Beta Diversity of Plant-Pollinator Networks and the Spatial Turnover of Pairwise Interactions

Interactions between species form complex networks that vary across space and time. Even without spatial or temporal constraints mutualistic pairwise interactions may vary, or rewire, across space but this variability is not well understood. Here, we quantify the beta diversity of species and interactions and test factors influencing the probability of turnover of pairwise interactions across space. We ask: 1) whether beta diversity of plants, pollinators, and interactions follow a similar trend across space, and 2) which interaction properties and site characteristics are related to the probability of turnover of pairwise interactions. Geographical distance was positively correlated with plant and interaction beta diversity. We find that locally frequent interactions are more consistent across space and that local flower abundance is important for the realization of pairwise interactions. While the identity of pairwise interactions is highly variable across space, some species-pairs form interactions that are locally frequent and spatially consistent. Such interactions represent cornerstones of interacting communities and deserve special attention from ecologists and conservation planners alike.     

多重空间尺度的神经表征

空间环境具有多重尺度特性,具体分成可操作的近尺度空间、可导航的单视点空间和环境空间,以及大尺度的地理空间,有效表征不同尺度的空间环境对于人和动物的日常生活至关重要。空间尺度的表征与其对应的功能需求有关,近尺度空间表征由顶叶负责;可导航空间表征在海马和皮层都表现出从后往前的“由粗到细”的梯度性;抽象社会空间的尺度表征则表现出二分性。未来研究应关注空间尺度表征的时间动态性及其对认知地图存在形式的影响。     

Bird Community Composition in a Shaded Coffee Agro-ecological Matrix in Puebla,Mexico: The Effects of Landscape Heterogeneity at Multiple Spatial Scales

This study examined the importance of habitat heterogeneity on the avian community composition, and investigated the scale at which species abundances respond to habitat variables. The study was conducted within a diverse landscape matrix of a shaded coffee region in Mexico. To detect at which characteristic spatial scale different species and foraging guilds respond most strongly we analyzed the effect of plot-, patch- and landscape-level variables at different spatial extent (i.e., different kilometer radii) on species composition and foraging guilds. We used redundancy analysis to identify species–environment correlations, and to identify predictor variables that best explained the bird community structure, quantified the influence of plot-, patch- and landscape-level variables on the bird community composition. In addition, we used the 4th-corner method to detect significant relationships between the dietary guilds and plot-, patch- and landscape-level variables. We recorded 12,335 individuals of 181 bird species; 105 bird species were recorded foraging within the shaded coffee plantations. We found that plot- and landscape-level variables significantly explained the bird community composition best across all scales, and were significantly correlated with the abundance of the dietary guilds. In contrast, patch-level variables were less important. Habitat composition variables (i.e., coffee, forest and agricultural area) were among the most important predictors. Canopy structure was more important than other vegetation structure variables in explaining dietary guild structure. Hence, the maintenance of a heterogeneous landscape with a high-quality matrix within an agro-ecological region enhances bird conservation.     

Changes in Task-Related Functional Connectivity across Multiple Spatial Scales Are Related to Reading Performance

Reading requires the interaction of a distributed set of cortical areas whose distinct patterns give rise to a wide range of individual skill. However, the nature of these neural interactions and their relation to reading performance are still poorly understood. Functional connectivity analyses of fMRI data can be used to characterize the nature of interactivity of distributed brain networks, yet most previous studies have focused on connectivity during task-free (i.e., “resting state”) conditions. Here, we report new methods for assessing task-related functional connectivity using data-driven graph theoretical methods and describe how large-scale patterns of connectivity relate to individual variability in reading performance among children. We found that connectivity patterns of subjects performing a reading task could be decomposed hierarchically into multiple sub-networks, and we observed stronger long-range interaction between sub-networks in subjects with higher task accuracy. Additionally, we found a network of hub regions known to be critical to reading that displays increased short-range synchronization in higher accuracy subjects. These individual differences in task-related functional connectivity reveal that increased interaction between distant regions, coupled with selective local integration within key regions, is associated with better reading performance. Importantly, we show that task-related neuroimaging data contains far more information than usually extracted via standard univariate analyses – information that can meaningfully relate neural connectivity patterns to cognition and task.     

