Mapping tree density at a global scale

Crowther, Thomas W.; Glick, Henry B.; Covey, Kristofer; Bettigole, Charlie; Maynard, Daniel S.; Thomas, S.; Smith, Jeffrey R.; Hintler, G.; Duguid, Marlyse C.; Amatulli, Giuseppe; Tuanmu, Mao‐Ning; Jetz, Walter; Salas, Christian; Stam, C.; Piotto, Daniel; Tavani, Rebecca; Green, S.; Bruce, George; Williams, S. Jeffress; Wiser, Susan K.; Huber, Markus; Hengeveld, G.M.; Nabuurs, Gert‐Jan; Тихонова, Елена; Borchardt, Peter; Li, C. F.; Powrie, L.W.; Fischer, Markus; Hemp, Andreas; Homeier, Jürgen; Cho, P.; Vibrans, Alexander Christian; Umunay, Peter M.; Piao, Shilong; Rowe, C. W.; Ashton, Mark S.; Crane, Peter R.; Bradford, Mark A.

doi:10.1038/nature14967

Cited by 758 publications

(520 citation statements)

References 31 publications

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“…Although a decease was detected, it remains relatively high in coverage. For the area whose crown cover fluctuates, additional research is suggested on the driving factor for the variation in forest cover, as is presented by Crowther et al [53]. …”

Section: Forest Cover Changementioning

confidence: 99%

Quantifying Multi-Decadal Change of Planted Forest Cover Using Airborne LiDAR and Landsat Imagery

et al. 2016

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Continuous monitoring of forest cover condition is key to understanding the carbon dynamics of forest ecosystems. This paper addresses how to integrate single-year airborne LiDAR and time-series Landsat imagery to derive forest cover change information. LiDAR data were used to extract forest cover at the sub-pixel level of Landsat for a single year, and the Landtrendr algorithm was applied to Landsat spectral data to explore the temporal information of forest cover change. Four different approaches were employed to model the relationship between forest cover and Landsat spectral data. The result shows incorporating the historic information using the temporal trajectory fitting process could infuse the model with better prediction power. Random forest modeling performs the best for quantitative forest cover estimation. Temporal trajectory fitting with random forest model shows the best agreement with validation data (R 2 " 0.82 and RMSE " 5.19%). We applied our approach to Youyu county in Shanxi province of China, as part of the Three North Shelter Forest Program, to map multi-decadal forest cover dynamics. With the availability of global time-series Landsat imagery and affordable airborne LiDAR data, the approach we developed has the potential to derive large-scale forest cover dynamics.

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Section: Forest Cover Changementioning

confidence: 99%

Quantifying Multi-Decadal Change of Planted Forest Cover Using Airborne LiDAR and Landsat Imagery

et al. 2016

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“…systems genetics | lignocellulosic biomass | cell wall | bioenergy | network-based data integration W ood (secondary xylem tissue) from trees represents a significant proportion of global carbon sequestration (1,2), while also providing raw materials, be it in the form of timber, paper, or other biomaterials and value-added derivatives, such as cellulose (3) and lignin (4). Fast-growing trees such as poplars and eucalypts with short rotation times, small genome sizes (500-600 Mbp), large genetic diversity, and established breeding populations are widely cultivated as woody biomass crops and are well suited for biotechnological improvement (5)(6)(7)(8).…”

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confidence: 99%

Network-based integration of systems genetics data reveals pathways associated with lignocellulosic biomass accumulation and processing

