Ecology Letters (2011) 14: 19–28
A recent increase in studies of β diversity has yielded a confusing array of concepts, measures and methods. Here, we provide a roadmap of the most widely used and ...ecologically relevant approaches for analysis through a series of mission statements. We distinguish two types of β diversity: directional turnover along a gradient vs. non‐directional variation. Different measures emphasize different properties of ecological data. Such properties include the degree of emphasis on presence/absence vs. relative abundance information and the inclusion vs. exclusion of joint absences. Judicious use of multiple measures in concert can uncover the underlying nature of patterns in β diversity for a given dataset. A case study of Indonesian coral assemblages shows the utility of a multi‐faceted approach. We advocate careful consideration of relevant questions, matched by appropriate analyses. The rigorous application of null models will also help to reveal potential processes driving observed patterns in β diversity.
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Understanding spatial variation in biodiversity along environmental gradients is a central theme in ecology. Differences in species compositional turnover among sites (β diversity) occurring along ...gradients are often used to infer variation in the processes structuring communities. Here, we show that sampling alone predicts changes in β diversity caused simply by changes in the sizes of species pools. For example, forest inventories sampled along latitudinal and elevational gradients show the well-documented pattern that β diversity is higher in the tropics and at low elevations. However, after correcting for variation in pooled species richness (γ diversity), these differences in β diversity disappear. Therefore, there is no need to invoke differences in the mechanisms of community assembly in temperate versus tropical systems to explain these global-scale patterns of β diversity.
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Aim: A long-standing challenge in ecology is to identify the suite of factors that lead to turnover in species composition in both space and time. These factors might be stochastic (e.g. sampling and ...priority effects) or deterministic (e.g. competition and environmental filtering). While numerous studies have examined the relationship between turnover and individual drivers of interest (e.g. primary productivity, habitat heterogeneity, or regional –'gamma' – diversity), few studies have disentangled the simultaneous influences of multiple stochastic and deterministic processes on both temporal and spatial turnover. If turnover is governed primarily by stochastic sampling processes, removing the sampling effects of gamma diversity should result in non-significant relationships between turnover and environmental variables. Conversely, if deterministic processes govern turnover patterns, removing sampling effects will have little influence on turnover gradients. Here, we test these predictions. Location: The United States. Methods: Continental-scale, multidecadal data were used to quantify spatial and temporal turnover in avian community composition within 295 survey routes. A series of regression and structural equation models were coupled with a null model to construct statistical models describing turnover patterns. Results: Examining explanatory variables alone or in combination showed that spatial and temporal turnover increased together, decreased with primary productivity and increased with habitat heterogeneity. The relationships between turnover and all variables became weaker when sampling effects were removed, but relationships with primary productivity and habitat heterogeneity remained relatively strong. In addition, spatial turnover increased strongly with spatial gamma diversity after sampling effects were removed. Main conclusions: Our results show that spatial and temporal turnover are related to each other through a stochastic sampling process, but that each type of turnover is further influenced by deterministic processes. The relative influence of deterministic processes appears, however, to decrease with primary productivity and increase with habitat heterogeneity across an east-west longitudinal gradient in North America.
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Whether species interactions are static or change over time has wide‐reaching ecological and evolutionary consequences. However, species interaction networks are typically constructed from temporally ...aggregated interaction data, thereby implicitly assuming that interactions are fixed. This approach has advanced our understanding of communities, but it obscures the timescale at which interactions form (or dissolve) and the drivers and consequences of such dynamics. We address this knowledge gap by quantifying the within‐season turnover of plant–pollinator interactions from weekly censuses across 3 years in a subalpine ecosystem. Week‐to‐week turnover of interactions (1) was high, (2) followed a consistent seasonal progression in all years of study and (3) was dominated by interaction rewiring (the reassembly of interactions among species). Simulation models revealed that species’ phenologies and relative abundances constrained both total interaction turnover and rewiring. Our findings reveal the diversity of species interactions that may be missed when the temporal dynamics of networks are ignored.
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Community structure and ecosystem processes often vary along elevational gradients. Their responses to elevation are commonly driven by changes in temperature, and many community-and ecosystem-level ...variables therefore frequently respond similarly to elevation across contrasting gradients. There are also many exceptions, sometimes because other factors such as precipitation can also vary with elevation. Given this complexity, our capacity to predict when and why the same variable responds differently among disparate elevational gradients is often limited. Furthermore, there is utility in using elevational gradients for understanding community and ecosystem responses to global climate change at much larger spatial and temporal scales than is possible through conventional ecological experiments. However, future studies that integrate elevational gradient approaches with experimental manipulations will provide powerful information that can improve predictions of climate change impacts within and across ecosystems.
