Two Worlds: contrasting Australia’s temperate regions

Temperate Australia

Australia is renowned for its unique diversity of species, and likewise for the diversity of ecosystems across the island continent. Although many would typically associate Australia with the golden sandy beaches, palm trees and warm weather of the tropical east coast, other ecosystems also hold both beautiful and interesting characteristics. Even the regions that might typically seem the dullest – the temperate zones in the southern portion of the continent – themselves hold unique stories of the bizarre and wonderful environmental history of Australia.

The two temperate zones

Within Australia, the temperate zone is actually separated into two very distinct and separate regions. In the far south-western corner of the continent is the southwest Western Australia temperate zone, which spans a significant portion. In the southern eastern corner, the unnamed temperate zone spans from the region surrounding Adelaide at its westernmost point, expanding to the east and encompassing Tasmanian and Victoria before shifting northward into NSW. This temperate zones gradually develops into the sub-tropical and tropical climates of more northern latitudes in Queensland and across to Darwin.


Labelled Koppen-Geiger map
The climatic classification (Koppen-Geiger) of Australia’s ecosystems, derived from the Atlas of Living Australia. The light blue region highlights the temperate zones discussed here, with an isolated region in the SW and the broader region of the SE as it transitions into subtropical and tropical climates northward.

The divide separating these two regions might be familiar to some readers – the Nullarbor Plain. Not just a particularly good location for fossils and mineral ores, the Nullarbor Plain is an almost perfectly flat arid expanse that stretches from the western edge of South Australia to the temperate zone of the southwest. As the name suggests, the plain is totally devoid of any significant forestry, owing to the lack of available water on the surface. This plain is a relatively ancient geological structure, and finished forming somewhere between 14 and 16 million years ago when tectonic uplift pushed a large limestone block upwards to the surface of the crust, forming an effective drain for standing water with the aridification of the continent. Thus, despite being relatively similar bioclimatically, the two temperate zones of Australia have been disconnected for ages and boast very different histories and biota.

Elevation map of NP.jpg
A map of elevation across the Australian continent, also derived from the Atlas of Living Australia. The dashed black line roughly outlines the extent of the Nullarbor Plain, a massively flat arid expanse.

The hotspot of the southwest

The southwest temperate zone – commonly referred to as southwest Western Australia (SWWA) – is an island-like bioregion. Isolated from the rest of the temperate Australia, it is remarkably geologically simple, with little topographic variation (only the Darling Scarp that separates the lower coast from the higher elevation of the Darling Plateau), generally minor river systems and low levels of soil nutrients. One key factor determining complexity in the SWWA environment is the isolation of high rainfall habitats within the broader temperate region – think of islands with an island.

SSWA environment.jpg
A figure demonstrating the environmental characteristics of SWWA, using data from the Atlas of Living AustraliaLeft: An elevation map of the region, showing some mountainous variation, but only one significant steep change along the coast (blue area). Right: A summary of 19 different temperature and precipitation variables, showing a relatively weak gradient as the region shifts inland.

Despite the lack of geological complexity and the perceived diversity of the tropics, the temperate zone of SWWA is the only internationally recognised biodiversity hotspot within Australia. As an example, SWWA is inhabited by ~7,000 different plant species, half of which are endemic to the region. Not to discredit the impressive diversity of the rest of the continent, of course. So why does this area have even higher levels of species diversity and endemism than the rest of mainland Australia?

speciation patterns in SWWA.jpg
A demonstration of some of the different patterns which might explain the high biodiversity of SWWA, from Rix et al. (2015). These predominantly relate to different biogeographic mechanisms that might have driven diversification in the region, from survivors of the Gondwana era to the more recent fragmentation of mesic habitats.

Well, a number of factors may play significant roles in determining this. One of these is the ancient and isolated nature of the region: SWWA has been separated from the rest of Australia for at least 14 million years, with many species likely originating much earlier than this. Because of this isolation, species occurring within SWWA have been allowed to undergo adaptive divergence from their east coast relatives, forming unique evolutionary lineages. Furthermore, the southwest corner of the continent was one of the last to break away from Antarctica in the dismantling of Gondwana >30 million years ago. Within the region more generally, isolation of mesic (wetter) habitats from the broader, arid (xeric) habitats also likely drove the formation of new species as distributions became fragmented or as species adapted to the new, encroaching xeric habitat. Together, this varies mechanisms all likely contributed in some way to the overall diversity of the region.

