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      A remote sensing derived data set of 100 million individual tree crowns for the National Ecological Observatory Network

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          Abstract

          Forests provide biodiversity, ecosystem, and economic services. Information on individual trees is important for understanding forest ecosystems but obtaining individual-level data at broad scales is challenging due to the costs and logistics of data collection. While advances in remote sensing techniques allow surveys of individual trees at unprecedented extents, there remain technical challenges in turning sensor data into tangible information. Using deep learning methods, we produced an open-source data set of individual-level crown estimates for 100 million trees at 37 sites across the United States surveyed by the National Ecological Observatory Network’s Airborne Observation Platform. Each canopy tree crown is represented by a rectangular bounding box and includes information on the height, crown area, and spatial location of the tree. These data have the potential to drive significant expansion of individual-level research on trees by facilitating both regional analyses and cross-region comparisons encompassing forest types from most of the United States.

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          Most cited references44

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          ImageNet: A large-scale hierarchical image database

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            High-resolution global maps of 21st-century forest cover change.

            Quantification of global forest change has been lacking despite the recognized importance of forest ecosystem services. In this study, Earth observation satellite data were used to map global forest loss (2.3 million square kilometers) and gain (0.8 million square kilometers) from 2000 to 2012 at a spatial resolution of 30 meters. The tropics were the only climate domain to exhibit a trend, with forest loss increasing by 2101 square kilometers per year. Brazil's well-documented reduction in deforestation was offset by increasing forest loss in Indonesia, Malaysia, Paraguay, Bolivia, Zambia, Angola, and elsewhere. Intensive forestry practiced within subtropical forests resulted in the highest rates of forest change globally. Boreal forest loss due largely to fire and forestry was second to that in the tropics in absolute and proportional terms. These results depict a globally consistent and locally relevant record of forest change.
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              Positive biodiversity-productivity relationship predominant in global forests

              The relationship between biodiversity and ecosystem productivity has been explored in detail in herbaceous vegetation, but patterns in forests are far less well understood. Liang et al. have amassed a global forest data set from >770,000 sample plots in 44 countries. A positive and consistent relationship can be discerned between tree diversity and ecosystem productivity at landscape, country, and ecoregion scales. On average, a 10% loss in biodiversity leads to a 3% loss in productivity. This means that the economic value of maintaining biodiversity for the sake of global forest productivity is more than fivefold greater than global conservation costs. Science , this issue p. [Related article:] 196 Global forest inventory records suggest that biodiversity loss would result in a decline in forest productivity worldwide. INTRODUCTION The biodiversity-productivity relationship (BPR; the effect of biodiversity on ecosystem productivity) is foundational to our understanding of the global extinction crisis and its impacts on the functioning of natural ecosystems. The BPR has been a prominent research topic within ecology in recent decades, but it is only recently that we have begun to develop a global perspective. RATIONALE Forests are the most important global repositories of terrestrial biodiversity, but deforestation, forest degradation, climate change, and other factors are threatening approximately one half of tree species worldwide. Although there have been substantial efforts to strengthen the preservation and sustainable use of forest biodiversity throughout the globe, the consequences of this diversity loss pose a major uncertainty for ongoing international forest management and conservation efforts. The forest BPR represents a critical missing link for accurate valuation of global biodiversity and successful integration of biological conservation and socioeconomic development. Until now, there have been limited tree-based diversity experiments, and the forest BPR has only been explored within regional-scale observational studies. Thus, the strength and spatial variability of this relationship remains unexplored at a global scale. RESULTS We explored the effect of tree species richness on tree volume productivity at the global scale using repeated forest inventories from 777,126 permanent sample plots in 44 countries containing more than 30 million trees from 8737 species spanning most of the global terrestrial biomes. Our findings reveal a consistent positive concave-down effect of biodiversity on forest productivity across the world, showing that a continued biodiversity loss would result in an accelerating decline in forest productivity worldwide. The BPR shows considerable geospatial variation across the world. The same percentage of biodiversity loss would lead to a greater relative (that is, percentage) productivity decline in the boreal forests of North America, Northeastern Europe, Central Siberia, East Asia, and scattered regions of South-central Africa and South-central Asia. In the Amazon, West and Southeastern Africa, Southern China, Myanmar, Nepal, and the Malay Archipelago, however, the same percentage of biodiversity loss would lead to greater absolute productivity decline. CONCLUSION Our findings highlight the negative effect of biodiversity loss on forest productivity and the potential benefits from the transition of monocultures to mixed-species stands in forestry practices. The BPR we discover across forest ecosystems worldwide corresponds well with recent theoretical advances, as well as with experimental and observational studies on forest and nonforest ecosystems. On the basis of this relationship, the ongoing species loss in forest ecosystems worldwide could substantially reduce forest productivity and thereby forest carbon absorption rate to compromise the global forest carbon sink. We further estimate that the economic value of biodiversity in maintaining commercial forest productivity alone is $166 billion to $490 billion per year. Although representing only a small percentage of the total value of biodiversity, this value is two to six times as much as it would cost to effectively implement conservation globally. These results highlight the necessity to reassess biodiversity valuation and the potential benefits of integrating and promoting biological conservation in forest resource management and forestry practices worldwide. The biodiversity-productivity relationship (BPR) is foundational to our understanding of the global extinction crisis and its impacts on ecosystem functioning. Understanding BPR is critical for the accurate valuation and effective conservation of biodiversity. Using ground-sourced data from 777,126 permanent plots, spanning 44 countries and most terrestrial biomes, we reveal a globally consistent positive concave-down BPR, showing that continued biodiversity loss would result in an accelerating decline in forest productivity worldwide. The value of biodiversity in maintaining commercial forest productivity alone—US$166 billion to 490 billion per year according to our estimation—is more than twice what it would cost to implement effective global conservation. This highlights the need for a worldwide reassessment of biodiversity values, forest management strategies, and conservation priorities.
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                Author and article information

