环境影响评价的尺度约束性及技术框架

尺度约束是地表复杂系统的基本规律,环评尺度约束常隐存于主观经验或零存于环评导则中,环评尺度约束较少被明确关注。讨论了环境影响尺度约束、环评尺度约束和环评技术框架尺度约束。研究发现,环境影响的尺度约束性内在原因在于环境影响主体、客体和影响内容存在等级结构;环评受空间、时间和分析三类尺度约束,空间尺度约束体现于空间范围和空间信息分辨率对环评影响,时间尺度约束体现于环评的时长和时频,分析尺度约束表现为环评技术方法和环境影响主观认知水平对评价的影响,三类尺度约束同时贯穿于环评过程,任何环评都可以在三类尺度空间中定位;环评技术框架的关键环节都受空间、时间和分析尺度约束,且以环境影响主体的空间、时间尺度为核心,具有一定弹性,一般空间或时间范围先放大再缩小、分辨率由粗到细。     

Relative importance of spatial processes and environmental factors in shaping alpine meadow communities

Aims Spatial processes and environmental control are the two distinct, yet not mutually exclusive forces of community structuring, but the relative importance of these factors is controversial due to the species-specific dispersal ability, sensitivity towards environmental variables, organism's abundance and the effect of spatial scale. In the present paper, we explored spatial versus environmental control in shaping community composition (i.e. β-diversity) and species turnover (i.e. change of β-diversity) at an alpine meadow along a slope aspect gradient on the Qinghai–Tibetan Plateau at different spatial scales of sampling (quadrats and plots), by taking account of seed dispersal mode and abundance.Methods We examined the relative importance of spatial processes and environmental factors using all species and four additional subsets of selected species. Moreover, we attempted to explore the effect of scale (quadrat refers to scale of ~0.3 m and plot of ~8 m) on their counter balance. The data were analyzed both by variation partitioning and multiple regressions on distance matrices. The spatial structure was modelled using Moran's eigenvector maps (MEM).Important findings Both spatial processes and environmental factors were important determinants of the community composition and species turnover. The community composition in the alpine meadow was controlled by spatially structured environment (17.6%), space independent of environment (18.0%) and a negligible effect of environment independent of space (4.4%) at the scale of quadrats. These three components contributed 21.8, 9.9 and 13.9%, respectively, at the scale of plots. The balance between the forces at different spatial scales drove community structures along the slope aspect gradient. The importance of environmental factors on β-diversity at alpine meadow increased with scale while that of spatial processes decreased or kept steady, depending on dispersal mode and abundance of species comprising the subset. But the 'pure' effect of spatial processes on species turnover increased with scale while that of environmental factors decreased. This discrepancy highlights that β-diversity and species turnover were determined jointly by spatial processes and environmental factors. We also found that the relative roles of these processes vary with spatial scale. These results underline the importance of considering species-specific dispersal ability and abundance of species comprising the communities and the appropriate spatial scale in understanding the mechanisms of community assembly.     

Environmental and biotic drivers of soil microbial β‐diversity across spatial and phylogenetic scales

Soil microbial communities play a key role in ecosystem functioning but still little is known about the processes that determine their turnover (β‐diversity) along ecological gradients. Here, we characterize soil microbial β‐diversity at two spatial scales and at multiple phylogenetic grains to ask how archaeal, bacterial and fungal communities are shaped by abiotic processes and biotic interactions with plants. We characterized microbial and plant communities using DNA metabarcoding of soil samples distributed across and within eighteen plots along an elevation gradient in the French Alps. The recovered taxa were placed onto phylogenies to estimate microbial and plant β‐diversity at different phylogenetic grains (i.e. resolution). We then modeled microbial β‐diversities with respect to plant β‐diversities and environmental dissimilarities across plots (landscape scale) and with respect to plant β‐diversities and spatial distances within plots (plot scale). At the landscape scale, fungal and archaeal β‐diversities were mostly related to plant β‐diversity, while bacterial β‐diversities were mostly related to environmental dissimilarities. At the plot scale, we detected a modest covariation of bacterial and fungal β‐diversities with plant β‐diversity; as well as a distance–decay relationship that suggested the influence of ecological drift on microbial communities. In addition, the covariation between fungal and plant β‐diversity at the plot scale was highest at fine or intermediate phylogenetic grains hinting that biotic interactions between those clades depends on early‐evolved traits. Altogether, we show how multiple ecological processes determine soil microbial community assembly at different spatial scales and how the strength of these processes change among microbial clades. In addition, we emphasized the imprint of microbial and plant evolutionary history on today's microbial community structure.     

