Milton Kampel

How do cold water biota arrive in a tropical bay near Rio de Janeiro, Brazil?

Abstract Previous ecological studies on foraminifera and ostracoda from the tropical Sepetiba Bay, located in the southern part of the State of Rio de Janeiro, Brazil, have noted the presence in this area of some cool water taxons typical of the Argentine continental platform. These studies have proposed that parcels of these temperate waters with their associated biological indicators are advected northward along the platform, penetrating into some tropical entrances of the southeast coast of Brazil. In the present study, ecological data (foraminifera, ostracoda and microbivalves), are used together with information obtained by satellite tracked drifting buoys and digital thermal imagery obtained from NOAA satellites to indicate the path taken by these high latitude species along the southern Brazilian coast to arrive in the Sepetiba Bay, near the city of Rio de Janeiro. Our general conclusion is that biotic elements native to the colder, less saline marine waters seen to the south of Brazil have been and are being advected northward along the inner part of the continental platform to about 22°S. Water parcels containing this biota may, in a sporadic fashion, enter into the tropical Sepetiba Bay. The passage of meteorological fronts through the region is considered to be an important if not the principal mechanism for the sporadic entry of the cool water into the Southern Coastal Entrance of the State of Rio de Janeiro.

Water Column Correction for Coral Reef Studies by Remote Sensing

Human activity and natural climate trends constitute a major threat to coral reefs worldwide. Models predict a significant reduction in reef spatial extension together with a decline in biodiversity in the relatively near future. In this context, monitoring programs to detect changes in reef ecosystems are essential. In recent years, coral reef mapping using remote sensing data has benefited from instruments with better resolution and computational advances in storage and processing capabilities. However, the water column represents an additional complexity when extracting information from submerged substrates by remote sensing that demands a correction of its effect. In this article, the basic concepts of bottom substrate remote sensing and water column interference are presented. A compendium of methodologies developed to reduce water column effects in coral ecosystems studied by remote sensing that include their salient features, advantages and drawbacks is provided. Finally, algorithms to retrieve the bottom reflectance are applied to simulated data and actual remote sensing imagery and their performance is compared. The available methods are not able to completely eliminate the water column effect, but they can minimize its influence. Choosing the best method depends on the marine environment, available input data and desired outcome or scientific application.

Multi-sensor synergistic analysis of mesoscale oceanic features: Campos Basin, south-eastern Brazil

This study presents a combined use of multi-sensor remote sensing and in situ data for the analysis and interpretation of oceanic features observed at the continental shelf and slope of the Campos Basin, south-eastern Brazil. Ocean colour (SeaWiFS), thermal infrared (AVHRR), scatterometer winds (QuikSCAT) and SAR (Radarsat-1) data were integrated to associate the different SAR backscatter patterns with physical and biological oceanic processes. The interpreted SAR features included processes such as oceanic fronts, current meandering and eddies, upwelling plumes, wind variability and algae blooms. The interpretation of these features was only feasible through the use of the multi-sensor synergistic approach complemented by timely field verification.

Mapping of mangrove forests on the southern coast of São Paulo, Brazil, using synthetic aperture radar data from ALOS/PALSAR

Widespread in the coastal zones of (sub)tropical regions, mangroves are an essential habitat for many animal species and provide subsistence resources for many human coastal communities. Among remote sensing techniques, synthetic aperture radar is a particularly advantageous method to monitor mangroves: images are not dependent on cloud cover and can provide information from forest understory. This article mapped mangrove forests in the southern coast of São Paulo State (Brazil) using frequency-based contextual classification of incoherent attributes derived from a multi-polarized Phased Array L-Band Synthetic Aperture Radar (PALSAR) image. The use of 10 incoherent attributes and only 3 Synthetic Aperture Radar (SAR) vegetation indices as input for digital classification showed the best accuracies with kappa index values of 0.739 and 0.734, respectively. HH polarization and SAR vegetation indices were the attributes that contributed most to the mangrove mapping procedure. The use of L-Band SAR data was effective for mapping mangrove areas, and therefore it is recommended as a tool for coastal management.

Simultaneous Measurements of Chlorophyll Concentration by Lidar, Fluorometry, above-Water Radiometry, and Ocean Color MODIS Images in the Southwestern Atlantic

