A note on non-parametric and semi-parametric modeling of wildfire hazard in Los Angeles County, California

This paper explores the use of, and problems that arise in, kernel smoothing and parametric estimation of the relationships between wildfire incidence and various meteorological variables. Such relationships may be treated as components in separable point process models for wildfire activity. The resulting models can be used for comparative purposes in order to assess the predictive performance of the Burning Index.

A stochastic forest fire growth model

We consider a stochastic fire growth model, with the aim of predicting the behaviour of large forest fires. Such a model can describe not only average growth, but also the variability of the growth. Implementing such a model in a computing environment allows one to obtain probability contour plots, burn size distributions, and distributions of time to specified events. Such a model also allows the incorporation of a stochastic spotting mechanism.

Sex ratio adjustment and maternal condition in two aphid species

We analyzed how offspring sex ratio varies with maternal condition in order to obtain evidence on the population structure in two aphid species with different life cycles. When fitness returns per unit investment differ for the production of daughters and sons, selection will favor an increasing investment into the sex with the higher returns. Therefore, the offspring sex ratios of individual mothers should become more biased towards the sex with the higher fitness returns as their condition or fecundity improves. The pattern of sex ratio adjustment we found in Uroleucon cirsii indicates local mate competition among males, while the pattern we found in Rhopalosiphum padi suggests local resource competition among sexual females. This might be the first evidence for local resource competition among females in an invertebrate species. Local mate competition means that fitness returns are limited by the availability of females as mates within local breeding groups, whereas local resource competition means that fitness returns are limited by the availability of resources for females competing within local groups. We discuss how the life cycles of both species fit to these hypotheses.

The fire frequency analysis branch of the pyrostatistics tree: sampling decisions and censoring in fire interval data

Statistical characterization of past fire regimes is important for both the ecology and management of fire-prone ecosystems. Survival analysis—or fire frequency analysis as it is often called in the fire literature—has increasingly been used over the last few decades to examine fire interval distributions. These distributions can be generated from a variety of sources (e.g., tree rings and stand age patterns), and analysis typically involves fitting the Weibull model. Given the widespread use of fire frequency analysis and the increasing availability of mapped fire history data, our goal has been to review and to examine some of the issues faced in applying these methods in a spatially explicit context. In particular, through a case study on the massive Cedar Fire in 2003 in southern California, we examine sensitivities of parameter estimates to the spatial resolution of sampling, point- and area-based methods for assigning sample values, current age surfaces versus historical intervals in generating distributions, and the inclusion of censored (i.e., incomplete) observations. Weibull parameter estimates were found to be roughly consistent with previous fire frequency analyses for shrublands (i.e., median age at burning of ~30–50 years and relatively low age dependency). Results indicate, however, that the inclusion or omission of censored observations can have a substantial effect on parameter estimates, far more than other decisions about specifics of sampling.

Modeling spatio-temporal wildfire ignition point patterns

We analyze and model the structure of spatio-temporal wildfire ignitions in the St. Johns River Water Management District in northeastern Florida. Previous studies, based on the K-function and an assumption of homogeneity, have shown that wildfire events occur in clusters. We revisit this analysis based on an inhomogeneous K-function and argue that clustering is less important than initially thought. We also use K-cross functions to study multitype point patterns, both under homogeneity and inhomogeneity assumptions, and reach similar conclusions as above regarding the amount of clustering. Of particular interest is our finding that prescribed burns seem not to reduce significantly the occurrence of wildfires in the current or subsequent year over this large geographical region. Finally, we describe various point pattern models for the location of wildfires and investigate their adequacy by means of recent residual diagnostics.

Spatial pattern and persistence of historical fire boundaries in southern interior British Columbia

Recent ecosystem and fire management research aims to quantify, model and understand historical fire disturbances focusing on their frequency, size and distribution. Less attention, however, has been paid to fire boundaries and their location on the landscape. Our study presents a spatial method to quantify the location, pattern and persistence of historical fire boundaries using tree ring fire scar data in the lower Stein watershed (British Columbia). Data from Pinus ponderosa and Pseudotsuga menziesii collected in 35 one-hectare plots over a 412-hectare study area were analyzed for the period between 1879 and 1947 using local spatial statistics and boundary detection techniques. Results of the analysis using local spatial statistic Moran’s I showed significant clustering of boundaries near topographic breaks. To determine and test whether fire boundaries between plots were persistent, we used boundary detection methods and developed a spatially restricted randomization test. The results revealed that out of 86 possible boundary links, 8 were significantly persistent (P < 0.025) while another 8 were significantly rare (P < 0.025). These spatial methods can help determine the historical spatial configuration of persistent boundaries and can be used to maintain natural forest dynamics.