Dissecting spatiotemporal patterns of functional diversity through the lens of Darwin's naturalization conundrum

Darwin's naturalization conundrum describes the paradigm that community assembly is regulated by two opposing processes, environmental filtering and competitive interactions, which predict both similarity and distinctiveness of species to be important for establishment. Our goal is to use long‐term, large‐scale, and high‐resolution temporal data to examine diversity patterns over time and assess whether environmental filtering or competition plays a larger role in regulating community assembly processes. We evaluated Darwin's naturalization conundrum and how functional diversity has changed in the Laurentian Great Lakes fish community from 1870 to 2010, which has experienced frequent introductions of non‐native species and extirpations of native species. We analyzed how functional diversity has changed over time by decade from 1870 to 2010 at three spatial scales (regional, lake, and habitat) to account for potential noninteractions between species at the regional and lake level. We also determined which process, environmental filtering or competitive interactions, is more important in regulating community assembly and maintenance by comparing observed patterns to what we would expect in the absence of an ecological mechanism. With the exception of one community, all analyses show that functional diversity and species richness has increased over time and that environmental filtering regulates community assembly at the regional level. When examining functional diversity at the lake and habitat level, the regulating processes become more context dependent. This study is the first to examine diversity patterns and Darwin's conundrum by integrating long‐term, large‐scale, and high‐resolution temporal data at multiple spatial scales. Our results confirm that Darwin's conundrum is highly context dependent.     

区域生态系统健康评价——研究方法与进展

生态系统健康评价是当前宏观生态学与生态系统管理研究的热点问题之一,区域尺度的生态系统健康评价则是生态系统健康评价研究的一个重要发展方向。在探讨生态系统健康时空尺度特征的基础上,明确界定了区域生态系统健康及其评价等相关概念,结合目前区域尺度生态系统健康评价的相关研究进展,从评价的区域类型、目标单元、模型方法、指标选取及其阈值、权重设定等方面探讨了区域生态系统健康评价的基本原理与方法,并展望了进一步研究的重点方向,即评价结果的多尺度综合与尺度转换、景观生态学理论与方法的应用、3S技术的综合应用等理论与技术问题。     

互花米草(Spartina alterniflora)潜在分布格局的空间尺度效应

了解不同空间尺度下外来入侵植物互花米草(Spartina alterniflora)的潜在分布格局,有助于制定科学的防治管理策略,维护滨海湿地的生物多样性。研究基于有效的地理分布点位和环境变量数据集,设置了3个研究区幅度(区域、国家、全球)和5种环境变量粒度(30″、1.0′、2.5′、5.0′、10′),应用最大熵(MaxEnt)模型预测互花米草在不同幅度和粒度下的潜在分布,探究互花米草分布格局及其环境影响因子对空间尺度响应。结果表明：(1)MaxEnt模型在不同空间尺度下的预测效果较好,各尺度下测试集的受试者曲线下面积(AUC)值均大于0.8,真实技巧统计值(TSS)值则超过0.56,但模型的预测精度对空间尺度变化较为敏感;(2)不同空间尺度下互花米草的潜在分布格局存在着显著的差异性,表现为适生区面积会随着空间范围扩大或环境变量分辨率降低而提高,且质心位置也在不断发生地带性转移;(3)空间尺度的变化会削弱主要环境变量的解释力。在大尺度范围和低分辨率环境变量图层中,气候因子的重要性较大,而在相反尺度下地形因子的影响度得到提升;(4)研究区范围与环境变量分辨率不匹配时,模型预测精度和物...     

