George L. W. Perry

Retrieval of biomass combustion rates and totals from fire radiative power observations: FRP derivation and calibration relationships between biomass consumption and fire radiative energy release

Estimates of wildfire aerosol and trace gas emissions are most commonly derived from assessments of biomass combusted. The radiative component of the energy liberated by burning fuel can be measured by remote sensing, and spaceborne fire radiative energy (FRE) measures can potentially provide detailed information on the amount and rate of biomass consumption over large areas. To implement the approach, spaceborne sensors must be able to derive fire radiative power (FRP) estimates from subpixel fires using observations in just one or two spectral channels, and calibration relationships between radiated energy and fuel consumption must be developed and validated. This paper presents results from a sensitivity analysis and from experimental fires conducted to investigate these issues. Within their methodological limits, the experimental work shows that FRP assessments made via independent hyperspectral and MIR radiance approaches in fact show good agreement, and fires are calculated to radiate 14 ± 3% [mean ± 1S.D.] of their theoretically available heat yield in a form capable of direct assessment by a nadir-viewing MIR imager. The relationship between FRE and fuel mass combusted is linear and highly significant (r2 = 0.98, n = 29, p < 0.0001), and FRP is well related to combustion rate (r2 = 0.90, n = 178, p < 0.0001), though radiation from the still-hot fuel bed can sometimes contribute significant FRP from areas where combustion has ceased. We conclude that FRE assessment offers a powerful tool for supplementing existing burned-area based fuel consumption measures, and thus shows significant promise for enhancing pyrogenic trace gas and aerosol emissions estimates

A comparison of methods for the statistical analysis of spatial point patterns in plant ecology

We describe a range of methods for the description and analysis of spatial point patterns in plant ecology. The conceptual basis of the methods is presented, and specific tests are compared, with the goal of providing guidelines concerning their appropriate selection and use. Simulated and real data sets are used to explore the ability of these methods to identify different components of spatial pattern (e.g. departure from randomness, regularity vs. aggregation, scale and strength of pattern). First-order tests suffer from their inability to characterise pattern at distances beyond those at which local interactions (i.e. nearest neighbours) occur. Nevertheless, the tests explored (first-order nearest neighbour, Diggle’s G and F) are useful first steps in analysing spatial point patterns, and all seem capable of accurately describing patterns at these (shorter) distances. Among second-order tests, a density-corrected form of the neighbourhood density function (NDF), a non-cumulative analogue of the commonly used Ripley’s K-function, most informatively characterised spatial patterns at a range of distances for both univariate and bivariate analyses. Although Ripley’s K is more commonly used, it can give very different results to the NDF because of its cumulative nature. A modified form of the K-function suitable for inhomogeneous point patterns is discussed. We also explore the use of local and spatially-explicit methods for point pattern analysis. Local methods are powerful in that they allow variations from global averages to be detected and potentially provide a link to recent spatial ecological theory by taking the ‚plant’s-eye view’. We conclude by discussing the problems of linking spatial pattern with ecological process using three case studies, and consider some ways that this issue might be addressed.

Monthly burned area and forest fire carbon emission estimates for the Russian Federation from SPOT VGT

Abstract Russian boreal forests contain around 25% of all global terrestrial carbon, some of which is released to the atmosphere when the forests burn. Whilst it is well known that fire is widespread in the boreal environment, there is a lack of good quality quantitative data on the extent of fire activity in Russian forests and on its interannual variation. This study provides one of the first comprehensive monthly satellite-based studies of fires occurring across the entire Russian Federation using a single, standardised methodology designed to map burned areas down to a size of 2 km 2 . Using data from SPOT VEGETATION (VGT), we detect newly burned pixels via a series of multi-temporal spectral reflectance differencing criteria. For the year 2001, the method is applied to 21 VGT 10-day syntheses (S10) scenes covering the Russian fire season. We map 2764 fires with a total area of 41,782 km 2 , and our methodology successfully detects all fires present in a comparison Landsat ETM+ data set, although it underestimates their size by on average of 18%. Using frequency–size relations, we estimate that 3790 fires of 1–2-km 2 area are likely to have remained unobserved by our method across the entire Russian region. Taking these corrections into account, we calculate the total burned area for the Russian Federation in 2001 as 51,546 km 2 , with 38,512 km 2 occurring in forest and 13,034 km 2 in other land use classes. Fire activity is strongest in August in Eastern Siberia and the northern part of the Russian Far East, and in May and October in the southern part of the Russian Far East. Using these data, we estimate direct carbon emissions from these Russian forest fires to be 39.3–55.4 Mt, five to eight times that from the 2001 North American boreal forest fires and around 11–17% of that years Russian industrial carbon emissions. This methodology will, in the future, be applied to the full VGT archive to quantify burned area and direct carbon emissions over a 5-year period in order to better assess the interannual variation in burned area and emissions and the relation to local climate.

