Multiple predators indirectly alter community assembly across ecological boundaries

Models of habitat selection often assume that organisms choose habitats based on their intrinsic quality, regardless of the position of these habitats relative to low-quality habitats in the landscape. We created a habitat matrix in which high-quality (predator-free) aquatic habitat patches were positioned adjacent to (predator-associated) or isolated from (control) patches with single or two species of caged predators. After 16 days of colonization, larval insect abundance was reduced by 50% on average in both the predator and predator-associated treatments relative to isolated controls. Effects were largely similar among predator treatments despite variation in number of predator species, predator biomass, and whether predators were native or nonnative. Importantly, the strength of effects did not depend on whether predators were physically present. These results demonstrate that predator cues can cascade with equal strength across ecological boundaries, indirectly altering community assembly via habitat selection in intrinsically high-quality habitats.     

Habitat selection predicts genetic relatedness in an alpine ungulate

Landscape heterogeneity plays an integral role in shaping ecological and evolutionary processes. Despite links between the two disciplines, ecologists and population geneticists have taken different approaches to evaluating habitat selection, animal movement, and gene flow across the landscape. Ecologists commonly use statistical models such as resource selection functions (RSFs) to identify habitat features disproportionately selected by animals, whereas population genetic approaches model genetic differentiation according to the distribution of habitat variables. We combined ecological and genetic approaches by using RSFs to predict genetic relatedness across a heterogeneous landscape. We constructed sex- and season-specific resistance surfaces based on RSFs estimated using data from 102 GPS (global positioning system) radio-collared mountain goats (Oreamnos americanus) in southeast Alaska, USA. Based on mountain goat ecology, we hypothesized that summer and male surfaces would be the best predictors of relatedness. All individuals were genotyped at 22 microsatellite loci, which we used to estimate genetic relatedness. Summer resistance surfaces derived from RSFs were the best predictors of genetic relatedness, and winter models the poorest. Mountain goats generally selected for areas close to escape terrain and with a high heat load (a metric related to vegetative productivity and snow depth), while avoiding valleys. Male- and female-specific surfaces were similar, except for winter, for which male habitat selection better predicted genetic relatedness. The null models of isolation-by-distance and barrier only outperformed the winter models. This study merges high-resolution individual locations through GPS telemetry and genetic data, that can be used to validate and parameterize landscape genetics models, and further elucidates the relationship between landscape heterogeneity and genetic differentiation.     

Being young in a changing world: how temperature and salinity changes interactively modify the performance of larval stages of the barnacle <Emphasis Type="Italic">Amphibalanus improvisus</Emphasis>

The fate of key species, such as the barnacle Amphibalanus improvisus, in the course of global change is of particular interest since any change in their abundance and/or performance may entail community-wide effects. In the fluctuating Western Baltic, species typically experience a broad range of environmental conditions, which may preselect them to better cope with climate change. In this study, we examined the sensitivity of two crucial ontogenetic phases (naupliar, cypris) of the barnacle toward a range of temperature (12, 20, and 28°C) and salinity (5, 15, and 30 psu) combinations. Under all salinity treatments, nauplii developed faster at intermediate and high temperatures. Cyprid metamorphosis success, in contrast, was interactively impacted by temperature and salinity. Survival of nauplii decreased with increasing salinity under all temperature treatments. Highest settlement rates occurred at the intermediate temperature and salinity combination, i.e., 20°C and 15 psu. Settlement success of “naive” cyprids, i.e., when nauplii were raised in the absence of stress (20°C/15 psu), was less impacted by stressful temperature/salinity combinations than that of cyprids with a stress history. Here, settlement success was highest at 30 psu particularly at low and high temperatures. Surprisingly, larval survival was not highest under the conditions typical for the Kiel Fjord at the season of peak settlement (20°C/15 psu). The proportion of nauplii that ultimately transformed to attached juveniles was, however, highest under these “home” conditions. Overall, only particularly stressful combinations of temperature and salinity substantially reduced larval performance and development. Given more time for adaptation, the relatively smooth climate shifts predicted will probably not dramatically affect this species.     