Evaluation for regional ecosystem health: methodology and research progress

The evaluation for ecosystem health is one of the hotspots in the fields of macro-ecology and ecosystem management. Conducting analysis at the regional scale is an important direction for evaluating ecosystem health. Changing the spatial scale from the local to the regional level leads to great differences in targets and methodologies for ecosystem health evaluation and creates a new direction for regional ecosystem health research. Compared with the ecosystem health at the local scale, which refers to a single ecosystem type, the regional ecosystem health focuses on the health conditions and spatial patterns of different ecosystem types. However, there has been little attention paid to this very research up to now. Based on the progress on ecosystem health studies at the regional scale, the study reported in this article aims to discuss the implications of the conception of regional ecosystem health and to put forward a methodology for evaluating the regional ecosystem health. The main results include: (1) there is a significant scaling effect on the ecosystem health analysis, and the regional level is the key scale used to focus on the correlation between spatially neighboring ecosystems in terms of ecosystem health; (2) regional ecosystem health can be defined through 4 aspects, i.e., vigor, organization, resilience, and ecosystem service functions; (3) the basic evaluation objects of the regional ecosystem health is spatial entity, which is the matrix of different ecosystem types; (4) indicator system method is the only approach to evaluate regional ecosystem health; (5) the absolute thresholds of the evaluation indicators for the regional ecosystem health do not exist; the aim of the evaluation is to discuss the temporal dynamic changes and spatial differences of health conditions rather than to ascertain whether a region is healthy or not in view of ecological sustainability; and (6) the integration of evaluation results at multispatial scales, the application of this methodology in the landscape ecology, and the utilization of geographic information systems (GIS), remote sensing (RS), and Global Positioning Systems (GPS) technologies are the main directions for further research.     

Occupancy versus colonization–extinction models for projecting population trends at different spatial scales

Understanding spatiotemporal population trends and their drivers is a key aim in population ecology. We further need to be able to predict how the dynamics and sizes of populations are affected in the long term by changing landscapes and climate. However, predictions of future population trends are sensitive to a range of modeling assumptions. Deadwood‐dependent fungi are an excellent system for testing the performance of different predictive models of sessile species as these species have different rarity and spatial population dynamics, the populations are structured at different spatial scales, and they utilize distinct substrates. We tested how the projected large‐scale occupancies of species with differing landscape‐scale occupancies are affected over the coming century by different modeling assumptions. We compared projections based on occupancy models against colonization–extinction models, conducting the modeling at alternative spatial scales and using fine‐ or coarse‐resolution deadwood data. We also tested effects of key explanatory variables on species occurrence and colonization–extinction dynamics. The hierarchical Bayesian models applied were fitted to an extensive repeated survey of deadwood and fungi at 174 patches. We projected higher occurrence probabilities and more positive trends using the occupancy models compared to the colonization–extinction models, with greater difference for the species with lower occupancy, colonization rate, and colonization:extinction ratio than for the species with higher estimates of these statistics. The magnitude of future increase in occupancy depended strongly on the spatial modeling scale and resource resolution. We encourage using colonization–extinction models over occupancy models, modeling the process at the finest resource‐unit resolution that is utilizable by the species, and conducting projections for the same spatial scale and resource resolution at which the model fitting is conducted. Further, the models applied should include key variables driving the metapopulation dynamics, such as the availability of suitable resource units, habitat quality, and spatial connectivity.     

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。     

Genetic Analysis of Invasive Plant Populations at Different Spatial Scales

Measuring genetic diversity requires selection of a spatial scale of analysis. Different levels of genetic structuring are revealed at different spatial scales, however, and the relative importance of factors driving genetic structuring varies along the spatial scale continuum. Unequal gene flow is a major factor determining genetic structure in plant populations at the local level, while the effect of selection imposed by environmental heterogeneity increases with the spatial scale of analysis. At a continental and global scale genetic structure of invasive plant populations is significantly affected by founder effect and propagule transport via human vectors. Although genetic analysis at one spatial scale provides only partial information about the invasion process, little published research reports such data for the same species at multiple scales. A multi-faceted approach to investigating the genetic structure of invasive plant species that incorporates sampling at different spatial and temporal scales would provide a more complete picture of the role of genetic forces in invasion.     