Regression Techniques for Examining Land Use/Cover Change: A Case Study of a Mediterranean Landscape

In many areas of the northern Mediterranean Basin the abundance of forest and scrubland vegetation is increasing, commensurate with decreases in agricultural land use(s). Much of the land use/cover change (LUCC) in this region is associated with the marginalization of traditional agricultural practices due to ongoing socioeconomic shifts and subsequent ecological change. Regression-based models of LUCC have two purposes: (i) to aid explanation of the processes driving change and/or (ii) spatial projection of the changes themselves. The independent variables contained in the single ‘best’ regression model (that is, that which minimizes variation in the dependent variable) cannot be inferred as providing the strongest causal relationship with the dependent variable. Here, we examine the utility of hierarchical partitioning and multinomial regression models for, respectively, explanation and prediction of LUCC in EU Special Protection Area 56, ‘Encinares del río Alberche y Cofio’ (SPA 56) near Madrid, Spain. Hierarchical partitioning estimates the contribution of regression model variables, both independently and in conjunction with other variables in a model, to the total variance explained by that model and is a tool to isolate important causal variables. By using hierarchical partitioning we find that the combined effects of factors driving land cover transitions varies with land cover classification, with a coarser classification reducing explained variance in LUCC. We use multinomial logistic regression models solely for projecting change, finding that accuracies of maps produced vary by land cover classification and are influenced by differing spatial resolutions of socioeconomic and biophysical data. When examining LUCC in human-dominated landscapes such as those of the Mediterranean Basin, the availability and analysis of spatial data at scales that match causal processes is vital to the performance of the statistical modelling techniques used here.

SpPack: spatial point pattern analysis in Excel using Visual Basic for Applications (VBA)

Many different sciences have developed many different tests to describe and characterise spatial point data. For example, all the trees in a given area may be mapped such that their x, y co-ordinates and other variables, or ‘marks’, (e.g. species, size) might be recorded. Statistical techniques can be used to explore interactions between events at different length scales and interactions between different types of events in the same area. SpPack is a menu-driven add-in for Excel written in Visual Basic for Applications (VBA) that provides a range of statistical analyses for spatial point data. These include simple nearest-neighbour-derived tests and more sophisticated second-order statistics such as Ripley’s K-function and the neighbourhood density function (NDF). Some simple grid or quadrat-based statistics are also calculated. The application of the SpPack add-in is demonstrated for artificially generated event sets with known properties and for a multi-type ecological event set.  2003 Elsevier Ltd. All rights reserved.

Current approaches to modelling the spread of wildland fire: a review:

This review considers the development of some of the models and modelling approaches designed to predict the spread and spatial behaviour of wildland fire events. Such events and their accurate prediction are of great importance to those seeking to understand and manage fire-prone ecosystems. The key problem which fire modelling seeks to address is outlined. Models predicting the rate of fire spread may be classified as physical, semi-physical or empirical according to the nature of their construction. The benefits and shortcomings of each type of model are considered with reference to specific examples of each type. It is shown that there are problems with current operational models which restrict their effective use. However, the development of rigorous physical models as replacements is impeded by conceptual and practical difficulties. Accurate estimation of the rate of spread and the intensity of a fire allows prediction of the final shape and area of a fire event. The modelling techniques used to estimate the shape and area of a fire are considered including the development of sophisticated computer-based simulations of fire spread. Spatial information technologies such as remote sensing and geographic information systems (GIS) offer great potential for the effective modelling of wildland fire behaviour. While such spatial information technologies have been frequently used in the evaluation of fire danger risk, their use for the simulation of the spatiotemporal behaviour of wildland fire is not common. The way in which spatial information technologies and decision-support systems are used for fire risk evaluation and fire spread simulation is discussed. Two research areas of great importance if fire modelling techniques are to improve are a better understanding of fire-dependent phenomena and the development of a ‘new generation’ of fire spread models; current trends in these areas of research are evaluated.

