999 resultados para Estimating chlorophyll concentration


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The effects of elevated CO2 and temperature on photosynthesis and calcification in the calcifying algae Halimeda macroloba and Halimeda cylindracea and the symbiont-bearing benthic foraminifera Marginopora vertebralis were investigated through exposure to a combination of four temperatures (28°C, 30°C, 32°C, and 34°C) and four CO2 levels (39, 61, 101, and 203 Pa; pH 8.1, 7.9, 7.7, and 7.4, respectively). Elevated CO2 caused a profound decline in photosynthetic efficiency (FV : FM), calcification, and growth in all species. After five weeks at 34°C under all CO2 levels, all species died. Chlorophyll (Chl) a and b concentration in Halimeda spp. significantly decreased in 203 Pa, 32°C and 34°C treatments, but Chl a and Chl c2 concentration in M. vertebralis was not affected by temperature alone, with significant declines in the 61, 101, and 203 Pa treatments at 28°C. Significant decreases in FV : FM in all species were found after 5 weeks of exposure to elevated CO2 (203 Pa in all temperature treatments) and temperature (32°C and 34°C in all pH treatments). The rate of oxygen production declined at 61, 101, and 203 Pa in all temperature treatments for all species. The elevated CO2 and temperature treatments greatly reduced calcification (growth and crystal size) in M. vertebralis and, to a lesser extent, in Halimeda spp. These findings indicate that 32°C and 101 Pa CO2, are the upper limits for survival of these species on Heron Island reef, and we conclude that these species will be highly vulnerable to the predicted future climate change scenarios of elevated temperature and ocean acidification.

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Parameters in the photosynthesis-irradiance (P-E) relationship of phytoplankton were measured at weekly to bi-weekly intervals for 20 yr at 6 stations on the Rhode River, Maryland (USA). Variability in the light-saturated photosynthetic rate, PBmax, was partitioned into interannual, seasonal, and spatial components. The seasonal component of the variance was greatest, followed by interannual and then spatial. Physiological models of PBmax based on balanced growth or photoacclimation predicted the overall mean and most of the range, but not individual observations, and failed to capture important features of the seasonal and interannual variability. PBmax correlated most strongly with temperature and the concentration of dissolved inorganic carbon (IC), with lesser correlations with chlorophyll a, diffuse attenuation coefficient, and a principal component of the species composition. In statistical models, temperature and IC correlated best with the seasonal pattern, but temperature peaked in late July, out of phase with PBmax, which peaked in September, coincident with the maximum in monthly averaged IC concentration. In contrast with the seasonal pattern, temperature did not contribute to interannual variation, which instead was governed by IC and the additional lesser correlates. Spatial variation was relatively weak and uncorrelated with ancillary measurements. The results demonstrate that both the overall distribution of PBmax and its relationship with environmental correlates may vary from year to year. Coefficients in empirical statistical models became stable after including 7 to 10 yr of data. The main correlates of PBmax are amenable to automated monitoring, so that future estimates of primary production might be made without labor-intensive incubations.

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Many studies have shown the considerable potential for the application of remote-sensing-based methods for deriving estimates of lake water quality. However, the reliable application of these methods across time and space is complicated by the diversity of lake types, sensor configuration, and the multitude of different algorithms proposed. This study tested one operational and 46 empirical algorithms sourced from the peer-reviewed literature that have individually shown potential for estimating lake water quality properties in the form of chlorophyll-a (algal biomass) and Secchi disc depth (SDD) (water transparency) in independent studies. Nearly half (19) of the algorithms were unsuitable for use with the remote-sensing data available for this study. The remaining 28 were assessed using the Terra/Aqua satellite archive to identify the best performing algorithms in terms of accuracy and transferability within the period 2001–2004 in four test lakes, namely Vänern, Vättern, Geneva, and Balaton. These lakes represent the broad continuum of large European lake types, varying in terms of eco-region (latitude/longitude and altitude), morphology, mixing regime, and trophic status. All algorithms were tested for each lake separately and combined to assess the degree of their applicability in ecologically different sites. None of the algorithms assessed in this study exhibited promise when all four lakes were combined into a single data set and most algorithms performed poorly even for specific lake types. A chlorophyll-a retrieval algorithm originally developed for eutrophic lakes showed the most promising results (R2 = 0.59) in oligotrophic lakes. Two SDD retrieval algorithms, one originally developed for turbid lakes and the other for lakes with various characteristics, exhibited promising results in relatively less turbid lakes (R2 = 0.62 and 0.76, respectively). The results presented here highlight the complexity associated with remotely sensed lake water quality estimates and the high degree of uncertainty due to various limitations, including the lake water optical properties and the choice of methods.

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This paper introduces a nonlinear measure of dependence between random variables in the context of remote sensing data analysis. The Hilbert-Schmidt Independence Criterion (HSIC) is a kernel method for evaluating statistical dependence. HSIC is based on computing the Hilbert-Schmidt norm of the cross-covariance operator of mapped samples in the corresponding Hilbert spaces. The HSIC empirical estimator is very easy to compute and has good theoretical and practical properties. We exploit the capabilities of HSIC to explain nonlinear dependences in two remote sensing problems: temperature estimation and chlorophyll concentration prediction from spectra. Results show that, when the relationship between random variables is nonlinear or when few data are available, the HSIC criterion outperforms other standard methods, such as the linear correlation or mutual information.

