Next-state comfort in learning a vertical stick transportation sequence

Over the last decade, the end-state comfort effect (e.g., Rosenbaum et al., 2006) has received a considerable amount of attention. However, some of the underlying mechanisms are still to be investigated, amongst others, how sequential planning affects end-state comfort and how this effect develops over learning. In a two-step sequencing task, e.g., postural comfort can be planned on the intermediate position (next state) or on the actual end position (final state). It might be hypothesized that, in initial acquisition, next state’s comfort is crucial for action planning but that, in the course of learning, final state’s comfort is taken more and more into account. To test this hypothesis, a variant of Rosenbaum’s vertical stick transportation task was used. Participants (N = 16, right-handed) received extensive practice on a two-step transportation task (10,000 trials over 12 sessions). From the initial position on the middle stair of a staircase in front of the participant, the stick had to be transported either 20 cm upwards and then 40 cm downwards or 20 cm downwards and then 40 cm upwards (N = 8 per subgroup). Participants were supposed to produce fluid movements without changing grasp. In the pre- and posttest, participants were tested on both two-step sequencing tasks as well as on 20 cm single-step upwards and downwards movements (10 trials per condition). For the test trials, grasp height was calculated kinematographically. In the pretest, large end/next/final-state comfort effects for single-step transportation tasks and large next-state comfort effects for sequenced tasks were found. However, no change in grasp height from pre- to posttest could be revealed. Results show that, in vertical stick transportation sequences, the final state is not taken into account when planning grasp height. Instead, action planning seems to be solely based on aspects of the next action goal that is to be reached.

Present state of global wetland extent and wetland methane modelling: conclusions from a model inter-comparison project (WETCHIMP)

Global wetlands are believed to be climate sensitive, and are the largest natural emitters of methane (CH4). Increased wetland CH4 emissions could act as a positive feedback to future warming. The Wetland and Wetland CH4 Inter-comparison of Models Project (WETCHIMP) investigated our present ability to simulate large-scale wetland characteristics and corresponding CH4 emissions. To ensure inter-comparability, we used a common experimental protocol driving all models with the same climate and carbon dioxide (CO2) forcing datasets. The WETCHIMP experiments were conducted for model equilibrium states as well as transient simulations covering the last century. Sensitivity experiments investigated model response to changes in selected forcing inputs (precipitation, temperature, and atmospheric CO2 concentration). Ten models participated, covering the spectrum from simple to relatively complex, including models tailored either for regional or global simulations. The models also varied in methods to calculate wetland size and location, with some models simulating wetland area prognostically, while other models relied on remotely sensed inundation datasets, or an approach intermediate between the two. Four major conclusions emerged from the project. First, the suite of models demonstrate extensive disagreement in their simulations of wetland areal extent and CH4 emissions, in both space and time. Simple metrics of wetland area, such as the latitudinal gradient, show large variability, principally between models that use inundation dataset information and those that independently determine wetland area. Agreement between the models improves for zonally summed CH4 emissions, but large variation between the models remains. For annual global CH4 emissions, the models vary by ±40% of the all-model mean (190 Tg CH4 yr−1). Second, all models show a strong positive response to increased atmospheric CO2 concentrations (857 ppm) in both CH4 emissions and wetland area. In response to increasing global temperatures (+3.4 °C globally spatially uniform), on average, the models decreased wetland area and CH4 fluxes, primarily in the tropics, but the magnitude and sign of the response varied greatly. Models were least sensitive to increased global precipitation (+3.9 % globally spatially uniform) with a consistent small positive response in CH4 fluxes and wetland area. Results from the 20th century transient simulation show that interactions between climate forcings could have strong non-linear effects. Third, we presently do not have sufficient wetland methane observation datasets adequate to evaluate model fluxes at a spatial scale comparable to model grid cells (commonly 0.5°). This limitation severely restricts our ability to model global wetland CH4 emissions with confidence. Our simulated wetland extents are also difficult to evaluate due to extensive disagreements between wetland mapping and remotely sensed inundation datasets. Fourth, the large range in predicted CH4 emission rates leads to the conclusion that there is both substantial parameter and structural uncertainty in large-scale CH4 emission models, even after uncertainties in wetland areas are accounted for.