高寒草甸植物群落中物种丰富度与生产力的关系研究

 以物种组成较为复杂的青藏高原东部地区典革高寒草甸植物群落为背景,从不同的时间和空间尺度水平研究了植物群落中物种丰富度与生产力（地上部生物量）关系的基本模式。结果表明：1）总体而言,高寒草甸植物群落中物种丰富度与生产力的关系呈对数线性增加关系,这实际上是空间和时间尺度放大时在时间和空间尺度的相互作用下高寒草甸植物群落中物种丰富度与生产力关系的一种总体模式;2）随着研究的时间和空间尺度的改变,物种丰富度与生产力的关系会发生一些相应的变化,但空间尺度比时间尺度对物种丰富度与生产力的关系造成的影响更为显著,这可能     

The sugarcane borer Diatraea saccharalis (Fabr.) (Lep., Crambidae) and its parasitoids: a synchrony approach to spatial and temporal dynamics

Abstract:  A data set on Diatraea saccharalis and its parasitoids, Cotesia flavipes and tachinid flies, was analysed at five spatial scales – sugarcane mill, region, intermediary, farm and zone – to determine the role of spatial scale in synchrony patterns, and on temporal population variability. To analyse synchrony patterns, only the three highest spatial scales were considered, but for temporal population variability, all spatial scales were adopted. The synchrony–distance relationship revealed complex spatial structures depending on both species and spatial scale. Temporal population variability [SD log( x  + 1)] levels were highest at the smallest spatial scales although, in the majority of the cases, temporal variability was inversely dependent on sample size. All the species studied, with a few exceptions, presented spatial synchrony independent of spatial scale. The tachinid flies exhibited stronger synchrony dynamics than D. saccharalis and C. flavipes in all spatial scales with the latter displaying the weakest synchrony levels, except when mill spatial scales were compared. In some cases spatial synchrony may at first decay and then increase with distance, but the presence of such patterns can change depending on the spatial scale adopted.     

Spatial and temporal variation of ecosystem properties at macroscales

Although spatial and temporal variation in ecological properties has been well‐studied, crucial knowledge gaps remain for studies conducted at macroscales and for ecosystem properties related to material and energy. We test four propositions of spatial and temporal variation in ecosystem properties within a macroscale (1000 km's) extent. We fit Bayesian hierarchical models to thousands of observations from over two decades to quantify four components of variation – spatial (local and regional) and temporal (local and coherent); and to model their drivers. We found strong support for three propositions: (1) spatial variation at local and regional scales are large and roughly equal, (2) annual temporal variation is mostly local rather than coherent, and, (3) spatial variation exceeds temporal variation. Our findings imply that predicting ecosystem responses to environmental changes at macroscales requires consideration of the dominant spatial signals at both local and regional scales that may overwhelm temporal signals.     

Frequency filter properties of lobster chemoreceptor cells determined with high-resolution stimulus measurement

1. We developed a high resolution, on-line stimulus measurement system for accurate control of chemical stimulus applications for Homarus americanus lateral antennule chemoreceptors. Focal stimulus presentations in an electrophysiological preparation with the receptor sensilla intact were measured at small spatial (30 μm) and time (5 ms) scales.
2. We tested 15 receptor cells with ten 100 ms pulses of 10⁴ M hydroxyproline at 0.5, 1, 2 and 4 Hz and with a single 8 s square pulse. Individual cells showed differences in their capabilities to resolve pulses (“flicker fusion”). At 2 Hz stimulation, some cells could follow stimulus pulses while others could not. At 4 Hz, 3 cells could still encode individual stimulus pulses accurately. The population resolved pulses up to 2 Hz; at 4 Hz, the population response to a pulse series approximated the response to a square pulse.
3. Repetitive stimulation caused a gradual decrease in the number of spikes and a gradual increase in first spike latency (“cumulative adaptation”). Increased stimulation frequency resulted in greater cumulative adaptation.
4. Since individual differences in adaptation and disadaptation rates of the receptor cells could not be attributed to measured stimulus variability in situ, lobster chemoreceptor cell populations have intrinsic temporal diversity which, we hypothesize, could be used to analyze pulsatile stimuli that occur in natural turbulent odor plumes.

