Sustainable coastal communities in the age of coastal storms: Reconceptualising coastal planning as ‘new’ naval architecture

Hurricanes devastated the Gulf coast of the USA in 2005. Hurricane Katrina, in particular, highlighted the compelling need to build more sustainable and hazard-resilient communities. Much can be learned from recovery efforts to rebuild the Gulf coast. Personal observations and interviews with planners, academics and others involved in recovery efforts inform this analysis, which focuses on New Orleans. A conceptual framework is developed and principles and operational imperatives outlined to guide action for building sustainable, hazard-resilient communities. Such communities will remain elusive unless ‘business as usual’ is confronted by a transformational process of developmental planning. Sustainable, hazard-resilient coastal communities are founded upon robust ‘critical infrastructure’ that is secured by planning and decision-making processes that enable coastal communities to build ‘layers of resilience’ to overcome ‘waves of adversity’. Planners need to take on a redefined role—as ‘new naval architects’—to design and build communities that are ‘sea-worthy’ in this age of coastal storms.

Spatial assessment of sea level rise on Martinique’s coastal zone and analysis of planning frameworks for adaptation

Accelerated sea level rise and hurricanes are increasingly influencing human coastal activities. With respect to the projected continuation of accelerated sea level rise and global warming one must count with additional expenses for adaptation strategies along the coasts. On the mountainous island Martinique the majority of settlements are situated along the coast almost at sea level. But potential rises in sea level and its impacts are not addressed in coastal management, even though saltwater intrusion and coastal erosion with increasing offshore loss of sediment are locally already a severe problem. At a sea level rise of 50 cm, one fourth of Martinique’s coastline will be affected by erosion and one fifth of the islands surface will have high probability to get flooded during coastal hazards. This is a growth of 5% of the impact area in comparison to present conditions. This article analyses potential adaptation strategies and argues that the development of a coastal zone management plan considering sea level rise and its impact area is of utmost importance. Empirical assessment models in combination with spatial analysis are useful in obtaining statements about coastal impacts concerning sea level rise. This paper sees itself as recommendation of action not only for Martinique.

Hierarchical spatial point process analysis for a plant community with high biodiversity

A complex multivariate spatial point pattern of a plant community with high biodiversity is modelled using a hierarchical multivariate point process model. In the model, interactions between plants with different post-fire regeneration strategies are of key interest. We consider initially a maximum likelihood approach to inference where problems arise due to unknown interaction radii for the plants. We next demonstrate that a Bayesian approach provides a flexible framework for incorporating prior information concerning the interaction radii. From an ecological perspective, we are able both to confirm existing knowledge on species’ interactions and to generate new biological questions and hypotheses on species’ interactions.

“Protecting coastal zones in the Mediterranean: an economic and regulatory analysis”

This paper examines existing measures taken to protect the coastal zones of the Mediterranean Sea and assesses their success. A summary of the main pressures facing this region is given, followed by an analysis of the legislation covering coastal zone development in ten countries: Algeria, Croatia, Egypt, France, Israel, Italy, Malta, Spain, Tunisia and Turkey. The paper finds that not all of these States have legislation specifically covering coastal zones, but there is concern in all areas that existing legislation is not working. The costs and benefits of controlling coastal development are examined. Firstly, a literature review of valuation studies identifies a range of values placed on the developed and undeveloped coastline for both users and local property owners. These values were then used in a model to evaluate policy options to control development of a stretch of coastline. The model indicates that a stricter control regime of coastal development may provide significant benefits.

Methodological approach of coastal areas concerning typology and spatial indicators, in the context of integrated management and environmental assessment

