Within-Otolith Variability in Chemical Fingerprints: Implications for Sampling Designs and Possible Environmental Interpretation

Largely used as a natural biological tag in studies of dispersal/connectivity of fish, otolith elemental fingerprinting is usually analyzed by laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS). LA-ICP-MS produces an elemental fingerprint at a discrete time-point in the life of a fish and can generate data on within-otolith variability of that fingerprint. The presence of within-otolith variability has been previously acknowledged but not incorporated into experimental designs on the presumed, but untested, grounds of both its negligibility compared to among-otolith variability and of spatial autocorrelation among multiple ablations within an otolith. Here, using a hierarchical sampling design of spatial variation at multiple scales in otolith chemical fingerprints for two Mediterranean coastal fishes, we explore: 1) whether multiple ablations within an otolith can be used as independent replicates for significance tests among otoliths, and 2) the implications of incorporating within-otolith variability when assessing spatial variability in otolith chemistry at a hierarchy of spatial scales (different fish, from different sites, at different locations on the Apulian Adriatic coast). We find that multiple ablations along the same daily rings do not necessarily exhibit spatial dependency within the otolith and can be used to estimate residual variability in a hierarchical sampling design. Inclusion of within-otolith measurements reveals that individuals at the same site can show significant variability in elemental uptake. Within-otolith variability examined across the spatial hierarchy identifies differences between the two fish species investigated, and this finding leads to discussion of the potential for within-otolith variability to be used as a marker for fish exposure to stressful conditions. We also demonstrate that a ‘cost’-optimal allocation of sampling effort should typically include some level of within-otolith replication in the experimental design. Our findings provide novel evidence to aid the design of future sampling programs and improve our general understanding of the mechanisms regulating elemental fingerprints.     

The importance of temporal climate variability for spatial patterns in plant diversity

Spatial variation in absolute climatic conditions (means, maxima or minima) is widely acknowledged to play a fundamental role in controlling species diversity patterns. In contrast, while evidence is accumulating that variability around mean climatic conditions may also influence species coexistence and persistence, the importance of spatial variation in temporal climatic variability for species diversity is still largely unknown. We used a unique dataset capturing fine‐scale spatial heterogeneity in temperature variability across 2490 plots in southeast Australia to examine the comparative strength of absolute temperature and temperature variability in explaining spatial variation in plant diversity. Across all plots combined and in three of five forest types, temperature variability emerged as the better predictor of diversity. In all but one forest type, diversity also exhibited either a significant unimodal or positive linear correlation with temperature variability. This relationship is consistent with theory that predicts diversity will initially increase along a climate variability gradient due to temporal niche partitioning, but at an intermediary point, may decline as the risk of stochastic extinction exceeds competitive stabilization. These findings provide critical empirical evidence of a linkage between spatial variation in temporal climate variability and plant species diversity, and in light of changing climate variability regimes, highlight the need for ecologists to expand their purview beyond absolutes and averages.     

Does biodiversity increase spatial stability in plant community biomass?

We tested the hypothesis that biodiversity decreases the spatial variability of biomass production between subplots taken within experimental grassland plots. Our findings supported this hypothesis if functional diversity (weighted Rao's Q ) was considered. Further analyses revealed that diversity in rooting depth and clonal growth form were the most important components of functional diversity stabilizing productivity. Using species or functional group richness as diversity measures there was no significant effect on spatial variability of biomass production, demonstrating the importance of the biodiversity component considered. Moreover, we found a significant increase in spatial variability of productivity with decreasing size of harvested area, suggesting small-scale heterogeneity as an important driver. The ability of diverse communities to stabilize biomass production across spatial heterogeneity may be due to complementary use of spatial niches. Nevertheless, the positive effect of functional diversity on spatial stability appears to be less pronounced than previously reported effects on temporal stability.     

