基于ArcGIS的下辽河平原地下水脆弱性评价及空间结构分析

以下辽河平原为研究区,通过选取1991、2000和2010年3个代表年的相关参数,在DRASTIC模型基础上构建评价指标体系进行地下水脆弱性评价,并以地下水中氮元素浓度为响应指标通过显著性检验,在此基础上借助GS+、Arc GIS和Geoda095i等软件的制图功能和空间统计分析功能,对下辽河平原地下水脆弱性的空间分布特征、变异规律以及空间关联格局进行研究分析,结果表明:11991—2010年下辽河平原地下水脆弱性总体上呈先增后减趋势,空间分布上以沈阳市为中心的地下水高脆弱区向南部沿海方向扩散;21991—2010年研究区地下水脆弱性Moran's I表现为较强正相关现象,且关联程度呈略微下降趋势;31991—2010年研究区地下水脆弱性局部空间自相关和显著性水平均发生了明显的变化;4研究区内地下水脆弱性受结构性因素和随机性因素共同作用,且随机性因素在3个时期内有逐步上升趋势。研究成果反映了研究区地下水脆弱性空间结构的变异规律及驱动机制,为决策者在未来地下水污染防治方面提供相关参考依据。     

我国省域基础设施投入对社会-生态系统脆弱性的影响

基础设施投入对社会经济或生态系统的影响已被广泛讨论,但对社会-生态系统(SES)的作用如何仍不得而知。本研究梳理了基础设施投入对SES脆弱性的影响机理,并在核算省域人均基础设施资本存量及综合评估SES脆弱性的基础上,采用空间自相关与空间计量模型实证分析了我国省域基础设施投入对SES脆弱性的作用。结果表明: 2004—2017年,我国省域人均基础设施投入水平显著提高,且呈北高南低、东西高中间低的空间分布格局;省域SES脆弱性也在不断改善,却表现出由东向西逐步恶化的分布特点;我国省域人均基础设施投入与SES脆弱性具有空间正相关性,存在聚集性分布特征;两者呈倒U型曲线关系,即早期适量基础设施投入会降低SES脆弱性,而过度投入则会导致SES脆弱性逐步增加。本研究揭示了基础设施投入对SES脆弱性的影响机理与动态特点,可为宏观层面统筹协调基础设施建设与SES脆弱性治理提供理论与决策支持。     

An improved method to assess torsional properties of rodent long bones

Torsion is an important testing modality commonly used to calculate structural properties of long bones. However, the effects of size and geometry must be excluded from the overall structural response in order to compare material properties of bones of different size, age and species. We have developed a new method to analyze torsional properties of bones using actual cross-sectional information and length-wise geometrical variations obtained by micro-computed topographic (μCT) imaging. The proposed method was first validated by manufacturing three rat femurs through rapid prototyping using a plastic with known material properties. The observed variations in calculated torsional shear modulus of the hollow elliptical model of mid-shaft cross-section (Ekeland et al.), multi-prismatic model of five true cross-sections (Levenston et al.) and multi-slice model presented in this study were 96%, ?7% and 6% from the actual properties of the plastic, respectively. Subsequently, we used this method to derive relationships expressing torsional properties of rat cortical bone as a function of μCT-based bone volume fraction or apparent density over a range of normal and pathologic bone densities. Results indicate that a regression model of shear modulus or shear strength and bone volume fraction or apparent density described at least 81% of the variation in torsional properties of normal and pathologic bones. Coupled with the structural rigidity analysis technique introduced by the authors, the relationships reported here can provide a non-invasive tool to assess fracture risk in bones affected by pathologies and/or treatment options.     

Climate‐niche factor analysis: a spatial approach to quantifying species vulnerability to climate change

Climate change vulnerability assessments are an important tool for understanding the threat that climate change poses to species and populations, but do not generally yield insight into the spatial variation in vulnerability throughout a species’ habitat. We demonstrate how to adapt the method of ecological‐niche factor analysis (ENFA) to objectively quantify aspects of species sensitivity to climate change. We then expand ENFA to quantify aspects of exposure and vulnerability to climate change as well, using future projections of global climate models. This approach provides spatially‐explicit insight into geographic patterns of vulnerability, relies only on readily‐available spatial data, is suitable for a wide range of species and habitats, and invites comparison between different species. We apply our methods to a case study of two species of montane mammals, the American pika Ochotona princeps and the yellow‐bellied marmot Marmota flaviventris.     

