Applications of Satellite Ocean Color Sensors for Monitoring and Predicting Harmful Algal Blooms

The new satellite ocean color sensors offer a means of detecting and monitoring algal blooms in the ocean and coastal zone. Beginning with SeaWiFS (Sea Wide Field-of-view Sensor) in September 1997, these sensors provide coverage every 1 to 2 days with 1-km pixel view at nadir. Atmospheric correction algorithms designed for the coastal zone combined with regional chlorophyll algorithms can provide good and reproducible estimates of chlorophyll, providing the means of monitoring various algal blooms. Harmful algal blooms (HABs) caused by Karenia brevis in the Gulf of Mexico are particularly amenable to remote observation. The Gulf of Mexico has relatively clear water and K. brevis, in bloom conditions, tends to produce a major portion of the phytoplankton biomass. A monitoring program has begun in the Gulf of Mexico that integrates field data from state monitoring programs with satellite imagery, providing an improved capability for the monitoring of K. brevis blooms.     

Remote sampling of harmful algal blooms: A case study on the Washington State coast

Strategic placement of moorings as an integrated element of ocean observing systems will be essential in the effective monitoring of harmful algal blooms that impact the sustainability of seafood harvest as well as human and marine animal health. Recent efforts have focused on in situ collection and analysis of biological samples, an arguably more difficult task than the measurement of chemical and physical parameters that has been automated for many years. Remote sampling and preservation of samples for later analysis can fill a gap that will allow analysis of time-series data that are essential for establishing interannual trends in coastal regions and provide timely warning of approaching harmful algal blooms. In addition, stored samples for subsequent laboratory analysis will provide important control samples needed to validate in situ, robotic analysis of biological samples. This monitoring for harmful algae and their toxins on moorings, gliders and other autonomous platforms as part of ocean observing systems requires consideration of sampling locations as well other factors such as preservative type used for sample collection and storage combined with a compatible method for toxin analysis. To that end, Pseudo-nitzschia abundance and domoic acid concentrations in seawater were measured from samples collected with a remote sampler moored in Willapa Bay, Washington, during the spring and summer from 2002 through 2006, and compared to data from two adjacent beach sites, Twin Harbors Beach and Long Beach, by Olympic Region Harmful Algal Bloom (ORHAB) personnel. Using enzyme-linked immunosorbent assay (ELISA), total toxin measurements in formalin-preserved whole water samples from Willapa Bay were shown to correlate well with changes in particulate domoic acid concentrations in filtered (particulate) seawater samples from adjacent beaches. A series of experiments confirm, for the first time, that formalin, but not Lugol's iodine or glutaraldehyde, is an effective preservative for phytoplankton samples that are stored for later analysis of domoic acid by ELISA. Together, these data confirm that placement of moorings for in situ sampling of biological and environmental parameters in the sheltered environment of Willapa Bay can accurately detect the arrival of harmful algal blooms that originate from offshore hotspots to shellfish harvesting beaches.     

IMOS National Reference Stations: A Continental-Wide Physical,Chemical and Biological Coastal Observing System

Sustained observations allow for the tracking of change in oceanography and ecosystems, however, these are rare, particularly for the Southern Hemisphere. To address this in part, the Australian Integrated Marine Observing System (IMOS) implemented a network of nine National Reference Stations (NRS). The network builds on one long-term location, where monthly water sampling has been sustained since the 1940s and two others that commenced in the 1950s. In-situ continuously moored sensors and an enhanced monthly water sampling regime now collect more than 50 data streams. Building on sampling for temperature, salinity and nutrients, the network now observes dissolved oxygen, carbon, turbidity, currents, chlorophyll a and both phytoplankton and zooplankton. Additional parameters for studies of ocean acidification and bio-optics are collected at a sub-set of sites and all data is made freely and publically available. Our preliminary results demonstrate increased utility to observe extreme events, such as marine heat waves and coastal flooding; rare events, such as plankton blooms; and have, for the first time, allowed for consistent continental scale sampling and analysis of coastal zooplankton and phytoplankton communities. Independent water sampling allows for cross validation of the deployed sensors for quality control of data that now continuously tracks daily, seasonal and annual variation. The NRS will provide multi-decadal time series, against which more spatially replicated short-term studies can be referenced, models and remote sensing products validated, and improvements made to our understanding of how large-scale, long-term change and variability in the global ocean are affecting Australia''s coastal seas and ecosystems. The NRS network provides an example of how a continental scaled observing systems can be developed to collect observations that integrate across physics, chemistry and biology.     

