From Drones to Phenotype: Using UAV-LiDAR to Detect Species and Provenance Variation in Tree Productivity and Structure

[1]  Barbara Koch,et al.  Automatic Single Tree Detection in Plantations using UAV-based Photogrammetric Point clouds , 2014 .

[2]  H. Hänninen,et al.  Potential for evolutionary responses to climate change – evidence from tree populations , 2013, Global change biology.

[3]  Michael F. Hutchinson,et al.  New developments and applications in the ANUCLIM spatial climatic and bioclimatic modelling package , 2013, Environ. Model. Softw..

[4]  Jonathan P. Dash,et al.  Phenotyping Whole Forests Will Help to Track Genetic Performance. , 2018, Trends in plant science.

[5]  Tanya G. Bailey,et al.  Evidence for local climate adaptation in early-life traits of Tasmanian populations of Eucalyptus pauciflora , 2015, Tree Genetics & Genomes.

[6]  David Pont,et al.  Forest-Scale Phenotyping: Productivity Characterisation Through Machine Learning , 2020, Frontiers in Plant Science.

[7]  A. Lowe,et al.  Priority Actions to Improve Provenance Decision-Making , 2018, BioScience.

[8]  Neil Davidson,et al.  Monitoring forest structure to guide adaptive management of forest restoration: a review of remote sensing approaches , 2019, New Forests.

[9]  M. Balsi,et al.  Single-tree detection in high-density LiDAR data from UAV-based survey , 2018 .

[10]  C. Silva,et al.  Individual tree detection from Unmanned Aerial Vehicle (UAV) derived canopy height model in an open canopy mixed conifer forest , 2017 .

[11]  J. Reif,et al.  Effects of vegetation structure on the diversity of breeding bird communities in forest stands of non-native black pine (Pinus nigra A.) and black locust (Robinia pseudoacacia L.) in the Czech Republic , 2016 .

[12]  Juha Hyyppä,et al.  Individual Tree Detection and Classification with UAV-Based Photogrammetric Point Clouds and Hyperspectral Imaging , 2017, Remote. Sens..

[13]  S. Aitken,et al.  Time to get moving: assisted gene flow of forest trees , 2015, Evolutionary applications.

[14]  N. Coops,et al.  Modeling realized gains in Douglas-fir (Pseudotsuga menziesii) using laser scanning data from unmanned aircraft systems (UAS) , 2020 .

[15]  Genetic variation in the susceptibility of Eucalyptus globulus to drought damage , 2012, Tree Genetics & Genomes.

[16]  Adam J. Leavesley,et al.  Bird's Response to Revegetation of Different Structure and Floristics—Are “Restoration Plantings” Restoring Bird Communities? , 2011 .

[17]  Gregory P. Asner,et al.  Cover of tall trees best predicts California spotted owl habitat , 2017 .

[18]  M. Fischer,et al.  Plant niche breadths along environmental gradients and their relationship to plant functional traits , 2018, Diversity and Distributions.

[19]  Nikolay S. Strigul,et al.  Augmentation of Traditional Forest Inventory and Airborne Laser Scanning with Unmanned Aerial Systems and Photogrammetry for Forest Monitoring , 2018, Remote. Sens..

[20]  S. Prober,et al.  Climate-adjusted provenancing: a strategy for climate-resilient ecological restoration , 2015, Front. Ecol. Evol..

[21]  Jan-Peter Mund,et al.  UAV-Based Photogrammetric Tree Height Measurement for Intensive Forest Monitoring , 2019, Remote. Sens..

[22]  Andreas Hamann,et al.  Genetic adaptation of aspen (Populus tremuloides) populations to spring risk environments: a novel remote sensing approach , 2010 .

[23]  Florian Zellweger,et al.  From field surveys to LiDAR: Shining a light on how bats respond to forest structure , 2016 .

[24]  C. Stone,et al.  Crown‐scale evaluation of spectral indices for defoliated and discoloured eucalypts , 2008 .

[25]  R. Dubayah,et al.  Monitoring individual tree‐based change with airborne lidar , 2018, Ecology and evolution.

[26]  Tanya G. Bailey,et al.  Climate adaptation and ecological restoration in eucalypts , 2016 .

[27]  J. Araus,et al.  Using unmanned aerial vehicle‐based multispectral, RGB and thermal imagery for phenotyping of forest genetic trials: A case study in Pinus halepensis , 2019, Annals of Applied Biology.

[28]  D. Steane,et al.  Molecular genetic diversity and population structure in Eucalyptus pauciflora subsp. pauciflora (Myrtaceae) on the island of Tasmania , 2014 .

[29]  Mathias Disney,et al.  Extracting individual trees from lidar point clouds using treeseg , 2018, Methods in Ecology and Evolution.

[30]  S. Puliti,et al.  Use of UAV photogrammetric data in forest genetic trials: measuring tree height, growth, and phenology in Norway spruce (Picea abies L. Karst.) , 2020 .

[31]  Markus Hollaus,et al.  A Benchmark of Lidar-Based Single Tree Detection Methods Using Heterogeneous Forest Data from the Alpine Space , 2015 .

[32]  Mark C. Vanderwel,et al.  Allometric equations for integrating remote sensing imagery into forest monitoring programmes , 2016, Global change biology.

[33]  Michele Dalponte,et al.  How to map forest structure from aircraft, one tree at a time , 2018, Ecology and evolution.

[34]  R. O’Hara,et al.  QST–FST comparisons: evolutionary and ecological insights from genomic heterogeneity , 2013, Nature Reviews Genetics.

[35]  Arko Lucieer,et al.  An Assessment of the Repeatability of Automatic Forest Inventory Metrics Derived From UAV-Borne Laser Scanning Data , 2014, IEEE Transactions on Geoscience and Remote Sensing.

[36]  Anne Chao,et al.  Airborne LiDAR reveals context dependence in the effects of canopy architecture on arthropod diversity , 2014 .

[37]  P. Fleming,et al.  Living (and reproducing) on the edge: reproductive phenology is impacted by rainfall and canopy decline in a Mediterranean eucalypt , 2016 .

[38]  Sergio Marconi,et al.  Individual Tree-Crown Detection in RGB Imagery Using Semi-Supervised Deep Learning Neural Networks , 2019, Remote. Sens..

[39]  Alain F. Zuur,et al.  A protocol for conducting and presenting results of regression‐type analyses , 2016 .

[40]  R. Vaillancourt,et al.  Allozyme variation and conservation of the Tasmanian endemics, Eucalyptus risdonii, E. tenuiramis and E. coccifera , 2000, Conservation Genetics.

[41]  M. Vanhellemont,et al.  Does neighbourhood tree diversity affect the crown arthropod community in saplings? , 2016, Biodiversity and Conservation.

[42]  Roland Brandl,et al.  Composition versus physiognomy of vegetation as predictors of bird assemblages: the role of lidar. , 2010 .

[43]  Tanya G. Bailey,et al.  Stability of species and provenance performance when translocated into different community assemblages , 2020, Restoration Ecology.

[44]  J. Kellner,et al.  The case for remote sensing of individual plants. , 2019, American journal of botany.

[45]  Tristan R. H. Goodbody,et al.  Characterizing variations in growth characteristics between Douglas-fir with different genetic gain levels using airborne laser scanning , 2020, Trees.

[46]  B. Potts,et al.  The natural distribution of Eucalyptus species in Tasmania , 1996 .