scholarly journals Spatially explicit and stochastic forest landscape model of fire disturbance and succession

2005 ◽  
Author(s):  
◽  
Jian Yang
Keyword(s):  
Fire Spread ◽  
Fire Disturbance ◽  
Spatially Explicit ◽  
Point Pattern ◽  
Forest Landscape ◽  
Simulation Methods ◽  
Fire Occurrence ◽  
Frequency Model ◽  
Landscape Models ◽  
Fire Patterns

Fire disturbance plays an important role in shaping ecosystem dynamics and vegetation patterns in many forested landscapes. This dissertation is dedicated to the modeling of fire disturbance in spatially explicit and stochastic forest landscape models, in particular, LANDIS model. A hierarchical fire frequency model was proposed to model fire occurrence. Four representative fire spread simulation methods were implemented in LANDIS. I compared fire patterns simulated using the four fire spread simulation methods under two fire occurrence process scenarios that are fuel-independent and fuel-dependent. Results showed that the incorporation of fuel into fire occurrence modeling greatly changes simulated fire patterns. Lastly, I used point process modeling approach to study the effects humans and other factors on the probability of fire occurrence in the Missouri Ozark Highlands. The spatial distribution of fire occurrence density, which is one of the results from point pattern modeling, can be further used in LANDIS as an input map for simulating fire occurrence.

Comparing effects of fire modeling methods on simulated fire patterns and succession: a case study in the Missouri Ozarks

2008 ◽  
Vol 38 (6) ◽  
pp. 1290-1302 ◽  
Author(s):  
Jian Yang ◽  
Hong S. He ◽  
Brian R. Sturtevant ◽  
Brian R. Miranda ◽  
Eric J. Gustafson
Keyword(s):  
Travel Time ◽  
Fire Regime ◽  
Time Algorithm ◽  
Fire Frequency ◽  
Fire Modeling ◽  
Simulation Methods ◽  
Fire Occurrence ◽  
Frequency Model ◽  
Modeling Methods ◽  
Fire Patterns

We compared four fire spread simulation methods (completely random, dynamic percolation, size-based minimum travel time algorithm, and duration-based minimum travel time algorithm) and two fire occurrence simulation methods (Poisson fire frequency model and hierarchical fire frequency model) using a two-way factorial design. We examined these treatment effects on simulated forest succession dynamics and fire patterns including fire frequency, size, burned area, and shape complexity of burned patches. The comparison was carried out using a forest landscape model (LANDIS) for a surface fire regime in the Missouri Ozark Highlands. Results showed that incorporation of fuel into fire occurrence modeling significantly changed simulated dynamics of fire frequency and area burned. The duration-based minimum travel time algorithm produced the highest variability in fire size, and the dynamic percolation method produced the most irregular burned patch shapes. We also found that various fire modeling methods greatly affected temporal fire patterns in the short term, but such effects were less prominent in the long term. The simulated temporal changes in landscape-level species abundances were similar for different fire modeling methods, suggesting that a complex fire modeling method may not be necessary for examining coarse-scale vegetation dynamics.

Comparison of spatially explicit forest landscape fire disturbance models

2008 ◽  
Vol 254 (3) ◽  
pp. 499-510 ◽  
Author(s):  
Chao Li ◽  
Harinder Hans ◽  
Hugh Barclay ◽  
Jianwei Liu ◽  
Greg Carlson ◽  
...  
Keyword(s):  
Fire Disturbance ◽  
Spatially Explicit ◽  
Forest Landscape

Current and future patterns of forest fire occurrence in China

2020 ◽  
Vol 29 (2) ◽  
pp. 104 ◽  
Author(s):  
Zhiwei Wu ◽  
Hong S. He ◽  
Robert E. Keane ◽  
Zhiliang Zhu ◽  
Yeqiao Wang ◽  
...  
Keyword(s):  
Forest Fire ◽  
General Circulation ◽  
Southern China ◽  
Northern China ◽  
General Circulation Models ◽  
Boosted Regression Trees ◽  
Fire Occurrence ◽  
Representative Concentration Pathways ◽  
Fire Patterns ◽  
In Fire

