41 research outputs found

    Evaluating the potential of full-waveform lidar for mapping pan-tropical tree species richness

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    AIM: Mapping tree species richness across the tropics is of great interest for effective conservation and biodiversity management. In this study, we evaluated the potential of full‐waveform lidar data for mapping tree species richness across the tropics by relating measurements of vertical canopy structure, as a proxy for the occupation of vertical niche space, to tree species richness. LOCATION: Tropics. TIME PERIOD: Present. MAJOR TAXA STUDIED: Trees. METHODS: First, we evaluated the characteristics of vertical canopy structure across 15 study sites using (simulated) large‐footprint full‐waveform lidar data (22 m diameter) and related these findings to in‐situ tree species information. Then, we developed structure–richness models at the local (within 25–50 ha plots), regional (biogeographical regions) and pan‐tropical scale at three spatial resolutions (1.0, 0.25 and 0.0625 ha) using Poisson regression. RESULTS: The results showed a weak structure–richness relationship at the local scale. At the regional scale (within a biogeographical region) a stronger relationship between canopy structure and tree species richness across different tropical forest types was found, for example across Central Africa and in South America [R^{2} ranging from .44–.56, root mean squared difference as a percentage of the mean (RMSD%) ranging between 23–61%]. Modelling the relationship pan‐tropically, across four continents, 39% of the variation in tree species richness could be explained with canopy structure alone (R^{2} = .39 and RMSD% = 43%, 0.25‐ha resolution). MAIN CONCLUSIONS: Our results may serve as a basis for the future development of a set of structure–richness models to map high resolution tree species richness using vertical canopy structure information from the Global Ecosystem Dynamics Investigation (GEDI). The value of this effort would be enhanced by access to a larger set of field reference data for all tropical regions. Future research could also support the use of GEDI data in frameworks using environmental and spectral information for modelling tree species richness across the tropics

    Attaining the canopy in dry and moist tropical forests: strong differences in tree growth trajectories reflect variation in growing conditions

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    Availability of light and water differs between tropical moist and dry forests, with typically higher understorey light levels and lower water availability in the latter. Therefore, growth trajectories of juvenile trees—those that have not attained the canopy—are likely governed by temporal fluctuations in light availability in moist forests (suppressions and releases), and by spatial heterogeneity in water availability in dry forests. In this study, we compared juvenile growth trajectories of Cedrela odorata in a dry (Mexico) and a moist forest (Bolivia) using tree rings. We tested the following specific hypotheses: (1) moist forest juveniles show more and longer suppressions, and more and stronger releases; (2) moist forest juveniles exhibit wider variation in canopy accession pattern, i.e. the typical growth trajectory to the canopy; (3) growth variation among dry forest juveniles persists over longer time due to spatial heterogeneity in water availability. As expected, the proportion of suppressed juveniles was higher in moist than in dry forest (72 vs. 17%). Moist forest suppressions also lasted longer (9 vs. 5 years). The proportion of juveniles that experienced releases in moist forest (76%) was higher than in dry forest (41%), and releases in moist forests were much stronger. Trees in the moist forest also had a wider variation in canopy accession patterns compared to the dry forest. Our results also showed that growth variation among juvenile trees persisted over substantially longer periods of time in dry forest (>64 years) compared to moist forest (12 years), most probably because of larger persistent spatial variation in water availability. Our results suggest that periodic increases in light availability are more important for attaining the canopy in moist forests, and that spatial heterogeneity in water availability governs long-term tree growth in dry forests

    Pantropical variability in tree crown allometry

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    Aim: Tree crowns determine light interception, carbon and water exchange. Thus, understanding the factors causing tree crown allometry to vary at the tree and stand level matters greatly for the development of future vegetation modelling and for the calibration of remote sensing products. Nevertheless, we know little about large‐scale variation and determinants in tropical tree crown allometry. In this study, we explored the continental variation in scaling exponents of site‐specific crown allometry and assessed their relationships with environmental and stand‐level variables in the tropics. / Location: Global tropics. / Time period: Early 21st century. / Major taxa studied: Woody plants. / Methods: Using a dataset of 87,737 trees distributed among 245 forest and savanna sites across the tropics, we fitted site‐specific allometric relationships between crown dimensions (crown depth, diameter and volume) and stem diameter using power‐law models. Stand‐level and environmental drivers of crown allometric relationships were assessed at pantropical and continental scales. / Results: The scaling exponents of allometric relationships between stem diameter and crown dimensions were higher in savannas than in forests. We identified that continental crown models were better than pantropical crown models and that continental differences in crown allometric relationships were driven by both stand‐level (wood density) and environmental (precipitation, cation exchange capacity and soil texture) variables for both tropical biomes. For a given diameter, forest trees from Asia and savanna trees from Australia had smaller crown dimensions than trees in Africa and America, with crown volumes for some Asian forest trees being smaller than those of trees in African forests. / Main conclusions: Our results provide new insight into geographical variability, with large continental differences in tropical tree crown allometry that were driven by stand‐level and environmental variables. They have implications for the assessment of ecosystem function and for the monitoring of woody biomass by remote sensing techniques in the global tropics