无人机在生物多样性遥感监测中的应用现状与展望

近十年, 无人机平台由于其灵活机动、成本低等优势在植被生态调查、资源环境监测、生物多样性保护等领域逐渐兴起。本文从生物多样性遥感监测应用角度首先介绍了无人机分类系统, 为具体工作开展过程中如何选择合适的载体和传感器提供了参考; 继而总结了不同类型无人机的适用性及其可搭载传感器的用途与区别。在此基础上, 针对无人机平台的高精度遥感信息具体应用案例, 就反映生物多样性变化并揭示其驱动机制方面的无人机遥感直接和间接指标的相关研究进展展开阐述。最后, 就目前无人机遥感技术在生物多样性监测领域的应用中存在的限制, 如软硬件结合匹配程度不够、部分设备过于昂贵、法律法规不完善、与传统生物多样性监测手段结合较弱等问题进行探讨。我们认为: 无人机遥感技术可以很好地弥补地面监测与航天、卫星遥感之间的尺度空缺, 更好地将监测点上的结果以准确、可靠的推绎方法扩展到区域尺度供决策分析使用。今后迫切需要进一步加大生物多样性近地面遥感监测项目建设的实施力度, 从整体上提高生物多样性热点区域应对变化的分析预警能力。     

海洋赤潮水色遥感技术研究进展

海洋水色遥感已成为赤潮探测与监测的重要技术手段之一。文章回顾了赤潮卫星遥感技术的发展历程,阐述了水色遥感的原理--水体的离水辐射及其光谱特征。着重论述了高光谱卫星在赤潮水色遥感中的作用,通过大气校正减少大气和气溶胶对遥感信息的衰减,同时就赤潮发生的海洋学机理进行了探讨。综合分析后指出中分辨率成像光谱辐射计(MODIS)作为图谱合一的新一代卫星传感器将在赤潮的卫星监测研究中发挥及其重要的作用。并对今后赤潮遥感的主攻方向提出了一些建议:拓宽遥感数据来源,与地理信息系统技术结合及加强赤潮的预警研究等。     

Sensing the sea

The development of the 'ecosystem approach' to the management of marine systems is leading to a requirement for data to be collected with greater frequency and spatial resolution than has been necessary in the past. This is being met both by the analysis of more samples (to better describe variability and temporal change) and by the deployment of instrumented platforms that gather data over long time periods. To meet these requirements in the hostile conditions at sea, a range of sensors based on physical, chemical and biological responses is being developed. These sensors have applications in laboratory analysis of collected samples, during field studies and directly in situ at remote sites for real-time observations of environmental trends. Here, we consider the role that biosensors could have in future marine monitoring programmes.     

A large and prolonged bloom of Karenia mikimotoi in Scottish waters in 2006

A prolonged bloom of Karenia mikimotoi was observed during 2006 in Scottish waters. This bloom is thought to be unique in the region in terms of its large spatial extent. From its first detection in the west of the country, the bloom moved clockwise around the coast eventually reaching the east coast and the Shetland Isles to the north. The bloom resulted in extensive mortalities of benthic organisms including annelids and molluscs and some species of fish. Farmed fish mortalities were absent but gill damage was reported. The availability of satellite remote sensing, phytoplankton counts from multiple sites, meteorological data and some water chemistry, as well as information on the physical characteristics of the sampling sites, provided an extensive spatial and temporal data set. Analysis of remotely sensed chlorophyll-a data from Aqua-MODIS indicated that this parameter is a useful early warning indicator of K. mikimotoi in shelf waters off the Scottish west coast, and suggested that the bloom developed in this region prior to its advection to coastal waters. An earth observation (EO) based harmful bloom classifier for K. mikimotoi recognised areas of elevated K. mikimotoi cell density but generated false positives in areas of high reflectance. Data were also used to evaluate, in Scottish waters, various hypotheses that exist to explain the formation of K. mikimotoi blooms including phototaxis, nutrient availability, cell transport and elevated water temperature. Specifically, we sought to evaluate if routinely collected environmental data (water temperature, insolation, wind strength and direction, and sea-loch aspect) could be used as a predictor of bloom magnitude near aquaculture facility locations, which typically lie within fjordic sea lochs. Path analysis was used to derive intuitive models linking environmental drivers to bloom magnitude. Once the effects of latitude such as northward water cooling were taken into account, only rainfall was a significant predictor of bloom magnitude at the sampling sites. Therefore, while the offshore development and progression of a bloom may be predicted from satellite information, it is likely that local hydrodynamic influences are crucial in determining its magnitude at coastal aquaculture sites.     