Mizrachi

Verbeke

Christie

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

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As a consequence of their remarkable adaptability, fast growth, and superior wood properties, eucalypt tree plantations have emerged as key renewable feedstocks (over 20 million ha globally) for the production of pulp, paper, bioenergy, and other lignocellulosic products. However, most biomass properties such as growth, wood density, and wood chemistry are complex traits that are hard to improve in long-lived perennials. Systems genetics, a process of harnessing multiple levels of component trait information (e.g., transcript, protein, and metabolite variation) in populations that vary in complex traits, has proven effective for dissecting the genetics and biology of such traits. We have applied a network-based data integration (NBDI) method for a systems-level analysis of genes, processes and pathways underlying biomass and bioenergy-related traits using a segregating Eucalyptus hybrid population. We show that the integrative approach can link biologically meaningful sets of genes to complex traits and at the same time reveal the molecular basis of trait variation. Gene sets identified for related woody biomass traits were found to share regulatory loci, cluster in network neighborhoods, and exhibit enrichment for molecular functions such as xylan metabolism and cell wall development. These findings offer a framework for identifying the molecular underpinnings of complex biomass and bioprocessing-related traits. A more thorough understanding of the molecular basis of plant biomass traits should provide additional opportunities for the establishment of a sustainable bio-based economy.systems genetics | lignocellulosic biomass | cell wall | bioenergy | network-based data integration

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“…A credible estimate of the current forest condition and ongoing dynamics is a basis for reliable forecasts of the global changes and sustainable forest management. Nowadays the most worldwide common approach for assessment of forest conditions and dynamics is based on the systematic ground-based forest monitoring, performed at a set of regularly structured locations (Ferretti 2013;Crowther et al 2015). In Europe, one of the most ambitious projects on forest description on a regular basis is the International Co-operative Programme on Assessment and Monitoring of Air Pollution Effects on Forests (ICP Forests).…”

Section: Introductionmentioning

confidence: 99%

Tree diversity patterns along the latitudinal gradient in the northwestern Russia

et al. 2017

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Background: One of the key forest characteristics is the biodiversity, particularly the diversity of trees which are forest ecosystem engineers. Nowadays the most worldwide common approach for assessment of forest conditions and dynamics is based on the systematic monitoring, performed at a set of regularly structured plots. To fulfill the existing gap in this sort of knowledge on the Russian forests, an extensive study of tree species diversity on a regular network was conducted in north-west of Russia. Methods: The study used the ICP Forests monitoring network that spans over 1700 km along the western Russian border from forest-tundra in the north to broadleaved-coniferous forests in the south. Tree data were collected at 710 sites that were assigned along a regular grid. We performed series of statistical analyses of the tree species distribution and diversity in relation to environmental and anthropogenic factors. Results: According to the Maxent species distribution modelling results only Pinus sylvestris, Betula sp. and Picea abies have the potential to grow throughout the study area. The locally maximum tree species diversity varies along the latitudinal gradient from 1 to 3 species in the north to 5-7 species in the south. Monocultural stands are relatively abundant across the study area, being especially common in the south taiga. The prevailing part of the monocultural stands is represented by Scots pine (72%). The age distribution of dominant trees has a clear connection with the intensity of forest use. We found that recent wildfire events had only little effect on tree diversity in the study area. Conclusions: We demonstrated that ICP Forests monitoring network enables to successfully establish the main qualitative and quantitative relations of the spatial variation of tree species diversity to climatic, landscape, soil and anthropogenic factors. Analysis of the influence of these factors on tree species distribution allowed us to conclude that with the continuing trend of reducing the frequency and intensity of fires, Norway spruce will further replace Scots pine and Betula sp. in the north-western Russia. Extending the monitoring network, especially adding the time-series context, could provide novel appealing opportunities for forest dynamics projection and sustainable management.

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Mapping tree density at a global scale

Cited by 758 publications

References 31 publications

Quantifying Multi-Decadal Change of Planted Forest Cover Using Airborne LiDAR and Landsat Imagery

Quantifying Multi-Decadal Change of Planted Forest Cover Using Airborne LiDAR and Landsat Imagery

Network-based integration of systems genetics data reveals pathways associated with lignocellulosic biomass accumulation and processing

Tree diversity patterns along the latitudinal gradient in the northwestern Russia

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