Journal articles on the topic 'Prescribed burning Australia Mathematical models'
To see the other types of publications on this topic, follow the link: Prescribed burning Australia Mathematical models.
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the top 15 journal articles for your research on the topic 'Prescribed burning Australia Mathematical models.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.
1
Florec, Veronique, Michael Burton, David Pannell, Joel Kelso, and George Milne. "Where to prescribe burn: the costs and benefits of prescribed burning close to houses." International Journal of Wildland Fire 29, no. 5 (2020): 440. http://dx.doi.org/10.1071/wf18192.
Full textAbstract:
Prescribed burning is used in Australia as a tool to manage fire risk and protect assets. A key challenge is deciding how to arrange the burns to generate the highest benefits to society. Studies have shown that prescribed burning in the wildland–urban interface (WUI) can reduce the risk of house loss due to wildfires, but the costs and benefits of different arrangements for prescribed burning treatments have rarely been estimated. In this study, we use three different models to explore the costs and benefits of modifying the spatial arrangement of prescribed burns on public land, using the south-west of Western Australia as a case study. We simulate two hypothetical scenarios: landscape treatments and WUI treatments. We evaluate the long-term costs and benefits of each scenario and compare the results from the three models, highlighting the management implications of each model. Results indicate that intensifying prescribed burning treatments in public land in the WUI achieves a greater reduction in damages compared with applying the majority of the treatments in rural areas. However, prescribed burning in the WUI is significantly more expensive and, despite additional benefits gained from this strategy, in most cases it is not the most economically efficient strategy.
2
Gould, JS, I. Knight, and AL Sullivan. "Physical Modelling of Leaf Scorch Height From Prescribed Fires in Young Eucalyptus Sieberi Regrowth Forests in South-Eastern Australia." International Journal of Wildland Fire 7, no. 1 (1997): 7. http://dx.doi.org/10.1071/wf9970007.
Full textAbstract:
Information on weather, fuel and fire behaviour were recorded on 56 experimental prescribed fires in young coastal silvertop ash (Eucalyptus sieberi) regrowth forest in south-east New South Wales, Australia. The thermal environment above the fire was measured in 14 of those fires. Existing plume models, based on the assumption of a uniformly burning line fire, were found to under-predict the temperature of the air rising into the canopy. An axially symmetric plume model, based on the observation that fires burning in non-uniform fuels are not uniformly burning line fires, was developed using standard plume rise equations. This model, called the Sporadic Axial Model (SAM), was calibrated using data from one fire. This model can be used to predict scorch height from known ambient temperature and Byram's fire line intensity. The SAM model suggests that scorch height will be greater for prescribed fires burnt under calm conditions than prescribed fires of the same intensity burnt under stronger wind conditions.
3
Howard, Trevor, Neil Burrows, Tony Smith, Glen Daniel, and Lachlan McCaw. "A framework for prioritising prescribed burning on public land in Western Australia." International Journal of Wildland Fire 29, no. 5 (2020): 314. http://dx.doi.org/10.1071/wf19029.
Full textAbstract:
A risk-based framework for targeting investment in prescribed burning in Western Australia is presented. Bushfire risk is determined through a risk assessment and prioritisation process. The framework provides principles and a rationale for programming fuel management with indicators to demonstrate that bushfire risk has been reduced to an acceptable level. Indicators provide targets for fuel management that are applicable throughout the state and can be customised to meet local circumstances. The framework identifies eight bushfire risk management zones having broad consistency of land use, fire environment and management approach, which combine to create a characteristic risk profile. Thirteen fuel types based primarily on structural attributes of the vegetation that influence fire behaviour are recognised and used to assign models for fuel accumulation and fire behaviour prediction. Each bushfire risk management zone is divided into fire management areas, based on the management intent. These are areas where fuels will be managed primarily to minimise the likelihood of fire causing adverse impacts on human settlements or critical infrastructure, to reduce the risk of bushfire at the landscape scale or to achieve other land management outcomes. Indicators of acceptable bushfire risk are defined for each fire management area and are modified according to the distribution of assets and potential fire behaviour in the landscape. Risk criteria established in the framework can be converted to spatially represented targets for fuel management in each zone and can be reported against to measure the effectiveness of the fuel management program. In areas where the primary intent is to reduce the risk of bushfire at the landscape scale, managers have flexibility to apply prescribed fire in ways that maintain and enhance ecosystem services, nature conservation and landscape values through variation in the seasonality, intensity and scale of planned burning.
