Productivity and persistence of perennial grass mixtures under competition from annual weeds in the alpine region of the Qinghai-Tibetan Plateau

In the alpine region of the Qinghai-Tibetan Plateau four indigenous perennial grass species Bromus inermis (BI), Elymus sibiricus (ES), Elymus nutans (EN) and Agropyron cristatum (AC) were cultivated as three mixtures with different compositions and seeding rates, BI + EN, BI + ES + AC and BI + ES + EN + AC. From 1998 to 2001 there were three different weeding treatments: never weeded (CK); weeded on three occasions in the first year (1-y) and weeded on three occasions in both the first and second year (2-y) and their effect of grass combination and interactions on sward productivity and persistence was measured. Intense competitive interference by weedy annuals reduced dry matter (DM) yield of the swards. Grass combination significantly affected sward DM yields, leaf area index (LAI) and foliar canopy cover and also species composition DM and LAI, and species plant cover. Interaction between weeding treatments and grass combination was significant for sward DM yield, LAI and canopy cover, but not on species composition for DM, LAI or species plant cover. Grass mixture BI + ES + EN + AC gave the highest sward DM yield and LAI for both weeding and non-weeding treatments. Species ES and EN were competitively superior to the others. Annual weedy forbs must be controlled to obtain productive and stable mixtures of perennial grasses, and germination/emergence is the most important time for removal. Weeding three times (late May, late June and mid-July) in the establishment year is enough to maintain the production and persistence of perennial grass mixtures in the following growing seasons. Extra weeding three times in the second growing year makes only a slight improvement in productivity.

空间及言语工作记忆任务的情绪效应：来自ERP/ fMRI的证据

In the present study, based on processing efficiency theory, we used the event-related potentials (ERP) and functional magnetic resonance image (fMRI) techniques to explore the underlying neutral mechanism of influences of negative emotion on three subsystems of working memory, phonological loop、 visuospatial sketh pad and the central executive. The modified DSMT (delayed matching-to-sample task) and n-back tasks were adopted and IAPS (International Affective Picture System) pictures were employed to induce the expected emotional state of subjects. The main results and conclusions obtained in the series of experiments are as the following: 1. In DSM tasks, we found P200 and P300 were reduced by negative emotion in both spatial and verbal tasks, however the increased negative slow wave were only observed in spatial tasks, not in verbal tasks. 2. In n-back tasks, the updating function of WM associated P300 was affected by negative emotion only in spatial tasks, not in verbal tasks. Current density analysis revealed strong current density in the fronto-parietal cortex only in the spatial tasks as well. 3. We adopted fMRI-block design and ROIs analysis, and found significant emotion and task effects in spatial WM-associated right superior parietal cortex; only emotion effect in verbal WM-associated Broca’s area; the interaction effect in attention-associated medial prefrontal area and bilateral inferior parietal cortex. These results implied the negative emotion mainly disturbed the spatial WM-related areas, and the attention control system play a key role in the interaction of spatial WM and negative emotion. 4. to further examine the effects of positive、negative and neutral emotion on tasks with different cognitive loads, the selective effect of emotion on the ERP components of spatial WM was only found in 2-back tasks, not in visual searching tasks. So, firstly the positive emotion as well as negative emotion selectively disturbed on spatial WM in light of the attention resource competition mechanism. Secondly, the selective influences based on the different WM systems, not the properties of spatial and verbal information. At last, the manner of the interaction of emotion and cognition is correlated with the cognitive load.