Boasting about backyard biodiversity

The easiest way for an aspiring naturalist to explore wildlife is by stepping out into their own backyard. Try it yourself. As I write this, I can look through my window at a Karoo Thrush hopping about my garden. But this post is not about the tiny garden surrounding my current apartment, but rather about my childhood home. I was tremendously fortunate to grow up on a 60 hectare farm, where  first discovered my love for nature.

Between wrapping up my PhD and starting my current lecturing position, I spent a few months of unemployment back in the house I grew up in. During that time, I discovered the thrill of recording unobtrusive nocturnal critters using a camera trap. Every afternoon, I set up the camera trap and eagerly explored the footage the following morning. It was so much fun.

After enough time, even I was amazed by the variety of species that lived on this relatively small farm. Perhaps, I should rephrase that last sentence. You see, calling it a farm is not accurate because it hasn’t been used for agricultural in more than ten years. The last cows were removed back in 2004 and since then the land was left dormant and only managed to minimise the risk of wild fire.

Still, I captured footage of 18 different mammal species, which is remarkably high for such a small area. Moreover, the camera trap is unlikely to capture any footage of bats and small rodents, so the total mammal diversity is probably even higher. I decided to write up these observations and the results have just been published online in the African Journal of Ecology. Continue reading

Species distribution modelling is not as simple as you think

One of the most fruitful sub-fields in ecology is using climate variables to predict species’ geographic distributions. For the uninitiated, species distribution modelling assumes that species are limited in their distributions to suitable climate zones. By studying the environmental conditions where species are known to occur, you can infer the total geographic distribution by calculating the suitability of unsampled regions based on the environmental. Furthermore, using the same principle, species distribution modelling can forecast the effect of future climate change of the distribution of life on earth.

Unfortunately, studies have shown that these fancy climate-based techniques cannot consistently outperform much simpler ones based on spatial phenomena. For instance, spatial interpolation between point occurrences outperforms sophisticated climate-based predictions. Similarly, elaborate climate-based predictions perform no better than expected from random chance.

The trouble lies in the spatially-structured world we live in. Species distributions, especially at large spatial scales, are spatially-autocorrelated due to constrained dispersal. Similarly, climate variables are also spatially structured because the meteorological processes at proximal regions are generally more similar than those at distant sites.

When trying to link species distributions to climate conditions, the challenge lies is separating spatial and environmental correlations in species distributions. Specifically, we should identify three patterns in the geographical species distributions.

  • We must first identify ‘true’ correlations with the environment, which are independent of spatial patterns (E|S).
  • Next, we must identify the environmental-associations that also have a strong spatial structure (E∩S). This is known as exogenous spatial autocorrelation because it is due to autocorrelation is the underlying variables.
  • Finally, we need to identify spatial patterns that are completely independent of environmental conditions (S|E). This is called endogenous spatial autocorrelation because it supposedly stems from spatial processes, such as dispersal.

In our latest study just published online at Ecography, we set out to quantify the degree of environmental correlation, exogenous and endogenous spatial autocorrelation in the distributions of 4 423 species of amphibians, reptiles, birds and mammals in Africa. Continue reading

Camera trap critters: Part 2

I’ve just returned to South Africa, where I’ll spend the next few months adding the final touches to my PhD thesis. Of course, being back home means that I spend my free time playing with my camera trap. I thought I’d share two of my favourite videos from the last few nights.

The first is a very short clip of the small-spotted genet (Genetta genetta). I’m very pleased about spotting this beautiful carnivore because I regularly found the remains of laughing doves and helmeted guineafowl and always assumed that they were killed by feral cats. It’s always nice to spot natural predators.

The second clip is of a male Impala (Aepyceros melampus) scent-marking his territory.


Classical camera trap critter compilation

Two years ago, I treated myself with a Bushnell 8MP camera trap. I bought this bit of kit purely for my own amusement – without any scientific intentions – but even I can’t believe how much fun I’ve had using it during the last two summers spent at home in South Africa. Below is a little video showcasing some of the cool animals I’ve managed capture on film.

The are some things to consider: I only have one camera so I needed 6 weeks of trapping (over two summers) for this 2 minute compilation. Not that I am complaining; I loved crawling on my belly to set up the camera in a rocky cave. Furthermore, this was all filmed on our family farm – not a nature reserve – so  I am sorry to disappoint if you were expecting the big five (Try the BBC, perhaps David Attenborough can provide that?). Lastly, please excuse my amateurish efforts because I know very little about video editing and even less about classical music.

How many species can you identify?