Novel methods improve prediction of species' distributions from occurrence data

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.

Crescent and star shapes of members of the Chlamydiales order: impact of fixative methods.

Members of the Chlamydiales order all share a biphasic lifecycle alternating between small infectious particles, the elementary bodies (EBs) and larger intracellular forms able to replicate, the reticulate bodies. Whereas the classical Chlamydia usually harbours round-shaped EBs, some members of the Chlamydia-related families display crescent and star-shaped morphologies by electron microscopy. To determine the impact of fixative methods on the shape of the bacterial cells, different buffer and fixative combinations were tested on purified EBs of Criblamydia sequanensis, Estrella lausannensis, Parachlamydia acanthamoebae, and Waddlia chondrophila. A linear discriminant analysis was performed on particle metrics extracted from electron microscopy images to recognize crescent, round, star and intermediary forms. Depending on the buffer and fixatives used, a mixture of alternative shapes were observed in varying proportions with stars and crescents being more frequent in C. sequanensis and P. acanthamoebae, respectively. No tested buffer and chemical fixative preserved ideally the round shape of a majority of bacteria and other methods such as deep-freezing and cryofixation should be applied. Although crescent and star shapes could represent a fixation artifact, they certainly point towards a diverse composition and organization of membrane proteins or intracellular structures rather than being a distinct developmental stage.

Bacterial contamination of platelet concentrates: pathogen detection and inactivation methods

Whereas the reduction of transfusion related viral transmission has been a priority during the last decade, bacterial infection transmitted by transfusion still remains associated to a high morbidity and mortality, and constitutes the most frequent infectious risk of transfusion. This problem especially concerns platelet concentrates because of their favorable bacterial growth conditions. This review gives an overview of platelet transfusion-related bacterial contamination as well as on the different strategies to reduce this problem by using either bacterial detection or inactivation methods.

Effect of collection and preprocessing methods on neutrophil elastase plasma concentrations.

OBJECTIVES: Elevated plasma levels of the elastase alpha 1-proteinase inhibitor complex (E-alpha 1 PI) have been proposed as a marker of bacterial infection and neutrophil activation. Liberation of elastase from neutrophils after collection of blood may cause falsely elevated results. Collection methods have not been validated for critically ill neonates and children. We evaluated the influence of preanalytical methods on E-alpha 1 PI results including the recommended collection into EDTA tubes. DESIGN AND METHODS: First, we compared varying acceleration speeds and centrifugation times. Centrifugation at 1550 g for 3 min resulted in reliable preparation of leukocyte free plasma. Second, we evaluated all collection tubes under consideration for absorption of E-alpha 1 PI. Finally, 12 sets of samples from healthy adults and 42 sets obtained from critically ill neonates and children were distributed into the various sampling tubes. Samples were centrifuged within 15 min of collection and analyzed with a new turbidimetric assay adapted to routine laboratory analyzers. RESULTS: One of the two tubes containing a plasma-cell separation gel absorbed 22.1% of the E-alpha 1 PI content. In the remaining tubes without absorption of E-alpha 1 PI no differences were observed for samples from healthy adult patients. However, in samples from critically ill neonates or children, significantly higher results were obtained for plain Li-heparin tubes (mean = 183 micrograms/L), EDTA tubes (mean = 93 micrograms/L), and citrate tubes (mean = 88.5 micrograms/L) than for the Li-hep tube with cell-plasma separation gel and no absorption of E-alpha 1 PI (mean = 62.4 micrograms/L, p < 0.01). CONCLUSION: Contrary to healthy adults, E-alpha 1 PI results in plasma samples from critically ill neonates and children depend on the type of collection tube.

