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

The Theory of Island Biogeography

https://www.cs.princeton.edu/~schapire/papers/ecolmod.pdf

Maximum entropy modeling of species geographic distributions

Statistical method for testing the neutral mutation hypothesis by DNA polymorphism.

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.

/pdf/novel-methods-improve-prediction-of-species-distributions-3cmioqeu6v.pdf

Novel methods improve prediction of species' distributions from occurrence data

Dengue is a systemic viral infection transmitted between humans by Aedes mosquitoes. For some patients, dengue is a life-threatening illness. There are currently no licensed vaccines or specific therapeutics, and substantial vector control efforts have not stopped its rapid emergence and global spread. The contemporary worldwide distribution of the risk of dengue virus infection and its public health burden are poorly known. Here we undertake an exhaustive assembly of known records of dengue occurrence worldwide, and use a formal modelling framework to map the global distribution of dengue risk. We then pair the resulting risk map with detailed longitudinal information from dengue cohort studies and population surfaces to infer the public health burden of dengue in 2010. We predict dengue to be ubiquitous throughout the tropics, with local spatial variations in risk influenced strongly by rainfall, temperature and the degree of urbanization. Using cartographic approaches, we estimate there to be 390 million (95% credible interval 284-528) dengue infections per year, of which 96 million (67-136) manifest apparently (any level of disease severity). This infection total is more than three times the dengue burden estimate of the World Health Organization. Stratification of our estimates by country allows comparison with national dengue reporting, after taking into account the probability of an apparent infection being formally reported. The most notable differences are discussed. These new risk maps and infection estimates provide novel insights into the global, regional and national public health burden imposed by dengue. We anticipate that they will provide a starting point for a wider discussion about the global impact of this disease and will help to guide improvements in disease control strategies using vaccine, drug and vector control methods, and in their economic evaluation.

/pdf/the-global-distribution-and-burden-of-dengue-4d1crnic4u.pdf

The global distribution and burden of dengue

Aim Conservation strategies need predictions that capture spatial community composition and structure. Currently, the methods used to generate these predictive maps generally focus on deterministic processes and omit stochasticity and other uncertainty in model outputs. Here we present a novel approach to model the means and variance of assemblage properties. Location The western Swiss Alps. Methods We propose a new approach to processing probabilistic predictions derived from stacked species distribution models (S-SDMs) in order to predict and assess the uncertainty in predictions of community properties. We compare the utility of our novel approach with that of a traditional threshold-based approach. We used data sampled in 2009 and 2010 from 192 sites in total for mountain butterfly communities spanning a large elevational gradient as a case study and evaluated the ability of our approach to model the species richness and phylogenetic diversity of communities within an ensemble forecasting

ARTICLE A probabilistic approach to niche-based community models for spatial forecasts of assemblage properties and their

/pdf/a-novel-integrated-assessment-framework-for-exploring-4o8dvhk9pr.pdf

A novel integrated assessment framework for exploring possible futures for Australia: the GNOME.3 suite for the Australian National Outlook

The diversity of terrestrial vascular plants plays a key role in maintaining the stability and productivity of ecosystems. Monitoring species compositional diversity across large spatial scales is challenging and time consuming. Airborne hyperspectral imaging has shown promise for mea-suring plant diversity remotely, but to operationalise these eﬀorts over large regions we need to advance satellite-based alternatives. The advanced spectral and spatial speciﬁcation of the recently launched DESIS (the DLR Earth Sensing Imaging Spectrometer) instrument provides a unique opportunity to test the potential for monitoring plant species diversity with spaceborne hyperspectral data. This study provides a quantitative assessment on the ability of DESIS hyperspectral data for predicting plant species richness in two diﬀerent habitat types in southeast Australia. Spectral features were ﬁrst extracted from the DESIS spectra, then regressed against on-ground estimates of plant species richness, with a two-fold cross validation scheme to assess the predictive performance. We tested and compared the eﬀectiveness of Principal Component Analysis (PCA), Canonical Correlation Analysis (CCA), and Partial Least Squares analysis (PLS) for feature extraction, and Kernel Ridge Regression (KRR), Gaussian Process Regression (GPR), and Random Forest Regression (RFR) for species richness prediction. The best prediction results were r = 0 . 76 and RMSE = 5 . 89 for the Southern Tablelands region, and r = 0 . 68 and RMSE = 5 . 95 for the Snowy Mountains region. Relative importance analysis for the DESIS spectral bands showed

Plant species richness prediction from DESIS hyperspectral data: A comparison study on feature extraction procedures and regression models

Estimating habitat condition using time series remote sensing and ecological survey data: preliminary investigations

Abstract Objectives Pelvic actinomycotic abscess is uncommon and its presentation as a post-cesarean complication may be confused with hemorrhagic mass. It is still a disease that poses a significant diagnostic challenge. Management and prognosis are not well known for this type of infection. Case presentation A 36-year-old woman was admitted to the hospital six days after the cesarean section with abdominal pain and dysuria. The second operation was diagnosed as pelvic abscess, debridement and drainage about 250 mL abscess. Bacterial culture of abscess confirmed as Actinomyces odontolyticus infection. Intravenous penicillin was given immediately, amoxicillin was taken orally for three months after discharge, and no recurrence was found after follow-up for ten months. Conclusions Pelvic A. odontolyticus abscess may be confirmed through correct bacterial culture and cured by a short-term course of Amoxicillin. With prompt recognition and treatment, favorable outcomes of pelvic Actinomycotic abscess in the perinatal period could be achieved.

Simon Ferrier

Papers

ARTICLE A probabilistic approach to niche-based community models for spatial forecasts of assemblage properties and their

A novel integrated assessment framework for exploring possible futures for Australia: the GNOME.3 suite for the Australian National Outlook

Plant species richness prediction from DESIS hyperspectral data: A comparison study on feature extraction procedures and regression models

Estimating habitat condition using time series remote sensing and ecological survey data: preliminary investigations

Pelvic abscess associated with Actinomyces species ‒ a rare post-cesarean complication