84 research outputs found

    Global airborne laser scanning data providers database (GlobALS)-A new tool for monitoring ecosystems and biodiversity

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    Protection and recovery of natural resource and biodiversity requires accurate monitoring at multiple scales. Airborne Laser Scanning (ALS) provides high-resolution imagery that is valuable for monitoring structural changes to vegetation, providing a reliable reference for ecological analyses and comparison purposes, especially if used in conjunction with other remote-sensing and field products. However, the potential of ALS data has not been fully exploited, due to limits in data availability and validation. To bridge this gap, the global network for airborne laser scanner data (GlobALS) has been established as a worldwide network of ALS data providers that aims at linking those interested in research and applications related to natural resources and biodiversity monitoring. The network does not collect data itself but collects metadata and facilitates networking and collaborative research amongst the end-users and data providers. This letter describes this facility, with the aim of broadening participation in GlobALS.</jats:p

    Forest biomass retrieval approaches from earth observation in different biomes

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    The amount and spatial distribution of forest aboveground biomass (AGB) were estimated using a range of regionally developed methods using Earth Observation data for Poland, Sweden and regions in Indonesia (Kalimantan), Mexico (Central Mexico and Yucatan peninsula), and South Africa (Eastern provinces) for the year 2010. These regions are representative of numerous forest biomes and biomass levels globally, from South African woodlands and savannas to the humid tropical forest of Kalimantan. AGB retrieval in each region relied on different sources of reference data, including forest inventory plot data and airborne LiDAR observations, and used a range of retrieval algorithms. This is the widest inter-comparison of regional-to-national AGB maps to date in terms of area, forest types, input datasets, and retrieval methods. The accuracy assessment of all regional maps using independent field data or LiDAR AGB maps resulted in an overall root mean square error (RMSE) ranging from 10 t ha−1 to 55 t ha−1 (37% to 67% relative RMSE), and an overall bias ranging from −1 t ha−1 to +5 t ha−1 at pixel level. The regional maps showed better agreement with field data than previously developed and widely used pan-tropical or northern hemisphere datasets. The comparison of accuracy assessments showed commonalities in error structures despite the variety of methods, input data, and forest biomes. All regional retrievals resulted in overestimation (up to 63 t ha−1) in the lower AGB classes, and underestimation (up to 85 t ha−1) in the higher AGB classes. Parametric model-based algorithms present advantages due to their low demand on in situ data compared to non-parametric algorithms, but there is a need for datasets and retrieval methods that can overcome the biases at both ends of the AGB range. The outcomes of this study should be considered when developing algorithms to estimate forest biomass at continental to global scale level

    The number of tree species on Earth.

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    One of the most fundamental questions in ecology is how many species inhabit the Earth. However, due to massive logistical and financial challenges and taxonomic difficulties connected to the species concept definition, the global numbers of species, including those of important and well-studied life forms such as trees, still remain largely unknown. Here, based on global ground-sourced data, we estimate the total tree species richness at global, continental, and biome levels. Our results indicate that there are ∼73,000 tree species globally, among which ∼9,000 tree species are yet to be discovered. Roughly 40% of undiscovered tree species are in South America. Moreover, almost one-third of all tree species to be discovered may be rare, with very low populations and limited spatial distribution (likely in remote tropical lowlands and mountains). These findings highlight the vulnerability of global forest biodiversity to anthropogenic changes in land use and climate, which disproportionately threaten rare species and thus, global tree richness

    Native diversity buffers against severity of non-native tree invasions

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    Determining the drivers of non-native plant invasions is critical for managing native ecosystems and limiting the spread of invasive species1,2^{1,2}. Tree invasions in particular have been relatively overlooked, even though they have the potential to transform ecosystems and economies3,4^{3,4}. Here, leveraging global tree databases5,6,7^{5,6,7}, 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

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

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    Native diversity buffers against severity of non-native tree invasions

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    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

    The global biogeography of tree leaf form and habit

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    Understanding what controls global leaf type variation in trees is crucial for comprehending their role in terrestrial ecosystems, including carbon, water and nutrient dynamics. Yet our understanding of the factors influencing forest leaf types remains incomplete, leaving us uncertain about the global proportions of needle-leaved, broadleaved, evergreen and deciduous trees. To address these gaps, we conducted a global, ground-sourced assessment of forest leaf-type variation by integrating forest inventory data with comprehensive leaf form (broadleaf vs needle-leaf) and habit (evergreen vs deciduous) records. We found that global variation in leaf habit is primarily driven by isothermality and soil characteristics, while leaf form is predominantly driven by temperature. Given these relationships, we estimate that 38% of global tree individuals are needle-leaved evergreen, 29% are broadleaved evergreen, 27% are broadleaved deciduous and 5% are needle-leaved deciduous. The aboveground biomass distribution among these tree types is approximately 21% (126.4 Gt), 54% (335.7 Gt), 22% (136.2 Gt) and 3% (18.7 Gt), respectively. We further project that, depending on future emissions pathways, 17-34% of forested areas will experience climate conditions by the end of the century that currently support a different forest type, highlighting the intensification of climatic stress on existing forests. By quantifying the distribution of tree leaf types and their corresponding biomass, and identifying regions where climate change will exert greatest pressure on current leaf types, our results can help improve predictions of future terrestrial ecosystem functioning and carbon cycling

    The global biogeography of tree leaf form and habit.

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    Understanding what controls global leaf type variation in trees is crucial for comprehending their role in terrestrial ecosystems, including carbon, water and nutrient dynamics. Yet our understanding of the factors influencing forest leaf types remains incomplete, leaving us uncertain about the global proportions of needle-leaved, broadleaved, evergreen and deciduous trees. To address these gaps, we conducted a global, ground-sourced assessment of forest leaf-type variation by integrating forest inventory data with comprehensive leaf form (broadleaf vs needle-leaf) and habit (evergreen vs deciduous) records. We found that global variation in leaf habit is primarily driven by isothermality and soil characteristics, while leaf form is predominantly driven by temperature. Given these relationships, we estimate that 38% of global tree individuals are needle-leaved evergreen, 29% are broadleaved evergreen, 27% are broadleaved deciduous and 5% are needle-leaved deciduous. The aboveground biomass distribution among these tree types is approximately 21% (126.4 Gt), 54% (335.7 Gt), 22% (136.2 Gt) and 3% (18.7 Gt), respectively. We further project that, depending on future emissions pathways, 17-34% of forested areas will experience climate conditions by the end of the century that currently support a different forest type, highlighting the intensification of climatic stress on existing forests. By quantifying the distribution of tree leaf types and their corresponding biomass, and identifying regions where climate change will exert greatest pressure on current leaf types, our results can help improve predictions of future terrestrial ecosystem functioning and carbon cycling
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