4
Dyer, Rodd, and Mark Stafford Smith. "Ecological and economic assessment of prescribed burning impacts in semi-arid pastoral lands of northern Australia." International Journal of Wildland Fire 12, no. 4 (2003): 403. http://dx.doi.org/10.1071/wf03026.
Full textAbstract:
Pastoral managers in savannas face difficult decisions about trading off short-term use of grass biomass for animal production against its longer term use as fuel to manage tree–grass balances with fire. This study develops a model to represent the interactions between seasonal variability, fire behaviour, tree response, pasture growth and condition, grazing utilisation and animal productivity in a grazed savanna ecosystem. It successfully integrates simplified versions of several existing models, results of local research and expert knowledge to permit economic evaluation of tradeoffs given various fire treatments. The modelling framework also enabled the effects of wildfire events to be simulated and allowed fire and livestock management costs and revenue to be quantified. Applied to one site and climate sequence, the initial results assuming constant stocking rates show the importance of burning for the long-term maintenance of productivity, and suggest that some level of late dry season fire is needed for this. Net present values of applying different fire regimes over different time horizons emphasise the factors that pastoralists must take into account in making decisions about preferred fire regimes.
5
Storey, Michael, Owen Price, and Elizabeth Tasker. "The role of weather, past fire and topography in crown fire occurrence in eastern Australia." International Journal of Wildland Fire 25, no. 10 (2016): 1048. http://dx.doi.org/10.1071/wf15171.
Full textAbstract:
We analysed the influence of weather, time since fire (TSF) and topography on the occurrence of crown fire, as mapped from satellite imagery, in 23 of the largest wildfires in dry sclerophyll forests in eastern Australia from 2002 to 2013. Fires were analysed both individually and as groups. Fire weather was the most important predictor of crown consumption. TSF (a surrogate for fuel accumulation) had complex nonlinear effects that varied among fires. Crown fire likelihood was low up to 4 years post-fire, peaked at ~10 years post-fire and then declined. There was no clear indication that recent burning became more or less effective as fire weather became more severe. Steeper slope reduced crown fire likelihood, contrary to the assumptions of common fire behaviour equations. More exposed areas (ridges and plains) had higher crown fire likelihood. Our results suggest prescribed burning to maintain an average of 10 years’ TSF may actually increase crown fire likelihood, but burning much more frequently can be effective for risk reduction. Our results also suggest the effects of weather, TSF and slope are not adequately represented in the underlying equations of most fire behaviour models, potentially leading to poor prediction of fire spread and risk.
6
Log, Torgrim. "Modeling Drying of Degenerated Calluna vulgaris for Wildfire and Prescribed Burning Risk Assessment." Forests 11, no. 7 (July 14, 2020): 759. http://dx.doi.org/10.3390/f11070759.
