Tag Archives: Paper of the Week

Paper Of The Week: Wilschut et al. (2015) Spatial distribution patterns of plague hosts: point pattern analysis of the burrows of great gerbils in Kazakhstan

24 Jun

Epidemiology has advanced beyond all recognition in recent years, but it is sometimes surprising just how little spatial information is incorporated into models about how diseases spread in space and time. Yet, the spread of disease will almost always have a spatial component, and ignoring this can result in a mis-understanding of how a given disease is likely to move across a given landscape.

This is a point highlighted by the authors of this weeks Paper of the Week. The paper itself is Wilschut et al. (2015) Spatial distribution patterns of plague hosts: point pattern analysis of the burrows of great gerbils in Kazakhstan, and it looks for evidence of spatial clustering in the distribution of a key reservoir species for plague bacteria in central Asia. The clustering they find, they point out, has important implications for our understanding of how plague can persist and spread through local landscapes. In particular, their results suggest that both the invasion and the persistence of plague will be influenced not only by the distances between occupied burrows (as might be expected), but also by the distances between clusters of occupied burrows, adding an extra level of complexity to the spatial elements of plague epidemiology.

The reason that I selected this paper was because it provides a nice case study of how other information, in this case the levels of spatial clustering in a reservoir host, needs to be studied and understood if we are to properly understand the epidemiology of any given disease. This means that epidemiologists need to not only understand diseases, but also GIS, in order to understand the landscapes in which the diseases they study occur.

========================

Dr Colin D. MacLeod,
Founder, GIS In Ecology
========================

Paper Of The Week: Maestri et al. (2015) Niche Suitability Affects Development: Skull Asymmetry Increases in Less Suitable Areas

17 Jun

Back in the mid-1990s, fluctuating asymmetry (FA) was a very trendy subject area in ecology. For those of you who don’t know, FA is the more or less random variations in morphological characteristics that should be perfectly bilaterally symmetric, and these variations are thought to be influenced by (amongst other things) the environmental stress that an organism experiences as it develops. However, since its peak in popularity, interest in FA has fallen somewhat by the wayside. This happened, in part, because like all trends it has to one day come to an end, but also because it was being heavily over-used and linked to almost everything, sometimes based on rather flimsy evidence.

Regardless of this, I’ve often thought that FA has now become a greatly under-used tool in the ecologists armoury, and it was for this reason that this weeks paper of the week caught my eye. Published recently in PLoS One, Maestri et al. (2015)’s paper is titled ‘Niche Suitability Affects Development: Skull Asymmetry Increases in Less Suitable Areas’. It neatly combines both my interest in FA, and one of my other favourite topics, Species Distribution Modelling, and I couldn’t resist selecting it for that very reason.

They hypothesis behind this paper is that animals which live in less suitable habitat, found at the edges of their niche, will be under greater stress than those which live closer better habitat found at the centre of the niche the species occupies, and so should have higher levels of FA. When they tested this hypothesis on a rodent species endemic to the Brazilian Atlantic forest, then found that, as predicted, the FA in skill morphology was negatively correlated with the habitat suitability, as measured using a species distribution model.

As well as having some interesting results, this paper highlights how GIS is starting to play an important role in areas of ecology which we would not traditionally associate with spatial analysis. After all, those studying morphology rarely think about whether they need to consider spatial elements in their analyses, other than broad location where a specimen was collected. However, it is just these types of areas where GIS can provide interesting, and unexpected, benefits, just as it did for Maestri’s study of fluctuating asymmetry.

========================

Dr Colin D. MacLeod,
Founder, GIS In Ecology
========================

Paper Of The Week: Lin et al. 2015. Classification of Tree Species in Overstorey Canopy of Subtropical Forest Using QuickBird Images

3 Jun

Remote sensing has become an integral part of using GIS in biological research, and this week’s paper of the week is a nice example of how just how detailed the information you can get from remote sensing can be. This paper is Lin et al. (2015) from PLoS One and is titled ‘Classification of Tree Species in Overstorey Canopy of Subtropical Forest Using QuickBird Images‘. In it, the authors set out to see if they could take high spatial resolution satellite imagery and use them to identify individual trees to the species level in a sub-tropical forest in Taiwan.

