板栗和锥栗同域居群的空间遗传结构

采用微卫星技术研究了板栗(Castanea mollissima)和锥栗(C. henryi)同域分布居群的空间遗传结构, 探讨了它们的遗传变异空间分布特征及其形成机制。结果表明,采用的7个微卫星在两物种中共扩增出173个等位基因,两物种都具有较高的遗传多样性且种间遗传分化水平较低(F_ST=0.051), 但空间自相关分析揭示板栗和锥栗在同域居群中具有不同的空间遗传结构,锥栗在100 m内有空间遗传结构,而板栗没有;同时,基于亲缘关系系数F_ij的Sp统计值也显示锥栗具有比板栗更强的空间遗传结构(板栗的Sp=0.002;锥栗的Sp=0.018)。居群遗传变异的空间结构是其传粉和种子散播及生境共同作用的结果,其中种子的近距离散播和居群密度可能是主要的因素。板栗和锥栗居群在小尺度上空间遗传结构的差异可能反映了它们种子的大小及扩散过程的差异。     

生态学系统的空间异质性

空间异质性是生态学系统的一个普遍牧场生,生态学家对它在生态学中的重要性已取得了比以往更深刻的认识。试图从空间异质性的含义,空间异质性与尺度和等级的关系,空间异质性的定量描述,空间异质性对生物和非生物过程的影响,以及空间异质性的动态等5个方面综述了有关空间异质性的生态学研究的新进展。     

Patterns in Temporal Variability of Temperature,Oxygen and pH along an Environmental Gradient in a Coral Reef

Spatial and temporal environmental variability are important drivers of ecological processes at all scales. As new tools allow the in situ exploration of individual responses to fluctuations, ecologically meaningful ways of characterizing environmental variability at organism scales are needed. We investigated the fine-scale spatial heterogeneity of high-frequency temporal variability in temperature, dissolved oxygen concentration, and pH experienced by benthic organisms in a shallow coastal coral reef. We used a spatio-temporal sampling design, consisting of 21 short-term time-series located along a reef flat-to-reef slope transect, coupled to a long-term station monitoring water column changes. Spectral analyses revealed sharp gradients in variance decomposed by frequency, as well as differences between physically-driven and biologically-reactive parameters. These results highlight the importance of environmental variance at organismal scales and present a new sampling scheme for exploring this variability in situ.     

Spatial Heterogeneity,Host Movement and Mosquito-Borne Disease Transmission

Mosquito-borne diseases are a global health priority disproportionately affecting low-income populations in tropical and sub-tropical countries. These pathogens live in mosquitoes and hosts that interact in spatially heterogeneous environments where hosts move between regions of varying transmission intensity. Although there is increasing interest in the implications of spatial processes for mosquito-borne disease dynamics, most of our understanding derives from models that assume spatially homogeneous transmission. Spatial variation in contact rates can influence transmission and the risk of epidemics, yet the interaction between spatial heterogeneity and movement of hosts remains relatively unexplored. Here we explore, analytically and through numerical simulations, how human mobility connects spatially heterogeneous mosquito populations, thereby influencing disease persistence (determined by the basic reproduction number R ₀), prevalence and their relationship. We show that, when local transmission rates are highly heterogeneous, R ₀ declines asymptotically as human mobility increases, but infection prevalence peaks at low to intermediate rates of movement and decreases asymptotically after this peak. Movement can reduce heterogeneity in exposure to mosquito biting. As a result, if biting intensity is high but uneven, infection prevalence increases with mobility despite reductions in R ₀. This increase in prevalence decreases with further increase in mobility because individuals do not spend enough time in high transmission patches, hence decreasing the number of new infections and overall prevalence. These results provide a better basis for understanding the interplay between spatial transmission heterogeneity and human mobility, and their combined influence on prevalence and R ₀.     

A practical approach to the study of spatial structure in simple cases of heterogeneous vegetation

Abstract. Spatial heterogeneity is a characteristic of most natural ecosystems which is difficult to handle analytically, particularly in the absence of knowledge about the exogenous factors responsible for this heterogeneity. While classical methods for analysis of spatial point patterns usually require the hypothesis of homogeneity, we present a practical approach for partitioning heterogeneous vegetation plots into homogeneous subplots in simple cases of heterogeneity without drastically reducing the data. It is based on the detection of endogenous variations of the pattern using local density and second‐order local neighbour density functions that allow delineation of irregularly shaped subplots that could be considered as internally homogeneous. Spatial statistics, such as Ripley's K‐function adapted to analyse plots of irregular shape, can then be computed for each of the homogeneous subplots. Two applications to forest ecological field data demonstrate that the method, addressed to ecologists, can avoid misinterpretations of the spatial structure of heterogeneous vegetation stands.     

