@article {BF-3142,
	title = {Neighbourhood rules make or break spatial scale invariance in a classic model of contagious disturbance},
	journal = {Ecological Complexity},
	volume = {8},
	year = {2011},
	month = {12/2011},
	pages = {347 - 356},
	abstract = {Scale invariant patterns have been observed in a range of terrestrial and marine ecosystems. These patterns are commonly interpreted as a signature of a self-organising system where global structures emerge from local dynamic interactions between system elements. In effect, an analogy is drawn to the scale invariant output of self-organised model systems, such as the Drossel and Schwabl forest fire model (FFM), and scale invariance in actual systems is then taken to be the product of self-organisation rather than some other process-specific, generative cause. Misinterpretation of the generative mechanism of scale invariance may well have significant consequences for ecosystem management.

In actual ecosystems spatial interactions typically vary in form, distance and direction over time, often dependent on exogenous factors such as weather. While simulation models may sometimes represent spatial processes using a variable interaction within a local neighbourhood, what influence this has on model phenomena that are normally attributable to self-organisation has been little studied. We relax a key assumption implicit in the FFM by allowing different sized neighbourhoods over which contagion can occur, rather than maintain a constant sized neighbourhood. We examine how the scaling behaviour of simulated fire sizes changes with a variable neighbourhood size, and show that the invariant scaling typical of the FFM {\textquoteleft}breaks{\textquoteright} with the relaxation of the neighbourhood assumption. Our findings are a strong indication that the generative origins of scale invariance in the FFM (i.e., self-organisation) and in actual fire-prone forest landscapes are essentially different, in contrast to conclusions of previous studies.},
	issn = {1476945X},
	doi = {10.1016/j.ecocom.2011.07.005},
	author = {Matthias M. Boer and Johnston, P and Sadler, Rohan J.}
}
@article {BF-2416,
	title = {Deriving state-and-transition models from an image series of grassland pattern dynamics},
	journal = {Ecological Modelling},
	volume = {221},
	year = {2010},
	month = {02/2010},
	pages = {433 - 444},
	abstract = {We present how state-and-transition models (STMs) may be derived from image data, providing a graphical means of understanding how ecological dynamics are driven by complex interactions among ecosystem events. A temporal sequence of imagery of fine scale vegetation patterning was acquired from close range photogrammetry (CRP) of 1 m quadrats, in a long term monitoring project of Themeda triandra (Forsskal) grasslands in north western Australia. A principal components scaling of image metrics calculated on the imagery defined the state space of the STM, and thereby characterised the different patterns found in the imagery. Using the state space, we were able to relate key events (i.e. fire and rainfall) to both the image data and aboveground biomass, and identified distinct ecological {\textquoteleft}phases{\textquoteright} and {\textquoteleft}transitions{\textquoteright} of the system. The methodology objectively constructs a STM from imagery and, in principle, may be applied to any temporal sequence of imagery captured in any event-driven system. Our approach, by integrating image data, addresses the labour constraint limiting the extensive use of STMs in managing vegetation change in arid and semiarid rangelands.},
	doi = {10.1016/j.ecolmodel.2009.10.027},
	author = {Sadler, Rohan J. and Hazelton, Martin and Matthias M. Boer and Grierson, Pauline}
}
@article {BF-2396,
	title = {Long-term impacts of prescribed burning on regional extent and incidence of wildfires{\textemdash}Evidence from 50 years of active fire management in SW Australian forests},
	journal = {Forest Ecology and Management},
	volume = {259},
	year = {2009},
	month = {12/2009},
	pages = {132 - 142},
	abstract = {Prescribed burning is advocated for the sustainable management of fire-prone ecosystems for its capacity to reduce fuel loads and mitigate large high-intensity wildfires. However, there is a lack of comprehensive field evidence on which to base predictions of the benefits of prescribed burning for meeting either wildfire hazard reduction or conservation goals. Australian eucalypt forests are among the very few forest types in the world where prescribed burning has been practised long enough and at a large enough spatial scale to quantify its effect on the incidence and extent of unplanned fires. Nevertheless even for Australian forests evidence of the effectiveness of prescribed burning remains fragmented and largely unpublished in the scientific literature.

We analysed a 52-year fire history from a eucalypt forest region in south-western Australia to quantify the impact of prescribed burning on the incidence, extent and size distribution of wildfires. Quantile regression identified the longevity of the influence of prescribed fire treatments on wildfire incidence and extent. Anomalies in the frequency-size distribution of unplanned fires were identified through a relative risk mapping using kernel density estimates. Changes in the spatial distribution of fuel age were quantified using patch metrics, while generalized additive models were applied to estimate effects of fuel age patterns on the incidence and extent of unplanned fire.