Pink landscapes: 1/f spectra of spatial environmental variability and bird community composition

Temporal and spatial environmental variability are predicted to have reddened spectra that reveal increases in variance with the period or length sampled. However, spectral analyses have seldom been performed on ecological data to determine whether these predictions hold true in the case of spatial environmental variability. For a 50 km long continuous transect of 128 point samples across a heterogeneous cultural landscape in the Czech Republic, both habitat composition and bird species composition decomposed by standard ordination techniques did indeed exhibit reddened spectra. The values of main ordination axes have relationships between log spectral density and log frequency with slopes close to -1, indicating 1/f, or 'pink' noise type of variability that is characterized by scale invariance. However, when habitat composition was controlled for and only residuals for bird species composition were analysed, the spectra revealed a peak at intermediate frequencies, indicating that population processes that structure bird communities but are not directly related to the structure of the environment might have some typical correlation length. Spatial variability of abundances of individual species was mostly reddened as well, but the degree was positively correlated to their total abundance and niche position (strength of species-habitat association). If 'pink' noise type of variability is as generally typical for spatial environmental variability as for temporal variability, the consequences may be profound for patterns of species diversity on different spatial scales, the form of species-area relationships and the distribution of abundances within species ranges.     

Spatial Distribution of a Large Herbivore Community at Waterholes: An Assessment of Its Stability over Years in Hwange National Park,Zimbabwe

The spatial structuring of populations or communities is an important driver of their functioning and their influence on ecosystems. Identifying the (in)stability of the spatial structure of populations is a first step towards understanding the underlying causes of these structures. Here we studied the relative importance of spatial vs. interannual variability in explaining the patterns of abundance of a large herbivore community (8 species) at waterholes in Hwange National Park (Zimbabwe). We analyzed census data collected over 13 years using multivariate methods. Our results showed that variability in the census data was mostly explained by the spatial structure of the community, as some waterholes had consistently greater herbivore abundance than others. Some temporal variability probably linked to Park-scale migration dependent on annual rainfall was noticeable, however. Once this was accounted for, little temporal variability remained to be explained, suggesting that other factors affecting herbivore abundance over time had a negligible effect at the scale of the study. The extent of spatial and temporal variability in census data was also measured for each species. This study could help in projecting the consequences of surface water management, and more generally presents a methodological framework to simultaneously address the relative importance of spatial vs. temporal effects in driving the distribution of organisms across landscapes.     

Temporal and spatial environmental variability in the Upper Rhône River and its floodplain

• 1 This paper develops a framework of spatial and temporal variability for a habitat typology of the Upper Rhône River (France) and its alluvial floodplain that is based on about 17 years of data collection and analysis. The aim was to provide a scale of spatial-temporal variability for river habitat templet predictions on trends in species traits and species richness.
• 2 In developing this framework, eight physical-chemical variables were available and could be considered for twenty-two habitat types: seventeen superficial (surface) and five interstitial (0.5 m below the substrate surface). These habitat types were selected in two areas (Jons and Brégnier-Cordon) after geomorphological considerations and because of differences in their biological characteristics.
• 3 The data sets used were processed by a ‘fuzzy coding’ method using, for each variable, the frequency distribution (by modalities = categories) of all measurements and monthly means over an annual scale. Two tables were produced; the first corresponded to an expression of the total variability, and the second represented an evaluation of the temporal variability.
• 4 Each of these tables was analysed by correspondence analysis, which provided factorial scores that were used to calculate, by habitat type and by variable, a total variability and a temporal variability in terms of cumulated variability of factorial scores for the eight physical–chemical variables. The rationale in describing variability from these two tables is that total variability equals temporal variability plus spatial variability. The spatial variability was then determined by the difference between total and temporal variability. From this procedure, a positioning of the twenty-two habitat types on the spatial and temporal variability axes was obtained.
• 5 The estimate of spatial variability did not consider any error term that may have occurred in the above model; it was then tested by an independent assessment of the spatial variability using thirteen variables in nine major habitat types. A high correlation between the two ways of assessing spatial variability (r = 0.85, P < 0.004) underscored the reliability of the spatial variability that was calculated previously.
• 6 The river habitat templet obtained for the Upper Rhône and its alluvial floodplain appears to be appropriate to test the predictions on patterns of species traits and species richness in the framework of spatial and temporal variability.