     

Functional differences between summer and winter season rain assessed with MODIS‐derived phenology in a semi‐arid region

Questions: We asked several linked questions about phenology and precipitation relationships at local, landscape, and regional spatial scales within individual seasons, between seasons, and between year temporal scales. (1) How do winter and summer phenological patterns vary in response to total seasonal rainfall? (2) How are phenological rates affected by the previous season rainfall? (3) How does phenological variability differ at landscape and regional spatial scales and at season and inter‐annual temporal scales? Location: Southern Arizona, USA. Methods: We compared satellite‐derived phenological variation between 38 distinct 625‐km² landscapes distributed in the northern Sonoran Desert region from 2000 to 2007. Regression analyses were used to identify relationships between landscape phenology dynamics in response to precipitation variability across multiple spatial and temporal scales. Results: While both summer and winter seasons show increases of peak greenness and peak growth with more precipitation, the timing of peak growth was advanced with more precipitation in winter, while the timing of peak greenness was advanced with more precipitation in summer. Surprisingly, summer maximum growth was negatively affected by winter precipitation. The spatial variations between summer and winter phenology were similar in magnitude and response. Larger‐scale spatial and temporal variation showed strong differences in precipitation patterns; however the magnitudes of phenological spatial variability in these two seasons were similar. Conclusions: Vegetation patterns were clearly coupled to precipitation variability, with distinct responses at alternative spatial and temporal scales. Disaggregating vegetation into phenological variation, spanning value, timing, and integrated components revealed substantial complexity in precipitation‐phenological relationships.     

Spatio‐temporal variation in European starling reproductive success at multiple small spatial scales

Understanding population dynamics requires spatio‐temporal variation in demography to be measured across appropriate spatial and temporal scales. However, the most appropriate spatial scale(s) may not be obvious, few datasets cover sufficient time periods, and key demographic rates are often incompletely measured. Consequently, it is often assumed that demography will be spatially homogeneous within populations that lack obvious subdivision. Here, we quantify small‐scale spatial and temporal variation in a key demographic rate, reproductive success (RS), within an apparently contiguous population of European starlings. We used hierarchical cluster analysis to define spatial clusters of nest sites at multiple small spatial scales and long‐term data to test the hypothesis that small‐scale spatio‐temporal variation in RS occurred. RS was measured as the number of chicks alive ca. 12 days posthatch either per first brood or per nest site per breeding season (thereby incorporating multiple breeding attempts). First brood RS varied substantially among spatial clusters and years. Furthermore, the pattern of spatial variation was stable across years; some nest clusters consistently produced more chicks than others. Total seasonal RS also varied substantially among spatial clusters and years. However, the magnitude of variation was much larger and the pattern of spatial variation was no longer temporally consistent. Furthermore, the estimated magnitude of spatial variation in RS was greater at smaller spatial scales. We thereby demonstrate substantial spatial, temporal, and spatio‐temporal variation in RS occurring at very small spatial scales. We show that the estimated magnitude of this variation depended on spatial scale and that spatio‐temporal variation would not have been detected if season‐long RS had not been measured. Such small‐scale spatio‐temporal variation should be incorporated into empirical and theoretical treatments of population dynamics.     

Long-term temporal and spatial variation of macrobenthos in the intertidal soft-bottom flats of two small bights (Chupa Inlet, Kandalaksha Bay, White Sea)

Despite the dynamic nature of spatial pattern, the temporal variation of spatial structure of marine benthic assemblages is rarely assessed using several temporal scales. We quantified the variability of density and biomass of main benthic species in the intertidal soft-bottom flats at two bights in Chupa Inlet (Kandalaksha Bay, the White Sea). The data cover the 21-year period (1987–2008) of a long-term monitoring survey (1987–present) using a hierarchical sampling design with two temporal (year, season within a year) and three spatial scales (bights—7 km, stations within a bight—10–100 m, and replicate samples—10 s cm apart). We used nested ANOVA to test significance and variance components to compare the relative contribution of different scales of variability of density and biomass of 18 most occurring macrobenthic species. Some species demonstrated high large-scale variability, however, the majority showed high small-scale variability and residual variance. The interactive variability was at least as important as the temporal effects, indicating that the spatial pattern changes through time. The assemblages were more variable at small scales and more stable at larger scales. Potential implications for sampling design are discussed.     

