玄武湖菹草种群空间格局分析及其环境效应

大型水生植物的分布格局与空间尺度有着密切关系,传统的分析方法只能分析一种尺度下的格局。引入点格局分析,以种群空间分布坐标点图为基础,分析各种尺度下的种群格局。运用点格局分析对玄武湖菹草种群的空间分布格局进行研究,并结合N、P等水质指标探讨其环境效应。结果表明,玄武湖菹草种群分布集群特征明显,且在尺度232~344m内聚集最为明显。从水质监测结果看,菹草种群有利于改善水体环境,无种群区的TN、TP和NO3-N浓度明显高于有种群区;溶解氧(DO)则表现为有种群区高于无种群区。菹草在空间分布上的明显规律性,会进一步导致水质参数的空间异质性。     

Graphical spatial models: a new view on interpreting spatial pattern

Graphical models provide an important tool for facilitating communication between scientists, decision-makers, and statisticians—many complicated ecological processes can be described in terms of “box-and-arrow” conceptual diagrams (e.g., Shipley in Cause and correlation in biology: a user’s guide to path analysis, structural equations and causal inferences, Cambridge Universtiy Press, Cambridge, 2000; Clark and Gelfand TRENDS in Ecology and Evolution 21:375–380, 2006). In particular, problems in landscape ecology often involve modeling relationships among multiple physical and/or biological variables that may operate on differing spatial scales (e.g., Rossi et al. in Ecol Monographs 62:277–314, 1992; Legendre et al. in Ecography 25:601–615, 2002; Overmars et al. in Ecol Model 164:257–270, 2003; Brown and Spector in J Appl Ecol 45:1639–1648, 2008; Koniak and Noy-Meir in Ecol Model 220:1148–1158, 2008). These problems are inherently multivariate, though researchers commonly rely on univariate methods, such as spatial regression models, to address them. In this paper, we introduce a multivariate method—graphical spatial models—that extends path analysis to incorporate spatial autocorrelation in one or more variables in a directed graph. We show how both exogenous and endogenous ecological processes as defined by Legendre et al. (Ecography 25:601–615, 2002) and Lichstein et al. (Ecol Monographs 72:445–463, 2002) can be represented in a graph. Most importantly, we show how to translate graphs representing these ecological processes into statistically estimable models. We motivate our theoretical results using an example of stream health data from the Willamette Valley, Oregon. For these data we are interested in the spatial pattern within both riparian land use and an index of stream health, and whether there is an association between land use and stream health, after accounting for these spatial patterns. We use a graphical spatial model to address these ecological questions simultaneously. We find that the health of a stream decreases as the percent of developed land within a 120-m riparian buffer increases; interestingly, there is only evidence of spatial pattern within land use.     

Chaos and pattern formation in a spatial tritrophic food chain

The model of Hastings and Powell describes a tritrophic food chain that exhibits chaotic dynamics. The model assumes that the populations are homogeneously mixed, so that the probability that any two individuals interact is uniform and space can be ignored. In this paper we propose a spatial version of the Hastings and Powell model in which predators seek their preys only in a finite neighborhood of their home location, breaking the mixing hypothesis. Treating both space and time as discrete variables we derive a set of coupled equations that describe the evolution of the populations at each site of the spatial domain. We show that the introduction of local predator–prey interactions result in qualitatively distinct dynamics of predator and prey populations. The evolution equations for the predators involve averages over the local density of preys, whereas the equations for the preys involve double averages, where the local density of both preys and predators appear. Our numerical simulations show that local predation also leads to spontaneous pattern formation and to qualitative changes in the global dynamics of the system. In particular, depending on the size of the predation neighborhoods, the chaotic strange attractor present in the original model of Hastings and Powell can be replaced by a stable fixed point or by an attractor of simpler topology.     

Study on changes of urban spatial pattern and heterogeneity of driving factors in the Su-Xi-Chang region

Environmental and Ecological Statistics - Using the Suzhou-Wuxi-Changzhou (referred to as Su-Xi-Chang) region as a case study, this work applied an Exploratory Spatial Data Analysis model to study...     

