29 resultados para Spatio-temporal dynamics
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Ecosystems consist of complex dynamic interactions among species and the environment, the understanding of which has implications for predicting the environmental response to changes in climate and biodiversity. However, with the recent adoption of more explorative tools, like Bayesian networks, in predictive ecology, few assumptions can be made about the data and complex, spatially varying interactions can be recovered from collected field data. In this study, we compare Bayesian network modelling approaches accounting for latent effects to reveal species dynamics for 7 geographically and temporally varied areas within the North Sea. We also apply structure learning techniques to identify functional relationships such as prey–predator between trophic groups of species that vary across space and time. We examine if the use of a general hidden variable can reflect overall changes in the trophic dynamics of each spatial system and whether the inclusion of a specific hidden variable can model unmeasured group of species. The general hidden variable appears to capture changes in the variance of different groups of species biomass. Models that include both general and specific hidden variables resulted in identifying similarity with the underlying food web dynamics and modelling spatial unmeasured effect. We predict the biomass of the trophic groups and find that predictive accuracy varies with the models' features and across the different spatial areas thus proposing a model that allows for spatial autocorrelation and two hidden variables. Our proposed model was able to produce novel insights on this ecosystem's dynamics and ecological interactions mainly because we account for the heterogeneous nature of the driving factors within each area and their changes over time. Our findings demonstrate that accounting for additional sources of variation, by combining structure learning from data and experts' knowledge in the model architecture, has the potential for gaining deeper insights into the structure and stability of ecosystems. Finally, we were able to discover meaningful functional networks that were spatially and temporally differentiated with the particular mechanisms varying from trophic associations through interactions with climate and commercial fisheries.
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Investigating the variability of Agulhas leakage, the volume transport of water from the Indian Ocean to the South Atlantic Ocean, is highly relevant due to its potential contribution to the Atlantic Meridional Overturning Circulation as well as the global circulation of heat and salt and hence global climate. Quantifying Agulhas leakage is challenging due to the non-linear nature of this process; current observations are insufficient to estimate its variability and ocean models all have biases in this region, even at high resolution . An Eulerian threshold integration method is developed to examine the mechanisms of Agulhas leakage variability in six ocean model simulations of varying resolution. This intercomparison, based on the circulation and thermo- haline structure at the Good Hope line, a transect to the south west of the southern tip of Africa, is used to identify features that are robust regardless of the model used and takes into account the thermohaline biases of each model. When determined by a passive tracer method, 60 % of the magnitude of Agulhas leakage is captured and more than 80 % of its temporal fluctuations, suggesting that the method is appropriate for investigating the variability of Agulhas leakage. In all simulations but one, the major driver of variability is associated with mesoscale features passing through the section. High resolution (<1/10 deg.) hindcast models agree on the temporal (2–4 cycles per year) and spatial (300–500 km) scales of these features corresponding to observed Agulhas Rings. Coarser resolution models (<1/4 deg.) reproduce similar time scale of variability of Agulhas leakage in spite of their difficulties in representing the Agulhas rings properties. A coarser resolution climate model (2 deg.) does not resolve the spatio-temporal mechanism of variability of Agulhas leakage. Hence it is expected to underestimate the contribution of Agulhas Current System to climate variability.
Resumo:
Investigating the variability of Agulhas leakage, the volume transport of water from the Indian Ocean to the South Atlantic Ocean, is highly relevant due to its potential contribution to the Atlantic Meridional Overturning Circulation as well as the global circulation of heat and salt and hence global climate. Quantifying Agulhas leakage is challenging due to the non-linear nature of this process; current observations are insufficient to estimate its variability and ocean models all have biases in this region, even at high resolution . An Eulerian threshold integration method is developed to examine the mechanisms of Agulhas leakage variability in six ocean model simulations of varying resolution. This intercomparison, based on the circulation and thermo- haline structure at the Good Hope line, a transect to the south west of the southern tip of Africa, is used to identify features that are robust regardless of the model used and takes into account the thermohaline biases of each model. When determined by a passive tracer method, 60 % of the magnitude of Agulhas leakage is captured and more than 80 % of its temporal fluctuations, suggesting that the method is appropriate for investigating the variability of Agulhas leakage. In all simulations but one, the major driver of variability is associated with mesoscale features passing through the section. High resolution (<1/10 deg.) hindcast models agree on the temporal (2–4 cycles per year) and spatial (300–500 km) scales of these features corresponding to observed Agulhas Rings. Coarser resolution models (<1/4 deg.) reproduce similar time scale of variability of Agulhas leakage in spite of their difficulties in representing the Agulhas rings properties. A coarser resolution climate model (2 deg.) does not resolve the spatio-temporal mechanism of variability of Agulhas leakage. Hence it is expected to underestimate the contribution of Agulhas Current System to climate variability.
