Institution
Wageningen University and Research Centre
Education•Wageningen, Netherlands•
About: Wageningen University and Research Centre is a education organization based out in Wageningen, Netherlands. It is known for research contribution in the topics: Population & Sustainability. The organization has 23474 authors who have published 54833 publications receiving 2608897 citations.
Topics: Population, Sustainability, Agriculture, Climate change, Gene
Papers published on a yearly basis
Papers
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University of Amsterdam1, Wageningen University and Research Centre2, Institut national de la recherche agronomique3, University of Lorraine4, University of Cologne5, National Research Council6, University of Turin7, Lund University8, Aarhus University9, University of A Coruña10, University College Dublin11, Leiden University12
TL;DR: It is proposed that relationships between soil food web structure and carbon cycling in soils need to be reconsidered and the efficiency of nutrient cycling and carbon uptake can increase by a shift in fungal composition and/or fungal activity during nature restoration.
Abstract: Soil organisms have an important role in aboveground community dynamics and ecosystem functioning in terrestrial ecosystems. However, most studies have considered soil biota as a black box or focussed on specific groups, whereas little is known about entire soil networks. Here we show that during the course of nature restoration on abandoned arable land a compositional shift in soil biota, preceded by tightening of the belowground networks, corresponds with enhanced efficiency of carbon uptake. In mid- and long-term abandoned field soil, carbon uptake by fungi increases without an increase in fungal biomass or shift in bacterial-to-fungal ratio. The implication of our findings is that during nature restoration the efficiency of nutrient cycling and carbon uptake can increase by a shift in fungal composition and/or fungal activity. Therefore, we propose that relationships between soil food web structure and carbon cycling in soils need to be reconsidered.
471 citations
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TL;DR: A review of state-of-the-art retrieval methods for quantitative terrestrial bio-geophysical variable extraction using optical remote sensing imagery and the prospects of implementing these methods into future processing chains for operational retrieval of vegetation properties are presented and discussed.
Abstract: Forthcoming superspectral satellite missions dedicated to land monitoring, as well as planned imaging spectrometers, will unleash an unprecedented data stream. The processing requirements for such large data streams involve processing techniques enabling the spatio-temporally explicit quantification of vegetation properties. Typically retrieval must be accurate, robust and fast. Hence, there is a strict requirement to identify next-generation bio-geophysical variable retrieval algorithms which can be molded into an operational processing chain. This paper offers a review of state-of-the-art retrieval methods for quantitative terrestrial bio-geophysical variable extraction using optical remote sensing imagery. We can categorize these methods into (1) parametric regression, (2) non-parametric regression, (3) physically-based and (4) hybrid methods. Hybrid methods combine generic capabilities of physically-based methods with flexible and computationally efficient methods, typically non-parametric regression methods. A review of the theoretical basis of all these methods is given first and followed by published applications. This paper focusses on: (1) retrievability of bio-geophysical variables, (2) ability to generate multiple outputs, (3) possibilities for model transparency description, (4) mapping speed, and (5) possibilities for uncertainty retrieval. Finally, the prospects of implementing these methods into future processing chains for operational retrieval of vegetation properties are presented and discussed.
471 citations
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TL;DR: The findings show that brachial FMD is inversely associated with future CVD events, with some indications for a stronger relation in diseased populations.
470 citations
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Smithsonian Tropical Research Institute1, Smithsonian Conservation Biology Institute2, National Museum of Natural History3, University of Alabama4, Stanford University5, Wilfrid Laurier University6, Mahidol University7, Department of National Parks, Wildlife and Plant Conservation8, University of Aberdeen9, Environmental Change Institute10, University of Queensland11, Xishuangbanna Tropical Botanical Garden12, University of Buea13, Indiana University14, United States Forest Service15, Indian Institute of Science16, Chinese Academy of Sciences17, National University of Colombia18, Forest Research Institute Malaysia19, University of California, Santa Cruz20, University of Peradeniya21, University of Hong Kong22, University of Alberta23, Oak Ridge National Laboratory24, University of Wisconsin–Green Bay25, University of California, Los Angeles26, College of Tropical Agriculture and Human Resources27, Wageningen University and Research Centre28, Kyoto University29, University of Nairobi30, Wildlife Conservation Society31, University of Montana32, Nanyang Technological University33, Utah State University34, Smithsonian Environmental Research Center35, Centre national de la recherche scientifique36, Natural England37, Washington University in St. Louis38, Academy of Sciences of the Czech Republic39, University of São Paulo40, University of the Philippines Diliman41, Harvard University42, University of Hawaii at Hilo43, Maejo University44, National Dong Hwa University45, University of Toronto46, Washington State University Vancouver47, University of Puerto Rico, Río Piedras48, Columbia University49, Pontificia Universidad Católica del Ecuador50, National Institute of Amazonian Research51, East China Normal University52, University of Minnesota53
TL;DR: The broad suite of measurements made at CTFS-ForestGEO sites makes it possible to investigate the complex ways in which global change is impacting forest dynamics, and continued monitoring will provide vital contributions to understanding worldwide forest diversity and dynamics in an era of global change.
