How do we best preserve the world’s remaining biodiversity? That was the topic of a conference I attended last week at the Royal Society in London on ‘Phylogeny, extinction risk and conservation’. The two-day conference included a range of interesting presentations on global to regional conservation efforts.
Obviously the extinction story can be a depressing one—the Yangtze River Dolphin is most likely extinct and one in five plant species are threatened with extinction. However, even given the looming threats to biodiversity, there is a huge effort underway to make informed decisions about how to prevent further losses. Continue reading Keeping the tree of life intact→
We have a new paper out at MEE. It is a guide on how to use Joint Species Distribution Models (JSDMs) originally known (to us) as Multivariate Probit models (MVP), a name which thankfully didn’t stick.
Locating areas where species will likely persist in future climate changes has recently become a conservation priority. How do we find these areas? A good first step is to look for places that species persisted through past climate changes (often termed ‘refugia’). We think we may have identified mini or micro-refugia for trees on deep, protected soils in the Grampians ranges, Victoria. Continue reading Where in the landscape are the refugia?→
We have a new paper out in Ecography. The aim was to link functional traits to environmental gradients. There are existing methods that do this, but they generally involve multiple steps. We created a hierarchical model that effectively joins a species distribution model with species trait values in one step. We were quite happy with the model because it worked well-better than we anticipated for rare species-and, importantly, produced sensible and interpretable results. Here is one example.
Specific leaf area (SLA) represents a tissue allocation strategy of either growing quickly or growing slowly with more tissue devoted to protection or conserving resources. SLA modifies species responses to rock cover. So, species with low SLA (thick, tough leaves) tend to increase in occurrence on increasingly rocky areas. Species with higher SLA (flimsy leaves) tend to be found on deeper, less rocky soil (see Figure).
The y-axis label looks complicated, but it’s simply the expected change in probability of species occurrence for a given change in surface rock cover. (technically, this is a partial response)..
Some key aspects of the model are:
1- species trait values actually modify species responses to environmental gradients. This may be useful for improving species distribution models when trait values are known.
2- rare species borrowed strength from common species. Species that are uncommon or have restricted distributions are usually quite difficult or impossible to model. I think this type of multi-species modelling shows real promise in this area.
I’ve finally been coerced into the online world beyond email. This is my attempt at sharing some of my research and hopefully connecting with other people with similar interests. And, if the time I spent picking out the theme for my blog is any indication, this will also be a great procrastination tool.