Phylogenetic relatedness and proboscis length contribute to structuring bumblebee communities in the extremes of abiotic and biotic gradients

Aim To improve our understanding of how biological communities assemble, we investigated changes in bumblebee communities in space along an elevation gradient. We assessed how much deterministic abiotic and biotic factors shape community assembly. We focused on proboscis length (influencing the species' dietary regime) and phylogenetic relatedness to investigate if competition and environmental filtering occur in more and less productive climates, respectively. Location Western Swiss Alps. Methods We recorded bumblebee species in 149 plots along a 1800-m wide elevation gradient. We contrasted two major clades of bumblebees, a short-tongued and a long-tongued clade. We calculated the phylogenetic and proboscis-length diversity of the bumblebee communities and compared these observed data with a random distribution to detect clustering likely to be caused by environmental filtering or overdispersion likely to be caused by competition. We compared the prevalence of clustered and overdispersed communities along the gradients of plant species richness (biotic) and temperature (abiotic). Results Under colder conditions, where plant species richness is lower and floral resources are scarcer, the clade with shorter proboscides prevails over the clade with longer proboscides, and communities are functionally and phylogenetic clustered. Under warmer conditions, we found phylogenetic but not functional overdispersion in communities. Main conclusions We show for the first time a strong correlation between phylogenetic relatedness, proboscis length and species distribution along temperature and plant richness gradients shaping bumblebee communities. The low temperatures and low levels of plant species richness limit the dispersal of the species from the long-tongued clade, which have more specialized diets, into high-elevation areas. Competition under warmer conditions may produce communities composed of less closely related species that share distinct ecological preferences. Our empirical results corroborate theoretical expectation as well as experiments on the prevalence of deterministic processes in the most severe and most productive parts of environmental gradients.

Comparison of estimation methods of soil strength in five soils

In agriculture, the soil strength is used to describe the susceptibility to deformation by pressure caused by agricultural machine. The purpose of this study was to compare different methods for estimating the inherent soil strength and to identify their suitability for the evaluation of load support capacity, compaction susceptibility and root growth. The physical, chemical, mineralogical and intrinsic strength properties of seven soil samples, collected from five sampling pits at different locations in Brazil, were measured. Four clay (CS) and three sandy clay loam (SCL) soils were used. The clay soils were collected on a farm in Santo Ângelo, RS (28 º 16 ' 16 '' S; 54 º 13 ' 11 '' W 290 m); A and B horizons at the Universidade Federal de Lavras, Lavras, MG (21 º 13 ' 47 '' S; 44 º 58 ' 6'' W; 918 m) and on the farm Sygenta, in Uberlandia, MG (18 º 58 ' 37 '' S; 48 º 12 ' 05 '' W 866 m). The sandy clay loam soils were collected in Aracruz, ES (19 º 47 ' 10 '' S; 40 º 16 ' 29 '' W 81 m), and on the farm Xavier, Lavras, MG (21 º 13 ' 24 '' S; 45 º 05 ' 00 '' W; 844 m). Soil strength was estimated based on measurements of: (a) a pneumatic consolidometer, (b) manual pocket (non-rotating) penetrometer; and (c) automatic (rotating) penetrometer. The results of soil strength properties were similar by the three methods. The soil structure had a significant influence on soil strength. Results of measurements with both the manual pocket and the electric penetrometer were similar, emphasizing the influence of soil texture. The data showed that, to enhance the reliability of predictions of preconsolidation pressure by penetrometers, it is better to separate the soils into the different classes, rather than analyze them jointly. It can be concluded that the consolidometer method, although expensive, is the best when evaluations of load support capacity and compaction susceptibility of soil samples are desired.

Treatment-Naive Individuals Are the Major Source of Transmitted HIV-1 Drug Resistance in Men Who Have Sex With Men in the Swiss HIV Cohort Study.