生态学中的尺度问题：内涵与分析方法

尺度问题已成为现代生态学的核心问题之一.尺度问题主要涉及3个方面：尺度概念、尺度分析和尺度推绎.主要评述前两个方面.生态学尺度有三重概念：维数、种类和组分,其中每重概念又包含了多个定义,有必要进行澄清、分类和统一.尺度分析涉及尺度效应分析和多尺度空间格局分析.格局、过程及它们之间的关系,以及某些景观特性均表现出尺度效应,因此多尺度研究非常必要和重要.多尺度空间格局分析（尤其是特征尺度的识别）是进行尺度效应分析和跨尺度推绎的基础.多尺度分析需要特定的方法,景观指数法是最常用和最简单的方法,但也常产生误导;空间统计学方法（如半方差分析法、尺度方差分析法、空隙度指数法和小波分析法等）和分维分析法在最近十几年发展起来,并逐渐应用于生态学,在尺度分析上具有很大的应用潜力.各种方法在尺度分析上各有优势和不足,有必要同时使用两种或两种以上方法进行比较和评估.总之,有关尺度分析的研究需要进一步加强,从而为下一步的尺度推绎提供可靠的依据.     

Environmental and spatial drivers of spider diversity at contrasting microhabitats

The relative importance of environmental and spatial drivers of animal diversity varies across scales, but identifying these scales can be difficult if a sampling design does not match the scale of the target organisms' interaction with their habitat. In this study, we quantify and compare the effects of environmental variation and spatial proximity on ground‐dwelling spider assemblages sampled from three distinct microhabitat types (open grassland, logs, trees) that recur across structurally heterogeneous grassy woodlands. We used model selection and multivariate procedures to compare the effects of different environmental attributes and spatial proximity on spider assemblages at each microhabitat type. We found that species richness and assemblage composition differed among microhabitat types. Bare ground cover had a negative effect on spider richness under trees, but a positive effect on spider richness in open grassland. Turnover in spider assemblages from open grassland was correlated with environmental distance, but not geographic distance. By contrast, turnover in spiders at logs and trees was correlated with geographic distance, but not environmental distance. Our study suggests that spider assemblages from widespread and connected open grassland habitat were more affected by environmental than spatial gradients, whereas spiders at log and tree habitats were more affected by spatial distance among these discrete but recurring microhabitats. Deliberate selection and sampling of small‐scale habitat features can provide robust information about the drivers of arthropod diversity and turnover in landscapes.     

How beta diversity and the underlying causes vary with sampling scales in the Changbai mountain forests

This study aims to establish a relationship between the sampling scale and tree species beta diversity temperate forests and to identify the underlying causes of beta diversity at different sampling scales. The data were obtained from three large observational study areas in the Changbai mountain region in northeastern China. All trees with a dbh ≥1 cm were stem‐mapped and measured. The beta diversity was calculated for four different grain sizes, and the associated variances were partitioned into components explained by environmental and spatial variables to determine the contributions of environmental filtering and dispersal limitation to beta diversity. The results showed that both beta diversity and the causes of beta diversity were dependent on the sampling scale. Beta diversity decreased with increasing scales. The best‐explained beta diversity variation was up to about 60% which was discovered in the secondary conifer and broad‐leaved mixed forest (CBF) study area at the 40 × 40 m scale. The variation partitioning result indicated that environmental filtering showed greater effects at bigger grain sizes, while dispersal limitation was found to be more important at smaller grain sizes. What is more, the result showed an increasing explanatory ability of environmental effects with increasing sampling grains but no clearly trend of spatial effects. The study emphasized that the underlying causes of beta diversity variation may be quite different within the same region depending on varying sampling scales. Therefore, scale effects should be taken into account in future studies on beta diversity, which is critical in identifying different relative importance of spatial and environmental drivers on species composition variation.     

Communicating about ocean health: theoretical and practical considerations

As anthropogenic stressors threaten the health of marine ecosystems, there is a need to better understand how the public processes and responds to information about ocean health. Recent studies of public perceptions about ocean issues report high concern but limited knowledge, prompting calls for information campaigns to mobilize public support for ocean restoration policy. Drawing on the literature from communication, psychology and related social science disciplines, we consider a set of social-cognitive challenges that researchers and advocates are likely to encounter when communicating with the public about ocean health and emerging marine diseases—namely, the psychological distance at which ocean issues are construed, the unfamiliarity of aquatic systems to many members of the public and the potential for marine health issues to be interpreted through politicized schemas that encourage motivated reasoning over the dispassionate consideration of scientific evidence. We offer theory-based strategies to help public outreach efforts address these challenges and present data from a recent experiment exploring the role of message framing (emphasizing the public health or environmental consequences of marine disease) in shaping public support for environmental policy.     