A 200-year perspective on alternative stable state theory and lake management from a biomanipulated shallow lake

Multiple stressors to a shallow lake ecosystem have the ability to control the relative stability of alternative states (clear, macrophyte-dominated or turbid, algal-dominated). As a consequence, the use of remedial biomanipulations to induce trophic cascades and shift a turbid lake to a clear state is often only a temporary solution. Here we show the instability of short-term manipulations in the shallow Lake Christina (Minnesota, USA) is governed by the long-term state following a regime shift in the lake. During the modern, managed period of the lake, three top-down manipulations (fish kills) were undertaken inducing temporary (5-10 years) unstable clear-water states. Paleoecological remains of diatoms, along with proxies of primary production (total chlorophyll a and total organic carbon accumulation rate) and trophic state (total P) from sediment records clearly show a single regime shift in the lake during the early 1950s; following this shift, the functioning of the lake ecosystem is dominated by a persistent turbid state. We find that multiple stressors contributed to the regime shift. First, the lake began to eutrophy (from agricultural land use and/or increased waterfowl populations), leading to a dramatic increase in primary production. Soon after, the construction of a dam in 1936 effectively doubled the depth of the lake, compounded by increases in regional humidity; this resulted in an increase in planktivorous and benthivorous fish reducing phytoplankton grazers. These factors further conspired to increase the stability of a turbid regime during the modern managed period, such that switches to a clear-water state were inherently unstable and the lake consistently returned to a turbid state. We conclude that while top-down manipulations have had measurable impacts on the lake state, they have not been effective in providing a return to an ecosystem similar to the stable historical period. Our work offers an example of a well-studied ecosystem forced by multiple stressors into a new long-term managed period, where manipulated clear-water states are temporary, managed features.     

Randomized graph sampling

Randomized graph sampling (RGS) is an approach for sampling populations associated with or describable as graphs, when the structure of the graph is known and the parameter of interest is the total weight of the graph. RGS is related to, but distinct from, other graph-based approaches such as snowball and network sampling. Graph elements are clustered into walks that reflect the structure of the graph, as well as operational constraints on sampling. The basic estimator in RGS can be constructed as a Horvitz-Thompson estimator. I prove it to be design-unbiased, and also show design-unbiasedness of an estimator of the sample variance when walks are sampled with replacement. Covariates can be employed for variance reduction either through improved assignment of selection probabilities to walks in the design step, or through the use of alternative estimators during analysis. The approach is illustrated with a trail maintenance example, which demonstrates that complicated approaches to assignment of selection probabilities can be counterproductive. I describe conditions under which RGS may be efficient in practice, and suggest possible applications.     

The emergence of team helping norms: Foundations within members' attributes and behavior

This research examined the antecedents of organizational citizenship behavior helping norms in teams, specifically with regard to how members' personality, values, beliefs, and helping behavior predict the emergence of helping norms in newly formed project teams. We drew from theory on emergent phenomena and team composition research to propose and test a compilation model of how helping norms are influenced by having at least one member with particularly low (minimum) or high (maximum) levels of attributes that may influence helping‐norm development (i.e., conscientiousness, agreeableness, other‐oriented values, personal helping beliefs). We further examined the extent to which members' helping behaviors, as rated by peers, predicted helping norms and whether these behaviors mediated the relationship between individual attributes and helping norms. The results of a longitudinal study of 47 student project teams revealed that teams' minimums on agreeableness, other‐oriented values, and personal helping beliefs had direct relationships with helping‐norm emergence, and the effects of agreeableness were mediated through mean helping behavior. By contrast, teams' maximums on these attributes showed no relationships with helping norms, and only a team maximum on agreeableness was associated with teams' mean helping behavior. Copyright © 2011 John Wiley & Sons, Ltd.     

“They’re lunatics on the road”: Exploring the normative influences of parents,friends, and police on young novices’ risky driving decisions

PurposeYoung novice drivers experience significantly greater risk of being injured or killed in car crashes than older more experienced drivers. This research utilised a qualitative approach guided by the framework of Akers’ social learning theory. It explored young novice drivers’ perspectives on risky driving including rewards and punishments expected from and administered by parents, friends, and police, imitation of parents’ and friends’ driving, and advantages and disadvantages of risky driving.MethodsTwenty-one young drivers (12 females, 9 males) aged 16–25 years (M = 17.71 years, SD = 2.15) with a Learner (n = 11) or Provisional (n = 10) driver licence participated in individual or small group interviews.Findings and conclusionsContent analysis supported four themes: (1) rewards and (2) punishments for risky driving, and the influence of (3) parents and (4) friends. The young novice drivers differed in their vulnerability to the negative influences of friends and parents, with some novices advising they were able to resist risky normative influences whilst others felt they could not. The authority of the police as enforcers of road rules was either accepted and respected or seen as being used to persecute young novices. These findings suggest that road safety interventions should consider the normative influence of parents and friends on the risky and safe behaviour of young novices. Police were also seen as influential upon behaviour. Future research should explore the complicated relationship between parents, friends, the police, young novices, and their risky driving behaviour.     