Resumo:
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) represents an established method for the detection and diagnosis of breast lesions. While mass-like enhancing lesions can be easily categorized according to the Breast Imaging Reporting and Data System (BI-RADS) MRI lexicon, a majority of diagnostically challenging lesions, the so called non-mass-like enhancing lesions, remain both qualitatively as well as quantitatively difficult to analyze. Thus, the evaluation of kinetic and/or morphological characteristics of non-masses represents a challenging task for an automated analysis and is of crucial importance for advancing current computer-aided diagnosis (CAD) systems. Compared to the well-characterized mass-enhancing lesions, non-masses have no well-defined and blurred tumor borders and a kinetic behavior that is not easily generalizable and thus discriminative for malignant and benign non-masses. To overcome these difficulties and pave the way for novel CAD systems for non-masses, we will evaluate several kinetic and morphological descriptors separately and a novel technique, the Zernike velocity moments, to capture the joint spatio-temporal behavior of these lesions, and additionally consider the impact of non-rigid motion compensation on a correct diagnosis.
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The North Sea cod (
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The abundance of ammonia-oxidising bacterial (AOB) and ammonia-oxidising archaeal (AOA) (amoA) genes and ammonia oxidation rates were compared bimonthly from July 2008 to May 2011 in 4 contrasting coastal sediments in the western English Channel. Despite a higher abundance of AOA amoA genes within all sediments and at all time-points, rates of ammonia oxidation correlated with AOB and not AOA amoA gene abundance. Sediment type was a major factor in determining both AOB amoA gene abundance and AOB community structure, possibly due to deeper oxygen penetration into the sandier sediments, increasing the area available for ammonia oxidation. Decreases in AOB amoA gene abundance were evident during summer and autumn, with maximum abundance and ammonia oxidation rates occurring in winter and early spring. PCR-DGGE of AOB amoA genes indicated that no seasonal changes to community composition occurred; however, a gradual movement in community composition occurred at 3 of the sites studied. The lack of correlation between AOA amoA gene abundance and ammonium oxidation rates, or any other environmental variable measured, may be related to the higher spatial variation amongst measurements, obscuring temporal trends, or the bimonthly sampling, which may have been too infrequent to capture temporal variability in the deposition of fresh organic matter. Alternatively, AOA may respond to changing substrate concentrations by an increase or decrease in transcript rather than gene abundance.
Resumo:
The development of population models able to reproduce the dynamics of zooplankton is a central issue when trying to understand how a changing environment would affect zooplankton in the future. Using 10 years of monthly data on phytoplankton and zooplankton abundance in the Bay of Biscay from the IEO's RADIALES time-series programme, we built non-parametric Generalized Additive Models (GAMs) able to reproduce the dynamics of plankton on the basis of environmental factors (nutrients, temperature, upwelling and photoperiod). We found that the interaction between these two plankton components is approximately linear, whereas the effects of environmental factors are non-linear. With the inclusion of the environmental variability, the main seasonal and inter-annual dynamic patterns observed within the studied plankton assemblage indicate the prevalence of bottom-up regulatory control. The statistically deduced models were used to simulate the dynamics of the phytoplankton and zooplankton. A good agreement between observations and simulations was obtained, especially for zooplankton. We are presently developing spatio-temporal GAM models for the North Sea based on the Continuous Plankton Recorder database.
Resumo:
The Continuous Plankton Recorder survey provides pan-oceanic data on geographic distribution, species composition, seasonal cycles of abundance, and long-term change during the last 70 years. In this paper we compare and contrast some of the historic data-analytic protocols of the survey, focusing primarily on the various means by which spatio-temporal information in CPR data has been exposed. Relative strengths and limitations are assessed, followed by suggestions for future approaches to the visualisation and summarising of CPR data.
