Evaluating the role of fire disturbance in structuring small reptile communities in temperate forests

Fire is an integral disturbance shaping forest community dynamics over large scales. However, understanding the relationship between fire induced habitat disturbance and biodiversity remain equivocal. Ecological theories including the intermediate disturbance hypothesis (IDH) and the habitat accommodation model (HAM) offer predictive frameworks that could explain faunal responses to fire disturbances. We used an 80 year post-fire chronosequence to investigate small reptile community responses to fires in temperate forests across 74 sites. First, we evaluated if changes in species richness, abundance and evenness post-fire followed trends of prior predictions, including the IDH. Second, using competing models of fine scale habitat elements we evaluated the specific ways which fire influenced small reptiles. Third, we evaluated support for the HAM by examining compositional changes of reptile community post-fire. Relative abundance was positively correlated to age post-fire while richness and evenness showed no associations. The abundance trend was as expected based on the prior prediction of sustained population increase post-disturbance, but the trend for richness contradicted the prediction of highest diversity at intermediate levels of disturbance (according to IDH). Abundance changes were driven mainly by changes in overstorey, ground layer, and shelter, while richness and evenness did not associate with any vegetation parameter. Community composition was not strongly correlated to age since fire, thus support for the HAM was weak. Overall, in this ecosystem, frequent fire disturbances can be detrimental to small reptiles. Future studies utilizing approaches based on species traits could enhance our understanding of biodiversity patterns post-disturbance.

Fire affects microhabitat selection, movement patterns, and body condition of an Australian rodent (Rattus fuscipes)

Resource selection by animals influences individual fitness, the abundance of local populations, and the distribution of species. Further, the degree to which individuals select particular resources can be altered by numerous factors including competition, predation, and both natural- and human-induced environmental change. Understanding the influence of such factors on the way animals use resources can guide species conservation and management in changing environments. In this study, we investigated the effects of a prescribed fire on small-scale (microhabitat) resource selection, abundance, body condition, and movement pathways of a native Australian rodent, the bush rat (Rattus fuscipes). Using a before-after, control-impact design, we gathered data from 60 individuals fitted with spool and line tracking devices. In unburnt forest, selection of resources by bush rats was positively related to rushes, logs and complex habitat, and negatively related to ferns and litter. Fire caused selection for spreading grass, rushes, and complex habitat to increase relative to an unburnt control location. At the burnt location after the fire, rats selected patches of unburnt vegetation, and no rats were caught at a trapping site where most of the understory had been burnt. The fire also reduced bush rat abundance and body condition and caused movement pathways to become more convoluted. After the fire, some individuals moved through burnt areas but the majority of movements occurred within unburnt patches. The effects of fire on bush rat resource selection, movement, body condition, and abundance were likely driven by several linked factors including limited access to shelter and food due to the loss of understory vegetation and heightened levels of perceived predation risk. Our findings suggest the influence of prescribed fire on small mammals will depend on the resulting mosaic of burnt and unburnt patches and how well this corresponds to the resource requirements of particular species.

An efficient hybrid algorithm for fire flame detection

Proposing efficient methods for fire protection is becoming more and more important, because a small flame of fire may cause huge problems in social safety. In this paper, an effective fire flame detection method is investigated. This fire detection method includes four main stages: in the first step, a linear transformation is applied to convert red, green, and blue (RGB) color space through a 3∗3 matrix to a new color space. In the next step, fuzzy c-mean clustering method (FCM) is used to distinguish between fire flame and non-fire flame pixels. Particle Swarm Optimization algorithm (PSO) is also utilized in the last step to decrease the error value measured by FCM after conversion. Finally, we apply Otsu threshold method to the new converted images to make a binary picture. Empirical results show the strength, accuracy and fast-response of the proposed algorithm in detecting fire flames in color images.