    TLR9-induced interferon β is associated with protection from gammaherpesvirus-induced exacerbation of lung fibrosis

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    Abstract Background We have shown previously that murine gammaherpesvirus 68 (γHV68) infection exacerbates established pulmonary fibrosis. Because Toll-like receptor (TLR)-9 may be important in controlling the immune response to γHV68 infection, we examined how TLR-9 signaling effects exacerbation of fibrosis in response to viral infection, using models of bleomycin- and fluorescein isothiocyanate-induced pulmonary fibrosis in wild-type (Balb/c) and TLR-9-/- mice. Results We found that in the absence of TLR-9 signaling, there was a significant increase in collagen deposition following viral exacerbation of fibrosis. This was not associated with increased viral load in TLR-9-/- mice or with major alterations in T helper (Th)1 and Th2 cytokines. We examined alveolar epithelial-cell apoptosis in both strains, but this could not explain the altered fibrotic outcomes. As expected, TLR-9-/- mice had a defect in the production of interferon (IFN)-β after viral infection. Balb/c fibroblasts infected with γHV68 in vitro produced more IFN-β than did infected TLR-9-/- fibroblasts. Accordingly, in vitro infection of Balb/c fibroblasts resulted in reduced proliferation rates whereas infection of TLR-9-/- fibroblasts did not. Finally, therapeutic administration of CpG oligodeoxynucleotides ameliorated bleomycin-induced fibrosis in wild-type mice. Conclusions These results show a protective role for TLR-9 signaling in murine models of lung fibrosis, and highlight differences in the biology of TLR-9 between mice and humans.http://deepblue.lib.umich.edu/bitstream/2027.42/112877/1/13069_2011_Article_57.pd

    Climatic controls of decomposition drive the global biogeography of forest-tree symbioses

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    The identity of the dominant root-associated microbial symbionts in a forest determines the ability of trees to access limiting nutrients from atmospheric or soil pools1,2, sequester carbon3,4 and withstand the effects of climate change5,6. Characterizing the global distribution of these symbioses and identifying the factors that control this distribution are thus integral to understanding the present and future functioning of forest ecosystems. Here we generate a spatially explicit global map of the symbiotic status of forests, using a database of over 1.1 million forest inventory plots that collectively contain over 28,000 tree species. Our analyses indicate that climate variables—in particular, climatically controlled variation in the rate of decomposition—are the primary drivers of the global distribution of major symbioses. We estimate that ectomycorrhizal trees, which represent only 2% of all plant species7, constitute approximately 60% of tree stems on Earth. Ectomycorrhizal symbiosis dominates forests in which seasonally cold and dry climates inhibit decomposition, and is the predominant form of symbiosis at high latitudes and elevation. By contrast, arbuscular mycorrhizal trees dominate in aseasonal, warm tropical forests, and occur with ectomycorrhizal trees in temperate biomes in which seasonally warm-and-wet climates enhance decomposition. Continental transitions between forests dominated by ectomycorrhizal or arbuscular mycorrhizal trees occur relatively abruptly along climate-driven decomposition gradients; these transitions are probably caused by positive feedback effects between plants and microorganisms. Symbiotic nitrogen fixers—which are insensitive to climatic controls on decomposition (compared with mycorrhizal fungi)—are most abundant in arid biomes with alkaline soils and high maximum temperatures. The climatically driven global symbiosis gradient that we document provides a spatially explicit quantitative understanding of microbial symbioses at the global scale, and demonstrates the critical role of microbial mutualisms in shaping the distribution of plant species

    Aboveground biomass density models for NASA's Global Ecosystem Dynamics Investigation (GEDI) lidar mission

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    NASA's Global Ecosystem Dynamics Investigation (GEDI) is collecting spaceborne full waveform lidar data with a primary science goal of producing accurate estimates of forest aboveground biomass density (AGBD). This paper presents the development of the models used to create GEDI's footprint-level (~25 m) AGBD (GEDI04_A) product, including a description of the datasets used and the procedure for final model selection. The data used to fit our models are from a compilation of globally distributed spatially and temporally coincident field and airborne lidar datasets, whereby we simulated GEDI-like waveforms from airborne lidar to build a calibration database. We used this database to expand the geographic extent of past waveform lidar studies, and divided the globe into four broad strata by Plant Functional Type (PFT) and six geographic regions. GEDI's waveform-to-biomass models take the form of parametric Ordinary Least Squares (OLS) models with simulated Relative Height (RH) metrics as predictor variables. From an exhaustive set of candidate models, we selected the best input predictor variables, and data transformations for each geographic stratum in the GEDI domain to produce a set of comprehensive predictive footprint-level models. We found that model selection frequently favored combinations of RH metrics at the 98th, 90th, 50th, and 10th height above ground-level percentiles (RH98, RH90, RH50, and RH10, respectively), but that inclusion of lower RH metrics (e.g. RH10) did not markedly improve model performance. Second, forced inclusion of RH98 in all models was important and did not degrade model performance, and the best performing models were parsimonious, typically having only 1-3 predictors. Third, stratification by geographic domain (PFT, geographic region) improved model performance in comparison to global models without stratification. Fourth, for the vast majority of strata, the best performing models were fit using square root transformation of field AGBD and/or height metrics. There was considerable variability in model performance across geographic strata, and areas with sparse training data and/or high AGBD values had the poorest performance. These models are used to produce global predictions of AGBD, but will be improved in the future as more and better training data become available

    Tallo: A global tree allometry and crown architecture database.

