Winners and Losers in a World with Global Warming: Noncooperation, Altruism, and Social Welfare

In this paper, global warming is an asymmetric transboundary externality which benefits some countries or regions and harms others. We use a simple two-country model to analyze the effects of global warming on resource allocations, the global-warming stock, and national and global welfare.     

Dispersal connectivity and reserve selection for marine conservation

Although larval dispersal is crucial for the persistence of most marine populations, dispersal connectivity between sites is rarely considered in designing marine protected area networks. In particular the role of structural characteristics (known as topology) for the network of larval dispersal routes in the conservation of metapopulations has not been addressed. To determine reserve site configurations that provide highest persistence values with respect to their connectivity characteristics, we model nine connectivity topological models derived from graph theory in a demographic metapopulation model. We identify reserve site configurations that provide the highest persistence values for each of the metapopulation connectivity models. Except for the minimally connected and fully connected populations, we observed two general ‘rules of thumb’ for optimising the mean life time for all topological models: firstly place the majority of reserves, so that they are neighbours of each other, on the sites where the number of connections between the populations is highest (hub), secondly when the reserves have occupied the majority of the vertices in the hub, then select another area of high connectivity and repeat. If there are no suitable hubs remaining then distribute the remaining reserves to isolated locations optimising contact with non-reserved sites.     

Resource allocation in two species systems: Is it worth acknowledging species interactions?

It is becoming increasingly popular to consider species interactions when managing ecological foodwebs. Such an approach is useful in determining how management can affect multiple species, with either beneficial or detrimental consequences. Identifying such actions is particularly valuable in the context of conservation decision making as funding is severely limited. This paper outlines a new approach that simplifies the resource allocation problem in a two species system for a range of species interactions: independent, mutualism, predator-prey, and competitive exclusion. We assume that both species are endangered and we do not account for decisions over time. We find that optimal funding allocation is to the conservation of the species with the highest marginal gain in expected probability of survival and that, across all except mutualist interaction types, optimal conservation funding allocation differs between species. Loss in efficiency from ignoring species interactions was most severe in predator-prey systems. The funding problem we address, where an ecosystem includes multiple threatened species, will only become more commonplace as increasing numbers of species worldwide become threatened.     

A stochastic model for estimating sustainable limits to wildlife mortality in a changing world

Human-caused mortality of wildlife is a pervasive threat to biodiversity. Assessing the population-level impact of fisheries bycatch and other human-caused mortality of wildlife has typically relied upon deterministic methods. However, population declines are often accelerated by stochastic factors that are not accounted for in such conventional methods. Building on the widely applied potential biological removal (PBR) equation, we devised a new population modeling approach for estimating sustainable limits to human-caused mortality and applied it in a case study of bottlenose dolphins affected by capture in an Australian demersal otter trawl fishery. Our approach, termed sustainable anthropogenic mortality in stochastic environments (SAMSE), incorporates environmental and demographic stochasticity, including the dependency of offspring on their mothers. The SAMSE limit is the maximum number of individuals that can be removed without causing negative stochastic population growth. We calculated a PBR of 16.2 dolphins per year based on the best abundance estimate available. In contrast, the SAMSE model indicated that only 2.3–8.0 dolphins could be removed annually without causing a population decline in a stochastic environment. These results suggest that reported bycatch rates are unsustainable in the long term, unless reproductive rates are consistently higher than average. The difference between the deterministic PBR calculation and the SAMSE limits showed that deterministic approaches may underestimate the true impact of human-caused mortality of wildlife. This highlights the importance of integrating stochasticity when evaluating the impact of bycatch or other human-caused mortality on wildlife, such as hunting, lethal control measures, and wind turbine collisions. Although population viability analysis (PVA) has been used to evaluate the impact of human-caused mortality, SAMSE represents a novel PVA framework that incorporates stochasticity for estimating acceptable levels of human-caused mortality. It offers a broadly applicable, stochastic addition to the demographic toolbox to evaluate the impact of human-caused mortality on wildlife.     

Spatial variability of infaunal nematode and polychaete assemblages in two muddy subtidal habitats

Spatial variation of populations and their assemblages is an important component of many aspects of ecology, including the maintenance of species diversity. In nature, organisms are generally aggregated in patches or form gradients or other spatially related patterns. This investigation quantified the degree of spatial structure in benthic invertebrate assemblages. It examined the distribution of infaunal assemblages of different size, mobility and contrasting life-history strategies (i.e. meiofaunal nematodes and macrofaunal polychaetes) in two offshore muddy habitats in the Celtic Deep and the NW Irish Sea off the west coast of the United Kingdom. The more heterogeneous habitat in the NW Irish Sea was characterised by higher tidal stress and bottom temperature while greater water depth, mean particle diameter and organic carbon content was typical for the comparatively homogeneous environment in the Celtic Deep. In both habitats, the environmental conditions became increasingly dissimilar with separation. A total of 125 nematode and 88 polychaete species were recorded with 69% of the nematode and 49% of polychaete species present at both study sites. Occurrence frequency of species, species diversity and average similarity of assemblage composition was higher in the Celtic Deep than in the NW Irish Sea. Results from correlation analyses revealed statistically robust relationships of community similarity and sample distance. Given their small size and low mobility, nematodes were more susceptible to within-habitat physical variability than larger-sized, more mobile polychaetes. This, coupled with limits to long-distance dispersal and likely restrictions in gene flow, resulted in a significant decrease in community similarity with distance at the spatial scales sampled (i.e. within 0.1–23 km). Polychaetes, in contrast, combined a higher dispersal potential (>23 km) with a relatively high tolerance to within-habitat environmental variability and these were the most likely causes for non-significant relationships between the similarity of their assemblages and sample distance. The potential mechanisms causing the observed variation and implications of results for environmental management strategies are discussed. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Conservation planning for successional landscapes

