Colonisation of pitcher plant leaves at several spatial scales

Abstract.  1. The effect of meso-scale (zone within bog and local plant density) and fine-scale (leaf length and resource availability) factors on the colonisation of pitcher plant leaves by arthropods was examined in an eastern Canadian bog.
2. In spring, the abundances of three arthropods, the mosquito Wyeomyia smithii , the midge Metriocnemus knabi , and the mite Sarraceniopus gibsoni , were determined for plots with low, moderate, and high densities of pitcher plants. All overwintering inhabitants were then removed from the plots. Newly opening leaves were colonised from outside the plots, and arthropod abundances were assessed again in autumn.
3. Pitcher plant fauna varied in their response to the meso-scale factors. In autumn (soon after colonisation), midges were more abundant in areas with high densities of pitcher plants. The relationship between mosquito abundance and plant density, and the variation in abundance among zones within the bog in the spring, were probably due to overwintering mortality.
4. All taxa responded to the fine-scale factors, leaf length, and capture rate, in the autumn, but the strength of the responses frequently depended on a meso-scale factor (plant density), in which responses were usually strongest where plants were sparse. Thus, the interaction between meso- and fine-scale processes needs to be considered when interpreting patterns of species abundance within arthropod assemblages in pitcher plant leaves.     

Interference at several temporal and spatial scales between two chestnut insects

Detection of interspecific competition between insects is often sensitive to scaling. We give an example of scale-dependent interference between the weevil Curculio elephas and the moth Cydia splendana, which both have larvae that develop in the fruits of chestnut Castanea sativa. Measures at three scales were considered: chestnut, husk (with one to three fertile fruits) and tree. Data come from observations in the field over 14 years, complemented by experiments done directly in trees. Data on individual chestnut fruits revealed a marked statistical interference between the two insects. Experiments demonstrated that presence of a moth larva in a fruit usually inhibits weevil egg-laying. Conversely, weevil presence does not strongly modify moth larval behavior. Cases of double infestation often correspond to fruits first attacked by the weevil. With measures on husks, interference between the two insects was observed only in some trees; its intensity was always weaker than in the chestnuts themselves. At the scale of entire trees, rates of infestation by each insect are not correlated. Interference in chestnut fruits is interpreted by assuming that the weevil female either is sensitive to a repellent molecule originating from a moth larva or its frass, or can detect moth larval sounds. Mechanisms governing infestation rates from data per tree are discussed in relation to those found at fruit scale and to plant-insect interactions. The need to estimate available resources both from quantitative and qualitative points of view is emphasized.     

自然保护区空间特征和地块最优化选择方法

自然保护区是保护物种和生态系统的有效方式,用于建立自然保护区的资源却是稀缺的,这就提出这样的问题：1)自然保护区在空间上应具有什么特征才是有效的;2)如何从许多备选地块中选择一部分组成自然保护区对稀缺资源进行最优化分配。为促进物种生存繁衍,在地块选择时应考虑保护区空间特征。这篇文章综述了该领域最近的研究进展,重点介绍了结合各种空间特征的保护区地块最优化选择模型。介绍了4个主要的空间特征：1)连续,2)间隔和距离,3)边界和集约,4)面积以及核心区和缓冲区。以前用启发式算法求解这些问题,但研究已显示该法不能保证资源的最优化分配。空间特征也可用线性整数规划模拟,用最优化软件求得最优解。目前的线性整数规划模型和软件还不能有效解决大型的保护区地块选择问题,计算效率易成为实际应用的瓶颈。文章概括了我国目前自然保护区设计领域的研究状况和面临的问题,最后讨论了该领域新的研究方向。     

Hierarchical Bayesian methods estimate invasive weed impacts at pertinent spatial scales

Invasive weed impact estimates are needed to determine whether or not weeds warrant costly control measures. Typically, land managers seek local weed impact estimates (e.g. ranches, parks) and policy-makers want to know how weeds are impacting entire regions. Our goal was to provide local and regional impact estimates for a ubiquitous invasive weed: leafy spurge (Euphorbia esula L.). The specific impacts we looked at related to desired species biomass production, livestock carrying capacities, and grazing land values. Our basic approach was to use an empirical model that characterizes weed biomass across the landscape in combination with another empirical model that predicts weed impact from weed biomass. Our investigation revealed that, without on-site plant biomass data, site-specific leafy spurge impacts are highly uncertain. Supplementing our general predictive model with small quantities of on-site data increased precision considerably. For the 17-state region we considered, 95% Bayesian credibility intervals indicated leafy spurge reduces cattle carrying capacities by 50–217 thousand animals a year and reduces grazing land values by 8–34 million dollars a year. Additional plant biomass data from randomly selected, leafy spurge-infested sites would shrink these fairly wide intervals.     

