Spatial and temporal distributions of epiphytic diatoms growing on Thalassia testudinum Banks ex König: relationships to water quality

The spatial and temporal distributions of the epiphytic diatom flora on Thalassia testudinum was described within the Florida Bay estuary and at one Atlantic site east of the Florida Keys over a 1-year period. Species of the genus Mastogloia dominated the epiphytic diatom flora (82 out of 332 total species). Nonmetric Multidimensional Scaling (NMDS) and Analysis of Similarity (ANOSIM) revealed four distinct spatial assemblages and two temporal assemblages. Eastern and western Florida Bay assemblages were identified within the estuary. The eastern diatom assemblage was characterized by high relative abundances of Brachysira aponina and Nitzschia liebetruthii, while the western assemblage was characterized by the abundance of Reimerothrix floridensis, particularly during summer. Two diverse and distinct marine assemblages, one located in the Gulf of Mexico along the western edge of Florida Bay and the other behind the Florida reef tract in the Atlantic Ocean, were also identified. Analysis of the spatial distribution of diatoms and water quality characteristics within Florida Bay suggest that these assemblages may be structured by salinity and nutrient availability, particularly P. The Gulf of Mexico and the western Florida Bay assemblages were associated with higher water column salinities and TP concentrations and lower DIN concentrations and TN:TP ratios relative to the eastern Florida Bay assemblage. The temporal variation in diatom assemblages was associated with water temperature, though temporal indicator species were few relative to the number of spatial indicators.

Influência dos fatores abióticos sobre a variação espaço-temporal de paralonchurus brasiliensis (Steindachner, 1875) (pisces, sciaenidae) componente da fauna acompanhante da pesca de camarões no litoral Norte de São Paulo

Knowledge of the environmental factors influence on the spatial-temporal variation of fishes is important to fisheries management and conservation. Thus, the aim of this work was to analyze the influence of the abiotical factors on the spatial-temporal distribution of Paralonchurus brasiliensis (Pisces, Sciaenidae) caught by-catch with the shrimp fishing of Ubatuba and Caraguatatuba regions, north coast of São Paulo State. The fishes were captured every month from January to December 2002. Samples were collected by otter trawl at 5, 10, 15, 20, 25, 30 and 35m depths. The temperatures (surface and bottom), salinities (surface and bottom), sediment features and organic matters were verified for each depth. During all period of the study 12.642 specimens of P. brasiliensis were captured at Ubatuba and 17.166 at Caraguatatuba, which totalized the biomass of 267 for the first and 339kg for the other region. The females outnumbered males in fish population. The greatest values of biomass and number of individuals were registered at the summer and autumn seasons, while the lowest values were observed at the winter and spring seasons. The greatest abundances were found from 15 to 25m depth. In this study, it was verified that P. brasiliensis is a coastal waters associate species. The spatialtemporal distribution of P. brasiliensis is affected by intrusion of SACW and depth for the coastal region and by depth and sediment in sheltered areas such as Caraguatatuba

Variação temporal da Comunidade de macroinvertebrados bentônicos em um riacho intermitente do semiárido brasileiro

In Brazilian semiarid region, the majority of water bodies are temporary and the biodiversity in these ecosystems is poorly known. The goal of this study was to describe the temporal variation of benthic macroinvertebrates in an intermittent stream in the Brazilian semiarid region. From March to July of 2009, surveys of benthic macroinvertebrates and water physiochemical parameters were done in a first order stream located at Piranhas-Açu River basin. 25 macroinvertebrates families were found, 21 belonging to Insecta class. The chironomids were the most abundant group during all study period and were represented by 19 genus. The largest densities and taxonomic richness were seen in the drying phase of the stream while the smallest values were found in the period with the heaviest rainfalls ( wet phase ). Only the families Chironomidae and Ceratopogonidae were found during all study period, suggesting that these groups have better adaptations to support floods and droughts. Furthermore, these two groups seemed to be pioneering in this stream. Among the chironomids, Paratendipes dominated the period of floods while Tanytarsus were more abundant in the drying phase . This study showed that hydrological fluctuation is the main force influencing the macroinvertebrate community in this stream, therefore, efforts seeking the conservation and management of Brazilian semiarid water bodies should consider this high natural variability in flow regime