The systematic conservation planning literature invariably assumes that the biodiversity features being preserved in sites do not change through time. We develop a conservation planning framework for ecosystems where disturbance events and succession drive vegetation dynamics. The framework incorporates three key attributes of disturbance theory: heterogeneity in disturbance rates, spatial correlation between disturbance events and different impacts of disturbance. In our conservation problem we wish to maximise the chance that we represent a certain number of successional types given a cap on the number of sites we can conserve. Correlation between disturbance events dramatically complicates the problem of choosing the optimal suite of sites. However, in our problem we discover that spatial correlation in disturbances affects the optimal reserve network very little. The reason is twofold: (i) through our probabilistic framework we focus on the long-term effectiveness of reserve networks and (ii) in the dynamics considered in our model the state of a site is not only affected by the most recent (correlated) disturbance event but also by the site's long-term stochastic history which blurs the impact of spatial correlation. If successional states are the conservation target rather than individual species then, conserving a site can only contribute to meeting one target. However, given that correlation of disturbance events may be ignored, we show that if the number of candidate reserves is sufficiently large the statistical dependence of different conservation targets may be ignored, too. We conclude that the computational complexity of reserve selection methods for dynamic ecosystems can be much simpler than they first appear.     

Assessment of GM Crops in Commercial Agriculture

The caliber of recent discourse regarding geneticallymodified organisms (GMOs) has suffered from a lack of consensuson terminology, from the scarcity of evidence upon which toassess risk to health and to the environment, and from valuedifferences between proponents and opponents of GMOs. Towardsaddressing these issues, we present the thesis that GM should bedefined as the forcible insertion of DNA into a host genome,irrespective of the source of the DNA, and exclusive ofconventional or mutation breeding.Some defenders of the commercial use of GMOs have referred to thescientific work of GMO critics as ``junk science.' Such a claim isfalse and misleading, given that many papers critical of both theutility and safety of GMOs have been published in peer reviewedjournals by respected scientists. In contrast, there is a dearthof peer reviewed work to substantiate the frequently heardassertions of either safety or utility in GMOs. The polarity,which now characterizes much of the public discourse on GMOs,reflects not simply scientific disagreement, but alsodisagreement in underlying value assumptions. Value differencesstrongly affect the assessment of both benefit and harm fromGMOs.The concept of substantial equivalence occupies a pivotalposition in the GMO risk assessment process that is used in bothCanada and the US. A GMO judged to be substantially equivalent toa conventional product – as have all submissions to date – ispresumed to be safe enough for commercialization. The conclusionof safety – from both human health and environmental perspectives– should be based on scientific evidence, corroborated by actualexperimentation. However, regulators infer safety largely fromassumptions-based reasoning, with little or no experimentalvalidation. The judgement of safety because of substantialequivalence is a dubious argument by analogy.     

Environmental and social impacts of electricity utilization: broadening the debate

Exposure of small laboratory animals to power-frequency high-voltage electric fields was reported to have endocrinological effects, including changes in pineal melatonin levels. It has been assumed that these results are directly attributable to electric-field effects, but this article suggests that air ionization, produced by corona activity at the animals’ body surfaces, may have been biologically active and could be relevant to the interpretation of some epidemiological and other studies. Although presently a matter of dispute, there is evidence that atmospheric ionization may be biologically active and could provide an alternative explanation for at least some apparent electromagnetic field interactions with biological subjects. Consideration of the electricity utilization environment as a whole, rather than one selected component, could allow the introduction of lower-cost, precautionary and putative hazard remediation measures.     

Improving the risk–risk trade-off method for use in safety project appraisal responses

Environmental Economics and Policy Studies - The risk–risk trade-off method is a technique used to elicit the relative trade-off between changes in morbidity and mortality risks in stated...     

Effects of spatial autocorrelation and sampling design on estimates of protected area effectiveness

Estimating the effectiveness of protected areas (PAs) in reducing deforestation is useful to support decisions on whether to invest in better management of areas already protected or to create new ones. Statistical matching is commonly used to assess this effectiveness, but spatial autocorrelation and regional differences in protection effectiveness are frequently overlooked. Using Colombia as a case study, we employed statistical matching to account for confounding factors in park location and accounted for for spatial autocorrelation to determine statistical significance. We compared the performance of different matching procedures—ways of generating matching pairs at different scales—in estimating PA effectiveness. Differences in matching procedures affected covariate similarity between matched pairs (balance) and estimates of PA effectiveness in reducing deforestation. Independent matching yielded the greatest balance. On average 95% of variables in each region were balanced with independent matching, whereas 33% of variables were balanced when using the method that performed worst. The best estimates suggested that average deforestation inside protected areas in Colombia was 40% lower than in matched sites. Protection significantly reduced deforestation, but PA effectiveness differed among regions. Protected areas in Caribe were the most effective, whereas those in Orinoco and Pacific were least effective. Our results demonstrate that accounting for spatial autocorrelation and using independent matching for each subset of data is needed to infer the effectiveness of protection in reducing deforestation. Not accounting for spatial autocorrelation can distort the assessment of protection effectiveness, increasing type I and II errors and inflating effect size. Our method allowed improved estimates of protection effectiveness across scales and under different conditions and can be applied to other regions to effectively assess PA performance.