Full textAbstract:
Research highlights: Moisture diffusion coefficients for stems and branches of degenerated Calluna vulgaris L. have been obtained and a mathematical model for the drying process has been developed and validated as an input to future fire danger modeling. Background and objectives: In Norway, several recent wildland–urban interface (WUI) fires have been attributed to climate changes and accumulation of elevated live and dead biomass in degenerated Calluna stands due to changes in agricultural activities, i.e., in particular abandonment of prescribed burning for sheep grazing. Prescribed burning is now being reintroduced in these currently fire prone landscapes. While available wildfire danger rating models fail to predict the rapidly changing fire hazard in such heathlands, there is an increasing need for an adapted fire danger model. The present study aims at determining water diffusion coefficients and develops a numerical model for the drying process, paving the road for future fire danger forecasts and prediction of safe and efficient conditions for prescribed burning. Materials and methods: Test specimens (3–6 mm diameter) of dead Calluna stems and branches were rain wetted 48 h and subsequently placed in a climate chamber at 20 °C and 50% relative humidity for mass loss recordings during natural convection drying. Based on the diameter and recorded mass versus time, diffusion coefficients were obtained. A numerical model was developed and verified against recoded mass loss. Results: Diffusion coefficients were obtained in the range 1.66–10.4 × 10−11 m2/s. This is quite low and may be explained by the very hard Calluna “wood”. The large span may be explained by different growth conditions, insect attacks and a varying number of years of exposure to the elements after dying. The mathematical model described the drying process well for the specimens with known diffusion coefficient. Conclusions: The established range of diffusion coefficients and the developed model may likely be extended for forecasting moisture content of degenerated Calluna as a proxy for fire danger and/or conditions for efficient and safe prescribed burning. This may help mitigate the emerging fire risk associated with degenerated Calluna stands in a changing climate.
7
Loh, Z. M., R. M. Law, K. D. Haynes, P. B. Krummel, L. P. Steele, P. J. Fraser, S. Chambers, and A. Williams. "Simulations of atmospheric methane for Cape Grim, Tasmania, to constrain South East Australian methane emissions." Atmospheric Chemistry and Physics Discussions 14, no. 15 (August 19, 2014): 21189–221. http://dx.doi.org/10.5194/acpd-14-21189-2014.
Full textAbstract:
Abstract. This study uses two climate models and six scenarios of prescribed methane emissions to compare modelled and observed atmospheric methane between 1994 and 2007, for Cape Grim, Australia (40.7° S, 144.7° E). The model simulations follow the TransCom-CH4 protocol and use the Australian Community Climate and Earth System Simulator (ACCESS) and the CSIRO Conformal-Cubic Atmospheric Model (CCAM). Radon is also simulated and used to reduce the impact of transport differences between the models and observations. Comparisons are made for air samples that have traversed the Australian continent. All six emission scenarios give modelled concentrations that are broadly consistent with those observed. There are three notable mismatches, however. Firstly, scenarios that incorporate interannually varying biomass burning emissions produce anomalously high methane concentrations at Cape Grim at times of large fire events in southeastern Australia, most likely due to the fire methane emissions being unrealistically input into the lowest model level. Secondly, scenarios with wetland methane emissions in the austral winter overestimate methane concentrations at Cape Grim during wintertime while scenarios without winter wetland emissions perform better. Finally, all scenarios fail to represent a methane source in austral spring implied by the observations. It is possible that the timing of wetland emissions in the scenarios is incorrect with recent satellite measurements suggesting an austral spring (September-October-November), rather than winter, maximum for wetland emissions.
8
Loh, Z. M., R. M. Law, K. D. Haynes, P. B. Krummel, L. P. Steele, P. J. Fraser, S. D. Chambers, and A. G. Williams. "Simulations of atmospheric methane for Cape Grim, Tasmania, to constrain southeastern Australian methane emissions." Atmospheric Chemistry and Physics 15, no. 1 (January 13, 2015): 305–17. http://dx.doi.org/10.5194/acp-15-305-2015.
