A quantitative and statistically robust method for the determination of xylem conduit spatial distribution

? Premise of the study: Because of their limited length, xylem conduits need to connect to each other to maintain water transport from roots to leaves. Conduit spatial distribution in a cross section plays an important role in aiding this connectivity. While indices of conduit spatial distribution already exist, they are not well defined statistically. ? Methods: We used point pattern analysis to derive new spatial indices. One hundred and five cross-sectional images from different species were transformed into binary images. The resulting point patterns, based on the locations of the conduit centers-of-area, were analyzed to determine whether they departed from randomness. Conduit distribution was then modeled using a spatially explicit stochastic model. ? Key results: The presence of conduit randomness, uniformity, or aggregation depended on the spatial scale of the analysis. The large majority of the images showed patterns significantly different from randomness at least at one spatial scale. A strong phylogenetic signal was detected in the spatial variables. ? Conclusions: Conduit spatial arrangement has been largely conserved during evolution, especially at small spatial scales. Species in which conduits were aggregated in clusters had a lower conduit density compared to those with uniform distribution. Statistically sound spatial indices must be employed as an aid in the characterization of distributional patterns across species and in models of xylem water transport. Point pattern analysis is a very useful tool in identifying spatial patterns.     

Segmentation of Fluorescence Microscopy Images for Quantitative Analysis of Cell Nuclear Architecture

Considerable advances in microscopy, biophysics, and cell biology have provided a wealth of imaging data describing the functional organization of the cell nucleus. Until recently, cell nuclear architecture has largely been assessed by subjective visual inspection of fluorescently labeled components imaged by the optical microscope. This approach is inadequate to fully quantify spatial associations, especially when the patterns are indistinct, irregular, or highly punctate. Accurate image processing techniques as well as statistical and computational tools are thus necessary to interpret this data if meaningful spatial-function relationships are to be established. Here, we have developed a thresholding algorithm, stable count thresholding (SCT), to segment nuclear compartments in confocal laser scanning microscopy image stacks to facilitate objective and quantitative analysis of the three-dimensional organization of these objects using formal statistical methods. We validate the efficacy and performance of the SCT algorithm using real images of immunofluorescently stained nuclear compartments and fluorescent beads as well as simulated images. In all three cases, the SCT algorithm delivers a segmentation that is far better than standard thresholding methods, and more importantly, is comparable to manual thresholding results. By applying the SCT algorithm and statistical analysis, we quantify the spatial configuration of promyelocytic leukemia nuclear bodies with respect to irregular-shaped SC35 domains. We show that the compartments are closer than expected under a null model for their spatial point distribution, and furthermore that their spatial association varies according to cell state. The methods reported are general and can readily be applied to quantify the spatial interactions of other nuclear compartments.     

Spatial patterns of surface soil properties and vegetation in a Mediterranean semi-arid steppe

In arid and semi-arid areas with sparse vegetation cover, the spatial pattern of surface soil properties affects water and nutrient flows, and is a question of considerable interest for understanding degradation processes and establishing adequate management measures. In this study, we investigate the spatial distribution of vegetation and surface soil properties (biological crusts, physical crusts, mosses, rock fragments, earthworm casts, fine root accumulation and below-ground stones) in a semi-arid Stipa tenacissima L. steppe in SE Spain. We applied the combination of spatial analysis by distance indices (SADIE) and geostatistics to assess the spatial pattern of soil properties and vegetation, and correlation analyses to explore how these patterns were related. SADIE analysis detected significant clumped patterns in the spatial distribution of vegetation, mosses, fine root accumulation and below-ground stone content. Contoured SADIE index of clustering maps suggested the presence of patchiness in the distribution of earthworm casts, fine roots, below-ground stone content, mosses and biological crusts. Correlation analyses suggested that spatial pattern of some soil properties such as biological crusts, moss cover, surface rock fragments, physical crusts and fine roots were significantly related with above-ground plant distribution. We discuss the spatial arrangement of surface soil properties and suggest mechanistic explanations for the observed spatial patterns and relationships.     