This may sound like an unlikely thing to be able to do, but it’s based on the idea that the leaves of different species of trees will reflect different wave lengths of light in slightly different ways, and while it takes some fairly fancy processing, it turn out that it’s possible. In fact, with the right images and the right processing, Lin et al. were able to separate out 40 different species of trees with a pretty high level of accuracy.

While this is impressive stuff in its own right, this isn’t the only reason I selected it as my paper of the week. I also selected it because of the potential that this type of processing offers to biologists. Through the processing and analysis of high spatial resolution images, it should possible to pull out almost any type of information that a biologist might ever need to know.

One example of this is something I’ve been pondering for some time now. This is how to assess the productivity of trees in an oak woodland as part of a study of breeding success in hole-nesting birds. The research question here is whether breeding success is related to the number of caterpillars found in the territory which surrounds each nest box. Now, measuring the number of caterpillars found around 300 nest boxes is just not feasible, but given that the number of caterpillars should be related to the productivity of the trees on which they are feeding, so this could be used as a proxy, and using the type of processing of high spatial resolution satellite imagery done by Lin et al. (2015) potentially provides a way to extract this information automatically. I haven’t yet had the chance to see whether this is, indeed, the case, but I’m looking forward to giving it a go (or more likely finding an eager student and persuading them into taking the project on!)

So, I think the take home point from this week’s paper is that it’s impressive just how much information can be extracted from high spatial resolution satellite images, and in many cases, all that’s needed is a bit of imagination, followed up by some intense work as you work out exactly how to pull out just the information you require to help you answer your research questions.

========================

Dr Colin D. MacLeod,
Founder, GIS In Ecology
========================

Paper Of The Week: Habel et al. 2015. Fragmentation genetics of the grassland butterfly Polyommatus coridon: Stable genetic diversity or extinction debt?

27 May

Back when I was an undergraduate, I was never that interested in genetic analysis: it seemed that it was all too much about the molecules and not enough about the biology. Worse, as someone who was very much a field ecologist even then, it seemed to be carried out by a bunch of pipette pushers who rarely ventured beyond their list of four alternating letters that make up the genetic code of all living things, let alone outside their laboratories. In short, while I could understand its importance for things like taxonomy and cladistics, I found it hard to see how it could be useful for doing the types of research I wanted to do.

This all changed, however, with the introduction of landscape genetics. What is landscape genetics? Well, most simply put, it’s taking the results of genetic analyses and laying them over the spatio-temporal environment from which the samples were taken. By doing this, you can start looking at not just how animals move through their environments, but also how their genes move through it. Suddenly, all that talk of minimum viable populations, genetic bottlenecks and gene flow takes on a spatial perspective, and by including information about the landscapes alongside the genetic information we can start to understand the processes of extinction and speciation in a way that we never have before.

This brings me round to my choice of paper of the week for this week.  It’s Habel et al. 2015. Fragmentation genetics of the grassland butterfly Polyommatus coridon: Stable genetic diversity or extinction debt? Why have I selected this paper? It’s because of the way it combines genetic analyses and spatial information to produce a result that, in my opinion, is greater than the sum of each individual part.

The starting point for Habel et al. (2015) is the general assumption that habitat fragmentation affects the viability of populations and so has a pivotal role to play in conservation. Given our current understanding, this should be particularly true for habitat specialists that are more likely to have both a naturally patchy distribution, and to be impacted by fragmentation. All this means, given conventional wisdom, that habitat fragmentation should lead a fragmentation of genetic populations, a reduction in local genetic diversity, and a resulting increased risk of extinction.

So far, so straight-forward, but then we get to the results of this particular study: when the authors looked at a specialist grassland butterfly, they found that genetic diversity wasn’t linked with habitat size, habitat
connectivity, or census population size. Thus, they found something very unexpected, given our current understanding of things.

How do they go about trying to explain this? The authors come up with two solutions. The first is that despite the fragmentation between populations and the specialisation in terms of habitat preferences, the species is somehow managing to keep up the levels of gene flow expected of more widespread  generalist species. For a mobile species like a butterfly, this is possible, but if true, it would suggest that dispersion and gene flow are not as limited by the surrounding landscape as we might assume, even for habitat specialists.

