Author
Oliver L. Phillips
Other affiliations: University of York, University of Brasília, Center for Plant Conservation ...read more
Bio: Oliver L. Phillips is an academic researcher from University of Leeds. The author has contributed to research in topics: Biodiversity & Amazon rainforest. The author has an hindex of 98, co-authored 336 publications receiving 50569 citations. Previous affiliations of Oliver L. Phillips include University of York & University of Brasília.
Papers published on a yearly basis
Papers
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01 Jan 2015
TL;DR: A field manual for intensive census plots (v3.0) as mentioned in this paper describes the field methods used across the RAINFOR-GEM network of forest census plots, including initial plot set up and ongoing measurement of ecosystem carbon components including above-ground live biomass, litter, roots, woody debris and various forms of CO2 efflux.
Abstract: A RAINFOR-GEM field manual for intensive census plots (v3.0) A complete description of the field methods used across the RAINFOR-GEM network of forest census plots, including initial plot set-up and ongoing measurement of ecosystem carbon components including above-ground live biomass, litter, roots, woody debris and various forms of CO2 efflux. See http://gem.tropicalforests.ox.ac.uk/page/resources/ and http://www.tobymarthews.com/rainfor-gem-manual-v30.html for further information. Data was collected 2011 to 2014
69 citations
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University of Leeds1, Royal Botanic Garden Edinburgh2, National Autonomous University of Mexico3, James Cook University4, University of Kent5, Universidad del Tolima6, Wageningen University and Research Centre7, National Institute of Amazonian Research8, University of Lorraine9, Paul Sabatier University10, University of Edinburgh11, University of Texas at Austin12, Museu Paraense Emílio Goeldi13, Smithsonian Tropical Research Institute14, University of Wisconsin–Milwaukee15, Amazon.com16, Conservation International17, University College London18, Environmental Change Institute19, Universidade do Estado de Mato Grosso20, National University of Colombia21, Duke University22, Universidad Nacional de la Amazonía Peruana23, University of Los Andes24, Empresa Brasileira de Pesquisa Agropecuária25, Universidade Federal do Acre26, Utrecht University27, Naturalis28
TL;DR: It is shown that fast demographic traits – short turnover times – are associated with high diversification rates across 51 clades of canopy trees, which reveals the crucial role of intrinsic, ecological variation among clades for understanding the origin of the remarkable diversity of Amazonian trees and forests.
Abstract: The Amazon rain forest sustains the world's highest tree diversity, but it remains unclear why some clades of trees are hyperdiverse, whereas others are not. Using dated phylogenies, estimates of current species richness and trait and demographic data from a large network of forest plots, we show that fast demographic traits – short turnover times – are associated with high diversification rates across 51 clades of canopy trees. This relationship is robust to assuming that diversification rates are either constant or decline over time, and occurs in a wide range of Neotropical tree lineages. This finding reveals the crucial role of intrinsic, ecological variation among clades for understanding the origin of the remarkable diversity of Amazonian trees and forests.
69 citations
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TL;DR: In this paper, the authors studied the ecological processes underpinning the structure and dynamics of a liana-infested forest in French Guiana, using a combination of long-term surveys (tree, liana, seedling and litterfall), soil chemical analyses and remote-sensing approaches (LiDAR and Landsat).
Abstract: 1. Empirical evidence and modelling both suggest that global changes may lead to an increased dominance of lianas and thus to an increased prevalence of liana-infested forest formations in tropical forests. The implications for tropical forest structure and the carbon cycle remain poorly understood.
2. We studied the ecological processes underpinning the structure and dynamics of a liana-infested forest in French Guiana, using a combination of long-term surveys (tree, liana, seedling and litterfall), soil chemical analyses and remote-sensing approaches (LiDAR and Landsat).
3. At stand scale and for adult trees, the liana-infested forest had higher growth, recruitment and mortality rates than the neighbouring high-canopy forest. Both total seedling density and tree seedling recruitment were lower in the liana-infested forest. Stand scale above-ground biomass of the
liana-infested forest was 58% lower than in the high-canopy forest.
4. Above-ground net primary productivity (ANPP) was comparable in the liana-infested and highcanopy forests. However, due to more abundant leaf production, the relative contribution of fast turnover carbon pools to ANPP was larger in the liana-infested forest and the carbon residence time
was half that of the high-canopy forest.
5. Although soils of the liana-infested forest were richer in nutrients, soil elemental ratios suggest that liana-infested forest and high-canopy forest soils both derive from the same geological substrate. The higher nutrient concentration in the liana-infested forest may therefore be the result of a release of nutrients from vegetation after a forest blowdown.
6. Using small-footprint LiDAR campaigns, we show that the overall extent of the liana-infested forest has remained stable from 2007 to 2012 but about 10% of the forest area changed in forest cover type. Landsat optical imagery confirms the liana-infested forest presence in the landscape for
at least 25 years.
7. Synthesis. Because persistently high rates of liana infestation are maintained by the fast dynamics of the liana-infested forest, liana-infested forests here appear to be the result of an arrested tropical forest succession. If the prevalence of such arrested succession forests were to increase in the future, this would have important implications for the carbon sink potential of Amazonian forests.
68 citations
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TL;DR: In this article, a simple model was applied to estimate and extrapolate necromass stocks across terra firma Amazonian forests, and the results showed that necrophages are positively related to both forest dynamics and a surrogate for decomposition rate (average wood density of living trees).
