Fire and The Australian Flora: A Review

Gill, A. Malcolm

doi:10.1080/00049158.1975.10675618

Cited by 523 publications

(362 citation statements)

References 47 publications

(63 reference statements)

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“…The rate and pattern of post-fire vegetation recovery in any ecosystem is determined by the 'fire regime', which incorporates the type, intensity, and frequency of fire, and the season of occurrence (Gill 1975). In this study, other factors which were important were propagule source, extent, distance, and transport mechanisms, as influenced by the area and proportion of the wetland burnt and its relative isolation from the nearest source populations.…”

Section: Rate and Pattern Of Recoverymentioning

confidence: 99%

Vegetation recovery following fire in two Waikato peatlands at Whangamarino and Moanatuatua, New Zealand

Clarkson

1997

New Zealand Journal of Botany

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After fires in 1984 and 1989 at Whangamarino wetland, and in 1972 at Moanatuatua Bog, peatland flora and vegetation were monitored to determine rates and pattems of recovery. Species with rhizomes that survived the fires were able to resprout and grow rapidly in the initial post-fire period. Species that were eliminated had to re-establish from seed and so recovered more slowly. The vegetation at Moanatuatua took almost 12 years to recover to pre-fire condition, twice as long as at Whangamarino. Adventive and early colonising native species were prominent only in the first 1-2 post-fire years, probably because of temporarily increased availability of nutrients and/or open habitat. Ordination techniques arranged the plots and species in a sequence from shrub-sedgeland (Whangamarino), through Empodisma minus restiad rushland (Whangamarino), to Sporadanthus traversii/ Empodisma restiad rushland (Moanatuatua) following a gradient of decreasing fertility with time. Fires reset the bog development process but generally do not alter the recovery pathways. In the absence of future major disturbance, including invasion by troublesome adventive species, the younger Whangamarino peatlands are expected to develop eventually into floristically poor, oligotrophic raised bogs similar to those at Moanatuatua and elsewhere in the Waikato district.

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Section: Rate and Pattern Of Recoverymentioning

confidence: 99%

Vegetation recovery following fire in two Waikato peatlands at Whangamarino and Moanatuatua, New Zealand

Clarkson

1997

New Zealand Journal of Botany

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“…Literature stated that characterizing the past fire regime, i.e. spatial pattern, frequency, intensity and seasonality of fires prevailing in an area (Gill, 1975;Pyne et al, 1996) is necessary to assess fire risk and the ecosystem vulnerability. Fire frequency is a main feature of fire regime which is notably characterized by fire intervals, i.e.…”

Section: Introductionmentioning

confidence: 99%

Wildfire frequency varies with the size and shape of fuel types in southeastern France: Implications for environmental management

Curt

Borgniet

Bouillon

2013

Journal of Environmental Management

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Characterizing time intervals between successive fires in the recent history is of main interest for fire hazard prevention and sustainable environmental management as it indicates what the typical fire return interval for each type of ecosystem is. We tested the extent to which fire return intervals (FRI) depend on fuel type and age, and we compared FRI values between two fire-prone areas of south-eastern France (Provence). These areas had similar weather and roughly similar fuel types but fuels occurred in patches with different sizes and shapes in the landscape. We built a fire database and we fitted Weibull distributions of FRI in order to compute the probability density function and the hazard of burning. Our results indicate maximal probability of burning again for shrublands (garrigues and maquis), and minimal values for mixed broadleaf-conifer forests and broadleaved forests. Most fuel types of Provence showed no effect of fuel age on the probability of burning again. Only the unmanaged maquis showed a linear increase of fire hazard in time due to a rapid postfire fuel build up. Rather long fire-free intervals and low age-dependency for most forest fuels of Provence suggest that reducing their biomass may not be sufficient to reduce fire risk. In contrast, the flammable shrublands have rather short fire intervals and represent a high fire hazard for the whole study area. The two areas had statistically significant difference of fire return intervals for a same fuel type (e.g. 18 to 22 years for shrublands, 20 to 24 years for pine forests, and 24 to 27 years for oak forests). This suggested that size, shape and connectivity of fuels play a major role in the probability of burning again and should be taken into account for fire management. The present policy of fire prevention puts efforts into public information and prevention, and preferential management of fuels at risk in the vicinity of roads and wildland-urban interfaces where fires occur preferentially. However, fire suppression may also take advantage of favouring low-flammable fuels with low age-dependency on strategic places in the landscape.