Improved monitoring of HABs using autonomous underwater vehicles (AUV)

Blooms of toxic algae are increasing in magnitude and frequency around the globe, causing extensive economic and environmental impacts. On the west coast of Florida, blooms of the toxic dinoflagellate Karenia brevis (Davis) have been documented annually for the last 30 years causing respiratory irritation in humans, fish kills, and toxin bioaccumulation in shellfish beds. As a result, methods need to be established to monitor and predict bloom formation and transport to mitigate their harmful effects on the surrounding ecosystems and local communities. In the past, monitoring and mitigation efforts have relied on visual confirmation of water discoloration, fish kills, and laborious cell counts, but recently satellite remote sensing has been used to track harmful algal blooms (HABs) along the Florida coast. Unfortunately satellite ocean color is limited by cloud cover, lack of detection below one optical depth, and revisit frequency, all of which can lead to extended periods without data. To address these shortcomings, an optical phytoplankton discriminator (OPD) was developed to detect K. brevis cells in mixed phytoplankton assemblages. The OPD was integrated into autonomous underwater vehicle (AUV) platforms to gather spatially and temporally relevant data that can be used in collaboration with satellite imagery to provide a 3D picture of bloom dynamics over time. In January 2005, a Remote Environmental Monitoring UnitS (REMUS) AUV with an OPD payload was deployed on the west coast of Florida to retrieve a similarity index (SI), which indicates when K. brevis dominates the phytoplankton community. SI was used to monitor a K. brevis bloom in relation to temperature, salinity, chlorophyll, and ocean currents. Current speed, SI, temperature, salinity, and chlorophyll a from the AUV were used to quantify a 1 km displacement of the K. brevis bloom front that was observed over the deployment period. The ability to monitor short term bloom movement will improve monitoring and predictive efforts that are used to provide warnings for local tourism and fishing industries. In addition, understanding the fine scale environmental conditions associated with bloom formation will increase our ability to predict the location and timing of K. brevis bloom formation. This study demonstrates the use of one autonomous platform and provides evidence that a nested array of AUVs and moorings equipped with new sensors, combined with remote sensing, can provide an early warning and monitoring system to reduce the impact of HABs.     

A coordinated coastal ocean observing and modeling system for the West Florida Continental Shelf

The evolution of harmful algal blooms, while dependent upon complex biological interactions, is equally dependent upon the ocean circulation since the circulation provides the basis for the biological interactions by uniting nutrients with light and distributing water properties. For the coastal ocean, the circulation and the resultant water properties, in turn, depend on interactions between both the continental shelf and the deep-ocean and the continental shelf and the estuaries since the deep-ocean and the estuaries are primary nutrient sources. Here we consider a coordinated program of observations and models for the West Florida Continental Shelf (WFS) intended to provide a supportive framework for K. brevis red-tide prediction as well as for other coastal ocean matters of societal concern. Predicated on lessons learned, the goal is to achieve a system complete enough to support data assimilative modeling and prediction. Examples of the observations and models are presented and application is made to aspects of the 2005 red-tide. From an observational perspective, no single set of measurements is adequate. Required are a broad mix of sensors and sensor delivery systems capable of describing the three-dimensional structure of the velocity and density fields. Similarly, models must be complete enough to include the relevant physical processes, and data assimilation provides the integrative framework for maximizing the joint utility of the observations and models. While we are still in the exploratory stages of development, the lessons learned and application examples may be useful to similar programs under development elsewhere. One scientific finding is that the key to understanding K. brevis red-tide on the WFS lies not at the surface, but at depth.     

OPTICAL MONITORING AND FORECASTING SYSTEMS FOR HARMFUL ALGAL BLOOMS: POSSIBILITY OR PIPE DREAM?