Outbreak suppression by predators depends on spatial distribution of prey

The capacity of a predator population to suppress a prey population that varies in abundance and spatial distribution is explored in a lattice simulation model. The model is based on empirically derived parameters for particular species. Within season predation by Pterostichus cupreus (Coleoptera: Carabidae) of varying densities and distributions of the prey Rhopalosiphum padi (Homoptera: Aphididae) in spring cereals was simulated. From these spatially explicit simulations prey population suppression was found to be largely dependent on the spatial distribution of the prey. A possible mechanism was that high degrees of prey aggregation provided refuge for the prey that, when aggregated, escaped detection by P. cupreus. In contrast, P. cupreus was found to efficiently suppress incipient outbreaks for evenly distributed prey populations, even at high prey densities. A higher predator density compensated for the lowered control ability of the predators for highly aggregated prey populations and hastened the decline of the prey population.     

Diversity pattern and spatial scale: a study of a tropical rain forest of Malaysia

Scale is emerging as one of the critical problems in ecology because our perception of most ecological variables and processes depends upon the scale at which the variables are measured. A conclusion obtained at one scale may not be valid at another scale without sufficient knowledge of the scaling effect, which is also a source of misinterpretation for many ecological problems, such as the design of reserves in conservation biology.This paper attempts to study empirically how scaling may affect the spatial patterns of diversity (tree density, richness and Shannon diversity) that we may perceive in tropical forests, using as a test-case a 50 ha forest plot in Malaysia. The effect of scale on measurements of diversity patterns, the occurrence of rare species, the fractal dimension of diversity patterns, the spatial structure and the nearest-neighbour autocorrelation of diversity are addressed. The response of a variable to scale depends on the way it is measured and the way it is distributed in space.We conclude that, in general, the effect of scaling on measures of biological diversity is non-linear; heterogeneity increases with the size of the sampling units, and fine-scale information is lost at a broad scale. Our results should lead to a better understanding of how ecological variables and processes change over scale.     

Hierarchical spatial modeling for estimation of population size

Estimation of population size has traditionally been viewed from a finite population sampling perspective. Typically, the objective is to obtain an estimate of the total population count of individuals within some region. Often, some stratification scheme is used to estimate counts on subregions, whereby the total count is obtained by aggregation with weights, say, proportional to the areas of the subregions. We offer an alternative to the finite population sampling approach for estimating population size. The method does not require that the subregions on which counts are available form a complete partition of the region of interest. In fact, we envision counts coming from areal units that are small relative to the entire study region and that the total area sampled is a very small proportion of the total study area. In extrapolating to the entire region, we might benefit from assuming that there is spatial structure to the counts. We implement this by modeling the intensity surface as a realization from a spatially correlated random process. In the case of multiple population or species counts, we use the linear model of coregionalization to specify a multivariate process which provides associated intensity surfaces hence association between counts within and across areal units. We illustrate the method of population size estimation with simulated data and with tree counts from a Southwestern pinyon-juniper woodland data set.     

The influence of intraguild predation on prey suppression and prey release: a meta-analysis

Intraguild predation (IGP) occurs when one predator species consumes another predator species with whom it also competes for shared prey. One question of interest to ecologists is whether multiple predator species suppress prey populations more than a single predator species, and whether this result varies with the presence of IGP. We conducted a meta-analysis to examine this question, and others, regarding the effects of IGP on prey suppression. When predators can potentially consume one another (mutual IGP), prey suppression is greater in the presence of one predator species than in the presence of multiple predator species; however, this result was not found for assemblages with unidirectional or no IGP. With unidirectional IGP, intermediate predators were generally more effective than the top predator at suppressing the shared prey, in agreement with IGP theory. Adding a top predator to an assemblage generally caused prey to be released from predation, while adding an intermediate predator caused prey populations to be suppressed. However, the effects of adding a top or intermediate predator depended on the effectiveness of these predators when they were alone. Effects of IGP varied across different ecosystems (e.g., lentic, lotic, marine, terrestrial invertebrate, and terrestrial vertebrate), with the strongest patterns being driven by terrestrial invertebrates. Finally, although IGP theory is based on equilibrium conditions, data from short-term experiments can inform us about systems that are dominated by transient dynamics. Moreover, short-term experiments may be connected in some way to equilibrium models if the predator and prey densities used in experiments approximate the equilibrium densities in nature.     