Species Richness-Environment Relationships of European Arthropods at Two Spatial Grains: Habitats and Countries

We study how species richness of arthropods relates to theories concerning net primary productivity, ambient energy, water-energy dynamics and spatial environmental heterogeneity. We use two datasets of arthropod richness with similar spatial extents (Scandinavia to Mediterranean), but contrasting spatial grain (local habitat and country). Samples of ground-dwelling spiders, beetles, bugs and ants were collected from 32 paired habitats at 16 locations across Europe. Species richness of these taxonomic groups was also determined for 25 European countries based on the Fauna Europaea database. We tested effects of net primary productivity (NPP), annual mean temperature (T), annual rainfall (R) and potential evapotranspiration of the coldest month (PET_min) on species richness and turnover. Spatial environmental heterogeneity within countries was considered by including the ranges of NPP, T, R and PET_min. At the local habitat grain, relationships between species richness and environmental variables differed strongly between taxa and trophic groups. However, species turnover across locations was strongly correlated with differences in T. At the country grain, species richness was significantly correlated with environmental variables from all four theories. In particular, species richness within countries increased strongly with spatial heterogeneity in T. The importance of spatial heterogeneity in T for both species turnover across locations and for species richness within countries suggests that the temperature niche is an important determinant of arthropod diversity. We suggest that, unless climatic heterogeneity is constant across sampling units, coarse-grained studies should always account for environmental heterogeneity as a predictor of arthropod species richness, just as studies with variable area of sampling units routinely consider area.     

Ecological Complexity in a Coffee Agroecosystem: Spatial Heterogeneity,Population Persistence and Biological Control

Background

Spatial heterogeneity is essential for the persistence of many inherently unstable systems such as predator-prey and parasitoid-host interactions. Since biological interactions themselves can create heterogeneity in space, the heterogeneity necessary for the persistence of an unstable system could be the result of local interactions involving elements of the unstable system itself.

Methodology/Principal Findings

Here we report on a predatory ladybird beetle whose natural history suggests that the beetle requires the patchy distribution of the mutualism between its prey, the green coffee scale, and the arboreal ant, Azteca instabilis. Based on known ecological interactions and the natural history of the system, we constructed a spatially-explicit model and showed that the clustered spatial pattern of ant nests facilitates the persistence of the beetle populations. Furthermore, we show that the dynamics of the beetle consuming the scale insects can cause the clustered distribution of the mutualistic ants in the first place.

Conclusions/Significance

From a theoretical point of view, our model represents a novel situation in which a predator indirectly causes a spatial pattern of an organism other than its prey, and in doing so facilitates its own persistence. From a practical point of view, it is noteworthy that one of the elements in the system is a persistent pest of coffee, an important world commodity. This pest, we argue, is kept within limits of control through a complex web of ecological interactions that involves the emergent spatial pattern.     

空间粒度变化对景观格局分析的影响

认识空间异质性的多尺度依赖性和景观格局特征对尺度效应关系的影响是进行空间尺度推绎的基础。以2种真实景观(中国广东粤北植被景观与美国凤凰城城市景观)和SIMMAP景观中性模型产生的27种模拟景观为对象。利用景观格局分析软件FRAGSTATS对18种常用景观指数的尺度效应进行了系统的分析。根据这些指数对空间粒度变化的响应曲线和尺度效应关系,18种景观指数可分为3类。第1类指数随空间粒度的增大单调减小。具有比较明确的尺度效应关系(幂函数下降),尺度效应关系受景观空间格局特征的影响较小;这类指数包括缀块数、缀块密度、边界总长、边界密度、景观形状指数、缀块面积变异系数、面积加权平均缀块形状指数、平均缀块分维数和面积加权平均缀块分维数。第2类指数随空间粒度的增大将最终下降。但不是单调下降的;尺度效应关系比较多样,可表现为幂函数下降、直线下降或阶梯形下降。主要受缀块空间分布方式和缀块类优势度的交互影响;这类指数有5种：平均缀块形状指数、双对数回归分维数、缀块丰度、缀块丰度密度和Shannon多样性指数。第3类指数随空间粒度的变粗而增加。随缀块类优势度均等性的增加。尺度效应关系由阶梯形增加、对数函数增加、直线增加向幂函数增加过渡。尺度效应关系主要受缀块类优势度的影响;此类指数包括平均缀块面积、缀块面积标准差、最大缀块指数与聚集度。景观指数随空间粒度变化是一种1临界现象,当粒度大于或小于1临界值时,景观指数对空间粒度变化非常敏感。变化速率非常大。绝大部分情况下。真实景观粒度效应关系和曲线形状与模拟景观所得分析结果相似。说明模拟景观具有很好的代表性。文中也讨论了本研究结果与前人研究的异同。分析了造成差异的原因。景观指数的粒度效应关系与指数本身所反映的景观格局信息有一定关系,总体上来说。随粒度增加。缀块数、边界长度、缀块形状的复杂性、多样性将减小,而平均缀块面积和聚集度将增加。一系列的尺度效应图和不同景观指数的尺度效应关系可作为景观格局分析时指数选择、分析结果的解释和进行空间尺度推绎的参考。     