Monitoring programs for harmful algal blooms (HABs) are currently reactive and provide little or no means for advance warning. Given this, the development of algal forecasting systems would be of great use because they could guide traditional monitoring programs and provide a proactive means for responding to HABs. Forecasting systems will require near real-time observational capabilities and hydrodynamic/biological models designed to run in the forecast mode. These observational networks must detect and forecast over ecologically relevant spatial/ temporal scales. One solution is to incorporate a multiplatform optical approach utilizing remote sensing and in situ moored technologies. Recent advances in instrumentation and data-assimilative modeling may provide the components necessary for building an algal forecasting system. This review will outline the utility and hurdles of optical approaches in HAB detection and monitoring. In all the approaches, the desired HAB information must be isolated and extracted from the measured bulk optical signals. Examples of strengths and weaknesses of the current approaches to deconvolve the bulk optical properties are illustrated. After the phytoplankton signal has been isolated, species-recognition algorithms will be required, and we demonstrate one approach developed for Gymnodinium breve Davis. Pattern-recognition algorithms will be species-specific, reflecting the acclimation state of the HAB species of interest.Field data will provide inputs to optically based ecosystem models, which are fused to the observational networks through data-assimilation methods. Potential model structure and data-assimilation methods are reviewed.     

Comparative Analysis of Three Brevetoxin-Associated Bottlenose Dolphin (Tursiops truncatus) Mortality Events in the Florida Panhandle Region (USA)

In the Florida Panhandle region, bottlenose dolphins (Tursiops truncatus) have been highly susceptible to large-scale unusual mortality events (UMEs) that may have been the result of exposure to blooms of the dinoflagellate Karenia brevis and its neurotoxin, brevetoxin (PbTx). Between 1999 and 2006, three bottlenose dolphin UMEs occurred in the Florida Panhandle region. The primary objective of this study was to determine if these mortality events were due to brevetoxicosis. Analysis of over 850 samples from 105 bottlenose dolphins and associated prey items were analyzed for algal toxins and have provided details on tissue distribution, pathways of trophic transfer, and spatial-temporal trends for each mortality event. In 1999/2000, 152 dolphins died following extensive K. brevis blooms and brevetoxin was detected in 52% of animals tested at concentrations up to 500 ng/g. In 2004, 105 bottlenose dolphins died in the absence of an identifiable K. brevis bloom; however, 100% of the tested animals were positive for brevetoxin at concentrations up to 29,126 ng/mL. Dolphin stomach contents frequently consisted of brevetoxin-contaminated menhaden. In addition, another potentially toxigenic algal species, Pseudo-nitzschia, was present and low levels of the neurotoxin domoic acid (DA) were detected in nearly all tested animals (89%). In 2005/2006, 90 bottlenose dolphins died that were initially coincident with high densities of K. brevis. Most (93%) of the tested animals were positive for brevetoxin at concentrations up to 2,724 ng/mL. No DA was detected in these animals despite the presence of an intense DA-producing Pseudo-nitzschia bloom. In contrast to the absence or very low levels of brevetoxins measured in live dolphins, and those stranding in the absence of a K. brevis bloom, these data, taken together with the absence of any other obvious pathology, provide strong evidence that brevetoxin was the causative agent involved in these bottlenose dolphin mortality events.     

Detection of Karenia brevis blooms on the west Florida shelf using in situ backscattering and fluorescence data

Using shipboard data collected from the central west Florida shelf (WFS) between 2000 and 2001, an optical classification algorithm was developed to differentiate toxic Karenia brevis blooms (>10⁴ cells l⁻¹) from other waters (including non-blooms and blooms of other phytoplankton species). The identification of K. brevis blooms is based on two criteria: (1) chlorophyll a concentration ≥1.5 mg m⁻³ and (2) chlorophyll-specific particulate backscattering at 550 nm ≤ 0.0045 m² mg⁻¹. The classification criteria yielded an overall accuracy of 99% in identifying both K. brevis blooms and other waters from 194 cruise stations. The algorithm was validated using an independent dataset collected from both the central and south WFS between 2005 and 2006. After excluding data from estuarine and post-hurricane turbid waters, an overall accuracy of 94% was achieved with 86% of all K. brevis bloom data points identified successfully. Satisfactory algorithm performance (88% overall accuracy) was also achieved when using underway chlorophyll fluorescence and backscattering data collected during a repeated alongshore transect between Tampa Bay and Florida Bay in 2005 and 2006. These results suggest that it may be possible to use presently available, commercial optical backscattering instrumentation on autonomous platforms (e.g. moorings, gliders, and AUVs) for rapid and timely detection and monitoring of K. brevis blooms on the WFS.     