Habitat selection by a large herbivore at multiple spatial and temporal scales is primarily governed by food resources

Habitat selection can be considered as a hierarchical process in which animals satisfy their habitat requirements at different ecological scales. Theory predicts that spatial and temporal scales should co‐vary in most ecological processes and that the most limiting factors should drive habitat selection at coarse ecological scales, but be less influential at finer scales. Using detailed location data on roe deer Capreolus capreolus inhabiting the Bavarian Forest National Park, Germany, we investigated habitat selection at several spatial and temporal scales. We tested 1) whether time‐varying patterns were governed by factors reported as having the largest effects on fitness, 2) whether the trade‐off between forage and predation risks differed among spatial and temporal scales and 3) if spatial and temporal scales are positively associated. We analysed the variation in habitat selection within the landscape and within home ranges at monthly intervals, with respect to land‐cover type and proxys of food and cover over seasonal and diurnal temporal scales. The fine‐scale temporal variation follows a nycthemeral cycle linked to diurnal variation in human disturbance. The large‐scale variation matches seasonal plant phenology, suggesting food resources being a greater limiting factor than lynx predation risk. The trade‐off between selection for food and cover was similar on seasonal and diurnal scale. Habitat selection at the different scales may be the consequence of the temporal variation and predictability of the limiting factors as much as its association with fitness. The landscape of fear might have less importance at the studied scale of habitat selection than generally accepted because of the predator hunting strategy. Finally, seasonal variation in habitat selection was similar at the large and small spatial scales, which may arise because of the marked philopatry of roe deer. The difference is supposed to be greater for wider ranging herbivores.     

How Entorhinal Grid Cells May Learn Multiple Spatial Scales from a Dorsoventral Gradient of Cell Response Rates in a Self-organizing Map

Place cells in the hippocampus of higher mammals are critical for spatial navigation. Recent modeling clarifies how this may be achieved by how grid cells in the medial entorhinal cortex (MEC) input to place cells. Grid cells exhibit hexagonal grid firing patterns across space in multiple spatial scales along the MEC dorsoventral axis. Signals from grid cells of multiple scales combine adaptively to activate place cells that represent much larger spaces than grid cells. But how do grid cells learn to fire at multiple positions that form a hexagonal grid, and with spatial scales that increase along the dorsoventral axis? In vitro recordings of medial entorhinal layer II stellate cells have revealed subthreshold membrane potential oscillations (MPOs) whose temporal periods, and time constants of excitatory postsynaptic potentials (EPSPs), both increase along this axis. Slower (faster) subthreshold MPOs and slower (faster) EPSPs correlate with larger (smaller) grid spacings and field widths. A self-organizing map neural model explains how the anatomical gradient of grid spatial scales can be learned by cells that respond more slowly along the gradient to their inputs from stripe cells of multiple scales, which perform linear velocity path integration. The model cells also exhibit MPO frequencies that covary with their response rates. The gradient in intrinsic rhythmicity is thus not compelling evidence for oscillatory interference as a mechanism of grid cell firing. A response rate gradient combined with input stripe cells that have normalized receptive fields can reproduce all known spatial and temporal properties of grid cells along the MEC dorsoventral axis. This spatial gradient mechanism is homologous to a gradient mechanism for temporal learning in the lateral entorhinal cortex and its hippocampal projections. Spatial and temporal representations may hereby arise from homologous mechanisms, thereby embodying a mechanistic “neural relativity” that may clarify how episodic memories are learned.     

