Impacts of climate variability and human colonization on the vegetation of the Galápagos Islands

A high-resolution (2-9 year sampling interval) fossil pollen record from the Galápagos Islands, which spans the last 2690 years, reveals considerable ecosystem stability. Vegetation changes associated with independently derived histories of El Ni?o Southern Oscillation variability provided evidence of shifts in the relative abundance of individual species rather than immigration or extinction. Droughts associated with the Medieval Climate Anomaly induced rapid ecological change that was followed by a reversion to the previous state. The paleoecological data suggested nonneutral responses to climatic forcing in this ecosystem prior to the period of human influence. Human impacts on the islands are evident in the record. A marked decline in long-term codominants of the pollen record, Alternanthera and Acalypha, produced a flora without modern analogue before 1930. Intensified animal husbandry after ca. 1930 may have induced the local extinction of Acalypha and Alternanthera. Reductions in populations of grazing animals in the 1970s and 1980s did not result in the return of the native flora, but in invasions by exotic species. After ca. 1970 the trajectory of habitat change accelerated, continuously moving the ecosystem away from the observed range of variability in the previous 2690 years toward a novel ecosystem. The last 40 years of the record also suggest unprecedented transport of lowland pollen to the uplands, consistent with intensified convection and warmer wet seasons.     

Invasive ecosystem engineer selects for different phenotypes of an associated native species

Invasive habitat-forming ecosystem engineers modify the abiotic environment and thus represent a major perturbation to many ecosystems. Because native species often persist in these invaded habitats but have no shared history with the ecosystem engineer, the engineer may impose novel selective pressure on native species. In this study, we used a phenotypic selection framework to determine whether an invasive habitat-forming ecosystem engineer (the seaweed Caulerpa taxifolia) selects for different phenotypes of a common co-occurring native species (the bivalve Anadara trapezia). Compared to unvegetated habitat, Caulerpa habitat has lower water flow, lower dissolved oxygen, and sediments are more silty and anoxic. We determined the performance consequences of variation in key functional traits that may be affected by these abiotic changes (shell morphology, gill mass, and palp mass) for Anadara transplanted into Caulerpa and unvegetated habitat. Both linear and nonlinear performance gradients in Anadara differed between habitats, and these gradients were stronger in Caulerpa compared to unvegetated sediment. Moreover, in Caulerpa alternate phenotypes performed well, and these phenotypes were different from the dominant phenotype in unvegetated sediment. By demonstrating that phenotype-performance gradients differ between habitats, we have highlighted a role for Caulerpa as an agent of selection on native species.     

Seed terminal velocity, wind turbulence, and demography drive the spread of an invasive tree in an analytical model

Little is known about the relative importance of mechanistic drivers of plant spread, particularly when long-distance dispersal (LDD) events occur. Most methods to date approach LDD phenomenologically, and all mechanistic models, with one exception, have been implemented through simulation. Furthermore, the few recent mechanistically derived spread models have examined the relative role of different dispersal parameters using simulations, and a formal analytical approach has not yet been implemented. Here we incorporate an analytical mechanistic wind dispersal model (WALD) into a demographic matrix model within an analytical integrodifference equation spread model. We carry out analytical perturbation analysis on the combined model to determine the relative effects of dispersal and demographic traits and wind statistics on the spread of an invasive tree. Models are parameterized using data collected in situ and tested using independent data on historical spread. Predicted spread rates and direction match well the two historical phases of observed spread. Seed terminal velocity has the greatest potential influence on spread rate, and three wind properties (turbulence coefficient, mean horizontal wind speed, and standard deviation of vertical wind speed) are also important. Fecundity has marginal importance for spread rate, but juvenile survival and establishment are consistently important. This coupled empirical/theoretical framework enables prediction of plant spread rate and direction using fundamental dispersal and demographic parameters and identifies the traits and environmental conditions that facilitate spread. The development of an analytical perturbation analysis for a mechanistic spread model will enable multispecies comparative studies to be easily implemented in the future.     

Evaluation of fast atmospheric dispersion models in a regular street network

Environmental Fluid Mechanics - The need to balance computational speed and simulation accuracy is a key challenge in designing atmospheric dispersion models that can be used in scenarios where...     

Assessing plausible rates of population growth in humpback whales from life-history data

The rate of growth of any population is a quantity of interest in conservation and management and is constrained by biological factors. In this study, recent data on life-history parameters influencing rates of population growth in humpback whales, including survival, age at first parturition and calving rate are reviewed. Monte Carlo simulations are used to compute a distribution of rates of increase (ROIs) taking into account uncertainty in biological parameter estimates. Two approaches for computing juvenile survival are proposed, which taken into account along with other life-history data, resulted in the following estimates of the rate of population growth: Approach A: mean of 7.3%/year (95% CI = 3.5–10.5%/year) and Approach B: mean of 8.6%/year (95% CI = 5.0–11.4%/year). It is proposed that the upper 99% quantile of the resulting distribution of the ROI for Approach B (11.8%/year) be established as the maximum plausible ROI for humpback whales and be used in population assessment of the species. Possible sources of positive and negative biases in the present estimates are presented and include measurement error in estimation of life-history parameters, changes in the environment within the period these quantities are measured, density dependence or other natural factors. However, it is difficult to evaluate potential biases without additional data. The methods presented in this study can be applied to other species for which life-history parameters are available and are useful in assessing plausibility in the estimation of population growth rates from time series of abundance estimates.     

