A new approach for objective identification of turns and steps in organism movement data relevant to random walk modelling

1. A first step in the analysis of complex movement data often involves discretisation of the path into a series of step-lengths and turns, for example in the analysis of specialised random walks, such as Lévy flights. However, the identification of turning points, and therefore step-lengths, in a tortuous path is dependent on ad-hoc parameter choices. Consequently, studies testing for movement patterns in these data, such as Lévy flights, have generated debate. However, studies focusing on one-dimensional (1D) data, as in the vertical displacements of marine pelagic predators, where turning points can be identified unambiguously have provided strong support for Lévy flight movement patterns. 2. Here, we investigate how step-length distributions in 3D movement patterns would be interpreted by tags recording in 1D (i.e. depth) and demonstrate the dimensional symmetry previously shown mathematically for Lévy-flight movements. We test the veracity of this symmetry by simulating several measurement errors common in empirical datasets and find Lévy patterns and exponents to be robust to low-quality movement data. 3. We then consider exponential and composite Brownian random walks and show that these also project into 1D with sufficient symmetry to be clearly identifiable as such. 4. By extending the symmetry paradigm, we propose a new methodology for step-length identification in 2D or 3D movement data. The methodology is successfully demonstrated in a re-analysis of wandering albatross Global Positioning System (GPS) location data previously analysed using a complex methodology to determine bird-landing locations as turning points in a Lévy walk. For this high-resolution GPS data, we show that there is strong evidence for albatross foraging patterns approximated by truncated Lévy flights spanning over 3·5 orders of magnitude. 5. Our simple methodology and freely available software can be used with any 2D or 3D movement data at any scale or resolution and are robust to common empirical measurement errors. The method should find wide applicability in the field of movement ecology spanning the study of motile cells to humans.

Identifying predictable foraging habitats for a wide-ranging marine predator using ensemble ecological niche models

Aim: Ecological niche modelling can provide valuable insight into species' environmental preferences and aid the identification of key habitats for populations of conservation concern. Here, we integrate biologging, satellite remote-sensing and ensemble ecological niche models (EENMs) to identify predictable foraging habitats for a globally important population of the grey-headed albatross (GHA) Thalassarche chrysostoma. Location: Bird Island, South Georgia; Southern Atlantic Ocean. Methods: GPS and geolocation-immersion loggers were used to track at-sea movements and activity patterns of GHA over two breeding seasons (n = 55; brood-guard). Immersion frequency (landings per 10-min interval) was used to define foraging events. EENM combining Generalized Additive Models (GAM), MaxEnt, Random Forest (RF) and Boosted Regression Trees (BRT) identified the biophysical conditions characterizing the locations of foraging events, using time-matched oceanographic predictors (Sea Surface Temperature, SST; chlorophyll a, chl-a; thermal front frequency, TFreq; depth). Model performance was assessed through iterative cross-validation and extrapolative performance through cross-validation among years. Results: Predictable foraging habitats identified by EENM spanned neritic (<500 m), shelf break and oceanic waters, coinciding with a set of persistent biophysical conditions characterized by particular thermal ranges (3–8 °C, 12–13 °C), elevated primary productivity (chl-a > 0.5 mg m−3) and frequent manifestation of mesoscale thermal fronts. Our results confirm previous indications that GHA exploit enhanced foraging opportunities associated with frontal systems and objectively identify the APFZ as a region of high foraging habitat suitability. Moreover, at the spatial and temporal scales investigated here, the performance of multi-model ensembles was superior to that of single-algorithm models, and cross-validation among years indicated reasonable extrapolative performance. Main conclusions: EENM techniques are useful for integrating the predictions of several single-algorithm models, reducing potential bias and increasing confidence in predictions. Our analysis highlights the value of EENM for use with movement data in identifying at-sea habitats of wide-ranging marine predators, with clear implications for conservation and management.

Identifying predictable foraging habitats for a wide-ranging marine predator using ensemble ecological niche models

Aim: Ecological niche modelling can provide valuable insight into species' environmental preferences and aid the identification of key habitats for populations of conservation concern. Here, we integrate biologging, satellite remote-sensing and ensemble ecological niche models (EENMs) to identify predictable foraging habitats for a globally important population of the grey-headed albatross (GHA) Thalassarche chrysostoma. Location: Bird Island, South Georgia; Southern Atlantic Ocean. Methods: GPS and geolocation-immersion loggers were used to track at-sea movements and activity patterns of GHA over two breeding seasons (n = 55; brood-guard). Immersion frequency (landings per 10-min interval) was used to define foraging events. EENM combining Generalized Additive Models (GAM), MaxEnt, Random Forest (RF) and Boosted Regression Trees (BRT) identified the biophysical conditions characterizing the locations of foraging events, using time-matched oceanographic predictors (Sea Surface Temperature, SST; chlorophyll a, chl-a; thermal front frequency, TFreq; depth). Model performance was assessed through iterative cross-validation and extrapolative performance through cross-validation among years. Results: Predictable foraging habitats identified by EENM spanned neritic (<500 m), shelf break and oceanic waters, coinciding with a set of persistent biophysical conditions characterized by particular thermal ranges (3–8 °C, 12–13 °C), elevated primary productivity (chl-a > 0.5 mg m−3) and frequent manifestation of mesoscale thermal fronts. Our results confirm previous indications that GHA exploit enhanced foraging opportunities associated with frontal systems and objectively identify the APFZ as a region of high foraging habitat suitability. Moreover, at the spatial and temporal scales investigated here, the performance of multi-model ensembles was superior to that of single-algorithm models, and cross-validation among years indicated reasonable extrapolative performance. Main conclusions: EENM techniques are useful for integrating the predictions of several single-algorithm models, reducing potential bias and increasing confidence in predictions. Our analysis highlights the value of EENM for use with movement data in identifying at-sea habitats of wide-ranging marine predators, with clear implications for conservation and management.