Spatial and temporal factors affecting parasite genotypes encountered by hosts: Empirical data from American dog ticks (Dermacentor variabilis) parasitising raccoons (Procyon lotor)

The American dog tick (Dermacentor variabilis) is an important vector of numerous pathogens of humans and animals. In this study, we analysed population genetic patterns in D. variabilis at scales of the host individual (infrapopulation) and population (component population) to elucidate fine-scale spatial and temporal factors influencing transmission dynamics. We genotyped D. variabilis collected from raccoons (Procyon lotor) trapped in two habitat patches (located in Indiana, USA) which were spatially proximate (5.9 km) and limited in size (10.48 Ha and 25.47 Ha, respectively). Despite the fine spatial sampling scale, our analyses revealed significant genetic differentiation amongst component populations and infrapopulations (within each component population), indicating a non-random pattern of encountering tick genotypes by raccoons at both scales evaluated. We found evidence for male-biased dispersal in the ticks themselves (in one component population) and an age-bias in spatial scales at which raccoons encountered ticks in the environment. At the scale of the component population, our analyses revealed that raccoons encountered ticks from a limited number of D. variabilis family groups, likely due to high reproductive variance amongst individual ticks. Finally, we found evidence for a temporal effect with raccoons encountering ticks in the environment as “clumps” of related individuals. While the genetic structure of parasite populations are increasingly being investigated at small spatial scales (e.g. the infrapopulation), our data reveal that genetic structuring can originate at scales below that of the infrapopulation, due to the interaction between temporal and biological factors affecting the encounter of parasites by individual hosts. Ultimately, our data indicate that genetic structure in parasites must be viewed as a consequence of both spatial and temporal variance in host-parasite interactions, which in turn are driven by demographic factors related to both the host and parasite.     

Criticality and disturbance in spatial ecological systems

Classical criticality describes sudden changes in the state of a system when underlying processes change slightly. At this transition, patchiness develops which lacks a characteristic or dominant spatial scale. Thus, criticality lies at the interface of two important subjects in ecology, threshold behavior and patchiness. Most ecological examples of criticality involve processes of disturbance and recovery; the spatial and temporal scales of these processes enable three different types of critical system to be distinguished: classical phase transitions, self organized criticality (SOC) and 'robust' criticality. Here, we review the properties defining these three types and their implications for threshold behavior and large intermittent temporal fluctuations, with examples taken from spatial stochastic models for predator-prey, infected-susceptible, and disturbance-recovery interactions. In critical systems, spatial properties of patchiness alone are insufficient indicators of impending sudden changes, unless complemented by the spatial and temporal scales of disturbance and recovery themselves.     

The Effects of Incidentally Learned Temporal and Spatial Predictability on Response Times and Visual Fixations during Target Detection and Discrimination

Responses are quicker to predictable stimuli than if the time and place of appearance is uncertain. Studies that manipulate target predictability often involve overt cues to speed up response times. However, less is known about whether individuals will exhibit faster response times when target predictability is embedded within the inter-trial relationships. The current research examined the combined effects of spatial and temporal target predictability on reaction time (RT) and allocation of overt attention in a sustained attention task. Participants responded as quickly as possible to stimuli while their RT and eye movements were measured. Target temporal and spatial predictability were manipulated by altering the number of: 1) different time intervals between a response and the next target; and 2) possible spatial locations of the target. The effects of target predictability on target detection (Experiment 1) and target discrimination (Experiment 2) were tested. For both experiments, shorter RTs as target predictability increased across both space and time were found. In addition, the influences of spatial and temporal target predictability on RT and the overt allocation of attention were task dependent; suggesting that effective orienting of attention relies on both spatial and temporal predictability. These results indicate that stimulus predictability can be increased without overt cues and detected purely through inter-trial relationships over the course of repeated stimulus presentations.     