Diurnal temporal patterns of the diversity and the abundance of reef fishes in a branching coral patch in New Caledonia

Small-scale spatial and temporal variability in animal abundance is an intrinsic characteristic of marine ecosystems but remains largely unknown for most animals, including coral reef fishes. In this study, we used a remote autonomous unbaited video system and recorded reef fish assemblages during daylight hours, 10 times a day for 34 consecutive days in a branching coral patch of the lagoon of New Caledonia. In total, 50 031 fish observations belonging to 114 taxa, 66 genera and 31 families were recorded in 256 recorded videos. Carnivores and herbivore-detritus feeders dominated the trophic structure. We found significant variations in the composition of fish assemblages between times of day. Taxa richness and fish abundance were greater in the early morning and in the late afternoon than during the day. Fourteen taxa displayed well-defined temporal patterns in abundance with one taxon influenced by time of day, six influenced by tidal state and seven influenced by both time of day and tidal state. None of these 14 taxa were piscivores, 10 were herbivore-detritus feeders, three were carnivores and one was plankton feeder. Our results suggest a diel migration from feeding grounds to shelter areas and highlight the importance of taking into account small-scale temporal variability in animal diversity and abundance when studying connectivity between habitats and monitoring communities.

Influência dos fatores abióticos sobre a variação espaço-temporal de paralonchurus brasiliensis (Steindachner, 1875) (pisces, sciaenidae) componente da fauna acompanhante da pesca de camarões no litoral Norte de São Paulo

Knowledge of the environmental factors influence on the spatial-temporal variation of fishes is important to fisheries management and conservation. Thus, the aim of this work was to analyze the influence of the abiotical factors on the spatial-temporal distribution of Paralonchurus brasiliensis (Pisces, Sciaenidae) caught by-catch with the shrimp fishing of Ubatuba and Caraguatatuba regions, north coast of São Paulo State. The fishes were captured every month from January to December 2002. Samples were collected by otter trawl at 5, 10, 15, 20, 25, 30 and 35m depths. The temperatures (surface and bottom), salinities (surface and bottom), sediment features and organic matters were verified for each depth. During all period of the study 12.642 specimens of P. brasiliensis were captured at Ubatuba and 17.166 at Caraguatatuba, which totalized the biomass of 267 for the first and 339kg for the other region. The females outnumbered males in fish population. The greatest values of biomass and number of individuals were registered at the summer and autumn seasons, while the lowest values were observed at the winter and spring seasons. The greatest abundances were found from 15 to 25m depth. In this study, it was verified that P. brasiliensis is a coastal waters associate species. The spatialtemporal distribution of P. brasiliensis is affected by intrusion of SACW and depth for the coastal region and by depth and sediment in sheltered areas such as Caraguatatuba

Variação temporal da Comunidade de macroinvertebrados bentônicos em um riacho intermitente do semiárido brasileiro

In Brazilian semiarid region, the majority of water bodies are temporary and the biodiversity in these ecosystems is poorly known. The goal of this study was to describe the temporal variation of benthic macroinvertebrates in an intermittent stream in the Brazilian semiarid region. From March to July of 2009, surveys of benthic macroinvertebrates and water physiochemical parameters were done in a first order stream located at Piranhas-Açu River basin. 25 macroinvertebrates families were found, 21 belonging to Insecta class. The chironomids were the most abundant group during all study period and were represented by 19 genus. The largest densities and taxonomic richness were seen in the drying phase of the stream while the smallest values were found in the period with the heaviest rainfalls ( wet phase ). Only the families Chironomidae and Ceratopogonidae were found during all study period, suggesting that these groups have better adaptations to support floods and droughts. Furthermore, these two groups seemed to be pioneering in this stream. Among the chironomids, Paratendipes dominated the period of floods while Tanytarsus were more abundant in the drying phase . This study showed that hydrological fluctuation is the main force influencing the macroinvertebrate community in this stream, therefore, efforts seeking the conservation and management of Brazilian semiarid water bodies should consider this high natural variability in flow regime

