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opencc-by-4.0Nov 2021View details →

Health assessment of plantations based on LiDAR canopy spatial structure parameters

The Yellow River Delta (YRD) has China's largest artificial Robinia pseudoacacia forest, which was planted in the late 1970s and suffered extensive dieback in the 1990s. The health grade of the R.pseudoacacia forest (named canopy vigor grade, CVG) could be achieved by using high-resolution images and canopy vigor indicators (CVIs). However, a previous study showed that there was no significant correlation between CVG and the field-estimated aboveground biomass (AGB) of R.pseudoacacia forest. Therefore, this study aims to construct forest health indicators (FHIs) based on canopy spatial structure parameters extracted from LiDAR. The FHIs included Weibull_α (the scale parameter of the Weibull density function that reflects the shape of the tree canopy), VCI (vertical complexity index), sdCC (the standard deviation of canopy cover), H99 (the 99th percentile height) and cvLAD (the coefficient of variation of leaf area density), and could significantly distinguish three forest health grades (FHG) (p < 0.05). The FHG was positively correlated with forest AGB (rs = 0.51, p = 0.004), and the similarity value with CVG was 63.33%. The results of this study confirmed that the FHIs can reflect both canopy vigor and tree productivity, and distinguish forest health status without prior classification information.

opencc-by-4.0Mar 2024View details →

Robust retrieval of forest canopy structural attributes using multi-platform airborne LiDAR

Data and R code to replicate the analyses presented in: Zhang et al. (2024) Robust retrieval of forest canopy structural attributes using multi-platform airborne LiDAR. Remote Sensing in Ecology and Conservation, <a href="https://doi.org/10.1002/rse2.398">https://doi.org/10.1002/rse2.398</a> If using these data and/or R code in your work please cite the original publication listed above, as well as this repository using the corresponding DOI.

opencc-by-4.0Jul 2024View details →

UAS-SfM data from Unoccupied aerial system (UAS) Structure-from-Motion canopy fuel parameters: Multisite area-based modelling across forests in California, USA

Data for: Unoccupied aerial system (UAS) Structure-from-Motion canopy fuel parameters: Multisite area-based modelling across forests in California, USA Sean Reilly 1, Matthew L. Clark 2, Lika Loechler 2, Jack Spillane 2, Melina Kozanitas 3, Paris Krause 4, David Ackerly 3, Lisa Patrick Bentley 4, and Imma Oliveras Menor 1,5 1 Environmental Change Institute, University of Oxford, Oxford OX1 3QY, UK 2 Center for Interdisciplinary Geospatial Analysis, Department of Geography, Environment, and Planning, Sonoma State University, Rohnert Park, CA 94928, USA 3 Departments of Integrative Biology and Environmental Science, Policy, and Management, University of California, Berkeley, CA 94720, USA 4 Department of Biology, Sonoma State University, Rohnert Park, CA 94928, USA 5 AMAP (Botanique et Modélisation de l’Architecture des Plantes et des Végétations), CIRAD, CNRS, INRA, IRD, Université de Montpellier, Montpellier, France Study abstract: There is a pressing need for well-informed management to reduce wildfire hazard and restore fire’s beneficial ecological role in the Mediterranean- and temperate-climate forests of California, USA. These efforts rely upon the accessibility of high spatial and temporal resolution data on biomass and canopy fuel parameters such as canopy base height (CBH), mean canopy height, canopy bulk density (CBD), canopy cover, and leaf area index (LAI). Remote sensing using unoccupied aerial system Structure-from-Motion (UAS-SfM) presents a promising technology for this application due to its accessibility, relatively low cost, and possibility for high temporal cadence. However, to date, this method has not been studied in the complex mosaic of forest types found across California. In this study we examined the capacity of structural and multispectral information obtained from UAS-SfM, in conjunction with machine learning methods, to model aboveground biomass and forest canopy fuel structural parameters using an area-based approach across multiple sites representing a diversity of forest types in California. Based on correlations with field measurements, fuel parameters separated into vertical (biomass, CBH, and mean height) and horizontal (LAI, CBD, canopy cover) groups. UAS-SfM random forest models performed well for modelling the vertical structure canopy fuels parameters (R2 0.69 – 0.75). These models exhibited strong performance in comparison to ALS, as well as when transferred to a novel site. Vertical structure predictors were prominent in these models, and did not improve with the addition of spectral predictors. UAS-SfM random forest models of horizontal structure parameters mainly used raster-based spectral indices (primarily NDVI) and had relatively low performance (R2 0.49 – 0.59). In addition, these models underperformed ALS and had poor performance when applied to a novel site. When applied to a region with widespread UAS-SfM coverage, models from both groups successfully produced contiguous maps that could be used for modelling fire behavior or in management decision making and monitoring. These findings indicate that UAS-SfM, without the need for multispectral sensors, is well suited for mapping area-based vertical-structure canopy parameters across diverse landscapes supporting a wide range of forest types. In contrast, the identification of spectral mean variables for modelling horizontal structure canopy fuels suggests the potential of multi- or hyperspectral sensors or high-resolution satellite imagery for meeting management information needs.  Published in Remote Sensing of Environment Contents: This repository contains multispectral UAS-SfM data from four sites around California, USA: jcksn: Jackson Demonstration State Forest ltr: LaTour Demonstration State Forest ppwd: Pepperwood Preserve sdlmtn: Saddle Mountain Open Space Preserve Data were collected during a series of campaigns: c1: Pepperwood, 2019-09-01 to 2019-10-15 c3: Jackson, 2020-06-15 to 2020-07-02 c4: LaTour, 2020-07-07 to 2020-07-17 c6: Saddle Mountain, 2020-08-04 to 2020-08-09 c9: Jackson, 2021-07-08 to 2021-07-12 Data are included in three formats: raw: Raw outputs from Pix4D (spectral and las) reg_grnd, reg_cnpy: Las files with merged multispectral data and classified ground, registered to ALS using either ground points (grnd) or, in cases with insufficient ground points for registration, to the canopy (cnpy) hnrm: Height normalized las files, normalization performed using ALS terrain model File naming structure: site_campaign_flightzone_uas_processedstate See accompanying paper for methods on data collection and processing Data are grouped into zipped folder by product type Funding: Funding for this research was supported by CAL FIRE Forest Health and Forest Legacy (8GG18806) and California State University, Agricultural Research Institute (20-01-106) awards to L.P.B and M.L.C. S.R. was funded by the Rhodes Trust and through the University of Oxford Environmental Change Institute Small Grant Scheme. Pepperwood ground data collection was supported by funding from the Gordon and Betty Moore Foundation and National Science Foundation grants 1754475 and 1835086. Citation: <div> <div>Reilly, S., Clark, M.L., Loechler, L., Spillane, J., Kozanitas, M., Krause, P., Ackerly, D., Bentley, L.P., Menor, I.O., 2024. Unoccupied aerial system (UAS) Structure-from-Motion canopy fuel parameters: Multisite area-based modelling across forests in California, USA. Remote Sensing of Environment 312, 114310. <a href="https://doi.org/10.1016/j.rse.2024.114310">https://doi.org/10.1016/j.rse.2024.114310</a></div> </div>

