Demystifying public environmental concerns: Implementing community assessments

Failure to resolve environmental concerns raised by the public can be costly for both public and private sector organizations. Designing effective community relations programs to address such issues requires an intimate understanding of the community and the stakeholders within it. The community assessment process provides insights into the reasons behind stakeholders' environmental concerns and how best to address them. Moreover, the assessment process can provide predictive information, so that managers can anticipate both the emergence of environmental concerns and the likely response patterns of stakeholders. The assessment process, which makes use of both qualitative information and quantitative data, tracks closely with the methodology used in industry analyses conducted by corporate strategic planners. Regrettably, many of the companies that have excellent skills in industry analysis fail to use their expertise to address environmental concerns involving their own plants. This article seeks to aid the reader in understanding how basic analytical skills can be used to understand and effectively address environmental concerns at the community level.     

Incorporating animal behavior into seed dispersal models: implications for seed shadows

Seed dispersal fundamentally influences plant population and community dynamics but is difficult to quantify directly. Consequently, models are frequently used to describe the seed shadow (the seed deposition pattern of a plant population). For vertebrate-dispersed plants, animal behavior is known to influence seed shadows but is poorly integrated in seed dispersal models. Here, we illustrate a modeling approach that incorporates animal behavior and develop a stochastic, spatially explicit simulation model that predicts the seed shadow for a primate-dispersed tree species (Virola calophylla, Myristicaceae) at the forest stand scale. The model was parameterized from field-collected data on fruit production and seed dispersal, behaviors and movement patterns of the key disperser, the spider monkey (Ateles paniscus), densities of dispersed and non-dispersed seeds, and direct estimates of seed dispersal distances. Our model demonstrated that the spatial scale of dispersal for this V. calophylla population was large, as spider monkeys routinely dispersed seeds >100 m, a commonly used threshold for long-distance dispersal. The simulated seed shadow was heterogeneous, with high spatial variance in seed density resulting largely from behaviors and movement patterns of spider monkeys that aggregated seeds (dispersal at their sleeping sites) and that scattered seeds (dispersal during diurnal foraging and resting). The single-distribution dispersal kernels frequently used to model dispersal substantially underestimated this variance and poorly fit the simulated seed-dispersal curve, primarily because of its multimodality, and a mixture distribution always fit the simulated dispersal curve better. Both seed shadow heterogeneity and dispersal curve multimodality arose directly from these different dispersal processes generated by spider monkeys. Compared to models that did not account for disperser behavior, our modeling approach improved prediction of the seed shadow of this V. calophylla population. An important function of seed dispersal models is to use the seed shadows they predict to estimate components of plant demography, particularly seedling population dynamics and distributions. Our model demonstrated that improved seed shadow prediction for animal-dispersed plants can be accomplished by incorporating spatially explicit information on disperser behavior and movements, using scales large enough to capture routine long-distance dispersal, and using dispersal kernels, such as mixture distributions, that account for spatially aggregated dispersal.     

The role of schools in helping communities copes with earthquake disasters: the case of the 2010–2011 New Zealand earthquakes

ABSTRACT

This article draws from the author’s four-year study of five school communities hit by the 2010–2011 earthquake sequence in the Canterbury region of New Zealand to highlight the roles that schools played in supporting their communities in the aftermath of the disaster. The article begins by synthesising the relevant literature on disasters, schools in earthquake disasters, and the importance of schools to their communities, pre- and post-disaster. The following themes from the data are discussed: (a) the role of schools in their communities prior to the earthquakes; (b) the role of schools in immediate rescue and response; (c) the role of schools in short-term relief; and (d) the role of schools in long-term recovery. The author then argues that as more evidence shows that schools play such crucial roles in post-disaster response and recovery, we need to better prepare and support them to undertake these functions. Further, we need to recognise the wider roles schools play supporting local communities to build and sustain resilience as part of on-going community cohesion and connectedness, so that society is better prepared when major disasters occur.     

The human cervical spine in tension: effects of frame and fixation compliance on structural responses

There is little data available on the responses of the human cervical spine to tensile loading. Such tests are mechanistically and technically challenging due to the variety of end conditions that need to be imposed and the difficulty of strong specimen fixation. As a result, spine specimens need to be tested using fairly complex, and potentially compliant, apparati in order to fully characterize the mechanical responses of each specimen. This, combined with the relatively high stiffness of human spine specimens, can result in errors in stiffness calculations. In this study, 18 specimen preparations were tested in tension. Tests were performed on whole cervical spines and on spine segments. On average, the linear stiffness of the segment preparations was 257 N/mm, and the stiffness of the whole cervical spine was 48 N/mm. The test frame was found to have a stiffness of 933 N/mm. Assembling a whole spine from a series combination of eight segments with a stiffness of 257 N/mm results in an estimated whole spine stiffness of 32.1 N/mm (32% error). The segment stiffnesses were corrected by assuming that the segment preparation stiffness is a series combination of the stiffnesses of the segment and the frame. This resulted in an average corrected segment stiffness of 356 N/mm. Taking the frame compliance into account, the whole spine stiffness is 51 N/mm. A series combination of eight segments using the corrected stiffnesses results in an estimated whole spine stiffness of 45.0 N/mm (12% error). We report both linear and nonlinear stiffness models for male spines and conclude that the compliance of the frame and the fixation must be quantified in all tension studies of spinal segments. Further, reported stiffness should be adjusted to account for frame and fixation compliance.