Spatial modelling of vegetation change in dynamic landscapes : a review of methods and applications

Because of the spatiotemporal scales involved and the logistical constraints in collecting landscape-level data, spatially explicit simulation models have become important tools in ecological and biogeographical studies conducted over broad extents. Here we review the methods used and some of the applications of landscape-level models of succession and disturbance dynamics. Mechanistic and stochastic models are compared and contrasted and the development, over the last 15 years, of spatial landscape models of ecological change is discussed. Coarse-grained spatial landscape models are compared with finer-grained individual-based approaches (eg, forest gap models). Management and monitoring applications of landscape models are considered alongside a discussion of the appropriate use of models in this context. A key area where spatial landscape models of the type described here need to develop is improved integration with the social sciences - both in terms of the parameters and the processes that the models incorporate. Finally issues related to scale and scaling are outlined and, in particular, the utility of methods for linking ecological models operating at disparate scales (eg, forest gap models versus landscape models) is examined.

Modelling Mediterranean landscape succession-disturbance dynamics: A landscape fire-succession model

We present a spatially explicit Landscape Fire-Succession Model (LFSM) developed to represent Mediterranean Basin landscapes and capable of integrating modules and functions that explicitly represent human activity. Plant-functional types are used to represent spatial and temporal competition for resources (water and light) in a rule-based modelling framework. Vegetation dynamics are represented using a rule-based community-level modelling approach that considers multiple succession pathways and vegetation climax states. Wildfire behaviour is represented using a cellular-automata model of fire spread that accounts for land-cover flammability, slope, wind and vegetation moisture. Results show that wildfire spread parameters have the greatest influence on two aspects of the model: land-cover change and the wildfire regime. This sensitivity highlights the importance of accurately parameterising this type of grid-based model for representing landscape-level processes. We use a pattern-oriented modelling approach in conjunction with wildfire power-law frequency-area scaling exponent @b to calibrate the model. Parameters describing the role of soil moisture on vegetation dynamics are also found to significantly influence land-cover change. Recent improvements in understanding the role of soil moisture and wildfire fuel loads at the landscape-level will drive advances in Mediterranean LFSMs.

Spatial patterns in species‐rich sclerophyll shrublands of southwestern Australia

Abstract Question: The drivers of spatial patterning among plant species and the implications of those patterns for the structure and function of plant communities are of ongoing interest and debate. Here we explore the spatial patterning shown by individual species in species-rich plant communities. We (1) compare the levels of aggregation in these communities to those observed in other species-rich communities, in particular tropical rain forests, and (2) consider how abiotic conditions might influence the levels of aggregation observed. Location: We describe the spatial structure of four species-rich Mediterranean-type shrubland communities near Eneabba, Western Australia. The four sites each contain > 10000 plants and up to 113 species, and differ in substrate-type, species richness and composition. Methods: We analysed the spatial patterning of all species with more than 20 individuals (233 species patterns), and used point process models for aggregated patterns to separate first-order gradient effects from second-order clustering. Results: Aggregated distributions were most common at all sites, but especially at the site with the highest resource availability and heterogeneity and lowest species richness. A Poisson cluster process best described the majority of aggregated species, suggesting that local interactions drive fine-scale patterns in these communities. Conclusions: As with many previous studies, we found that most species showed strong local aggregation. The proportion of species showing aggregation was less than has been described in species-rich tropical rainforests but was higher than observed in many temperate plant communities. The highest proportion of aggregated species was seen at the most resource-abundant site; this is in direct contrast to conceptual models that suggest that competition should be weakest, and aggregation most prevalent, in the most resource-limited sites.

Pyrodiversity is the coupling of biodiversity and fire regimes in food webs.

Fire positively and negatively affects food webs across all trophic levels and guilds and influences a range of ecological processes that reinforce fire regimes, such as nutrient cycling and soil development, plant regeneration and growth, plant community assembly and dynamics, herbivory and predation. Thus we argue that rather than merely describing spatio-temporal patterns of fire regimes, pyrodiversity must be understood in terms of feedbacks between fire regimes, biodiversity and ecological processes. Humans shape pyrodiversity both directly, by manipulating the intensity, severity, frequency and extent of fires, and indirectly, by influencing the abundance and distribution of various trophic guilds through hunting and husbandry of animals, and introduction and cultivation of plant species. Conceptualizing landscape fire as deeply embedded in food webs suggests that the restoration of degraded ecosystems requires the simultaneous careful management of fire regimes and native and invasive plants and animals, and may include introducing new vertebrates to compensate for extinctions that occurred in the recent and more distant past. This article is part of the themed issue ‘The interaction of fire and mankind’.