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Stephen E. Williams

Bio: Stephen E. Williams is an academic researcher from James Cook University. The author has contributed to research in topics: Biodiversity & Climate change. The author has an hindex of 53, co-authored 126 publications receiving 25868 citations. Previous affiliations of Stephen E. Williams include International Union for Conservation of Nature and Natural Resources & Cooperative Research Centre.


Papers
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Journal ArticleDOI
31 Jul 2013-PLOS ONE
TL;DR: Temperature is confirmed as an important factor driving elevational distributions of tropical montane birds, and species will shift upslope to track their preferred environmental conditions, according to models of temperature gradients derived from broad-scale climate surfaces.
Abstract: Among birds, tropical montane species are likely to be among the most vulnerable to climate change, yet little is known about how climate drives their distributions, nor how to predict their likely responses to temperature increases. Correlative models of species' environmental niches have been widely used to predict changes in distribution, but direct tests of the relationship between key variables, such as temperature, and species' actual distributions are few. In the absence of historical data with which to compare observations and detect shifts, space-for-time substitutions, where warmer locations are used as analogues of future conditions, offer an opportunity to test for species' responses to climate. We collected density data for rainforest birds across elevational gradients in northern and southern subregions within the Australian Wet Tropics (AWT). Using environmental optima calculated from elevational density profiles, we detected a significant elevational difference between the two regions in ten of 26 species. More species showed a positive (19 spp.) than negative (7 spp.) displacement, with a median difference of ∼80.6 m across the species analysed that is concordant with that expected due to latitudinal temperature differences (∼75.5 m). Models of temperature gradients derived from broad-scale climate surfaces showed comparable performance to those based on in-situ measurements, suggesting the former is sufficient for modeling impacts. These findings not only confirm temperature as an important factor driving elevational distributions of these species, but also suggest species will shift upslope to track their preferred environmental conditions. Our approach uses optima calculated from elevational density profiles, offering a data-efficient alternative to distribution limits for gauging climate constraints, and is sensitive enough to detect distribution shifts in this avifauna in response to temperature changes of as little as 0.4 degrees. We foresee important applications in the urgent task of detecting and monitoring impacts of climate change on montane tropical biodiversity.

27 citations

Book Chapter
01 Sep 2004
TL;DR: This paper examined the distribution of possums and gliders within the five most northerly bioregions of Queensland using point data and the DOMAIN bioclimatic modelling technique.
Abstract: A regional resource inventory forms the basis of conservation management. This chapter examines the distribution of possums and gliders within the five most northerly bioregions of Queensland using point data and the DOMAIN bioclimatic modelling technique. The Wet Tropics and Cape York Peninsula are the only bioregions to have been surveyed at a bioregional scale, the former more thoroughly than the latter. Einasleigh Uplands has been the subject of some intensive surveys, but not in a bioregional context. The few possum records from the North West Highlands are concentrated in the northern part, while those from the Gulf Plains are limited to an upland isolate at the southern end of the Gregory Range. Species richness of up to 11 species per km2 is based on predicted core climatic envelopes for each species. Extensions of known geographical range are predicted are predicted for woodland possums along a Wet Tropics/Einasleigh Uplands/Gulf Plains gradient and into the south-west of Cape York Peninsula. Suitable climate and habitat exists for the rock ringtail possum south-east of its present known range and for the endangered mahogany glider south of Cairns, about 90 km north of its presently known range. For rainforest species, the green ringtail possum needs confirming north of the Daintree River. Potentially suitable climate and habitat exists for the long-tailed pygmy-possum on the summit zone of the McIlwraith Range. An assessment of conservation status identifies the need to review this for several species. The status of the yellow-bellied glider within the Wet Tropics may need changing from Vulnerable to Endangered. The isolated Gregory Range population of the greater glider may require classifying as either Rare or Vulnerable. The four upland rainforest possums endemic to the Wet Tropics, the lemuroid ringtail possum, Herbert River ringtail possum, Daintree River ringtail possum and the green ringtail possum are threatened by global warming which will progressively worsen their status from Rare. The present status of Common for most woodland species could be optimistic because two, the common brushtail possum and common ringtail possum, appear to have suffered significant population declines. The rock ringtail is vulnerable to local extinctions of population isolates, and little is known about the population viability of the sugar, squirrel and feathertail gliders.

25 citations

Journal ArticleDOI
TL;DR: In this article, a generalized linear model and Bayesian information criteria were used to develop a predictive model based on the abundance of the grey-headed robin (GHR) and the data of climatic environmental variables.
Abstract: Climate is predicted to change rapidly in the current century, which may lead to shifts of species’ ranges, reduced populations and extinctions. Predicting the responses of species abundance to climate change can provide valuable information to quantify climate change impacts and inform their management and conservation, but most studies have been limited to changes in habitat area due to a lack of abundance data. Here, we use generalized linear model and Bayesian information criteria to develop a predictive model based on the abundance of the grey-headed robin (GHR) and the data of climatic environmental variables. The model is validated by leave-one-out cross-validation and equivalence tests. The responses of GHR abundance, population size and habitat area by elevation are predicted under the current climate and 15 climate change scenarios. The model predicts that when temperature increases, abundance of GHR displays a positive response at high elevation, but a negative response at low elevation. High precipitation at the higher elevations is a limiting factor to GHR and any reduction in precipitation at high elevation creates a more suitable environment, leading to an increase in abundance of GHR, whereas changes in precipitation have little impact at low elevation. The loss of habitat is much more than would otherwise be assumed in response to climate change. Temperature increase is the predominant factor leading to habitat loss, whereas changes in precipitation play a secondary role. When climate changes, the species not only loses part of its habitat but also suffers a loss in its population size in the remaining habitat. Population size declines more than the habitat area under all considered climate change scenarios, which implies that the species might become extinct long before the complete loss of its habitat. This study suggests that some species might experience much more severe impacts from climate change than predicted from models of habitat area alone. Management policies based on predictions of habitat area decline using occurrence data need to be re-evaluated and alternative measures need to be developed to conserve species in the face of rapid climate change.