Detection of process-related changes in plant patterns at extended spatial scales during early dryland desertification

Arid and semiarid shrublands occupy extensive land areas over the world, are susceptible to desertification by anthropic use and can contribute to regional climate change. These prompt the interest to monitor and evaluate these lands adequately in order to detect early stages of degradation. Evaluation topics must refer to biology‐relevant characteristics of these systems, while simultaneously satisfying sampling consistency over extended landscape areas. We present an analysis of process‐relevant parameters related to changes in the spatial arrangement of the plant canopy of shrublands inferred from high‐resolution panchromatic aerial photos and Interferometric Synthetic Aperture Radar imagery. We obtained low‐altitude images systematically located along several gradients of land‐use intensity in a Patagonian Monte shrubland in Argentina. Images were digitized to spatial resolutions ranging from 0.09 to 0.72 m (pixel size) and the average values and an‐isotropic characteristics of the plant canopy patterns were quantified by means of a Fourier metric. We used radar‐derived imagery to overlay the panchromatic images on a digital elevation model in order to study the correspondence of potential runoff patterns and the spatial arrangement of plants. We related an‐isotropic features of the plant canopy images to the prevailing wind regime. Observed trends were further interpreted on the basis of a spatial‐explicit simulation model describing the dynamics of the main functional groups in the plant community. We conclude that early stages of anthropic‐driven dryland degradation in the Patagonian Monte can be characterized by the incipient un‐coupling of spatial vegetation patterns from those of runoff at a landscape scale, and a progressive coupling to the spatial pattern of the wind regime. The method and metrics we present can be used to quantify early desertification changes in other similar drylands at extended spatial scales.     

Electric field interactions in pairs of electric fish: modeling and mimicking naturalistic inputs

Weakly electric fish acquire information about their surroundings by detecting and interpreting the spatial and temporal patterns of electric potential across their skin, caused by perturbations in a self-generated, oscillating electric field. Computational and experimental studies have focused on understanding the electric images due to simple, passive objects. The present study considers electric images of a conspecific fish. It is known that the electric fields of two fish interact to produce beats with spatially varying profiles of amplitude and phase. Such patterns have been shown to be critical for electrosensory-mediated behaviours, such as the jamming avoidance response, but they have yet to be well described. We have created a biophysically realistic model of a wave-type weakly electric fish by using a genetic algorithm to calibrate the parameters to the electric field of a real fish. We use the model to study a pair of fish and compute the electric images of one fish onto the other at three representative phases within a beat cycle. Analysis of the images reveals rostral/caudal and ipsilateral/contralateral patterns of amplitude and phase that have implications for localization of conspecifics (both position and orientation) and communication between conspecifics. We then show how the common stimulation paradigm used to mimic a conspecific during in vivo electrophysiological experiments, based on a transverse arrangement of two electrodes, can be improved in order to more accurately reflect the important qualitative features of naturalistic inputs, as revealed by our model.     

Spatial patterns of weeds along a gradient of landscape complexity

Processes that drive spatial patterning among plant species are of ongoing interest, mostly because these patterns have implications for the structure and function of plant communities. We investigated the spatial strategies of weeds focusing on how spatial patterns of weeds are mediated by agricultural landscape complexity and species life-history attributes. We quantified the spatial distribution of 110 weed species using data collected in ten landscapes in central western France along a gradient of landscape complexity, from structurally complex (numerous small fields) to structurally simple (few large fields). We then related differences observed in species’ distribution patterns to ecological attributes of species for resource exploitation and dispersion. Our study reveals that weeds were spatially aggregated at the landscape scale. Their spatial patterns are related to the frequency of occurrence of weeds but surprisingly not directly to the seed dispersal type, nor to the degree of habitat specialization. We show that landscape complexity had no direct effect on the spatial patterning of weeds but through interactions with species attributes. Our results point to the importance of interactions between landscape complexity and species attributes in the spatial patterning of weed species even in intensively managed fields. These patterns appear to be a consequence of the spatial arrangement of landscape elements as well as the result of landscape filtering on species attributes.     

扩展点格局分析方法在灌木种群空间分布格局研究中的应用

当研究对象个体差异很大或者研究尺度与植物大小属于一个数量级时,传统的以种群空间分布的坐标点图为基础的点格局分析方法存在局限性.本文引入一种在传统点格局分析方法基础上发展起来的以栅格数据为分析对象的新方法——扩展点格局分析方法,用以分析具有一定面积和形状对象的空间格局和生态过程,该方法适用于灌木研究对象.以狭域特有种四合木(Tetraena mongolica)种群的空间分布格局分析为例,采用摄影定位法,用图像处理软件及地理信息系统软件将样地信息数字化后,利用扩展点格局分析方法分析了群落中四合木单种的空间分布格局及其与群落中霸王(Zygophyllum xanthoxylum)种群的关系,四合木种群在69～ 99 cm尺度上表现为均匀分布,四合木与霸王在350 ～570cm尺度上表现出显著的负关联关系.结果揭示了灌木种群的空间结构特征.     