     

插值方法与样点数对县域土壤有效磷空间变异特征评价的影响

与欧美大规模农场经营不同,土地分散经营使我国县域土壤养分空间变异特征评价更加困难.本研究以安徽芜湖土壤有效磷为例,系统地评价插值方法与样点数对县域土壤养分空间变异特征评价准确性的影响.结果表明：局部多项式、普通克里格、简单克里格和析取克里格插值方法的评价效果优于反距离加权法、全局多项式、径向基插值和泛克里格等插值方法,考虑到实际操作简单,推荐用普通克里格方法进行县域土壤有效磷空间变异特征评价.随着参与空间插值样点数的增加,县域土壤有效磷空间变异特征预测的准确性增加,充分考虑评价的准确性和田间取样费用,建议县域土壤有效磷空间变异特征评价的适宜样点数应介于500～1000个.     

荒漠人工固沙植被区土壤水分的时空变异性

表层土壤水分具有高度的时间和空间变异性.研究的目的:(1)揭示沙坡头人工固沙植被区浅层土壤水分的时空变异性特征;(2)确定驱动土壤水分变异的主要环境因子.在人工固沙植被区内一个4500m2的网格样地上每隔10m设置取样点,在连续7个月的时间内 (2005年4～10月),每隔15d用时域反射仪测量各样点表层以下15cm和30cm深度的土壤容积含水量.结果表明,该区网格尺度上浅层土壤水分的分布具有明显的空间变异性,其变异性随着土壤水分含量的降低而减小;相对海拔是驱动土壤水分空间变异的主要环境因子,其作用在降雨后尤为显著,且其对土壤下层的影响比上层更明显;植被和土壤水分含量的相关性时间序列与相对海拔一致--降雨使其相关性增加;土壤质地(土壤粒径分布)和土壤水分含量的相关性时间序列特征与植被和相对海拔相反,且其对土壤上层的影响比下层更明显.因此,在沙坡头荒漠人工固沙植被区,降雨后的短暂湿润期,地形和植被是驱动浅层土壤水分变异的主要影响因子,而随着降雨之后土壤逐渐变干,土壤质地的影响变得更加明显.     

Temporal and spatial variability in soil food web structure

Heterogeneity is a prominent feature of most ecosystems. As a result of environmental heterogeneity the distribution of many soil organisms shows a temporal as well as horizontal and vertical spatial patterning. In spite of this, food webs are usually portrayed as static networks with highly aggregated trophic groups over broader scales of time and space. The variability in food web structure and its consequences have seldom been examined. Using data from a Scots pine forest soil in the Netherlands, we explored (1) the temporal and spatial variability of a detrital food web and its components, (2) the effect of taxonomic resolution on the perception of variability over time and across space, and (3) the importance of organic matter quality as an explanatory factor for variability in food web composition. Compositional variability, expressed using the Bray‐Curtis similarity index, was measured over 2.5 years using a stratified litterbag design with three organic horizons per litterbag set. Variability in community composition and organic matter degradation increased over time in the litter horizon only. Seasonal variation in community composition was larger than variation between samples from the same season in different years. Horizontal spatial variability in community composition and organic matter degradation was relatively low, with no increase in variability with increasing distance between samples. Vertically, communities and organic matter degradation was more different between the non‐adjacent litter and humus horizons than between adjacent layers. These findings imply that soil food webs, at least in temperate forest plantations, are more variable than is currently appreciated in experiments and model studies, and that organic matter turnover might be an important factor explaining variability in community composition. Species composition was more variable than functional group composition, which implies that aggregated food webs will seem less sensitive to local temporal and spatial changes than they in fact are.     