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“…Difficulties arise because sedimentation rates respond not only to fire frequency, but also to the type of vegetation burned and the completeness of combustion (11); a change in vegetation or the season of burning could be misinterpreted as a change in fire frequency and vice versa. For this reason, analyses usually limit themselves to descriptive scales such as more biomass burning or less biomass burning (11,12), which are difficult to relate to particular characteristics of a fire regime (13). Moreover, separating the human signal from variability caused by changes in vegetation and climate over the time periods studied is often impossible (10,14).…”

mentioning

confidence: 99%

Evolution of human-driven fire regimes in Africa

Archibald

Staver

Levin

2011

Proc. Natl. Acad. Sci. U.S.A.

315

272

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Human ability to manipulate fire and the landscape has increased over evolutionary time, but the impact of this on fire regimes and consequences for biodiversity and biogeochemistry are hotly debated. Reconstructing historical changes in human-derived fire regimes empirically is challenging, but information is available on the timing of key human innovations and on current human impacts on fire; here we incorporate this knowledge into a spatially explicit fire propagation model. We explore how changes in population density, the ability to create fire, and the expansion of agropastoralism altered the extent and seasonal distribution of fire as modern humans arose and spread through Africa. Much emphasis has been placed on the positive effect of population density on ignition frequency, but our model suggests this is less important than changes in fire spread and connectivity that would have occurred as humans learned to light fires in the dry season and to transform the landscape through grazing and cultivation. Different landscapes show different limitations; we show that substantial human impacts on burned area would only have started ∼4,000 B.P. in open landscapes, whereas they could have altered fire regimes in closed/dissected landscapes by ∼40,000 B.P. Dry season fires have been the norm for the past 200-300 ky across all landscapes. The annual area burned in Africa probably peaked between 4 and 40 kya. These results agree with recent paleocarbon studies that suggest that the biomass burned today is less than in the recent past in subtropical countries.human evolution | human ignition | savanna | fire spread model F ire has been a part of the earth system for billions of years (1), but recently-within the past million years at most-humans have provided a new and different source of ignition. Today, fires in all ecosystems are largely started by human ignitions, whether intentionally (for land management or arson) or by accident.From studies in modern systems we know that humans can affect fire regimes via their effects on both ignition (frequency, season, and location) and landscape connectivity. However, we lack an understanding of how these different impacts might have emerged as humans learned to control fire and as they spread throughout the globe. Moreover, the degree to which current human-ignited fire regimes differ from historical, lightning-driven regimes is largely unresolved (2).The question is complicated by the fact that the potential limitations on fire are various and system specific (3), and as one constraint is released, others can come into play. Thus, the number of ignitions can increase without a concomitant increase in area burned (4, 5), and responses of fire to drivers like population density can be nonlinear (6). Most ecosystems in Africa are probably not ignition-limited currently; ignition rates are more than sufficient to burn the available fuel, and climate and landscape connectivity act as the main limitations on fire (5, 7, 8).Interpreting historical human effects on fire regim...

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Fire and The Australian Flora: A Review

Cited by 523 publications

References 47 publications

Vegetation recovery following fire in two Waikato peatlands at Whangamarino and Moanatuatua, New Zealand

Vegetation recovery following fire in two Waikato peatlands at Whangamarino and Moanatuatua, New Zealand

Wildfire frequency varies with the size and shape of fuel types in southeastern France: Implications for environmental management

Evolution of human-driven fire regimes in Africa

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