Use of precise spatial data for describing spatial patterns and plant interactions in a diverse Great Basin shrub community

Community-structuring processes continue to be of great interest to plant ecologists, and plant spatial patterns have been linked to processes including disturbance, dispersal, environmental heterogeneity, and plant interactions. Under the assumption that the analysis of the spatial structure of plant communities can help to elucidate the type and importance of the predominant community-structuring processes, many studies have analyzed point pattern data on various plant species. A variety of methods have been devised to acquire point pattern data for individual plants, however, the classic tradeoff between the speed of acquisition and the precision of spatial data has meant that large and precise datasets on plant locations are difficult to obtain. The primary goal of this study was to develop a GPS-based methodology for the rapid collection of precise spatial data on plant locations in a semi-arid shrubland in the Great Basin, USA. The secondary goal was to demonstrate a potential application of this approach by using recently developed univariate and bivariate spatial statistics to test for aggregation within the shrub community, as observed in other semi-arid shrublands. We efficiently mapped 2,358 individuals of five shrub species with a spatial error of ≤0.02 m, and found strong statistical evidence of fine-scale aggregation (1) independent of species, (2) within species, and (3) between two species pairs. Our approach is useful for rapidly collecting precise point pattern data in plant communities, and has other applications related to population modeling, GIS analysis, and conservation.     

Electric images of two low resistance objects in weakly electric fish

Electroreceptive fish detect nearby objects by processing the information contained in the pattern of electric currents through their skin. In weakly electric fish, these currents arise from a self-generated field (the electric organ discharge), depending on the electrical properties of the surrounding medium. The electric image can be defined as the pattern of transepidermal voltage distributed over the receptive surface. To understand electrolocation it is necessary to know how electric image of objects are generated. In pulse mormyrids, the electric organ is localized at the tail, far from the receptors and fires a short biphasic pulse. Consequently, if all the elements in the environment are resistive, the stimulus at every point on the skin has the same waveform. Then, any measure of the amplitude (for example, the peak to peak amplitude) could be the unique parameter of the stimulus at any point of the skin. We have developed a model to calculate the image, corroborating that images are spread over the whole sensory surface and have an opposite center-surround, "Mexican-hat" shape. As a consequence, the images of different objects superimpose. We show theoretically and by simulation that the image of a pair of objects is not the simple addition of the individual images of these objects.     

Contribution of rarity and commonness to patterns of species richness

There is little understanding in ecology as to how biodiversity patterns emerge from the distribution patterns of individual species. Here we consider the question of the contributions of rare (restricted range) and common (widespread) species to richness patterns. Considering a species richness pattern, is most of the spatial structure, in terms of where the peaks and troughs of diversity lie, caused by the common species or the rare species (or neither)? Using southern African and British bird richness patterns, we show here that commoner species are most responsible for richness patterns. While rare and common species show markedly different species richness patterns, most spatial patterning in richness is caused by relatively few, more common, species. The level of redundancy we found suggests that a broad understanding of what determines the majority of spatial variation in biodiversity may be had by considering only a minority of species.     

基于不同零模型的点格局分析

在种群空间格局研究中,定量分析格局及其形成过程已成为生态学家的主要目标。在量化分析的众多方法中,点格局分析是最常用的方法,而在选择零模型时,完全空间随机模型以外的复杂零模型很少使用,实际上,这些零模型可能有助于认识格局的内在特征。为此,我们在研究实例中,选择完全空间随机模型(complete spatial randomness)、泊松聚块模型(Poisson cluster process)和嵌套双聚块模型(nested double-cluster process)对典型草原处于不同恢复演替阶段的羊草(Leymus chinensis)种群空间格局进行了分析。结果发现:完全空间随机模型仅能检测种群在不同尺度下的格局类型;而通过泊松聚块模型和嵌套双聚块模型检验表明,在恢复演替的初期阶段,羊草种群在小尺度范围内偏离泊松聚块模型,而在整个取样范围内完全符合嵌套双聚块模型;随着恢复演替时间的推移,在恢复演替的后期,在整个取样尺度上,羊草种群与泊松聚块模型相吻合。这是很有意义的生态学现象。这一实例表明在应用点格局分析种群空间格局时,仅通过完全空间随机模型的检验来分析格局特征,或许很难论证复杂的生态过程,而选择一些完全空间随机模型以外的较复杂的零模型,可能发现一些有价值的生态学现象,对揭示格局掩盖下的内在机制有所裨益。     

