Investigating the effects of fire management on savanna biodiversity with grid‐based spatially explicit population simulations

The development of effective fire management regimes is a global challenge. New research from Davies and colleagues aims to develop a flexible modelling approach to investigate how the spatiotemporal application of fire influences savanna biodiversity.

Despite the integral role that fire plays in the functioning of ecosystems around the world, there remain few areas where the occurrence of fire has not been disrupted, in some cases irreversibly.

Be it through land clearing, invasive weeds, the dispossession of Indigenous people or climate change, this disruption is a contributing factor to the catastrophically high rate of species extinction that is currently jeopardising the functioning of ecosystems on which all life depends.

Given the ongoing collapse of biodiversity across northern Australian savannas, there is an urgent need to better understand the ecological consequences of prescribed fire management.

a low intensity early dry season savanna fire
A low intensity early dry season savanna fire. Photo: Hugh Davies

The effects of fire on biodiversity are often complex, indirect, and driven by numerous factors that are spatially- and temporally-variable. Not surprisingly, this complexity poses significant challenges when trying to identify the optimal approach to fire management. These challenges have often resulted in management approaches being underpinned by vague notions of maximising pyrodiversity which lack clear on-ground targets, guidance on how such targets can be achieved, or the capacity for meaningful evaluation.

The highly dynamic nature of fire, the logistical difficulties in replicating ‘real-world’ fire experiments, and the need to understand population changes at large spatiotemporal scales, make computer simulations a particularly useful tool for identifying optimal management strategies. Crucially, advances in computer processing power enables increasingly complex simulations that realistically model critical ecological processes.

In our study, we used existing data from a landscape-scale fire experiment to develop spatiotemporally explicit population simulations using a new R package, steps, for three mammal species across the Kapalga area of Kakadu National Park.

Davis Fig 1
Common brushtail possum (Trichosurus vulpecula). Photo: Georgina Neave

We simulated how populations of the common brushtail possum (Trichosurus vulpecula), grassland melomys (Melomys burtoni), and northern brown bandicoot (Isoodon macrourus) were expected to change between 1995 and 2015 in response to the fire patterns observed at Kapalga, and under a hypothetical management scenario of extensive prescribed burning.

Our models predicted a substantial decline in all three species, suggesting that the fire patterns observed at Kapalga were not conducive with the persistence of native mammal populations. Our prescribed burning scenario had little effect on the predicted population trajectory of the common brushtail possum and grassland melomys, but markedly improved the population trajectory of the northern brown bandicoot.

bandicoot_baseline 1
Predicted trajectory of northern brown bandicoot population under the fire patterns that occurred across the Kapalga area of Kakadu between 1995 and 2015
bandicoot_AEF 2
Predicted trajectory of northern brown bandicoot under a management scenario of extensive prescribed burning across the Kapalga rea of Kakadu National Park

These inconsistencies highlight the need for a nuanced approach to fire management across northern Australian savannas, that is tailored to local conditions and management objectives.

The modelling approach outlined here provides a basis for identifying fire patterns that are beneficial for conserving biodiversity, thereby increasing our capacity to establish clear targets for prescribed fire management. Importantly, this approach is flexible and can be easily adapted to other taxa and fire-prone ecosystems.

Read the full Open Access article, Investigating the effects of fire management on savanna biodiversity with grid‐based spatially explicit population simulations, in Journal of Applied Ecology.

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