Comparisons between in situ measurements of surface chlorophyll-a concentration (CHL) and ocean color remote sensing estimates were conducted during an oceanographic cruise on the Brazilian Southeastern continental shelf and slope, Southwestern South Atlantic. In situ values were based on fluorometry, above-water radiometry and lidar fluorosensor. Three empirical algorithms were used to estimate CHL from radiometric measurements: Ocean Chlorophyll 3 bands (OC3MRAD), Ocean Chlorophyll 4 bands (OC4v4RAD), and Ocean Chlorophyll 2 bands (OC2v4RAD). The satellite estimates of CHL were derived from data collected by the MODerate-resolution Imaging Spectroradiometer (MODIS) with a nominal 1.1 km resolution at nadir. Three algorithms were used to estimate chlorophyll concentrations from MODIS data: one empirical - OC3MSAT, and two semi-analytical - Garver, Siegel, Maritorena version 01 (GSM01SAT), and CarderSAT. In the present work, MODIS, lidar and in situ above-water radiometry and fluorometry are briefly described and the estimated values of chlorophyll retrieved by these techniques are compared. The chlorophyll concentration in the study area was in the range 0.01 to 0.2 mg/m3. In general, the empirical algorithms applied to the in situ radiometric and satellite data showed a tendency to overestimate CHL with a mean difference between estimated and measured values of as much as 0.17 mg/m3 (OC2v4RAD). The semi-analytical GSM01 algorithm applied to MODIS data performed better (rmse 0.28, rmse-L 0.08, mean diff. -0.01 mg/m3) than the Carder and the empirical OC3M algorithms (rmse 1.14 and 0.36, rmse-L 0.34 and 0.11, mean diff. 0.17 and 0.02 mg/m3, respectively). We find that rmsd values between MODIS relative to the in situ radiometric measurements are < 26%, i.e., there is a trend towards overestimation of RRS by MODIS for the stations considered in this work. Other authors have already reported over and under estimation of MODIS remotely sensed reflectance due to several errors in the bio-optical algorithm performance, in the satellite sensor calibration, and in the atmospheric-correction algorithm.

Performance analysis of MODIS 500-m spatial resolution products for estimating chlorophyll-a concentrations in oligo- to meso-trophic waters case study: Itumbiara reservoir, Brazil

Monitoring chlorophyll-a (chl-a) concentrations is important for the management of water quality, because it is a good indicator of the eutrophication level in an aquatic system. Thus, our main purpose was to develop an alternative technique to monitor chl-a in time and space through remote sensing techniques. However, one of the limitations of remote sensing is the resolution. To achieve a high temporal resolution and medium space resolution, we used the Moderate Resolution Imaging Spectroradiometer (MODIS) 500-m reflectance product, MOD09GA, and limnological parameters from the Itumbiara Reservoir. With these data, an empirical (O14a) and semi-empirical (O14b) algorithm were developed. Algorithms were cross-calibrated and validated using three datasets: one for each campaign and a third consisting of a combination of the two individual campaigns. Algorithm O14a produced the best validation with a root mean square error (RMSE) of 30.4%, whereas O14b produced an RMSE of 32.41% using the mixed dataset calibration. O14a was applied to MOD09GA to build a time series for the reservoir for the year of 2009. The time-series analysis revealed that there were occurrences of algal blooms in the summer that were likely related to the additional input of nutrients caused by rainfall runoff. During the winter, however, the few observed algal blooms events were related to periods of atmospheric meteorological variations that represented an enhanced external influence on the processes of mixing and stratification of the water column. Finally, the use of remote sensing techniques can be an important tool for policy makers, environmental managers and the scientific community with which to monitor water quality.

Influence of solar radiation absorbed by phytoplankton on the thermal structure and circulation of the tropical Atlantic Ocean

Numerical experiments conducted with an ocean general ocean circulation model reveal the potential influence of solar radiation absorbed by phytoplankton on the thermal structure and currents of the Tropical Atlantic Ocean. In the model, solar radiation penetration is parameterized explicitly as a function of chlorophyll-a concentration, the major variable affecting water turbidity in the open ocean. Two types of runs are performed, a clear water (control) run with a constant minimum chlorophyll-a concentration of 0.02 mgm-3, and a turbid water (chlorophyll) run with space- and time-varying chlorophyll-a concentration from satellite data. The difference between results from the two runs yields the biological effects. In the chlorophyll run, nutrients and biology production are implicitly taken into account, even though biogeochemical processes are not explicitly included, since phytoplankton distribution, prescribed from observations, is the result of those processes. Due to phytoplankton-radiation forcing, the surface temperature is higher by 1-2 K on average annually in the region of the North Equatorial current, the Northern part of the South Equatorial current, and the Caribbean system, and by 3-4 K in the region of the Guinea current. In this region, upwelling is reduced, and heat trapped in the surface layers by phytoplankton is not easily removed. The surface temperature is lower by 1 K in the Northern region of the Benguela current, due to increased upwelling. At depth, the equatorial Atlantic is generally cooler, as well as the eastern part of the tropical basin (excluding the region of the sub-tropical gyres). The North and South equatorial currents, as well as the Equatorial undercurrent, are enhanced by as much as 3-4 cms-1, and the circulation of the subtropical gyres is increased. Pole-ward heat transport is slightly reduced North of 35°N, suggesting that phytoplankton, by increasing the horizontal return flow in the subtropical region, may exert a cooling influence on higher latitude regions. The findings indicate that biology-induced buoyancy plays a significant role, in an indirect if not direct way, in the variability of the Tropical Atlantic Ocean, with consequences on atmospheric circulation and climate.