Spatial Analysis of Heterodera glycines Populations in Field Plots

Spatial heterogeneity in nematode population densities presents an obstacle to the precise determination of infestation levels. Three field plots were intensively sampled for soybean cyst nematode (Heterodera glycines Ich.) cysts before and after spring cultivation to quantify the spatial attributes of the population. Population density strata were detected running parallel to plant rows. Highest population densities before cultivation were found in the plant row and the middle furrow, Population density in the plant row averaged 26% higher and 4% lower than the whole-plot mean before and after cultivation, respectively. Cysts containing fewer than 25 eggs were not stratified, indicating that most were produced before the previous season. Sample population counts were fit to the negative binomial distribution model before cultivation, but distributions differed among plots. The Neyman type A and negative binomial distributions both fit the data after cultivation disturbed the soil. Population clusters 1-3 m long were detected in plant beds before cultivation. Heterogeneity in population density increased with plant row length after cultivation. Optimum plot length for minimal spatial heterogeneity in four-row mechanically tended field plots was estimated at 6 m after trimming plot ends.     

Association of GSTP1 Ile105Val Polymorphism and Risk of Head and Neck Cancers: A Meta-Analysis of 28 Case-Control Studies

Background and Aims

The Glutathione S-transferase P1 (GSTP1) polymorphism have been considered a risk modifier for developing head and neck cancer (HNC) in many studies; however, the results of such studies are inconsistent. The aim of this study was to evaluate the possible association between the GSTP1 Ile105Val polymorphism and risk of HNC.

Method

We performed a search in the relevant electronic database and a meta-analysis based on 28 published case–control studies that included 6,404 cases and 6,523 controls. To take into account the possibility of heterogeneity across the studies, a Chi-square based I²-statistic test was performed. Crude pooled odds ratios (ORs) with 95% confidence intervals (CIs) were assessed using both fixed-effects and random-effects models.

Results

The results of this meta-analysis showed that the GSTP1 Ile105Val polymorphism was not significantly associated with risk of HNC in the overall study population (pooled OR 1.00, 95% CI 0.92–1.09) or in subgroup analyses stratified by ethnicity, sample size, tumor site or publication year. Moreover, substantial evidence of heterogeneity among the studies was observed. Publication year was identified as the main cause of heterogeneity.

Conclusion

This meta-analysis does not support a significant association between the GSTP1 Ile105Val polymorphism and risk of HNC.     

Ecosystem spatial self-organization: Free order for nothing?

