Community structure across a large-scale ocean productivity gradient: Marine bird assemblages of the Southern Indian Ocean

149

142

The Ideal Free Distribution theory predicts a close spatial match between predators and prey. Studies have shown that seabird and prey distribution seldom conforms with this prediction. In this study, I review recent theoretical advances in spatial predator-prey interactions and relate these with studies of seabirds and pelagic schooling fish and crustaceans. Studies on seabirds and prey have generally assumed that prey are nonresponsive. Predator-prey interactions should, however, be viewed as a 2-way spatial game where seabirds track concentrations of prey while prey move away from areas with high risk of predation. The outcome of the game depends on how seabirds and prey are spatially constrained. Constraints include the spatial distribution of resources, interspecific competition, the location of spawning and breeding areas, and limitations on diving depth. Although game theoretic models can explain some general aspects of the spatial interaction, the spatial distribution of seabirds and prey is generally much more aggregated and elusive than can be expected from the game theoretic equilibrium. This is because spatial pattern is formed through selforganizing behavior that includes schooling, local enhancement and area-restricted search (ARS). Schooling and local enhancement are processes with strong positive density dependence that destabilize the predator-prey interaction locally. However, the unstable local dynamics might be stabilized by spatial constraints and the effects of ARS processes at large scales.

Section: Spatial Handicaps Of Preymentioning

confidence: 99%

Spatial interaction between seabirds and prey: review and synthesis

Fauchald¹

2009

149

142

“…mapping, geographic information systems [GIS]) aimed at displaying the data and supporting pertinent hypotheses for further testing (Harrison 1982, Joiris 1991, Hull et al 1997, Ollason et al 1997, (2) Table 2. Contents of the categories that group statistical techniques used to relate seabird distributions and environmental variables 1997, Karnovsky et al 2003, Weichler et al 2004, Hyrenbach et al 2007) and (6) multi-scale approaches (e.g. wavelets, fractal geometry) investigating ecological functional relationships (Russell et al 1992b, Logerwell et al 1998, Mehlum et al 1999, Swartzman & Hunt 2000 that are known to change with scale (Levin 1992).…”

Section: Association Between Seabird Distribution and Environmental Vmentioning

confidence: 99%

Analytical approaches to investigating seabird–environment interactions: a review

Tremblay¹,

Bertrand²,

Henry³

et al. 2009

A goal of seabird ecology is to relate the physiology, population dynamics, distribution and behaviour of seabirds with their biotic and abiotic environments. One of the most challenging aspects is to understand how seabirds interact with their environment when direct observations are not always possible or practical. In the present paper, we reviewed 218 published studies that examined associations between seabird distribution, behaviour and their environment, in order to assess current trends, weaknesses and the future directions of research. Based on the number of publications, it is evident that the field is growing rapidly and that methods for evaluating seabird distribution are becoming increasingly more sophisticated and are changing from Eulerian (grid-like) to Lagrangian (particle-like) data types. This has been accompanied by a reduction in the spatial and temporal scale of observation, where, in most cases, no behavioural information is inferred from Lagrangian data; instead they are often used as if they were Eulerian data. In parallel, environmental remote sensing is becoming more common; however, we did not record significant changes in the statistical approaches used to describe seabird distributions and used to link them with oceanographic variables. In particular, despite the spatially explicit nature of the data, spatial statistics have rarely been used. The vast majority of studies used environmental variables that described water masses (descriptive approach), whereas a few studies determined oceanographic features that enhance prey availability to seabirds (process-based approach). Future studies could enhance their ecological interpretation of seabird -environment interactions by making greater use of ad hoc statistical approaches that facilitate appropriate pattern detection (e.g. area-restricted searching pattern for birds, mesoscale patterns for environment). Furthermore, appropriate hypothesis testing and modelling that accounts for the spatially explicit, multiscale and multivariate nature of the interaction between seabirds and their habitats is recommended. Although quantitative methods currently exist (but are rarely used), further application could greatly improve our understanding of the processes linking seabird distribution to their environment.

“…Relatively little research has been done on the community structure of pelagic marine organisms, most likely due to the difficulty of gathering such data (Venrick 1990). Despite these difficulties, research in pelagic systems has shown clear gradients and structure in the following pelagic communities: marine phytoplankton (Venrick 1982(Venrick , 1990; marine zooplankton (McGowan & Walker 1979, 1985; marine birds (Ballance et al 1997, Woehler et al 2003, Hyrenbach et al 2007; and marine mammals , Baumgartner et al 2001, Hamazaki 2002, Palacios 2003.…”

Section: Introductionmentioning

confidence: 99%

Community structure in pelagic marine mammals at large spatial scales

Schick¹,

Halpin²,

Read³

et al. 2011

The understanding of a species' niche is fundamental to the concept of ecology, yet relatively little work has been done on niches in pelagic marine mammal communities. Data collection on the distribution and abundance of marine mammals is costly, time consuming and complicated by logistical difficulties. Here we take advantage of a data archive comprising many different datasets on the distribution and abundance of cetaceans from Nova Scotia through the Gulf of Mexico in an effort to uncover community structure at large spatial scales (1000s of km). We constructed a multivariate ordination of the species data, tested for group structure that might exist within the ordination space, and determined how these groups might differ in environmental space. We examined 3 biogeographic regions: the oceanic waters north and south of Cape Hatteras, NC, and the Gulf of Mexico. North of Hatteras, we found 2 main groups split along a temperature and chlorophyll gradient, with most piscivores being found in cooler, more productive waters of the continental shelf, and most teuthivores being found farther offshore in warmer, less productive waters at the shelf break (200 m isobath). South of Hatteras, we found 3 groups, with the largest group being in warmer, lower chlorophyll waters that are closest to shore. In the Gulf of Mexico, we found 7 groups arrayed along a bottom depth gradient. We also tested the effect of taxonomically lumping different beaked whale species on ordination results. Results showed that when beaked whales were identified to the species level, they clustered out into distinct niches that are separate from those of other Odontocete groups. These results add to an increasing understanding of wildlife habitat associations and niche partitionings in the community structure of pelagic species, and provide important baseline information for future population monitoring efforts. KEY WORDS: Cetaceans · Group contrast Mantel test · Nonmetric dimensional scaling · Multivariate ordination · Northwest Atlantic OceanResale or republication not permitted without written consent of the publisher