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The relationship between phytoplankton assemblages and the associated optical properties of the water body is important for the further development of algorithms for large-scale remote sensing of phytoplankton biomass and the identification of phytoplankton functional types (PFTs), which are often representative for different biogeochemical export scenarios. Optical in-situ measurements aid in the identification of phytoplankton groups with differing pigment compositions and are widely used to validate remote sensing data. In this study we present results from an interdisciplinary cruise aboard the RV Polarstern along a north-to-south transect in the eastern Atlantic Ocean in November 2008. Phytoplankton community composition was identified using a broad set of in-situ measurements. Water samples from the surface and the depth of maximum chlorophyll concentration were analyzed by high performance liquid chromatography (HPLC), flow cytometry, spectrophotometry and microscopy. Simultaneously, the above- and underwater light field was measured by a set of high spectral resolution (hyperspectral) radiometers. An unsupervised cluster algorithm applied to the measured parameters allowed us to define bio-optical provinces, which we compared to ecological provinces proposed elsewhere in the literature. As could be expected, picophytoplankton was responsible for most of the variability of PFTs in the eastern Atlantic Ocean. Our bio-optical clusters agreed well with established provinces and thus can be used to classify areas of similar biogeography. This method has the potential to become an automated approach where satellite data could be used to identify shifting boundaries of established ecological provinces or to track exceptions from the rule to improve our understanding of the biogeochemical cycles in the ocean.

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Tese de Doutoramento, Física, 17 de Dezembro de 2013, Universidade dos Açores.

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In the California Current System the spring transition from poleward to equatorward alongshore wind stress heralds the beginning of upwelling-favorable conditions. The phytoplankton response to this transition is investigated using 8 years ( 1998-2005) of daily, 4-km resolution, Sea-viewing Wide Field of view Sensor ( SeaWiFS) chlorophyll a concentration data. Cluster analysis of the chlorophyll a time series at each location is used to separate the inshore upwelling region from offshore and oligotrophic areas. An objective method for estimating the timing of bloom initiation is used to construct a map of the mean bloom start date. Interannual variability in bloom timing and magnitude is investigated in four regions: 45 degrees N - 50 degrees N, 40 degrees N - 45 degrees N, 35 degrees N - 40 degrees N and 20 degrees N - 35 degrees N. Daily satellite derived wind data ( QuikSCAT) allow the timing of the first episode of persistently upwelling favorable winds to be estimated. Bloom initiation generally coincides with the onset of upwelling winds ( +/- 15 days). South of similar to 35 degrees N, where winds are southward year-round, the timing of increased chlorophyll concentration corresponds closely to timing of the seasonal increase in upwelling intensity. A 1-D model and satellite derived photosynthetically available radiation data are used to estimate time series of depth- averaged irradiance. In the far north of the region (> 46 degrees N) light is shown to limit phytoplankton growth in early spring. In 2005 the spring bloom in the northern regions (> 35 degrees N) had a "false start''. A sharp increase in chl a in February quickly receded, and a sustained increase in biomass was delayed until July. We hypothesize that this resulted in a mismatch in timing of food availability to higher trophic levels.

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Time series of satellite measurements are used to describe patterns of surface temperature and chlorophyll associated with the 1996 cold La Nina phase and the 1997-1998 warm El Nino phase of the El Nino - Southern Oscillation cycle in the upwelling region off northern Chile. Surface temperature data are available through the entire study period. Sea-viewing Wide Field-of-view Sensor (SeaWiFS) data first became available in September 1997 during a relaxation in El Nino conditions identified by in situ hydrographic data. Over the time period of coincident satellite data, chlorophyll patterns closely track surface temperature patterns. Increases both in nearshore chlorophyll concentration and in cross-shelf extension of elevated concentrations are associated with decreased coastal temperatures during both the relaxation in El Nino conditions in September-November 1997 and the recovery from EI Nino conditions after March 1998. Between these two periods during austral summer (December 1997 to March 1998) and maximum El Nino temperature anomalies, temperature patterns normally associated with upwelling were absent and chlorophyll concentrations were minimal. Cross-shelf chlorophyll distributions appear to be modulated by surface temperature frontal zones and are positively correlated with a satellite-derived upwelling index. Frontal zone patterns and the upwelling index in 1996 imply an austral summer nearshore chlorophyll maximum, consistent with SeaWiFS data from I 1998-1999, after the El Nino. SeaWiFS retrievals in the data set used here are higher than in situ measurements by a factor of 2-4; however, consistency in the offset suggests relative patterns are valid.

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The marine laboratories in Plymouth have sampled at two principle sites in the Western English Channel for over a century in open-shelf (station E1; 50° 02'N, 4° 22'W) and coastal (station L4; 50° 15'N, 4° 13'W) waters. These stations are seasonally stratified from late-April until September, and the variable biological response is regulated by subtle variations in temperature, light, nutrients and meteorology. Station L4 is characterized by summer nutrient depletion, although intense summer precipitation, increasing riverine input to the system, results in pulses of increased nitrate concentration and surface freshening. The winter nutrient concentrations at E1 are consistent with an open-shelf site. Both stations have a spring and autumn phytoplankton bloom; at station E1, the autumn bloom tends to dominate in terms of chlorophyll concentration. The last two decades have seen a warming of around 0.6°C per decade, and this is superimposed on several periods of warming and cooling over the past century. In general, over the Western English Channel domain, the end of the 20th century was around 0.5°C warmer than the first half of the century. The warming magnitude and trend is consistent with other stations across the north-west European Shelf and occurred during a period of reduced wind stress and increased levels of insolation (+20%); these are both correlated with the larger scale climatic forcing of the North Atlantic Oscillation.