The second possibility is perhaps more interesting. This is that there is lag between the fragmentation of a species with a relatively continuous historic distribution into small isolated populations and the loss of genetic diversity. If this is true, then it would suggest that we could easily overlook the negative effects of fragmentation on population viability because we might mistake the effects of historic gene flow for evidence of current gene flow even in the light of habitat fragmentation. Thus, we may make false assumptions about the impacts of specific human activities, such as habitat destruction, on the long term viability of individual species and populations, and that would not be good.

As you will have guessed from the start of this post, I am no geneticist, so I cannot say which of these is more likely to be correct, but simply the possibility that the second option could be true means that measuring the impacts of things like habitat fragmentation on population viability might be much more difficult to do in anything close to real time than we might otherwise assume. And without the further integration of GIS into genetic studies, we will have no way test which, if either, is correct. Thus, because of landscape genetics, GIS has the potential to be as important to genetic studies as it is to many other areas of ecology.

========================

Dr Colin D. MacLeod,
Founder, GIS In Ecology

========================

Paper Of The Week: Pauli et al. 2015. The simulated effects of timber harvest on suitable habitat for Indiana and northern long-eared bats

20 May

Ecology is sometimes criticised for being an observational science rather than a truly predictive one. That is, much of what we, as ecologists, do is to try to explain existing or past patterns, rather than use our knowledge to predict what is likely to happen in the future or under different conditions. When combined with conservation, this means that ecologists are often left to implement conservation strategies reactively, after something has happened or changed, rather than pro-actively, before the change occurs in the first place. This is unfortunate as, if done properly, a pro-active approach is likely to lead to much better conservation and management outcomes than reactive ones.

However, with the advent of new statistical approaches, the availability of cheap, powerful personal computers and advances in GIS, our ability to make the types of predictions needed to test whether specific changes to the environment, especially those made by humans or those under our control, might have on specific ecosystems or species before they occur is finally within the reach of almost every ecologist. Yes, the techniques and skills might be difficult to get your head round at first, but the results are often more than worth the effort.

A great example of this is a recent paper by Pauli et al. (2015) from the journal Ecosphere titled The simulated effects of timber harvest on suitable habitat for Indiana and northern long-eared bats. Bats, like many other species, can be impacted heavily by human actions in forestry management, but what timber harvesting strategies are likely to be best for their conservation? And which are likely to be the worst?

While I’m a marine biologist at heart, this is a subject I’ve dabbled in before. This is one of the reasons I found Pauli et al.’s paper so interesting. While, in our own study, we looked at historic effects of forest management on bats, they looked at future ones, and specifically, they combined species distribution modelling and forest succession models to compare the likely impacts of nine different timber harvesting strategies on two bat species over a prolonged period of time. They also considered the differences that impacts might have on nocturnal foraging habitat and diurnal roosting habitats, an interesting extension to the more traditional approach of just looking at one, or a combination of, habitat requirements rather than looking separately at each individual component.

So what did they find? Well, you’ll have to read the paper to get the full details, but in summary, they found that the overall suitability of habitat was primarily driven by the requirements for diurnal rather than nocturnal habitats, that what might be the best strategy for one species may not necessarily be the best strategy for another, and that if you wish to have the best outcome for multiple species, you might want to select a timber harvesting strategy that was somewhere between theses two.

While these results are relatively complex and at times contradictory in terms of their impacts on the two species, they do provide concrete information that can be used to ensure that any timber-harvesting strategies are implemented in such a way as to have the best outcome possible for all species being considered, and that is something that is always better to know before you implement them, rather than afterwards.

Of course, as with any predictions which you’re going to use for setting conservation or management strategies, you have to ensure that your predictions are accurately, but as long as you have the appropriate spatial and temporal validation as part of the investigation process, this issue can often be easily avoided. Then all that’s left is to say: welcome to the world of predictive ecology.