Complex role of predators in structuring soft-sediment macrobenthic communities: Implications of changes in spatial scale for experimental studies

In estuarine and coastal soft-sediment systems, the role that predators play in structuring communities appears to be variable. Attributes of a particular predator that influence its role in structuring the community include: the rate of prey consumption; the behaviour, morphology and mobility of the predator; and, in soft- sediment communities, sediment disturbances associated with feeding. Reviews of field experiments designed to assess the role of predators in influencing the structure and function of soft-sediment communities have concluded that many of the predators are generalists and there is usually a lack of competitive exclusion. Thus predation structures communities by many complex and indirect interactions that are often difficult to predict and generalize. Variations in the apparent strength and role of predation in structuring benthic communities may depend on a variety of ecosystem characteristics and/or aspects of study design. In this paper, I consider whether we have been conducting our experiments at the appropriate scales. Five case studies from Manukau Harbour (New Zealand) illustrate how small changes in the spatial scale can affect results, due to predator perceptions and prey mobility. The results of these studies demonstrate the need to identify scales at which predator effects are likely to be important and to fit experiments within the dynamics and heterogeneity of the system being studied. To do this, we need basic information on the natural history, behaviour and spatial and temporal variability of both predators and prey communities. We also need to be specific about scales of measurement when matching theoretical predictions to field observations/experiments. Finally, to enhance our ability to generalize from specific studies, we need to gather data that will enable us to both predict and test the importance of predation over a range of spatial and temporal scales.     

Small-scale spatial variability in intertidal and subtidal turfing algal assemblages and the temporal generality of these patterns

Spatial and temporal variation in patterns of distribution and abundance of algal assemblages is large and often occurs at extremely small spatial and temporal scales. Despite this, few studies investigate interactions between these scales, that is, how patterns of spatial variation change through time. This study investigated a number of scales of spatial variation (from tens of centimetres to kilometres) in assemblages of intertidal and subtidal turfing algae. Significant differences were found in the composition and abundances of species in assemblages of turf at all spatial scales tested. Much of the variation among assemblages could, however, be explained at the scale of quadrats (tens of centimetres apart) (27±1.4 (SE)% of dissimilarity) with an additional 7±1.2% explained at the scale of sites (tens of metres apart) and 10±1.5% at the scale of locations (kilometres apart). Although the greatest dissimilarity in assemblages occurred at the scale of habitats, this accounted for a relatively small proportion of the overall variation in assemblages. These patterns were consistent through time, that is, at each sampling time the spatial scale explaining the greatest proportion of variation in assemblages was replicate quadrats separated by tens of centimetres. These patterns appear to be due to small-scale variation in patterns of distribution and abundances of the individual species that comprise turfing algal assemblages. The results of this experiment suggest that large scale processes have less effect on patterns of variability of algal assemblages than those occurring on relatively smaller spatial scales and that small-scale spatial variation should not be considered as simply “noise”.     

Multiscale monitoring of a multispecies case study: two grass species at Sevilleta

Monitoring multiple species and their interactions at multiple scales is critical for any useful habitat conservation plans and for adaptive ecosystem management programs. Viability of single species can be understood only in the context of ecological interactions with other species at multiple spatial and temporal scales. Here, we present a case study of the spatial and temporal dynamics for two perennial grasses, Bouteloua eriopoda and B. gracilis, by using long-term, high resolution transect data from 1989 to 1998 at two sites in the Sevilleta National Wildlife Refuge (Deep Well and Five Points) in central New Mexico, USA. Information entropy was used to describe the spatial distribution of each species and the fractal dimension of information entropy was used to characterize the complexity of species dynamics across scales. When considered individually, the spatial distribution of each species was scale-invariant. However, species joint occurrences changed as scale of resolution increased at both sites. Interactions changed at scales less than 3.2 m at Deep Well and less than 1.6 m at Five Points. Across years, the interactions of these species at Deep Well were significantly different in 1989 from all other years. Our results argue that monitoring multiple species at multiple spatial and temporal scales is necessary to better understand multispecies interactions and community dynamics both of which have important conservation implications under changing environmental conditions.     