                Contributors
                Role: Reviewing Editor
                Role: Senior Editor
                Journal
                eLife
                Elife
                eLife
                eLife
                eLife Sciences Publications, Ltd
                2050-084X
                19 February 2021
                2021
                : 10
                : e62922
                Affiliations
                [1 ]Department of Wildlife Ecology and Conservation, University of Florida GainesvilleUnited States
                [2 ]School of Forest Resources and Conservation, University of Florida GainesvilleUnited States
                [3 ]Department of Electrical and Computer Engineering, University of Florida GainesvilleUnited States
                [4 ]Department of Agricultural & Biological Engineering, University of Florida GainesvilleUnited States
                [5 ]Nelson Institute for Environmental Studies, University of Wisconsin-Madison MadisonUnited States
                [6 ]Informatics Institute, University of Florida GainesvilleUnited States
                [7 ]Biodiversity Institute, University of Florida GainesvilleUnited States
                University of Zurich Switzerland
                University of Zurich Switzerland
                University of Zurich Switzerland
                University of Zurich Switzerland
                Author information
                https://orcid.org/0000-0002-2176-7935
                https://orcid.org/0000-0002-4847-7604
                https://orcid.org/0000-0001-6728-7745
                Article
                62922
                10.7554/eLife.62922
                7895524
                33605211
                6d5438ad-0c0a-477a-a330-663a1b672228
                © 2021, Weinstein et al

                This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

                History
                : 09 September 2020
                : 15 February 2021
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000936, Gordon and Betty Moore Foundation;
                Award ID: GBMF4563
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000001, National Science Foundation;
                Award ID: 1926542
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100005825, National Institute of Food and Agriculture;
                Award ID: McIntire Stennis projects #1007080
                Award Recipient :
                The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
                Categories
                Tools and Resources
                Ecology
                Custom metadata
                A first continental data set of tree crown predictions is derived across the United States for the National Ecological Observatory Network.

                Life sciences
                trees,neon,remote sensing,object detection,deep learning,other
                Life sciences
                trees, neon, remote sensing, object detection, deep learning, other

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