In search of surrogates for genetic variation
Species that are threatened with extinction usually exist in small numbers and occur in groups that are often isolated from each other. Central to conservation planning is the effort to maximise representation and persistence of biodiversity at minimum cost. The great majority of plans, however, only focus on representation. To incorporate aspects of persistence it is essential to include processes that affect the amount and distribution of biological variability and the ability for organisms to adapt and evolve. And that means factoring in genetic variation. The genetic divergence that accumulates through time, leads to speciation; while the genetic diversity increases the reproductive variability.
Unfortunately, factoring in genes is easier said than done. Protecting all the populations of a threatened species is often an impossible task because financial resources for conservation tend to be limited and genetic analysis tends to be expensive. For example, if we had enough funds to protect only three populations of a threatened species found across an archipelago of many islands and we wanted to choose those islands where this species occurs with the highest genetic or phenotypic diversity and divergence, how would we make this choice?
One option would be to go out into the field and sample the different populations on a range islands. Then we could take those samples back to the lab and using genetic tools determine which of the islands has the highest diversity. However, such analysis takes time and money. It’s possible that we might be able to identify the three islands with the greatest diversity but then not have the funds to be able to adequately protect them. And the process of genetic analysis can add considerable time to the planning process, which might be problematic if an imperilled species needs rapid protection.
Is there another way to approach this? By identifying simpler ways that allow us to select islands with high genetic or phenotypic diversity and divergence we could potentially be able to make better conservation decisions. Would geographic measures allow us to identify the genetically most diverse or divergent populations? Distance between islands and the size of islands are both factors, for example, that contribute to genetic diversity over time.
Choosing populations with the largest distance between them might select for the highest divergence, as the geographic distance will limit the gene flow between populations and therefore reduce the presence of shared alleles.
Another option is selecting the biggest islands. This could help minimize the effects of the genetic drift, and therefore capture the highest diversity. Genetic drift is more obvious in smaller populations (smaller islands) where rare alleles are sometimes lost.
Finally, selecting a subset of islands that best represent the geographical coverage of the archipelago might be the way to go. This would be the set of islands with the shortest average distance between selected and unselected islands. With this measurement we might expect to get a combination of diversity and divergence.
A few years ago, researchers from the Imperial College in London, assessed the genetic diversity, divergence and morphology of two species of silvereyes (Zosterops flavifrons, and Z. lateralis) in Vanuatu. They visited the 13 main islands of the Vanuatu archipelago, each with a different population of silvereye.
They found that the species have different genetic structures: Z. flavifrons is endemic to Vanuatu and it colonized the archipelago between 2-4 million years ago and the genetic structure is driven by genetic drift. The plumage of the populations can vary between yellow and dark.
Z. lateralis is not endemic to Vanuatu. It arrived half a million years ago and its population genetic structure is driven by a distance-mediated gene flow.
Using these genetic analyses we came up with a suite of geographic measures that could be used as surrogates (Ponce-Reyes et al., 2014) and then used these geographic measures in a conservation planning exercise to see if we could create a plan that effectively conserved genetic variation. If the geographic measures could be used instead of the actual genetic results it would enable a simpler and inexpensive way of incorporating genetic processes into conservation planning.
We found that if you only had money to protect half of the total populations, selecting islands with the maximum distance between them was the best approach in both species if the aim is to capture the highest genetic divergence. But this approach worked best when looking at protecting the phenotypic divergence (based on the morphology of the birds), especially for Z. lateralis.
If we were interested in protecting the genetic diversity, choosing the biggest islands worked well for Z. flavifrons when selecting less than 50% of the islands. However for Z. lateralis this was not the case, choosing the biggest islands was less effective than simply picking the islands randomly.
The maximum representation generally tended to perform as the best metric when a higher number of islands were selected (more than half of the total).
Incorporating genetic variation in conservation planning is important to preserving evolutionary processes. However, it can be expensive and time consuming. Consequently, the use of surrogates for measuring this variation is worth exploring.
The effectiveness of the surrogates that we tested was variable. We didn’t identify a measure that performed consistently better
than just selecting islands randomly. The next step will be to test if combing several surrogates will enhance the benefits for genetic and phenotypic variation and even serve to maximize the evolutionary potential of protected populations. For example, the rate of speciation on islands depends on the size, age, topography and habitat diversity, evolutionary and geological features and island isolation; as well as the targeted species.
We acknowledge that without previous knowledge of the population genetic structure, planners might be reluctant to use the geographic measures as surrogates for genetic analyses. However delaying the decision for conservation while gathering data may lead to lost opportunities for conservation.
We also acknowledge that insufficient prior knowledge may lead to poor decisions. Hence with this study we are not arguing that genetic studies are not desirable to improve conservation decisions but to analyze the trade-off between time and money required to gain genetic information and the benefits those data can provide relative to an immediately available surrogate.
The Vanuatu white-eye or yellow-fronted white-eye (Zosterops flavifrons) is a small passerine bird belonging to the genus Zosterops in the white-eye family Zosteropidae. It is endemic to Vanuatu, where it is one of the most common birds.
This bird is 11–12 cm long. The adult male is yellow-green above while the underparts are bright yellow or yellow-green depending on the subspecies. The forehead is yellow and there is a white ring around the eye. The legs and feet are dark grey and the bill is brown above and pinkish below. Female and immature birds are similar to the male but paler. The immatures also have a narrower eye-ring.
The contact call is short and high-pitched. The song is a repeated warbling.
There are seven subspecies distributed almost throughout Vanuatu from the Banks Islands in the north to Aneityum in the south. The species occurs in a variety of habitats including forest, plantations and gardens from sea-level to the mountains. It forages in bushes and trees, moving around in pairs or small flocks. The varied diet includes insects, nectar and fruit such as lantana berries and wild figs.
The neat, cup-shaped nest is built 2.5 metres or more above the ground and is made of grass, pieces of bark and spider webs. The eggs are bluish-white and there are three in a clutch.
More info: Rocio.Poncereyes@csiro.au
Ponce-Reyes R, SM Clegg, SB Carvalho, E McDonald-Madden & HP Possingham (2014). Geographical surrogates of genetic variation for selecting island populations for conservation. Diversity and Distributions 20: 640–651.