Scale-dependent spatial variance patterns and correlations of seabirds and prey in the southeastern Bering Sea as revealed by spectral analysis

Uni- and bivariate spectral analyses of the spatial distribution of thick-billed murres Uria lomvia and acoustic estimates of prey biomass in the southeastern Bering Sea were used to examine the spatial variance patterns of a predator and its prey at multiple spatial scales. Power, phase and coherency spectra from individual transects, as well as those averaged over all transects, were examined. The average spectra, representing a temporal scale of months, showed that murres and prey had similar spatial variance patterns and were positively correlated over the range of spatial scales studied. The individual spectra, representing a temporal scale of hours, showed several patterns that were not evident in the average spectra. In particular, the transect-level analyses showed that the correlation between murres and prey was poor at spatial scales where prey variance was relatively low. This result suggests a new hypothesis to explain poor small-scale correlations between consumers and resources: resource distribution is relatively uniform at small scales resulting in only a slight increase in foraging return for consumers showing an aggregative response at these scales. The differences among spatial scales and between the average and individual spectra illustrate how ecological patterns can vary with temporal and spatial scale.     

Normal variability of the amplitude and phase of steady-state VEPs

The present study quantifies the amplitude and phase variability of steady-state VEPs (S-VEPs) and compares this variability between subjects and between individual runs. The S-VEPs were recorded repeatedly in 14 normal subjects with varying spatial and temporal frequencies of sinusoidal gratings; 6 spatial frequencies (range 0.5–8.0 c/deg) with 3 temporal frequencies (4, 6 and 8 Hz) were used. A total of 75 responses were averaged and analyzed by the Fourier method. Four recordings were obtained in each spatio-temporal combination.In general, the phase data showed small inter- and intrasubject variability. As anticipated, the amplitude data showed a large degree of intersubject variability, although the intrasubject variability was very small. In addition, in some stimulus conditions the inter- and intrasubject variability increased, which thus suggested the existence of an optimal spatio-temporal combination. Therefore, these stimulus parameters should be taken into consideration when S-VEPs are applied in clinical practice.     

Effects of stimulus transformations on estimates of sensory neuron selectivity

Stimulus selectivity of sensory systems is often characterized by analyzing response-conditioned stimulus ensembles. However, in many cases these response-triggered stimulus sets have structure that is more complex than assumed. If not taken into account, when present it will bias the estimates of many simple statistics, and distort the estimated stimulus selectivity of a neural sensory system. We present an approach that mitigates these problems by modeling some of the response-conditioned stimulus structure as being generated by a set of transformations acting on a simple stimulus distribution. This approach corrects the estimates of key statistics and counters biases introduced by the transformations. In cases involving temporal spike jitter or spatial jitter of images, the main observed effects of transformations are blurring of the conditional mean and introduction of artefacts in the spectral decomposition of the conditional covariance matrix. We illustrate this approach by analyzing and correcting a set of model stimuli perturbed by temporal and spatial jitter. We apply the approach to neurophysiological data from the cricket cercal sensory system to correct the effects of temporal jitter. Action Editor: Matthew Wiener     

A multi-scale comparison of trait linkages to environmental and spatial variables in fish communities across a large freshwater lake

Species present in communities are affected by the prevailing environmental conditions, and the traits that these species display may be sensitive indicators of community responses to environmental change. However, interpretation of community responses may be confounded by environmental variation at different spatial scales. Using a hierarchical approach, we assessed the spatial and temporal variation of traits in coastal fish communities in Lake Huron over a 5-year time period (2001–2005) in response to biotic and abiotic environmental factors. The association of environmental and spatial variables with trophic, life-history, and thermal traits at two spatial scales (regional basin-scale, local site-scale) was quantified using multivariate statistics and variation partitioning. We defined these two scales (regional, local) on which to measure variation and then applied this measurement framework identically in all 5 study years. With this framework, we found that there was no change in the spatial scales of fish community traits over the course of the study, although there were small inter-annual shifts in the importance of regional basin- and local site-scale variables in determining community trait composition (e.g., life-history, trophic, and thermal). The overriding effects of regional-scale variables may be related to inter-annual variation in average summer temperature. Additionally, drivers of fish community traits were highly variable among study years, with some years dominated by environmental variation and others dominated by spatially structured variation. The influence of spatial factors on trait composition was dynamic, which suggests that spatial patterns in fish communities over large landscapes are transient. Air temperature and vegetation were significant variables in most years, underscoring the importance of future climate change and shoreline development as drivers of fish community structure. Overall, a trait-based hierarchical framework may be a useful conservation tool, as it highlights the multi-scaled interactive effect of variables over a large landscape.