The temperate south-east of Australia

Contrastingly, the temperate region in the south-east of the continent is much more complex. For one, the topography of the zone is much more variable: there are a number of prominent mountain chains (such as the extended Great Dividing Range), lowland basins (such as the expansive Murray-Darling Basin) and variable valley and river systems. Similarly, the climate varies significantly within this temperate region, with the more northern parts featuring more subtropical climatic conditions with wetter and hotter summers than the southern end. There is also a general trend of increasing rainfall and lower temperatures along the highlands of the southeast portion of the region, and dry, semi-arid conditions in the western lowland region.

MDB map
A map demonstrating the climatic variability across the Murray-Darling Basin (which makes up a large section of the SE temperate zone), from Brauer et al. (2018). The different heat maps on the left describe different types of variables; a) and b) represent temperature variables, c) and d) represent precipitation (rainfall) variables, and e) and f) represent water flow variables. Each variable is a summary of a different set of variables, hence the differences.

A complicated history

The south-east temperate zone is not only variable now, but has undergone some drastic environmental changes over history. Massive shifts in geology, climate and sea-levels have particularly altered the nature of the area. Even volcanic events have been present at some time in the past.

One key hydrological shift that massively altered the region was the paleo-megalake Bungunnia. Not just a list of adjectives, Bungunnia was exactly as it’s described: a historically massive lake that spread across a huge area prior to its demise ~1-2 million years ago. At its largest size, Lake Bungunnia reached an area of over 50,000 km­­­2, spreading from its westernmost point near the current Murray mouth although to halfway across Victoria. Initially forming due to a tectonic uplift event along the coastal edge of the Murray-Darling Basin ~3.2 million years ago, damming the ancestral Murray River (which historically outlet into the ocean much further east than today). Over the next few million years, the size of the lake fluctuated significantly with climatic conditions, with wetter periods causing the lake to overfill and burst its bank. With every burst, the lake shrank in size, until a final break ~700,000 years ago when the ‘dam’ broke and the full lake drained.

Lake Bungunnia map 2.jpg
A map demonstrating the sheer size of paleo megalake Bungunnia at it’s largest extent, taken from McLaren et al. (2012).

Another change in the historic environment readers may be more familiar with is the land-bridge that used to connect Tasmania to the mainland. Dubbed the Bassian Isthmus, this land-bridge appeared at various points in history of reduced sea-levels (i.e. during glacial periods in Pleistocene cycle), predominantly connecting via the still-above-water Flinders and Cape Barren Islands. However, at lower sea-levels, the land bridge spread as far west as King Island: central to this block of land was a large lake dubbed the Bass Lake (creative). The Bassian Isthmus played a critical role in the migration of many of the native fauna of Tasmania (likely including the Indigenous peoples of the now-island), and its submergence and isolation leads to some distinctive differences between Tasmanian and mainland biota. Today, the historic presence of the Bassian Isthmus has left a distinctive mark on the genetic make-up of many species native to the southeast of Australia, including dolphins, frogs, freshwater fishes and invertebrates.

Bass Strait bathymetric contours.jpg
An elevation (Etopo1) map demonstrating the now-underwater land bridge between Tasmania and the mainland. Orange colours denote higher areas whilst light blue represents lower sections.

Don’t underestimate the temperates

Although tropical regions get most of the hype for being hotspots of biodiversity, the temperate zones of Australia similarly boast high diversity, unique species and document a complex environmental history. Studying how the biota and environment of the temperate regions has changed over millennia is critical to predicting the future effects of climatic change across large ecosystems.

The MolEcol Toolbox: Species Distribution Modelling

Where on Earth are species?

Understanding the spatial distribution of species is a critical component for many different aspects of biological studies. Particularly for conservation, the biogeography of regions is a determinant factor for designating and managing biodiversity hotspots and management units. Or understanding the biogeographical mechanisms that have shaped modern biodiversity may allow us to understand how species will change under future climate change scenarios, and how their distributions will (and have) shift(ed).

Typically, the maximum distribution of species is based on their ecological tolerances: that is, the most extreme environments they can tolerate and proliferate within. Of course, there are a huge number of other factors on top of just natural environment which can shape species distributions, particularly related to human-induced environmental changes (or introducing new species as invasive pests, which we seem to be good at). But exactly where species are and why they occur there are intrinsically linked to the adaptive characteristics of species relative to their environment.

Species distribution modelling

The connection of a species distribution with innate environmental tolerances is the background for a type of analysis we call species distribution modelling (SDM) or environmental niche modelling (ENM). Species distribution modelling seeks to correlate the locations where a species occurs with the local environment around those sites to predict where the species should occur. This is an effective tool for trying to understand the distribution of species that might be tricky to study so thoroughly in the wild; either because they are hard to catch, live in very remote areas, or because they are highly threatened. There are a number of different algorithms and data types that will work with SDM, and there is always ongoing debate about ‘best practices’ in modelling techniques.