景观格局-土壤侵蚀研究中景观指数的意义解释及局限性

景观格局分析是景观生态学研究的重要组成部分。景观指数是景观格局分析的有力工具。近年来,景观格局与土壤侵蚀关系的相关研究增多,常规景观格局指数得到应用。但针对土壤侵蚀过程的景观指数意义解释不足,景观指数在刻画景观格局-土壤侵蚀过程关系存在局限。选择了连接性、多样性、边界/斑块密度、形状4个方面的12个常用景观指数,对这些指数在景观格局-土壤侵蚀过程关系研究中的意义进行阐述,对指数应用的局限性及其原因进行了分析。景观数据属性、景观指数本身性质和土壤侵蚀过程的复杂性使得常规景观格局指数在景观格局-土壤侵蚀关系研究中存在不足。这3方面的影响使得常规景观格局指数与土壤侵蚀表征变量之间不存在确定的关系,从而难以通过景观指数来表征景观土壤侵蚀特征。缺乏土壤侵蚀过程基础是常规景观指数在土壤侵蚀研究应用中存在局限的主要原因。因此,构建基于土壤侵蚀过程的景观指数是景观格局-土壤侵蚀关系研究的需要和新的发展方向。     

Contributions of Ignitions,Fuels, and Weather to the Spatial Patterns of Burn Probability of a Boreal Landscape

The spatial pattern of fire observed across boreal landscapes is the outcome of complex interactions among components of the fire environment. We investigated how the naturally occurring patterns of ignitions, fuels, and weather generate spatial pattern of burn probability (BP) in a large and highly fire-prone boreal landscape of western Canada, Wood Buffalo National Park. This was achieved by producing a high-resolution map of BP using a fire simulation model that models the ignition and spread of individual fires for the current state of the study landscape (that is, the ‘control’). Then, to extract the effect of the variability in ignitions, fuels, and weather on spatial BP patterns, we subtracted the control BP map to those produced by “homogenizing” a single environmental factor of interest (that is, the ‘experimental treatments’). This yielded maps of spatial residuals that represent the spatial BP patterns for which the heterogeneity of each factor of interest is responsible. Residuals were analyzed within a structural equation modeling framework. The results showed unequal contributions of fuels (67.4%), weather (29.2%), and ignitions (3.4%) to spatial BP patterning. The large contribution of fuels reflects how substantial heterogeneity of land cover on this landscape strongly affects BP. Although weather has a chiefly temporal control on fire regimes, the variability in fire-conducive weather conditions exerted a surprisingly large influence on spatial BP patterns. The almost negligible effect of spatial ignition patterns was surprising but explainable in the context of this area’s fire regime. Similar contributions of fuels, weather, and ignitions could be expected in other parts of the boreal forest that lack a strong anthropogenic imprint, but are likely to be altered in human-dominated fire regimes.     

Wavelet analysis for detecting anisotropy in point patterns

Although many methods have been proposed for analysing point locations for spatial pattern, previous methods have concentrated on clumping and spacing. The study of anisotropy (changes in spatial pattern with direction) in point patterns has been limited by lack of methods explicitly designed for these data and this purpose; researchers have been constrained to choosing arbitrary test directions or converting their data into quadrat counts and using methods designed for continuously distributed data. Wavelet analysis, a booming approach to studying spatial pattern, widely used in mathematics and physics for signal analysis, has started to make its way into the ecological literature. A simple adaptation of wavelet analysis is proposed for the detection of anisotropy in point patterns. The method is illustrated with both simulated and field data. This approach can easily be used for both global and local spatial analysis.     

Spatial variation of woolly apple aphid (

There is an increasing requirement to breed durable resistances to woolly apple aphid (WAA) into apple cultivars. Genetically diverse apple plantings have been established in New Zealand with one aim to identify new sources of resistance to this pest, and also to allow the computation of parameters of genetic interest. Such computations are hindered by the uneven distribution of the pest in the orchard. The spatial distribution of WAA was investigated using local trend surfaces to examine large scale patterns, and point process analyses to check for the presence of small scale clumping. Large scale patterns in WAA distribution were found which could be attributed to the degree of exposure of the trees, and clumping was also detectable. The experimental design was found to adequately accommodate these spatial patterns. The application of the point process analysis to other ecological situations, and manners in which it could be extended, are discussed.     