Forest fire patterns are likely to be altered by climate change. We used boosted regression trees modelling and the MODIS Global Fire Atlas dataset (2003–15) to characterise relative influences of nine natural and human variables on fire patterns across five forest zones in China. The same modelling approach was used to project fire patterns for 2041–60 and 2061–80 based on two general circulation models for two representative concentration pathways scenarios. The results showed that, for the baseline period (2003–15) and across the five forest zones, climate variables explained 37.4–43.5% of the variability in fire occurrence and human activities were responsible for explaining an additional 27.0–36.5% of variability. The fire frequency was highest in the subtropical evergreen broadleaf forests zone in southern China, and lowest in the warm temperate deciduous broadleaved mixed-forests zone in northern China. Projection results showed an increasing trend in fire occurrence probability ranging from 43.3 to 99.9% and 41.4 to 99.3% across forest zones under the two climate models and two representative concentration pathways scenarios relative to the current climate (2003–15). Increased fire occurrence is projected to shift from southern to central-northern China for both 2041–60 and 2061–80.

scholarly journals Future forests and indicator-species population models

2007 ◽  
Vol 83 (1) ◽  
pp. 36-40 ◽  
Author(s):  
L A Venier ◽  
J L Pearce ◽  
B A Wintle ◽  
S A Bekessy
Keyword(s):  
Forest Management ◽  
Indicator Species ◽  
Sustainable Forest Management ◽  
Population Change ◽  
Biological Indicators ◽  
Spatially Explicit ◽  
Landscape Models ◽  
Dynamic Landscape ◽  
Brown Creeper ◽  
The Impact

In this paper, we provide an overview of a project that we initiated to explore the utility of spatially-explicit metapopulation models linked to dynamic landscape models as a way of incorporating biological indicators into sustainable forest management. We developed models for three indicator species as case studies; brown creeper (Certhis americana), redbacked vole (Clethrionomys gapperi) and red-backed salamander (Plethodon cinereus) in a northern Ontario landscape. Results from the project to date suggest that there are significant advantages to models that are spatially-explicit and dynamic in their treatment of both populations and landscapes. Dynamic landscape metapopulation (DLMP) models allow a manager to track population change through time in response to a changing landscape and a fluctuating environment. These DLMP models may be used to predict the impact of current and alternative forest management strategies on population sizes of a suite of species chosen to indicate the health of forest ecosystems. Key words: biological indicators, population viability analysis, population modeling, dynamic landscape modeling, sustainable forest management, brown creeper, red-backed salamander, red-backed vole

Relating surface fire spread to landscape structure: An application of FARSITE in a managed forest landscape

2007 ◽  
Vol 83 (4) ◽  
pp. 275-283 ◽  
Author(s):  
Soung-Ryoul Ryu ◽  
Jiquan Chen ◽  
Daolan Zheng ◽  
Jacob J. Lacroix
Keyword(s):  
Landscape Structure ◽  
Fire Spread ◽  
Forest Landscape ◽  
Managed Forest ◽  
Surface Fire

Assessing spatial attributes of forest landscape values: an internet-based participatory mapping approach

2008 ◽  
Vol 38 (2) ◽  
pp. 289-303 ◽  
Author(s):  
Jennifer L. Beverly ◽  
Kinga Uto ◽  
Justin Wilkes ◽  
Peter Bothwell
Keyword(s):  
Biological Diversity ◽  
Spatial Scales ◽  
Point Pattern Analysis ◽  
Point Pattern ◽  
Forest Landscape ◽  
Hotspot Detection ◽  
Road Density ◽  
Landscape Values ◽  
Forest Fire Management ◽  
Value Types

We designed and developed an internet mapping application to collect data on the locations of forest landscape values across a 2.4 million hectare study area in the province of Alberta, Canada. Four communities in the study area were surveyed and 8053 point locations were mapped for 10 different value types. Importance weights of landscape values were determined through a ranking exercise. Nearest-neighbour and second-order spatial point pattern analysis (K functions) suggested that all value types were significantly clustered across the study area. Recreational, wilderness, existence, and biological diversity values exhibited maximum clustering at larger spatial scales in comparison with educational, economic, historic or cultural, and spiritual values. Maximum clustering was positively related to mean road density and negatively related to mean distance to water, which suggests that landscape features influence the spatial pattern of values by acting as focal points or attractors for values. An applied use of the data for values hotspot detection and community protection zoning in forest fire management planning is presented.

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