Spatial Heterogeneity in Ecologically Important Climate Variables at Coarse and Fine Scales in a High-Snow Mountain Landscape

Climate plays an important role in determining the geographic ranges of species. With rapid climate change expected in the coming decades, ecologists have predicted that species ranges will shift large distances in elevation and latitude. However, most range shift assessments are based on coarse-scale climate models that ignore fine-scale heterogeneity and could fail to capture important range shift dynamics. Moreover, if climate varies dramatically over short distances, some populations of certain species may only need to migrate tens of meters between microhabitats to track their climate as opposed to hundreds of meters upward or hundreds of kilometers poleward. To address these issues, we measured climate variables that are likely important determinants of plant species distributions and abundances (snow disappearance date and soil temperature) at coarse and fine scales at Mount Rainier National Park in Washington State, USA. Coarse-scale differences across the landscape such as large changes in elevation had expected effects on climatic variables, with later snow disappearance dates and lower temperatures at higher elevations. However, locations separated by small distances (∼20 m), but differing by vegetation structure or topographic position, often experienced differences in snow disappearance date and soil temperature as great as locations separated by large distances (>1 km). Tree canopy gaps and topographic depressions experienced later snow disappearance dates than corresponding locations under intact canopy and on ridges. Additionally, locations under vegetation and on topographic ridges experienced lower maximum and higher minimum soil temperatures. The large differences in climate we observed over small distances will likely lead to complex range shift dynamics and could buffer species from the negative effects of climate change.     

Population Genetics of the Eastern Hellbender (Cryptobranchus alleganiensis alleganiensis) across Multiple Spatial Scales

Conservation genetics is a powerful tool to assess the population structure of species and provides a framework for informing management of freshwater ecosystems. As lotic habitats become fragmented, the need to assess gene flow for species of conservation management becomes a priority. The eastern hellbender (Cryptobranchus alleganiensis alleganiensis) is a large, fully aquatic paedamorphic salamander. Many populations are experiencing declines throughout their geographic range, yet the genetic ramifications of these declines are currently unknown. To this end, we examined levels of genetic variation and genetic structure at both range-wide and drainage (hierarchical) scales. We collected 1,203 individuals from 77 rivers throughout nine states from June 2007 to August 2011. Levels of genetic diversity were relatively high among all sampling locations. We detected significant genetic structure across populations (F_st values ranged from 0.001 between rivers within a single watershed to 0.218 between states). We identified two genetically differentiated groups at the range-wide scale: 1) the Ohio River drainage and 2) the Tennessee River drainage. An analysis of molecular variance (AMOVA) based on landscape-scale sampling of basins within the Tennessee River drainage revealed the majority of genetic variation (∼94–98%) occurs within rivers. Eastern hellbenders show a strong pattern of isolation by stream distance (IBSD) at the drainage level. Understanding levels of genetic variation and differentiation at multiple spatial and biological scales will enable natural resource managers to make more informed decisions and plan effective conservation strategies for cryptic, lotic species.     