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    This is the final version. Available from Wiley via the DOI in this record. Data capturing multiple axes of tree size and shape, such as a tree's stem diameter, height and crown size, underpin a wide range of ecological research-from developing and testing theory on forest structure and dynamics, to estimating forest carbon stocks and their uncertainties, and integrating remote sensing imagery into forest monitoring programmes. However, these data can be surprisingly hard to come by, particularly for certain regions of the world and for specific taxonomic groups, posing a real barrier to progress in these fields. To overcome this challenge, we developed the Tallo database, a collection of 498,838 georeferenced and taxonomically standardized records of individual trees for which stem diameter, height and/or crown radius have been measured. These data were collected at 61,856 globally distributed sites, spanning all major forested and non-forested biomes. The majority of trees in the database are identified to species (88%), and collectively Tallo includes data for 5163 species distributed across 1453 genera and 187 plant families. The database is publicly archived under a CC-BY 4.0 licence and can be access from: https://doi.org/10.5281/zenodo.6637599. To demonstrate its value, here we present three case studies that highlight how the Tallo database can be used to address a range of theoretical and applied questions in ecology-from testing the predictions of metabolic scaling theory, to exploring the limits of tree allometric plasticity along environmental gradients and modelling global variation in maximum attainable tree height. In doing so, we provide a key resource for field ecologists, remote sensing researchers and the modelling community working together to better understand the role that trees play in regulating the terrestrial carbon cycle.Natural Environment Research Council (NERC)Natural Environment Research Council (NERC); Ministry of Education, Youth and Sports of the Czech RepublicFAPEMIGUniversidad Nacional Autónoma de MéxicoUniversidad Nacional Autónoma de MéxicoConsejo Nacional de Ciencia y TecnologíaSwedish Energy AgencyUKRIFederal Ministry of Education and ResearchNational Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaNational Science FoundationNational Science FoundationInternational Foundation for ScienceP3FACDynAfForNanjing Forestry UniversityJiangsu Science and Technology Special ProjectHebei UniversityAgence Nationale de la RechercheAgence Nationale de la RechercheAgua Salud ProjectU.S. Department of EnergyCAPE

    Native diversity buffers against severity of non-native tree invasions.

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    This is the final version. Available from Nature Research via the DOI in this record. Data availability: Data used in this study can be found in cited references for the Global Naturalized Alien Flora (GloNAF) database6 (non-native status), the KEW Plants of the World database5 (native ranges) and the Global Environmental Composite63,77 (environmental data layers). Plant trait data were extracted from Maynard et al.78. Data from the Global Forest Biodiversity Initiative (GFBI) database57 are not available due to data privacy and sharing restrictions, but can be obtained upon request via Science-I (https://science-i.org/) or GFBI (gfbinitiative.org) and an approval from data contributors.Code availability All code used to complete analyses for the manuscript is available at the following link: https://github.com/thomaslauber/Global-Tree-Invasion. Data analyses were conducted and were visualizations generated in R (v. 4.2.2), Python (v. 3.9.7), Google Earth Engine (earthengine-api 0.1.306), QGIS-LTR (v. 3.16.7) and the ETH Zurich Euler cluster.Determining the drivers of non-native plant invasions is critical for managing native ecosystems and limiting the spread of invasive species1,2. Tree invasions in particular have been relatively overlooked, even though they have the potential to transform ecosystems and economies3,4. Here, leveraging global tree databases5-7, we explore how the phylogenetic and functional diversity of native tree communities, human pressure and the environment influence the establishment of non-native tree species and the subsequent invasion severity. We find that anthropogenic factors are key to predicting whether a location is invaded, but that invasion severity is underpinned by native diversity, with higher diversity predicting lower invasion severity. Temperature and precipitation emerge as strong predictors of invasion strategy, with non-native species invading successfully when they are similar to the native community in cold or dry extremes. Yet, despite the influence of these ecological forces in determining invasion strategy, we find evidence that these patterns can be obscured by human activity, with lower ecological signal in areas with higher proximity to shipping ports. Our global perspective of non-native tree invasion highlights that human drivers influence non-native tree presence, and that native phylogenetic and functional diversity have a critical role in the establishment and spread of subsequent invasions.Swiss National Science FoundationSwiss National Science FoundationBernina FoundationDOB Ecolog
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