Summary1. Increasingly, ecologists conceptualize local communities as connected to a regional species pool rather than as isolated entities. By this paradigm, community structure is determined through the relative strengths of dispersal-driven regional effects and local environmental factors. However, despite explicit incorporation of dispersal, metacommunity models and frameworks often fail to capture the realities of natural systems by not accounting for the configuration of space within which organisms disperse. This shortcoming may be of particular consequence in riverine networks which consist of linearly -arranged, hierarchical, branching habitat elements. Our goal was to understand how constraints of network connectivity in riverine systems change the relative importance of local vs. regional factors in structuring communities. 2. We hypothesized that communities in more isolated headwaters of riverine networks would be structured by local forces, while mainstem sections would be structured by both local and regional processes. We examined these hypotheses using a spatially explicit regional analysis of riverine macroinvertebrate communities, focusing on change in community similarity with distance between local communities [i.e., distance-decay relationships; (DDRs)], and the change in environmental similarity with distance. Strong DDRs frequently indicate dispersal-driven dynamics. 3. There was no evidence of a DDR in headwater communities, supporting our hypothesis that dispersal is a weak structuring force. Furthermore, a positive relationship between community similarity and environmental similarity supported dynamics driven by local environmental factors (i.e., species sorting). In mainstem habitats, significant DDRs and community · environment similarity relationships suggested both dispersal-driven and environmental constraints on local community structure (i.e., mass effects). 4. We used species traits to compare communities characterized by low vs. high dispersal taxa. In headwaters, neither strength nor mode (in-network vs. out of network) of dispersal changed our results. However, outcomes in mainstems changed substantially with both dispersal mode and strength, further supporting the hypothesis that regional forces drive community dynamics in mainstems.5. Our findings demonstrate that the balance of local and regional effects changes depending on location within riverine network with local (environmental) factors dictating community structure in headwaters, and regional (dispersal driven) forces dominating in mainstems.

The effect of biodiversity on natural communities has recently emerged as a topic of considerable ecological interest. We review studies that explicitly test whether the number of species in a community (species richness) regulates the temporal variability of aggregate community (total biomass, productivity, nutrient cycling) and population (density, biomass) properties. Theoretical studies predict that community variability should decline with increasing species richness, while population variability should increase. Many, but not all, empirical studies support these expectations. However, a closer look reveals that several empirical studies have either imperfect experimental designs or biased methods of calculating variability. Furthermore, most theoretical studies rely on highly unrealistic assumptions. We conclude that evidence to support the claim that biodiversity regulates temporal variability is accumulating, but not unequivocal. More research, in a broader array of ecosystem types and with careful attention to methodological considerations, is needed before we can make definitive statements regarding richness‐variability relationships.

Linear regression and analysis of variance (ANOVA) are two of the most widely used statistical techniques in ecology. Regression quantitatively describes the relationship between a response variable and one or more continuous independent variables, while ANOVA determines whether a response variable differs among discrete values of the independent variable(s). Designing experiments with discrete factors is straightforward because ANOVA is the only option, but what is the best way to design experiments involving continuous factors? Should ecologists prefer experiments with few treatments and many replicates analyzed with ANOVA, or experiments with many treatments and few replicates per treatment analyzed with regression? We recommend that ecologists choose regression, especially replicated regression, over ANOVA when dealing with continuous factors for two reasons: (1) regression is generally a more powerful approach than ANOVA and (2) regression provides quantitative output that can be incorporated into ecological models more effectively than ANOVA output.

Explaining the mechanisms underlying patterns of species diversity and composition in riverine networks is challenging. Historically, community ecologists have conceived of communities as largely isolated entities and have focused on local environmental factors and interspecific interactions as the major forces determining species composition. However, stream ecologists have long embraced a multiscale approach to studying riverine ecosystems and have studied both local factors and larger-scale regional factors, such as dispersal and disturbance. River networks exhibit a dendritic spatial structure that can constrain aquatic organisms when their dispersal is influenced by or confined to the river network. We contend that the principles of metacommunity theory would help stream ecologists to understand how the complex spatial structure of river networks mediates the relative influences of local and regional control on species composition. From a basic ecological perspective, the concept is attractive because new evidence suggests that the importance of regional processes (dispersal) depends on spatial structure of habitat and on connection to the regional species pool. The role of local factors relative to regional factors will vary with spatial position in a river network. From an applied perspective, the long-standing view in ecology that local community composition is an indicator of habitat quality may not be uniformly applicable across a river network, but the strength of such bioassessment approaches probably will depend on spatial position in the network. The principles of metacommunity theory are broadly applicable across taxa and systems but seem of particular consequence to stream ecology given the unique spatial structure of riverine systems. By explicitly embracing processes at multiple spatial scales, metacommunity theory provides a foundation on which to build a richer understanding of stream communities.

