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.

Do species traits determine patterns of wood production in Amazonian forests

Abstract: . Understanding the relationships between plant traits and ecosystem properties at large spatial scales is important for predicting how compositional change will affect carbon cycling in tropical forests. In this study, we examine the relationships between species wood density, maximum height and above-ground, coarse wood production of trees ≥10 cm diameter (CWP) for 60 Amazonian forest plots. Average species maximum height and wood density are lower in Western than Eastern Amazonia and are negatively correlated with CWP. To test the hypothesis that variation in these traits causes the variation in CWP, we generate plot-level estimates of CWP by resampling the full distribution of tree biomass growth rates whilst maintaining the appropriate tree-diameter and functional-trait distributions for each plot. These estimates are then compared with the observed values. Overall, the estimates do not predict the observed, regional-scale pattern of CWP, suggesting that the variation in community-level trait values does not determine variation in coarse wood productivity in Amazonian forests. Instead, the regional gradient in CWP is caused by higher biomass growth rates across all tree types in Western Amazonia. Therefore, the regional gradient in CWP is driven primarily by environmental factors, rather than the particular functional composition of each stand. These results contrast with previous findings for forest biomass, where variation in wood density, associated with variation in species composition, is an important driver of regional-scale patterns in above-ground biomass. Therefore, in tropical forests, above-ground wood productivity may be less sensitive than biomass to compositional change that alters community-level averages of these plant traits.

The changing ecology of tropical forests

Abstract: The threat to tropical forests is often gauged in terms of deforestation rates and the total area remaining. Recently, however, there has been a growing realization that forest can appear intact on a satellite image yet be biologically degraded or vulnerable to degradation. The array of direct threats to humid tropical forest biodiversity, in addition to deforestation, includes: selective extraction of plants; selective extraction of animals; biological invasion; fragmentation; climate change; changing atmospheric composition; and increasing tree turnover rates. The threats are linked to one another by a poorly understood network of causality and feedback effects. Moreover, their potential impacts on forest biodiversity are hard to assess because each threat is as likely to precipitate indirect effects as direct effects, and because several threats are likely to interact synergistically with one another. In spite of the uncertainties, it is clear that the biological health of tropical forests can become seriously degraded as a result of these threats, and it is unlikely that any tropical forest will escape significant ecological changes. Some groups of plants and animals are likely to benefit at the expense of others. Species diversity is expected to decline as a consequence of the changes in forest ecology. In the 21st century scientists and conservationists will be increasingly challenged to monitor, understand, prevent and head off these threats.

Solar radiation and functional traits explain the decline of forest primary productivity along a tropical elevation gradient

Abstract: One of the major challenges in ecology is to understand how ecosystems respond to changes in environmental conditions, and how taxonomic and functional diversity mediate these changes. In this study, we use a trait-spectra and individual-based model, to analyse variation in forest primary productivity along a 3.3 km elevation gradient in the Amazon-Andes. The model accurately predicted the magnitude and trends in forest productivity with elevation, with solar radiation and plant functional traits (leaf dry mass per area, leaf nitrogen and phosphorus concentration, and wood density) collectively accounting for productivity variation. Remarkably, explicit representation of temperature variation with elevation was not required to achieve accurate predictions of forest productivity, as trait variation driven by species turnover appears to capture the effect of temperature. Our semi-mechanistic model suggests that spatial variation in traits can potentially be used to estimate spatial variation in productivity at the landscape scale.

Analysing Amazonian forest productivity using a new individual and trait-based model (TFS v.1)

Abstract: . Repeated long-term censuses have revealed large-scale spatial patterns in Amazon basin forest structure and dynamism, with some forests in the west of the basin having up to a twice as high rate of aboveground biomass production and tree recruitment as forests in the east. Possible causes for this variation could be the climatic and edaphic gradients across the basin and/or the spatial distribution of tree species composition. To help understand causes of this variation a new individual-based model of tropical forest growth, designed to take full advantage of the forest census data available from the Amazonian Forest Inventory Network (RAINFOR), has been developed. The model allows for within-stand variations in tree size distribution and key functional traits and between-stand differences in climate and soil physical and chemical properties. It runs at the stand level with four functional traits – leaf dry mass per area (Ma), leaf nitrogen (NL) and phosphorus (PL) content and wood density (DW) varying from tree to tree – in a way that replicates the observed continua found within each stand. We first applied the model to validate canopy-level water fluxes at three eddy covariance flux measurement sites. For all three sites the canopy-level water fluxes were adequately simulated. We then applied the model at seven plots, where intensive measurements of carbon allocation are available. Tree-by-tree multi-annual growth rates generally agreed well with observations for small trees, but with deviations identified for larger trees. At the stand level, simulations at 40 plots were used to explore the influence of climate and soil nutrient availability on the gross (ΠG) and net (ΠN) primary production rates as well as the carbon use efficiency (CU). Simulated ΠG, ΠN and CU were not associated with temperature. On the other hand, all three measures of stand level productivity were positively related to both mean annual precipitation and soil nutrient status. Sensitivity studies showed a clear importance of an accurate parameterisation of within- and between-stand trait variability on the fidelity of model predictions. For example, when functional tree diversity was not included in the model (i.e. with just a single plant functional type with mean basin-wide trait values) the predictive ability of the model was reduced. This was also the case when basin-wide (as opposed to site-specific) trait distributions were applied within each stand. We conclude that models of tropical forest carbon, energy and water cycling should strive to accurately represent observed variations in functionally important traits across the range of relevant scales.

Low stocks of coarse woody debris in a southwest Amazonian forest

Abstract: The stocks and dynamics of coarse woody debris (CWD) are significant components of the carbon cycle within tropical forests. However, to date, there have been no reports of CWD stocks and fluxes from the approximately 1.3 million km2 of lowland western Amazonian forests. Here, we present estimates of CWD stocks and annual CWD inputs from forests in southern Peru. Total stocks were low compared to other tropical forest sites, whether estimated by line-intercept sampling (24.4 ± 5.3 Mg ha−1) or by complete inventories within 11 permanent plots (17.7 ± 2.4 Mg ha−1). However, annual inputs, estimated from long-term data on tree mortality rates in the same plots, were similar to other studies (3.8 ± 0.2 or 2.9 ± 0.2 Mg ha−1 year−1, depending on the equation used to estimate biomass). Assuming the CWD pool is at steady state, the turnover time of coarse woody debris is low (4.7 ± 2.6 or 6.1 ± 2.6 years). These results indicate that these sites have not experienced a recent, large-scale disturbance event and emphasise the distinctive, rapid nature of carbon cycling in these western Amazonian forests.

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

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。

The Theory of Island Biogeography

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

Novel methods improve prediction of species' distributions from occurrence data

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.

Planetary boundaries: Guiding human development on a changing planet

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.