白牛槭和假色槭种子繁育技术研究

对黑龙江省槭树科秋季红叶植物中具有较高观赏价值的白牛槭和假色槭两种植物,进行了多年的种子繁育研究,从小试到中试,形成了一套完整的、适合于生产的种子繁育技术,使白牛槭和假色槭的出苗率达80％以上。     

不同外源物质调控对紫花槭生长的影响

本实验拟为解决紫花槭圃地育苗生长势弱、生长缓慢提供技术参考,通过利用赤霉素(GA3)、吲哚乙酸(IAA)、腐殖酸液肥、尿素、磷酸二氢钾、氯化钾等外源物质,对圃地紫花槭幼苗进行生长调控,测定分析其对紫花槭各项生长指标的影响。实验结果:高浓度的赤霉素使紫花槭徒长,浓度为300ppm吲哚乙酸,6ml·L-1腐殖酸液肥,4g·L-1尿素和5g·L-1磷酸二氢钾对紫花槭各生长指标有不同的促进作用;氯化钾作用不明显且易对紫花槭叶产生药害。     

紫花槭的抗寒适应性分析

通过野生树种紫花槭的引种和人工繁殖栽培,对紫花槭的抗寒适应性等进行了观测记录和分析研究,掌握了紫花槭具体的寒害胁迫情况和耐寒力的变化趋势,对紫花槭的抗寒适应性作出了综合评价。     

薜荔在室内光照适应范围的研究

研究了薜荔的绿叶(Ficus pumila)及花叶(Ficus pumila'Sunny White')品种的室内光照适应范围问题;根据室内光的分布,选择房间内具有代表性的光区进行栽培试验;在16～28℃,RH30%～64%条件下;经栽培82天后,用LI-6400测定其不同光强下的光合特性,计算光补偿点、光饱和点、最大净光合速率,并测定不同试验区枝条长度的生长量;结果表明,在该条件下,绿叶品种生长的适宜光照为7.8～527.0μmol/m2.s(392～26350 lx),薜荔花叶品种为6.9～491.0μmol/m2.s(347～24550 lx)。     

An agent-based learning-embedded model (ABM-learning) for urban land use planning: A case study of residential land growth simulation in Shenzhen,China

A forward-looking urban land use plan is crucial to a city’s sustainability, which requires a deep understanding of human-environment interactions between different domains, and modelling them soundly. One of the key challenges of modelling these interactions is to understand and model how human individuals make and develop their location decisions by learning that then shape urban land-use patterns. To investigate this issue, we have constructed an extended experience-weighted attraction learning model to represent the human agents’ learning when they make location decisions. Consequently, we propose and have developed an agent-based learning-embedded model (ABM-learning) for residential land growth simulation that incorporates a learning model, a decision-making model, a land use conversion model and the constraint of urban land use master plan. The proposed model was used for a simulation of the residential land growth in Shenzhen city, China. By validating the model against empirical data, the results showed that the site-specific accuracy of the model has been improved when embedding learning model. The analysis on the simulation accuracies has proved the argument that modelling individual-level learning matters in the agent’s decision model and the agent-based models. We also applied the model to predict residential land growth in Shenzhen from 2015 to 2035, and the result can be a reference for land-use allocation in detailed planning of Shenzhen. The ABM-learning is applicable to studying the past urban growth trajectory, aiding in the formulation of detailed residential land and public service facility planning and assessing the land use planning effectiveness.     

厚朴林和杜仲林间作玉米与大豆系统的土地利用率研究

研究土地利用率的核心意义,原于其能够缓解土地资源禀赋稀缺的现状;发展厚朴林和杜仲林间作玉米与大豆系统可以提高土地利用率,促进林农集约经营,有效保护生物多样性,促进中药材产业发展,增加农民的经济收益,推动社会主义新农村建设。