Composition and temporal dynamics of a temperate rocky cryptobenthic fish assemblage

Temporal variation in a temperate cryptobenthic fish assemblage at the Arrabida Marine Park (Portugal) was assessed by visual Surveys during 2002 and 2003. A total of 9596 fish from 11 families and 30 species was recorded. There were no changes in structure or density at the assemblage level between years, whereas diversity changed significantly due to a higher number of abundant species in the second year. A similar seasonal trend was found between years, with a significant overall density increase in autumn. This is partially explained by the arrival of new recruits of some of the most abundant species in the assemblage. Assemblage diversity and structure also changed across seasons. A group of species encompassing Gobius xanthocephalus, Tripterygion delaisi, Parablennius pilicornis, Gobius paganellus, Lepadogaster candollii and Lepadogaster spp. were analysed in detail. The temporal patterns of two of the most abundant species, G. xanthocephalus and T delaisi, mimicked the overall temporal patterns of the assemblage. We suggest that the inter-annual stability in density of this subtidal fish assemblage may be similar to what has been reported for the intertidal and that strong post-settlement processes are probably shaping this assemblage.

Prevalencia e incidencia de cáncer en habitantes de Sibaté, y georeferenciación de casos 2010-2014

Introducción: El Cáncer es prevenible en algunos casos, si se evita la exposición a sustancias cancerígenas en el medio ambiente. En Colombia, Cundinamarca es uno de los departamentos con mayores incrementos en la tasa de mortalidad y en el municipio de Sibaté, habitantes han manifestado preocupación por el incremento de la enfermedad. En el campo de la salud ambiental mundial, la georreferenciación aplicada al estudio de fenómenos en salud, ha tenido éxito con resultados válidos. El estudio propuso usar herramientas de información geográfica, para generar análisis de tiempo y espacio que hicieran visible el comportamiento del cáncer en Sibaté y sustentaran hipótesis de influencias ambientales sobre concentraciones de casos. Objetivo: Obtener incidencia y prevalencia de casos de cáncer en habitantes de Sibaté y georreferenciar los casos en un periodo de 5 años, con base en indagación de registros. Metodología: Estudio exploratorio descriptivo de corte transversal,sobre todos los diagnósticos de cáncer entre los años 2010 a 2014, encontrados en los archivos de la Secretaria de Salud municipal. Se incluyeron unicamente quienes tuvieron residencia permanente en el municipio y fueron diagnosticados con cáncer entre los años de 2010 a 2104. Sobre cada caso se obtuvo género, edad, estrato socioeconómico, nivel académico, ocupación y estado civil. Para el análisis de tiempo se usó la fecha de diagnóstico y para el análisis de espacio, la dirección de residencia, tipo de cáncer y coordenada geográfica. Se generaron coordenadas geográficas con un equipo GPS Garmin y se crearon mapas con los puntos de la ubicación de las viviendas de los pacientes. Se proceso la información, con Epi Info 7 Resultados: Se encontraron 107 casos de cáncer registrados en la Secretaria de Salud de Sibaté, 66 mujeres, 41 hombres. Sin división de género, el 30.93% de la población presento cáncer del sistema reproductor, el 18,56% digestivo y el 17,53% tegumentario. Se presentaron 2 grandes casos de agrupaciones espaciales en el territorio estudiado, una en el Barrio Pablo Neruda con 12 (21,05%) casos y en el casco Urbano de Sibaté con 38 (66,67%) casos. Conclusión: Se corroboro que el análisis geográfico con variables espacio temporales y de exposición, puede ser la herramienta para generar hipótesis sobre asociaciones de casos de cáncer con factores ambientales.

