12 research outputs found

    Networking the forest infrastructure towards near real-time monitoring – A white paper

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    Forests account for nearly 90 % of the world's terrestrial biomass in the form of carbon and they support 80 % of the global biodiversity. To understand the underlying forest dynamics, we need a long-term but also relatively high-frequency, networked monitoring system, as traditionally used in meteorology or hydrology. While there are numerous existing forest monitoring sites, particularly in temperate regions, the resulting data streams are rarely connected and do not provide information promptly, which hampers real-time assessments of forest responses to extreme climate events. The technology to build a better global forest monitoring network now exists. This white paper addresses the key structural components needed to achieve a novel meta-network. We propose to complement - rather than replace or unify - the existing heterogeneous infrastructure with standardized, quality-assured linking methods and interacting data processing centers to create an integrated forest monitoring network. These automated (research topic-dependent) linking methods in atmosphere, biosphere, and pedosphere play a key role in scaling site-specific results and processing them in a timely manner. To ensure broad participation from existing monitoring sites and to establish new sites, these linking methods must be as informative, reliable, affordable, and maintainable as possible, and should be supplemented by near real-time remote sensing data. The proposed novel meta-network will enable the detection of emergent patterns that would not be visible from isolated analyses of individual sites. In addition, the near real-time availability of data will facilitate predictions of current forest conditions (nowcasts), which are urgently needed for research and decision making in the face of rapid climate change. We call for international and interdisciplinary efforts in this direction

    Networking the forest infrastructure towards near real-time monitoring - A white paper.

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    Forests account for nearly 90 % of the world's terrestrial biomass in the form of carbon and they support 80 % of the global biodiversity. To understand the underlying forest dynamics, we need a long-term but also relatively high-frequency, networked monitoring system, as traditionally used in meteorology or hydrology. While there are numerous existing forest monitoring sites, particularly in temperate regions, the resulting data streams are rarely connected and do not provide information promptly, which hampers real-time assessments of forest responses to extreme climate events. The technology to build a better global forest monitoring network now exists. This white paper addresses the key structural components needed to achieve a novel meta-network. We propose to complement - rather than replace or unify - the existing heterogeneous infrastructure with standardized, quality-assured linking methods and interacting data processing centers to create an integrated forest monitoring network. These automated (research topic-dependent) linking methods in atmosphere, biosphere, and pedosphere play a key role in scaling site-specific results and processing them in a timely manner. To ensure broad participation from existing monitoring sites and to establish new sites, these linking methods must be as informative, reliable, affordable, and maintainable as possible, and should be supplemented by near real-time remote sensing data. The proposed novel meta-network will enable the detection of emergent patterns that would not be visible from isolated analyses of individual sites. In addition, the near real-time availability of data will facilitate predictions of current forest conditions (nowcasts), which are urgently needed for research and decision making in the face of rapid climate change. We call for international and interdisciplinary efforts in this direction

    Meta-analysis of multidecadal biodiversity trends in Europe

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    Abstract Local biodiversity trends over time are likely to be decoupled from global trends, as local processes may compensate or counteract global change. We analyze 161 long-term biological time series (15–91 years) collected across Europe, using a comprehensive dataset comprising ~6,200 marine, freshwater and terrestrial taxa. We test whether (i) local long-term biodiversity trends are consistent among biogeoregions, realms and taxonomic groups, and (ii) changes in biodiversity correlate with regional climate and local conditions. Our results reveal that local trends of abundance, richness and diversity differ among biogeoregions, realms and taxonomic groups, demonstrating that biodiversity changes at local scale are often complex and cannot be easily generalized. However, we find increases in richness and abundance with increasing temperature and naturalness as well as a clear spatial pattern in changes in community composition (i.e. temporal taxonomic turnover) in most biogeoregions of Northern and Eastern Europe

    Environment and host as large-scale controls of ectomycorrhizal fungi

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    Early stage litter decomposition across biomes

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    Through litter decomposition enormous amounts of carbon is emitted to the atmosphere. Numerous large-scale decomposition experiments have been conducted focusing on this fundamental soil process in order to understand the controls on the terrestrial carbon transfer to the atmosphere. However, previous studies were mostly based on site-specific litter and methodologies, adding major uncertainty to syntheses, comparisons and meta-analyses across different experiments and sites. In the TeaComposition initiative, the potential litter decomposition is investigated by using standardized substrates (Rooibos and Green tea) for comparison of litter mass loss at 336 sites (ranging from −9 to +26 °C MAT and from 60 to 3113 mm MAP) across different ecosystems. In this study we tested the effect of climate (temperature and moisture), litter type and land-use on early stage decomposition (3 months) across nine biomes. We show that litter quality was the predominant controlling factor in early stage litter decomposition, which explained about 65% of the variability in litter decomposition at a global scale. The effect of climate, on the other hand, was not litter specific and explained <0.5% of the variation for Green tea and 5% for Rooibos tea, and was of significance only under unfavorable decomposition conditions (i.e. xeric versus mesic environments). When the data were aggregated at the biome scale, climate played a significant role on decomposition of both litter types (explaining 64% of the variation for Green tea and 72% for Rooibos tea). No significant effect of land-use on early stage litter decomposition was noted within the temperate biome. Our results indicate that multiple drivers are affecting early stage litter mass loss with litter quality being dominant. In order to be able to quantify the relative importance of the different drivers over time, long-term studies combined with experimental trials are needed.This work was performed within the TeaComposition initiative, carried out by 190 institutions worldwide. We thank Gabrielle Drozdowski for her help with the packaging and shipping of tea, Zora Wessely and Johannes Spiegel for the creative implementation of the acknowledgement card, Josip Dusper for creative implementation of the graphical abstract, Christine Brendle for the GIS editing, and Marianne Debue for her help with the data cleaning. Further acknowledgements go to Adriana Principe, Melanie Köbel, Pedro Pinho, Thomas Parker, Steve Unger, Jon Gewirtzman and Margot McKleeven for the implementation of the study at their respective sites. We are very grateful to UNILEVER for sponsoring the Lipton tea bags and to the COST action ClimMani for scientific discussions, adoption and support to the idea of TeaComposition as a common metric. The initiative was supported by the following grants: ILTER Initiative Grant, ClimMani Short-Term Scientific Missions Grant (COST action ES1308; COST-STSM-ES1308-36004; COST-STM-ES1308-39006; ES1308-231015-068365), INTERACT (EU H2020 Grant No. 730938), and Austrian Environment Agency (UBA). Franz Zehetner acknowledges the support granted by the Prometeo Project of Ecuador's Secretariat of Higher Education, Science, Technology and Innovation (SENESCYT) as well as Charles Darwin Foundation for the Galapagos Islands (2190). Ana I. Sousa, Ana I. Lillebø and Marta Lopes thanks for the financial support to CESAM (UID/AMB/50017), to FCT/MEC through national funds (PIDDAC), and the co-funding by the FEDER, within the PT2020 Partnership Agreement and Compete 2020. The research was also funded by the Portuguese Foundation for Science and Technology, FCT, through SFRH/BPD/107823/2015 (A.I. Sousa), co-funded by POPH/FSE. Thomas Mozdzer thanks US National Science Foundation NSF DEB-1557009. Helena C. Serrano thanks Fundação para a Ciência e Tecnologia (UID/BIA/00329/2013). Milan Barna acknowledges Scientific Grant Agency VEGA (2/0101/18). Anzar A Khuroo acknowledges financial support under HIMADRI project from SAC-ISRO, India
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