New Radiometric Approaches to Compute Underwater Irradiances: Potential Applications for High-Resolution and Citizen Science-Based Water Quality Monitoring Programs.

Measuring the diffuse attenuation coefficient (Kd) allows for monitoring the water body's environmental status. This parameter is of particular interest in water quality monitoring programs because it quantifies the presence of light and the euphotic zone's depth. Citizen scientists can meaningfully contribute by monitoring water quality, complementing traditional methods by reducing monitoring costs and significantly improving data coverage, empowering and supporting decision-making. However, the quality of the acquisition of in situ underwater irradiance measurements has some limitations, especially in areas where stratification phenomena occur in the first meters of depth. This vertical layering introduces a gradient of properties in the vertical direction, affecting the associated Kd. To detect and characterize these variations of Kd in the water column, it needs a system of optical sensors, ideally placed in a range of a few cm, improving the low vertical accuracy. Despite that, the problem of self-shading on the instrumentation becomes critical. Here, we introduce a new concept that aims to improve the vertical accuracy of the irradiance measurements: the underwater annular irradiance (Ea). This new concept consists of measuring the irradiance in an annular-shaped distribution. We first compute the optimal annular angle that avoids self-shading and maximizes the light captured by the sensors. Second, we use different scenarios of water types, solar zenith angle, and cloud coverage to assess the robustness of the corresponding diffuse attenuation coefficient, Ka. Finally, we derive empirical functions for computing Kd from Ka. This new concept opens the possibility to a new generation of optical sensors in an annular-shaped distribution which is expected to (a) increase the vertical resolution of the irradiance measurements and (b) be easy to deploy and maintain and thus to be more suitable for citizen scientists.

Estimating the Underwater Diffuse Attenuation Coefficient with a Low-Cost Instrument: The KdUINO DIY Buoy.

A critical parameter to assess the environmental status of water bodies is the transparency of the water, as it is strongly affected by different water quality related components (such as the presence of phytoplankton, organic matter and sediment concentrations). One parameter to assess the water transparency is the diffuse attenuation coefficient. However, the number of subsurface irradiance measurements obtained with conventional instrumentation is relatively low, due to instrument costs and the logistic requirements to provide regular and autonomous observations. In recent years, the citizen science concept has increased the number of environmental observations, both in time and space. The recent technological advances in embedded systems and sensors also enable volunteers (citizens) to create their own devices (known as Do-It-Yourself or DIY technologies). In this paper, a DIY instrument to measure irradiance at different depths and automatically calculate the diffuse attenuation Kd coefficient is presented. The instrument, named KdUINO, is based on an encapsulated low-cost photonic sensor and Arduino (an open-hardware platform for the data acquisition). The whole instrument has been successfully operated and the data validated comparing the KdUINO measurements with the commercial instruments. Workshops have been organized with high school students to validate its feasibility.

Cost-Effective Hyperspectral Transmissometers for Oceanographic Applications: Performance Analysis.

The recent development of inexpensive, compact hyperspectral transmissometers broadens the research capabilities of oceanographic applications. These developments have been achieved by incorporating technologies such as micro-spectrometers as detectors as well as light emitting diodes (LEDs) as light sources. In this study, we evaluate the performance of the new commercial LED-based hyperspectral transmissometer VIPER (TriOS GmbH, Rastede, Germany), which combines different LEDs to emulate the visible light spectrum, aiming at the determination of attenuation coefficients in coastal environments. For this purpose, experimental uncertainties related to the instrument stability, the effect of ambient light and derived temperature, and salinity correction factors are analyzed. Our results identify some issues related to the thermal management of the LEDs and the contamination of ambient light. Furthermore, the performance of VIPER is validated against other transmissometers through simultaneous field measurements. It is demonstrated that VIPER provides a compact and cost-effective alternative for beam attenuation measurements in coastal waters, but it requires the consideration of several optimizations.

Analysis of discrimination techniques for low-cost narrow-band spectrofluorometers.