========================

Dr Colin D. MacLeod,
Founder, GIS In Ecology
========================

Paper Of The Week: Buschke et al. 2015. Simple mechanistic models can partially explain local but not range-wide co-occurrence of African mammals

13 May

When doing GIS, sometimes you can get so caught up in all the fancy things that you can do with it, that you forget that, just like statistics, while GIS can do many amazing things, it’s still just a tool which you can use to answer research questions which interest you. This is why some of my favourite examples of the practical application of GIS to biological research don’t necessarily contain huge amounts of complex GIS-based data manipulations, but instead just use some basic GIS processing to bring data together so they can be analysed to help investigate interesting questions.

In the case of this week’s paper of the week, the interesting question being investigated is: why are variations in species diversity often linked with variations in climate? It seems a straight-forward enough question, but it’s one that we really don’t yet have a satisfactory explanation for. This is where a recent study by Buschke et al. 2015 comes in. In this study, titled ‘Simple mechanistic models can partially explain local but not range-wide co-occurrence of African mammals‘ (Global Ecology and Biogeography doi: 10.1111/geb.12316), the authors sought to explore this very issue (a summary of this paper, containing some nice animations, written by the lead author, can be found here on the Solitary Ecologist blog).

As is often the case, the GIS work involved in this is well-hidden within the methodology, but it involves calculating species richness within individual grid cells so that the local diversity of mammals can be compared to local climatic conditions. As such, while the actual spatial processing is relatively basic and straight-forward, without GIS, this study would not have been possible. However, the term GIS isn’t even mentioned once. I point this out not as a criticism of the authors, but rather to highlight how the importance of GIS to individual studies, and to biology as a whole, can often be overlooked in preference to detailed descriptions and discussions of statistical analyses.

So, with that personal bugbear out of the way, what did the study actually find? Well, they found that the evidence suggests that climate doesn’t influence the ranges of individual species, which in turn determines species richness. Rather, they suggest that climate may influence how many species can persist in a local area, and it is this that then determines the variations in local biodiversity linked to variations in climate.

This is an interesting idea, and one which is worthy of further investigation, especially with other taxa, in parts of the world and in environments (this study only looked at terrestrial mammals in Africa). In particular, it would be interesting to see how this hypothesis transfers into the marine environment, and whether patterns of biodiversity in marine mammals follow the same rules as their terrestrial relatives. In marine mammals, there are clear relationships between biodiversity and water temperature, but no one has really come up with a decent explanation as to why and maybe this hypothesis could provide one.

Does this matter? Well, quite frankly, yes. If we’re to understand how climate change will affect local diversity of marine mammals (or indeed any other taxa), we need to understand why species diversity is linked to climate in the first place.  So, if there are any students out there looking for an interesting GIS-related project, this would be one that, following the methods laid out in Buschke et al., would be both relatively easy to conduct, and that could potentially play an important role in understanding how climate change is likely to impact marine mammals.

========================
Dr Colin D. MacLeod,
Founder, GIS In Ecology
========================

Paper Of The Week: : Nesterova et al. (2015) The Effect Of Experienced Individuals On Navigation By King Penguin Chick Pairs.

22 Apr

While GIS is often used in biology to study how species are distributed over large areas, or monitor the movements of individuals over long distances, it can also be used for studying biology at much smaller scales. This is nicely demonstrated by this week’s paper of the week: Nesterova et al. (2015) The Effect Of Experienced Individuals On Navigation By King Penguin Chick Pairs. Animal Behaviour, 104: 69 – 78.

In this neat little study, the researchers investigated how long it took king penguin chicks to return to their original locations after they were displaced. This is an important survival skill because if chicks get displaced while their parents are away foraging at sea, thy need to be able to get back to their proper place in the colony or their parents will not be able to find them again. Amongst other things, this paper found that the more experienced the chick, the quicker they were able to return to their rightful place.

In terms of GIS, it provides a nice example of how GIS analysis can be used to help study aspects of behaviour that are occurring at very fine scales. In addition, the analysis wasn’t conducted in traditional GIS software. Instead, it was conducted in R, an open source software package which is already widely used by biologists and ecologists for statistical analysis. While there are some potential pitfalls to its use, R is rapidly becoming an important tool for conducting GIS in biology as it allows the close integration of GIS and spatial statistical analyses in ways that are not currently possible in specialist GIS software packages.

========================
Dr Colin D. MacLeod,
Founder, GIS In Ecology
========================