Contribution of size fractions of planktonic algae to primary organic productivity in the coastal waters of Cochin- south west coast of lndia

This thesis entitled “Contribution of size fractions of planktonic algae to primary organic productivity in the coastal waters of cochin,south west coast of india”. Marine ecosystems planktonic algae are the most important primary producers on wliich considerable attention is being given on account of their supreme status in the marine food chain.The study of primary production in the Indian Ocean started With DANA (I928-30),, John Murray t I933-34). Discovery ( I934) and Albatross (I947-48) expeditions which tried to evaluate productivity from nutrients and standing crop of phytoplankton .The bioproductivity of the marine environment is dependent on various primary producers. ranging in size from picoplankton to larger macro phytoplankton. The quantity and quality of various size fractions of planktonic algae at any locality depend mainly on the hydrographic conditions of the area .In the coastal waters of Cochin- south west coast of lndia. Planktonic algal community is composed mainly of the diatoms, the dinoflagellates, the blue-green algae and the silicoflagellates, the former two contributing the major flora and found distributed in the all size fractions. The maximum number of species of diatoms at station 1 and station 2 was found in the pre-monsoon season.. The size groups of planktonic algae greater than 53 um are dominated by filamentous- chain forming and colonial diatoms. The coastal waters of Cochin. planktonic algae less than 53 um in size contribute significantly to primary productivity and the biodiversity of the microflora, indicating the presence of rich fishery resources in the south west coast of india.The study of different size fractions of planktonic algae and their relative contribution to the primary organic production is a useful tool for the estimation of the quantity and quality of fisheries.A deeper investigation on the occurrence of these microalgae and proper identification of their species would be of immense help for the assessment of the specificity and magnitude of fishery resources.

Chemical composition and tissue energy density of the cuttlefish (Sepia apama) and its assimilation efficiency by Diomedea albatrosses.

The cuttlefish Sepia apama Gray (Mollusca: Cephalopoda) is a seasonally abundant food resource exploited annually by moulting albatrosses throughout winter and early spring in the coastal waters of New South Wales, Australia. To assess its nutritional value as albatross forage, we analysed S. apama for water, lipid protein, ash contents, energy density and amino acid composition. Because albatrosses consistently consume S. apama parts preferentially in the order of head, viscera and mantle, we analysed these sections separately, but did not identify any nutritional basis for this selective feeding behaviour. The gross energy value of S. apama bodies was 20.9 kJ/g dry mass, but their high water content (>83%; cf <70% for fish) results in a relatively low energy density of 3.53 kJ/g. This may contribute to a need to take large meals, which subsequently degrade flight performance. Protein content was typically >75% dry mass, whereas fat content was only about 1%. Albatrosses feed on many species of cephalopods and teleost fish, and we found the amino acid composition of S. apama to be comparable to a range of species within these taxa. We used S. apama exclusively in feeding trials to estimate the energy assimilation efficiency for Diomedea albatrosses. We estimated their nitrogen-corrected apparent energy assimilation efficiency for consuming this prey to be 81.82 ± 0.72% and nitrogen retention as 2.90 ± 0.11 g N kg^-1 d^-1. Although S. apama has a high water content and relatively low energy density, its protein composition is otherwise comparable to other albatross prey species. Consequently, the large size and seasonal abundance of this prey should ensure that albatrosses remain replete and adequately nourished on this forage while undergoing moult.

Satellite telemetry suggests high levels of fishing-induced mortality in marine turtles

Long-term records of nesting numbers, or proxies to nesting numbers, show a precipitous decline in the size of many sea turtle populations. Population declines are most frequently attributed to fisheries bycatch, although direct quantification of this level of mortality is rare. We used satellite-tracking records for turtles in the Mediterranean Sea and Pacific, Atlantic and Indian Oceans to identify when turtles had been captured. Evidence for capture came from a combination of an increase in good quality locations from transmitters, transmitters moving inland to coastal towns and villages, and on-board submergence data, showing that transmitters had come out of the water. A high level of mortality was calculated, confirming current concerns regarding the outlook for sea turtles.

Charismatic marine mega-fauna: some recent discoveries and future challenges

 The last 20 years have been exciting times for scientists working with charismatic marine mega-fauna. Here recent advances are reviewed. There have been advances in both data gathering and data-analysis techniques that have allowed new insights into the physiological and behavioural ecology of free-ranging mega-faunal species; some marine mega-faunal species have now become model organisms for cutting edge approaches to identify the underlying mathematical properties of animal search patterns and hence the underlying behavioural processes (e.g. Levy flight versus Brownian motion); the implications of climate change have started to become more apparent with extended time-series of animal movements, abundance and performance; conservation issues have become integrated into marine planning and have resulted in the advent of extended networks of marine protected areas (MPAs) as well as large MPAs that span many 100,000 km2; and collaborative crossdisciplinary teams have started to reveal the importance of ocean currents in animal dispersal, the ontogeny of migration and population genetic structure. Looking to the future, increased data availability (e.g. through data sharing) will likely allow more holistic across-taxa analyses to become routine.
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