2018 in an old-growth conifer forest
<p>We analysed ground vegetation in 250 plots in 2018 in the old-growth <em>Picea abies-</em>dominated<em> </em>forest Säby Västerskog, SE Sweden as a follow-up of studies in 1946 and 1998 with the same layout of plots. The vegetation changes were not clearly directional: the species composition in 2018 was intermediate between that of 1946 and 1998, whereas in 1998 species richness was higher and with the unique presence of a number of species indicating small-scale disturbances. <em>Vaccinium myrtillus</em> increased in cover since 1946 and <em>Avenella flexuosa</em> decreased. This goes against regional trends, attributed to climate warming and changes in nitrogen deposition. Regional changes are overshadowed by fine-scale disturbances and micro-successions.</p>
Figs. 3A-D. Growth habits. A in Vegetative anatomy of some Brazilian Zygopetalinae (Orchidaceae)
Figs. 3A-D. Growth habits. A. Dichaea pendula; B. Dichaea trulla; C. Zygopetalum pedicelatum; D. Hoehneella gehrtiana.
Data from: Vegetation dynamics 1946–2018 in an old-growth conifer forest
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Data from: Influence of Myrmecophytic Acacia drepanolobium on the composition and growth of surrounding herbaceous vegetation
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Soil Moisture and vegetation cover patterns after logging and burning an old-growth Douglas-fir forest in the Andrews Experimental Forest, 1960-1983
This soil moisture study was initiated in 1960 to investigate the effects of patch clearcut logging and slash burning (1962-63) in an old-growth Douglas-fir forest in the Oregon Cascade Range. Since soil moisture and vegetation sampling continued regularly until 1980, this is a unique data set that represents nearly two decades of post-treatment information. Plant cover exerts a profound influence on soil moisture levels through its effects on interception, infiltration, evaporation, and transpiration. In the Douglas-fir forests of the Pacific Northwest, clearcut logging and slash burning are common practices that can dramatically alter plant cover and soil moisture. Logging can increase soil moisture by temporarily reducing cover and associated water use, and burning may further augment soil moisture levels by suppressing the survival and regrowth of vegetation. Indeed, part of the rationale for slash burning in the region is to control shrubs and other vegetation that would otherwise compete with conifer seedlings for available moisture, light, and nutrients. Within a few years after burning, however, invading vegetation may deplete soil moisture to levels comparable to forested areas. Such observations point to the value of long-term information to better understand dynamic soil moisture and plant cover responses to forest practices.
Highly-replicated soil, topography and vegetation sampling across an old-growth tropical rain forest landscape
<p class="MsoNormal">Here we present data from highly-replicated sampling of soil, topography, and vegetation across an old-growth tropical rainforest landscape at the La Selva Biological Station, Costa Rica. Samples were taken at 100 x 50 m spacing using an existing surveyed grid system. The 573-ha sample area spanned a variety of soil, topographic and vegetation conditions, including flat terraces on old alluvial soil, ridge tops and steep slopes on residual soil, riparian habitats and fresh-water swamps. At each of 1170 grid points we established a circular 0.01 ha quadrat (radius = 5.64 m). We sampled soil at 30-50 cm depth with a soil augur and collected a sample for subsequent analysis. We measured slope angle with a clinometer and slope direction with a compass. We measured stem diameter to <u>+</u>1 mm with a synthetic fabric diameter tape for all stems <u>></u>10 cm diameter (N= 5236) at 1.3 m from the ground or to ~ 6 m height if there were basal irregularities. We classified stems to life form (tree, palm, liana), and identified all trees and palms to species or morphospecies (N=266; lianas were not identified to species). We collected vouchers from all trees that we could not positively identify in the field (N=920).</p> <p class="MsoNormal">As a whole the data set presents an integrated view of soil, topography and vegetation across a mesoscale old-growth tropical rain forest landscape. The data have been used to refine a reserve-wide soils map for La Selva, and for a variety of papers analyzing the interactions of soil, topography and species distributions at landscape scales (see the 10 papers listed in the Related Works section below).</p> <p class="MsoNormal">There are no restrictions at all on the use of these data, and we think they will be useful for teaching and analysis projects as well as further original research applications. The data also provide a detailed benchmark of the status of old-growth vegetation in 1993-95 for one of the most intensively studied tropical rain forest landscapes in the world. Because the data are accurately georeferenced and detailed metadata on all methods are provided, this study could be repeated at any time to assess the trajectory of vegetation changes at La Selva, particularly in relation to local disturbances and changing regional and global climates. </p>
Top-down photographs of Columbia-0 Arabidopsis thaliana vegetative growth under 16-hour days
<p>Photograph with Raspberry Pi camera v1. Six overlapping fields of view (07 to 12). Two photos per hour from 11:30 UTC to 0300 UTC. (Photographed at 5-minute intervals -- this is a subset of the data.) Manifest file with checksums for the 2712 photos included.</p>
Top-down time-lapse photograph dataset: Columbia-0 Arabidopsis thaliana vegetative growth under 8-hour days #2
<p>Photographed with Raspberry Pi camera v1. Twelve overlapping fields of view (01 to 12). Two photos per hour from ZT 0030 to ZT 0800 (9 AM to 4:30 PM local time). Photographs were taken at 5-minute intervals -- this is a subset of the data. Manifest file with checksums for the 4752 photos (JPEG files) included.</p>
Top-down time-lapse photograph dataset: Columbia-0 Arabidopsis thaliana vegetative growth under 8-hour days #1
<p>Photographed with Raspberry Pi camera v1. Twelve overlapping fields of view (01 to 12). Two photos per hour from ZT 0030 to ZT 0800 (9 AM to 4:30 PM local time). Photographs were taken at 5-minute intervals -- this is a subset of the data. Manifest file with checksums for the 6181 photos (JPEG files) included.</p> <p>First timepoint photo was not captured for fov-04. An extra photo was captured right at dawn (8:30 AM) for both fov-04 and fov-06 and is included. Additional metadata will be deposited in a separate Zenodo record.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.