Field-oriented assessment of agricultural crops through temporal segmentation of modis VI data.

Monitoring agricultural crops constitutes a vital task for the general understanding of land use spatio-temporal dynamics. This paper presents an approach for the enhancement of current crop monitoring capabilities on a regional scale, in order to allow for the analysis of environmental and socio-economic drivers and impacts of agricultural land use. This work discusses the advantages and current limitations of using 250m VI data from the Moderate Resolution Imaging Spectroradiometer (MODIS) for this purpose, with emphasis in the difficulty of correctly analyzing pixels whose temporal responses are disturbed due to certain sources of interference such as mixed or heterogeneous land cover. It is shown that the influence of noisy or disturbed pixels can be minimized, and a much more consistent and useful result can be attained, if individual agricultural fields are identified and each field's pixels are analyzed in a collective manner. As such, a method is proposed that makes use of image segmentation techniques based on MODIS temporal information in order to identify portions of the study area that agree with actual agricultural field borders. The pixels of each portion or segment are then analyzed individually in order to estimate the reliability of the temporal signal observed and the consequent relevance of any estimation of land use from that data. The proposed method was applied in the state of Mato Grosso, in mid-western Brazil, where extensive ground truth data was available. Experiments were carried out using several supervised classification algorithms as well as different subsets of land cover classes, in order to test the methodology in a comprehensive way. Results show that the proposed method is capable of consistently improving classification results not only in terms of overall accuracy but also qualitatively by allowing a better understanding of the land use patterns detected. It thus provides a practical and straightforward procedure for enhancing crop-mapping capabilities using temporal series of moderate resolution remote sensing data.

Shoot growth dynamics and photosynthetic response to increased nitrogen availability in the alpine willow salix-glauca

Plants subjected to increases in the supply of resource(s) limiting growth may allocate more of those resources to existing leaves, increasing photosynthetic capacity, and/or to production of more leaves, increasing whole-plant photosynthesis. The responses of three populations of the alpine willow, Salix glauca, growing along an alpine topographic sequence representing a gradient in soil moisture and organic matter, and thus potential N supply, to N amendments, were measured over two growing seasons, to elucidate patterns of leaf versus shoot photosynthetic responses. Leaf-(foliar N, photosynthesis rates, photosynthetic N-use efficiency) and shoot-(leaf area per shoot, number of leaves per shoot, stem weight, N resorption efficiency) level measurements were made to examine the spatial and temporal variation in these potential responses to increased N availability. The predominant response of the willows to N fertilization was at the shoot-level, by production of greater leaf area per shoot. Greater leaf area occurred due to production of larger leaves in both years of the experiment and to production of more leaves during the second year of fertilization treatment. Significant leaf-level photosynthetic response occurred only during the first year of treatment, and only in the dry meadow population. Variation in photosynthesis rates was related more to variation in stomatal conductance than to foliar N concentration. Stomatal conductance in turn was significantly related to N fertilization. Differences among the populations in photosynthesis, foliar N, leaf production, and responses to N fertilization indicate N availability may be lowest in the dry meadow population, and highest in the ridge population. This result is contrary to the hypothesis that a gradient of plant available N corresponds with a snowpack/topographic gradient.

Spatial analysis of notified dengue fever infections

This study aimed to investigate the spatial clustering and dynamic dispersion of dengue incidence in Queensland, Australia. We used Moran’s I statistic to assess the spatial autocorrelation of reported dengue cases. Spatial empirical Bayes smoothing estimates were used to display the spatial distribution of dengue in postal areas throughout Queensland. Local indicators of spatial association (LISA) maps and logistic regression models were used to identify spatial clusters and examine the spatio-temporal patterns of the spread of dengue. The results indicate that the spatial distribution of dengue was clustered during each of the three periods of 1993–1996, 1997–2000 and 2001–2004. The high-incidence clusters of dengue were primarily concentrated in the north of Queensland and low-incidence clusters occurred in the south-east of Queensland. The study concludes that the geographical range of notified dengue cases has significantly expanded in Queensland over recent years.