Studying dispersal at the landscape scale: efficient combination of population surveys and capture-recapture data

Researchers often rely on capture-mark-recapture (CMR) data to study animal dispersal in the wild. Yet their spatial coverage often does not encompass the entire dispersal range of the study individuals, sometimes producing misleading results. Information contained in population surveys and variation in population spatial structure can be used to overcome this issue. We build an integrated model in a multisite context in which CMR data are only collected at a subset of sites, but numbers of breeding pairs are counted at all sites. In a Black-headed Gull Chroicocephalus ridibundus population, the integrated-modeling approach induces an increase in precision for the demographic parameters of interest (variances, on average, were decreased by 20%) and provides a more precise extrapolation of results from the CMR data to the whole population. Patterns of condition-dependent dispersal are therefore made easier to detect, and we obtain evidence for colony-size dependence in recruitment, dispersal, and breeding success. These results suggest that first-time breeders disperse to small colonies in order to recruit earlier. The exchange of experienced breeders between colonies appears as a main determinant of the observed variation in colony sizes.     

Persistence models for mark-recapture

The stable of models available for analyzing mark-recapture data (Otis et al. Wild Momogr 66:135, 1978) includes those having behavioral characteristics, time variation, heterogeneity, along with combinations of those characteristics. This paper proposes use of a series of models based on the persistence model of Ramsey and Usner (Biometrics 59:331–339, 2003). We show that persistence can be modeled in combination with behavior and with time variation. We apply the persistence model to situations in which capture occasions are not equally-spaced in time. Two case studies illustrate the use of these extended persistence models.     

A quantitative risk management framework for dust and hybrid mixture explosions

Dust and hybrid-mixture explosions continue to occur in industrial processes that handle fine powders and flammable gases. Considerable research is therefore conducted throughout the world with the objective of both preventing the occurrence and mitigating the consequences of such events. In the current work, research has been undertaken to help move the field of dust explosion prevention and mitigation from its current emphasis on hazards (with an accompanying reliance on primarily engineered safety features) to a focus on risk (with an accompanying reliance on hierarchical, risk-based, decision-making tools). Employing the principles of quantitative risk assessment (QRA) of dust and hybrid-mixture explosions, a methodological framework for the management of these risks has been developed.The QRA framework is based on hazard identification via credible accident scenarios for dust explosions, followed by probabilistic fault-tree analysis (using Relex – Reliability Excellence – software) and consequence severity analysis (using DESC – Dust Explosion Simulation Code – software). Identification of risk reduction measures in the framework is accomplished in a hierarchical manner by considering inherent safety measures, passive and active engineered devices, and procedural measures (in that order). An industrial case study is presented to show how inherent safety measures such as dust minimization and dust/process moderation can be helpful in reducing dust and hybrid-mixture explosion consequences in a 400-m³ polyethylene storage silo.     

An optimal level of dust explosion risk management: Framework and application

The current research provides guidance on the prevention and mitigation of dust explosion using a Quantitative Risk Management Framework (QRMF). Using concepts drawn from previous studies, the framework consists of three main steps: (i) a new combined safety management protocol, (ii) the use of DESC (Dust Explosion Simulation Code) and FTA (Fault Tree Analysis) to assess explosion consequences and likelihood, respectively, and (iii) application of the hierarchy of controls (inherent, engineered and procedural safety). QRMF assessment of an industrial case study showed that the original process was at high risk. DESC simulations and Probit equations determined the destructive percentages. FTAs revealed high probabilities of explosion occurrence; in addition, detailed individual and societal risks calculations were made, before and after the framework was applied. Based on the hierarchy of controls technique, the framework showed significant risk reduction to the point where the residual risk was acceptable for the process.     

Analyzing system safety and risks under uncertainty using a bow-tie diagram: An innovative approach

A bow-tie diagram combines a fault tree and an event tree to represent the risk control parameters on a common platform for mitigating an accident. Quantitative analysis of a bow-tie is still a major challenge since it follows the traditional assumptions of fault and event tree analyses. The assumptions consider the crisp probabilities and “independent” relationships for the input events. The crisp probabilities for the input events are often missing or hard to come by, which introduces data uncertainty. The assumption of “independence” introduces model uncertainty. Elicitation of expert's knowledge for the missing data may provide an alternative; however, such knowledge incorporates uncertainties and may undermine the credibility of risk analysis.This paper attempts to accommodate the expert's knowledge to overcome missing data and incorporate fuzzy set and evidence theory to assess the uncertainties. Further, dependency coefficient-based fuzzy and evidence theory approaches have been developed to address the model uncertainty for bow-tie analysis. In addition, a method of sensitivity analysis is proposed to predict the most contributing input events in the bow-tie analysis. To demonstrate the utility of the approaches in industrial application, a bow-tie diagram of the BP Texas City accident is developed and analyzed.