Ecosystems are complex adaptive systems (CAS) by nature, which means that macroscopic patterns and properties emerge from, and feed back to affect, the interactions among adaptive individual ecological agents. These agents then further adapt (genetically) to the outcomes of those interactions. The concept of self-organization has become increasingly important for understanding ecosystem spatial heterogeneity and its consequences. It is well accepted that ecosystems can self-organize, and that resulting spatial structures carry functional consequences. Feedbacks from the outcome of spatial pattern to the individual agents from which patterns emerge, are an essential component of the definition of CAS but have been rarely examined for ecosystems. We explore whether spatial self-organization provides a mechanism for such feedback for ecosystems as CAS, that is, whether ecosystem-level outcomes of self-organized patterning could feed back to affect or even reinforce local pattern-forming processes at the agent level. Diffuse feedbacks of ecological and evolutionary significance ensue as a result of spatial heterogeneity and regular patterning, whether this spatial heterogeneity results from an underlying template effect or from self-organization. However, feedbacks directed specifically at pattern-forming agents to enhance pattern formation—reinforcing feedback—depend upon the level of organization of agents. Reinforcing evolutionary feedbacks occur at the individual level or below. At the ecosystem level, evidence for mechanisms of feedback from outcomes to patterning to agents forming the patterning remain tenuous. Spatial self-organization is a powerful dynamic in ecosystem and landscape science but feedbacks have been only loosely integrated so far. Self-organized patterns influencing dynamics at the ecosystem level represent “order for free”. Whether or not this free order generated at the ecosystem level carries evolutionary function or is merely epiphenomenal is a fundamental question that we address here.     

Metabolic Flexibility as a Major Predictor of Spatial Distribution in Microbial Communities

A better understand the ecology of microbes and their role in the global ecosystem could be achieved if traditional ecological theories can be applied to microbes. In ecology organisms are defined as specialists or generalists according to the breadth of their niche. Spatial distribution is often used as a proxy measure of niche breadth; generalists have broad niches and a wide spatial distribution and specialists a narrow niche and spatial distribution. Previous studies suggest that microbial distribution patterns are contrary to this idea; a microbial generalist genus (Desulfobulbus) has a limited spatial distribution while a specialist genus (Methanosaeta) has a cosmopolitan distribution. Therefore, we hypothesise that this counter-intuitive distribution within generalist and specialist microbial genera is a common microbial characteristic. Using molecular fingerprinting the distribution of four microbial genera, two generalists, Desulfobulbus and the methanogenic archaea Methanosarcina, and two specialists, Methanosaeta and the sulfate-reducing bacteria Desulfobacter were analysed in sediment samples from along a UK estuary. Detected genotypes of both generalist genera showed a distinct spatial distribution, significantly correlated with geographic distance between sites. Genotypes of both specialist genera showed no significant differential spatial distribution. These data support the hypothesis that the spatial distribution of specialist and generalist microbes does not match that seen with specialist and generalist large organisms. It may be that generalist microbes, while having a wider potential niche, are constrained, possibly by intrageneric competition, to exploit only a small part of that potential niche while specialists, with far fewer constraints to their niche, are more capable of filling their potential niche more effectively, perhaps by avoiding intrageneric competition. We suggest that these counter-intuitive distribution patterns may be a common feature of microbes in general and represent a distinct microbial principle in ecology, which is a real challenge if we are to develop a truly inclusive ecology.     

Ecological application of wavelet analysis in the scaling of spatial distribution patterns of Ceratoides ewersmanniana

Ecological experiments are usually conducted on small scales, but the ecological and environmental issues are usually on large scales. Hence, there is a clear need of scaling. Namely, when we deal with patterns and processes on larger scales, a special connection needs to be established on the small scales that we are familiar with. Here we presented a wavelet analysis method that could build relationships between spatial distribution patterns on different scales. With this method, we also studied how spatial heterogeneity and distribution patterns changed with the scale. We investigated the distribution and the habitat of C. ewersmanniana in two plots (200 m × 200 m; the distance between these two plots is 15 km) at Mosuowan desert. The results demonstrated that spatial heterogeneity and distribution patterns were incorporated into larger scales when the wavelet scale varied from one (5 m) to four (20 m). However, if the wavelet scale was above five (25 m), the spatial distribution patterns varied placidly, the oscillation frequency of landforms stabilized at 110 m, and the dynamic quantity period of C. ewersmanniana stabilized at 115–125 m. We also identified signal mutation points with wavelet analysis and verified the heterogeneity degree of local space with position variance. We found that position variance decomposed the distribution patterns on large scales into small sampling plots, and the position with the largest variance also had the strongest heterogeneity. In a word, the wavelet analysis method could scale-up spatial distribution patterns and habitat heterogeneity. With this method and other methods derived from this one, such as wavelet scale, wavelet variance, position variance and extremely direct-viewing graphs, wavelet analysis could be widely applied in solving the scaling problem in ecological and environmental studies.     