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The Black Sea ecosystem experienced severe eutrophication-related degradation during the 1970s and 1980s. However, in recent years the Black Sea has shown some signs of recovery which are often attributed to a reduction in nutrient loading. Here, SeaWiFS chlorophyll a (chl a), a proxy for phytoplankton biomass, is used to investigate spatio-temporal patterns in Black Sea phytoplankton dynamics and to explore the potential role of climate in the Black Sea's recovery. Maps of chl a anomalies, calculated relative to the 8 year mean, emphasize spatial and temporal variability of phytoplankton biomass in the Black Sea, particularly between the riverine-influenced Northwest Shelf and the open Black Sea. Evolution of phytoplankton biomass has shown significant spatial variability of persistence of optimal bloom conditions between three major regions of the Black Sea. With the exception of 2001, chl a has generally decreased during our 8 year time-series. However, the winter of 2000–2001 was anomalously warm with low wind stress, resulting in reduced vertical mixing of the water column and retention of nutrients in the photic zone. These conditions were associated with anomalously high levels of chl a throughout much of the open Black Sea during the following spring and summer. The unusual climatic conditions occurring in 2001 may have triggered a shift in the Black Sea's chl a regime. The long-term significance of this recent shift is still uncertain but illustrates a non-linear response to climate forcing that makes future ecosystem changes in the pelagic Black Sea ecosystem difficult to predict.
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1.Understanding which environmental factors drive foraging preferences is critical for the development of effective management measures, but resource use patterns may emerge from processes that occur at different spatial and temporal scales. Direct observations of foraging are also especially challenging in marine predators, but passive acoustic techniques provide opportunities to study the behaviour of echolocating species over a range of scales. 2.We used an extensive passive acoustic data set to investigate the distribution and temporal dynamics of foraging in bottlenose dolphins using the Moray Firth (Scotland, UK). Echolocation buzzes were identified with a mixture model of detected echolocation inter-click intervals and used as a proxy of foraging activity. A robust modelling approach accounting for autocorrelation in the data was then used to evaluate which environmental factors were associated with the observed dynamics at two different spatial and temporal scales. 3.At a broad scale, foraging varied seasonally and was also affected by seabed slope and shelf-sea fronts. At a finer scale, we identified variation in seasonal use and local interactions with tidal processes. Foraging was best predicted at a daily scale, accounting for site specificity in the shape of the estimated relationships. 4.This study demonstrates how passive acoustic data can be used to understand foraging ecology in echolocating species and provides a robust analytical procedure for describing spatio-temporal patterns. Associations between foraging and environmental characteristics varied according to spatial and temporal scale, highlighting the need for a multi-scale approach. Our results indicate that dolphins respond to coarser scale temporal dynamics, but have a detailed understanding of finer-scale spatial distribution of resources.
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Ca2+-dependent signalling processes enable plants to perceive and respond to diverse environmental stressors, such as osmotic stress. A clear understanding of the role of spatiotemporal Ca2+ signalling in green algal lineages is necessary in order to understand how the Ca2+ signalling machinery has evolved in land plants. We used single-cell imaging of Ca2+-responsive fluorescent dyes in the unicellular green alga Chlamydomonas reinhardtii to examine the specificity of spatial and temporal dynamics of Ca2+ elevations in the cytosol and flagella in response to salinity and osmotic stress. We found that salt stress induced a single Ca2+ elevation that was modulated by the strength of the stimulus and originated in the apex of the cell, spreading as a fast Ca2+ wave. By contrast, hypo-osmotic stress induced a series of repetitive Ca2+ elevations in the cytosol that were spatially uniform. Hypo-osmotic stimuli also induced Ca2+ elevations in the flagella that occurred independently from those in the cytosol. Our results indicate that the requirement for Ca2+ signalling in response to osmotic stress is conserved between land plants and green algae, but the distinct spatial and temporal dynamics of osmotic Ca2+ elevations in C. reinhardtii suggest important mechanistic differences between the two lineages.
Resumo:
Ca2+-dependent signalling processes enable plants to perceive and respond to diverse environmental stressors, such as osmotic stress. A clear understanding of the role of spatiotemporal Ca2+ signalling in green algal lineages is necessary in order to understand how the Ca2+ signalling machinery has evolved in land plants. We used single-cell imaging of Ca2+-responsive fluorescent dyes in the unicellular green alga Chlamydomonas reinhardtii to examine the specificity of spatial and temporal dynamics of Ca2+ elevations in the cytosol and flagella in response to salinity and osmotic stress. We found that salt stress induced a single Ca2+ elevation that was modulated by the strength of the stimulus and originated in the apex of the cell, spreading as a fast Ca2+ wave. By contrast, hypo-osmotic stress induced a series of repetitive Ca2+ elevations in the cytosol that were spatially uniform. Hypo-osmotic stimuli also induced Ca2+ elevations in the flagella that occurred independently from those in the cytosol. Our results indicate that the requirement for Ca2+ signalling in response to osmotic stress is conserved between land plants and green algae, but the distinct spatial and temporal dynamics of osmotic Ca2+ elevations in C. reinhardtii suggest important mechanistic differences between the two lineages.