Monitoring animal behaviour and environmental interactions : GPS collars and satellite remote sensing within a satellite remote sensing context

Remote monitoring of animal behaviour in the environment can assist in managing both the animal and its environmental impact. GPS collars which record animal locations with high temporal frequency allow researchers to monitor both animal behaviour and interactions with the environment. These ground-based sensors can be combined with remotely-sensed satellite images to understand animal-landscape interactions. The key to combining these technologies is communication methods such as wireless sensor networks (WSNs). We explore this concept using a case-study from an extensive cattle enterprise in northern Australia and demonstrate the potential for combining GPS collars and satellite images in a WSN to monitor behavioural preferences and social behaviour of cattle.

Monitoring animal behaviour and environmental interactions using wireless sensor networks, GPS collars and satellite remote sensing

Remote monitoring of animal behaviour in the environment can assist in managing both the animal and its environmental impact. GPS collars which record animal locations with high temporal frequency allow researchers to monitor both animal behaviour and interactions with the environment. These ground-based sensors can be combined with remotely-sensed satellite images to understand animal-landscape interactions. The key to combining these technologies is communication methods such as wireless sensor networks (WSNs). We explore this concept using a case-study from an extensive cattle enterprise in northern Australia and demonstrate the potential for combining GPS collars and satellite images in a WSN to monitor behavioural preferences and social behaviour of cattle.

Impact of temperature on childhood pneumonia estimated from satellite remote sensing

The effect of temperature on childhood pneumonia in subtropical regions is largely unknown so far. This study examined the impact of temperature on childhood pneumonia in Brisbane, Australia. A quasi-Poisson generalized linear model combined with a distributed lag non linear model was used to quantify the main effect of temperature on emergency department visits (EDVs) for childhood pneumonia in Brisbane from 2001 to 2010. The model residuals were checked to identify added effects due to heat waves or cold spells. Both high and low temperatures were associated with an increase in EDVs for childhood pneumonia. Children aged 2–5 years, and female children were particularly vulnerable to the impacts of heat and cold, and Indigenous children were sensitive to heat. Heat waves and cold spells had significant added effects on childhood pneumonia, and the magnitude of these effects increased with intensity and duration. There were changes over time in both the main and added effects of temperature on childhood pneumonia. Children, especially those female and Indigenous, should be particularly protected from extreme temperatures. Future development of early warning systems should take the change over time in the impact of temperature on children’s health into account.

An oceanographic characterizations of the Olympic Coast National Marine Sanctuary and Pacific Northwest: interpretive summary of ocean climate and regional processes through satellite remote sensing

This report presents the results of a two-year investigation and summary of oceanographic satellite data obtained from multiple operational data providers and sources, spanning years of operational data collection. Long-term summaries of Sea Surface Temperature (SST) and SST fronts, Sea Surface Height Anomalies (SSHA), surface currents, ocean color chlorophyll and turbidity, and winds are provided. Merged satellite oceanographic data revealed information on: (1) seasonal cycles and timing of transition periods; (2) linkages between seasonal effects (warming and cooling), upwelling processes and transport; and (3) nutrient/sediment sources, sinks, and physical limiting factors controlling surface response for Olympic Coast marine environments. These data and information can be used for building relevant hind cast models, ecological forecasts, and regional environmental indices (e.g. upwelling, climate, “hot spot”) on biological distribution and/or response in the PNW.

Fishery dynamics of the California market squid (Loligo opalescens), as measured by satellite remote sensing

Novel data on the spatial and temporal distribution of fishing effort and population abundance are presented for the market squid fishery (Loligo opalescens) in the Southern California Bight, 1992−2000. Fishing effort was measured by the detection of boat lights by the Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS). Visual confirmation of fishing vessels by nocturnal aerial surveys indicated that lights detected by satellites are reliable indicators of fishing effort. Overall, fishing activity was concentrated off the following Channel Islands: Santa Rosa, Santa Cruz, Anacapa, and Santa Catalina. Fishing activity occurred at depths of 100 m or less. Landings, effort, and squid abundance (measured as landings per unit of effort, LPUE) markedly declined during the 1997−98 El Niño; landings and LPUE increased afterwards. Within a fishing season, the location of fishing activity shifted from the northern shores of Santa Rosa and Santa Cruz Islands in October, the typical starting date for squid fishing in the Bight, to the southern shores by March, the typical end of the squid season. Light detection by satellites offers a source of fine-scale spatial and temporal data on fishing effort for the market squid fishery off California, and these data can be integrated with environmental data and fishing logbook data in the development of a management plan.

SATELLITE REMOTE-SENSING PREDICTION OF JAPANESE PILCHARD FISHING GROUND IN THE HUANGHAI SEA AND THE EAST-CHINA-SEA

The thermophily, fishing season and central fishing ground of Japanese pilchard (Sardinops melanosticta) were studied by using satellite remote sensing (SRS) and other methods in Haizhou Bay and Tsushima waters during 1986-1990. A rapid prediction method of fishing ground is presented. Moreover, the results indicated that the thermophilic values of the fish stock are 11-20 degrees C and both fishing grounds are in increasing temperature process from the beginning to the end of the fishing period. The Japanese pilchards gather vigorously at the sea surface temperature of 15-17 degrees C. The water temperature is a key factor affecting the fishing season and the catch of the fishing ground. The increasing temperature process restricts the fishing season development and central fishing ground formation. The accuracy of 15 predictions made in the Haizhou Bay fishing ground is up to 91.3%, and 37 predictions made in the Tsushima, fishing ground shorten the fish detection time by 13.4% - 22% on the average.