Abstract: . The Amazon basin, one of the most substantial biomass carbon pools on earth, is characterised by strong macroecological gradients in biomass, mortality rates, and wood density from west to east. These gradients could affect necromass stocks, but this has not yet been tested. This study aims to assess the stocks and determinants of necromass across Amazonian forests. Field-based and literature data were used to find relationships between necromass and possible determinants. Furthermore, a simple model was applied to estimate and extrapolate necromass stocks across terra firma Amazonian forests. In eight northwestern and three northeastern Amazonian permanent plots, volumes of coarse woody debris (≥10 cm diameter) were measured in the field and the density of each decay class was estimated. Forest structure and historical mortality data were used to determine the factors controlling necromass. Necromass is greater in forests with low stem mortality rates (northeast) rather than in forests with high stem mortality rates (northwest) (58.5±10.6 and 27.3±3.2 Mg ha−1, respectively). Using all published necromass values, we find that necromass across terra firma forests in Amazonia is positively related to both forest dynamics (mortality mass inputs and a surrogate for decomposition rate (average wood density of living trees)) and forest structure (biomass), but is better explained by forest dynamics. We propose an improved method to estimate necromass for plots where necromass has not been measured. The estimates, together with other actual measurements of necromass, were scaled-up to project a total Amazonian necromass of 9.6±1.0 Pg C. The ratio of necromass (on average weighted by forest region) to coarse aboveground biomass is 0.127. Overall, we find (1) a strong spatial trend in necromass in parallel with other macroecological gradients and (2) that necromass is a substantial component of the carbon pool in the Amazon.
68 citations
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TL;DR: In this paper, the authors show how a global community is responding to the challenges of tropical ecosystem research with diverse teams measuring forests tree-by-tree in thousands of long-term plots.
66 citations
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28 Jul 2005
TL;DR: PfPMP1)与感染红细胞、树突状组胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作�ly.
Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1(PfPMP1)与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员,通过启动转录不同的var基因变异体为抗原变异提供了分子基础。
18,940 citations
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TL;DR: Preface to the Princeton Landmarks in Biology Edition vii Preface xi Symbols used xiii 1.
Abstract: Preface to the Princeton Landmarks in Biology Edition vii Preface xi Symbols Used xiii 1. The Importance of Islands 3 2. Area and Number of Speicies 8 3. Further Explanations of the Area-Diversity Pattern 19 4. The Strategy of Colonization 68 5. Invasibility and the Variable Niche 94 6. Stepping Stones and Biotic Exchange 123 7. Evolutionary Changes Following Colonization 145 8. Prospect 181 Glossary 185 References 193 Index 201
14,171 citations
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TL;DR: In this paper, the use of the maximum entropy method (Maxent) for modeling species geographic distributions with presence-only data was introduced, which is a general-purpose machine learning method with a simple and precise mathematical formulation.
13,120 citations
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University of Melbourne1, Stony Brook University2, City University of New York3, Princeton University4, University of Lausanne5, University of California, Berkeley6, University of Alaska Fairbanks7, National Institute of Water and Atmospheric Research8, Commonwealth Scientific and Industrial Research Organisation9, University of São Paulo10, University of Missouri11, Consejo Nacional de Ciencia y Tecnología12, University of Kansas13, Landcare Research14, AT&T15, McGill University16, James Cook University17, Swiss Federal Institute for Forest, Snow and Landscape Research18
TL;DR: This work compared 16 modelling methods over 226 species from 6 regions of the world, creating the most comprehensive set of model comparisons to date and found that presence-only data were effective for modelling species' distributions for many species and regions.
Abstract: Prediction of species' distributions is central to diverse applications in ecology, evolution and conservation science. There is increasing electronic access to vast sets of occurrence records in museums and herbaria, yet little effective guidance on how best to use this information in the context of numerous approaches for modelling distributions. To meet this need, we compared 16 modelling methods over 226 species from 6 regions of the world, creating the most comprehensive set of model comparisons to date. We used presence-only data to fit models, and independent presence-absence data to evaluate the predictions. Along with well-established modelling methods such as generalised additive models and GARP and BIOCLIM, we explored methods that either have been developed recently or have rarely been applied to modelling species' distributions. These include machine-learning methods and community models, both of which have features that may make them particularly well suited to noisy or sparse information, as is typical of species' occurrence data. Presence-only data were effective for modelling species' distributions for many species and regions. The novel methods consistently outperformed more established methods. The results of our analysis are promising for the use of data from museums and herbaria, especially as methods suited to the noise inherent in such data improve.
7,589 citations
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Australian National University1, Stockholm Resilience Centre2, University of Copenhagen3, McGill University4, Stellenbosch University5, University of Wisconsin-Madison6, Wageningen University and Research Centre7, Stockholm University8, Royal Swedish Academy of Sciences9, Potsdam Institute for Climate Impact Research10, Commonwealth Scientific and Industrial Research Organisation11, International Livestock Research Institute12, University College London13, Stockholm Environment Institute14, The Energy and Resources Institute15, University of California, San Diego16, Royal Institute of Technology17
TL;DR: An updated and extended analysis of the planetary boundary (PB) framework and identifies levels of anthropogenic perturbations below which the risk of destabilization of the Earth system (ES) is likely to remain low—a “safe operating space” for global societal development.
Abstract: The planetary boundaries framework defines a safe operating space for humanity based on the intrinsic biophysical processes that regulate the stability of the Earth system. Here, we revise and update the planetary boundary framework, with a focus on the underpinning biophysical science, based on targeted input from expert research communities and on more general scientific advances over the past 5 years. Several of the boundaries now have a two-tier approach, reflecting the importance of cross-scale interactions and the regional-level heterogeneity of the processes that underpin the boundaries. Two core boundaries—climate change and biosphere integrity—have been identified, each of which has the potential on its own to drive the Earth system into a new state should they be substantially and persistently transgressed.
7,169 citations