Hierarchical Bayesian models for estimating the extent of plant pest invasions

Plant biosecurity requires statistical tools to interpret field surveillance data in order to manage pest incursions that threaten crop production and trade. Ultimately, management decisions need to be based on the probability that an area is infested or free of a pest. Current informal approaches to delimiting pest extent rely upon expert ecological interpretation of presence / absence data over space and time. Hierarchical Bayesian models provide a cohesive statistical framework that can formally integrate the available information on both pest ecology and data. The overarching method involves constructing an observation model for the surveillance data, conditional on the hidden extent of the pest and uncertain detection sensitivity. The extent of the pest is then modelled as a dynamic invasion process that includes uncertainty in ecological parameters. Modelling approaches to assimilate this information are explored through case studies on spiralling whitefly, Aleurodicus dispersus and red banded mango caterpillar, Deanolis sublimbalis. Markov chain Monte Carlo simulation is used to estimate the probable extent of pests, given the observation and process model conditioned by surveillance data. Statistical methods, based on time-to-event models, are developed to apply hierarchical Bayesian models to early detection programs and to demonstrate area freedom from pests. The value of early detection surveillance programs is demonstrated through an application to interpret surveillance data for exotic plant pests with uncertain spread rates. The model suggests that typical early detection programs provide a moderate reduction in the probability of an area being infested but a dramatic reduction in the expected area of incursions at a given time. Estimates of spiralling whitefly extent are examined at local, district and state-wide scales. The local model estimates the rate of natural spread and the influence of host architecture, host suitability and inspector efficiency. These parameter estimates can support the development of robust surveillance programs. Hierarchical Bayesian models for the human-mediated spread of spiralling whitefly are developed for the colonisation of discrete cells connected by a modified gravity model. By estimating dispersal parameters, the model can be used to predict the extent of the pest over time. An extended model predicts the climate restricted distribution of the pest in Queensland. These novel human-mediated movement models are well suited to demonstrating area freedom at coarse spatio-temporal scales. At finer scales, and in the presence of ecological complexity, exploratory models are developed to investigate the capacity for surveillance information to estimate the extent of red banded mango caterpillar. It is apparent that excessive uncertainty about observation and ecological parameters can impose limits on inference at the scales required for effective management of response programs. The thesis contributes novel statistical approaches to estimating the extent of pests and develops applications to assist decision-making across a range of plant biosecurity surveillance activities. Hierarchical Bayesian modelling is demonstrated as both a useful analytical tool for estimating pest extent and a natural investigative paradigm for developing and focussing biosecurity programs.

Hierarchical Bayesian modelling of early detection surveillance for plant pest invasions

Early detection surveillance programs aim to find invasions of exotic plant pests and diseases before they are too widespread to eradicate. However, the value of these programs can be difficult to justify when no positive detections are made. To demonstrate the value of pest absence information provided by these programs, we use a hierarchical Bayesian framework to model estimates of incursion extent with and without surveillance. A model for the latent invasion process provides the baseline against which surveillance data are assessed. Ecological knowledge and pest management criteria are introduced into the model using informative priors for invasion parameters. Observation models assimilate information from spatio-temporal presence/absence data to accommodate imperfect detection and generate posterior estimates of pest extent. When applied to an early detection program operating in Queensland, Australia, the framework demonstrates that this typical surveillance regime provides a modest reduction in the estimate that a surveyed district is infested. More importantly, the model suggests that early detection surveillance programs can provide a dramatic reduction in the putative area of incursion and therefore offer a substantial benefit to incursion management. By mapping spatial estimates of the point probability of infestation, the model identifies where future surveillance resources can be most effectively deployed.