Landscape Ecotoxicology and Assessment of Risk at Multiple Scales

Traditional approaches to ecotoxicology and ecological risk assessment frequently have ignored the complexities arising due to the spatial heterogeneity of natural systems. In recent years, however, ecologists have become increasingly aware of the influence of spatial organization on ecological processes. Landscape ecology provides a conceptual and theoretical framework for the analysis of spatial patterns, the characterization of spatial aspects of ecosystem function, and the understanding of landscape dynamics. Incorporating the insights of landscape ecology into ecotoxicology will enhance our ability to understand and ultimately predict the effects of toxic substances in ecological systems. Ecological risk assessments need to explicitly consider multiple spatial scales, accounting for heterogeneity within contaminated areas and for the larger landscape context. A simple simulation model is presented to illustrate the effects of spatial heterogeneity by linking an individual-based toxicokinetic model with a spatially distributed metapopulation model. Dispersal of organisms between contaminated and uncontaminated patches creates a situation where risk analysis must consider a spatial extent broader than the toxicant-contaminated area. In general, the addition of a toxicant to a source patch (i.e., a net exporter of individuals) will have a greater impact than the same toxicant addition to a sink patch (i.e., a net importer of individuals).     

Community Turnover of Wood-Inhabiting Fungi across Hierarchical Spatial Scales

For efficient use of conservation resources it is important to determine how species diversity changes across spatial scales. In many poorly known species groups little is known about at which spatial scales the conservation efforts should be focused. Here we examined how the community turnover of wood-inhabiting fungi is realised at three hierarchical levels, and how much of community variation is explained by variation in resource composition and spatial proximity. The hierarchical study design consisted of management type (fixed factor), forest site (random factor, nested within management type) and study plots (randomly placed plots within each study site). To examine how species richness varied across the three hierarchical scales, randomized species accumulation curves and additive partitioning of species richness were applied. To analyse variation in wood-inhabiting species and dead wood composition at each scale, linear and Permanova modelling approaches were used. Wood-inhabiting fungal communities were dominated by rare and infrequent species. The similarity of fungal communities was higher within sites and within management categories than among sites or between the two management categories, and it decreased with increasing distance among the sampling plots and with decreasing similarity of dead wood resources. However, only a small part of community variation could be explained by these factors. The species present in managed forests were in a large extent a subset of those species present in natural forests. Our results suggest that in particular the protection of rare species requires a large total area. As managed forests have only little additional value complementing the diversity of natural forests, the conservation of natural forests is the key to ecologically effective conservation. As the dissimilarity of fungal communities increases with distance, the conserved natural forest sites should be broadly distributed in space, yet the individual conserved areas should be large enough to ensure local persistence.     

Integrating the Study of Non-native Plant Invasions across Spatial Scales

Non-native (alien, exotic) plant invasions are affecting ecological processes and threatening biodiversity worldwide. Patterns of plant invasions, and the ecological processes which generate these patterns, vary across spatial scales. Thus, consideration of spatial scale may help to illuminate the mechanisms driving biological invasions, and offer insight into potential management strategies. We review the processes driving movement of non-native plants to new locations, and the patterns and processes at the new locations, as they are variously affected by spatial scale. Dispersal is greatly influenced by scale, with different mechanisms controlling global, regional and local dispersal. Patterns of invasion are rarely documented across multiple spatial scales, but research using multi-scale approaches has generated interesting new insights into the invasion process. The ecological effects of plant invasions are also scale-dependent, ranging from altered local community diversity and homogenization of the global flora, to modified biogeochemical cycles and disturbance regimes at regional or global scales. Therefore, the study and control of invasions would benefit from documenting invasion processes at multiple scales.     

Heterogeneity,Mixing, and the Spatial Scales of Mosquito-Borne Pathogen Transmission

The Ross-Macdonald model has dominated theory for mosquito-borne pathogen transmission dynamics and control for over a century. The model, like many other basic population models, makes the mathematically convenient assumption that populations are well mixed; i.e., that each mosquito is equally likely to bite any vertebrate host. This assumption raises questions about the validity and utility of current theory because it is in conflict with preponderant empirical evidence that transmission is heterogeneous. Here, we propose a new dynamic framework that is realistic enough to describe biological causes of heterogeneous transmission of mosquito-borne pathogens of humans, yet tractable enough to provide a basis for developing and improving general theory. The framework is based on the ecological context of mosquito blood meals and the fine-scale movements of individual mosquitoes and human hosts that give rise to heterogeneous transmission. Using this framework, we describe pathogen dispersion in terms of individual-level analogues of two classical quantities: vectorial capacity and the basic reproductive number, . Importantly, this framework explicitly accounts for three key components of overall heterogeneity in transmission: heterogeneous exposure, poor mixing, and finite host numbers. Using these tools, we propose two ways of characterizing the spatial scales of transmission—pathogen dispersion kernels and the evenness of mixing across scales of aggregation—and demonstrate the consequences of a model''s choice of spatial scale for epidemic dynamics and for estimation of , both by a priori model formulas and by inference of the force of infection from time-series data.     