Fig. 4 in Canopy crane survey of the hemipteran assemblage structure in a Bornean forest

Fig. 4. NMDS ordination plots for (a) all species based on the Sørensen similarity index and (b) abundant species based on the Bray–Curtis dissimilarity index. White circle indicates the GF period and black circle indicates the non-GF period.

Fig. 3 in Canopy crane survey of the hemipteran assemblage structure in a Bornean forest

Fig. 3. Log-transformed numbers of (a) adult species, (b) adult individuals and (c) nymphs during each sampling period. Different letters indicate significant differences in abundance (Kruskal–Wallis with post hoc tests, p <0.01). Box plots indicate the range of the data within the ends of the whiskers; the middle two quartiles are within the box; and the median value is indicated by the bold line. The end of the whisker indicates Q3 + 1.5×(Q3 – Q1) and the outliner is above it.

Fig. 2 in Canopy crane survey of the hemipteran assemblage structure in a Bornean forest

Fig. 2. Species accumulation curves (Sobs, Mao Tau) for adult hemipteran species during each sampling period. The curves are the result 50 randomisations.

Fig. 1 in Canopy crane survey of the hemipteran assemblage structure in a Bornean forest

Fig. 1. Proportions of target canopy tree individuals with mature leaves, immature leaves, buds, flowers or seeds (see text for definitions). Numbers above bars represent the number of target trees during each sampling period.

publicMar 2021View details →

dryad40/100

Biodiversity facets, canopy structure and surface temperature of grassland communities

Open the record for dataset details and reuse information.

edi40/100

Comparisons among five canopy-cover estimating methods in five Douglas-fir/western hemlock structure types in the western Oregon Cascades

Estimates of forest canopy cover are widely used in forest research and management, yet methods used to quantify canopy cover and the estimates they provide vary greatly. Four ground-based techniques for estimating overstory cover -line- intercept, spherical densiometer, moosehorn, and hemispherical photography-and cover estimates generated using the Forest Vegetation Simulator (FVS) were compared in five Douglas- fir/western hemlock structure types in western Oregon. Differences in cover estimates among the ground-based methods did not depend on the structure type in which they were measured (p=0.33). As expected, estimates of cover increased and within-stand variability decreased with increasing angle of view among techniques. However, the moosehorn provided the most conservative estimates of vertical-projection overstory cover. The FVS-generated cover was consistently lower (by up to 44%, 17% on average) than the ground-based estimates and is not advised as a substitute for ground-based measures in these forest types. Regression equations are provided to allow conversion among canopy cover estimates developed with the four ground-based methods.