A model to assess relationships between forest dynamics and spatial structure

Abstract. A spatially explicit model was developed to study the relationships between the dynamics and spatial structure of forest stands. The objective was to test whether tree spatial structure can be used as an indicator of stand dynamics. The model simulates the growth, mortality and recruitment of trees in a multi‐specific and uneven‐aged stand. It includes deterministic and stochastic processes so that repeated simulations do not lead to the same stand but provide several possible results for a given dynamic (defined by a set of parameters). Second‐order neighbourhood analyses were used to characterize the resulting spatial structures. They showed a high variability for a given set of parameters. Only the main trends in the spatial structure can be interpreted. Sensitivity analyses, concerning the influence of competition on spatial structure, showed that in heterogeneous stands confounding effects can hinder the interpretation of the spatial structure if all the trees are considered. The spatial structure of the canopy trees alone proved easier to interpret as it is directly linked to post recruitment competition. Inference on the dominant modality of competition (one‐sided or two‐sided) based on the spatial structure proved difficult.     

An improved neutral landscape model for recreating real landscapes and generating landscape series for spatial ecological simulations

Many studies have assessed the effect of landscape patterns on spatial ecological processes by simulating these processes in computer‐generated landscapes with varying composition and configuration. To generate such landscapes, various neutral landscape models have been developed. However, the limited set of landscape‐level pattern variables included in these models is often inadequate to generate landscapes that reflect real landscapes. In order to achieve more flexibility and variability in the generated landscapes patterns, a more complete set of class‐ and patch‐level pattern variables should be implemented in these models. These enhancements have been implemented in Landscape Generator (LG), which is a software that uses optimization algorithms to generate landscapes that match user‐defined target values. Developed for participatory spatial planning at small scale, we enhanced the usability of LG and demonstrated how it can be used for larger scale ecological studies. First, we used LG to recreate landscape patterns from a real landscape (i.e., a mountainous region in Switzerland). Second, we generated landscape series with incrementally changing pattern variables, which could be used in ecological simulation studies. We found that LG was able to recreate landscape patterns that approximate those of real landscapes. Furthermore, we successfully generated landscape series that would not have been possible with traditional neutral landscape models. LG is a promising novel approach for generating neutral landscapes and enables testing of new hypotheses regarding the influence of landscape patterns on ecological processes. LG is freely available online.     

下辽河平原景观格局脆弱性及空间关联格局

以东北三省开发强度最大的辽河中下游地区——下辽河平原为研究对象,根据景观格局脆弱性的概念及内涵,通过景观敏感度指数和景观适应度指数构建景观格局脆弱度指数,并借助地统计学和空间自相关模型分析的理论方法,对下辽河平原景观格局脆弱度的空间分布特征、变异规律以及空间关联格局进行探讨,结果表明:①1989—2010年下辽河平原景观格局脆弱度总体上呈递减趋势;②1989—2010年研究区景观格局脆弱度Moran's I表现为一定程度的正相关,且相关程度略微呈下降趋势;③1989—2010年研究区景观格局脆弱度局部空间自相关和显著性水平均发生了明显的变化;④研究区各时期景观格局脆弱度的空间相关性是受结构性因素和非结构性因素共同影响,C0所占的比例在3a期间有逐步上升趋势,表明非结构性因素对景观格局脆弱度演变的影响程度不断加深,但是结构性因素(地形地貌、水文、土壤植被类型等)仍然对本区景观格局脆弱度的空间分布起决定性作用。     

Stepping inside the niche: microclimate data are critical for accurate assessment of species' vulnerability to climate change

To assess a species'' vulnerability to climate change, we commonly use mapped environmental data that are coarsely resolved in time and space. Coarsely resolved temperature data are typically inaccurate at predicting temperatures in microhabitats used by an organism and may also exhibit spatial bias in topographically complex areas. One consequence of these inaccuracies is that coarsely resolved layers may predict thermal regimes at a site that exceed species'' known thermal limits. In this study, we use statistical downscaling to account for environmental factors and develop high-resolution estimates of daily maximum temperatures for a 36 000 km² study area over a 38-year period. We then demonstrate that this statistical downscaling provides temperature estimates that consistently place focal species within their fundamental thermal niche, whereas coarsely resolved layers do not. Our results highlight the need for incorporation of fine-scale weather data into species'' vulnerability analyses and demonstrate that a statistical downscaling approach can yield biologically relevant estimates of thermal regimes.     