The need for covering large areas in oceanographic measurement campaigns and the general interest in reducing the observational costs open the necessity to develop new strategies towards this objective, fundamental to deal with current and future research projects. In this respect, the development of low-cost instruments becomes a key factor, but optimal signal-processing techniques must be used to balance their measurements with those obtained from accurate but expensive instruments. In this paper, a complete signal-processing chain to process the fluorescence spectra of marine organisms for taxonomic discrimination is proposed. It has been designed to deal with noisy, narrow-band and low-resolution data obtained from low-cost sensors or instruments and to optimize its computational cost, and it consists of four separated blocks that denoise, normalize, transform and classify the samples. For each block, several techniques are tested and compared to find the best combination that optimizes the classification of the samples. The signal processing has been focused on the Chlorophyll-a fluorescence peak, since it presents the highest emission levels and it can be measured with sensors presenting poor sensitivity and signal-to-noise ratios. The whole methodology has been successfully validated by means of the fluorescence spectra emitted by five different cultures.

Revealing biases in insect observations: A comparative analysis between academic and citizen science data.

Citizen Science is a powerful tool for biodiversity research, as it facilitates data recording at large scales that would otherwise be impossible to cover by standard academic research. Despite its benefits, the accuracy of citizen science data remains a subject of concern among scientists, with varying results reported so far. Neither citizen science data nor academic records are immune to biases, which can significantly impact the quality and reliability of observations. Here, using insects in the Iberian Peninsula as a case study, we compare data collected by participatory platforms to those obtained through academic research projects, and assess their taxonomic, spatial, temporal, and environmental biases. Results show a prominent taxonomic bias in both academic and citizen science data, with certain insect orders receiving more attention than others. These taxonomic biases are conserved between different participatory platforms, as well as between groups of users with different levels of contribution performance. The biases captured by leading contributors in participatory platforms mirrored those of sporadic users and academic data. Citizen science data had higher spatial coverage and less spatial clustering than academic data, showing also clearer trends in temporal seasonality. Environmental coverage over time was more stable in citizen science than in academic records. User behaviour, preference, taxonomical expertise, data collection methodologies and external factors may contribute to these biases. This study shows the multifaceted nature of biases present in academic records and citizen science platforms. The insights gained from this analysis emphasize the need for careful consideration of these biases when making use of biodiversity data from different sources. Combining academic and citizen science data enhances our understanding of biodiversity, as their integration offers a more comprehensive perspective than relying solely on either dataset alone, especially since biases in these two types of data are not always the same.

Ice phenology interactions with water and air temperatures in high mountain lakes.

Ice phenology is of great importance for the thermal structure of lakes and ponds and the biology of lake species. Under the current climate change conditions, ice-cover duration has been reduced by an advance in ice-off, and a delay in ice-on, and future projections foresee this trend as continuing. Here, we describe the current ice phenology of Pyrenean high mountain lakes and ponds, including ice-cover duration and ice-on and ice-off dates. We used mixed models to identify the variables that explained the observed patterns, extrapolated them across all water bodies in the mountain range, and related the seasonality of air and water temperatures with ice phenology using structural equation models. Ice phenology was obtained from the temperature series of 85 lakes and ponds for fourteen years, including 2001 to 2004 and 2009 to 2019. We discovered that high autumn precipitation was related to earlier ice-on dates, and that earlier ice-off dates were associated with higher following-summer water temperatures. We found a greater predictability of ice-off dates and ice-cover duration than ice-on dates. Altitude was the most important variable explaining the variation in ice phenology, followed by latitude, which was related to climatic differences among the northern and southern slopes of the mountain range. The lake area was significant for ice-on dates and ice-cover duration. The interannual variability in air temperature and radiation was remarkable for the ice-off date and ice-cover duration but not for the ice-on date. In contrast, wind speed was related to an earlier ice-off date and shorter ice-cover duration. All the measured lakes and ponds froze in winter during the studied period, a feature maintained in the extrapolation to the whole set of water bodies.

Factors of surface thermal variation in high-mountain lakes of the Pyrenees.