Neurological illnesses associated with Florida red tide (Karenia brevis) blooms

Human respiratory and gastrointestinal illnesses can result from exposures to brevetoxins originating from coastal Florida red tide blooms, comprising the marine alga Karenia brevis (K. brevis). Only limited research on the extent of human health risks and illness costs due to K. brevis blooms has been undertaken to date. Because brevetoxins are known neurotoxins that are able to cross the blood-brain barrier, it is possible that exposure to brevetoxins may be associated with neurological illnesses. This study explored whether K. brevis blooms may be associated with increases in the numbers of emergency department visits for neurological illness. An exposure-response framework was applied to test the effects of K. brevis blooms on human health, using secondary data from diverse sources. After controlling for resident population, seasonal and annual effects, significant increases in emergency department visits were found specifically for headache (ICD-9 784.0) as a primary diagnosis during proximate coastal K. brevis blooms. In particular, an increased risk for older residents (≥55 years) was identified in the coastal communities of six southwest Florida counties during K. brevis bloom events. The incidence of headache associated with K. brevis blooms showed a small but increasing association with K. brevis cell densities. Rough estimates of the costs of this illness were developed for hypothetical bloom occurrences.     

Potential response to climate change of a semi-arid coastal ecosystem in eastern Mediterranean

Eastern Mediterranean gulfs, adjacent to small semi-arid watersheds are particularly susceptible to climate changes. In this study, an analysis was performed for air temperature and rainfall during 1955–2010 over a coastal ecosystem in NE Aegean, and potential effects of recent changes on the physical setting and ecological status of the marine system were studied. A trend toward drier conditions was revealed, and in order to assess possible effects on the surrounding basin, a watershed model was applied. In addition, the hydrology and ecology of the marine ecosystem were studied using a water budget model along with available field data. Based on local climatological data, dryness may lead to a decrease of one to two orders of magnitude in the amount of runoff during a dry annual cycle, resulting to a fivefold increase in the residence time of the marine system. High residence time associated with terrestrial nutrient inputs and strong stratification result to phytoplankton blooms during winter, including harmful algal blooms. Integrated approaches, modeling both the hydrology and ecology of watersheds and adjacent water bodies, are essential toward forecasting, understanding and management of potential alterations in functioning of coastal ecosystems due to recent climate changes.     

On the Potential of Surfers to Monitor Environmental Indicators in the Coastal Zone

The social and economic benefits of the coastal zone make it one of the most treasured environments on our planet. Yet it is vulnerable to increasing anthropogenic pressure and climate change. Coastal management aims to mitigate these pressures while augmenting the socio-economic benefits the coastal region has to offer. However, coastal management is challenged by inadequate sampling of key environmental indicators, partly due to issues relating to cost of data collection. Here, we investigate the use of recreational surfers as platforms to improve sampling coverage of environmental indicators in the coastal zone. We equipped a recreational surfer, based in the south west United Kingdom (UK), with a temperature sensor and Global Positioning System (GPS) device that they used when surfing for a period of one year (85 surfing sessions). The temperature sensor was used to derive estimates of sea-surface temperature (SST), an important environmental indicator, and the GPS device used to provide sample location and to extract information on surfer performance. SST data acquired by the surfer were compared with data from an oceanographic station in the south west UK and with satellite observations. Our results demonstrate: (i) high-quality SST data can be acquired by surfers using low cost sensors; and (ii) GPS data can provide information on surfing performance that may help motivate data collection by surfers. Using recent estimates of the UK surfing population, and frequency of surfer participation, we speculate around 40 million measurements on environmental indicators per year could be acquired at the UK coastline by surfers. This quantity of data is likely to enhance coastal monitoring and aid UK coastal management. Considering surfing is a world-wide sport, our results have global implications and the approach could be expanded to other popular marine recreational activities for coastal monitoring of environmental indicators.     

Satellite remote sensing of harmful algal blooms: A new multi-algorithm method for detecting the Florida Red Tide (Karenia brevis)

In a continuing effort to develop suitable methods for the surveillance of Harmful Algal Blooms (HABs) of Karenia brevis using satellite radiometers, a new multi-algorithm method was developed to explore whether improvements in the remote sensing detection of the Florida Red Tide was possible. A Hybrid Scheme was introduced that sequentially applies the optimized versions of two pre-existing satellite-based algorithms: an Empirical Approach (using water-leaving radiance as a function of chlorophyll concentration) and a Bio-optical Technique (using particulate backscatter along with chlorophyll concentration). The long-term evaluation of the new multi-algorithm method was performed using a multi-year MODIS dataset (2002 to 2006; during the boreal Summer-Fall periods - July to December) along the Central West Florida Shelf between 25.75°N and 28.25°N. Algorithm validation was done with in situ measurements of the abundances of K. brevis; cell counts ≥1.5×10(4) cells l(-1) defined a detectable HAB. Encouraging statistical results were derived when either or both algorithms correctly flagged known samples. The majority of the valid match-ups were correctly identified (~80% of both HABs and non-blooming conditions) and few false negatives or false positives were produced (~20% of each). Additionally, most of the HAB-positive identifications in the satellite data were indeed HAB samples (positive predictive value: ~70%) and those classified as HAB-negative were almost all non-bloom cases (negative predictive value: ~86%). These results demonstrate an excellent detection capability, on average ~10% more accurate than the individual algorithms used separately. Thus, the new Hybrid Scheme could become a powerful tool for environmental monitoring of K. brevis blooms, with valuable consequences including leading to the more rapid and efficient use of ships to make in situ measurements of HABs.     