Confidence limits on one-stage model parameters in benchmark risk assessment

In modern environmental risk analysis, inferences are often desired on those low dose levels at which a fixed benchmark risk is achieved. In this paper, we study the use of confidence limits on parameters from a simple one-stage model of risk historically popular in benchmark analysis with quantal data. Based on these confidence bounds, we present methods for deriving upper confidence limits on extra risk and lower bounds on the benchmark dose. The methods are seen to extend automatically to the case where simultaneous inferences are desired at multiple doses. Monte Carlo evaluations explore characteristics of the parameter estimates and the confidence limits under this setting.

A note on data augmentation and iterative simulation for survival rate estimation

In this paper we examine the use of data augmentation techniques for simplifying iterative simulation in the context of both Bayesian and classical statistical inference for survival rate estimation. We examine two distinct model families common in population ecology to illustrate our ideas, ring-recovery models and capture–recapture models, and we present the computational advantage of this approach. We discuss also the fact that problems associated with identifiability in the classical framework can be overcome using data augmentation, but highlight the dangers in doing so under both inferential paradigms.

Reciprocal altruism and food sharing decisions among Hiwi and Ache hunter–gatherers

The common occurrence of food transfers within human hunter–gatherer and forager–horticulturalist groups presents exciting test cases for evolutionary models of altruism. While kin biases in sharing are consistent with nepotism based on kin selection, there is much debate over the extent to which reciprocal altruism and tolerated scrounging provide useful explanations of observed behavior. This paper presents a model of optimal sharing breadth and depth, based on a general non-tit-for-tat form of risk-reduction based reciprocal altruism, and tests a series of predictions using data from Hiwi and Ache foragers. I show that large, high variance food items are shared more widely than small, easily acquired food items. Giving is conditional upon receiving in pairwise interactions and this correlation is usually stronger when the exchange of value rather than quantities is considered. Larger families and low producing families receive more and give less, consistent with the notion that marginal value may be a more salient currency than quantity.

Behavior of yellowfin (<Emphasis Type="Italic">Thunnus albacares</Emphasis>) and bigeye (<Emphasis Type="Italic">T. obesus</Emphasis>) tuna in a network of fish aggregating devices (FADs)

The influence of multiple anchored fish aggregating devices (FADs) on the spatial behavior of yellowfin (Thunnus albacares) and bigeye tuna (T. obesus) was investigated by equipping all thirteen FADs surrounding the island of Oahu (HI, USA) with automated sonic receivers (“listening stations”) and intra-peritoneally implanting individually coded acoustic transmitters in 45 yellowfin and 12 bigeye tuna. Thus, the FAD network became a multi-element passive observatory of the residence and movement characteristics of tuna within the array. Yellowfin tuna were detected within the FAD array for up to 150 days, while bigeye tuna were only observed up to a maximum of 10 days after tagging. Only eight yellowfin tuna (out of 45) and one bigeye tuna (out of 12) visited FADs other than their FAD of release. Those nine fish tended to visit nearest neighboring FADs and, in general, spent more time at their FAD of release than at the others. Fish visiting the same FAD several times or visiting other FADs tended to stay longer in the FAD network. A majority of tagged fish exhibited some synchronicity when departing the FADs but not all tagged fish departed a FAD at the same time: small groups of tagged fish left together while others remained. We hypothesize that tuna (at an individual or collective level) consider local conditions around any given FAD to be representative of the environment on a larger scale (e.g., the entire island) and when those conditions become unfavorable the tuna move to a completely different area. Thus, while the anchored FADs surrounding the island of Oahu might concentrate fish and make them more vulnerable to fishing, at a meso-scale they might not entrain fish longer than if there were no (or very few) FADs in the area. At the existing FAD density, the ‘island effect’ is more likely to be responsible for the general presence of fish around the island than the FADs. We recommend further investigation of this hypothesis.

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Social network analysis and valid Markov chain Monte Carlo tests of null models

Analyses of animal social networks derived from group-based associations often rely on randomisation methods developed in ecology (Manly, Ecology 76:1109–1115, 1995) and made available to the animal behaviour community through implementation of a pair-wise swapping algorithm by Bejder et al. (Anim Behav 56:719–725, 1998). We report a correctable flaw in this method and point the reader to a wider literature on the subject of null models in the ecology literature. We illustrate the importance of correcting the method using a toy network and use it to make a preliminary analysis of a network of associations among eagle rays.

Testing homogeneity of capture probabilities of animals in a removal experiment

Consider the removal experiment used to estimate population sizes. Statistical methods towards testing the homogeneity of capture probabilities of animals, including a graphical diagnostic and a formal test, are presented and illustrated by real biological examples. Simulation is used to assess the test and compare it with the χ² test.