Background. Human immunodeficiency virus type 1 (HIV-1) transmitted drug resistance (TDR) can compromise antiretroviral therapy (ART) and thus represents an important public health concern. Typically, sources of TDR remain unknown, but they can be characterized with molecular epidemiologic approaches. We used the highly representative Swiss HIV Cohort Study (SHCS) and linked drug resistance database (SHCS-DRDB) to analyze sources of TDR. Methods. ART-naive men who have sex with men with infection date estimates between 1996 and 2009 were chosen for surveillance of TDR in HIV-1 subtype B (N = 1674), as the SHCS-DRDB contains pre-ART genotypic resistance tests for >69% of this surveillance population. A phylogeny was inferred using pol sequences from surveillance patients and all subtype B sequences from the SHCS-DRDB (6934 additional patients). Potential sources of TDR were identified based on phylogenetic clustering, shared resistance mutations, genetic distance, and estimated infection dates. Results. One hundred forty of 1674 (8.4%) surveillance patients carried virus with TDR; 86 of 140 (61.4%) were assigned to clusters. Potential sources of TDR were found for 50 of 86 (58.1%) of these patients. ART-naive patients constitute 56 of 66 (84.8%) potential sources and were significantly overrepresented among sources (odds ratio, 6.43 [95% confidence interval, 3.22-12.82]; P < .001). Particularly large transmission clusters were observed for the L90M mutation, and the spread of L90M continued even after the near cessation of antiretroviral use selecting for that mutation. Three clusters showed evidence of reversion of K103N or T215Y/F. Conclusions. Many individuals harboring viral TDR belonged to transmission clusters with other Swiss patients, indicating substantial domestic transmission of TDR in Switzerland. Most TDR in clusters could be linked to sources, indicating good surveillance of TDR in the SHCS-DRDB. Most TDR sources were ART naive. This, and the presence of long TDR transmission chains, suggests that resistance mutations are frequently transmitted among untreated individuals, highlighting the importance of early diagnosis and treatment.

Root system distribution of sugar cane as related to nitrogen fertilization, evaluated by two methods: monolith and probes

Few studies on sugar cane have evaluated the root system of the crop, in spite of its importance. This is mainly due to the difficulty of evaluation and high variability of results. The objective of this study was to develop an evaluation method of the cane root system by means of probes so as to evaluate the mass, distribution and metabolically active roots related to N fertilization at planting. For this purpose, an experiment was conducted in an Arenic Kandiustults with medium texture in Jaboticabal/SP, in a randomized block design with four replications and four treatments: control (without N) and 40, 80 and 120 kg ha-1 of N applied in the form of urea in the planting furrow of the cane variety SP81 3250. One week before harvest, a urea-15N solution was applied at the cane stalk base to detect active metabolism in the root system. Trenches of 1.5 m length and 0.6 m depth were opened between two sugar cane rows for root sampling by two methods: monoliths (0.3, 0.2 and 0.15 m wide, deep and long respectively) taken from the trench wall and by probe (internal diameter 0.055 m). For each method, 15 samples per plot were collected. The roots were separated from the soil in a sieve (2 mm mesh), oven-dried (at 65 ºC) and the dry matter was measured. Root sampling by probes resulted in root mass that did not differ from the evaluation in monoliths, indicating that this evaluation method may be used for sugar cane root mass, although neither the root distribution in the soil profile nor the rhizome mass were efficiently evaluated, due to the small sample volume. Nitrogen fertilization at planting did not result in a greater root accumulation in the sugar cane plant, but caused changes in the distribution of the root system in the soil. The absence of N fertilization led to a better root distribution in the soil profile, with 50, 34 and 16 % in the 0-0.2, 0.2-0.4 and 0.4-0.6 m layers, respectively; in the fertilized treatments the roots were concentrated in the surface layer, with on average 70, 17 and 13 % for the same layers. The metabolically active roots were concentrated in the center of the cane stool, amounting to 40 % of the total root mass, regardless of N fertilization (application of 120 kg ha-1 N or without N).

