@mastersthesis {725,
	title = {Controls on disturbance regime dynamics: Fire in Los Padres National Forest},
	year = {1999},
	month = {1999},
	pages = {163},
	school = {University of California, Santa Barbara},
	address = {Santa Barbara},
	author = {Moritz, M. A.}
}
@article {528,
	title = {A systematic process for selecting representative Research Natural Areas},
	journal = {Natural Areas Journal},
	volume = {18},
	number = {4},
	year = {1998},
	pages = {338-349},
	abstract = {<p>Prioritizing sites as potential Research Natural Areas to represent a set of target vegetation types is a complex planning problem in which competing objectives must be satisfied simultaneously, including suitability and efficiency. We describe a general process for identifying and siting potential Research Natural Areas that is based on a systematic description of vegetation and environmental variation in the region, analysis of patterns of vegetation ownership and management, and optimal site selection based both on vegetational and environmental criteria. The approach is demonstrated with an application to siting Research Natural Areas to represent Mixed Evergreen Forest types on Los Padres National Forest in the central coast of California. We envision this process as a preliminary step that would precede more detailed ground survey and administrative review procedures as currently practiced. It could also be adapted to similar programs of regional conservation planning.</p>
},
	keywords = {reserve selection algorithm weighted-benefits maximal covering location problem Los Padres National Forest research natural areas},
	url = {http://fiesta.bren.ucsb.edu/~fd/Pubs/stoms_et_al_RNA98.pdf},
	author = {Stoms, D. M. and Borchert, M. I. and Moritz, M. A. and Davis, F. W. and Church, R. L.}
}
@article {724,
	title = {Analyzing extreme disturbance events: Fire in Los Padres National Forest},
	journal = {Ecological Applications},
	volume = {7},
	year = {1997},
	month = {1997},
	pages = {1252-1262},
	abstract = {Extreme disturbance events may strongly influence the structure and functioning of many ecosystems, particularly those in which large, infrequent events are the defining forces within the region. This paper introduces the extremal fire regime (i.e., the time series of the largest fire per year) and the assumptions implicit in its analysis. I describe the statistics of extremes and demonstrate their application to the fire regime of Los Padres National Forest, California, to compare two regions (i.e., Main and Monterey Divisions), to test for a shift in fire regime due to fire suppression, and to examine climatic events as a forcing mechanism for large fires. Despite their similarity and proximity, the Main Division exhibited a much higher frequency of large fires (and shorter return time) compared to the Monterey Division. Comparison of time periods 1911-1950 and 1951-1991 indicated that fire suppression had no effect on the distribution of very large fires in the Main Division, although the frequency of fires smaller than ~4,000 ha declined. Comparing distributions of an index for severity of Santa Ana conditions (i.e., characterized by hot, dry winds) and extreme fire events in the Main Division indicated a convergence of distributions with increasing event size. The distribution of fire events larger than ~4,000 ha appears to be coupled with that of severe Santa Ana conditions, suggesting a strong climatic forcing for extreme fires and a threshold for the transition from small- to large-fire dynamics. Results indicate the usefulness of extremal fire regime analysis for comparisons over space and time and for examining a potential forcing mechanism. This approach can be applied to any disturbance regime in which large events play an important role, providing ecologists and land managers a useful tool for understanding and predicting dynamics of extreme disturbance events.},
	author = {Moritz, M. A.}
}
@conference {726,
	title = {A method for examining patterns in mapped fire histories: identification of homogeneous fire landscapes},
	booktitle = {Fire in California Ecosystems: Integrating Ecology, Prevention, and Management},
	year = {1997},
	month = {1997},
	address = {San Diego},
	abstract = {In examining the mapped fire history of a large region, one may need to separate a study area into sub-regions that are homogeneous in terms of fire regime (i.e., to identify homogeneous "fire landscapes"). Because a fire regime is the result of complex interactions between fuel distributions, weather, and the cause and spatio-temporal patterns of ignitions, identification of fire landscapes may not be an easy task. Simplification of a fire regime (e.g., to fire frequency) or the use of surrogates (e.g., climatic regions or fuel maps) is often used, but this approach may ignore important aspects of how a fire regime manifests itself in a particular area. Inclusion of all available information, such as the fire size range, seasonality, and unusual intervals between fires, can provide a much better view of how fire landscapes differ from each other in significant ways. We propose an objective and repeatable method using variables generated from a mapped fire history, and we apply it to Los Padres National Forest in central coastal California. Fire variables were calculated on a regular grid spacing and incorporate the following: seasonality and cause of fire starts, number of times burned, longest and shortest interval between fires, and largest and smallest fires to pass over a site. Results indicate that this method captures the vast majority