Prescribed burning has pronouncedly changed the spatial distribution of fuel age in the study area and has significantly reduced the incidence and extent of unplanned fires. This effect on both the incidence and extent of unplanned fires was minimal for time lags greater than 6 years between fuel treatment and response. When averaged over 6-year periods, the annual extent of prescribed burning explained 24\% and 71\% of the variation in the mean annual number and extent of unplanned fires, respectively. The incidence of large unplanned fires was significantly less than the long-term average for the region when the annual extent of prescribed fire was at a maximum and significantly more when the annual extent of prescribed fire was at a minimum. Since the 1960s, the length of time sites remain unburned by wildfire has approximately doubled to not, vert, similar9 years. We found that each unit area reduction in unplanned fire required about four units of prescription fire. These findings concur with the observations of experienced field practitioners who identify the 6-year mark as effective at reducing wildfire hazard. Our findings provide strong empirical evidence of the effectiveness of prescribed burning for mitigating wildfire hazard in SW Australian forests. Ongoing research and development is needed to implement managed fire regimes that integrate wildfire mitigation with conservation of biodiversity and other environmental values.},
	doi = {10.1016/j.foreco.2009.10.005},
	author = {Matthias M. Boer and Sadler, Rohan J. and Wittkuhn, Roy and Lachlan W. McCaw and Grierson, Pauline}
}
@article {BF-2376,
	title = {Mapping burned areas and burn severity patterns in SW Australian eucalypt forest using remotely-sensed changes in leaf area index},
	journal = {Remote Sensing of Environment},
	volume = {112},
	year = {2008},
	month = {12/2008},
	pages = {4358 - 4369},
	abstract = {Remote sensing is the most practical method available to managers of fire-prone forests for quantifying and mapping fire impacts. Differenced Normalised Burn Ratio (ΔNBR) is among the most widely used spectral indices for the mapping of burn severity but is difficult to interpret in terms of fire-related changes in key biophysical attributes and processes. We propose to quantify burn severity as a change in the leaf area index (ΔLAI) of a stand. LAI is a key biophysical attribute of forests, and is central to understanding their water and carbon cycles. Previous studies have suggested that changes in canopy LAI may be a major contributor to ΔNBR and to the composite burn index (CBI) that is frequently used in combination with the NBR to assess burn severity on the ground. We applied remotely-sensed ΔLAI to map burn severity in jarrah (Eucalyptus marginata) forest in south-western Australia burnt during the January 2005 Perth Hills wildfires. Ground-based digital photography was used to measure LAI in typical stands representing the full range of canopy densities present in the study area as well as variation in the time since the last fire. Regression models for the prediction of LAI were developed using NBR, the Normalised Difference Vegetation Index (NDVI) or the Simple Ratio (SR) as the independent variable. All three LAI models had equally high coefficients of determination (R2: 0.87) and small root mean squared errors (RMSE: 0.27{\textendash}0.28). ΔLAI was calculated as the difference between pre- and post-fire LAI, predicted using imagery from January 2004 and February 2005, respectively. The area affected by the January 2005 fire and the burn severity patterns within that area were mapped using ΔLAI and ΔNBR. Landscape patterns of burn severity obtained from differencing pre- and post-fire LAI were similar to those mapped by ΔNBR. We conclude that fire-affected areas and burn severity patterns in the northern jarrah forest can be objectively mapped using remotely-sensed changes in LAI, while offering the important advantage over NBR of being readily interpretable in the wider context of ecological forest management.},
	doi = {10.1016/j.rse.2008.08.005},
	author = {Matthias M. Boer and Macfarlane, C and Jaymie Norris and Sadler, Rohan J. and Wallace, J and Grierson, Pauline}
}
@article {BF-2377,
	title = {Spatial scale invariance of southern Australian forest fires mirrors the scaling behaviour of fire-driving weather events},
	journal = {Landscape Ecology},
	year = {2008},
	abstract = {Power law frequency-size distributions of forest fires have been observed in a range of environments. The scaling behaviour of fires, and more generally of landscape patterns related to recurring disturbance and recovery, have previously been explained in the frameworks of self-organized criticality (SOC) and highly optimized tolerance (HOT). In these frameworks the scaling behaviour of the fires is the global structure that either emerges spontaneously from locally operating processes (SOC) or is the product of a tuning process aimed at optimizing the trade-offs between system yield and tolerance to risks (HOT). Here, we argue that the dominant role of self-organized or optimised fuel patterns in constraining unplanned-fire sizes, implicit in the SOC and HOT frameworks, fails to recognise the strong exogenous controls of fire spread (i.e. by weather, terrain, and suppression) observed in many fire-prone landscapes. Using data from southern Australia we demonstrate that forest fire areas and the magnitudes of corresponding weather events have distributions with closely matching scaling exponents. We conclude that the spatial scale invariance of forest fires may also be a mapping of the meteorological forcing pattern. },
	doi = {10.1007/s10980-008-9260-5},
	author = {Matthias M. Boer and Sadler, Rohan J. and Ross Bradstock and Gill, A. Malcolm and Grierson, Pauline}
}
@proceedings {BF-2993,
	title = {Fitting Ecological Knowledge to Remotely Sensed Long-term Monitoring Data: A framework from semi-arid grasslands of the Pilbara region of north-western Australia},
	year = {2005},
	month = {August 2005},
	publisher = {Ecological Society of America},
	address = {USA, United States of America },
	keywords = {long-term monitoring, model fitting, remotely sensed data, vegetation dynamics},
	url = {http://abstracts.co.allenpress.com/pweb/esa2005/document/47881},
	author = {Sadler, Rohan J. and Hazelton, Martin and Grierson, Pauline}
}