SDM method.jpg
The generalised pipeline of SDM, taken from Svenning et al. (2011). By correlating species occurrence data (bottom left) with environmental data (top left), we can develop a model that describes how the species is distributed based on environmental limitations (top right). From here, we can choose to validate the model with other methods (top and bottom centre) or see how the distribution might change with different environmental changes (e.g. bottom right).

A basic how-to on running SDM

The first major component that is needed for SDM is the occurrence data. Some methods will work with presence-only data: that is, a map of GPS coordinates which describes where that species has been found. Others work with presence-absence data, which may require including sites of known non-occurrence. This is an important aspect as the non-occurring sites defines the environment beyond the tolerance threshold of the species: however, it’s very likely that we haven’t sampled every location where they occur, and there will be some GPS co-ordinates that appear to be absent of our species where they actually occur. There are some different analytical techniques which can account for uneven sampling across the real distribution of the species, but they can get very technical.

An example of species (occurrence only) locality data (with >72,000 records) for the koala (Phascolarctos cinereus) across Australia, taken from the Atlas of Living Australia. Carefully checking the locality data is important, as visual inspection clearly shows records where koalas are not native: they might have been recorded from an introduced individual, given incorrect GPS coordinates or incorrectly identified (red circles).

The second major component is our environmental data. Typically, we want to include environmental data for the types of variables that are likely to constrain the distribution of our species: often temperature and precipitation variables are included, as these two largely predict habitat types. However, it can also be important to include non-climatic variables such as topography (e.g. elevation, slope) in our model to help constrain our predictions to a more reasonable area. It is also important to test for correlation between our variables, as using many variables which are highly correlated may ‘overfit’ the model and underestimate the range of the distribution by placing an unrealistic number of restrictions on the model.

An example of some of the environmental data/maps we might choose to include in a species distribution model, obtained from the Atlas of Living AustraliaA) Mean annual temperature. B) Mean annual precipitation. C) Elevation. D) Weighted distance to nearest waterbody (e.g. rivers, lakes, streams).

Our SDM analysis of choice (e.g. MaxEnt) will then use various algorithms to build a model which best correlates where the species occurs with the environmental variables at those sites. The model tries to create a set of environmental conditions that best encapsulate the occurrence sites whilst excluding the non-occurrence sites from the prediction. From the final model, we can evaluate how strong the effect of each of our variables is on the distribution of the species, and also how well our overall model predicts the locality data.

Projecting our SDM into the past and the future

One reason to use SDM is the ability to project distributions onto alternative environments based on the correlative model. For example, if we have historic data (say, from the last glacial maximum, 21,000 years ago), we can use our predictions of how the species responds to climatic variables and compare that to the environment back then to see how the distribution would have shifted. Similarly, if we have predictions for future climates based on climate change models, we can try and predict how species distributions may shift in the future (an important part of conservation management, naturally).


Correct LGM projection example.png
An example of projecting a species distribution model back in time (in this case, to the Last Glacial Maximum 21,000 years ago), taken from Pelletier et al. (2016). On the left is the contemporary distribution of each species; on the right the historic projection. The study focused on three different species of American salamanders and how they had evolved and responded to historic climate change. This figure clearly shows how the distribution of the species have changed over time, particularly how the top two species have significantly reduced in distribution in modern times.


Species distribution modelling continues to be a useful tool for conservation and evolution studies, and improvements in analytical algorithms, available environmental data and increased sampling of species will similarly improve SDM. Particularly, improvements in environmental projections from both the distant past and future will improve our ability to understand and predict how species will change, and have changed, with climatic changes

Surviving the Real-World Apocalypse

The changing world

Climate change seems to be the centrefold of a large amount of scientific research and media attention, and rightly so: it has the capacity to affect every living organism on the planet. It’s our duty as curators and residents of Earth to be responsible for our influences on the global environmental stage. While a significant part of this involves determining causes and solutions to our contributions to climate change, we also need to know how extensive the effects will be: for example, how can we predict how well species will do in the future?

Predicting the effect of climate change on all of the world’s biodiversity is an immense task. Climate change itself is a complicated system, and causes diverse, interconnected and complex alterations to both global and local climate. Adding on top of this, though, is that climate affects different species in different ways; where some species might be sensitive to some climatic variables (such as rainfall, available sunlight, seasonality), others may be more tolerant to the same factors. But all living things share some requirements, so surely there must be some consistency in their responses to climate change, right?