High-level techno-economic assessment of negative emissions technologies

This paper presents results from research conducted to provide a high level techno-economic and performance assessments of various emerging technologies for capturing CO₂ from the air, directly and indirectly, on a life-cycle basis. The technologies assessed include ‘artificial trees’, the soda lime process, augmented ocean disposal, biochar and bio-energy with carbon capture and storage.These technologies are subjected to quantitative and qualitative analyses, based on the most recent peer reviewed data in the literature, to identify their potential performance as well as the technical and non-technical barriers to their adoption and scale up. Key findings for each technology are presented which seek to highlight the state of technological development and research needs, the anticipated life cycle capture cost in $/tCO₂ based on their potential to deliver a 0.1 ppm CO₂ reduction per annum, policy requirements for scale up and, in light of these findings, the likely role that they will play in addressing climate change and broader environmental issues in the medium to long term.The key finding from the work is that the degree of scale-up required for negative emissions technologies to have a material impact on atmospheric emissions (i.e. at a ppm level) is probably unrealistic in less than 20 years. Therefore, emissions prevention efforts should remain the main focus in addressing climate change and the likely role for negative emissions technologies will be in augmenting a suite of mitigation measures targeting economically or practically difficult emissions.     

Negative carbon via Ocean Afforestation

Ocean Afforestation, more precisely Ocean Macroalgal Afforestation (OMA), has the potential to reduce atmospheric carbon dioxide concentrations through expanding natural populations of macroalgae, which absorb carbon dioxide, then are harvested to produce biomethane and biocarbon dioxide via anaerobic digestion. The plant nutrients remaining after digestion are recycled to expand the algal forest and increase fish populations. A mass balance has been calculated from known data and applied to produce a life cycle assessment and economic analysis. This analysis shows the potential of Ocean Afforestation to produce 12 billion tons per year of biomethane while storing 19 billion tons of CO₂ per year directly from biogas production, plus up to 34 billion tons per year from carbon capture of the biomethane combustion exhaust. These rates are based on macro-algae forests covering 9% of the world's ocean surface, which could produce sufficient biomethane to replace all of today's needs in fossil fuel energy, while removing 53 billion tons of CO₂ per year from the atmosphere, restoring pre-industrial levels. This amount of biomass could also increase sustainable fish production to potentially provide 200 kg/yr/person for 10 billion people. Additional benefits are reduction in ocean acidification and increased ocean primary productivity and biodiversity.     

Unravelling a ‘miner’s myth’ that environmental contamination in mining towns is naturally occurring

Australia has a long history of metal mining and smelting. Extraction and processing have resulted in elevated levels of toxic metals surrounding mining operations, which have adverse health effects, particularly to children. Resource companies, government agencies and employees often construct ‘myths’ to down play potential exposure risks and responsibility arising from operating emissions. Typical statements include: contaminants are naturally occurring, the wind blows emissions away from residential areas, contaminants are not bioavailable, or the problem is a legacy issue and not related to current operations. Evidence from mining and smelting towns shows that such ‘myths’ are exactly that. In mining towns, the default and primary defence against contamination is that elevated metals in adjacent urban environments are from the erosion and weathering of the ore bodies over millennia—hence ‘naturally occurring’. Not only is this a difficult argument to unravel from an evidence-based perspective, but also it causes confusion and delays remediation work, hindering efforts to reduce harmful exposures to children. An example of this situation is from Broken Hill, New South Wales, home to one of the world’s largest lead–zinc–silver ore body, which has been mined continuously for over 130 years. Environmental metal concentration and lead isotopic data from soil samples collected from across Broken Hill are used to establish the nature and timing of lead contamination. We use multiple lines of evidence to unravel a ‘miner’s myth’ by evaluating current soil metal concentrations and lead isotopic compositions, geological data, historical environmental assessments and old photographic evidence to assess the impacts from early smelting along with mining to the surface soils in the city.