Spatial variability in intertidal macroalgal assemblages on the North Portuguese coast: consistence between species and functional group approaches

Natural assemblages are variable in space and time; therefore, quantification of their variability is imperative to identify relevant scales for investigating natural or anthropogenic processes shaping these assemblages. We studied the variability of intertidal macroalgal assemblages on the North Portuguese coast, considering three spatial scales (from metres to 10 s of kilometres) following a hierarchical design. We tested the hypotheses that (1) spatial pattern will be invariant at all the studied scales and (2) spatial variability of macroalgal assemblages obtained by using species will be consistent with that obtained using functional groups. This was done considering as univariate variables: total biomass and number of taxa as well as biomass of the most important species and functional groups and as multivariate variables the structure of macroalgal assemblages, both considering species and functional groups. Most of the univariate results confirmed the first hypothesis except for the total number of taxa and foliose macroalgae that showed significant variability at the scale of site and area, respectively. In contrast, when multivariate patterns were examined, the first hypothesis was rejected except at the scale of 10 s of kilometres. Both uni- and multivariate results indicated that variation was larger at the smallest scale, and thus, small-scale processes seem to have more effect on spatial variability patterns. Macroalgal assemblages, both considering species and functional groups as surrogate, showed consistent spatial patterns, and therefore, the second hypothesis was confirmed. Consequently, functional groups may be considered a reliable biological surrogate to study changes on macroalgal assemblages at least along the investigated Portuguese coastline.     

Stability and synchrony across ecological hierarchies in heterogeneous metacommunities: linking theory to data

Understanding stability across ecological hierarchies is critical for landscape management in a changing world. Recent studies showed that synchrony among lower‐level components is key to scaling temporal stability across two hierarchical levels, whether spatial or organizational. But an extended framework that integrates both spatial scale and organizational level simultaneously is required to clarify the sources of ecosystem stability at large scales. However, such an extension is far from trivial when taking into account the spatial heterogeneities in real‐world ecosystems. In this paper, we develop a partitioning framework that bridges variability and synchrony measures across spatial scales and organizational levels in heterogeneous metacommunities. In this framework, metacommunity variability is expressed as the product of local‐scale population variability and two synchrony indices that capture the temporal coherence across species and space, respectively. We develop an R function ‘var.partition’ and apply it to five types of desert plant communities to illustrate our framework and test how diversity shapes synchrony and variability at different hierarchical levels. As the observation scale increased from local populations to metacommunities, the temporal variability of plant productivity was reduced mainly by factors that decreased species synchrony. Species synchrony decreased from local to regional scales, and spatial synchrony decreased from species to community levels. Local and regional species diversity were key factors that reduced species synchrony at the two scales. Moreover, beta diversity contributed to decreasing spatial synchrony among communities. We conclude that our new framework offers a valuable toolbox for future empirical studies to disentangle the mechanisms and pathways by which ecological factors influence stability at large scales.     

Characterising the temporal variability of the spatial distribution of animals: an application to seabirds at sea

Understanding the patterns of spatial and temporal variations in animal abundance is a fundamental question in ecology. Here, we propose a method to quantify temporal variations in animal spatial patterns and to determine the spatial scale at which such temporal variability is expressed. The methodology extends from the approach proposed by Taylor (Taylor, L. R. 1961. Aggregation, variance and the mean. Nature 189: 732–735) and relies on models of the relationship between temporal mean and variance in animal abundance. Repeated observations of the spatial distribution of populations are used to construct spatially explicit models of Taylor's power law. The resulting slope parameters of the Taylor power law provide local measures of the temporal variability in animal abundance. We investigate if the value of the slope varies significantly with spatial location and with spatial scale. The method is applied to seabirds distribution in the Bay of Biscay. We study four taxa (northern gannets, large gulls, auks and kittiwakes) that display distinct geographical distribution, spatial structure and foraging strategy. Our results show that the temporal variability associated to the spatial distribution of northern gannets is high and spatially homogeneous. By contrast, kittiwakes present large geographical areas associated with high and low variability. The temporal variability of auk's spatial distribution is strongly scale-dependent: at fine scale high variability is associated to high abundance, but at large scale high variability is associated to the external border of their distribution range. The method provides satisfactory results and useful information on species spatio-temporal distribution.     