25 citations

Journal ArticleDOI
20 Feb 2014-PLOS ONE
TL;DR: Flightless ground beetles are among the most vulnerable taxa to climate change impacts so far investigated in the Wet Tropics World Heritage Area of Australia, and their findings have dramatic implications for all other flightless insect taxa and the future biodiversity of this region.
Abstract: With the impending threat of climate change, greater understanding of patterns of species distributions and richness and the environmental factors driving them are required for effective conservation efforts. Species distribution models enable us to not only estimate geographic extents of species and subsequent patterns of species richness, but also generate hypotheses regarding environmental factors determining these spatial patterns. Projected changes in climate can then be used to predict future patterns of species distributions and richness. We created distribution models for most of the flightless ground beetles (Carabidae) within the Wet Tropics World Heritage Area of Australia, a major component of regionally endemic invertebrates. Forty-three species were modelled and the environmental correlates of these distributions and resultant patterns of species richness were examined. Flightless ground beetles generally inhabit upland areas characterised by stable, cool and wet environmental conditions. These distribution and richness patterns are best explained using the time-stability hypothesis as this group's primary habitat, upland rainforest, is considered to be the most stable regional habitat. Projected changes in distributions indicate that as upward shifts in distributions occur, species currently confined to lower and drier mountain ranges will be more vulnerable to climate change impacts than those restricted to the highest and wettest mountains. Distribution models under projected future climate change suggest that there will be reductions in range size, population size and species richness under all emission scenarios. Eighty-eight per cent of species modelled are predicted to decline in population size by over 80%, for the most severe emission scenario by the year 2080. These results suggest that flightless ground beetles are among the most vulnerable taxa to climate change impacts so far investigated in the Wet Tropics World Heritage Area. These findings have dramatic implications for all other flightless insect taxa and the future biodiversity of this region.

20 citations

Journal ArticleDOI
TL;DR: In this paper, near-infrared spectroscopy (NIRS) was used to explore leaf-litter chemical quality and the controls on decomposition in the tropical rainforest region of north Queensland Australia.
Abstract: Plant-litter chemical quality is an important driver of many ecosystem processes, however, what actually constitutes high- or low-quality litter (chemical potential for fast and slow decomposition, respectively) is often interpreted by the indices available. Here, near-infrared spectroscopy (NIRS) was used to explore leaf-litter chemical quality and the controls on decomposition in the tropical rainforest region of north Queensland Australia. Leaf-litter samples from litterfall collections and litterbag studies were used. NIRS was used to calibrate the chemical compositions of the material (N, P, C, Mg, Ca, acid detergent fiber, acid detergent lignin, α-cellulose, and total phenolics) from a smaller sample set covering the spectral range in the full set of samples. Calibrations were compared for both separate (local) and combined models, for litterbags, and litterfall. Coefficients of determination (r2) in the local models ranged from 0.88 (litterbag Mg) to 0.99 (litterfall N), with residual prediction deviation ratios > 3 for all constituents except Mg (≈ 2.5). Mass loss in the litterbags was strongly related to the NIR spectra, with model r2's of 0.75 (in situ leaves) and 0.76 (common control leaf). In situ decomposability was determined from modeling the initial NIR spectra prior to decomposition with litterbag exponential-decay rates (model r2 of 0.81, n = 85 initial samples). A best subset model including litter-quality, climate, and soil variables predicted decay better than the NIR decomposability model (r2 = 0.87). For litter quality alone the NIR model predicted decay rate better than all of the best predictive litter–chemical quality indices. The decomposability model was used to predict in situ decomposability in the litterfall samples. The chemical variables explaining NIR decomposability for litterfall were initial P, C, and phenolics (linear model r2 = 0.80, n = 2471). NIRS is a holistic technique that is just as, if not more accurate, than litter–chemical quality indices, when predicting decomposition and decomposability, shown here in a regional field study.

19 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 Article
Fumio Tajima1
30 Oct 1989-Genomics
TL;DR: It is suggested that the natural selection against large insertion/deletion is so weak that a large amount of variation is maintained in a population.

11,521 citations

01 Jun 2012
TL;DR: SPAdes as mentioned in this paper is a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler and on popular assemblers Velvet and SoapDeNovo (for multicell data).
Abstract: The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online ( http://bioinf.spbau.ru/spades ). It is distributed as open source software.

10,124 citations