Disentangling scale dependencies in species environmental niches and distributions

Understanding species’ responses to environmental conditions, and how these ­species–environment associations shape spatial distributions, are longstanding goals in ecology and biogeography. However, an essential component of species–environment relationships – the spatial unit, or grain, at which they operate – remains unresolved. We identify three components of scale‐dependence in analyses of species–environment associations: 1) response grain, the grain at which species respond most strongly to their environment; 2) environment spatial structure, the pattern of spatial autocorrelation intrinsic to an environmental factor; and 3) analysis grain, the grain at which analyses are conducted and ecological inferences are made. We introduce a novel conceptual framework that defines these scale components in the context of analyzing species–environment relationships, and provide theoretical examples of their interactions for species with various ecological attributes. We then use a virtual species approach to investigate the impacts of each component on common methods of measuring and predicting species–environment relationships. We find that environment spatial structure has a substantial impact on the ability of even simple, univariate species distribution models (SDMs) to recover known species–­environment associations at coarse analysis grains. For simulated environments with ‘fine’ and ‘intermediate’ spatial structure, model explanatory power, and the frequency with which simple SDMs correctly estimated a virtual species’ response to the simulated environment, dramatically declined as analysis grain increased. Informed by these results, we use a scaling analysis to identify maximum analysis grains for individual environmental factors, and a scale optimization procedure to determine the grain of maximum predictive accuracy. Implementing these analysis grain thresholds and model performance standards in an example east African study system yields more accurate distribution predictions, compared to SDMs independently constructed at arbitrary analysis grains. Finally, we integrate our conceptual framework with virtual and empirical results to provide practical recommendations for researchers asking common questions about species–environment relationships.     

Fine scale waterbody data improve prediction of waterbird occurrence despite coarse species data

While modelling habitat suitability and species distribution, ecologists must deal with issues related to the spatial resolution of species occurrence and environmental data. Indeed, given that the spatial resolution of species and environmental datasets range from centimeters to hundreds of kilometers, it underlines the importance of choosing the optimal combination of resolutions to achieve the highest possible modelling prediction accuracy. We evaluated how the spatial resolution of land cover/waterbody datasets (meters to 1 km) affect waterbird habitat suitability models based on atlas data (grid cell of 12 × 11 km). We hypothesized that the area, perimeter and number of waterbodies computed from high resolution datasets would explain distributions of waterbirds better because coarse resolution datasets omit small waterbodies affecting species occurrence. Specifically, we investigated which spatial resolution of waterbodies better explain the distribution of seven waterbirds nesting on ponds/lakes with areas ranging from 0.1 ha to hundreds of hectares. Our results show that the area and perimeter of waterbodies derived from high resolution datasets (raster data with 30 m resolution, vector data corresponding with map scale 1:10 000) explain the distribution of the waterbirds better than those calculated using less accurate datasets despite the coarse grain of the species data. Taking into account the spatial extent (global vs regional) of the datasets, we found the Global Inland Waterbody Dataset to be the most suitable for modelling distribution of waterbirds. In general, we recommend using land cover data of a resolution sufficient to capture the smallest patches of the habitat suitable for a given species’ presence for both fine and coarse grain habitat suitability and distribution modelling.     

Functional diversity of phyllostomid bats in an urban–rural landscape: A scale-dependent analysis

Urbanization is one of the most pervasive processes of landscape transformation, responsible for novel selection agents promoting functional community homogenization. Bats may persist in those environments, but the mechanisms responsible for their adaptability and the spatial scales in which the landscape imposes environmental filtering remain poorly studied in the Neotropics. We tested the hypothesis that landscape composition interacts with the spatial scale to affect the functional diversity of phyllostomids in an urban–rural gradient. Based on functional traits, we calculated indices of functional richness, divergence, evenness, and community-weighted means of morphological traits, and classified species into functional groups. We evaluated the changes in those variables in response to forest, grassland, and urbanized areas at 0.5, 1.25, and 2km scales. The number of functional groups, functional richness, and functional evenness tended to be higher in areas far from cities and with higher forest cover, whereas functional divergence increased in more urbanized areas. Our results show that the mean value of wing loading in the assemblage was negatively associated with landscape transformation at several spatial scales. However, environmental filtering driven by grass cover was particularly robust at the 0.5km scale, affecting big-sized species with long-pointed wings. Retaining natural forest in cattle ranging systems at ~12 km² appears to favor the functional evenness and number of functional groups of phyllostomids. Recognizing the scale of the effect on phyllostomid functional responses appears to be a fundamental issue for elucidating the spatial extent to which phyllostomid conservation planning in urban–rural landscapes should be addressed.     

