Scale-dependent foraging ecology of a marine top predator modelled using passive acoustic data

1.Understanding which environmental factors drive foraging preferences is critical for the development of effective management measures, but resource use patterns may emerge from processes that occur at different spatial and temporal scales. Direct observations of foraging are also especially challenging in marine predators, but passive acoustic techniques provide opportunities to study the behaviour of echolocating species over a range of scales. 2.We used an extensive passive acoustic data set to investigate the distribution and temporal dynamics of foraging in bottlenose dolphins using the Moray Firth (Scotland, UK). Echolocation buzzes were identified with a mixture model of detected echolocation inter-click intervals and used as a proxy of foraging activity. A robust modelling approach accounting for autocorrelation in the data was then used to evaluate which environmental factors were associated with the observed dynamics at two different spatial and temporal scales. 3.At a broad scale, foraging varied seasonally and was also affected by seabed slope and shelf-sea fronts. At a finer scale, we identified variation in seasonal use and local interactions with tidal processes. Foraging was best predicted at a daily scale, accounting for site specificity in the shape of the estimated relationships. 4.This study demonstrates how passive acoustic data can be used to understand foraging ecology in echolocating species and provides a robust analytical procedure for describing spatio-temporal patterns. Associations between foraging and environmental characteristics varied according to spatial and temporal scale, highlighting the need for a multi-scale approach. Our results indicate that dolphins respond to coarser scale temporal dynamics, but have a detailed understanding of finer-scale spatial distribution of resources.

An interlaboratory comparison for the quantification of aqueous dimethylsulfide

An interlaboratory comparison (ILC) was conducted to evaluate the proficiency of multiple laboratories to quantify dimethylsulfide (DMS) in aqueous solution. Ten participating laboratories were each supplied with blind duplicate test solutions containing dimethylsulfoniopropionate hydrochloride (DMSP HCl) dissolved in acidified artificial seawater. The test solutions were prepared by the coordinating laboratory from a DMSP HCl reference material that was synthesized and purity certified for this purpose. A concentration range was specified for the test solutions and the participating laboratories were requested to dilute them as required for their analytical procedure, together with the addition of excess alkali under gas-tight conditions to convert the DMSP to DMS. Twenty-two DMS concentrations and their estimated expanded measurement uncertainties (95% confidence level) were received from the laboratories. With two exceptions, the within-laboratory variability was 5% or less and the between-laboratory variability was ~ 25%. The magnitude of expanded measurement uncertainties reported from all participants ranged from 1% to 33% relative to the result. The information gained from this pilot ILC indicated the need for further test sample distribution studies of this type so that participating laboratories can identify systematic errors in their analysis procedures and realistically evaluate their measurement uncertainty. The outcome of ILC studies provides insights into the comparability of data in the global surface seawater DMS database.

Statistical Procedure For Estimating Grey Seal Pup Production From A Single Census

The variable start and duration of the Grey seal breeding season makes the estimation of total pup production from a single census very difficult. Classifying the count into morphological age classes enables the form and timing of the birth rate curve and estimates of pup mortality rates to be elucidated. A simulation technique is described which enables the duration of each morphological stage to be determined from a series of such classified counts taken over one season. A further statistical technique uses these estimates to calculate the mean timing and duration of the breeding season from a single classified count taken from similar populations in subsequent years. This information allows total pup production to be calculated for any appropriate breeding colony. Some guidance is given as to the optimal timing of that single census which would yield the best estimate of production, although the precise date is not critical to the success of the technique. Results from single census estimates obtained in this way are compared with known production data from more detailed surveys for a number of different colonies.

A new procedure to optimize the selection of groups in a classification tree

Agglomerative cluster analyses encompass many techniques, which have been widely used in various fields of science. In biology, and specifically ecology, datasets are generally highly variable and may contain outliers, which increase the difficulty to identify the number of clusters. Here we present a new criterion to determine statistically the optimal level of partition in a classification tree. The criterion robustness is tested against perturbated data (outliers) using an observation or variable with values randomly generated. The technique, called Random Simulation Test (RST), is tested on (1) the well-known Iris dataset [Fisher, R.A., 1936. The use of multiple measurements in taxonomic problems. Ann. Eugenic. 7, 179–188], (2) simulated data with predetermined numbers of clusters following Milligan and Cooper [Milligan, G.W., Cooper, M.C., 1985. An examination of procedures for determining the number of clusters in a data set. Psychometrika 50, 159–179] and finally (3) is applied on real copepod communities data previously analyzed in Beaugrand et al. [Beaugrand, G., Ibanez, F., Lindley, J.A., Reid, P.C., 2002. Diversity of calanoid copepods in the North Atlantic and adjacent seas: species associations and biogeography. Mar. Ecol. Prog. Ser. 232, 179–195]. The technique is compared to several standard techniques. RST performed generally better than existing algorithms on simulated data and proved to be especially efficient with highly variable datasets.

Analytical phytoplankton carbon measurements spanning diverse ecosystems

The measurement of phytoplankton carbon (Cphyto) in the field has been a long-sought but elusive goal in oceanography. Proxy measurements of Cphyto have been employed in the past, but are subject to many confounding influences that undermine their accuracy. Here we report the first directly measured Cphyto values from the open ocean. The Cphyto samples were collected from a diversity of environments, ranging from Pacific and Atlantic oligotrophic gyres to equatorial upwelling systems to temperate spring conditions. When compared to earlier proxies, direct measurements of Cphyto exhibit the strongest relationship with particulate backscattering coefficients (bbp) (R2=0.69). Chlorophyll concentration and total particulate organic carbon (POC) concentration accounted for ~20% less variability in Cphyto than bbp. Ratios of Cphyto to Chl a span an order of magnitude moving across and within distinct ecosystems. Similarly, Cphyto:POC ratios were variable with the lowest values coming from productive temperate waters and the highest from oligotrophic gyres. A strong relationship between Cphyto and bbp is particularly significant because bbp is a property retrievable from satellite ocean color measurements. Our results, therefore, are highly encouraging for the global monitoring of phytoplankton biomass from space. The continued application of our Cphyto measurement approach will enable validation of satellite retrievals and contribute to an improved understanding of environmental controls on phytoplankton biomass and physiology.