青藏高原湿地景观空间格局的变化

在RS和GIS技术的支持下,以1990年左右的TM、2000年左右的ETM和2006年为主的CBERS遥感影像为主要数据源,利用人机交互目视解译方法获取青藏高原景观数据,运用景观生态学原理,选取景观异质性指数,对青藏高原湿地景观格局及其动态变化进行定量分析.结果表明,(1)青藏高原现有湿地面积131894.18 km2.(2)近16年来湿地总面积先大幅度减少后显著增加,柴达木盆地内的湿地减少量最为明显,长江流域次之;羌塘高原的湿地增加最为显著,塔里木盆地、雅鲁藏布江流域次之.(3)景观格局整体波动较大,多样性指数和均匀度指数降低,优势度指数增加,破碎度指数先增加后减少.     

The memory of spatial patterns: changes in local abundance and aggregation in a tropical forest

The current spatial pattern of a population is the result of previous individual birth, death, and dispersal events. We present a simple model followed by a comparative analysis for a species-rich plant community to show how the current spatial aggregation of a population may hold information about recent population dynamics. Previous research has shown how locally restricted seed dispersal often leads to stronger aggregation in less abundant populations than it does in more abundant populations. In contrast, little is known about how changes in the local abundance of a species may affect the spatial distribution of individuals. If the level of aggregation within a species depends to some extent on the abundance of the species, then changes in abundance should lead to subsequent changes in aggregation. However, an overall change of spatial pattern relies on many individual birth and death events, and a surplus of deaths or births may have short-term effects on aggregation that are opposite to the long-term change predicted by the change in abundance. The change in aggregation may therefore lag behind the change in abundance, and consequently, the current aggregation may hold information about recent population dynamics. Using an individual-based simulation model with local dispersal and density-dependent competition, we show that, on average, recently growing populations should be more aggregated than shrinking populations of the same current local abundance. We tested this hypothesis using spatial data on individuals from a long-term tropical rain forest plot, and find support for this relationship in canopy trees, but not in understory and shrub species. On this basis we argue that current spatial aggregation is an important characteristic that contains information on recent changes in local abundance, and may be applied to taxonomic groups where dispersal is limited and within-species aggregation is observed.     

Interactive effects of prey and p,p'-DDE on burrowing owl population dynamics.

We used population models to explore the effects of the organochlorine contaminant p,p'-DDE and fluctuations in vole availability on the population dynamics of Burrowing Owls (Athene cunicularia). Previous work indicated an interaction between low biomass of voles in the diet and moderate levels of p,p'-DDE in Burrowing Owl eggs that led to reproductive impairment. We constructed periodic and stochastic matrix models that incorporated three vole population states observed in the field: average, peak, and crash years. We modeled varying frequencies of vole crash years and a range of impairment of owl demographic rates in vole crash years. Vole availability had a greater impact on owl population growth rate than did reproductive impairment if vole populations peaked and crashed frequently. However, this difference disappeared as the frequency of vole crash years declined to once per decade. Fecundity, the demographic rate most affected by p,p'-DDE, had less impact on population growth rate than adult or juvenile survival. A life table response experiment of time-invariant matrices for average, peak, and crash vole conditions showed that low population growth under vole crash conditions was due to low adult and juvenile survival rates, whereas the extremely high population growth under vole peak conditions was due to increased fecundity. Our results suggest that even simple models can provide useful insights into complex ecological interactions. This is particularly valuable when temporal or spatial scales preclude manipulative experimental work in the field or laboratory.     

Temporal and spatial changes in plant dune diversity in urban resorts

We investigated the temporal and spatial changes in the floristic composition and abundance in sand dunes along a coastal strip in the province of Buenos Aires (Argentina). Firstly, we analysed changes over a span of 70 years, comparing 41 of our own inventories carried out in 14 beach resorts in 2005–2006 with 18 inventories made in the first half of the XXth century (1930–1940) in the same study area. We grouped sampled plots into four categories for comparison, taking into account the time period (1930–1940 or 2005–2006) and location at each end of the surveyed coastal strip in the northern or southern ‘tourist’ sectors. Secondly, we analysed the effect of afforestation with exotic trees on extant sand dune vegetation for the period 2005–2006. A total of 74 plant inventories were carried out in afforested and natural dunes at the same resorts. In both comparisons we contrasted plant richness, percentage plant cover, similarity and diversity. A cluster analysis was used to classify categories taking into account plant abundance and composition. Significant differences in total diversity were observed between sampling years, suggesting an increase in diversity at the present time due to urbanization and recreation related activities. Nevertheless, no single exotic plant species was clearly dominant across the sampled sites, suggesting that these coastal areas are, up to now, resistant to alien invasion. Diversity indexes discriminated by plant groups indicating different habitat conditions and exotics were shown to be more sensitive to existing changes than to total richness and cover.     