一种基于SWAT模型的干旱牧区生态脆弱性评价方法——以艾布盖河流域为例

针对干旱牧区生态脆弱性特点,以GIS为平台,利用气象、土壤、土地利用、水资源开发利用等数据,结合SWAT模型模拟结果,建立了一种基于SWAT模型子流域划分的干旱牧区生态脆弱性评价体系,对西北干旱牧区艾布盖河流域1990年、2010年生态脆弱性进行了评价。从评价结果可以看出,研究区北部及西部生态稳定性保持较好,生态脆弱等级下降主要发生在研究区的东南部,20年间耕地扩张造成的草地被侵占及水资源过度开发利用是造成生态退化的主要原因。评价体系紧紧围绕干旱牧区"水-草-畜"关系设置评价指标,将观测数据与水文模型模拟相结合,统计数据与空间地类相联系,点面结合,能够较好的反映出研究区20年间生态脆弱程度变化趋势及主要问题。     

综合土地利用及空间异质性的土壤有机碳空间插值模型

土壤有机碳库是陆地碳库的重要组成部分,土壤有机碳库及其动态变化对陆地生态系统碳循环有着重要的影响.土壤有机碳密度(SOCD)是土壤碳储量的重要参数,也是评价农田土壤质量的重要指标,准确预测区域SOCD空间分布对发展精确农业有重要意义.本文使用江汉平原地区242个农田土壤样本数据,探究平原地区土地利用类型对SOCD空间分布的影响,以及当SOCD空间分布规律呈现空间异质性且存在空间异常值的情况下,虚拟变量回归克里格法(DV_RK)、均值中心化克里格法(MC_OK1)和中位数中心化克里格法(MC_OK2)这3种结合土地利用的克里格法在SOCD空间预测中的应用.结果表明: 土地利用方式的差异是研究区水田和水浇地SOCD存在空间异质性的原因之一,导致SOCD存在空间非平稳特征,降低了普通克里格法(OK)的预测精度;而DV_RK、MC_OK1和MC_OK2在消除了由土地利用引起的SOCD空间异质性对建模的影响后,模型的稳定性提升,其预测精度均高于OK,其中,MC_OK2的模型可靠程度、预测精度和对SOCD总方差的解释能力最优.因此,土地利用类型作为易获取的辅助变量,可以有效减弱空间异质性和空间异常值对SOCD空间插值的影响,提升模型精度,降低不确定性,并与MC_OK2结合生成更高精度的SOCD空间分布图,帮助揭示SOCD空间分异规律,指导农业生产.     

基于社会-生态系统的沙漠化逆转过程脆弱性评价指标体系

土地沙漠化是当今世界最为严峻的生态环境问题之一。沙漠化逆转作为其反向转化过程,存在一定的脆弱性和不稳定性,即沙漠化逆转趋势减弱或反向发展的倾向。社会-生态系统理念是当今世界生态系统分析的新思路,从该视角界定沙漠化逆转过程的脆弱性概念,选取Driving-Pressure-Status-Impact-Response(DPSIR)分析框架,以农牧交错带典型沙漠化逆转区宁夏盐池县为案例,针对沙漠化逆转的因果联系和过程特点,构建一套涵盖气候湿润指数、生态治理指数、沙地所占比例在内的4层、5要素、41指标的评价体系,进而探讨驱动力、压力、状态、影响、响应5项要素间的逻辑因果关系及其脆弱性定量化计算方法,以期科学评估沙漠化逆转过程的脆弱性,为该类型区沙漠化问题的进一步治理和调控提供科学依据。     

Probabilistic spatio‐temporal assessment of vegetation vulnerability to climate change in Swaziland