Abstract: Global change is impacting forests worldwide, threatening biodiversity and ecosystem services including climate regulation. Understanding how forests respond is critical to forest conservation and climate protection. This review describes an international network of 59 long-term forest dynamics research sites (CTFS-ForestGEO) useful for characterizing forest responses to global change. Within very large plots (median size 25ha), all stems 1cm diameter are identified to species, mapped, and regularly recensused according to standardized protocols. CTFS-ForestGEO spans 25 degrees S-61 degrees N latitude, is generally representative of the range of bioclimatic, edaphic, and topographic conditions experienced by forests worldwide, and is the only forest monitoring network that applies a standardized protocol to each of the world's major forest biomes. Supplementary standardized measurements at subsets of the sites provide additional information on plants, animals, and ecosystem and environmental variables. CTFS-ForestGEO sites are experiencing multifaceted anthropogenic global change pressures including warming (average 0.61 degrees C), changes in precipitation (up to +/- 30% change), atmospheric deposition of nitrogen and sulfur compounds (up to 3.8g Nm(-2)yr(-1) and 3.1g Sm(-2)yr(-1)), and forest fragmentation in the surrounding landscape (up to 88% reduced tree cover within 5km). The broad suite of measurements made at CTFS-ForestGEO sites makes it possible to investigate the complex ways in which global change is impacting forest dynamics. Ongoing research across the CTFS-ForestGEO network is yielding insights into how and why the forests are changing, and continued monitoring will provide vital contributions to understanding worldwide forest diversity and dynamics in an era of global change.
470 citations
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TL;DR: It is found that community structure shaped the local environment and that strong relationships existed between this environment and the traits of the most successful species of the regeneration communities, demonstrating that environmental filtering is a predictable and fundamental process of community assembly, even in a complex system such as a tropical forest.
Abstract: Mechanistic models of community assembly state that biotic and abiotic filters constrain species establishment through selection on their functional traits. Predicting this assembly process is hampered because few studies directly incorporate environmental measurements and scale up from species to community level and because the functional traits' significance is environment dependent. We analyzed community assembly by measuring structure, environmental conditions, and species traits of secondary forests in a species-rich tropical system. We found, as hypothesized, that community structure shaped the local environment and that strong relationships existed between this environment and the traits of the most successful species of the regeneration communities. Path and multivariate analyses showed that temperature and leaf traits that regulate it were the most important factors of community differentiation. Comparisons between the trait composition of the forest's regeneration, juvenile, and adult communities showed a consistent community assembly pattern. These results allowed us to identify the major functional traits and environmental factors involved in the assembly of dry-forest communities and demonstrate that environmental filtering is a predictable and fundamental process of community assembly, even in a complex system such as a tropical forest.
470 citations
Authors
Showing all 23851 results
Name | H-index | Papers | Citations |
---|---|---|---|
Walter C. Willett | 334 | 2399 | 413322 |
Albert Hofman | 267 | 2530 | 321405 |
Frank B. Hu | 250 | 1675 | 253464 |
Willem M. de Vos | 148 | 670 | 88146 |
Willy Verstraete | 139 | 920 | 76659 |
Jonathan D. G. Jones | 129 | 417 | 80908 |
Bert Brunekreef | 124 | 806 | 81938 |
Pedro W. Crous | 115 | 809 | 51925 |
Marten Scheffer | 111 | 350 | 73789 |
Wim E. Hennink | 110 | 600 | 49940 |
Daan Kromhout | 108 | 453 | 55551 |
Peter H. Verburg | 107 | 464 | 34254 |
Marcel Dicke | 107 | 613 | 42959 |
Vincent W. V. Jaddoe | 106 | 1008 | 44269 |
Hao Wu | 105 | 669 | 42607 |