Integration of ground-penetrating radar and microgravimetric methods to map shallow caves

Ground-penetrating radar (GPR) and microgravimetric surveys have been conducted in the southern Jura mountains of western Switzerland in order to map subsurface karstic features. The study site, La Grande Rolaz cave, is an extensive system in which many portions have been mapped. By using small station spacing and careful processing for the geophysical data, and by modeling these data with topographic information from within the cave, accurate interpretations have been achieved. The constraints on the interpreted geologic models are better when combining the geophysical methods than when using only one of the methods, despite the general limitations of two-dimensional (2D) profiling. For example, microgravimetry can complement GPR methods for accurately delineating a shallow cave section approximately 10 X 10 mt in size. Conversely, GPR methods can be complementary in determining cavity depths and in verifying the presence of off-line features and numerous areas of small cavities and fractures, which may be difficult to resolve in microgravimetric data.

BIO-INSPIRED COMPUTATIONAL TECHNIQUES APPLIED TO THE CLUSTERING AND VISUALIZATION OF SPATIO-TEMPORAL GEOSPATIAL DATA

The coverage and volume of geo-referenced datasets are extensive and incessantly¦growing. The systematic capture of geo-referenced information generates large volumes¦of spatio-temporal data to be analyzed. Clustering and visualization play a key¦role in the exploratory data analysis and the extraction of knowledge embedded in¦these data. However, new challenges in visualization and clustering are posed when¦dealing with the special characteristics of this data. For instance, its complex structures,¦large quantity of samples, variables involved in a temporal context, high dimensionality¦and large variability in cluster shapes.¦The central aim of my thesis is to propose new algorithms and methodologies for¦clustering and visualization, in order to assist the knowledge extraction from spatiotemporal¦geo-referenced data, thus improving making decision processes.¦I present two original algorithms, one for clustering: the Fuzzy Growing Hierarchical¦Self-Organizing Networks (FGHSON), and the second for exploratory visual data analysis:¦the Tree-structured Self-organizing Maps Component Planes. In addition, I present¦methodologies that combined with FGHSON and the Tree-structured SOM Component¦Planes allow the integration of space and time seamlessly and simultaneously in¦order to extract knowledge embedded in a temporal context.¦The originality of the FGHSON lies in its capability to reflect the underlying structure¦of a dataset in a hierarchical fuzzy way. A hierarchical fuzzy representation of¦clusters is crucial when data include complex structures with large variability of cluster¦shapes, variances, densities and number of clusters. The most important characteristics¦of the FGHSON include: (1) It does not require an a-priori setup of the number¦of clusters. (2) The algorithm executes several self-organizing processes in parallel.¦Hence, when dealing with large datasets the processes can be distributed reducing the¦computational cost. (3) Only three parameters are necessary to set up the algorithm.¦In the case of the Tree-structured SOM Component Planes, the novelty of this algorithm¦lies in its ability to create a structure that allows the visual exploratory data analysis¦of large high-dimensional datasets. This algorithm creates a hierarchical structure¦of Self-Organizing Map Component Planes, arranging similar variables' projections in¦the same branches of the tree. Hence, similarities on variables' behavior can be easily¦detected (e.g. local correlations, maximal and minimal values and outliers).¦Both FGHSON and the Tree-structured SOM Component Planes were applied in¦several agroecological problems proving to be very efficient in the exploratory analysis¦and clustering of spatio-temporal datasets.¦In this thesis I also tested three soft competitive learning algorithms. Two of them¦well-known non supervised soft competitive algorithms, namely the Self-Organizing¦Maps (SOMs) and the Growing Hierarchical Self-Organizing Maps (GHSOMs); and the¦third was our original contribution, the FGHSON. Although the algorithms presented¦here have been used in several areas, to my knowledge there is not any work applying¦and comparing the performance of those techniques when dealing with spatiotemporal¦geospatial data, as it is presented in this thesis.¦I propose original methodologies to explore spatio-temporal geo-referenced datasets¦through time. Our approach uses time windows to capture temporal similarities and¦variations by using the FGHSON clustering algorithm. The developed methodologies¦are used in two case studies. In the first, the objective was to find similar agroecozones¦through time and in the second one it was to find similar environmental patterns¦shifted in time.¦Several results presented in this thesis have led to new contributions to agroecological¦knowledge, for instance, in sugar cane, and blackberry production.¦Finally, in the framework of this thesis we developed several software tools: (1)¦a Matlab toolbox that implements the FGHSON algorithm, and (2) a program called¦BIS (Bio-inspired Identification of Similar agroecozones) an interactive graphical user¦interface tool which integrates the FGHSON algorithm with Google Earth in order to¦show zones with similar agroecological characteristics.

