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Oliver L. Phillips

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
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Journal ArticleDOI
TL;DR: In this paper, the authors verified the field carbon concentration values of living trees and woody debris in two distinct tropical forests in Taiwan and found that both wood density and carbon concentration (carbon mass/total mass) declined significantly with the decay class of the wood.

17 citations

Book ChapterDOI
01 Jan 1991

16 citations

Journal ArticleDOI
TL;DR: In this paper, a ground-based quantification of gold mining impacts on Amazon forest biomass recovery is presented, showing that the recovery process is highly dependent on nitrogen availability rather than mercury contamination, affecting woody biomass regrowth.
Abstract: 1 Gold mining has rapidly increased across the Amazon Basin in recent years, especially in the Guiana shield, where it is responsible for >90% of total deforestation However, the ability of forests to recover from gold mining activities remains largely unquantified 2 Forest inventory plots were installed on recently abandoned mines in two major mining regions in Guyana, and re‐censused 18 months later, to provide the first ground‐based quantification of gold mining impacts on Amazon forest biomass recovery 3 We found that woody biomass recovery rates on abandoned mining pits and tailing ponds are among the lowest ever recorded for tropical forests, with close to no woody biomass recovery after 3–4 years 4 On the overburden sites (ie areas not mined but where excavated soil is deposited), however, above‐ground biomass recovery rates (04–54 Mg ha−1 year−1) were within the range of those recorded in other secondary forests across the Neotropics following abandonment of pastures and agricultural lands 5 Our results suggest that forest recovery is more strongly limited by severe mining‐induced depletion of soil nutrients, especially nitrogen, than by mercury contamination, due to slowing of growth in nutrient‐stripped soils 6 We estimate that the slow recovery rates in mining pits and ponds currently reduce carbon sequestration across Amazonian secondary forests by ~21,000 t C/year, compared to the carbon that would have accumulated following more traditional land uses such as agriculture or pasture 7 Synthesis and applications To achieve large‐scale restoration targets, Guyana and other Amazonian countries will be challenged to remediate previously mined lands The recovery process is highly dependent on nitrogen availability rather than mercury contamination, affecting woody biomass regrowth The significant recovery in overburden zones indicates that one potential active remediation strategy to promote biomass recovery may be to backfill mining pits and ponds with excavated soil

16 citations

Journal ArticleDOI
01 May 2021
TL;DR: In this article, the authors provide a protocol for permanent monitoring plots in tropical dry forests. But despite increasing appreciation of their threatened status, biodiversity, and importance to the global carbon cycle, monitoring in tropical drier forests is still in its infancy.
Abstract: Understanding of tropical forests has been revolutionized by monitoring in permanent plots. Data from global plot networks have transformed our knowledge of forests? diversity, function, contribution to global biogeochemical cycles, and sensitivity to climate change. Monitoring has thus far been concentrated in rain forests. Despite increasing appreciation of their threatened status, biodiversity, and importance to the global carbon cycle, monitoring in tropical dry forests is still in its infancy. We provide a protocol for permanent monitoring plots in tropical dry forests. Expanding monitoring into dry biomes is critical for overcoming the linked challenges of climate change, land use change, and the biodiversity crisis.

15 citations


Cited by
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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

Journal ArticleDOI
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

Journal ArticleDOI
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

Journal ArticleDOI
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

Journal ArticleDOI
13 Feb 2015-Science
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