In a spatially explicit climate change impact assessment, a Bayesian network (BN) model was implemented to probabilistically simulate future response of the four major vegetation types in Swaziland. Two emission scenarios (A2 and B2) from an ensemble of three statistically downscaled coupled atmosphere‐ocean global circulation models (CSIRO‐Mk3, CCCma‐CGCM3 and UKMO‐HadCM3) were used to simulate possible changes in BN‐based environmental envelopes of major vegetation communities. Both physiographic and climatic data were used as predictors representing the 2020s, 2050s and the 2080s periods. A comparison of simulated vegetation distribution and the expert vegetation map under baseline conditions showed an overall correspondence of 97.7% and a Kappa coefficient of 0.966. Although the ensemble projections showed comparable trends during the 2020s, the results from the A2 storyline were more drastic indicating that grassland and the Lebombo bushveld will be impacted negatively as early as the 2020s with about 1 °C temperature increase. The bioclimatically suitable areas of all but one vegetation type decline drastically after about 2 °C warming, more so under the more severe A2 scenario and in particular during the 2080s. The sour bushveld is the only vegetation type that initially responds positively to warming by possibly encroaching to the highly vulnerable grassland areas. Vulnerability of vegetation is increased by the limited ability to migrate into suitable climates due to close affinity to certain geological formations and the fragmentation of the landscape by agriculture and other land uses. This is expected to have serious impacts on biodiversity in the country. Under warmer climates, the likely vegetation types to emerge are uncertain due to future novel combinations of climate and bedrock lithology. The strengths and limitations of the BN approach are also discussed.     

An integrate-and-fire model for synchronized bursting in a network of cultured cortical neurons

It has been suggested that spontaneous synchronous neuronal activity is an essential step in the formation of functional networks in the central nervous system. The key features of this type of activity consist of bursts of action potentials with associated spikes of elevated cytoplasmic calcium. These features are also observed in networks of rat cortical neurons that have been formed in culture. Experimental studies of these cultured networks have led to several hypotheses for the mechanisms underlying the observed synchronized oscillations. In this paper, bursting integrate-and-fire type mathematical models for regular spiking (RS) and intrinsic bursting (IB) neurons are introduced and incorporated through a small-world connection scheme into a two-dimensional excitatory network similar to those in the cultured network. This computer model exhibits spontaneous synchronous activity through mechanisms similar to those hypothesized for the cultured experimental networks. Traces of the membrane potential and cytoplasmic calcium from the model closely match those obtained from experiments. We also consider the impact on network behavior of the IB neurons, the geometry and the small world connection scheme. Action Editor: David Golomb     

An enhanced elastic network model to represent the motions of domain-swapped proteins

Domain swapping is a process where two (or more) protein molecules form a dimer (or higher oligomer) by exchanging an identical domain. In this article, based on the observation that domains are rigid and hinge loops are highly flexible, we propose a new Elastic Network Model, domain-ENM, for domain-swapped proteins. In this model, the rigidity of domains is taken into account by using a larger spring constant for intradomain contacts. The large-scale transition of domain swapping is then novelly decomposed into the relative motion between the rigid domains (only 6 degrees of freedom) plus the internal fluctuations of each domain. Consequently, this approach has the potential to produce much more meaningful transition pathways than other simulation approaches that try to find pathways in a search space of large numbers of dimensions. In this article, we also propose a new way to define the overlap measure. Past approaches used an inappropriate comparison of the large-scale conformation displacement against the computed infinitesimal motions of modes. Here, we propose an infinitesimal version of the large-scale conformation change and then compare it with the modes of motions. As a result, we obtain much better overlap values. Using this new overlap definition, we are also able for the first time to give a clear, intuitive explanation why "open" forms tend to produce better overlap values than "closed" forms with traditional ENMs. Finally, as an application, we present a simple approach to show how domain-ENM can be used to generated transition pathways for domain-swapped proteins.     

呼包鄂榆城市群耦合空间碳排放生态网络构建

构建生态网络是维持景观连通性、提升包括固碳在内的生态系统服务功能的重要手段。为了更好地响应固碳增汇目标及其政策要求,有必要将空间碳排放因素纳入区域生态网络分析框架。选择高能耗、高碳排且生态脆弱的呼包鄂榆城市群作为研究区,采用生态系统服务和连通性分析识别生态源地,并结合电路理论和重力模型提取生态廊道,得到区域景观生态格局;通过获取夜间灯光数据模拟得到城市群栅格尺度碳排放空间格局,并与景观生态格局进行空间叠加,以此补充“生态-碳排”耦合节点和规划廊道,进而构建考虑区域碳排放空间格局的城市群生态网络。结果表明：1)仅考虑生态因素构建的区域生态网络东西两侧生态源地连通性不足,网络呈“中部阻断型”分布;2)区域碳排放存在明显空间特征,高值区出现在人为生态扰动显著的中部矿产资源开发区和主要城镇地区;3)通过耦合区域碳排放格局,补充了23个“生态-碳排”耦合节点和67条规划廊道,生态网络结构由树状转变为蜂巢状,网络闭合度、线点率和连接度分别提升了92%、30.48%和27.45%。因此,通过耦合空间碳排放因素改进的生态网络构建方法,对于提高生态网络的多功能性和稳定性,以及促进以增加碳汇能力为目标的生...     