Full textAbstract:
Abstract. This study uses two climate models and six scenarios of prescribed methane emissions to compare modelled and observed atmospheric methane between 1994 and 2007, for Cape Grim, Australia (40.7° S, 144.7° E). The model simulations follow the TransCom-CH4 protocol and use the Australian Community Climate and Earth System Simulator (ACCESS) and the CSIRO Conformal-Cubic Atmospheric Model (CCAM). Radon is also simulated and used to reduce the impact of transport differences between the models and observations. Comparisons are made for air samples that have traversed the Australian continent. All six emission scenarios give modelled concentrations that are broadly consistent with those observed. There are three notable mismatches, however. Firstly, scenarios that incorporate interannually varying biomass burning emissions produce anomalously high methane concentrations at Cape Grim at times of large fire events in southeastern Australia, most likely due to the fire methane emissions being unrealistically input into the lowest model level. Secondly, scenarios with wetland methane emissions in the austral winter overestimate methane concentrations at Cape Grim during wintertime while scenarios without winter wetland emissions perform better. Finally, all scenarios fail to represent a~methane source in austral spring implied by the observations. It is possible that the timing of wetland emissions in the scenarios is incorrect with recent satellite measurements suggesting an austral spring (September–October–November), rather than winter, maximum for wetland emissions.
9
Sitters, Holly, Julian Di Stefano, Fiona J. Christie, Paul Sunnucks, and Alan York. "Bird diversity increases after patchy prescribed fire: implications from a before–after control–impact study." International Journal of Wildland Fire 24, no. 5 (2015): 690. http://dx.doi.org/10.1071/wf14123.
Full textAbstract:
Increasingly, patchy prescribed fire of low severity is used by land managers to mitigate wildfire risk, but there are relatively few experimental studies on the effects of low-severity fire on fauna. We used a before–after control–impact experiment to examine avian responses to prescribed fire at two scales in topographically variable, tall-open eucalypt forest in south-east Australia. We surveyed birds at control and impact areas twice before and twice after fire, and applied mixed models to investigate responses of avian turnover, richness and the occurrence of selected species. Approximately half of the impact area was burnt and topographic variation generated a finger-like configuration of burnt patches on ridges and unburnt patches in gullies. Our findings at the smaller scale (0.8 ha) indicated that the fire resulted in increased bird diversity because a patchwork of burnt and unburnt areas provided a mosaic of distinct successional states in which different species occurred. Additionally, we found that the effect of fire on species richness and occurrence was a function of the presence of unburnt topographic refuges. In contrast, we found no compelling evidence to suggest that birds responded to the fire at the larger scale (400 ha). We conclude that application of low-severity fire in a patchy manner enhanced avian diversity and facilitated the persistence of the birds detected in pre-fire surveys. Although the levels of patchiness required to sustain diverse taxa warrant further study, our findings highlight the importance of formally incorporating patchiness into prescribed burning for the ecologically sensitive management of contemporary landscapes.
10
Kukkonen, J., J. Nikmo, M. Sofiev, K. Riikonen, T. Petäjä, A. Virkkula, J. Levula, S. Schobesberger, and D. M. Webber. "Applicability of an integrated plume rise model for the dispersion from wild-land fires." Geoscientific Model Development Discussions 7, no. 1 (January 16, 2014): 483–527. http://dx.doi.org/10.5194/gmdd-7-483-2014.
Full textAbstract:
Abstract. We have presented an overview of a mathematical model, BUOYANT, that was originally designed for the evaluation of the dispersion of buoyant plumes originated from major warehouse fires. The model addresses the variations of the cross-plume integrated properties of a buoyant plume in the presence of a vertically varying atmosphere. The model also includes a treatment for a rising buoyant plume interacting with an inversion layer. We have compared the model predictions with the data of two prescribed wild-land fire experiments. For the SCAR-C experiment in Quinault (US) in 1994, the predicted vertical extents of the plume at maximum plume rise were between 500–800 m and 200–700 m, using two alternative meteorological datasets. The corresponding observed injection heights of the aerosol particles measured using an airborne LIDAR (LIght Detection And Ranging) ranged from 250 and 600 m. For the prescribed burning experiment in Hyytiälä (Finland) in 2009, the model predictions were compared with plume elevations and diameters, determined based on particulate matter number concentration measurements on board an aeroplane. The agreement of modelled and measured results was good, provided that one assumes the measured maximum convective heat fluxes as input data for the model. The results demonstrate that in field experiments on wild-land fires, there are substantial uncertainties in estimating both (i) the source terms for the atmospheric dispersion computations, and (ii) the relevant vertical meteorological profiles. The results provide more confidence that cross-plume integrated mathematical models, such as the BUOYANT model, can be used to fairly good accuracy for evaluating the dispersion from major wild-land fires.