An intercomparison of bio-optical techniques for detecting dominant phytoplankton size class from satellite remote sensing

Satellite remote sensing of ocean colour is the only method currently available for synoptically measuring wide-area properties of ocean ecosystems, such as phytoplankton chlorophyll biomass. Recently, a variety of bio-optical and ecological methods have been established that use satellite data to identify and differentiate between either phytoplankton functional types (PFTs) or phytoplankton size classes (PSCs). In this study, several of these techniques were evaluated against in situ observations to determine their ability to detect dominant phytoplankton size classes (micro-, nano- and picoplankton). The techniques are applied to a 10-year ocean-colour data series from the SeaWiFS satellite sensor and compared with in situ data (6504 samples) from a variety of locations in the global ocean. Results show that spectral-response, ecological and abundance-based approaches can all perform with similar accuracy. Detection of microplankton and picoplankton were generally better than detection of nanoplankton. Abundance-based approaches were shown to provide better spatial retrieval of PSCs. Individual model performance varied according to PSC, input satellite data sources and in situ validation data types. Uncertainty in the comparison procedure and data sources was considered. Improved availability of in situ observations would aid ongoing research in this field.

Macroscale factors affecting diatom abundance: a synergistic use of Continuous Plankton Recorder and satellite remote sensing data

Diatoms exist in almost every aquatic regime; they are responsible for 20% of global carbon fixation and 25% of global primary production, and are regarded as a key food for copepods, which are subsequently consumed by larger predators such as fish and marine mammals. A decreasing abundance and a vulnerability to climatic change in the North Atlantic Ocean have been reported in the literature. In the present work, a data matrix composed of concurrent satellite remote sensing and Continuous Plankton Recorder (CPR) in situ measurements was collated for the same spatial and temporal coverage in the Northeast Atlantic. Artificial neural networks (ANNs) were applied to recognize and learn the complex non-monotonic and non-linear relationships between diatom abundance and spatiotemporal environmental factors. Because of their ability to mimic non-linear systems, ANNs proved far more effective in modelling the diatom distribution in the marine ecosystem. The results of this study reveal that diatoms have a regular seasonal cycle, with their abundance most strongly influenced by sea surface temperature (SST) and light intensity. The models indicate that extreme positive SSTs decrease diatom abundances regardless of other climatic conditions. These results provide information on the ecology of diatoms that may advance our understanding of the potential response of diatoms to climatic change.

Progress in satellite remote sensing for studying physical processes at the ocean surface and its borders with the atmosphere and sea-ice

Physical oceanography is the study of physical conditions, processes and variables within the ocean, including temperature-salinity distributions, mixing of the water column, waves, tides, currents, and air-sea interaction processes. Here we provide a critical review of how satellite sensors are being used to study physical oceanography processes at the ocean surface and its borders with the atmosphere and sea-ice. The paper begins by describing the main sensor types that are used to observe the oceans (visible, thermal infrared and microwave) and the specific observations that each of these sensor types can provide. We then present a critical review of how these sensors and observations are being used to study i) ocean surface currents, ii) storm surges, iii) sea-ice, iv) atmosphere-ocean gas exchange and v) surface heat fluxes via phytoplankton. Exciting advances include the use of multiple sensors in synergy to observe temporally varying Arctic sea-ice volume, atmosphere- ocean gas fluxes, and the potential for 4 dimensional water circulation observations. For each of these applications we explain their relevance to society, review recent advances and capability, and provide a forward look at future prospects and opportunities. We then more generally discuss future opportunities for oceanography-focussed remote-sensing, which includes the unique European Union Copernicus programme, the potential of the International Space Station and commercial miniature satellites. The increasing availability of global satellite remote-sensing observations means that we are now entering an exciting period for oceanography. The easy access to these high quality data and the continued development of novel platforms is likely to drive further advances in remote sensing of the ocean and atmospheric systems.

Modelling the time-evolution of phytoplankton size spectra from satellite remote sensing

A dynamic size-structured model is developed for phytoplankton and nutrients in the oceanic mixed layer and applied to extract phytoplankton biomass at discrete size fractions from remotely sensed, ocean-colour data. General relationships between cell size and biophysical processes (such as sinking, grazing, and primary production) of phytoplankton were included in the model through a bottom–up approach. Time-dependent, mixed-layer depth was used as a forcing variable, and a sequential data-assimilation scheme was implemented to derive model trajectories. From a given time-series, the method produces estimates of size-structured biomass at every observation, so estimates seasonal succession of individual phytoplankton size, derived here from remote sensing for the first time. From these estimates, normalized phytoplankton biomass size spectra over a period of 9 years were calculated for one location in the North Atlantic. Further analysis demonstrated that strong relationships exist between the seasonal trends of the estimated size spectra and the mixed-layer depth, nutrient biomass, and total chlorophyll. The results contain useful information on the time-dependent biomass flux in the pelagic ecosystem.