Using a phenological network to assess weather influences on first appearance of butterflies in the Netherlands

Phenological responses of butterflies to temperature have been demonstrated in several European countries by using data from standardized butterfly monitoring schemes. Recently, phenological networks have enabled volunteers to record phenological observations at project websites. In this study, the quality of the first appearance data of butterflies from the Dutch phenological network ‘De Natuurkalender’ was examined and these data were then used to analyze trends in butterfly appearance between 2001 and 2013, the effects of climatic factors on appearance of butterflies as well as the phenological interaction of one butterfly species, Anthocharis cardamines, and its two major host plants. Although phenological networks are relatively unstructured, this study shows that data from De Natuurkalender were highly comparable to more standardized data collected by the Dutch Butterfly Monitoring Scheme. No trend in first appearance of any butterfly species was found during the time period 2001–2013. The first appearance dates of most butterflies showed, however, a clear relationship with spring temperature. Higher temperatures, especially in March and April, advanced the first appearance of butterflies. Therefore, with climatic warming in the future, earlier appearance of butterflies is expected. Although climate warming is a potential threat for phenological mismatches between different trophic levels, this study shows a similar temperature response of A. cardamines and its main host plants in the Netherlands. However, as only few phenological interactions between species are examined, further research including rarer monophagous butterfly species and their host plants is needed.     

Structural vulnerability of the French swine industry trade network to the spread of infectious diseases

The networks generated by live animal movements are the principal vector for the propagation of infectious agents between farms, and their topology strongly affects how fast a disease may spread. The structural characteristics of networks may thus provide indicators of network vulnerability to the spread of infectious disease. This study applied social network analysis methods to describe the French swine trade network. Initial analysis involved calculating several parameters to characterize networks and then identifying high-risk subgroups of holdings for different time scales. Holding-specific centrality measurements (‘degree’, ‘betweenness’ and ‘ingoing infection chain’), which summarize the place and the role of holdings in the network, were compared according to the production type. In addition, network components and communities, areas where connectedness is particularly high and could influence the speed and the extent of a disease, were identified and analysed. Dealer holdings stood out because of their high centrality values suggesting that these holdings may control the flow of animals in part of the network. Herds with growing units had higher values for degree and betweenness centrality, representing central positions for both spreading and receiving disease, whereas herds with finishing units had higher values for in-degree and ingoing infection chain centrality values and appeared more vulnerable with many contacts through live animal movements and thus at potentially higher risk for introduction of contagious diseases. This reflects the dynamics of the swine trade with downward movements along the production chain. But, the significant heterogeneity of farms with several production units did not reveal any particular type of production for targeting disease surveillance or control. Besides, no giant strong connected component was observed, the network being rather organized according to communities of small or medium size (<20% of network size). Because of this fragmentation, the swine trade network appeared less structurally vulnerable than ruminant trade networks. This fragmentation is explained by the hierarchical structure, which thus limits the structural vulnerability of the global trade network. However, inside communities, the hierarchical structure of the swine production system would favour the spread of an infectious agent (especially if introduced in breeding herds).     

A neuronal network model of primary visual cortex explains spatial frequency selectivity

We address how spatial frequency selectivity arises in Macaque primary visual cortex (V1) by simulating V1 with a large-scale network model consisting of O(10⁴) excitatory and inhibitory integrate-and-fire neurons with realistic synaptic conductances. The new model introduces variability of the widths of subregions in V1 neuron receptive fields. As a consequence different model V1 neurons prefer different spatial frequencies. The model cortex has distributions of spatial frequency selectivity and of preference that resemble experimental findings from the real V1. Two main sources of spatial frequency selectivity in the model are the spatial arrangement of feedforward excitation, and cortical nonlinear suppression, a result of cortical inhibition. Action Editor: Jonathan D. Victor