Spatial and temporal variability in a butterfly population

Summary The dynamics of a butterfly (Plebejus argus) population were analysed at two levels, (i) the population as a whole and (ii) sections within the population. Some sections of the population fluctuated out of synchrony with others, such that the variability [SD Log(Density+1)] shown by the population as a whole was less than the variability shown by each part of the population — overall temporal variability was dampened by spatial asynchrony. Since observed population variability depends on the spatial scale that is sampled, comparisons of population variability among taxa should be carried out only with caution. Implications for island biogeography and conservation biology are discussed.     

Spatial coherence and stationarity of local field potentials in an isolated whole hippocampal preparation <Emphasis Type="Italic">in vitro</Emphasis>

Local field potential (LFP) multielectrode recordings of spontaneous rhythms in an isolated whole hippocampal preparation are characterized with respect to their spatial variability within the hippocampus, and their frequency properties. Using simulated data, we categorize potential relationships between frequency variation over time in LFP recordings and spatial variability between electrodes. We then use data recorded from the intact preparation to distinguish between our theoretical categories. We find that the LFP recordings have a close to spatially invariant frequency distribution (not phase) across the hippocampus, and differ in frequency only in a component that may be seen as physiological noise. From these facts, we conclude that the isolated hippocampal LFP recordings represent a single signal and may be regarded as a unitary circuitry. We additionally examine phase differences across our recording sites. We use our characterization of the hippocampal isolate’s properties to predict its spatial coherence in response to high frequency stimulation. We find that there is a finely tuned inverse relationship between temporal variability in the hippocampal isolate’s LFP recordings and their spatial coherence.     

Effects of black mustard population size on the taxonomic composition of pollinators

In plant species that are pollinated by a variety of animal species, spatial and temporal variability in the taxonomic composition of those pollinators may cause spatial and temporal variability in selection on floral traits. While temporal variation in pollinator composition has been widely reported, spatial variability, particularly on a local scale, has been studied less frequently; nevertheless, available evidence suggests that local spatial variability may be a widespread feature of plant-pollinator interactions. In addition, the causes of this spatial variability are poorly known. This study was undertaken to quantify variability in the taxonomic composition of pollinators visiting local populations of black mustard, Brassica nigra, and to determine some of the causes of this variability. Simultaneous observations were conducted in seven pairs of black mustard populations. The members of each pair were in close spatial proximity but differed in number of plants. Larger plant populations were visited by significantly greater numbers of honey bees and significantly fewer small bees than small populations on a per-plant basis. There was also a trend toward greater syrphid fly visitation in small populations. The increased numbers of honey bees at large plant populations is probably due to their ability to recruit long distances to the most rewarding plant populations. The lower number of small bees at large plant populations may be due to competition from honey bees and/or spreading a constant number of small bees over the larger number of plants in large populations.This paper is dedicated to the memory of George Eickwort     

哺乳动物种群系统时空变异性透视

综述了数学和统计学对哺乳动物种群系统生态学过程与环境随机过程交互作用的研究进展,以及种群波动同步性的Moran原理及效应。自然种群最普遍的现象是其数量在时间和空间上的变异性。在不同种群之间,种群大小的波动方式存在显著的差异。阐明和理解这种差异,探讨其随环境条件而改变的潜在规律,是种群和群落生态学的主要挑战之一。种群变异性存在空间分量,在相对大的距离内,种群的波动常同步发生。对种群内部密度制约过程与诸如环境变异性等外部因子交互作用的检验正在成为哺乳动物种群系统生态学领域关注的论题。     

Fine-Scale Distribution and Spatial Variability of Benthic Invertebrate Larvae in an Open Coastal Embayment in Nova Scotia,Canada

