Priorities for migratory networks

Making good decisions with limited information


Key messages:
  • Migratory species are declining globally at greater rates than non-migratory species, and are in need of urgent and strategic conservation action
  • We show how small amounts of tracking data can be used to increase our understand of where migratory animals travel (which helps in setting conservation priorities)
  • Including connectivity information always improves conservation outcomes for migratory species

Catching and tagging birds is a large part of understanding where they migrate. However, if we tag a few birds in multiple locations, we can learn more about how the population behaves as a whole, than if we tag many birds in the same location. (Photo by Kiran Dhanjal-Adams)

Catching and tagging birds is a large part of understanding where they migrate. However, if we tag a few birds in multiple locations, we can learn more about how the population behaves as a whole, than if we tag many birds in the same location. (Photo by Kiran Dhanjal-Adams)

The movie Jaws turned great white sharks into world-famous human eaters. Less well-known about great whites is that they can undertake astounding migrations. In 2002, a shark tagged in South Africa was tracked all the way to Western Australia (see Figure 1). Though it lost its tag in Australia, it was re-sighted again in South Africa, proving the species capable of migrating some 20,000 kilometers.

Great whites are, however, far from being alone when it comes to astounding feats of migration. Dragonflies have been found to travel similar distances between India and Africa, stopping off in the Maldives on the way. The longest recorded migration of all is that of an Arctic tern, which flew 70,000 km over a year from one pole to the other and back, in search of an eternal summer.

A lifestyle on the move is not without risk. Migration is physically demanding, and migratory species are highly reliant on places to stop, rest and feed along the way. Unfortunately, human activities are making it riskier for animals to travel, while also reducing the number of places they can travel to. Fishing, culling, fence-building, deforestation, land-reclamation and plastic pollution are all making it increasingly difficult for many species to migrate. So much so, that migratory species populations are declining at much greater rates than nonmigratory species.

This suggests that current conservation strategies are not working as well as we would like them to. We are still at the early stages of understanding migration, and data detailing where, when and how far many species migrate is still sparse. Though a few individuals of some species have been tracked, it remains unclear how these few tracked individuals reflect the migration patterns of an entire species.

What should we measure?

Because of this poor understanding of where animals migrate, conservation strategies are currently set using the data we have – animal counts. Indeed, it is not unreasonable to assume that sites with lots of migrants are probably more useful to the population than sites with fewer migrants. However, research is increasingly showing that where these sites are relative to each other is equally important. This is because the distance between two sites is likely to impact the number of animals able to travel between the two. Connected sites are therefore more useful to the population than unconnected sites.

So, how do we marry abundance measures with connectivity measures to set conservation priorities for migratory species when so few animals have been tracked? To help maximise the value of limited information, we have developed a methodology for using as few as three tracked individuals to calculate the probability of an animal travelling between any two places (Dhanjal-Adams et al, 2016). By augmenting these measures with count data, it is then easy to draw up the migratory network of a species.

Figure1. Positions of (dots) and track followed by (black line) shark ‘P12’ during coastal and transoceanic movement. (Image from Bonfil et al, 2005)

Figure1. Positions of (dots) and track followed by (black line) shark ‘P12’ during coastal and transoceanic movement. (Image from Bonfil et al, 2005)

What should we prioritise?

We did this for seven migratory shorebird species in the East Asian-Australasian Flyway. We found that conservation strategies that prioritise sites based on connectivity and abundance together, always outperform strategies that only prioritise sites based on abundance (Fig 2).

Figure 2: In our study, we drew up a migratory network and removed sites according to different prioritisation strategies to see how they influenced population declines. The flow prioritisation strategy (black triangles) includes connectivity data as well as abundance data. The maximum count prioritisation strategy only includes abundance data (squares). The random prioritisation strategy does not include any connectivity data or abundance data, but choses sites at random for conservation. We therefore perform the random prioritisation strategy 1000 times to have a representative spread of possible results (black circles; ±95% quantiles) We compared these three strategies for seven different migratory shorebird species: a) bar-tailed godwit, b) eastern curlew, c) great knot, d) grey-tailed tattler, e) red knot, f) ruddy turnstone and g) sanderling. As you can see, the flow prioritisation strategy always outperforms the count prioritisation strategy and random prioritisation strategy.

Figure 2: In our study, we drew up a migratory network and removed sites according to different prioritisation strategies to see how they influenced population declines. The flow prioritisation strategy (black triangles) includes connectivity data as well as abundance data. The maximum count prioritisation strategy only includes abundance data (squares). The random prioritisation strategy does not include any connectivity data or abundance data, but choses sites at random for conservation. We therefore perform the random prioritisation strategy 1000 times to have a representative spread of possible results (black circles; ±95% quantiles) We compared these three strategies for seven different migratory shorebird species: a) bar-tailed godwit, b) eastern curlew, c) great knot, d) grey-tailed tattler, e) red knot, f) ruddy turnstone and g) sanderling. As you can see, the flow prioritisation strategy always outperforms the count prioritisation strategy and random prioritisation strategy.

Interestingly, sites with a smaller number of birds can be given a higher conservation priority than sites with lots of birds. This is because groupings of small sites can act as a unit, which together, support a higher proportion of the population than an isolated site with a higher bird count. These groupings of small sites are therefore prioritized over the site with slightly more birds. However, these tradeoffs are complex and difficult to predict, making it important to draw up a migratory network during the planning process.

By using very simple metrics, we show that it is possible, despite a lack of tracking data, to come up with estimates of where migratory species might travel, which in turn can be used to inform conservation planning. Importantly, given migratory species are declining despite the current protection, methods like the one we have developed can be used to determine the value of adding additional habitat to the current network of protected areas.


Tracking turtles

Developing conservation plans for a threatened migratory animal like the loggerhead sea turtle presents multiple challenges.  (Photo by Tessa Mazor)

Developing conservation plans for a threatened migratory animal like the loggerhead sea turtle presents multiple challenges. (Photo by Tessa Mazor)

Another example of the importance of information for planning conservation management for migratory species comes from a recent CEED investigation on loggerhead sea turtles in the Mediterranean.

Tessa Mazor and colleagues developed conservation plans for the loggerhead turtles using four approaches (Mazor et al, 2016). Each approach required increasing amounts of information (and therefore increasing cost). Their analysis revealed that spatial priorities for sea turtle conservation are very sensitive to the type of information being used. Setting conservation targets for migration tracks altered the location of conservation priorities.

This indicates that conservation plans designed without such data would miss important sea turtle habitat.

Reference

Mazor T, M Beger, J McGowan, HP Possingham & S Kark (2016). The value of migration information for conservation prioritization of sea turtles in the Mediterranean. Global Ecology and Biogeography. 25: 540–552. doi: 10.1111/geb.12434 (And see Decision Point #96)

 


More info: Kiran Dhanjal-Adams kiran.dhanjaladams@uqconnect.edu.au

Reference

Dhanjal-Adams KL, M Klaassen, S Nicol, HP Possingham, I Chadès & RA Fuller (2016). Setting conservation priorities for migratory networks under uncertainty. Conservation Biology.  http://onlinelibrary.wiley.com/doi/10.1111/cobi.12842/epdf

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