Seed dormancy-breaking and germination requirements ofDrosera anglica,an insectivorous species of the Northern Hemisphere

Seeds of Drosera anglica collected in Sweden were dormant at maturity in late summer, and dormancy break occurred during cold stratification. Stratified seeds required light for germination, but light had to be given after temperatures were high enough to be favorable for germination. Seeds stratified in darkness at 5/1 °C and incubated in light at 12/12 h daily temperature regimes of 15/6, 20/10 and 25/15 °C germinated slower and to a significantly lower percentage at each temperature regime than those stratified in light and incubated in light. Length of the stratification period required before seeds would germinate to high percentages depended on (1) whether seeds were in light or in darkness during stratification and during the subsequent incubation period, and (2) the temperature regime during incubation. Seeds collected in 1999 germinated to 4, 24 and 92 % in light at 15/6, 20/10 and 25/15 °C, respectively, after 2 weeks of stratification in light. Seeds stratified in light for 18 weeks and incubated in light at 15/6, 20/10 and 25/15 °C germinated to 87, 95 and 100 %, respectively, while those stratified in darkness for 18 weeks and incubated in light germinated to 6, 82 and 91 %, respectively. Seeds collected from the same site in 1998 and 1999, stratified in light at 5/1 °C and incubated in light at 15/6 °C germinated to 22 and 87 %, respectively, indicating year-to-year variation in degree of dormancy. As dormancy break occurred, the minimum temperature for germination decreased. Thus, seed dormancy is broken in nature by cold stratification during winter, and by spring, seeds are capable of germinating at low habitat temperatures, if they are exposed to light.     

Effects of Sand Dune Stabilization on the Spatial Pattern of Artemisia ordosica Population in Mu Us Desert,Northwest China

Vegetation patterns are strongly influenced by sand mobility in desert ecosystems. However, little is known about the spatial patterns of Artemisia ordosica, a dominant shrub in the Mu Us desert of Northwest China, in relation to sand fixation. The aim of this study was to investigate and contrast the effects of sand dune stabilization on the population and spatial distribution of this desert shrub. Spatial autocorrelation, semi-variance analysis, and point-pattern analysis were used jointly in this study to investigate the spatial patterns of A. ordosica populations on dunes in Yanchi County of Ningxia, China. The results showed that the spatial autocorrelation and spatial heterogeneity declined gradually, and the distance between the clustered individuals shortened following sand dune fixation. Seedlings were more aggregated than adults in all stage of dune stabilization, and both were more aggregated on shifting sand dunes separately. Spatial associations of the seedlings with the adults were mostly positive at distances of 0–5 m in shifting sand dunes, and the spatial association changed from positive to neutral in semi-fixed sand dunes. The seedlings were spaced in an almost random pattern around the adults, and their distances from the adults did not seem to affect their locations in semi-fixed sand dunes. Furthermore, spatial associations of the seedlings with the adults were negative in the fixed sand dune. These findings demonstrate that sand stabilization is an important factor affecting the spatial patterns of A. ordosica populations in the Mu Us desert. These findings suggest that, strong association between individuals may be the mechanism to explain the spatial pattern formation at preliminary stage of dune fixation. Sand dune stabilization can change the spatial pattern of shrub population by weakening the spatial association between native shrub individuals, which may affect the development direction of desert shrubs.     

Spatial variation of biochemical and ecological phenotypes in Drosophila: Electrophoretic and quantitative variation

Electrophoretic variation at three enzyme loci-alcohol dehydrogenase (Adh), glycerophosphate dehydrogenase (Gpdh), triosephosphate isomerase (Tpi)- is compared in Australian Drosophila melanogaster populations at three levels of spatial heterogeneity; among breeding sites, within populations, and between populations at the geographic level. Heterogeneity at the breeding site level greatly exceeds that among adults within populations, indicating greater intermixing at the mobile adult stage than at the developmentally immature and less migratory larval stage. Heterogeneity at the microspatial level is large relative to the geographic level at two of these loci. Spatial patterns of variation in ecological phenotypes are also considered. It is argued that electrophoretic variants may contribute little to an understanding of this quantitative variation, and that a more useful approach in ecological genetics is to consider ecological phenotypes as primary data.     