11
Price, Owen F., Bronwyn Horsey, and Ningbo Jiang. "Local and regional smoke impacts from prescribed fires." Natural Hazards and Earth System Sciences 16, no. 10 (October 14, 2016): 2247–57. http://dx.doi.org/10.5194/nhess-16-2247-2016.
Full textAbstract:
Abstract. Smoke from wildfires poses a significant threat to affected communities. Prescribed burning is conducted to reduce the extent and potential damage of wildfires, but produces its own smoke threat. Planners of prescribed fires model the likely dispersion of smoke to help manage the impacts on local communities. Significant uncertainty remains about the actual smoke impact from prescribed fires, especially near the fire, and the accuracy of smoke dispersal models. To address this uncertainty, a detailed study of smoke dispersal was conducted for one small (52 ha) and one large (700 ha) prescribed fire near Appin in New South Wales, Australia, through the use of stationary and handheld pollution monitors, visual observations and rain radar data, and by comparing observations to predictions from an atmospheric dispersion model. The 52 ha fire produced a smoke plume about 800 m high and 9 km long. Particle concentrations (PM2.5) reached very high peak values (> 400 µg m−3) and high 24 h average values (> 100 µg m−3) at several locations next to or within ∼ 500 m downwind from the fire, but low levels elsewhere. The 700 ha fire produced a much larger plume, peaking at ∼ 2000 m altitude and affecting downwind areas up to 14 km away. Both peak and 24 h average PM2.5 values near the fire were lower than for the 52 ha fire, but this may be because the monitoring locations were further away from the fire. Some lofted smoke spread north against the ground-level wind direction. Smoke from this fire collapsed to the ground during the night at different times in different locations. Although it is hard to attribute particle concentrations definitively to smoke, it seems that the collapsed plume affected a huge area including the towns of Wollongong, Bargo, Oakdale, Camden and Campbelltown (∼ 1200 km2). PM2.5 concentrations up to 169 µg m−3 were recorded on the morning following the fire. The atmospheric dispersion model accurately predicted the general behaviour of both plumes in the early phases of the fires, but was poor at predicting fine-scale variation in particulate concentrations (e.g. places 500 m from the fire). The correlation between predicted and observed varied between 0 and 0.87 depending on location. The model also completely failed to predict the night-time collapse of the plume from the 700 ha fire. This study provides a preliminary insight into the potential for large impacts from prescribed fire smoke to NSW communities and the need for increased accuracy in smoke dispersion modelling. More research is needed to better understand when and why such impacts might occur and provide better predictions of pollution risk.
12
Walsh, Sean F., Petter Nyman, Gary J. Sheridan, Craig C. Baillie, Kevin G. Tolhurst, and Thomas J. Duff. "Hillslope-scale prediction of terrain and forest canopy effects on temperature and near-surface soil moisture deficit." International Journal of Wildland Fire 26, no. 3 (2017): 191. http://dx.doi.org/10.1071/wf16106.
Full textAbstract:
Soil moisture has important effects on fuel availability, but is often assessed using drought indices at coarse spatial resolution, without accounting for the fine-scale spatial effects of terrain and canopy variation on forest floor moisture. In this study, we examined the spatial variability of air temperature, litter temperature and near-surface soil moisture (θ, 0–100 mm) using data from field experiments at 17 sites in south-east Australia, covering a range of topographic aspects and vegetation types, within climates from semiarid to wet montane. Temperatures and θ in mountainous environments were found to vary at much finer spatial scales than typical drought index grid dimensions (several kilometres). Using terrain elevation, local insolation ratio and plant area index, we developed semi-empirical microclimate models for air and litter temperatures, then used modelled temperatures as input into calculations of the Keetch–Byram Drought Index, a widely used index of soil moisture deficit. Drought index results based on predicted litter temperature were found to explain 91% of the spatial variation in near-surface soil moisture at our experimental sites. These results suggest the potential for routine hillslope-scale predictions of forest floor moisture status, which may be useful in the management of fire, particularly prescribed burning, in complex terrain.