Multiple scales and the relationship between density and spatial aggregation in littoral zone communities

Understanding the constraints on community composition at multiple spatial scales is an immense challenge to community and ecosystem ecologists. As community composition is basically the composite result of species’ spatial patterning, studying this spatial patterning across scales may yield clues as to which scales of environmental heterogeneity influence communities. The now widely documented positive interspecific relationship between ‘regional’ range and mean ‘local’ abundance has become a generalisation describing the spatial patterning of species at coarse scales. We address some of the shortcomings of this generalisation, as well as examine the cross‐scale spatial patterning (aggregation and density levels) of littoral‐benthic invertebrates in very large lakes. Specifically, we (a) determine whether the positive range‐abundance relationship can be reinterpreted in terms of the actual spatial structure of species distributions, (b) examine the relationship between aggregation and density across different spatial scales, and (c) determine whether the spatial patterning of species (e.g. low density/aggregated distribution) is constant across scales, that is, whether our interpretation of a species spatial pattern is dependent on the scale at which we choose to observe the system. Spatial aggregation of littoral invertebrates was generally a negative function of mean density across all spatial scales and seasons (autumn and spring). This relationship may underlie positive range‐abundance relationships. Species that were uncommon and highly aggregated at coarse spatial scales can be abundant and approach random distributions at finer spatial scales. Also, the change in spatial aggregation of closely related taxa across spatial scales was idiosyncratic. The idiosyncratic cross‐scale spatial patterning of species implies that multiple scales of environmental heterogeneity may influence the assembly of littoral communities. Due to the multi‐scale, species‐specific spatial patterning of invertebrates, littoral zone communities form a complex spatial mosaic, and a ‘spatially explicit’ approach will be required by limnologists in order to link littoral‐benthic community patterns with ecosystem processes in large oligotrophic lakes.     

Hyperparasitoid aggregation in response to variation in Aphidius ervi host density at three spatial scales

1. This article investigates the pattern of hyperparasitism of the host Aphidius ervi Haliday (Hymenoptera, Aphidiidae), a primary parasitoid of the pea aphid, Acyrthosiphon pisum (Harris) (Homoptera: Aphididae) at three spatial scales.
2. In the laboratory, the hyperparasitoid Asaphes lucens (Provancher) (Hymenoptera: Pteromalidae) was introduced into cages containing sixteen alfalfa plants with varying numbers of A. ervi mummies (the stage susceptible to hyperparasitism). The pattern of hyperparasitism at the end of the 48-h trials showed no density-dependent hyperparasitoid aggregation, although there was strong density-independent hyperparasitoid aggregation.
3. In the field, the density of A. ervi mummies was manipulated in twelve 2 × 2-m plots containing 1309–1654 alfalfa stems. Variation in hyperparasitism among plots showed no density-dependent aggregation, although there was strong density-independent aggregation.
4. Finally, at the largest scale of the study, the distribution of hyperparasitism was sampled among twelve alfalfa fields within a 5 × 3-km area. At this scale there was both density-dependent and density-independent hyperparasitoid aggregation.
5. The natural variation in A. ervi mummy density is greatest at the larger scales of study. Therefore, density-dependent hyperparasitism occurs only when there is high natural variation in mummy density.     

A review of delirium rating scales

Delirium is a severe psychiatric syndrome that is highly prevalent in elderly general hospital patients. However, the diagnosis of delirium is often missed. The use of rating scales can be helpful in detecting and measuring delirium symptom severity. This article reviews recent developments with regard to psychometric qualities, measurement goal, content and rating procedures of some of the available rating scales in clinical practise. Studies that used delirium rating scales were searched for using the MEDLINE and subsequent examination of reference lists. Ten rating scales were selected for further evaluation. The Confusional Assessment Method (CAM), NEECHAM Confusion Scale (NEECHAM) and Delirium Observation Scale (DOS) appear to be most suitable as a screening instrument, depending on the type of rater (physician or nurse). The (revised) Delirium Rating Scale (DRS(-R-98)) seems to be particularly useful for measuring delirium severity or monitoring change.     