Urban Land Use Decouples Plant-Herbivore-Parasitoid Interactions at Multiple Spatial Scales

Intense urban and agricultural development alters habitats, increases fragmentation, and may decouple trophic interactions if plants or animals cannot disperse to needed resources. Specialist insects represent a substantial proportion of global biodiversity and their fidelity to discrete microhabitats provides a powerful framework for investigating organismal responses to human land use. We sampled site occupancy and densities for two plant-herbivore-parasitoid systems from 250 sites across a 360 km² urban/agricultural landscape to ask whether and how human development decouples interactions between trophic levels. We compared patterns of site occupancy, host plant density, herbivory and parasitism rates of insects at two trophic levels with respect to landcover at multiple spatial scales. Geospatial analyses were used to identify landcover characters predictive of insect distributions. We found that herbivorous insect densities were decoupled from host tree densities in urban landcover types at several spatial scales. This effect was amplified for the third trophic level in one of the two insect systems: despite being abundant regionally, a parasitoid species was absent from all urban/suburban landcover even where its herbivore host was common. Our results indicate that human land use patterns limit distributions of specialist insects. Dispersal constraints associated with urban built development are specifically implicated as a limiting factor.     

Scales of Spatial Heterogeneity of Plastic Marine Debris in the Northeast Pacific Ocean

Plastic debris has been documented in many marine ecosystems, including remote coastlines, the water column, the deep sea, and subtropical gyres. The North Pacific Subtropical Gyre (NPSG), colloquially called the “Great Pacific Garbage Patch,” has been an area of particular scientific and public concern. However, quantitative assessments of the extent and variability of plastic in the NPSG have been limited. Here, we quantify the distribution, abundance, and size of plastic in a subset of the eastern Pacific (approximately 20–40°N, 120–155°W) over multiple spatial scales. Samples were collected in Summer 2009 using surface and subsurface plankton net tows and quantitative visual observations, and Fall 2010 using surface net tows only. We documented widespread, though spatially variable, plastic pollution in this portion of the NPSG and adjacent waters. The overall median microplastic numerical concentration in Summer 2009 was 0.448 particles m⁻² and in Fall 2010 was 0.021 particles m⁻², but plastic concentrations were highly variable over the submesoscale (10 s of km). Size-frequency spectra were skewed towards small particles, with the most abundant particles having a cross-sectional area of approximately 0.01 cm². Most microplastic was found on the sea surface, with the highest densities detected in low-wind conditions. The numerical majority of objects were small particles collected with nets, but the majority of debris surface area was found in large objects assessed visually. Our ability to detect high-plastic areas varied with methodology, as stations with substantial microplastic did not necessarily also contain large visually observable objects. A power analysis of our data suggests that high variability of surface microplastic will make future changes in abundance difficult to detect without substantial sampling effort. Our findings suggest that assessment and monitoring of oceanic plastic debris must account for high spatial variability, particularly in regards to the evaluation of initiatives designed to reduce marine debris.     