The general objective of this paper is to trigger off the development of a more comprehensive approach to Hellenic coastal areas (in the perspective of territorial cohesion), at local level and especially along the non-urban areas close to the sea. Methodological issues linked to the building of an appropriate coastal database constitute the key goal of this paper (the space and time scale, the relationship to the already proposed set of indicators, the impact of driving forces and policies, the possible sources of data and their feasibility etc.). Furthermore, specific emphasis should be given to the choice of new indicators, particularly for the coastal abiotic environment and the land cover/uses along coastal areas, especially near the seafront. Those indicators should be able to aid the formation (in the near future) of an algorithm linked to the total man-made activities in coastal areas. In conclusion, this paper will be considered successful if the just above illustrated objectives could enrich the argument about the typology of coastal areas and the development of a spatial (coastal) observatory. Actually, this paper is part of a broader research of the author regarding the monitoring of coastal spatial changes in different scales (AMICA, “Appraisal of man-made interventions along the Hellenic coastal areas”). This research aims to broaden the coastal knowledge (not only by means of coastal data) on behalf of all stakeholders been implicated into sustainable spatial planning, integrated coastal management and the strategic environmental assessment along coastal areas.

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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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.

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.

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.

A Bayesian approach to multi-source forest area estimation

In efforts such as land use change monitoring, carbon budgeting, and forecasting ecological conditions and timber supply, there is increasing demand for regional and national data layers depicting forest cover. These data layers must permit small area estimates of forest area and, most importantly, provide associated error estimates. This paper presents a model-based approach for coupling mid-resolution satellite imagery with plot-based forest inventory data to produce estimates of probability of forest and associated error at the pixel-level. The proposed Bayesian hierarchical model provides access to each pixel’s posterior predictive distribution allowing for a highly flexible analysis of pixel and multi-pixel areas of interest. The paper presents a trial using multiple dates of Landsat imagery and USDA Forest Service Forest Inventory and Analysis plot data. The results describe the spatial dependence structure within the trial site, provide pixel and multi-pixel summaries of probability of forest land use, and explore discretization schemes of the posterior predictive distributions to forest and non-forest classes. Model prediction results of a holdout set analysis suggest the proposed model provides high classification accuracy, 88%, for the trial site.

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.

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.

Some comments on design-based line-intersect sampling with segmented transects

Line-intersect sampling based on segmented transects is adopted in many forest inventories to quantify important ecological indicators such as coarse woody debris attributes. By assuming a design-based approach, Affleck, Gregoire and Valentine (2005, Environ Ecol Stat 12:139–154) have recently proposed a sampling protocol for this line-intersect setting and have suggested an estimation method based on linear homogeneous estimators. However, their proposal does not encompass the estimation procedure currently adopted in some national forest inventories. Hence, the present paper aims to introduce a unifying perspective for both methods. Moreover, it is shown that the two procedures give rise to coincident estimators for almost all the usual field applications. Finally, some strategies for efficient segmented-transect replications are considered.

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.

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.

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.

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.

Is bird song a reliable signal of aggressive intent?

In this commentary, we discuss recent experiments on the reliability of bird song as a signal of aggressive intent during territorial conflicts. We outline relevant theoretical views on honest signaling, highlighting the vulnerability handicap hypothesis as a possible explanation for soft song’s reliability in predicting attack. We also sketch possible methods of testing whether soft song agrees with key predictions of the vulnerability handicap hypothesis. Finally, we suggest possible empirical refinements that may be useful in future studies of signals of intent, both in birds and in animals broadly. In particular, we argue that future studies of intent should strive to incorporate the following elements into their experimental design: (1) multi-modal signal components, (2) interaction dynamics, and (3) minimal time intervals. Simulated exchanges using dynamically interactive models may provide a powerful means of incorporating all three of these design features simultaneously.

Replace the NOAEL and LOAEL with the BMDL01 and BMDL10

Although benchmark-dose methodology has existed for more than 20 years, benchmark doses (BMDs) still have not fully supplanted the no-observed-adverse-effect level (NOAEL) and lowest-observed-adverse-effect level (LOAEL) as points of departure from the experimental dose–response range for setting acceptable exposure levels of toxic substances. Among the issues involved in replacing the NOAEL (LOAEL) with a BMD are (1) which added risk level(s) above background risk should be targeted as benchmark responses (BMRs), (2) whether to apply the BMD methodology to both carcinogenic and noncarcinogenic toxic effects, and (3) how to model continuous health effects that aren’t observed in a natural risk-based context like dichotomous health effects. This paper addresses these issues and recommends specific BMDs to replace the NOAEL and LOAEL.