Beyond inappropriate fire regimes: A synthesis of fire‐driven declines of threatened mammals in Australia

Abstract

Fire can promote biodiversity, but changing patterns of fire threaten species worldwide. While scientific literature often describes ‘‘inappropriate fire regimes’’ as a significant threat to biodiversity, less attention has been paid to the characteristics that make a fire regime inappropriate. We go beyond this generic description and synthesize how inappropriate fire regimes contribute to declines of animal populations using threatened mammals as a case study. We developed a demographic framework for classifying mechanisms by which fire regimes cause population decline and applied the framework in a systematic review to identify fire characteristics and interacting threats associated with population declines in Australian threatened land mammals (n = 99). Inappropriate fire regimes threaten 88% of Australian threatened land mammals. Our review indicates that intense, large, and frequent fires are the primary cause of fire‐related population declines, particularly through their influence on survival rates. However, several species are threatened by a lack of fire, and there is considerable uncertainty in the evidence base for fire‐related declines. Climate change and predation are documented or predicted to interact with fire to exacerbate mammalian declines. This demographic framework will help target conservation actions globally and will be enhanced by empirical studies of animal survival, movement, and reproduction.

What environmental and climatic factors influence multidecadal fire frequency?

“…Altered fire regimes pose a major risk to ecosystems (Flores & Holmgren, 2021;Syphard et al, 2022), biodiversity (Keeley & Pausas, 2019;Kelly et al, 2020), and human life and property (Bushfire Royal Commission, 2020;Gibbons et al, 2012;Moritz et al, 2014). Understanding how they might be changing is critical to making informed decisions about both fire management and ecosystem management (Levine et al, 2022;Santos et al, 2022). Our empirical analyses revealed that fire frequency in Victoria was heterogeneous both in time and in space as indicated by evidence of: (1) a change in the frequency of wildfires over the past 40 years (between 1981 and 2020), with a marked increase in the past 20 years (2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016)(2017)(2018)(2019)(2020) relative to the 20 years prior (1981)(1982)(1983)(1984)(1985)(1986)(1987)(1988)(1989)(1990)(1991)(1992)(1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000); (2) changes in fire frequency not being spatially uniform, with increases more pronounced i...…”

Quantifying the direct fire threat to a critically endangered arboreal marsupial using biophysical, mechanistic modelling

“…Byram's fire intensity is often used as a metric for decision‐making in fire management, as it ostensibly represents the heat output of the fire (Alexander, 1982). As per the conservation advice for ngwayir, fire risk to fauna is expected to be less when fires are of low intensity (Santos et al, 2022). As shown here, however, Byram's intensity was unrelated to mortality rates, with the slower spread of ‘low intensity’ fires actually related to torching events (Figure 3a–d).…”

“…This included 55 threatened species (Wintle et al, 2020). Such changing fire regimes – in particular the increase in intense, large and frequent fires – directly threaten 88% of Australia's threatened land mammals (Santos et al, 2022). In response to these realities, changes to fire regimes in Australia have been recognized nationally as a Key Threatening Process (KTP) (DAWE, 2022).…”

“…In response to these realities, changes to fire regimes in Australia have been recognized nationally as a Key Threatening Process (KTP) (DAWE, 2022). Fire regimes are defined by fire frequency, seasonality, type and intensity (Gill, 1975), and these can affect animals directly (first‐order effects) such as through heat and smoke, or indirectly (second‐order effects) through changes to habitat, predator–prey balances, food availability and other factors (Santos et al, 2022).…”

“…Mass mortality events such as the direct death of 17 million vertebrates in the Brazilian Pantanal (Tomas et al, 2021) have been recorded, but the absence of longitudinal data excludes these from the global average. In the absence of longitudinal data, studies more frequently ascertain broad population changes, which may result largely from indirect effects (Santos et al, 2022).…”