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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University of São Paulo1, Escola Superior de Agricultura Luiz de Queiroz2, University of Leeds3, State University of Campinas4, Paul Sabatier University5, National Institute of Amazonian Research6, Amazon.com7, United States Department of Agriculture8, University of New Hampshire9, Federal University of Rio de Janeiro10, Universidade Federal de Minas Gerais11, National Institute for Space Research12, Universidade Federal do Acre13, University of California, Berkeley14
TL;DR: In this paper, the authors present and discuss the best methods to estimate live above ground biomass in the Atlantic Forest, which is a function of wood volume, obtained from the diameter and height, architecture and wood density (dry weight per unit volume of fresh wood).
Abstract: The main objective of this paper is to present and discuss the best methods to estimate live above ground biomass in the Atlantic Forest. The methods presented and conclusions are the products of a workshop entitled "Estimation of Biomass and Carbon Stocks: the Case of Atlantic Rain Forest". Aboveground biomass (AGB) in tropical forests is mainly contained in trees. Tree biomass is a function of wood volume, obtained from the diameter and height, architecture and wood density (dry weight per unit volume of fresh wood). It can be quantified by the direct (destructive) or indirect method where the biomass quantification is estimated using mathematical models. The allometric model can be site specific when elaborated to a particular ecosystem or general that can be used in different sites. For the Atlantic Forest, despite the importance of it, there are only two direct measurements of tree biomass, resulting in allometric models specific for this ecosystem. To select one or other of the available models in the literature to estimate AGB it is necessary take into account what is the main question to be answered and the ease with which it is possible to measure the independent variables in the model. Models that present more accurate estimates should be preferred. However, more simple models (those with one independent variable, usually DBH) can be used when the focus is monitoring the variation in carbon storage through the time. Our observations in the Atlantic Forest suggest that pan-tropical relations proposed by Chave et al. (2005) can be confidently used to estimated tree biomass across biomes as long as tree diameter (DBH), height, and wood density are accounted for in the model. In Atlantic Forest, we recommend the quantification of biomass of lianas, bamboo, palms, tree ferns and epiphytes, which are an important component in this ecosystem. This paper is an outcome of the workshop entitled "Estimation of Biomass and Carbon Stocks: the Case of Atlantic Rain Forest", that was conducted at Ubatuba, Sao Paulo, Brazil, between 4 and 8 December 2006 as part of the Brazilian project "Ombrophylus Dense Forest floristic composition, structure and function at the Nucleos Picinguaba and Santa Virginia of the Serra do Mar State Park", BIOTA Gradiente.
119 citations
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TL;DR: In this article, a U-net convolutional network was used to identify and segment natural forests and eucalyptus plantations, and an indicator of forest disturbance, the tree species Cecropia hololeuca, in very high resolution images (0.3 m) from the WorldView-3 satellite in the Brazilian Atlantic rainforest region.
Abstract: Mapping forest types and tree species at regional scales to provide information for ecologists and forest managers is a new challenge for the remote sensing community. Here, we assess the potential of a U‐net convolutional network, a recent deep learning algorithm, to identify and segment (1) natural forests and eucalyptus plantations, and (2) an indicator of forest disturbance, the tree species Cecropia hololeuca, in very high resolution images (0.3 m) from the WorldView‐3 satellite in the Brazilian Atlantic rainforest region. The networks for forest types and Cecropia trees were trained with 7611 and 1568 red‐green‐blue (RGB) images, respectively, and their dense labeled masks. Eighty per cent of the images were used for training and 20% for validation. The U‐net network segmented forest types with an overall accuracy >95% and an intersection over union (IoU) of 0.96. For C. hololeuca, the overall accuracy was 97% and the IoU was 0.86. The predictions were produced over a 1600 km2 region using WorldView‐3 RGB bands pan‐sharpened at 0.3 m. Natural and eucalyptus forests compose 79 and 21% of the region's total forest cover (82 250 ha). Cecropia crowns covered 1% of the natural forest canopy. An index to describe the level of disturbance of the natural forest fragments based on the spatial distribution of Cecropia trees was developed. Our work demonstrates how a deep learning algorithm can support applications such as vegetation, tree species distributions and disturbance mapping on a regional scale.
117 citations
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TL;DR: In this article, the woody biomass residence time (τw) of an ecosystem is an important variable for accurately simulating its biomass stocks, and the authors reviewed published data from 177 ecosystems.
Abstract: Background: The woody biomass residence time (τw) of an ecosystem is an important variable for accurately simulating its biomass stocks. Methods and results: We reviewed published data from 177 for...
117 citations
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TL;DR: Vormisto et al. as mentioned in this paper carried out a comparison among the floristic patterns of four different plant groups (palms, trees, melastomes and pteridophytes) in a lowland rainforest site in Peruvian Amazonia.
Abstract: Vormisto, J., Phillips, O. L., Ruokolainen, K., Tuomisto, H. and Vasquez, R. 2000. A comparison of fine-scale distribution patterns of four plant groups in an Amazo- nian rainforest. - Ecography 23: 349-359. We carried out a comparison among the floristic patterns of four different plant groups (palms, trees, melastomes and pteridophytes) in a lowland rainforest site in Peruvian Amazonia. The study site consisted of a mosaic of edaphic patches reflecting the different geological formations that can be found on the surface. We collected the data along a linear transect (500 m long, divided into 20 20 mo r 5 20 m subplots), and recorded of the four plant groups all individuals that exceeded a minimum size limit predefined for each plant group. We also recorded the drainage conditions and soil type classes in each subplot of the transect. The results indicated that different plant groups can produce similar floristic patterns in local spatial scales, and that these patterns reflect similarities in edaphic conditions. All matrix correlations calculated between pairs of the four plant groups were positive and statistically significant. Floristic composition in all plant groups correlated with soil class, and to a somewhat lesser degree with drainage. These results imply that any one of the four plant groups could serve as a rough indicator of more general floristic patterns, and that even the inventory of a limited part of the flora can shed light on the floristic variation found in Amazonian forests.
116 citations
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James Cook University1, University of Leeds2, University of Edinburgh3, Forest Research Institute4, Commonwealth Scientific and Industrial Research Organisation5, Universidade do Estado de Mato Grosso6, Royal Botanic Garden Edinburgh7, University of Yaoundé I8, National Institute of Amazonian Research9, University of Brasília10, Forestry Commission11, University of Tasmania12, Conservation International13, University College London14
TL;DR: In this article, the authors integrated observed variations in tropical vegetation structure and floristic composition into a single classification scheme by using clustering techniques to identify twelve structural groupings based on height and canopy cover of the dominant upper stratum.
Abstract: Background: There is no generally agreed classification scheme for the many different vegetation formation types occurring in the tropics. This hinders cross-continental comparisons and causes confusion as words such as ‘forest’ and ‘savanna’ have different meanings to different people. Tropical vegetation formations are therefore usually imprecisely and/or ambiguously defined in modelling, remote sensing and ecological studies. Aims: To integrate observed variations in tropical vegetation structure and floristic composition into a single classification scheme. Methods: Using structural and floristic measurements made on three continents, discrete tropical vegetation groupings were defined on the basis of overstorey and understorey structure and species compositions by using clustering techniques. Results: Twelve structural groupings were identified based on height and canopy cover of the dominant upper stratum and the extent of lower-strata woody shrub cover and grass cover. Structural classifications di...
110 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