Patterns and ecological consequences of abiotic heterogeneity in managed cork oak forests of Southern Spain

Spatial heterogeneity of abiotic factors influences the structure and function of forests and must be taken into account for their conservation and sustainable management. In this study, we evaluate the heterogeneity of abiotic environmental variables in managed cork oak (Quercus suber L.) forests in southern Spain at patch, site and regional scales. The extent of spatial heterogeneity depended on the environmental variable examined and the scale considered. For example, soil Mn and P and light availability in the understorey were very heterogeneous at the regional scale, while soil N had low regional heterogeneity, but high spatial variability, at patch scale, attributed to open overstorey and grazing disturbance. There was a general trend of increasing heterogeneity with spatial scale. We also study the effects of a silvicultural practice—shrub clearing on the forest environment and its consequence for spatial heterogeneity. Shrub clearing increased understorey light and decreased its spatial heterogeneity with idiosyncratic effects on soil properties and their spatial heterogeneity at each site. Finally, we compare the heterogeneity (estimated by the coefficient of variation) obtained in these cork oak forests with a database compiled from published studies on other forest environments. The comparison revealed a remarkable extent of abiotic heterogeneity in the cork oak forests studied, suggesting that a sustainable management of these forests should combine intrinsic and human induced abiotic heterogeneity to preserve crucial ecological processes and to maintain high levels of biodiversity.     

Assessment of Genetic Heterogeneity in Structured Plant Populations Using Multivariate Whole-Genome Regression Models

Plant breeding populations exhibit varying levels of structure and admixture; these features are likely to induce heterogeneity of marker effects across subpopulations. Traditionally, structure has been dealt with as a potential confounder, and various methods exist to “correct” for population stratification. However, these methods induce a mean correction that does not account for heterogeneity of marker effects. The animal breeding literature offers a few recent studies that consider modeling genetic heterogeneity in multibreed data, using multivariate models. However, these methods have received little attention in plant breeding where population structure can have different forms. In this article we address the problem of analyzing data from heterogeneous plant breeding populations, using three approaches: (a) a model that ignores population structure [A-genome-based best linear unbiased prediction (A-GBLUP)], (b) a stratified (i.e., within-group) analysis (W-GBLUP), and (c) a multivariate approach that uses multigroup data and accounts for heterogeneity (MG-GBLUP). The performance of the three models was assessed on three different data sets: a diversity panel of rice (Oryza sativa), a maize (Zea mays L.) half-sib panel, and a wheat (Triticum aestivum L.) data set that originated from plant breeding programs. The estimated genomic correlations between subpopulations varied from null to moderate, depending on the genetic distance between subpopulations and traits. Our assessment of prediction accuracy features cases where ignoring population structure leads to a parsimonious more powerful model as well as others where the multivariate and stratified approaches have higher predictive power. In general, the multivariate approach appeared slightly more robust than either the A- or the W-GBLUP.     

The effects of thin layers on the vertical distribution of larval Pacific herring, Clupea pallasi

Temporal and spatial heterogeneity of resources is likely to have dramatic effects on the behaviors of zooplankton and ichthyoplankton, which in turn are likely to have strong effects on ecological dynamics such as predation, growth, and mating. The objective of this study was to determine whether vertically thin layers of extreme prey concentration affect the vertical distribution of larval Pacific herring (Clupea pallasi). We employed 2-m tall experimental tanks equipped with video cameras that scanned the vertical extent of the tanks to investigate the effects of thin layers on the vertical distribution of 5- and 10-day-old herring larvae. Three treatments were established: (1) a thin layer of prey (rotifers, Brachionus plicatilis) through density (salinity) stratification, (2) homogeneous vertical distribution of both prey and density, and (3) density (salinity) stratification, but with a homogeneous distribution of prey. We found that in all treatments the majority of larval herring were at the surface, near the light, despite the absence of a peak in rotifer abundance at this depth in some instances. However, there were also clear effects of the thin layers—secondary subsurface peaks in herring abundance occurred at the mid-depths in the stratified tanks, in and around the thin layers. In addition, our results provide some evidence that thin layers specifically, rather than prey patches generally, influence the vertical distribution of larval herring, i.e., larvae may use the physical properties of thin layers to locate and distribute themselves, instead of reacting solely to the prey patches. Thus thin layers can affect directly the vertical distribution of larval herring, and perhaps indirectly their horizontal distribution, as herring larvae live in environments (e.g., estuaries) where advective transport is also often vertically heterogeneous.     

生态空间理论与景观异质性

概述生态空间理论的若干主要方面：尺度、空间格局、景观异质性、镶嵌与生态交错带以及干扰与景观动态等。生态空间理论是景观评价,管理和生态规划的重要基础,对于区域可持续发展和生物多样性保护等方面的研究都具有重要的指导意义。