内蒙古土地利用变化对生态系统防风固沙功能的影响

土壤风蚀是内蒙古的严重环境问题之一。在对内蒙古2000年到2010年的土地利用变化特征进行分析的基础上,分析了内蒙古土地利用变化的主要特征,以RWEQ模型估算了内蒙古2000年和2010年的固沙物质量,采用空间统计分析评估了固沙功能对土地利用变化的响应,结果表明:(1)2000—2010年土地利用变化以城镇高速发展、草地和湿地面积锐减、林地灌丛有所恢复以及荒漠环境改善为主要特征。(2)2000—2010的十年间内蒙古固沙物质总量增长了17.75%,草地总面积虽有所降低,但是部分区域草地覆盖度的上升增强了草地固沙能力,而林地的固沙物质量则由于农田、草地改为林地的短期内地表保护力的下降而有所降低。(3)十年间农田退耕还草、荒漠环境的改善、草地质量提高等土地利用变化方式有益于生态环境质量的提高,使生态防风固沙功能得以增强,造成固沙物质量提高了约0.25亿t。(4)农田开垦、城镇发展、荒漠化发展、湿地萎缩以及草地的退化等土地利用变化会使生态环境质量降低,生态系统防风固沙功能下降,累计造成的固沙物质量的减少总量约为0.19亿t。从十年间综合来看,内蒙古的土地利用变化对区域固沙功能有一定的增强作用,但是尚存在城镇发展过快、草地湿地转化压力过大、草地退化、荒漠化对固沙功能的弱化问题,需要在今后的土地利用规划和管理工作中予以改进以进一步增强区域固沙功能,构建北方地区生态安全屏障。     

环渤海滨海湿地鸻鹬类水鸟多样性及其环境影响因子

环渤海湿地是水鸟南北迁徙的重要驿站,尤其对于该线路上的鸻鹬鸟类具有非常重要的意义。以环渤海地区12处典型滨海湿地为研究对象,于2016-2020年每年春季开展水鸟调查,明确了鸻鹬类水鸟群落组成及其时空变化,采用结构方程模型 （Structural Equation Modeling,SEM）分析了鸻鹬类水鸟多样性与环境因子的响应关系,评估了各环境因子的影响强度。结果表明：（1）共记录到鸻鹬类水鸟7科51种,几乎全部为旅鸟。全球极危物种1种,濒危物种3种,近危物种9种。国家一级保护鸟类2种,国家二级保护鸟类8种。黑腹滨鹬（Calidris alpina）、大滨鹬（Calidris tenuirostris）、黑尾塍鹬（Limosa limosa）、灰鸻（Pluvialis squatarola）、斑尾塍鹬（Limosa lapponica）个体数量最多。（2）山东黄河三角洲、辽宁辽河口、天津北大港等河口湿地,水鸟种类多,单位面积水鸟数量较少。（3）河北沧州沿海、山东滨州贝壳堤岛及其周边区域为环渤海地区湿地集中区,水鸟种类较多。（4）综合影响强度为保护强度>食物>气候,建立自然保护地是保护水鸟多样性的最有效措施。（5）建议将河北南大港湿地和鸟类省级自然保护区提升至国家级,扩大滨州贝壳堤岛与湿地国家级自然保护区面积,对山东黄河三角洲、辽宁辽河口覆盖的各级各类自然保护地进行优化整合。研究结果能为环渤海地区鸻鹬类水鸟保护策略的制定提供相关依据。     

Competition limits adaptation and productivity in a photosynthetic alga at elevated CO2

When competitive exclusion between lineages and genetic adaptation within lineages occur on the same timescale, the two processes have the potential to interact. I use experimental microbial evolution where strains of a photosynthetic microbe that differ in their physiological response to CO₂ enrichment are grown either alone or in communities for hundreds of generations under CO₂ enrichment. After about 300 generations of growth, strains that experienced competition while adapting to environmental change are both less productive and less fit than corresponding strains that adapted to that same environmental change in the absence of competitors. In addition, I find that excluding competitors not only limits that strain''s adaptive response to abiotic change, but also decreases community productivity; I quantify this effect using the Price equation. Finally, these data allow me to empirically test the common hypothesis that phytoplankton that are most able to take advantage of carbon enrichment in single-strain populations over the short term will increase in frequency within multi-strain communities over longer timescales.     

生物种群动态微分方程模型参数估计方法

本文以数值分析和最优化技术的有机结合为基础,提出了一种新的对动态微分方程模型直接进行数据拟合和参数估计方法,并以Logistic微分方程、生物种间竞争关系微分方程以及一种复合形态的Logistic微分方程为例进行了数据拟合试验．结果表明,该方法对各种动态微分方程模型均能进行最优拟合分析并求解其参数．同时发现,以前有的作者〔1,2,3,4,5〕提出的方法所得到的参数估计值存在系统误差且误差较大．     

Synthesis of robust tunable oscillators using mitogen activated protein kinase cascades

Mitogen activated protein kinase (MAPK) cascade is evolutionally preserved in all eukaryotic cells, and regulates various cellular activities such as gene expression, mitosis, differentiation, and apoptosis. Recently, Bashor et al. have shown that Ste5 scaffold protein can be used to reshape the MAPK cascade through engineered feedback loops, and have used heuristic tuning mechanisms to synthesize the feedback. A problem of interest is to determine whether information regarding the underlying biochemical reactions can be used to synthesize robust feedback that will ensure that the resultant circuit has the desired properties. In this paper, we consider the problem of engineering feedback in MAPK cascade to synthesize an oscillator of the desired frequency. Our approach builds on the MAPK cascade model derived by Chikarmane et al. who have exploited the existence of a Hopf bifurcation point in the Markevich model of the MAPK cascade to synthesize the exciting kinase as a function of the doubly phosphorylated protein. We show how the L₁\mathcal{L}_1-control theory can be used for a robust synthesis of the oscillator and present the simulation results.     

An optimization framework of biological dynamical systems

Different biological dynamics are often described by different mathematical equations. On the other hand, some mathematical models describe many biological dynamics universally. Here, we focus on three biological dynamics: the Lotka-Volterra equation, the Hopfield neural networks, and the replicator equation. We describe these three dynamical models using a single optimization framework, which is constructed with employing the Riemannian geometry. Then, we show that the optimization structures of these dynamics are identical, and the differences among the three dynamics are only in the constraints of the optimization. From this perspective, we discuss the unified view for biological dynamics. We also discuss the plausible categorizations, the fundamental nature, and the efficient modeling of the biological dynamics, which arise from the optimization perspective of the dynamical systems.