珠江三角洲地区高速公路沿线景观格局变化研究

根据1995年和2005年土地利用数据,借助地理信息系统软件和景观生态学方法研究珠江三角洲区域发展轴线——广深高速公路和广珠高速公路运营前后沿线区域的土地利用和景观格局变化,并进一步对比分析相同功能等级道路的生态效应差异。结果表明：（1）高速公路运营后,沿线区域建设用地增加迅速,耕地大量流失且迅速向建设用地转化;（2）公路的建设运营使得沿线区域人工干扰强度加大,景观斑块密度增加、面积减少、斑块形状趋向复杂,景观破碎化加剧;（3）道路途径区域的社会经济条件以及原有的景观格局特征是导致道路生态破碎效应差异的重要原因;（4）公路对自然景观的影响效应远大于其对人工景观的影响效应。     

Forecasting population trend from the scaling pattern of occupancy

Forecasting the temporal trend of a focal species, its range expansion or retraction, provides crucial information regarding population viability. To this end, we require the accumulation of temporal records which is evidently time consuming. Progress in spatial data capturing has enabled rapid and accurate assessment of species distribution across large scales. Therefore, it would be appealing to infer the temporal trends of populations from the spatial structure of their distributions. Based on a combination of models from the fields of range dynamics, occupancy scaling and spatial autocorrelation, here I present a model for forecasting the population trend solely from its spatial distribution. Numerical tests using cellular automata confirm a positive correlation, as inferred from the model, between the temporal change in species range sizes and the exponent of the power-law scaling pattern of occupancy. The model is thus recommended for rapid estimation of species range dynamics from a single snapshot of its current distribution. Further applications in biodiversity conservation could provide a swift risk assessment, especially, for endangered and invasive species.     

Movement of foraging Tundra Swans explained by spatial pattern in cryptic food densities

We tested whether Tundra Swans use information on the spatial distribution of cryptic food items (below ground Sago pondweed tubers) to shape their movement paths. In a continuous environment, swans create their own food patches by digging craters, which they exploit in several feeding bouts. Series of short (<1 m) intra-patch movements alternate with longer inter-patch movements (>1 m). Tuber biomass densities showed a positive spatial auto-correlation at a short distance (<3 m), but not at a larger distance (3-8 m). Based on the spatial pattern of the food distribution (which is assumed to be pre-harvest information for the swan) and the energy costs and benefits for different food densities at various distances, we calculated the optimal length of an inter-patch movement. A swan that moves to the patch with the highest gain rate was predicted to move to the adjacent patch (at 1 m) if the food density in the current patch had been high (>25 g/m2) and to a more distant patch (at 7-8 m) if the food density in the current patch had been low (<25 g/m2). This prediction was tested by measuring the response of swans to manipulated tuber densities. In accordance with our predictions, swans moved a long distance (>3 m) from a low-density patch and a short distance (<3 m) from a high-density patch. The quantitative agreement between prediction and observation was greater for swans feeding in pairs than for solitary swans. The result of this movement strategy is that swans visit high-density patches at a higher frequency than on offer and, consequently, achieve a 38% higher long-term gain rate. Swans also take advantage of spatial variance in food abundance by regulating the time in patches, staying longer and consuming more food from rich than from poor patches. We can conclude that the shape of the foraging path is a reflection of the spatial pattern in the distribution of tuber densities and can be understood from an optimal foraging perspective.     