Thermal variables are crucial drivers of biological processes in lakes and ponds. In the current context of climate change, determining which factors better constrain their variation within lake districts become of paramount importance for understanding species distribution and their conservation. In this study, we describe the regional and short-term interannual variability in surface water temperature of high mountain lakes and ponds of the Pyrenees. And, we use mixed regression models to identify key environmental factors and to infer mean and maximum summer temperature, accumulated degree-days, diel temperature ranges and three-days' oscillation. The study is based on 59 lake-temperature series measured from 2001 to 2014. We found that altitude was the primary explicative factor for accumulated degree-days and mean and maximum temperature. In contrast, lake area showed the most relevant effect on the diel temperature range and temperature oscillations, although diel temperature range was also found to decline with altitude. Furthermore, the morphology of the catchment significantly affected accumulated degree-days and maximum and mean water temperatures. The statistical models developed here were applied to upscale spatially the current thermic conditions across the whole set of lakes and ponds of the Pyrenees.

Spatial and temporal land cover changes in Terminos Lagoon Reserve, Mexico.

Terminos Lagoon ecosystem is the largest fluvial-lagoon estuarine system in the country and one of the most important reserves of coastal flora and fauna in Mexico. Since the seventies, part of the main infrastructure for country's oil extraction is located in this area. Its high biodiversity has motivated different type of studies including deforestation processes and land use planning. In this work we used satellite image analysis to determine land cover changes in the area from 1974 to 2001. Our results indicate that tropical forest and mangroves presented the most extensive losses in its coverage. In contrast, urban areas and induced grassland increased considerably. In 2001 more than half of the ecosystem area showed changes from its original land cover, and a third part of it was deteriorated. The main causes of deforestation were both the increase in grassland and the growth of urban areas. However, deforestation was attenuated by natural reforestation and plant canopy recovery. We conclude that the introduction of cattle and urban development were the main causes for the land cover changes; however, the oil industry activity located in the ecosystem, has promoted indirectly to urban growth and rancher boom.

Citclops: A next-generation sensor system for the monitoring of natural waters and a citizens' observatory for the assessment of ecosystems' status.

The European-Commission-funded project 'Citclops' (Citizens' observatory for coast and ocean optical monitoring) developed methods, tools and sensors, which can be used by citizens to monitor natural waters, with a strong focus on long-term data series related to environmental sciences. The new sensors, based on optical technologies, respond to a number of scientific, technical and societal objectives, ranging from more precise monitoring of key environmental descriptors of the aquatic environment (water colour, transparency and fluorescence) to an improved management of data collected with citizen participation. The sensors were tested, calibrated, integrated on several platforms, scientifically validated and demonstrated in the field. The new methods and tools were tested in a citizen-science context. The general conclusion is that citizens are valuable contributors in quality and quantity to the objective of collecting, integrating and analysing fragmented and diverse environmental data. An integration of these data into data-analysis tools has a large potential to support authoritative monitoring and decision-making. In this paper, the project's objectives, results, technical achievements and lessons learned are presented.

A rapid technique for classifying phytoplankton fluorescence spectra based on self-organizing maps.

Fluorescence spectroscopy has been demonstrated to be a powerful tool for characterizing phytoplankton communities in marine environments. Using different fluorescence spectra techniques, it is now possible to discriminate the major phytoplankton groups. However, most of the current techniques are based on fluorescence excitation measurements, which require stimulation at different wavelengths and thus considerable time to obtain the complete spectral profile. This requirement may be an important constraint for several mobile oceanographic platforms, such as vertical profilers or autonomous underwater vehicles, which require rapid-acquisition instruments. This paper presents a novel technique for classifying fluorescence spectra based on self-organizing maps (SOMs), one of the most popular artificial neural network (ANN) methods. The method is able to achieve phytoplankton discrimination using only fluorescence emission spectra (single wavelength excitation), thus reducing the acquisition time. The discrimination capabilities of SOM using excitation and emission spectra are compared. The analysis shows that the SOM has a good performance using excitation spectra, whereas data preprocessing is required in order to obtain similar discrimination capabilities using emission spectra. The final results obtained using emission spectra indicate that the discrimination is properly achieved even between algal groups, such as diatoms and dinoflagellates, which cannot be discriminated with previous methods. We finally point out that although techniques based on excitation spectra can achieve a better taxonomic accuracy, there are some applications that require faster acquisition processes. Acquiring emission spectra is almost instantaneous, and techniques such as SOM can achieve good classification performance using appropriately preprocessed data.