openCC0Sep 2004View details →

edi40/100

Ice Storm Experiment (ISE) Canopy Structure Data, 2015-present

To evaluate the effects of ice storm disturbance on forest canopy structure and complexity terrestrial lidar data were collected within the Hubbard Brook Ice Storm Experiment plots starting in 2015 (prior to ice treatment) and annually thereafter. Data were collected using a ground-based portable canopy lidar (PCL) system during the growing season in August of each year along 5 permanently marked 30 m transects in each 20 x 30 m ISE plot. These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station.

openCC (other)May 2021View details →

opencc-zeroAug 2020View details →

Data from: Defining a spectrum of integrative trait-based vegetation canopy structural types

Vegetation canopy structure is a fundamental characteristic of terrestrial ecosystems that defines vegetation types and drives ecosystem functioning. We use the multivariate structural trait composition of vegetation canopies to classify ecosystems within a global canopy structure spectrum. Across the temperate forest subset of this spectrum we assess gradients in canopy structural traits, characterize canopy structural types (CST), and evaluate drivers and functional consequences of canopy structural variation. We derive CSTs from multivariate canopy structure data, illustrating variation along three primary structural axes and resolution into six largely distinct and functionally relevant CSTs. Our results illustrate that within-ecosystem successional processes and disturbance legacies can produce variation in canopy structure similar to that associated with sub-continental variation in forest types and ecoclimatic zones. The potential to classify ecosystems into CSTs based on suites of structural traits represents an important advance in understanding and modeling structure-function relationships in vegetated ecosystems.

opencc-zeroJan 2022View details →

Metabarcoding of canopy arthropods reveals negative impacts of forestry insecticides on community structure across multiple taxa

1. Insecticides used to combat outbreaks of forest defoliators can adversely affect non-target arthropods. Forest use insecticides typically suppress Lepidoptera larvae which are the keystone of the canopy community of deciduous oak forests. The abrupt removal of this dominant component of the food web could have far-reaching implications for forest ecosystems, yet it is rarely investigated in practice owing to several methodological shortcomings. The taxonomic impediment and the biased nature of arthropod sampling techniques particularly impede the assessment of insecticide impacts on diverse communities. 2. To tackle this issue, we propose an experimental approach combining pyrethrum knockdown sampling and species determination via DNA metabarcoding, using community subsampling to derive estimates of species abundances. We applied this protocol to investigate the short-term effects of the insecticides diflubenzuron (DFB) or Bacillus thuringiensis var. kurstaki (BTK) on canopy-dwelling arthropod communities in German oak woodlands. 3. Our approach allowed us to include most of the detected diversity and integrate species abundances in our analyses. By classifying arthropod species into assemblages based on their expected sensitivity rather than coarse taxonomic groupings, we could unveil substantial effects of DFB across multiple taxa five weeks after application. 4. Although strong effects on single species appear related to direct toxicity, substantial impacts of DFB on parasitoids and xylophagous beetles suggest that anti-defoliator treatments can have previously unsuspected indirect effects on some components of forest arthropod communities. The impacts of BTK on community structure were consistent with but much weaker than that of DFB. 5. Synthesis and applications. Comparing diversity patterns in the arthropod communities of sprayed and unsprayed oak canopies, our results show that selective insecticides can alter species diversity in presumably non-sensitive taxa. Even though the ecological significance of these impacts has yet to be assessed in an operational setting, their existence calls for increased regulatory scrutiny on indirect effects. As community approaches become more attainable with the rapid development of DNA metabarcoding, we suggest the inclusion of community level endpoints as regulatory requirements for the approval of forest use insecticides.

opencc-by-4.0Jan 2022View details →

UAS spherical photography for the vertical characterisation of canopy structural traits

Data and scripts for New Phytologist manuscript: UAS spherical photography for the vertical characterisation of canopy structural traits  Vicent Agustí Ribas Costa, Maxime Durand, T Matthew Robson, Albert Porcar-Castell, Ilkka Korpela, Jon Atherton The current version is 2.0.0; please do not use the data/code from the peer review version 1.  In the Early View version 2.0.0 we have fixed minor bugs in data (incorrectly flipped images), and updated our code. We also reduced the data archive size to approx 5 GB.     Note that individual (i.e. pre-stitched) UAS photos from vertical profiles are not included due to the size (>50 GB). If you want all the individual files then contact Jon. Data was compiled by Vicent, but feel free to contact Jon in case of any issues.

