The growing economic and ecological damage associated with biological invasions, which will likely be exacerbated by climate change, necessitates improved projections of invasive spread. Generally, potential changes in species distribution are investigated using climate envelope models; however, the reliability of such models has been questioned and they are not suitable for use at local scales. At this scale, mechanistic models are more appropriate. This paper discusses some key requirements for mechanistic models and utilises a newly developed model ( PSS [gt]) that incorporates the influence of habitat type and related features (e.g., roads and rivers), as well as demographic processes and propagule dispersal dynamics, to model climate induced changes in the distribution of an invasive plant ( G unnera tinctoria ) at a local scale. A new methodology is introduced, dynamic baseline benchmarking, which distinguishes climate‐induced alterations in species distributions from other potential drivers of change. Using this approach, it was concluded that climate change, based on IPCC and C4i projections, has the potential to increase the spread‐rate and intensity of G . tinctoria invasions. Increases in the number of individuals were primarily due to intensification of invasion in areas already invaded or in areas projected to be invaded in the dynamic baseline scenario. Temperature had the largest influence on changes in plant distributions. Water availability also had a large influence and introduced the most uncertainty in the projections. Additionally, due to the difficulties of parameterising models such as this, the process has been streamlined by utilising methods for estimating unknown variables and selecting only essential parameters.

A mechanistic model designed to simulate the spread of invasive plants that primarily propagate via dispersal corridors is described. The model has been parameterised for use with Gunnera tinctoria, an invasive herbaceous plant that is believed to spread via abiotic dispersal corridors, such as roads and rivers. It is an individual based, spatiotemporally explicit, stochastic computer simulation. The model can simulate the influence of habitat type, habitat features (e.g. roads and rivers), propagule pressure, varying climatic conditions, and stochastic long distance dispersal, on plant spread, establishment and survival. A process-based approach, which allows for the non-linear movement of propagules through heterogeneous environments, is used to simulate long distance propagule dispersal. The model is relatively easy to parameterise and provides abundance predictions. An analytical technique for evaluating model accuracy when binned percentage cover data is available for comparison is also presented. To evaluate the model's predictive capabilities, it was seeded at the presumed point of initial invasion on the west coast of Ireland in 1908 and then run for 100 timesteps (timesteps = one year). The simulated distributions were compared to detailed distribution maps of G. tinctoria, which had been recorded in 2008. The 2008 distribution of G. tinctoria was accurately reproduced, as confirmed by all the statistical approaches used (e.g. AUC = 0.891, kappa =0.710). Habitat type and abiotic habitat features were shown to play a critical role in determining plant distributions. Predictions on the future spread of G. tinctoria, up to 2031, indicate that this species will substantially increase in abundance (+similar to 98%) and distribution (+similar to 59%) unless effective management protocols can be designed and implemented. (C) 2012 Elsevier B.V. All rights reserved.

Animations of horses are commonly used for entertainment purposes. A realistic animated model must move with a gait appropriate to its velocity. We present a kinematic animation system in which a horse model moves using gaits and transitions based on predictions from Dynamic Similarity theory. A Genetic Programming technique is used to evolve gait motion with dynamically adjustable limb extent. The system is controlled in real-time using a MIDI controller system based around the model’s Froude number. We were successful in producing high quality animations of the horse’s natural gaits and transitions.

Motion data is required for realistic animation of physics-based animal models. This data is expensive to acquire for a single animal and in herd situations, the large variation in animal shape and consequent motion increases this expense. We propose a method in which data measured from a single horse can be used to animate horses of different age, breed and conformation. The construction and animation of a physics-based horse is described. Details of an application, which automatically generates horse models of a user-specified age, are also presented. We compare two approaches in which Grammatical Evolution is used to optimise a generated model’s motion parameters, to produce realistic motion. In one approach, the constant coefficients of a model’s spring-damper based muscle system are optimised prior to the gait optimisation. We contrast this method with a parallel optimisation of both spring-damper constants and gait. The sequential approach was found to be the most successful for gait optimisation.