Surveying carnivores at large spatial scales: a comparison of four broad-applied methods

Reliable methods to estimate species richness are very important to managers and conservationists because they provide key data to make the right decisions in conservation programmes. In the case of carnivore mammals, traditional methods, such as direct count censuses, are not useful since these animals are usually scarce, elusive and nocturnal. Difficulties in carnivore sampling are compounded when monitoring programmes are developed at large spatial scales, where high economic costs and field efforts are necessary to achieve reliable richness or abundance estimates. These problems have highlighted the need to find more effective carnivore survey methods, especially in regions with high rates of landscape change, such as the Mediterranean basin. The present study, performed in a typical Mediterranean area, was the first in Europe to test simultaneously the relative efficiencies of four broad-applied sampling methods to detect carnivore species at large spatial scales. Sign surveys based on scat detection, scent stations, camera-trapping and live-trapping were investigated. We compared efficiencies using biological parameters and by considering both the logistic and economic costs of each method. Overall, scent stations and sign surveys were the most efficient methods both in economic and logistic terms. In addition, the use of scent stations may be necessary to detect species rarely detected by scats. Detailed and extensive training programmes for conducting sign surveys and scent stations may overcome perceived problems thus enhancing the widespread use of both methods. Our results are applicable not only to other Mediterranean areas, but also to other habitats and regions of the world. More research into the suitability of these and other methods in relation to different landscapes, seasons and species is required.     

Approximate aggregation of a two time scales periodic multi-strain SIS epidemic model: A patchy environment with fast migrations

In this work we consider a spatially distributed periodic multi strain SIS epidemic model. We let susceptible and infected individuals migrate between patches, with periodic migration rates. Considering that migrations are much faster than the epidemic process, we build up a less dimensional (aggregated) system that allows to study some features of the asymptotic behavior of the original model. In particular, we are able to define global reproduction numbers in the non-spatialized aggregated system that serve to decide the eradication or endemicity of the epidemic in the initial spatially distributed nonautonomous model. Comparing these global reproductive numbers with those corresponding to isolated patches we show that adequate periodic fast migrations can in many cases reverse local endemicity and get global eradication of the epidemic.     

Long-term demographics of a coral-reef fish: growth,survival and abundance at several spatial scales

Coral Reefs - In marine organisms, pelagic larval dispersal often results in genetic panmixis among widely separated populations; however, local conditions may produce populations of marine...     

Positive effects of shrubs on herbaceous species richness across several spatial scales: evidence from the semiarid Andean subtropics

Question: What is the effect of shrubs on herbaceous species richness at three spatial scales: quadrat, site, and region? Location: Prepuna, subtropical semi‐arid Andes. Methods: At eight sites, we recorded the presence of herbaceous species in spaces beneath shrubs/small trees and in open areas. At the quadrat scale, the average species number per quadrat was calculated and compared between the two microhabitats (shrubs/open). At the local (site) scale, all quadrats of each site were pooled according to microhabitat, and all sites were then combined for the regional analysis. Results and conclusions: We found greater herbaceous species richness below shrubs at all three spatial scales considered. Several species were found exclusively associated with the shrub undercanopy. This effect seems to depend more on greater inventory diversity at the different scales than on greater differentiation diversity in the herbaceous communities associated with shrubs. Facilitation seems to be responsible for the increase of species richness beneath shrubs, but further experimental study is needed to obtain insight into the underlying mechanisms.     