Apocalypse 2
Lucky for Mr Fish here, he’s responding to a (very dramatic) climate change much, much better than his bird counterpart.

How predictable are species responses to climate change?

Well, evidence would surprisingly suggest not. Many species, even closely related ones, can show very different responses to the exact same climatic pressures or biogeographical events. There are a number of different traits that might affect a species’ ability to adapt, particularly their adaptive genetic diversity (which underpins ‘adaptive potential’). Thus, we need good information of a variety of genetic, physiological and life history traits to be able to make predictions about how likely a species is to adapt and respond to future (and current) climate changes.

Although this can be hard to study in species of high extinction risk (getting a good number of samples is always an issue…), traditional phylogeographic methods might help us to make some comparisons. See, although the modern Earth is rapidly changing (undoubtedly influenced by human society), the climate of the globe has always varied to some degree. There has always been some tumultuousness in the climate and specific Earth history events like volcano eruptions, sea-level changes, or glaciation periods (‘ice ages’) have had diverse effects on organisms globally.

Using comparative phylogeography to predict species responses

One tool for looking at how different species have, in the past, responded to the same biogeographical force is the domain of ‘comparative phylogeography’. Phylogeography itself is something we have discussed before: the ‘comparative’ aspect simply means comparing (with complex statistical methods) these patterns across different and often unrelated species to see how universal (‘congruent’) or unique (‘incongruent’) these patterns are among species. The more broadly we look at the species community in the region, the more we can observe widespread effects of any given environmental or geographical event: if we only look at fish, for example, we might not to be able to infer what response mammals, birds or invertebrates have had to our given event. Sometimes this still meets the scale we wish to focus; other times, we want to see how all the species of an area have been affected.

Actual island diagram
An (very busy) example of different species responses to a single environmental event. In this example, we have three species (a fish, a lizard, and a bird) all living on the same island. In the middle of the island, there is a small mountain range (A). At this point in time, all three species are connected across the whole island; fish can travel via lakes and wetlands (green arrows), lizards can travel across the land (blue arrow) and birds can fly anywhere. However, as the mountain range grows with tectonic movements, the waterways are altered and the north and south are disconnected (B). The fish species is now split into two evolutionarily separate groups (green and gold), while lizards and birds are not. As the range expands further, however, the dispersal route for lizards is cut off, causing them to eventually also become separated into blue and black groups (C). Birds, however, have no problems flying over the mountain range and remain one unified and connected orange group over time (D). Thus, each species has a different response to the formation of the mountain range.
Evol history of island diagram
The phylogenetic history of the three different species in the above example. As you can see, each lineage has a slightly different pattern; birds show no divergences at all, whereas the timing of the lizard and fish N/S splits are different (i.e. temporally incongruent).

Typically, comparative phylogeographic studies have looked at the neutral components of species’ evolution (as is the realm of traditional phylogeography). This includes studying the size of populations over time, how well connected they are and were, what their spatial patterns are and how these relate to the environment. Comparing all of these patterns across species can allow us to start painting a fuller picture of the history of biota in a region. In this way, we can start to see exactly which species have shown what responses and start to relate these to the characteristics that allowed them to respond in that certain way (and including adaptation in our studies). So, what kinds of traits are important?

What traits matter? Who wins?

Often, we find that life history traits of an organism better dictates how they will respond to a certain pressure than other factors such as phylogeny (e.g. one group does not always do better than another). Instead, individual species with certain physical characteristics might handle the pressure better than others. For example, a fish, bird and snake that are all able to tolerate higher temperatures than other fish, birds or snakes in that region are more likely to survive a drought. In this case, none of the groups (fish, birds or snakes) inherently do better than the other two groups. Thus, it can be hard to predict how a large swathe of species will respond to any given environmental change, unless we understand the physical characteristics of every species.

Climate change risk flowchart
A generalised framework of various factors, and their interactions, on the vulnerability of species under current and future climate changes by Williams et al. 2018. The schematic includes genetic, ecological, physical and environmental factors and how these can interact with one another to alleviate or exacerbate the risk of extinction.

We can also see that other physiological or ecological traits, such as climatic preferences and tolerance thresholds, can be critical for adapting to climatic pressures. Naturally, the genetic diversity of species is also an important component underlying their ability to adapt to these new selective pressures and to survive into the future. Trying to incorporate all of these factors into a projected model can be difficult, but with more data of higher quality we can start to make more refined predictions. But by understanding how particular traits influence how well a species may adapt to a changing climate, as well as knowing the what traits different species have, might just be the key to predicting who wins and who dies in the real-world Game of Thrones.