Temporal resolutions in species distribution models of highly mobile marine animals: Recommendations for ecologists and managers

While ecologists have long recognized the influence of spatial resolution on species distribution models (SDMs), they have given relatively little attention to the influence of temporal resolution. Considering temporal resolutions is critical in distribution modelling of highly mobile marine animals, as they interact with dynamic oceanographic processes that vary at time‐scales from seconds to decades. We guide ecologists in selecting temporal resolutions that best match ecological questions and ecosystems, and managers in applying these models. We group the temporal resolutions of environmental variables used in SDMs into three classes: instantaneous, contemporaneous and climatological. We posit that animal associations with fine‐scale and ephemeral features are best modelled with instantaneous covariates. Associations with large scale and persistent oceanographic features are best modelled with climatological covariates. Associations with mesoscale features are best modelled with instantaneous or contemporaneous covariates if ephemeral processes are present or interannual variability occurs, and climatological covariates if seasonal processes dominate and interannual variability is weak.     

The influence of different spatial‐scale variables on caddisfly assemblages in Flemish lowland streams

1. Patterns in species assemblages are the result of the combined influence of processes acting on different spatial scales. Various studies describe the distribution of macroinvertebrate communities and their relationship with environmental factors at different geographical scales, but only a few of these studies concentrate on Western European lowlands. 2. Using Flanders as representative for the densely populated Western‐European lowlands, the specific aims of this study are: (i) to identify the different trichopteran species assemblages and to characterise them biologically using indicator species; (ii) to determine which environmental gradients most influence the observed species assemblages; and (iii) to analyse the relative importance of different spatial scale variables in constraining the Trichoptera distributions. 3. Assessment of the main environmental gradients suggested that the absence of Trichoptera from certain locations was mainly due to elevated nutrient concentrations and lower oxygen contents, confirming their sensitivity to anthropogenic disturbance. 4. Five Trichoptera species assemblages were distinguished based on Bray–Curtis dissimilarity coefficients. These assemblages did not differ significantly in species richness, but a shift in stream zonation preference was observed. In the ordination analysis 11 variables that were selected using a stepwise model building function manifested themselves as upstream–downstream and size‐related gradients. The Trichoptera assemblages in lowland streams thus appear to follow a longitudinal succession pattern that corresponds with the species‐specific preferences. 5. Partitioning the variance over the different spatial scales indicated that the reach‐scale variables were far more important in explaining the variation in species composition. The study design, which limited the minimum–maximum range of catchment‐scale characteristics, however, may have led to an overestimation of the impact of the local‐scale variables.     

Reconciling the influence of global climate phenomena on macrofaunal temporal dynamics at a variety of spatial scales

Determining the relative importance of environmental forces on population dynamics is a fundamental question for ecologists. Growing concern over the ecological effects of climate change emphasizes the importance of defining whether broad-scale environmental forces uniformly act upon local populations (hierarchy theory) or cross-scale interactions influence local responses (multiscale theory). This study analyses 13 years of data on species abundances at six sites within a large harbour to determine the effect of the El Niño Southern Oscillation (ENSO). Environmental variables both directly and indirectly related to ENSO were observed to be important predictors of the temporal dynamics of abundance in many species, but the observed effects were not consistent across sites or species. While nearly all species were affected by large temporal and spatial scale variability, smaller temporal scale, location-specific environmental variables (such as wind-generated wave exposure and turbidity) were also generally important, increasing the variability explained by our models by up to 25%. As with many other broad-scale variables, generality of response to ENSO is affected by interactions across time and space with smaller scale heterogeneity. This study therefore suggests that the degree of interaction between broad-scale climatic factors, such as ENSO, with smaller scale variability, will determine the consistency of responses over large spatial scales, and control our ability to predict effects of climate change on coastal and estuarine communities.