scholarly journals Spatial Modeling of Fire Occurrence Probability in a Protected Area in Western Mexico

Forestist ◽  
2021 ◽  
Author(s):  
Francisco Javier Sahagún-Sánchez ◽  
◽  
Abril Joaquina Méndez-García ◽  
Francisco Martín Huerta-Martínez ◽  
Marco Antonio Espinoza-Guzmán ◽  
...  
Keyword(s):  
Spatial Modeling ◽  
Protected Area ◽  
Fire Occurrence ◽  
Occurrence Probability ◽  
Western Mexico

A probability model for long-term forest fire occurrence in the Karst forest management area of Slovenia

2017 ◽  
Vol 26 (5) ◽  
pp. 399 ◽  
Author(s):  
Tomaž Šturm ◽  
Tomaž Podobnikar
Keyword(s):  
Forest Management ◽  
Forest Fire ◽  
Probability Model ◽  
Target Area ◽  
Fire Occurrence ◽  
Occurrence Probability ◽  
Karst Forest ◽  
Management Area ◽  
Stand Characteristics

The aim of this study is to develop a long-term forest fire occurrence probability model in the Karst forest management area of Slovenia. The target area has the greatest forest fire occurrence rates and the largest burned areas in the country. To discover how the forest stand characteristics influence forest fire occurrence, we developed a long-term linear regression model. The geographically weighted regression method was applied to build the model, using forest management plans and land-based datasets as explanatory variables and a past forest fire activity dataset as a predicted variable. The land-based dataset was used to represent human activity as a key component in fire occurrence. Variables representing the natural and the anthropogenic environment used in the model explained 39% of past forest fire occurrences and predicted areas with the highest likelihood of forest fire occurrence. The results show that forest fire occurrence probability in a stand increases with lower wood stock, lower species diversity and lower thickness diversity, and in stands dominated by conifer trees under normal canopy closure. These forests stand characteristics are planned to be used in forest management and silviculture planning to reduce fire damage in Slovenian forests.

Forest fire risk assessment using point process modelling of fire occurrence and Monte Carlo fire simulation

2017 ◽  
Vol 26 (9) ◽  
pp. 789 ◽  
Author(s):  
Hyeyoung Woo ◽  
Woodam Chung ◽  
Jonathan M. Graham ◽  
Byungdoo Lee
Keyword(s):  
Risk Assessment ◽  
Monte Carlo ◽  
Forest Fire ◽  
Fire Risk ◽  
Fire Spread ◽  
Fire Occurrence ◽  
Occurrence Probability ◽  
Burn Probability ◽  
Forest Fire Risk ◽  
Fire Ignition

Risk assessment of forest fires requires an integrated estimation of fire occurrence probability and burn probability because fire spread is largely influenced by ignition locations as well as fuels, weather, topography and other environmental factors. This study aims to assess forest fire risk over a large forested landscape using both fire occurrence and burn probabilities. First, we use a spatial point processing method to generate a fire occurrence probability surface. We then perform a Monte Carlo fire spread simulation using multiple fire ignition points generated from the fire occurrence surface to compute burn probability across the landscape. Potential loss per land parcel due to forest fire is assessed as the combination of burn probability and government-appraised property values. We applied our methodology to the municipal boundary of Gyeongju in the Republic of Korea. The results show that the density of fire occurrence is positively associated with low elevation, moderate slope, coniferous land cover, distance to roads, high density of tombs and interaction among fire ignition locations. A correlation analysis among fire occurrence probability, burn probability, land property value and potential value loss indicates that fire risk in the study landscape is largely associated with the spatial pattern of burn probability.

scholarly journals Projected Impacts of Climate Change on the Protected Areas of Myanmar

Climate ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 99
Author(s):  
Thazin Nwe ◽  
Robert J. Zomer ◽  
Richard T. Corlett
Keyword(s):  
Climate Change ◽  
Protected Areas ◽  
Spatial Modeling ◽  
Protected Area ◽  
Economic Problems ◽  
Global Environmental ◽  
Elevational Range ◽  
Environmental Stratification ◽  
Open Forests ◽  
Impacts Of Climate Change

Protected areas are the backbone of biodiversity conservation but are fixed in space and vulnerable to anthropogenic climate change. Myanmar is exceptionally rich in biodiversity but has a small protected area system. This study aimed to assess the potential vulnerability of this system to climate change. In the absence of good biodiversity data, we used a spatial modeling approach based on a statistically derived bioclimatic stratification (the Global Environmental Stratification, GEnS) to understand the spatial implications of projected climate change for Myanmar’s protected area system by 2050 and 2070. Nine bioclimatic zones and 41 strata were recognized in Myanmar, but their representation in the protected area system varied greatly, with the driest zones especially underrepresented. Under climate change, most zones will shift upslope, with some protected areas projected to change entirely to a new bioclimate. Potential impacts on biodiversity include mountaintop extinctions of species endemic to isolated peaks, loss of climate specialists from small protected areas and those with little elevational range, and woody encroachment into savannas and open forests as a result of both climate change and rising atmospheric CO2. Myanmar needs larger, better connected, and more representative protected areas, but political, social, and economic problems make this difficult.

Making protected area networks effective for marine top predators

2011 ◽  
Vol 13 (3) ◽  
pp. 203-218 ◽  
Author(s):  
SK Hooker ◽  
A Cañadas ◽  
KD Hyrenbach ◽  
C Corrigan ◽  
JJ Polovina ◽  
...  
Keyword(s):  
Protected Area ◽  
Top Predators

Seagrass amphipod assemblages in a Mediterranean marine protected area: a multiscale approach

2014 ◽  
Vol 506 ◽  
pp. 175-192 ◽  
Author(s):  
N Sturaro ◽  
G Lepoint ◽  
A Pérez-Perera ◽  
S Vermeulen ◽  
P Panzalis ◽  
...  
Keyword(s):  
Protected Area ◽  
Marine Protected Area ◽  
Multiscale Approach
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