Data Integration through Proximity-Based Networks Provides Biological Principles of Organization across Scales

Plant behaviors across levels of cellular organization, from biochemical components to tissues and organs, relate and reflect growth habitats. Quantification of the relationship between behaviors captured in various phenotypic characteristics and growth habitats can help reveal molecular mechanisms of plant adaptation. The aim of this article is to introduce the power of using statistics originally developed in the field of geographic variability analysis together with prominent network models in elucidating principles of biological organization. We provide a critical systematic review of the existing statistical and network-based approaches that can be employed to determine patterns of covariation from both uni- and multivariate phenotypic characteristics in plants. We demonstrate that parameter-independent network-based approaches result in robust insights about phenotypic covariation. These insights can be quantified and tested by applying well-established statistics combining the network structure with the phenotypic characteristics. We show that the reviewed network-based approaches are applicable from the level of genes to the study of individuals in a population of Arabidopsis thaliana. Finally, we demonstrate that the patterns of covariation can be generalized to quantifiable biological principles of organization. Therefore, these network-based approaches facilitate not only interpretation of large-scale data sets, but also prediction of biochemical and biological behaviors based on measurable characteristics.     

嘉陵江流域植被景观异质性的空间梯度变化

在遥感图像基础上,利用ArcView GIS和景观统计软件FRAGSTATS从东西、南北以及西北至东南3个方向对嘉陵江流域的植被景观异质性进行了空间梯度分析。结果表明:(1)栽培植被面积占总流域面积的51.81%,为整个流域植被景观的基质,聚合性最强,联结度最高;针叶林和灌丛的斑块数较多,但面积较小,破碎化程度较高,而裸地/城镇破碎化最低;灌丛斑块间距最大,聚合性最弱;高山植被分布零星,联结度最低;(2)沿东西方向,植被景观异质性逐步下降,在流域中部降至最低,但随着进一步向西推移又明显升高,表现出先降后升的总趋势;(3)从北至南植被景观异质性向上波动3次后逐步下降,在接近流域南端时降至最低后又略有升高,表现出先升高再逐渐波动下降的总趋势;(4)沿西北至东南方向植被景观异质性上下波动1次后在近东南端降至最低,随后略有小幅波动,但波动次数和幅度远低于北南方向,表现出先降低再波动下降的总趋势。     

Diminishing Spatial Heterogeneity in Soil Organic Matter across a Prairie Restoration Chronosequence

Habitat restoration resulting in changes in plant community composition or species dominance can affect the spatial pattern and variability of soil nutrients. Questions about how these changes in soil spatial heterogeneity develop over time at restoration sites, however, remain unaddressed. In this study, a geostatistical approach was used to quantify changes over time in the spatial heterogeneity of soil organic matter (SOM) across a 26‐year chronosequence of tallgrass prairie restoration sites at FermiLab, outside of Chicago, Illinois. We used total soil N and C as an index of the quantity of SOM. We also examined changes in C:N ratio, which can influence the turnover of SOM. Specifically, the spatial structure of total N, total C, and C:N ratio in the top 10 cm of soil was quantified at a macroscale (minimum spacing of 1.5 m) and a microscale (minimum spacing of 0.2 m). The magnitude of spatial heterogeneity (MSH) was characterized as the proportion of total sample variation explained by spatially structured variation. At the macroscale, the MSH for total N decreased with time since restoration (r²= 0.99, p < 0.001). The decrease in spatial heterogeneity over time corresponded with a significant increase in the dominance of the C₄ grasses. At the microscale, there was significant spatial structure for total N at the 4‐year‐old, 16‐year‐old, and 26‐year‐old sites, and significant spatial structure for total C at the 16‐year‐old and 26‐year‐old sites. These results suggest that an increase in dominance of C₄ grasses across the chronosequence is homogenizing organic matter variability at the field scale while creating fine‐scale patterns associated with the spacing of vegetation. Areas of higher soil moisture were associated with higher soil N and C at the two oldest restoration sites and at the native prairie site, potentially suggesting patches of increased belowground productivity in areas of higher soil moisture. This study is one of the first to report significant changes over time in the spatial structure of organic matter in response to successional changes initiated by restoration.