Scaling of Activity Space in Marine Organisms across Latitudinal Gradients.

AbstractUnifying models have shown that the amount of space used by animals (e.g., activity space, home range) scales allometrically with body mass for terrestrial taxa; however, such relationships are far less clear for marine species. We compiled movement data from 1,596 individuals across 79 taxa collected using a continental passive acoustic telemetry network of acoustic receivers to assess allometric scaling of activity space. We found that ectothermic marine taxa do exhibit allometric scaling for activity space, with an overall scaling exponent of 0.64. However, body mass alone explained only 35% of the variation, with the remaining variation best explained by trophic position for teleosts and latitude for sharks, rays, and marine reptiles. Taxon-specific allometric relationships highlighted weaker scaling exponents among teleost fish species (0.07) than sharks (0.96), rays (0.55), and marine reptiles (0.57). The allometric scaling relationship and scaling exponents for the marine taxonomic groups examined were lower than those reported from studies that had collated both marine and terrestrial species data derived using various tracking methods. We propose that these disparities arise because previous work integrated summarized data across many studies that used differing methods for collecting and quantifying activity space, introducing considerable uncertainty into slope estimates. Our findings highlight the benefit of using large-scale, coordinated animal biotelemetry networks to address cross-taxa evolutionary and ecological questions.

Crossing latitudes--long-distance tracking of an apex predator.

Tiger sharks (Galeocerdo cuvier) are apex predators occurring in most tropical and warm temperate marine ecosystems, but we know relatively little of their patterns of residency and movement over large spatial and temporal scales. We deployed satellite tags on eleven tiger sharks off the north-western coast of Western Australia and used the Brownian Bridge kernel method to calculate home ranges and analyse movement behaviour. One individual recorded one of the largest geographical ranges of movement ever reported for the species, travelling over 4000 km during 517 days of monitoring. Tags on the remainder of the sharks reported for shorter periods (7-191 days). Most of these sharks had restricted movements and long-term (30-188 days) residency in coastal waters in the vicinity of the area where they were tagged. Core home range areas of sharks varied greatly from 1166.9 to 634,944 km2. Tiger sharks spent most of their time in water temperatures between 23°-26°C but experienced temperatures ranging from 6°C to 33°C. One shark displayed seasonal movements among three distinct home range cores spread along most of the coast of Western Australia and generalized linear models showed that this individual had different patterns of temperature and depth occupancy in each region of the coast, with the highest probability of residency occurring in the shallowest areas of the coast with water temperatures above 23°C. These results suggest that tiger sharks can migrate over very large distances and across latitudes ranging from tropical to the cool temperate waters. Such extensive long-term movements may be a key element influencing the connectivity of populations within and among ocean basins.

Growth of tropical Dasyatid rays estimated using a multi-analytical approach.

We studied the age and growth of four sympatric stingrays: reticulate whipray, Himanutra uarnak (n=19); blue mask, Neotrygon kuhlii (n=34); cowtail, Pastinachus atrus (n=32) and blue-spotted fantail, Taeniura lymma (n=40) rays at Ningaloo Reef, a fringing coral reef on the north-western coast of western Australia. Age estimates derived from band counts within sectioned vertebrae ranged between 1 and 27 years (H. uarnak, 1 - 25 yrs.; N. kuhlii, 1.5 - 13 yrs.; P. atrus, 1 - 27 yrs. and T. lymma, 1 -11 yrs.). Due to limitations of sample sizes, we combined several analytical methods for estimating growth parameters. First, we used nonlinear least squares (NLS) to identify the growth model that best fitted the data. We then used this model, prior information and the data within a Bayesian framework to approximate the posterior distribution of the growth parameters. For all species the two-parameter von Bertalanffy growth model provided the best fit to size-at-age datasets. Based on this model, the Bayesian approach allowed the estimation of median values of W(D∞) (cm) and k (yr(-1)) for the four species (H. uarnak: 149 and 0.12; N. kuhlii: 42 and 0.38; P. atrus 156 and 0.16, and T. lymma 33 and 0.24, respectively). Our approach highlights the value of combining different analytical methods and prior knowledge for estimating growth parameters when data quality and quantity are limited.