Local and global error models to improve uncertainty quantification

In groundwater applications, Monte Carlo methods are employed to model the uncertainty on geological parameters. However, their brute-force application becomes computationally prohibitive for highly detailed geological descriptions, complex physical processes, and a large number of realizations. The Distance Kernel Method (DKM) overcomes this issue by clustering the realizations in a multidimensional space based on the flow responses obtained by means of an approximate (computationally cheaper) model; then, the uncertainty is estimated from the exact responses that are computed only for one representative realization per cluster (the medoid). Usually, DKM is employed to decrease the size of the sample of realizations that are considered to estimate the uncertainty. We propose to use the information from the approximate responses for uncertainty quantification. The subset of exact solutions provided by DKM is then employed to construct an error model and correct the potential bias of the approximate model. Two error models are devised that both employ the difference between approximate and exact medoid solutions, but differ in the way medoid errors are interpolated to correct the whole set of realizations. The Local Error Model rests upon the clustering defined by DKM and can be seen as a natural way to account for intra-cluster variability; the Global Error Model employs a linear interpolation of all medoid errors regardless of the cluster to which the single realization belongs. These error models are evaluated for an idealized pollution problem in which the uncertainty of the breakthrough curve needs to be estimated. For this numerical test case, we demonstrate that the error models improve the uncertainty quantification provided by the DKM algorithm and are effective in correcting the bias of the estimate computed solely from the MsFV results. The framework presented here is not specific to the methods considered and can be applied to other combinations of approximate models and techniques to select a subset of realizations

Selection methods regulate evolution of cooperation in digital evolution.

A key, yet often neglected, component of digital evolution and evolutionary models is the 'selection method' which assigns fitness (number of offspring) to individuals based on their performance scores (efficiency in performing tasks). Here, we study with formal analysis and numerical experiments the evolution of cooperation under the five most common selection methods (proportionate, rank, truncation-proportionate, truncation-uniform and tournament). We consider related individuals engaging in a Prisoner's Dilemma game where individuals can either cooperate or defect. A cooperator pays a cost, whereas its partner receives a benefit, which affect their performance scores. These performance scores are translated into fitness by one of the five selection methods. We show that cooperation is positively associated with the relatedness between individuals under all selection methods. By contrast, the change in the performance benefit of cooperation affects the populations' average level of cooperation only under the proportionate methods. We also demonstrate that the truncation and tournament methods may introduce negative frequency-dependence and lead to the evolution of polymorphic populations. Using the example of the evolution of cooperation, we show that the choice of selection method, though it is often marginalized, can considerably affect the evolutionary dynamics.

Cross validation of experts versus registration methods for target localization in deep brain stimulation.

In the last five years, Deep Brain Stimulation (DBS) has become the most popular and effective surgical technique for the treatent of Parkinson's disease (PD). The Subthalamic Nucleus (STN) is the usual target involved when applying DBS. Unfortunately, the STN is in general not visible in common medical imaging modalities. Therefore, atlas-based segmentation is commonly considered to locate it in the images. In this paper, we propose a scheme that allows both, to perform a comparison between different registration algorithms and to evaluate their ability to locate the STN automatically. Using this scheme we can evaluate the expert variability against the error of the algorithms and we demonstrate that automatic STN location is possible and as accurate as the methods currently used.