of variation in fire variables and their spatial pattern, providing mapped fire landscapes for use in fire planning or for further statistical analysis. Fire is the primary ecological disturbance structuring many of the world{\textquoteright}s terrestrial ecosystems, and spatio-temporal patterns of fires can provide insights into how these systems have developed and how we should manage them. In analyzing the fire history of a specific region, one is concerned that the fire regime be stationary (i.e., not containing mixed distributions) over space and time, but the scale and timing of dominant mechanisms are often poorly understood. Temporal shifts in fire regime can be caused by changes in climate or fire suppression, and different methods have been developed for dealing with mixed distributions over time (Clark 1989, Johnson and Gutsell 1994). Identification of areas that are spatially homogeneous in terms of fire history has received some attention, but many studies are performed using the spatial unit for which data were collected (e.g., at the scale of a specific county or forest). This scale may be appropriate, particularly if the goal is to characterize a process at a regional scale. Conversely, one may need to separate a study area into spatial units that are homogeneous in terms of fire history to examine the importance of local factors. A notable example of this is Baker (1989), in which homogeneous regions were sought by fitting fire-interval distributions to fire history data. Although characterization of fire frequency is a well established approach (Heinselman 1973, Johnson and Gutsell 1994, Johnson and Van Wagner 1985), the focus on fire intervals can omit important aspects of a fire regime that many mapped fire histories contain. Chou and others (1990) used a fire history to examine the distribution of fires and their spatial neighborhood effects, but the study area had been simplified to a binary variable (i.e., burned versus unburned). Inclusion of all available information, such as the fire size range, seasonality, and unusual intervals between fires, can provide a more complete view of how regions differ from each other in important ways. We propose here a methodology that is flexible, yet quantitative and repeatable, for identifying "fire landscapes" that are homogeneous in terms of several fire-related attributes. As a demonstration of its usefulness, we quantify and compare the vegetation composition of resulting fire landscapes on Los Padres National Forest (LPNF) in central coastal California to test whether analysis of fuel dependency at the scale of the entire study area is appropriate.},
	url = {http://www.ice.ucdavis.edu/cafe/agenda97/FireManagement/Modeling/4moritz.html},
	author = {Moritz, M. A. and Davis, F. W.}
}
@article {418,
	title = {Scaling and uncertainty in the relationship between the NDVI and land surface biophysical variables: An analysis using a scene simulation model and data from FIFE},
	journal = {Remote Sensing of Environment},
	volume = {54},
	number = {3},
	year = {1995},
	note = {JOURNAL ARTICLE; RESEARCH ARTICLE},
	pages = {233-246},
	abstract = {Biophysical inversion of remotely sensed data is constrained by the complexity of the remote sensing process. Variations in sensor response associated with solar and sensor geometries, surface directional reflectance, topography, atmospheric absorption and scattering, and sensor electrical-optical engineering interact in complex manners that are difficult to deconvolve and quantify in individual images or in time series of images. We have developed a model of the remote sensing process to allow systematic examination of these factors. The model is composed of three main components, including a ground scene model, an atmospheric model, and a sensor model, and may be used to simulate imagery produced by instruments such as the Landsat Thematic Mapper and the Advanced Very High Resolution Radiometer. Using this model, we examine the effect of subpixel variance in leaf area index (LAI) on relationships among LAI, the fraction of absorbed photosynthetically active radiation (FPAR), and the normalized difference vegetation index (NDVI). To do this, we use data from the first ISLSICP Field Experiment (FIFE) to parameterize ground scene properties within the model. Our results demonstrate interactions between sensor spatial resolution and spatial autocorrelation in ground scenes that produce a variety of effects in the relationship between both LAI and FPAR and NDVI. Specifically, sensor regularization, nonlinearity in the relationship between LAI and NDVI, and scaling the NDVI all influence the range, variance, and uncertainty associated with estimates of LAI and FPAR inverted from simulated NDVI data. These results have important implications for parameterization of land surface process models using biophysical variables such as LAI and FPAR estimated from remotely sensed data.},
	keywords = {Documentation, General{\textendash}Field Apparatus) (Mathematical Biology and Statistical Methods) (Ecology Environmental Biology{\textendash}Bioclimatology and Biometeorology) (Ecology Environmental Biology{\textendash}Plant) (Biophysics{\textendash}Biocybernetics (1972- )) (Forestry and Forest Products) Pl, General{\textendash}Field Methods) (Methods, Materials and Apparatus, Nomenclature and Terminology) (General Biology{\textendash}Information, Plantae-Unspecified (General Biology{\textendash}Taxonomy, Retrieval and Computer Applications) (Methods},
	author = {Friedl, M. A. and Davis, F. W. and Michaelsen, J. and Moritz, M. A.}
}