opencc-by-4.0Apr 2022View details →

Snow pit dataset from "Comparison of snowpack structure in gaps and under the canopy in a humid boreal forest"

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 “Comparison of snowpack structure in gaps and under the canopy in a humid boreal forest” from Bouchard et al., 2022. In this dataset you can find:   <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>   <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>   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 International Classification for Seasonal Snow (Fierz et al., 2009):   <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>

opencc-zeroApr 2022View details →

Improving landscape-scale productivity estimates by integrating trait-based models and remotely-sensed foliar-trait and canopy-structural data

Assessing the impacts of anthropogenic degradation and climate change on global carbon cycling is hindered by a lack of clear, flexible, and easy-to-use productivity models along with scarce trait and productivity data for parameterizing and testing those models. We provide a simple solution: a mechanistic framework (RS-CFM) that combines remotely-sensed foliar-trait and canopy-structural data with trait-based metabolic theory to efficiently map productivity at large spatial scales. We test this framework by quantifying net primary productivity (NPP) at high-resolution (0.01-ha) in hyper-diverse Peruvian tropical forests (30,040 hectares) along a 3,322-m elevation gradient. Our analysis captures hotspots and elevational shifts in productivity more accurately and in greater detail than alternative empirical- and process-based models that use plant functional types. This result exposes how high-resolution, location-specific variation in traits and light competition drive variability in productivity, opening up possibilities to fully harness remote sensing data and reliably scale up from traits to map global productivity in a more direct, efficient, and cost-effective manner.

opencc-zeroJul 2024View details →

Data from: Structure and composition of a canopy-beetle community (Coleoptera) in a Neotropical lowland rainforest in southern Venezuela

Species richness, community structure, and taxonomic composition are important characteristics of biodiversity. Beetle communities show distinct diversity patterns according to habitat attributes. Tropical rainforest canopies, which are well known for their richness in Coleoptera, represent such a conspicuous life zone. Here, I describe a canopy-inhabiting beetle community associated with 23 tree species in a Neotropical lowland rainforest. Adult beetles were sampled manually and in aerial traps using a large tower crane for a cumulative year. The sample revealed 6738 adult beetles, which were assigned to 862 (morpho-)species in 45 families. The most species-rich beetle families were Curculionidae (n = 246), Chrysomelidae (n = 121), and Cerambycidae (n = 89). The most abundant families were Curculionidae (n = 2746) and Chrysomelidae (n = 1409). Dominant beetle families were found in most assemblages. The beetle community consisted of 400 singletons (46.4%). A similar proportion was evident for assemblages of single tree species. I found that 74.5% of all beetle species were restricted in their occurrence on host trees to the phenological season and time of the day. This daily and seasonal migration causes patterns similar to mass effects, and therefore accounts for the high proportion of singletons.

opencc-by-4.0Jun 2019View details →

Persistent effects of fragmentation on tropical rainforest canopy structure after 20 years of isolation

Data of Ecological Application paper "Persistent effects of fragmentation on tropical rainforest canopy structure after 20 years of isolation"

opencc-by-4.0Mar 2023View details →

Datasets used for the publication: UAV-Lidar reveals that canopy structure mediates the influence of edge effects on forest diversity, function and microclimate

Datasets used for the publication: UAV-Lidar reveals that canopy structure mediates the influence of edge effects on forest diversity, function and microclimate. The file "Blanchard_et_al_JoE_2023_data_plot_trees.csv" contains individual tree indentification data for the 46 plots used in the study. The file "Blanchard_et_al_JoE_2023_data_plot_aggregated.csv" contains plot-level aggregated metrics used for the analyses: - distance to the forest edge - diversity indices : the 20-sp rarefied species richness "rar_sp_richness_20" and the 20-sp rarefied Beta diversity "Beta_div" which corresponds to the plos coordinates on the PCoA first axis. - functional indices: the community weighted mean trait values for the four traits used in this study : ,"WD","SLA","LA","LDMC"; the fonctional divergence index "FD_trans.FDiv"; and the synthetic community weigthed mean trait wich corresponds to the postion on plots on the principal component analysis of species trait values "Functional_composition_trans". Note that the SLA and LA values were log-transformed before computing "FD_trans.FDiv" and "Functional_composition_trans". - UAV-LiDAR-dervived metrics: canopy height, gap fraction ("gap_fraction2"), slope, curvature - The estimated plot above graound biomass "agb_plot", and the mean value of the vapor pressure deficit during the drisest month "max_monthly_VPD". - coordinates of the plots in UTM 58S (Coordinate reference system) Please read the material and method section of the article for more informations on this dataset.