Physics-based animal animations require data for realistic motion. This data is expensive to acquire through motion capture and inaccurate when estimated by an artist. Grammatical Evolution (GE) can be used to optimise pre-existing motion data or generate novel motions. Optimised motion data produces sustained locomotion in a physics-based model. To explore the use of GE for gait optimisation, the motion data of a walking horse, from a veterinary publication, is optimised for a physics-based horse model. The results of several grammars are presented and discussed. GE was found to be successful for optimising motion data using a grammar based on the concatenation of sinusoidal functions.

Artists and scientists require tools to construct physics- based animal models. However, animating these models requires motion data for realistic movement. Motion data ma y either be measured from real-life animals-in-motion or generated using an optimisation approach. We propose a so lution for retargeting gait data from one animal to another. The retargeted gait cycles are generated using a Gr ammatical Evolution optimisation approach and the search space is constrained based on dynamic similarity pri nciples.

The kinetics of the reactions of the CH radical with ethene (k(1)), propene (k(2)) and 1-butene (k(3)) are studied over a temperature range of T = 96-296 K. The low-temperature environment is provided by a pulsed Laval nozzle supersonic expansion of nitrogen with admixed radical precursor and reactant gases. The OH radicals are produced by pulsed photolysis of H2O2 at 248 nm. Laser-induced fluorescence of the OH radicals excited in the (1,0) band of the A(2)Sigma(+)-X(2)Pi(i) transition is used to monitor the OH decay kinetics to obtain the bimolecular rate coefficients. At T = 296 K, the rate constants k(1), k(2), and k(3) are also measured as a function of total pressure. The room-temperature falloff parameters are used as the basis for extrapolation of the low-temperature kinetic data, obtained over a limited range of gas number density, to predict the high-pressure limits of all three rate coefficients at low temperatures. The temperature dependence of the measured high-pressure rate constants for T = 96-296 K can be expressed as follows: k(1,infinity) = (8.7 +/- 0.7) x 10(-12)(T/300)((-0.85+/-0.11)) cm(3) molecule(-1) s(-1); k(2,infinity) = (2.95 +/- 0.10) x 10(-11)(T/300)((-1.06+/-0.13)) cm(3) molecule(-1) s(-1); k(3,infinity) = (3.02 +/- 0.15) x 10(-11)(T/300)((-1.44+/-0.10)) cm(3) molecule(-1) s(-1). All three high-pressure rate constants show a slight negative temperature dependence, which is generally in agreement with both low-temperature and high-temperature kinetic data available in the literature. Implications to the atmospheric chemistry of Saturn are discussed. Incorporating the new experimental data on k(1) in photochemical models of Saturn's atmosphere may significantly increase the predicted rate of photochemical conversion of H2O into C-O containing molecules.

The kinetics of the reactions of C2H radical with ethane (k1), propane (k2), and n-butane (k3) are studied over the temperature range of T = 96–296 K with a pulsed Laval nozzle apparatus that utilizes a pulsed laser photolysis–chemiluminescence technique. The C2H decay profiles in the presence of both the alkane reactant and O2 are monitored by the CH(A2Δ) chemiluminescence tracer method. The results, together with available literature data, yield the following Arrhenius expressions: k1(T) = (0.51 ± 0.06) × 10−10 exp[(−76 ± 30)K/T] cm3 molecule−1 s−1 (T = 96–800 K), k2(T) = (0.98 ± 0.32) × 10−10exp[(−71 ± 60)K/T] cm3 molecule−1 s−1 (T = 96–361 K), and k3(T) = (1.23 ± 0.26) × 10−10 cm3 molecule−1 s−1 (T = 96–297 K). At T = 296 K, k1 is measured as a function of total pressure and has little or no pressure dependence. The results from this work support a direct hydrogen abstraction mechanism for the title reactions. Implications to the atmospheric chemistry of Titan are discussed.

In a multiprogramming environment, special care must be taken to insure that, for a given physical record on a data set, only one task at a time is involved in the following sequence: 1) Read the physical record (with update in mind); 2) Find the logical record to be changed; 3) Change the logical record; 4) Write the "new" physical record.