Online forecasting chlorophyll a concentrations by an auto-regressive integrated moving average model: Feasibilities and potentials

Algal blooms are commonly observed in freshwater and coastal areas, causing significant damage to drinking water and aquaculture production. Predictive models are effective for algal bloom forecasting and management. In this paper, an auto-regressive integrated moving average (ARIMA) model was developed to predict daily chlorophyll a (Chl a) concentrations, using data from Taihu Lake in China. For comparison, a multivariate linear regression (MVLR) model was also established to predict daily Chl a concentrations using the same data. Results showed that the ARIMA model generally performed better than the MVLR model with respect to the absolute error of peak value, root mean square error and index of agreement. Because the ARIMA model needs only one input variable, it shows greater applicability as an algal bloom early warning system using online sensors of Chl a.     

Compositional changes in neurotoxins and their oxidative derivatives from the dinoflagellate, Karenia brevis, in seawater and marine aerosol

The harmful alga, Karenia brevis, produces a suite of polyether neurotoxins, brevetoxins or PbTx, that cause marine animal mortality and neurotoxic shellfish poisoning (NSP). A characteristic of K. brevis blooms is associated airborne toxins that result in severe respiratory problems. This study was undertaken to determine the composition of aerosolized brevetoxins and oxidative derivatives to which beachgoers are exposed during a K. brevis bloom. The suite of brevetoxins and derivatives in seawater is comprised of intra-cellular (IC) and extra-cellular (EC) compounds. We hypothesized that aerosolized compounds are generated primarily from EC, hydrophobic compounds in seawater by bubble-mediated transport. Thus the composition of aerosolized brevetoxins and derivatives, to which beachgoers are exposed, would reflect the EC composition of the source matrix (the local surf zone). Brevetoxins were extracted from water collected along the shore and from marine aerosols along Siesta Beach and Lido Beach in Sarasota, FL, USA, during K. brevis blooms. Water samples were further processed into IC and EC components. The primary brevetoxins observed in water and air included PbTx-1, -2, -3, -PbTx-2-carboxylic acid, and brevenal. Oxidation and/or hydrolysis products of PbTx-1, -2, -3 and -7 were also found in EC water and in aerosol, but not IC.     

Beyond the benchtop and the benthos: Dataset management planning and design for time series of ocean carbonate chemistry associated with Durafet®-based pH sensors

To better understand the impact of ocean acidification on marine ecosystems, an important ongoing research priority for marine scientists is to characterize present-day pH variability. Following recent technological advances, autonomous pH sensor deployments in shallow coastal marine environments have revealed that pH dynamics in coastal oceans are more variable in space and time than the discrete, open-ocean measurements that are used for ocean acidification projections. Data from these types of deployments will benefit the research community by facilitating the improved design of ocean acidification studies as well as the identification or evaluation of natural and human-influenced pH variability. Importantly, the collection of ecologically relevant pH data and a cohesive, user-friendly integration of results across sites and regions requires (1) effective sensor operation to ensure high-quality pH data collection and (2) efficient data management for accessibility and broad reuse by the marine science community. Here, we review the best practices for deployment, calibration, and data processing and quality control, using our experience with Durafet®-based pH sensors as a model. Next, we describe information management practices for streamlining preservation and distribution of data and for cataloging different types of pH sensor data, developed in collaboration with two U.S. Long Term Ecological Research (LTER) sites. Finally, we assess sensor performance and data recovery from 73 SeaFET deployments in the Santa Barbara Channel using our quality control guidelines and data management tools, and offer recommendations for improved data yields. Our experience provides a template for other groups contemplating using SeaFET technology as well as general steps that may be helpful for the design of data management for other complex sensors.