Using Bayesian methods for the estimation of uncertainty in complex statistical models

The research objectives of this thesis were to contribute to Bayesian statistical methodology by contributing to risk assessment statistical methodology, and to spatial and spatio-temporal methodology, by modelling error structures using complex hierarchical models. Specifically, I hoped to consider two applied areas, and use these applications as a springboard for developing new statistical methods as well as undertaking analyses which might give answers to particular applied questions. Thus, this thesis considers a series of models, firstly in the context of risk assessments for recycled water, and secondly in the context of water usage by crops. The research objective was to model error structures using hierarchical models in two problems, namely risk assessment analyses for wastewater, and secondly, in a four dimensional dataset, assessing differences between cropping systems over time and over three spatial dimensions. The aim was to use the simplicity and insight afforded by Bayesian networks to develop appropriate models for risk scenarios, and again to use Bayesian hierarchical models to explore the necessarily complex modelling of four dimensional agricultural data. The specific objectives of the research were to develop a method for the calculation of credible intervals for the point estimates of Bayesian networks; to develop a model structure to incorporate all the experimental uncertainty associated with various constants thereby allowing the calculation of more credible credible intervals for a risk assessment; to model a single day’s data from the agricultural dataset which satisfactorily captured the complexities of the data; to build a model for several days’ data, in order to consider how the full data might be modelled; and finally to build a model for the full four dimensional dataset and to consider the timevarying nature of the contrast of interest, having satisfactorily accounted for possible spatial and temporal autocorrelations. This work forms five papers, two of which have been published, with two submitted, and the final paper still in draft. The first two objectives were met by recasting the risk assessments as directed, acyclic graphs (DAGs). In the first case, we elicited uncertainty for the conditional probabilities needed by the Bayesian net, incorporated these into a corresponding DAG, and used Markov chain Monte Carlo (MCMC) to find credible intervals, for all the scenarios and outcomes of interest. In the second case, we incorporated the experimental data underlying the risk assessment constants into the DAG, and also treated some of that data as needing to be modelled as an ‘errors-invariables’ problem [Fuller, 1987]. This illustrated a simple method for the incorporation of experimental error into risk assessments. In considering one day of the three-dimensional agricultural data, it became clear that geostatistical models or conditional autoregressive (CAR) models over the three dimensions were not the best way to approach the data. Instead CAR models are used with neighbours only in the same depth layer. This gave flexibility to the model, allowing both the spatially structured and non-structured variances to differ at all depths. We call this model the CAR layered model. Given the experimental design, the fixed part of the model could have been modelled as a set of means by treatment and by depth, but doing so allows little insight into how the treatment effects vary with depth. Hence, a number of essentially non-parametric approaches were taken to see the effects of depth on treatment, with the model of choice incorporating an errors-in-variables approach for depth in addition to a non-parametric smooth. The statistical contribution here was the introduction of the CAR layered model, the applied contribution the analysis of moisture over depth and estimation of the contrast of interest together with its credible intervals. These models were fitted using WinBUGS [Lunn et al., 2000]. The work in the fifth paper deals with the fact that with large datasets, the use of WinBUGS becomes more problematic because of its highly correlated term by term updating. In this work, we introduce a Gibbs sampler with block updating for the CAR layered model. The Gibbs sampler was implemented by Chris Strickland using pyMCMC [Strickland, 2010]. This framework is then used to consider five days data, and we show that moisture in the soil for all the various treatments reaches levels particular to each treatment at a depth of 200 cm and thereafter stays constant, albeit with increasing variances with depth. In an analysis across three spatial dimensions and across time, there are many interactions of time and the spatial dimensions to be considered. Hence, we chose to use a daily model and to repeat the analysis at all time points, effectively creating an interaction model of time by the daily model. Such an approach allows great flexibility. However, this approach does not allow insight into the way in which the parameter of interest varies over time. Hence, a two-stage approach was also used, with estimates from the first-stage being analysed as a set of time series. We see this spatio-temporal interaction model as being a useful approach to data measured across three spatial dimensions and time, since it does not assume additivity of the random spatial or temporal effects.