Patterns of coexistence of two species of freshwater turtles are affected by spatial scale

Inferring biotic interactions from the examination of patterns of species occurrences has been a central tenet in community ecology, and it has recently gained interest in the context of single-species distribution modelling. However, understanding of how spatial extent and grain size affect such inferences remains elusive. For example, would inferences of biotic interactions from broad-scale patterns of coexistence provide a surrogate for patterns at finer spatial scales? In this paper we examine how the spatial and environmental association between two closely related species of freshwater turtles in the Iberian Peninsula is affected by the geographical extent and resolution of the analysis. Species coexistence was compared across spatial scales using five datasets at varying spatial extents and resolutions. Both similarities in the two species’ use of space and in their responses to environmental variables were explored by means of regression analyses. We show that a positive association between the two species measured at broader scales can switch to a negative association at finer scales. We demonstrate that without examination of the effects of spatial scale when investigating biotic interactions using co-occurrence patterns observed at coarse resolutions, conclusions can be deeply misleading.     

Representation of objective similarity among three-dimensional shapes in the monkey

Humans have been recently shown to represent parameterized three-dimensional objects in a manner that preserves relative similarities (as measured by parameter-space distances) among the objects (Cutzu and Edelman 1996). We show that the representation of objects in the monkey visual system is similarly faithful to the parametric variation built into the stimulus set. A monkey (Macaca fuscata) performed a delayed matching-to-sample task with 28 images (4 views 7 objects). Stimuli in each of the two experiments were seven computer-rendered parameterized animal-like shapes, arranged in a low-dimensional configuration (namely, a two-dimensional TRIANGLE) in a common 56-dimensional parameter space. The monkey's task was to match objects (not views). Each experiment lasted for 3–4 weeks after the introduction of the stimulus set to the subject. Error rates were entered into a object confusion matrix and submitted to nonmetric multidimensional scaling (MDS). In both experiment 1 (mean correct rate 69.7%) and experiment 2 (mean correct rate 59.9%), the MDS solutions resembled closely the low-dimensional parameter-space patterns built into the stimuli, in the sense that the point corresponding to the central one in the original pattern was inside the other six points and that the order of the six points in angular positions around the center point was preserved. A simulation study showed that the resemblance could not be due to chance. These results demonstrate the possibility of veridical representation of parametric similarity among complex objects in the monkey. Received: 9 May 1997 / Accepted in revised form: 18 September 1997     

Negative density dependence and environmental heterogeneity effects on tree ferns across succession in a tropical montane forest

Although tree ferns are an important component of temperate and tropical forests, very little is known about their ecology. Their peculiar biology (e.g., dispersal by spores and two-phase life cycle) makes it difficult to extrapolate current knowledge on the ecology of other tree species to tree ferns. In this paper, we studied the effects of negative density dependence (NDD) and environmental heterogeneity on populations of two abundant tree fern species, Cyathea caracasana and Alsophila engelii, and how these effects change across a successional gradient. Species patterns harbor information on processes such as competition that can be easily revealed using point pattern analysis techniques. However, its detection may be difficult due to the confounded effects of habitat heterogeneity. Here, we mapped three forest plots along a successional gradient in the montane forests of Southern Ecuador. We employed homogeneous and inhomogeneous K and pair correlation functions to quantify the change in the spatial pattern of different size classes and a case–control design to study associations between juvenile and adult tree ferns. Using spatial estimates of the biomass of four functional tree types (short- and long-lived pioneer, shade- and partial shade-tolerant) as covariates, we fitted heterogeneous Poisson models to the point pattern of juvenile and adult tree ferns and explored the existence of habitat dependencies on these patterns. Our study revealed NDD effects for C. caracasana and strong environmental filtering underlying the pattern of A. engelii. We found that adult and juvenile populations of both species responded differently to habitat heterogeneity and in most cases this heterogeneity was associated with the spatial distribution of biomass of the four functional tree types. These findings show the effectiveness of factoring out environmental heterogeneity to avoid confounding factors when studying NDD and demonstrate the usefulness of covariate maps derived from mapped communities.     

Active manual control of object views facilitates visual recognition

Active exploration of large-scale environments leads to better learning of spatial layout than does passive observation [1] [2] [3]. But active exploration might also help us to remember the appearance of individual objects in a scene. In fact, when we encounter new objects, we often manipulate them so that they can be seen from a variety of perspectives. We present here the first evidence that active control of the visual input in this way facilitates later recognition of objects. Observers who actively rotated novel, three-dimensional objects on a computer screen later showed more efficient visual recognition than observers who passively viewed the exact same sequence of images of these virtual objects. During active exploration, the observers focused mainly on the 'side' or 'front' views of the objects (see also [4] [5] [6]). The results demonstrate that how an object is represented for later recognition is influenced by whether or not one controls the presentation of visual input during learning.