Evaluation of Primary Production in the Lower Amazon River Based on a Dissolved Oxygen Stable Isotopic Mass Balance

The Amazon River outgasses nearly an equivalent amount of CO2 as the rainforest sequesters on an annual basis due to microbial decomposition of terrigenous and aquatic organic matter. Most research performed in the Amazon has been focused on unraveling the mechanisms driving CO2 production since the recognition of a persistent state of CO2 supersaturation. However, although the river system is clearly net heterotrophic, the interplay between primary production and respiration is an essential aspect to understanding the overall metabolism of the ecosystem and potential transfer of energy up trophic levels. For example, an efficient ecosystem is capable of both decomposing high amounts of organic matter at lower trophic levels, driving CO2 emissions, and accumulating energy/biomass in higher trophic levels, stimulating fisheries production. Early studies found minimal evidence for primary production in the Amazon River mainstem and it has since been assumed that photosynthesis is strongly limited by low light penetration attributed to the high sediment load. Here, we test this assumption by measuring the stable isotopic composition of O2 (δ18O-O2) and O2 saturation levels in the lower Amazon River from Obidos to the river mouth and its major tributaries, the Xingu and Tapajos rivers, during high and low water periods. An oxygen mass balance model was developed to estimate the input of photosynthetic oxygen in the discrete reach from Obidos to Almeirim, midway to the river mouth. Based on the oxygen mass balance we estimate that primary production occurred at a rate of 0.39 ± 0.24 g O m3 d-1 at high water and 1.02 ± 0.55 g O m3 d-1 at low water. This translates to 41 ± 24% of the rate of O2 drawdown via respiration during high water and 67 ± 33% during low water. These primary production rates are 2-7 times higher than past estimates for the Amazon River mainstem. It is possible that at high water much of this productivity signal is the result of legacy advection from floodplains, whereas limited floodplain connectivity during low water implies that most of this signal is the result of in situ primary production in the Amazon River mainstem.

Assessment of remotely sensed chlorophyll-a concentration in Guanabara Bay, Brazil

Abstract. The Guanabara Bay (GB) is an estuarine system in the metropolitan region of Rio de Janeiro (Brazil), with a surface area of ∼346  km2 threatened by anthropogenic pressure. Remote sensing can provide frequent data for studies and monitoring of water quality parameters, such as chlorophyll-a concentration (Chl-a). Different combination of Medium Resolution Imaging Spectrometer (MERIS) remote sensing reflectance band ratios were used to estimate Chl-a. Standard algorithms such as Ocean Color 3-band, Ocean Color-4 band, fluorescence line height, and maximum chlorophyll index were also tested. The MERIS Chl-a estimates were statistically compared with a dataset of in situ Chl-a (2002 to 2012). Good correlations were obtained with the use of green, red, and near-infrared bands. The best performing algorithm was based on the red (665 nm) and green (560 nm) band ratio, named “RG3” algorithm (r2=0.71, chl-a=62,565*x1.6118). The RG3 was applied to a time series of MERIS images (2003- to 2012). The GB has a high temporal and spatial variability of Chl-a, with highest values found in the wet season (October to March) and in some of the most internal regions of the estuary. Lowest concentrations are found in the central circulation channel due to the flushing of ocean water masses promoted by pumping tide.

Spatiotemporal total suspended matter estimation in Itumbiara reservoir with Landsat-8/OLI images

ABSTRACT The transparency of water is affected by the amount of sunlight available, suspended particles and dissolved solids such as colored dissolved organic material present in the water column. High concentrations of total suspended matter (TSM) reduce water clarity, which can affect photosynthesis of submerged aquatic vegetation, thereby affecting oxygen production which is essential to aquatic organisms at upper levels in the food chain. The aim of this work is to evaluate the use of Landsat-8 Operational Land Imager (OLI) sensor to estimate TSM concentrations in the Itumbiara hydroelectric reservoir, Midwest Brazil (18°25′ S, 49°06′ W). Concurrent proximal remote-sensing and limnological data were collected in May and September 2009, acquired between 10:00 and 14:00 (Brazil time UTC-3) to provide representative daily readings. In situ above-water radiometric data were used to simulate remote-sensing reflectance (Rrs) for the Landsat-8/OLI spectral bands. TSM empirical models were derived from Landsat-8/OLI simulated spectral bands. The data set acquired in September 2009 was used to derive the models and the data collected in May 2009 was used for validation. To assess the similarities and differences between measured and model derived TSM concentrations, two statistical indicators were calculated. The model with lowest error was applied to selected Landsat-8/OLI images. Preliminary results showed that the model with lowest error was calibrated using Rrs from bands 2 and 3 as index. The results obtained here show that Landsat-8/OLI sensor has enough sensibility to estimate TSM concentrations in inland waters in Brazil.