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Wetland connectivity: understanding the dispersal of organisms that occur in Victoria’s wetlands draft


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Stable isotopes


Studies by Fry (1981) and others in the early 1980s pioneered the use of stable isotopes in studying animal movement. Stable isotopes are naturally occurring forms of an element that differ in the number of neutrons held in the nucleus, forming heavier and lighter forms of the element (Fry 2006). The use of stable isotopes in studying animal movement requires that the natural abundance of isotopes in dietary sources of a target animal varies geographically, and that these signatures are incorporated in animal tissues. If these prerequisites are fulfilled, stable isotopic analysis of potential dietary sources and animal tissues can reveal the location of major food sources, giving an indirect measure of movement (Hobson 1999, Fry 2006). In metabolically active tissues such as muscles the isotopic signatures may last only months, but in metabolically inert tissues such a fur and feathers the signature may be preserved until the tissue is shed, allowing movement over longer time frames to be detected (Hobson 1999).

In aquatic systems, stable isotopes have been employed to study animal movement among estuaries, lakes and rivers. Typically, multiple isotopes are analysed to develop a clear spatial signal; the most commonly used are 13C, 15N, 34S, D and 87Sr (Hobson 1999). Many studies have used stable isotopes to assess patterns of animal movement between marine and freshwater systems, since dietary sources associated with these ecosystems have distinct isotopic signatures (13C 15N, 34S). The taxa studied in these systems include fish, terns, cormorants, mink and rats. In fish otoliths, calcium carbonate structures of the inner ear, layers of inert tissue that are laid down each year store the isotopic signature of the water occupied by the fish. Fish otoliths therefore provide a persistent record of movement between rivers and estuaries over the life of diadromous fish (Nelson et al. 1989).

Fine-scale movement can be detected where the isotopic signatures of dietary sources are distinct over small spatial scales. Although isotopic differentiation at small spatial scales may not be common, one study in which this approach was informative was an Australian study by Cook et al. (2007). This study used isotopes (15N, 13C) as well as other approaches to assess movement, both among and within stream habitats, of the threatened Southern Pigmy-perch (Nannoperca australis). In a stream where base flows ceased in summer, isotopic signatures from muscle tissues of fish caught at several sites in the stream closely matched dietary sources at the site of collection. This suggested that populations were isolated at small spatial scales. In contrast, in a stream where base-flows persisted in summer, isotopic signatures of fish were not as good a match to the dietary sources at collection sites, suggesting greater mobility.

Stable hydrogen isotope ratios have been used to study large-scale movements of birds (Rubenstein et al. 2002) and the Monarch butterfly (Danaus plexippus) (Hobson et al. 1999). Stable hydrogen isotope ratios of precipitation vary geographically because water vapour is rich in the lighter isotope of hydrogen whereas rainfall is rich in the heavier isotope. As moist air masses move from low to high latitudes and from low to high altitudes, rainfall becomes progressively depleted in the heaver isotope (Fry 2006). Rainfall with different ratios of isotopes is subsequently incorporated into food webs, producing strong signatures that change with latitude and altitude. Stable isotope methods have so far been applied only to track animal movements, but could prove useful in tracing the origins of seeds or seedlings, and hence dispersal distances (Wang and Smith 2002).


    1. Genetic markers


When dispersal results in successful colonisation, or when pollen reaches plants from other habitats, genetic information is exchanged. The levels of genetic variation among populations can therefore be used to infer levels of connectivity among habitats (Sork et al. 1999, Wang and Smith 2002). Populations that are highly connected will have high levels of gene flow and will be genetically similar. Populations that are isolated experience genetic drift and have high levels of genetic differentiation. These assumptions underlie the use of genetics in identifying patterns of movement (Hughes 2007).

Genetic markers allow levels of genetic variation among populations to be assessed (Bilton et al. 2001). The fixation index (FST) provides a measure of gene flow among populations by comparing levels of genetic variation within populations with levels of variation among populations (Holsinger and Weir 2009). When the level of genetic variation within habitats approximates that found among populations, FST is small and the population is likely to be well connected to other populations in the landscape. Conversely, where the pattern of genetic variation within habitats differs substantially to that found among populations, FST is large and the population is likely to be isolated from other populations (Wang and Smith 2002). Genetic techniques can also be used to determine the probability that an individual is from a particular population and when juveniles are studied it can provide insights into recent patterns of dispersal, provided there is a high level of genetic variation among populations (Sork et al. 1999).

There are many instances when genetic markers fail to represent levels of dispersal. Firstly, both zooplankton and aquatic plants (via clonal growth) are capable of rapid population growth upon colonising new habitats. Therefore early colonists can dominate the genetic makeup of the population, giving a picture of lower connectivity even when propagule or pollen exchange is frequent (Boileau et al. 1992, Gómez et al. 2002, DeMeester et al. 2002). This ‘founder effect’ is reinforced when large resting propagule banks are produced by early colonists (De Meester et al. 2002). Secondly, in some habitats natural selection may produce a gene pool best suited to the local conditions, and new colonists will then be at a competitive disadvantage and be less successful at colonisation. As a result, high rates of immigration may exert little effect on the gene pool. Low levels of connectivity will be incorrectly inferred when cryptic species are not distinguished among populations, and if geographical barriers have existed in the past, it may take thousands of years for the gene pool to reach an equilibrium that reflects contemporary patterns of gene flow (Bohonak and Jenkins 2003, Balkenhol et al. 2009).

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