This study quantified the fine- scale (0.5 km) of variability in the horizontal distributions of benthic invertebrate larvae and related this variability to that in physical and biological variables, such as density, temperature, salinity, fluorescence and current velocity. Larvae were sampled in contiguous 500-m transects along two perpendicular 10-km transects with a 200-µm plankton ring net (0.75-m diameter) in St. George’s Bay, Nova Scotia, Canada, in Aug 2009. Temperature, conductivity, pressure and fluorescence were measured with a CTD cast at each station, and currents were measured with an Acoustic Doppler Current Profiler moored at the intersection of the 2 transects. Gastropod, bivalve and, to a lesser extent, bryozoan larvae had very similar spatial distributions, but the distribution of decapod larvae had a different pattern. These findings suggest that taxonomic groups with functionally similar larvae have similar dispersive properties such as distribution and spatial variability, while the opposite is true for groups with functionally dissimilar larvae. The spatial variability in larval distributions was anisotropic and matched the temporal/spatial variability in the current velocity. We postulate that in a system with no strong oceanographic features, the scale of spatially coherent physical forcing (e.g. tidal periodicity) can regulate the formation or maintenance of larval patches; however, swimming ability may modulate it.     

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.     

The Trade-Off between Spatial and Temporal Variabilities in Reciprocal Upper-Limb Aiming Movements of Different Durations

The spatial and temporal aspects of movement variability have typically been studied separately. As a result the relationship between spatial and temporal variabilities remains largely unknown. In two experiments we examined the evolution and covariation of spatial and temporal variabilities over variations in the duration of reciprocal aiming movements. Experiments differed in settings: In Experiment 1 participants moved unperturbed whereas in Experiment 2 they were confronted with an elastic force field. Different movement durations—for a constant inter-target distance—were either evoked by imposing spatial accuracy constraints while requiring participants to move as fast as possible, or prescribed by means of an auditory metronome while requiring participants to maximize spatial accuracy. Analyses focused on absolute and relative variabilities, respectively captured by the standard deviation (SD) and the coefficient of variation (CV = SD/mean). Spatial variability (both SDspace and CVspace) decreased with movement duration, while temporal variability (both SDtime and CVtime) increased with movement duration. We found strong negative correlations between spatial and temporal variabilities over variations in movement duration, whether the variability examined was absolute or relative. These findings observed at the level of the full movement contrasted with the findings observed at the level of the separate acceleration and deceleration phases of movement. During the separate acceleration and deceleration phases both spatial and temporal variabilities (SD and CV) were found to increase with their respective durations, leading to positive correlations between them. Moreover, variability was generally larger at the level of the constituent movement phases than at the level of the full movement. The general pattern of results was robust, as it emerged in both tasks in each of the two experiments. We conclude that feedback mechanisms operating to maximize task performance are subjected to a form of competition between spatial and temporal variabilities.     

Phosphorus in agricultural soils: drivers of its distribution at the global scale

Phosphorus (P) availability in soils limits crop yields in many regions of the World, while excess of soil P triggers aquatic eutrophication in other regions. Numerous processes drive the global spatial distribution of P in agricultural soils, but their relative roles remain unclear. Here, we combined several global data sets describing these drivers with a soil P dynamics model to simulate the distribution of P in agricultural soils and to assess the contributions of the different drivers at the global scale. We analysed both the labile inorganic P (P_ILAB), a proxy of the pool involved in plant nutrition and the total soil P (P_TOT). We found that the soil biogeochemical background corresponding to P inherited from natural soils at the conversion to agriculture (BIOG) and farming practices (FARM) were the main drivers of the spatial variability in cropland soil P content but that their contribution varied between P_TOT vs. P_ILAB. When the spatial variability was computed between grid cells at half‐degree resolution, we found that almost all of the P_TOT spatial variability could be explained by BIOG, while BIOG and FARM explained 38% and 63% of P_ILAB spatial variability, respectively. Our work also showed that the driver contribution was sensitive to the spatial scale characterizing the variability (grid cell vs. continent) and to the region of interest (global vs. tropics for instance). In particular, the heterogeneity of farming practices between continents was large enough to make FARM contribute to the variability in P_TOT at that scale. We thus demonstrated how the different drivers were combined to explain the global distribution of agricultural soil P. Our study is also a promising approach to investigate the potential effect of P as a limiting factor for agroecosystems at the global scale.