| 1. |
- Hyde, Kevin D., et al.
(författare)
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One stop shop: backbones trees for important phytopathogenic genera: I (2014)
- 2014
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Ingår i: Fungal diversity. - : Springer Science and Business Media LLC. - 1560-2745 .- 1878-9129. ; 67:1, s. 21-125
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Tidskriftsartikel (refereegranskat)abstract
- Many fungi are pathogenic on plants and cause significant damage in agriculture and forestry. They are also part of the natural ecosystem and may play a role in regulating plant numbers/density. Morphological identification and analysis of plant pathogenic fungi, while important, is often hampered by the scarcity of discriminatory taxonomic characters and the endophytic or inconspicuous nature of these fungi. Molecular (DNA sequence) data for plant pathogenic fungi have emerged as key information for diagnostic and classification studies, although hampered in part by non-standard laboratory practices and analytical methods. To facilitate current and future research, this study provides phylogenetic synopses for 25 groups of plant pathogenic fungi in the Ascomycota, Basidiomycota, Mucormycotina (Fungi), and Oomycota, using recent molecular data, up-to-date names, and the latest taxonomic insights. Lineage-specific laboratory protocols together with advice on their application, as well as general observations, are also provided. We hope to maintain updated backbone trees of these fungal lineages over time and to publish them jointly as new data emerge. Researchers of plant pathogenic fungi not covered by the present study are invited to join this future effort. Bipolaris, Botryosphaeriaceae, Botryosphaeria, Botrytis, Choanephora, Colletotrichum, Curvularia, Diaporthe, Diplodia, Dothiorella, Fusarium, Gilbertella, Lasiodiplodia, Mucor, Neofusicoccum, Pestalotiopsis, Phyllosticta, Phytophthora, Puccinia, Pyrenophora, Pythium, Rhizopus, Stagonosporopsis, Ustilago and Verticillium are dealt with in this paper.
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| 2. |
- Davies, Stuart J., et al.
(författare)
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ForestGEO: Understanding forest diversity and dynamics through a global observatory network
- 2021
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Ingår i: Biological Conservation. - : Elsevier BV. - 0006-3207. ; 253
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Tidskriftsartikel (refereegranskat)abstract
- ForestGEO is a network of scientists and long-term forest dynamics plots (FDPs) spanning the Earth's major forest types. ForestGEO's mission is to advance understanding of the diversity and dynamics of forests and to strengthen global capacity for forest science research. ForestGEO is unique among forest plot networks in its large-scale plot dimensions, censusing of all stems ≥1 cm in diameter, inclusion of tropical, temperate and boreal forests, and investigation of additional biotic (e.g., arthropods) and abiotic (e.g., soils) drivers, which together provide a holistic view of forest functioning. The 71 FDPs in 27 countries include approximately 7.33 million living trees and about 12,000 species, representing 20% of the world's known tree diversity. With >1300 published papers, ForestGEO researchers have made significant contributions in two fundamental areas: species coexistence and diversity, and ecosystem functioning. Specifically, defining the major biotic and abiotic controls on the distribution and coexistence of species and functional types and on variation in species' demography has led to improved understanding of how the multiple dimensions of forest diversity are structured across space and time and how this diversity relates to the processes controlling the role of forests in the Earth system. Nevertheless, knowledge gaps remain that impede our ability to predict how forest diversity and function will respond to climate change and other stressors. Meeting these global research challenges requires major advances in standardizing taxonomy of tropical species, resolving the main drivers of forest dynamics, and integrating plot-based ground and remote sensing observations to scale up estimates of forest diversity and function, coupled with improved predictive models. However, they cannot be met without greater financial commitment to sustain the long-term research of ForestGEO and other forest plot networks, greatly expanded scientific capacity across the world's forested nations, and increased collaboration and integration among research networks and disciplines addressing forest science.
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| 3. |
- Yu, Kailiang, et al.
(författare)
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Forest demography and biomass accumulation rates are associated with transient mean tree size vs. density scaling relations
- 2024
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Ingår i: PNAS Nexus. - 2752-6542. ; 3:2
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Tidskriftsartikel (refereegranskat)abstract
- Linking individual and stand-level dynamics during forest development reveals a scaling relationship between mean tree size and tree density in forest stands, which integrates forest structure and function. However, the nature of this so-called scaling law and its variation across broad spatial scales remain unquantified, and its linkage with forest demographic processes and carbon dynamics remains elusive. In this study, we develop a theoretical framework and compile a broad-scale dataset of long-term sample forest stands (n = 1,433) from largely undisturbed forests to examine the association of temporal mean tree size vs. density scaling trajectories (slopes) with biomass accumulation rates and the sensitivity of scaling slopes to environmental and demographic drivers. The results empirically demonstrate a large variation of scaling slopes, ranging from −4 to −0.2, across forest stands in tropical, temperate, and boreal forest biomes. Steeper scaling slopes are associated with higher rates of biomass accumulation, resulting from a lower offset of forest growth by biomass loss from mortality. In North America, scaling slopes are positively correlated with forest stand age and rainfall seasonality, thus suggesting a higher rate of biomass accumulation in younger forests with lower rainfall seasonality. These results demonstrate the strong association of the transient mean tree size vs. density scaling trajectories with forest demography and biomass accumulation rates, thus highlighting the potential of leveraging forest structure properties to predict forest demography, carbon fluxes, and dynamics at broad spatial scales.
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