Search for: All records

Hyperspectral images taken from aircraft or satellites contain information from hundreds of spectral bands, within which lie latent lower-dimensional structures that can be exploited for classifying vegetation and other materials. A disadvantage of working with hyperspectral images is that, due to an inherent trade-off between spectral and spatial resolution, they have a relatively coarse spatial scale, meaning that single pixels may correspond to spatial regions containing multiple materials. This article introduces the Diffusion and Volume maximization-based Image Clustering (D-VIC) algorithm for unsupervised material clustering to address this problem. By directly incorporating pixel purity into its labeling procedure, D-VIC gives greater weight to pixels corresponding to a spatial region containing just a single material. D-VIC is shown to outperform comparable state-of-the-art methods in extensive experiments on a range of hyperspectral images, including land-use maps and highly mixed forest health surveys (in the context of ash dieback disease), implying that it is well-equipped for unsupervised material clustering of spectrally-mixed hyperspectral datasets. 

Abstract. Interactions between wind and trees control energy exchanges between theatmosphere and forest canopies. This energy exchange can lead to thewidespread damage of trees, and wind is a key disturbance agent in many ofthe world's forests. However, most research on this topic has focused onconifer plantations, where risk management is economically important, ratherthan broadleaf forests, which dominate the forest carbon cycle. This studybrings together tree motion time-series data to systematically evaluate thefactors influencing tree responses to wind loading, including data from bothbroadleaf and coniferous trees in forests and open environments. We found that the two most descriptive features of tree motion were (a) the fundamental frequency, which is a measure of the speed at which a treesways and is strongly related to tree height, and (b) the slope of the powerspectrum, which is related to the efficiency of energy transfer from wind totrees. Intriguingly, the slope of the power spectrum was found to remainconstant from medium to high wind speeds for all trees in this study. Thissuggests that, contrary to some predictions, damping or amplificationmechanisms do not change dramatically at high wind speeds, and therefore winddamage risk is related, relatively simply, to wind speed. Conifers from forests were distinct from broadleaves in terms of theirresponse to wind loading. Specifically, the fundamental frequency of forestconifers was related to their size according to the cantilever beam model(i.e. vertically distributed mass), whereas broadleaves were betterapproximated by the simple pendulum model (i.e. dominated by the crown).Forest conifers also had a steeper slope of the power spectrum. We interpretthese finding as being strongly related to tree architecture; i.e. conifersgenerally have a simple shape due to their apical dominance, whereasbroadleaves exhibit a much wider range of architectures with more dominantcrowns. 

Abstract Here we provide the ‘Global Spectrum of Plant Form and Function Dataset’, containing species mean values for six vascular plant traits. Together, these traits –plant height, stem specific density, leaf area, leaf mass per area, leaf nitrogen content per dry mass, and diaspore (seed or spore) mass – define the primary axes of variation in plant form and function. The dataset is based on ca. 1 million trait records received via the TRY database (representing ca. 2,500 original publications) and additional unpublished data. It provides 92,159 species mean values for the six traits, covering 46,047 species. The data are complemented by higher-level taxonomic classification and six categorical traits (woodiness, growth form, succulence, adaptation to terrestrial or aquatic habitats, nutrition type and leaf type). Data quality management is based on a probabilistic approach combined with comprehensive validation against expert knowledge and external information. Intense data acquisition and thorough quality control produced the largest and, to our knowledge, most accurate compilation of empirically observed vascular plant species mean traits to date. 

Abstract Arbuscular mycorrhizal (AM) and ectomycorrhizal (EcM) associations are critical for host-tree performance. However, how mycorrhizal associations correlate with the latitudinal tree beta-diversity remains untested. Using a global dataset of 45 forest plots representing 2,804,270 trees across 3840 species, we test how AM and EcM trees contribute to total beta-diversity and its components (turnover and nestedness) of all trees. We find AM rather than EcM trees predominantly contribute to decreasing total beta-diversity and turnover and increasing nestedness with increasing latitude, probably because wide distributions of EcM trees do not generate strong compositional differences among localities. Environmental variables, especially temperature and precipitation, are strongly correlated with beta-diversity patterns for both AM trees and all trees rather than EcM trees. Results support our hypotheses that latitudinal beta-diversity patterns and environmental effects on these patterns are highly dependent on mycorrhizal types. Our findings highlight the importance of AM-dominated forests for conserving global forest biodiversity.