Assessing temporal scales and patterns in time series: Comparing methods based on redundancy analysis

Time-series modelling techniques are powerful tools for studying temporal scaling structures and dynamics present in ecological and other complex systems and are gaining popularity for assessing resilience quantitatively. Among other methods, canonical ordinations based on redundancy analysis are increasingly used for determining temporal scaling patterns that are inherent in ecological data. However, modelling outcomes and thus inference about ecological dynamics and resilience may vary depending on the approaches used. In this study, we compare the statistical performance, logical consistency and information content of two approaches: (i) asymmetric eigenvector maps (AEM) that account for linear trends and (ii) symmetric distance-based Moran's eigenvector maps (MEM), which requires detrending of raw data to remove linear trends prior to analysis. Our comparison is done using long-term water quality data (25 years) from three Swedish lakes. This data set therefore provides the opportunity for assessing how the modelling approach used affects performance and inference in time series modelling. We found that AEM models had consistently more explanatory power than MEM, and in two out of three lakes AEM extracted one more temporal scale than MEM. The scale-specific patterns detected by AEM and MEM were uncorrelated. Also individual water quality variables explaining these patterns differed between methods, suggesting that inferences about systems dynamics are dependent on modelling approach. These findings suggest that AEM might be more suitable for assessing dynamics in time series analysis compared to MEM when temporal trends are relevant. The AEM approach is logically consistent with temporal autocorrelation where earlier conditions can influence later conditions but not vice versa. The symmetric MEM approach, which ignores the asymmetric nature of time, might be suitable for addressing specific questions about the importance of correlations in fluctuation patterns where there are no confounding elements of linear trends or a need to assess causality.     

The effect of travel time on oviposition behavior and spatial egg aggregation: experiments with Drosophila

A higher degree of spatial egg aggregation is often observed in environments where resource patches are more sparsely distributed. This suggests a higher probability of species coexistence when resource distribution is sparse. However, it is still unclear how the degree of spatial egg aggregation increases. I propose a model to explain this phenomenon, which assumes that (i) egg load (the number of mature eggs in ovaries) increases in the travel period between resource patches and (ii) the retention of eggs in the ovaries is harmful (egg load pressure). With these assumptions, a female would lay accumulated eggs on arrival at a new resource patch, resulting in a higher degree of spatial egg aggregation. Laboratory experiments with three drosophilid species, Drosophila simulans Surtevant, Drosophila auraria Peng, and Drosophila immigrans Sturtevant, support the model. This study provides evidence that host availability affects the spatial egg aggregation via egg load.     

How spatial and temporal scales influence understanding of Sperm Whale distribution: a review

For much of the past two centuries, sperm whaling has been economically very profitable, and therefore whalers and, more recently, scientists have tried to understand Sperm Whale ( Physeter macrocephalus ) distribution and the factors controlling it. However, due to their deep-living mode of life, their cosmopolitan distribution and our limited knowledge about their main prey species, the task has proved very difficult. This paper reviews studies of Sperm Whale distribution and the factors controlling it. The conclusions of these studies are very equivocal and often appear to contradict one another. It is suggested that this apparent confusion is mainly due to poorly defined spatial and temporal scales, the use of only one scale in most studies and the absence of consideration of the spatial and temporal scales at which relevant oceanographic processes occur. It is concluded that multiscale studies, covering the scales of oceanographic process, are needed to obtain a better understanding of Sperm Whale distribution.     

A review of methods for analysing spatial and temporal patterns in coastal water quality

Coastal environments contain some of the marine world's most important ecosystems and represent significant resources for human industry and recreation. Water quality in the coastal environment is extremely important for a number of reasons from the protection of marine organisms and the well being of marine ecosystems to the health of people in the region and the safety of industries such as aquaculture. As a result it is essential that environmental health in coastal environments is monitored. Traditional monitoring methods include assessment of biological indices or direct measurements of water quality, which are based on in situ data collection and hence are often spatially or temporally limited. Remote sensing imagery is increasingly used as a rich source of spatial information, providing more detailed coverage then other methods. But the complexity of information in the imagery requires new analysis techniques that allow us to identify the components and possible causes of spatial and temporal variability.This paper presents a review of methods to analyse spatial and temporal variations in remote sensing data of coastal water quality and discusses and compares these methods and the outcomes they achieve. Selected techniques are illustrated by using a sample dataset of MODIS chlorophyll-a imagery. We consider classification methods (cluster analysis, discriminant analysis) that may be used in exploratory, confirmatory and predictive ways, methods that summarize and identify patterns within complex datasets (factor analysis, principal components analysis, self-organizing maps), and techniques that explicitly analyse spatial relationships (the semivariogram and geographically weighted regression). Each technique has a different purpose and addresses different questions. This review identifies how these methods can be utilized to address water quality variability in order to foster a wider application of such techniques for coastal water quality assessment and monitoring.