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Plant biodiversity is often correlated with ecosystem functioning in terrestrial ecosystems. However, we know little about the relative and combined effects of above- and belowground biodiversity on ...multiple ecosystem functions (for example, ecosystem multifunctionality, EMF) or how climate might mediate those relationships. Here we tease apart the effects of biotic and abiotic factors, both above- and belowground, on EMF on the Tibetan Plateau, China. We found that a suite of biotic and abiotic variables account for up to 86% of the variation in EMF, with the combined effects of above- and belowground biodiversity accounting for 45% of the variation in EMF. Our results have two important implications: first, including belowground biodiversity in models can improve the ability to explain and predict EMF. Second, regional-scale variation in climate, and perhaps climate change, can determine, or at least modify, the effects of biodiversity on EMF in natural ecosystems.
Spatial variation in filters imposed by the abiotic environment causes variation in functional traits within and among plant species. This is abundantly clear for plant species along elevational ...gradients, where parallel abiotic selection pressures give rise to predictable variation in leaf phenotypes among ecosystems. Understanding the factors responsible for such patterns may provide insight into the current and future drivers of biodiversity, local community structure and ecosystem function. In order to explore patterns in trait variation along elevational gradients, we conducted a meta‐analysis of published observational studies that measured three key leaf functional traits that are associated with axes of variation in both resource competition and stress tolerance: leaf mass:area ratio (LMA), leaf nitrogen content per unit mass (Nₘₐₛₛ) and N content per unit area (Nₐᵣₑₐ). To examine whether there may be evidence for a genetic basis underlying the trait variation, we conducted a review of published results from common garden experiments that measured the same leaf traits. Within studies, LMA and Nₐᵣₑₐ tended to decrease with mean annual temperature (MAT) along elevational gradients, while Nₘₐₛₛ did not vary systematically with MAT. Correlations among pairs of traits varied significantly with MAT: LMA was most strongly correlated with Nₘₐₛₛ and Nₐᵣₑₐ at high‐elevation sites with relatively lower MAT. The strengths of the relationships were equal or greater within species relative to the relationships among species, suggesting parallel evolutionary dynamics along elevational gradients among disparate biomes. Evidence from common garden studies further suggests that there is an underlying genetic basis to the functional trait variation that we documented along elevational gradients. Taken together, these results indicate that environmental filtering both selects locally adapted genotypes within plant species and constrains species to elevational ranges based on their ranges of potential leaf trait values. If individual phenotypes are filtered from populations in the same way that species are filtered from regional species pools, changing climate may affect both the species and functional trait composition of plant communities.
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Fifty Years of Mountain Passes Sheldon, Kimberly S.; Huey, Raymond B.; Kaspari, Michael ...
The American naturalist,
05/2018, Volume:
191, Issue:
5
Journal Article
Peer reviewed
In 1967, Dan Janzen published “Why Mountain Passes Are Higher in the Tropics” in The American Naturalist. Janzen’s seminal article has captured the attention of generations of biologists and ...continues to inspire theoretical and empirical work. The underlying assumptions and derived predictions are broadly synthetic and widely applicable. Consequently, Janzen’s “seasonality hypothesis” has proven relevant to physiology, climate change, ecology, and evolution. To celebrate the fiftieth anniversary of this highly influential article, we highlight the past, present, and future of this work and include a unique historical perspective from Janzen himself.
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Macroecology seeks to understand broad-scale patterns in the diversity and abundance of organisms, but macroecologists typically study aboveground macroorganisms. Belowground organisms regulate ...numerous ecosystem functions, yet we lack understanding of what drives their diversity. Here, we examine the controls on belowground diversity along latitudinal and elevational gradients. We performed a global meta-analysis of 325 soil communities across 20 studies conducted along temperature and soil pH gradients. Belowground taxa, whether bacterial or fungal, observed along a given gradient of temperature or soil pH were equally likely to show a linear increase, linear decrease, humped pattern, trough-shaped pattern, or no pattern in diversity along the gradient. Land-use intensity weakly affected the diversity-temperature relationship, but no other factor did so. Our study highlights disparities among diversity patterns of soil microbial communities. Belowground diversity may be controlled by the associated climatic and historical contexts of particular gradients, by factors not typically measured in community-level studies, or by processes operating at scales that do not match the temporal and spatial scales under study. Because these organisms are responsible for a suite of key processes, understanding the drivers of their distribution and diversity is fundamental to understanding the functioning of ecosystems.
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