13
Levin, Noam, Marta Yebra, and Stuart Phinn. "Unveiling the Factors Responsible for Australia’s Black Summer Fires of 2019/2020." Fire 4, no. 3 (September 4, 2021): 58. http://dx.doi.org/10.3390/fire4030058.
Full textAbstract:
The summer season of 2019–2020 has been named Australia’s Black Summer because of the large forest fires that burnt for months in southeast Australia, affecting millions of Australia’s citizens and hundreds of millions of animals and capturing global media attention. This extensive fire season has been attributed to the global climate crisis, a long drought season and extreme fire weather conditions. Our aim in this study was to examine the factors that have led some of the wildfires to burn over larger areas for a longer duration and to cause more damage to vegetation. To this end, we studied all large forest and non-forest fires (>100 km2) that burnt in Australia between September 2019 and mid-February 2020 (Australia’s Black Summer fires), focusing on the forest fires in southeast Australia. We used a segmentation algorithm to define individual polygons of large fires based on the burn date from NASA’s Visible Infrared Imaging Radiometer Suite (VIIRS) active fires product and the Moderate Resolution Imaging Spectroradiometer (MODIS) burnt area product (MCD64A1). For each of the wildfires, we calculated the following 10 response variables, which served as proxies for the fires’ extent in space and time, spread and intensity: fire area, fire duration (days), the average spread of fire (area/days), fire radiative power (FRP; as detected by NASA’s MODIS Collection 6 active fires product (MCD14ML)), two burn severity products, and changes in vegetation as a result of the fire (as calculated using the vegetation health index (VHI) derived from AVHRR and VIIRS as well as live fuel moisture content (LFMC), photosynthetic vegetation (PV) and combined photosynthetic and non-photosynthetic vegetation (PV+NPV) derived from MODIS). We also computed more than 30 climatic, vegetation and anthropogenic variables based on remotely sensed derived variables, climatic time series and land cover datasets, which served as the explanatory variables. Altogether, 391 large fires were identified for Australia’s Black Summer. These included 205 forest fires with an average area of 584 km2 and 186 non-forest fires with an average area of 445 km2; 63 of the forest fires took place in southeast (SE) Australia (the area between Fraser Island, Queensland, and Kangaroo Island, South Australia), with an average area of 1097 km2. Australia’s Black Summer forest fires burnt for more days compared with non-forest fires. Overall, the stepwise regression models were most successful at explaining the response variables for the forest fires in SE Australia (n = 63; median-adjusted R2 of 64.3%), followed by all forest fires (n = 205; median-adjusted R2 of 55.8%) and all non-forest fires (n = 186; median-adjusted R2 of 48.2%). The two response variables that were best explained by the explanatory variables used as proxies for fires’ extent, spread and intensity across all models for the Black Summer forest and non-forest fires were the change in PV due to fire (median-adjusted R2 of 69.1%) and the change in VHI due to fire (median-adjusted R2 of 66.3%). Amongst the variables we examined, vegetation and fuel-related variables (such as previous frequency of fires and the conditions of the vegetation before the fire) were found to be more prevalent in the multivariate models for explaining the response variables in comparison with climatic and anthropogenic variables. This result suggests that better management of wildland–urban interfaces and natural vegetation using cultural and prescribed burning as well as planning landscapes with less flammable and more fire-tolerant ground cover plants may reduce fire risk to communities living near forests, but this is challenging given the sheer size and diversity of ecosystems in Australia.