The spatial pattern of nitrogen cycling in the Adirondack Park, New York

Maps of canopy nitrogen obtained through analysis of high-resolution, hyperspectral, remotely sensed images now offer a powerful means to make landscape-scale to regional-scale estimates of forest N cycling and net primary production (NPP). Moreover, recent research has suggested that the spatial variability within maps of canopy N may be driven by environmental gradients in such features as historic forest disturbance, temperature, species composition, moisture, geology, and atmospheric N deposition. Using the wide variation in these six features found within the diverse forest ecosystems of the 2.5 million ha Adirondack Park, New York, USA, we examined linkages among environmental gradients and three measures of N cycling collected during the 2003 growing season: (1) field survey of canopy N, (2) field survey of soil C:N, and (3) canopy N measured through analysis of two 185 x 7.5 km Hyperion hyperspectral images. These three measures of N cycling strongly related to forest type but related poorly to all other environmental gradients. Further analysis revealed that the spatial pattern in N cycling appears to have distinct inter- and intraspecific components of variability. The interspecific component, or the proportional contribution of species functional traits to canopy biomass, explained 93% of spatial variability within the field canopy N survey and 37% of variability within the soil C:N survey. Residual analysis revealed that N deposition accounted for an additional 2% of variability in soil C:N, and N deposition and historical forest disturbance accounted for an additional 2.8% of variability in canopy N. Given our finding that 95.8% of the variability in the field canopy N survey could be attributed to variation in the physical environment, our research suggests that remotely sensed maps of canopy N may be useful not only to assess the spatial variability in N cycling and NPP, but also to unravel the relative importance of their multiple controlling factors.     

人类活动对上海市生物多样性空间格局的影响

为了揭示人类活动对城市化地区生物多样性空间格局的影响及其景观生态学机制,文章将上海市作为研究对象,选择3个人类活动指标、3个主要类型生态系统的4个景观特征指标与8个生物多样性指标,探讨人类活动强度、野生动植物生境景观特征及生物多样性三者之间的相互关系。结果显示,人口增长和城市扩张对上海市生物多样性的空间格局产生了显著影响。在上海地区,人口密度较高、交通较为发达的区域,湿地和农田的景观连续性较低,生物多样性也较低,外来入侵物种丰度较高。这表明在快速城市化过程中,人类活动通过改变野生动植物栖息地景观质量来对区域生物多样性产生影响。本研究还显示,经济发展并非一定对生物多样性具有负面影响。因此,在保持经济发展的同时,通过优化产业结构与加强生物多样性管理,可实现对生物多样性有效保护。     

Statistical inference using the g or K point pattern spatial statistics

Spatial point pattern analysis provides a statistical method to compare an observed spatial pattern against a hypothesized spatial process model. The G statistic, which considers the distribution of nearest neighbor distances, and the K statistic, which evaluates the distribution of all neighbor distances, are commonly used in such analyses. One method of employing these statistics involves building a simulation envelope from the result of many simulated patterns of the hypothesized model. Specifically, a simulation envelope is created by calculating, at every distance, the minimum and maximum results computed across the simulated patterns. A statistical test is performed by evaluating where the results from an observed pattern fall with respect to the simulation envelope. However, this method, which differs from P. Diggle's suggested approach, is invalid for inference because it violates the assumptions of Monte Carlo methods and results in incorrect type I error rate performance. Similarly, using the simulation envelope to estimate the range of distances over which an observed pattern deviates from the hypothesized model is also suspect. The technical details of why the simulation envelope provides incorrect type I error rate performance are described. A valid test is then proposed, and details about how the number of simulated patterns impacts the statistical significance are explained. Finally, an example of using the proposed test within an exploratory data analysis framework is provided.     

Finite population properties of individual predictors based on spatial patterns

In this study a conceptual framework for assessing the statistical properties of a non-stochastic spatial interpolator is developed through the use of design-based finite population inference tools. By considering the observed locations as the result of a probabilistic sampling design, we propose a standardized weighted predictor for spatial data starting from a deterministic interpolator that usually does not provide uncertainty measures. The information regarding the coordinates of the spatial locations is known at the population level and is directly used in constructing the weighting system. Our procedure captures the spatial pattern by means of the Euclidean distances between locations, which are fixed and do not require any further assessment after the sample has been drawn. The predictor for any individual value turns in a ratio of design-based random quantities. We illustrate the predictor design-based statistical properties, i.e. asymptotically p-unbiasedness and p-consistency, for simple random sampling without replacement. An application to a couple of environmental datasets is presented, for assessing predictor performances in correspondence of different population characteristics. A comparison with the equivalent non-spatial predictor is presented.     

Age-dependent population dynamics with several interior variables and spatial spread

The problems of the asymptotic behavior of age-dependent population models with interior and spatial structures are considered. It is proved that the existence and uniqueness of the stable state and its exact form is founded for general linear models. Problems on the speed of convergence to stable state and transitional effects are investigated. Methods of solving two special classes of nonlinear models (separate models and models of the Gurtin-MacCami type) are suggested. A model of forest stand dynamics on the basis of conception of layer-mosaic characteristics of the spatial-temporal structure of stands is examined as an example of the application of given results.