Interoperable web GIS services for marine pollution monitoring and forecasting

This paper presents services and systems developed in the FP6 InterRisk (Interoperable GMES Services for Environmental Risk Management in Marine and Coastal Areas of Europe) project, which addresses the need for better access to information for risk management in Europe, both in cases of natural hazards and industrial accidents. The overall objective of the project is to develop a pilot system for interoperable GMES monitoring and forecasting services for environmental management in marine and coastal areas. This pilot system is based on established and widely adopted web-GIS standards, in line with INSPIRE recommendations. The pilot is comprised of, among other things, a portal and a web-GIS map viewer, both developed using open source tools. Providers using commercial tools adhering to the adopted standards, however, can also deliver products to the InterRisk pilot. The InterRisk services and system are based on a combination of free and commercial software, and have been demonstrated to end-users in three European areas: Norwegian, UK and Irish waters, and German and Polish waters. Products and services offered in these areas are presented, along with an outline of the technical development of web-GIS clients and portals.

Fishery resource management in Chilika lagoon: a study on coastal conservation in the Eastern Coast of India

A significant proportion of the fishing population comprises small-scale fishermen and many studies illustrate that these people are exploited by middlemen in the process of fish marketing combined with money lending. The negative dependency gives rise to poverty and triggers indiscriminate fish catch that threatens fishery resources depletion. This article explores the root causes of failures in resource-led development from the viewpoint of coastal resource conservation. The study presents a case study of Chilika lagoon, India and focuses on the interaction between small-scale fishermen and middlemen. The findings reveal that most of the small-scale fishermen have been exploited by specific middlemen and the underlying causes of the present fish marketing structure stem from (i) indebtedness and (ii) the unstable situation because of perpetual conflicts over fishery resources among the fishers across Chilika lagoon. Based on these observations, this article presents some recommendations on fishery resource conservation from the perspective of a fish marketing structure.

Multi-parameter renewal processes and simulation of forest fires

The concept of the renewal property is extended to processes indexed by a multidimensional time parameter. The definition given includes not only partial sum processes, but also Poisson processes and many other point processes whose jump points are not totally ordered. Various properties of renewal processes are discussed. Renewal processes are proposed as a basis for modelling the spread of a forest fire under a prevailing wind.

Flexible hierarchical mark-recapture modeling for open populations using WinBUGS

Hierarchical mark-recapture models offer three advantages over classical mark-recapture models: (i) they allow expression of complicated models in terms of simple components; (ii) they provide a convenient way of modeling missing data and latent variables in a way that allows expression of relationships involving latent variables in the model; (iii) they provide a convenient way of introducing parsimony into models involving many nuisance parameters. Expressing models using the complete data likelihood we show how many of the standard mark-recapture models for open populations can be readily fitted using the software WinBUGS. We include examples that illustrate fitting the Cormack–Jolly–Seber model, multi-state and multi-event models, models including auxiliary data, and models including density dependence.

Prospective spatial prediction of infectious disease: experience of New York State (USA) with West Nile Virus and proposed directions for improved surveillance

Infectious disease surveillance has become an international top priority due to the perceived risk of bioterrorism. This is driving the improvement of real-time geo-spatial surveillance systems for monitoring disease indicators, which is expected to have many benefits beyond detecting a bioterror event. West Nile Virus surveillance in New York State (USA) is highlighted as a working system that uses dead American Crows (Corvus brachyrhynchos) to prospectively indicate viral activity prior to human onset. A cross-disciplinary review is then presented to argue that this system, and infectious disease surveillance in general, can be improved by complementing spatial cluster detection of an outcome variable with predictive “risk mapping” that incorporates spatiotemporal data on the environment, climate and human population through the flexible class of generalized linear mixed models.

Benchmark calculations from summarized data: an example

Benchmark calculations often are made from data extracted from publications. Such data may not be in a form most appropriate for benchmark analysis, and, as a result, suboptimal and/or non-standard benchmark analyses are often applied. This problem can be mitigated in some cases using Monte Carlo computational methods that allow the likelihood of the published data to be calculated while still using an appropriate benchmark dose (BMD) definition. Such an approach is illustrated herein using data from a study of workers exposed to styrene, in which a hybrid BMD calculation is implemented from dose response data reported only as means and standard deviations of ratios of scores on neuropsychological tests from exposed subjects to corresponding scores from matched controls. The likelihood of the data is computed using a combination of analytic and Monte Carlo integration methods.

Maximum likelihood fitting of the Poisson lognormal distribution

In this paper some properties and analytic expressions regarding the Poisson lognormal distribution such as moments, maximum likelihood function and related derivatives are discussed. The author provides a sharp approximation of the integrals related to the Poisson lognormal probabilities and analyzes the choice of the initial values in the fitting procedure. Based on these he describes a new procedure for carrying out the maximum likelihood fitting of the truncated Poisson lognormal distribution. The method and results are illustrated on real data. The computer program for calculations is freely available.