14
Friend, Adrian J., Godwin A. Ayoko, Daniel Jager, Megan Wust, E. Rohan Jayaratne, Milan Jamriska, and Lidia Morawska. "Sources of ultrafine particles and chemical species along a traffic corridor: comparison of the results from two receptor models." Environmental Chemistry 10, no. 1 (2013): 54. http://dx.doi.org/10.1071/en12149.
Full textAbstract:
Environmental context Identifying the sources responsible for air pollution is crucial for reducing the effect of the pollutants on human health. The sources of the pollutants were found here by applying two mathematical models to data consisting of particle size distribution and chemical composition data. The identified sources could be used as the basis for controlling or reducing emissions of air pollution into the atmosphere. Abstract Particulate matter is common in our environment and has been linked to human health problems particularly in the ultrafine size range. In this investigation, the sources of particles measured at two sites in Brisbane, Australia, were identified by analysing particle number size distribution data, chemical species concentrations and meteorological data with two source apportionment models. The source apportionment results obtained by positive matrix factorisation (PMF) and principal component analysis–absolute principal component scores (PCA–APCS) were compared with information from the gaseous chemical composition analysis. Although PCA–APCS resolved more sources, the results of the PMF analysis appear to be more reliable. Six common sources were identified by both methods and these include: traffic 1, traffic 2, local traffic, biomass burning and two unassigned factors. Thus motor vehicle related activities had the greatest effect on the data with the average contribution from nearly all sources to the measured concentrations being higher during peak traffic hours and weekdays. Further analyses incorporated the meteorological measurements into the PMF results to determine the direction of the sources relative to the measurement sites, and this indicated that traffic on the nearby road and intersection was responsible for most of the factors. The described methodology that utilised a combination of three types of data related to particulate matter to determine the sources and combination of two receptor models could assist future development of particle emission control and reduction strategies.
15
Hradsky, Bronwyn A. "Conserving Australia’s threatened native mammals in predator-invaded, fire-prone landscapes." Wildlife Research 47, no. 1 (2020): 1. http://dx.doi.org/10.1071/wr19027.
Full textAbstract:
Abstract Inappropriate fire regimes and predation by introduced species each pose a major threat to Australia’s native mammals. They also potentially interact, an issue that is likely to be contributing to the ongoing collapse of native mammal communities across Australia. In the present review, I first describe the mechanisms through which fire could create predation pinch points, exacerbating the impacts of predators, including red foxes, Vulpes vulpes, and feral cats, Felis catus, on their native mammalian prey. These mechanisms include a localised increase in predator activity (a numerically mediated pathway) and higher predator hunting success after fire (a functionally moderated pathway), which could both increase native mammal mortality and limit population recovery in fire-affected landscapes. Evidence for such interactions is growing, although largely based on unreplicated experiments. Improving native mammal resilience to fire in predator-invaded landscapes requires addressing two key questions: how can the impacts of introduced predators on native mammals in fire-affected areas be reduced; and, does a reduction in predation by introduced species result in higher native mammal survival and population recovery after fire? I then examine potential management options for reducing predator impacts post-fire. The most feasible are landscape-scale predator control and the manipulation of fire regimes to create patchy fire scars. However, robust field experiments with adequate statistical power are required to assess the effectiveness of these approaches and preclude null (e.g. compensatory mortality) or adverse (e.g. mesopredator or competitor release) outcomes. Ongoing predator management and prescribed burning programs provide an opportunity to learn through replicated natural experiments as well as experimental manipulations. Standardised reporting protocols and cross-jurisdiction monitoring programs would help achieve necessary spatial and environmental replication, while multi-trophic, spatially explicit simulation models could help synthesise findings from disparate study designs, predict management outcomes and generate new hypotheses. Such approaches will be key to improving management of the complex mechanisms that drive threatened native mammal populations in Australia’s predator-invaded, fire-prone landscapes.