Spatiotemporal Dynamics and Climate Influence of Forest Fires in Fujian Province, China

Zeng, Aicong; Yang, Song; Zhu, He; Tigabu, Mulualem; Su, Zhangwen; Wang, Guangyu; Guo, Futao

doi:10.3390/f13030423

Cited by 8 publications

(4 citation statements)

References 57 publications

(72 reference statements)

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“…It might be worth looking at changes in the occurrence of fires over time and forecasting throughout the year, which we strongly recommend. This conclusion is also supported by the results of fire studies from Fujian province in China in the 2001 to 2016 period [30], where the incidence of forest fires first increased and then decreased over the years, but the percentage of forest fires declined during the fire prevention season. The number of forest fires increased significantly in spring and summer, exceeding the number of forest fires occurring during the 2010 fire prevention period [30].…”

Section: Discussionmentioning

confidence: 53%

“…This conclusion is also supported by the results of fire studies from Fujian province in China in the 2001 to 2016 period [30], where the incidence of forest fires first increased and then decreased over the years, but the percentage of forest fires declined during the fire prevention season. The number of forest fires increased significantly in spring and summer, exceeding the number of forest fires occurring during the 2010 fire prevention period [30]. The spatial distribution of forest fires also changed: the number of fires decreased from northwestern to southeastern coastal areas, and the number of forest fires in the northwestern mountainous areas declined rapidly in autumn and winter.…”

Section: Discussionmentioning

confidence: 53%

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Spatio-Temporal Dynamics of Forest Fires in Poland and Consequences for Fire Protection Systems: Seeking a Balance between Efficiency and Costs

Kolanek,

Szymanowski,

Małysz

2023

Sustainability

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An important issue from the forest fire protection system perspective is forecasting fires and maintaining a high readiness of firefighting units at a low cost. In Poland, the level of fire protection is defined by the degree of forest fire risk, based on forecasts made for 1 March to 30 September, i.e., the risk period (the so-called fire season). In this paper, based on classical statistical and spatial analysis, we positively verify the research hypothesis that the fire season in Poland changes in terms of start and end dates depending on the region. We therefore propose a modification to the forecasting period, adapted to local conditions and calculated annually on the basis of the previous period. Then, using network analysis, we negatively verify the hypothesis that the size of the burned area is related to the distance from fire brigades, which proves that the reasons for such a differentiation in the number of fires should be sought elsewhere than in the system used for allocating fire units. On the basis of cluster analysis, attention is drawn to areas where large fires break out more often.

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Section: Discussionmentioning

confidence: 53%

Section: Discussionmentioning

confidence: 53%

Spatio-Temporal Dynamics of Forest Fires in Poland and Consequences for Fire Protection Systems: Seeking a Balance between Efficiency and Costs

Kolanek,

Szymanowski,

Małysz

2023

Sustainability

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show abstract

“…The frequent forest res in recent years are believed to be attributed to the changing climate conditions. In other words, climate determines the spatiotemporal distribution, intensity, and patterns of forest res by affecting vegetation and the extent of drought (Zeng et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Unveiling the Impact of Climate Variability on Forest Fire Occurrence in Namibia: A Modelling Study

Nikodemus

Trubin

Bernal

et al. 2023

Preprint

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Background Forest fire is the primary disturbance affecting the structure and composition of many forest ecosystems worldwide. Forest fires caused severe destruction to forest ecosystems in Namibia (South West Africa) during the period of 2011–2021. The aim of this paper is to assess the impacts of climate variability on forest fire occurrence in Namibia. Results A total of 38.184 Mha of forests was burned during the study period. Forest fire occurrence fluctuated in response to changes in climate variability (temperature, precipitation, and wind speed). Using linear regression models, ranked according to the Akaike information criterion (AIC), we found a combination of average wind speed in the 3-month period of July, August, September, and average monthly wind speed in January, May July, and August, to be the most important drivers of forest fires. Conclusions Forest fire occurrences are highly concentrated in the north-eastern and north-central regions. Forest fire occurrence is not limited to climate variability. There is little scientific evidence about other factors influencing forest fire occurrence in Namibia, in addition to climate variability.

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“…[17]. Fires also have an impact on these factors; for example, studies have shown that the occurrence of forest fires changes the distribution of vegetation [18].…”

Section: Introductionmentioning

confidence: 99%

Analysis of Factors Related to Forest Fires in Different Forest Ecosystems in China

Wang

et al. 2022

Forests

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Forests are the largest terrestrial ecosystem with major benefits in three areas: economy, ecology, and society. However, the frequent occurrence of forest fires has seriously affected the structure and function of forests. To provide a strong scientific basis for forest fire prevention and control, Ripley’s K(d) function and the LightGBM algorithm were used to determine the spatial pattern of forest fires in four different provinces (Heilongjiang, Jilin, Liaoning, Hebei) in China from 2019 to 2021 and the impact of driving factors on different ecosystems. In addition, this study also identified fire hotspots in the four provinces based on kernel density estimation (KDE). An artificial neural network model (ANN) was created to predict the probability of occurrence of forest fires in the study area. The results showed that the forest fires were spatially clustered, but the variable importance of different factors varied widely among the different forest ecosystems. Forest fires in Heilongjiang and Liaoning Provinces were mainly caused by human-driven factors. For Jilin, meteorological factors were important in the occurrence of fires. Topographic and vegetation factors exhibited the greatest importance in Hebei Province. The selected driving factors were input to the ANN model to predict the probability of fire occurrence in the four provinces. The ANN model accurately captured 93.17%, 90.28%, 83.16%, and 89.18% of the historical forest fires in Heilongjiang, Jilin, Liaoning, and Hebei Provinces; Precision, Recall, and F-measure based on the full dataset are 0.87, 0.88, and 0.87, respectively. The results of this study indicated that there were differences in the driving factors of fire in different forest ecosystems. Different fire management policies must be formulated in response to this spatial heterogeneity.

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Spatiotemporal Dynamics and Climate Influence of Forest Fires in Fujian Province, China

Cited by 8 publications

References 57 publications

Spatio-Temporal Dynamics of Forest Fires in Poland and Consequences for Fire Protection Systems: Seeking a Balance between Efficiency and Costs

Spatio-Temporal Dynamics of Forest Fires in Poland and Consequences for Fire Protection Systems: Seeking a Balance between Efficiency and Costs

Unveiling the Impact of Climate Variability on Forest Fire Occurrence in Namibia: A Modelling Study

Analysis of Factors Related to Forest Fires in Different Forest Ecosystems in China

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