Towards Cost-Effective Operational Monitoring Systems for Complex Waters: Analyzing Small-Scale Coastal Processes with Optical Transmissometry.

The detection and prediction of changes in coastal ecosystems require a better understanding of the complex physical, chemical and biological interactions, which involves that observations should be performed continuously. For this reason, there is an increasing demand for small, simple and cost-effective in situ sensors to analyze complex coastal waters at a broad range of scales. In this context, this study seeks to explore the potential of beam attenuation spectra, c(λ), measured in situ with an advanced-technology optical transmissometer, for assessing temporal and spatial patterns in the complex estuarine waters of Alfacs Bay (NW Mediterranean) as a test site. In particular, the information contained in the spectral beam attenuation coefficient was assessed and linked with different biogeochemical variables. The attenuation at λ = 710 nm was used as a proxy for particle concentration, TSM, whereas a novel parameter was adopted as an optical indicator for chlorophyll a (Chl-a) concentration, based on the local maximum of c(λ) observed at the long-wavelength side of the red band Chl-a absorption peak. In addition, since coloured dissolved organic matter (CDOM) has an important influence on the beam attenuation spectral shape and complementary measurements of particle size distribution were available, the beam attenuation spectral slope was used to analyze the CDOM content. Results were successfully compared with optical and biogeochemical variables from laboratory analysis of collocated water samples, and statistically significant correlations were found between the attenuation proxies and the biogeochemical variables TSM, Chl-a and CDOM. This outcome depicted the potential of high-frequency beam attenuation measurements as a simple, continuous and cost-effective approach for rapid detection of changes and patterns in biogeochemical properties in complex coastal environments.

Spatial and temporal land cover changes in Terminos Lagoon Reserve, Mexico

Terminos Lagoon ecosystem is the largest fluvial-lagoon estuarine system in the country and one of the most important reserves of coastal flora and fauna in Mexico. Since the seventies, part of the main infrastructure for country’s oil extraction is located in this area. Its high biodiversity has motivated different type of studies including deforestation processes and land use planning. In this work we used satellite image analysis to determine land cover changes in the area from 1974 to 2001. Our results indicate that tropical forest and mangroves presented the most extensive losses in its coverage. In contrast, urban areas and induced grassland increased considerably. In 2001 more than half of the ecosystem area showed changes from its original land cover, and a third part of it was deteriorated. The main causes of deforestation were both the increase in grassland and the growth of urban areas. However, deforestation was attenuated by natural reforestation and plant canopy recovery. We conclude that the introduction of cattle and urban development were the main causes for the land cover changes; however, the oil industry activity located in the ecosystem, has promoted indirectly to urban growth and rancher boom. Rev. Biol. Trop. 58 (2): 565-575. Epub 2010 June 02.

El ecosistema de Laguna de Términos es el más grande sistema fluvio lagunar estuarino del país y una de las reservas más importantes de flora y fauna costera en México. Desde la década de los setentas, parte de la infraestructura necesaria para la explotación del petróleo en el país se encuentra localizada en esta área. Su importante biodiversidad ha motivado diferentes estudios en el área que incluyen procesos de deforestación y ordenamiento del territorio. Se realizó un análisis de imágenes de satélite para determinar los cambios de uso del suelo y vegetación en el área entre 1974 y 2001. Los resultados indican que la selva tropical y el mangle presentan las mayores pérdidas de cobertura. En contraste, las áreas urbanas y los pastos inducidos han incrementado considerablemente su extensión. En el año 2001 más de la mitad del área ocupada por el ecosistema mostró cambios en sus coberturas originales y una tercera parte estaba deteriorada. La deforestación fue causada principalmente por el incremento de los pastizales y el crecimiento de las áreas urbanas. Sin embargo, estas pérdidas fueron atenuadas por la regeneración natural. Se concluye que la introducción de pasto para la ganadería y el desarrollo urbano fueron las principales causas de los cambios de uso de suelo, sin embargo, la industria petrolera asentada en el ecosistema ha fomentado indirectamente el crecimiento urbano y el auge ganadero.