Although all natural systems are heterogeneous, the direct influence of spatial heterogeneity on most ecological variables is unknown. In many systems, spatial heterogeneity is positively correlated with both microhabitat refugia and species richness. Both an increased number of microhabitat refugia and the effects of statistical averaging via increased species richness should lead to an inverse relationship between spatial heterogeneity and variability in community composition. To test this prediction, I measured diversity and temporal variability of invertebrate communities in a northern New Hampshire stream along a natural gradient of spatial heterogeneity formed by variation in stream substrates. On average, there was a 42% decrease in community variability along a gradient of increasing heterogeneity. This pattern was robust to changes in metrics of both heterogeneity and community variability. There was also a significant positive relationship between taxon richness and spatial heterogeneity with predicted taxon richness increasing c. 1.5× along the heterogeneity gradient. By resampling community abundance data, I estimated that statistical averaging accounted for only 4% of the observed decrease in community variability in this study. I concluded that the remaining decrease was very likely explained by a greater number of refugia from predation and/or flooding in high‐heterogeneity habitats. The results of this study suggest that maximizing heterogeneity in ecological restoration programmes may promote temporally stable and diverse communities and may aid in responsible management of aquatic resources.

Metacommunity ecology has rapidly become a dominant framework through which ecologists understand the natural world. Unfortunately, persistent misunderstandings regarding metacommunity theory and the methods for evaluating hypotheses based on the theory are common in the ecological literature. Since its beginnings, four major paradigms-species sorting, mass effects, neutrality, and patch dynamics-have been associated with metacommunity ecology. The Big 4 have been misconstrued to represent the complete set of metacommunity dynamics. As a result, many investigators attempt to evaluate community assembly processes as strictly belonging to one of the Big 4 types, rather than embracing the full scope of metacommunity theory. The Big 4 were never intended to represent the entire spectrum of metacommunity dynamics and were rather examples of historical paradigms that fit within the new framework. We argue that perpetuation of the Big 4 typology hurts community ecology and we encourage researchers to embrace the full inference space of metacommunity theory. A related, but distinct issue is that the technique of variation partitioning is often used to evaluate the dynamics of metacommunities. This methodology has produced its own set of misunderstandings, some of which are directly a product of the Big 4 typology and others which are simply the product of poor study design or statistical artefacts. However, variation partitioning is a potentially powerful technique when used appropriately and we identify several strategies for successful utilization of variation partitioning.

Ecological theory and observational evidence suggest that symbiotic interactions such as cleaning symbioses can shift from mutualism to parasitism. However, field experimental evidence documenting these shifts has never been reported for a cleaning symbiosis. Here, we demonstrate shifts in a freshwater cleaning symbiosis in a system involving crayfish and branchiobdellid annelids. Branchiobdellids have been shown to benefit their hosts under some conditions by cleaning material from host crayfish's gill filaments. The system is uniquely suited as an experimental model for symbiosis due to ease of manipulation and ubiquity of the organisms. In three field experiments, we manipulated densities of worms on host crayfish and measured host growth in field enclosures. In all cases, the experiments revealed shifts from mutualism to parasitism: host crayfish growth was highest at intermediate densities of branchiobdellid symbionts, while high symbiont densities led to growth that was lower or not significantly different from 0-worm controls. Growth responses were consistent even though the three experiments involved different crayfish and worm species and were performed at different locations. Results also closely conformed to a previous laboratory experiment using the same system. The mechanism for these shifts appears to be that branchiobdellids switched from cleaning host gills at intermediate densities of worms to consuming host gill tissue at high densities. These outcomes clearly demonstrate shifts along a symbiosis continuum with the maximum benefits to the host at intermediate symbiont densities. At high symbiont densities, benefits to the host disappear, and there is some evidence for a weak parasitism. These are the first field experimental results to demonstrate such shifts in a cleaning symbiosis.

Abstract-The design of a hyper-redundant serial-linkage snake robot is the focus of this paper. The snake, which consists of many fully enclosed actuators, incorporates a modular architecture. In our design, which we call the Unified Snake, we consider size, weight, power, and speed tradeoffs. Each module includes a motor and gear train, an SMA wire actuated bistable brake, custom electronics featuring several different sensors, and a custom intermodule connector. In addition to describing the Unified Snake modules, we also discuss the specialized head and tail modules on the robot and the software that coordinates the motion.