An obligate beach bird selects sub-, inter- and supra-tidal habitat elements
Introduction
Ocean shores represent the most distinct ecological interface, between marine and terrestrial ecosystems, on the planet (Schlacher et al., 2008). Sandy shores differ from marine or terrestrial habitats in that there is little primary productivity on beaches, rather ecological subsidies occur from marine and terrestrial environments (Huijbers et al., 2013). Coastal wildlife dependent on beaches directly exploit these energy flows through scavenging on beach-cast carrion or preying upon infauna, which themselves depend on energetic subsidies (Spiller et al., 2010, Huijbers et al., 2013). While sandy shores are extensive, they are highly varied, in terms of geomorphology, sand grain size, and biodiversity (McLachlan and Brown, 2006). For example, benthic infauna is patchily distributed, being influenced by a range of factors including sediment grain size, wave action, and anthropogenic stressors such as beach nourishment (Schlacher et al., 2008).
Few vertebrates can be considered high-energy, sandy-shore obligates; those that are, are not well studied. A classification of niche specialisation of coastal wildlife is currently unavailable, although it is clear there are differences in the way wildlife uses beaches, and we provisionally suggest a classification here (Fig. 1). Sandy coast obligate species may exploit resources in near-shore hinterlands (e.g. dunes), from the beach itself, and from the intertidal zones. Thus, their habitat includes marine and terrestrial elements. They rely on these areas to provide resources for foraging, shelter (from weather and predators) and breeding (McLachlan and Brown, 2006).
One prominent group of sandy shore obligate vertebrates includes populations of particular coastal shorebirds. Many of these species are under conservation stress, and are the subject of ongoing conservation efforts (e.g. Piping Plover Charadrius melodus, Wemmer et al., 2001, Shore Plover Thinornis novaeseelandiae, Marchant and Higgins, 1993, Hooded Plover Thinornis cucullatus, Maguire et al., 2013, Chatham Island Oystercatcher Haematopus chathamensis, Department of Conservation, (2001)). Shorebirds which occupy sandy shorelines are often widespread at low densities when they breed (Page et al., 1983, Marchant and Higgins, 1993, Weston et al., 2009), with breeding territory formation being driven presumably by competition for resources required for producing young (Brown, 1969, Sergio et al., 2009). Because of their widespread distributions, there is a tendency for managers and ecologists to assume that all coastal high energy sandy shorelines (beaches) represent ‘habitat’ of equivalent suitability or quality for these birds, despite the occurrence of substantial stretches of unoccupied beach (see, for example, Fig. 1 in Weston et al., 2012). This assumption has made it difficult to assess population viability, including determining carrying capacity of coastlines, and to identify priority breeding habitats. Conservation management for coastal obligates has focused largely on improving reproductive success (Weston et al., 2003), however the availability of breeding territories is also likely to be critical for recovery of these taxa (Wemmer et al., 2001). Thus, an improved understanding of which beaches represent habitat, and the factors which influence suitable habitat, is required to improve species management. Additionally, such understanding is required to help predict the impact of rising sea levels on species viability (Convertino et al., 2012). Shorebirds are also considered to be valuable indicators of sandy shore ecosystems, and enjoy substantial public interest and engagement, which assists with the attainment of management objectives (Schlacher et al., 2014, Schlacher et al., 2015).
Habitat models have become prominent features of species management, especially for species which are widespread, rare or both (e.g., Guisan and Zimmermann, 2000, Klar et al., 2008, Convertino et al., 2011, Convertino et al., 2012). They offer insights into the extent of viable habitat for species (Convertino et al., 2011, Gratto-Trevor, 1996, Meager et al., 2012, Schlacher et al., 2013), to model different conservation options (e.g., Wemmer et al., 2001, Murray et al., 2011) and have even been used to help identify stakeholders in species conservation (Weston et al., 2012). The vast majority of models are terrestrial (e.g. Lauver et al., 2002), though some marine seafloor models are also available but are often restricted by geographic extent due to the lack of data availability in coastal zones (Ierodiaconou et al., 2011). Mapping the seafloor is difficult along coastal margins, especially exposed coasts, which present a range of challenging obstacles due to wave action and turbidity (Chust et al., 2010). Habitat models of coastal biodiversity are uncommon (Ozesmi and Mitsch, 1997, Willems et al., 2008), though a few exceptions model the habitat suitability of coastal shorebirds (Convertino et al., 2011, Convertino et al., 2012, Meager et al., 2012), and of those, are often restricted to the use of supra-tidal or intertidal data only. One challenge to building habitat models in coastal environments is the feasibility of collecting baseline data on the presence/absence of species, along with descriptions of underlying habitat features both above and below the water over large areas. Fortunately, developments in remote sensing, and especially the application of Light Detection And Ranging (LiDAR) technologies to coasts, hold great promise in mapping habitat of coastal biodiversity (Goodale et al., 2007, Ledee et al., 2008; Zavalas et al., 2014; Jalali et al., 2015). LiDAR can provide high resolution digital elevation models and surface complexity information with seamless mosaics over large geographic extents across the common terrestrial-marine divide that can be used to characterise habitats (Vierling et al., 2008, Kennedy et al., 2014). In addition, the growing use of volunteers, or Citizen Scientists, in the collection of monitoring data provides a means by which presence-absence of species can be confirmed across much larger areas than is possible by individual researchers (Greenwood, 2007, Dunn and Weston, 2008).
In this study, we develop a simple habitat model for an obligate coastal vertebrate, which considers supra-, inter- and sub-tidal variables. We aim to examine whether any habitat preferences exist in the selection of breeding territories by this species, and if so, to document those factors associated with suitable habitat. We do not address habitat quality but recognise that breeding success data could underpin a habitat quality model in future.
Section snippets
Methods
The Eastern Hooded Plover Thinornis cucullatus cucullatus is a threatened, obligate, beach-nesting shorebird which occurs in temperate south-eastern Australia. Populations have long been in decline, and the species has become locally extinct in parts of their former range as a result multiple threats including human disturbance and interference, habitat modification and altered predator environments including introduced carnivorous, and superabundant omnivorous, predators (Dowling and Weston,
Results
Table 1 presents summary statistics for the variables measured. The 512 model set yielded eight models with substantial support (delta AICc < 2; Table 2). Four variables had considerable support (variable weights >0.5) and were positively related to territory selection (Table 3). The amount of dune in breeding territories was the most influential variable identified by model selection with a variable weight of 0.91 (Table 3). The mean predicted probability of occurrence for this variable
Discussion
As is usual for shorebirds, Hooded Plovers are highly mobile - regular movement between breeding and flocking sites is evident and movement rates are significant, especially for non-breeding adults and juveniles (Weston et al., 2009). However, while the taxon is mobile and its distribution highly dispersed, distinct fine scale distributional patterns are evident - it does not occupy all parts of high energy sandy coasts (Weston et al., 2009, Driessen and Maguire, 2015). This indicates that
Acknowledgments
Funding was provided by BirdLife Australia's Beach-nesting Birds project, via the Australian Government's Caring for Our Country Programme. We thank the Department of Environment and Primary Industries (Victoria, Australia) and the Future Coasts Program for access to the LiDAR data. Thanks to Graeme Newell and Anna Cuttriss (Department of Environment and Primary Industries) for helpful discussions and site photographs, and to Thomas Schlacher and two anonymous referees. Thanks to Estelle Barker
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